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NIGERIAN JOURNAL OF ENVIRONMENTAL SCIENCES AND TECHNOLOGY (NIJEST)
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https://www.nijest.com Volume 3 | Number 2 | October 2019
NIJEST / Nig. J. of Env. Sci. & Tech. 3 (2), October 2019
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Prof. Clinton O. Aigbavboa Prof. Toshiroh Ikegami Department of Construction Management and Quantity Department of Urban Studies / School of Policy Studies, Surveying, University of Johannesburg, South Africa Kwansei Gakuin University, Yubinbango Nishinomiya, Japan
Prof. Samuel Laryea Dr. (Ms) Oluropo Ogundipe School of Construction Economics and Management, Nottingham Geospatial Engineering Department, University University of Witwatersrand, Johannesburg, South of Nottingham, UK Africa
Prof. Stephen Ogunlana Dr. Eugene Levin School of the Built Environment, Heriot Watt Geomatics Engineering Department, Michigan University, UK Technological University, Michigan, USA
Prof. A. N. Aniekwu Prof. P. S. Ogedengbe Department of Architecture, University of Benin, Department of Estate Management, University of Benin, Benin City, Nigeria Benin City, Nigeria
Dr. H. A. P. Audu Dr. Patrick Ogbu Department of Civil Engineering, University of Benin, Department of Quantity Surveying, University of Benin, Benin City, Nigeria Benin City, Nigeria
Prof. Tito Aighewi Department of Environmental Management and Toxicology, University of Benin, Benin City, Nigeria
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Nigerian Journal of Environmental of Environmental Sciences and Technology (NIJEST) Journal available online at http://www.nijest.com Vol 3 No. 2 October 2019 ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Contents
Article Page Spatial pattern of Land Surface Temperature over Umuahia North and Bende LGA, Abia State, Nigeria
Uchendu U. I., Kanu C., Kanu K. C. and Mpamah C. I. 210 – 217 Impact of Land Use Types and Soil Depths on the Distribution of Soil Physical and Chemical Properties in Soils of Aboy Gara Watershed, at Gidan District, North Wollo Zone, Ethiopia
Gebeyaw T. Y. 218 – 232 Implementation of Condition Equation Model in Geodetic Observation: A Case Study of Circular Reservoir Structure
Oladosu S. O., Okonofua S. E. and Ehigiator-Irughe R. 233 – 244 Finite Element Application in Reservoir Deformation analysis (Pilot Phase 1)
Ehigiator-Irughe R. 245 – 255 Analysis of Impact of Exposures and Hydrological Modelling of Flood Peak Zones in Adamawa Catchment, Nigeria
Nwilo P. C., Olayinka N. D. and Adzandeh A. E. 256 – 267 The Impacts of Climate Change on Nigerian Ecosystems: A Review
Ikumbur B. and Iornumbe S. 268 – 291 Macroinvertebrates’ Pollution Tolerance Index in Calabar River, Cross River State, Nigeria
Bate G. B. and Sam–Uket N. O. 292 – 297 Solid Waste Management Practice and Challenges in Gashua, Yobe State, Nigeria
Saleh A. and Ahmed A. 298 – 303 Subsurface Structural Mapping over Koton Karifi and Adjoining Areas, Southern Bida Basin, Nigeria, using High-Resolution Aeromagnetic Data
Ikumbur E. B., Ogah V. E. and Akiishi M. 304 – 316 Mapping the Impact of Land Use and Land Cover Change on Urban Land and Vegetation in Osun State, Nigeria
Abiodun O. E. and Akinola D. J. 317 – 330 Studies on the effect of Cold Plastic Deformation and Heat Treatment on the Microstructural Arrangement and Corrosion Behaviour of Mild Steel in Acidic Media
Obayi C. S., Nwobodo J. C., Neife S. I. and Daniel-Mkpume C. C. 331 – 341 Development of Asbestos-free Brake Pads Using Bamboo Leaves
Adekunle N. O., Oladejo K. A., Kuye S. I. and Aikulola A. D. 342 – 351 Strength and Workability Assessment of Concrete Produced by Partial Replacement of Cement with Waste Clay Bricks
Nwankwo E. and John A. T. 352 – 360 Assessment of Hospital Wastes Management Practices in Lagos, Nigeria, using Two Health Care Centres as Case Studies
Alani R., Nwude D. and Adeniyi O. 361 – 369 Application of Remote Sensing, GIS and Hydrogeophysics to Groundwater Exploration in Ogun State: A case study of OGDSparklight Estate
Epuh E. E., Jimoh N. O, Orji M. J. and Daramola O. E. 370 – 385
Article Page Geometric and Dynamic Application of Satellite Geodesy in Environmental Mapping: A Conceptual Review 386 – 397 Hart L., Oba T. and Babalola A. Residents’ Perception of Importance and Satisfaction with Infrastructure in Selected Public Housing Estates in Osun State, Nigeria
Oyedele J. B. and Oyesode M. F. 398 – 409 Engineering Feasibility of Building Blocks Produced from Recycled Rice Husks
Atikpo E., Ukala D. C., Agori J. E., Agbi G. G., Iwemah E. R., Umukoro L. O. and Michael A. 410 – 415
Nigerian Journal of Environmental Sciences and Technology (NIJEST)
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 210 – 217
Spatial pattern of Land Surface Temperature over Umuahia North and Bende LGA, Abia State, Nigeria
Uchendu U. I *, Kanu C., Kanu K. C. and Mpamah C. I. Department of Environmental Management and Toxicology, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria Corresponding Author: *[email protected], [email protected]
https://doi.org/10.36263/nijest.2019.02.0138
ABSTRACT
This study evaluated the Spatial pattern of Land Surface Temperature (LST) over Umuahia North (Urban Area) and Bende LGA (Rural Area), Abia State, Southeast Nigeria. LANDSAT Imagery spanning Row 056 and Path 188, with 30m spatial resolution was captured on the 17th of May, 2018. Temperature and relative humidity were measured using a thermometer and multi-purpose Hydro-20 - 100 % model. Eight measurements were taken for each parameter at an interval of 8 hours at an elevation of 1.5m above the ground. Coordinates and elevation of the points were captured using a Garmin Handheld GPS. Data obtained were imported in compatible formats with ArcGIS 10.5 and the values for the un-sampled locations within the study area was determined through the interpolation of the collected data. A subset covering the study area was extracted for bands 1,2,3,4 and 5. Bands 1, 2 and 3 which are visible bands were used in generating a true colour composite image of the study area; the bands 4 and 5 which are not visible bands were used for the NDVI (Normalized Differential Vegetation Index). Result showed that Bende LGA had a vegetal cover of 45,741.26hectares out of a total of 60,152.76 hectares while Umuahia North had 19,689.09 hectares of vegetal cover out of a total of 24,459.75 hectares. Umuahia North had an average daily temperature of 31.309̊ C while Bende had 27.405̊ C. The average relative humidity in Bende LGA was 82.37% while Umuahia North was 67.274%. In conclusion, the study showed the existence of heat islands in the urban areas in Umuahia North LGA which was characterized by higher temperature but lower relative humidity. The heat island could be attributed to the gradual loss of vegetation cover and the increase in built-up environments in Umuahia North LGA.
Keywords: Land uses, soil depth, soil physical and chemical properties, watershed
1.0. Introduction
Urban population is increasing and the infrastructural development required often leads to higher building density, resulting in a lack of green spaces (Abdollah, 2012). In comparison with rural areas, urban areas are more prone to the risks of lack of green space. One of the effects of urbanization is the urban heat island effect (UHI) (Kleerekoper et al., 2012). Urban heat island is an urban area whose ambient temperature is higher than the surrounding rural areas due to human activities which increasingly use asphalt and modify land surfaces while decreasing the green spaces and evaporation surfaces (Mobaraki et. al., 2012). Surface temperature is important to urban climates because it regulates the air temperature of the lowest layers of the atmosphere mostly affecting city dwellers (Voogt and Oke, 2003). Increased surface temperature from UHI effects impacts on air quality and environmental conditions. Higher temperature increases ozone production at ground level from volatile organic compounds emitted from the combustion of fossil fuels. Ground level ozone and elevated temperatures are hazardous to public health because it can cause respiratory and cardiovascular problems (Quattrochi and Lo, 2003). The elevated temperatures within urban environment also have biological impacts. Warmer temperatures in urban areas result in earlier green-up of flowers and trees in the city, a longer growing
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 210 - 217 season and the attraction of birds to warmer habitats (Albers et al., 2015). Changes in the composition of the urban land structure and transforming the naturally vegetated land into the built-up area have been mainly caused by the formation of the UHIs. Similarly, other anthropocentric factors, such as industrial activities, transportation, emission of CO2, and energy consumption, have affected an increase in the magnitude of UHIs in both day and night (Igun, 2017). In view of the above, earlier studies have identified LST also known as surface urban heat island (SUHI) by assessing measured rural-urban temperature differences (Balogun et al., 2012; Ojeh et al., 2016) in some areas in Nigeria. For instance, Ojeh et al. (2016) investigated urban temperature conditions based on the hourly air temperature difference between City hall (Urban area) and Okoafo (Rural area) in Lagos, Nigeria. The study found that maximum nocturnal LST magnitudes in Lagos can exceed 7°C during the dry season, and during the rainy season, wet soils in the rural environment supersede regional wind speed as the dominant control over LST magnitude. The study of Ojeh et al. (2016) was in agreement with Balogun et al. (2012), which found that nocturnal heat island was more frequent than the day-time heat island over Akure city, Nigeria. More recently, studies have employed remote sensing and GIS techniques to analyze and quantify the effect of Land-use/Land-cover (LULC) change on LST (Ishola. et al., 2016b). In Umuahia and Bende LGA in Abia State of Nigeria, where this study is focused, land use and land cover patterns have undergone a rapid change due to accelerated expansion over the years. Urban growth has increased tremendously and extreme stress to the environment has occurred (Eniolorunda et. al., 2017). This increasing level of migration may be attributed to favorable socio-economic, agricultural, political and physical factors. Furthermore, environmental changes due to urbanization can have significant effects on local climate. One of the most familiar effects of urbanization is the urban heat island, which is the direct representation of environmental degradation. Increase in population and anthropogenic heat might have also contributed to this phenomenon (Babalola and Akinsanola, 2016). Thus, the aim of the study was to evaluate the Spatial pattern of Land Surface Temperature (LST) over Umuahia North (Urban Area) and Bende LGA (Rural Area), Abia State, Southeast Nigeria.
2.0. Materials and Methods 2.1. The Study Area This study was carried out in Umuahia North and Bende local government areas in Abia State, South- East Nigeria. This area is located in the lowland rainforest zone of Nigeria which lies between Latitude 05029′ to 05042′ North and Longitude 07029′ to 07033′ East. The area has an average rainfall of 2,238 mm per year that is distributed over seven months rainy season period (Nzegbule and Ogbonna, 2008). It has bimodal peaks, the first occurring in the month of June or July and the second occurring in the month of September. Its minimum and maximum temperatures are 230C and 320C respectively and a relative humidity of 60-80% (Nzegbule and Ogbonna, 2008). The capital of Abia state is Umuahia which is bounded by Port-Harcourt to its South and Enugu city to its north. Umuahia has a population of 359,230 according to the 2006 Nigerian Population Census.
2.2. Collection of Remotely Sensed Images Remotely sensed satellite images and field observations provided the datasets that were used to achieve the objectives of the study. Remotely sensed data was obtained from a Landsat data spanning Row 056 and Path 188, with 30m spatial resolution captured on the 17th of May, 2018. The data was obtained from the earth explorer website, which provides a range of satellite images with varying spatial resolution for download. Landsat was chosen because of its suitability for land use/land cover studies. Varying landcover types such as built-up areas/settlements, vegetal cover, water bodies, rocky and bare surfaces can be measured from this satellite image.
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2.3. Collection of field Data
Field data collected during the study includes temperature, relative humidity using a thermometer, Multi-purpose Hydro-20 - 100 % model, while location coordinates and elevation were captured using Magnetic Compass and a Garmin handheld GPS. Data were collected at 6 hours interval at an elevation of 1.5m above the ground. Data obtained for each sampled location were analyzed and then imported in compatible formats with ArcGIS 10.5 and allocated to its location using the longitude and latitudinal values obtained with the GPS. The values for the unsampled locations within the study area was determined through the interpolation of the values obtained from each location.
2.4. Processing of the Remotely Sensed Data Visible bands 1,2,3 were extracted from the Landsat imagery and a sub map covering Umuahia North and Bende Local Government Areas was created, which is a representation of the study area. This sub scene was extracted from the original dataset covering Row 056 and Path 188. The submap was created using vector layers covering the extent of the two Local Government Areas of Interest. A true colour composite which displays a combination of visible red, green and blue bands to the corresponding red, green and blue channels on the computer display was created for the study area (Figure 1). This results to an image representing what the eye would see naturally i.e. vegetation as green, water as shades of blue, while bare ground and impervious surfaces are shown as shades of light gray and brown. This was chosen over a false color composite as it suits the purpose of the research. Bands 4 and 5 which are not visible bands were used for the Normalized Differential Vegetation Index (NDVI). The NDVI is a standardized vegetation index which is used to generate images showing relative biomass. The chlorophyll absorption in red band and relatively high reflectance of vegetation in near infrared band were used to calculate NDVI. This was used to determine the vigour of vegetation within the study area. Supervised image classification was carried out on the satellite image and samples such as built up areas, settlements, impervious surfaces and vegetation were identified and captured through pixel training and the maximum likelihood classification algorithm.
Figure 1: True color composite landsat imagery of the study area
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3.0. Results and Discussion 3.1. Temperature Analysis of the data showed higher temperature in Umuahia North LGA an urban area compared with Bende LGA a rural Area (Table 1). Higher values were recorded in the morning and evening in Umuahia North LGA when compared to Bende LGA. The average daily temperature recorded for Umuahia North LGA was 31.309oC while that of Bende LGA was 27.405oC. Variations in temperature observed in the study locations was in line with the study of Roth, (2007) who observed higher temperature in urbanized areas compared with areas that exhibit the rural attributes. This variation in temperature is often due to the difference in vegetal cover, paved surfaces, human population, economic activities, roofing sheets and emission from vehicles and industries. Due to urbanization activities in Umuahia North LGA as compared to Bende LGA, there was higher temperature experienced in the area, this is due to the land use in Umuahia North LGA which is predominantly built-up area and agricultural land.
3.2. Relative Humidity Lower relative humidity was observed in Umuahia North LGA compared with Bende LGA (Table 1). The average relative humidity values recorded for Bende LGA during the period of study was 82.37% while that of Umuahia North LGA was 67.274%. The higher relative humidity observed in Bende LGA can attributed to the lower temperature in the area, more vegetation and evapotranspiration and fewer population and human activities. There is an inverse relationship between relative humidity and temperature (Mallik et al., 2008). Studies in the past have shown that cold air holds more water vapour than warm air, relative humidity falls when the temperature rises. Whenever the relative humidity value of 100% is attained the air becomes saturated.
Table 1: Weather Parameters at the sampled point in the study area
Temperature (oC) Relative Humidity (%) Time Location Average Lowest Highest Average Lowest Highest
Bende Morning 29.444 25.67 36.11 80.8 77.9 84.5
Umuahia North 34.85 32.43 38.27 58.394 46.4 63.45
Bende Evening 25.366 22.56 26.61 83.94 80.3 87.4
Umuahia North 27.768 23.7 29.65 76.154 56.67 83.6
Bende Daily 27.405 22.56 38.27 82.37 77.9 87.4
Umuahia North 31.309 23.7 38.27 67.274 46.4 83.6
Source: Field Survey, 2018.
3.3. Image Classification, Vegetal Cover, NDVI and Heat Island Occurrence The image classification analysis (Figures 2 and 3) showed that Bende has more vegetal cover than Umuahia North LGA. The vegetal cover of Bende LGA was 45,741.255 hectares while Umuahia North had 19,689.087 hectares of vegetal cover. The vegetal cover observed in Bende LGA was healthier than the vegetal cover in Umuahia North LGA. Loss of vegetation in urban areas increases heat storage in the ground and buildings which in turn could lead to higher air and surface temperature compared to the surrounding areas (Oke, 1982).
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Figure 2: Classified landsat imagery of the study area
Figure 3: Distribution of observed parameters by LGA
The findings of this study also showed that there is a reversed relationship between vegetation, NDVI and the existence of heat island (Figures 4 – 6), implying that an increase in vegetation abundance would generally reduce surface temperatures, and thus UHI intensity, this is due to the impact of the different properties of Land use Land cover (LULC) (Voogt and Oke, 2003). While the vegetation areas are directly related to lower surface temperatures, responsible for generating the cooling effect
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 210 - 217 in the urban microclimate, concrete built-up areas add to the existing high temperatures. The built-up areas and road and network have influenced the NDVI of Umuahia North LGA. Previous studies have shown negative correlation between temperature and urban vegetation abundance (Weng et al., 2004; Chen et al., 2006; Mallik et al., 2008; Sundara et al., 2012).
Figure 4: Heat map of the study area by LGA
Figure 5: Landuse map of the study area by LGA
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Figure 6: NDVI map of the study area by LGA
4.0. Conclusion The study showed the existence of SUHI in the urban areas in Umuahia North LGA which was characterized by higher temperature but lower relative humidity compared with the lower temperature and higher relative humidity observed in Bende LGA a rural area. The SUHI could be attributed to the gradual loss of vegetation cover and the increase in the built-up environments in Umuahia North LGA. This study recommends that Landuse planning should be instituted and implemented in Umuahia and its environs. This is to ensure that rural landuse is sustainable. This effort should involve the Abia State Ministry of Environment, Urban Development Board and relevant bodies of the Local Government Areas. Urbanisation is a process that cannot be halted hence, urban managers and planners should embark on re-designing cities in such a way that a lot of parks, gardens, orchards, and open spaces will be accommodated into the city physical plans. These provisions will allow for the free flow and passage of air as well as provision of shades that will contribute to city cooling.
References Abdollah, M. (2012). Strategies for Mitigating Urban Heat Island Effects in Cities: Case of Shiraz City Center. Eastern Mediterranean University Gazimağusa, North Cyprus. Albers, R. A, Bosch, W, Rovers, V. (2015). Overview of challenges and achievements in the climate adaptation of cities and in the Climate Proof Cities program. Building and Environment, 83, 1–10. doi:10.1016/j.buildenv.2014.09.006 Babalola OS, Akinsanola AA. (2016). Change detection in land surface temperature and land use land cover over Lagos Metropolis, Nigeria. J. Remote Sens. GIS. 5, 2. Balogun, I.A., Balogun, A.A., Adeyewa, Z.D., (2012). Observed urban heat island characteristics in Akure, Nigeria. African J. Environ. Sci. Technol. 6 (1), 1–8. Chen, X.L., Zhao, H.M., Li, P.X., & Yin, Z.Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133-146.
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Eniolorunda NB, Mashi SA, Nsofor GN. (2017). Toward achieving a sustainable management: characterization of land use/land cover in Sokoto Rima floodplain, Nigeria. Environ. Dev. Sustain. 19, 1855–1878. (doi:10.1007/s10668-016-9831-6) EPA. 2009. Reducing Urban Heat Islands: Compendium of Strategies: Heat Island Effect US EPA. http://www.epa.gov/heatisland/resources/compendium.htm Igun, E. (2017) Analysis and sustainable management of urban growth’s impact on land surface temperature in Lagos, Nigeria. J. Remote Sens. GIS 2017, 6. Ishola, K.A., Okogbue, E.C., Adeyeri, O.E., (2016b). Dynamics of surface urban biophysicalcompositions and its impact on land surface thermal field. Model. Earth Syst. Environ. 2, 208. http://dx.doi.org/10.1007/s40808-016-0265-9. Kleerekoper, L., van Esch, M., & Salcedo, T. B. (2012). How to make a city climate-proof, addressing the urban heat island effect. Resources, Conservation and Recycling, 64, 30–38. Mallik, J., Yogesh Kant, & Bharath, B.D. (2008). Estimation of land surface temperature over Delhi using landsat-7 ETM+. J. Ind. Geophysics Union, 12(3), 131-140. Mobaraki Omid, Jamal Mohammadi & Asghar Zarabi. (2012). Urban Form and Sustainable Development: The Case of Urmia City. Journal of Geography and Geology; Vol. 4, No. 2; 2012 Nzegbule, E., & Ogbonna, P. (2008). Quantity and Quality of Litterfall In Pure Pine and Pine/Gmelina Mixed Plantations in Umuahia, Abia State. Global Journal of Agricultural Sciences Vol. 7 No. 1 2008: 93 – 96 Ojeh, V.N., Balogun, A.A., Okhimamhe, A.A., (2016). Urban-rural temperature differences in lagos. Climate 4, 29. http://dx.doi.org/10.3390/cli4020029. Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of Royal Meteorology Society, 108, 1 – 24. Quattrochi D. and Lo C. (2003). “Land-Use and Land-Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach”. Photogrammetric Engineering & Remote Sensing 69.9: 1053-1063. Roth, M. (2007). Review of urban climate research in (sub)tropical regions. International Journal of Climatology, 27(14), 1859–1873.doi:10.1002/joc.1591 Sundara Kumar, K., Udaya Bhaskar, P., & Padmakumari, K. (2012). Estimation of Land Surface Temperature to study Urban Heat Island effect using Landsat ETM+ Image. International Journal of Engineering Science and Technology, 4(2), 771-778. Voogt, J., & Oke, T. (2003). Thermal remote sensing of urban climates. Remote Sensing of Environment, 86(3), 370–384. doi:10.1016/s0034-4257(03)00079-8 Weng, Q., Lu, D., & Schubring, J. (2004). Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89, 467-483.
Cite this article as:
Uchendu U. I., Kanu C., Kanu K. C. and Mpamah C. I. 2019. Spatial pattern of Land Surface Temperature over Umuahia North and Bende LGA, Abia State, Nigeria. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 210-217. https://doi.org/10.36263/nijest.2019.02.0138
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Nigerian Journal of Environmental Sciences and Technology (NIJEST)
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 218 - 232
Impact of Land Use Types and Soil Depths on the Distribution of Soil Physical and Chemical Properties in Soils of Aboy Gara Watershed, at Gidan District, North Wollo Zone, Ethiopia
Gebeyaw T. Y.* Department of Soil and Water Resources Management, Faculty of Agriculture, Woldia University, Woldia, Ethiopia Corresponding Author: *[email protected]
https://doi.org/10.36263/nijest.2019.02.0102
ABSTRACT
The study was conducted at the degraded land soils of the Abuhoy Gara Catchment, which is located in the Gidan District of North Wello Zone, Ethiopia to determine the impact of land use type and soil depth on the distribution of soil physical and chemical properties. Soil samples were collected from representative locations with four replications at two depths, surface (0-15 cm) and subsurface (15-30 cm) of cultivated, grazing and bush land use types. One hundred eighty soil samples were collected from the depths of 0-15 and 15-30 cm each in a radial sampling scheme using an auger. Totally, twelve composite soil samples were collected using flexible grid survey method of 1:30,000 scales. The collected samples were air-dried, homogenized and sieved to pass a 2 mm mesh sieve for the standard physical and chemical analyses. Results showed that the soil physical and chemical properties were significantly affected by the interaction of land uses and soil depths. Silt content decreases while clay content increases across depth from surface to subsurface soils. The lowest pH-H2O was registered at the subsurface soils of the grazing lands, while the highest was recorded at the surface soils of the bush land. The interaction effect of land use by soil depth on the variability of soil organic matter was significantly higher at surface layer of the grazing land and lower at surface layer of cultivated land. Similarly, soil total nitrogen was highest in surface layer of the grazing land, while it was lowest in subsurface layer of the bush land. Exchangeable bases were highest in surface soils of the bush land and lowest in the surface soils of cultivated land. The contents of both exchangeable bases were decreasing with soil depth in all land uses except the bush land. Significant difference in cation exchange capacity contents was observed as highest in surface soil layer of the bush land and lowest in surface soil layer of the cultivated land. From the results of the study, it can be concluded that the interaction of land use with soil depth showed negative effects especially disturbance of soil nutrient status on cultivated land in surface soils. In general, the spatial variability of soil properties indicates the soil conditions were strongly affected by inappropriate land use and soil management practices including soil depth. Therefore, reducing intensity of cultivation, adopting integrated soil fertility management and application of organic fertilizers could maintain the existing soil condition and replenish degraded soil properties.
Keywords: Land uses, soil depth, soil physical and chemical properties, watershed
1.0. Introduction
Securing food and a livelihood is inextricably linked to the exploitation of the natural resource base (land, water and forest) in Ethiopia, where over 85 percent of the population lives in rural areas and contribute significantly to the total export value (Alemneh, 2003). Land degradation, mainly due to soil erosion and nutrient depletion, has become one of the most important environmental and economic problems in the highlands of Ethiopia (World Bank, 2008). And it was estimated that half of the Ethiopian highlands’ arable lands are moderately to severely degraded and nutritionally depleted due to pressure of intense human activity and improper farming and management practices
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 such as over cultivation, over grazing, primitive production techniques, and over dependent on rainfall (Hugo et al., 2002). As the interaction between natural and anthropogenic management system persists (Assefa and van Keulen, 2009), soil undergoes vertical exchange of materials which in turn resulted in physical and chemical changes from surface soil to sub-soils (Brady and Weil, 1999). Human management system such as frequent plowing and tillage for the purpose of cultivation, grazing or similar uses changes the proportions of many soil properties with changing depths (Ali et al., 1997; MacCarthy et al., 2013). According to the report by Islam and Weil (2000), tillage mechanically disintegrates soil particles and modifies soil conditions for plant growth and intensive leaching, and hastens organic matter decomposition. Sheet erosion and intensive leaching process leads to higher concentration of clay content and lesser concentration of calcium, magnesium, potassium and sodium in the subsoil than the topsoil (Adeboye et al., 2011). Although, as soil quality has emerged as a leading concept in natural resource conservation and protection, the agricultural land area expansion with uncontrolled farming pose serious threats to the sustainability and the suitability of soil for crop production which is based on the quality of the soil’s physical, chemical and biological properties. On the other hand, there is no available study that examines dynamics of soil properties under different land covers to establishing appropriate management options and to restoring degraded soils in the highlands. So, stronger emphasis is now being placed on appropriate fertility management technologies to enhance these dynamic soil properties by understanding soil performances. Research investigation in relation to soil fertility status in line with land use and soil depth can provide information on soil suitability for crop production, diagnosing soil constraints for agriculture and improved technique for future rehabilitation program which can serve as a basis for fertilizer recommendations. The outcome of the investigation can provide suitable guidelines for future research on the development of promising conservation technologies and implementation approaches. The objective of the study was to determine the impact of land use types and soil depths on the distribution of soil physical and chemical properties in eroded soils of Aboy Gara watershed.
2.0. Methodology 2.1. Description of the study area The study was conducted at Abuhoy Gara catchement in Gidan district (Figure 1) which is found in North Wollo Zone of Amhara National Regional State, Ethiopia. Gidan is bordered by Tigray Region in the North; Gubalafto district in the North east; Meket district in the south east and Lasta district in the south and south west. Astronomically, it is located between 11053’-12016’ North and 39010’_39035’ east39010’_39035’ East. Muja is the administrative town of the district and is situated at about 595km from the capital city, Addis Ababa. According to the district agricultural office report, the population of the study catchment is 580 people of whom 420 are male and 160 are female. The total area of Abuhoy Gara catchment is about 615 hectares (250 hectares cultivated and 365 hectares none cultivated lands). According to North-East Amhara meteorological data service, the mean annual rainfall is 1100 mm with mean annual maximum and minimum temperature of 21.23°C and 9.57°C, respectively. The topography and land form of the area is dominated by rolling hills dissected streams and valleys. The altitude ranges from 3,089 to 3,559 m.a.s.l (having an average altitude of 3,324 m.a.s.l). The topography of the watershed (i.e., at total of 1819 ha) is characterized as 15% gentle slopes, 53.6% steep slope, 31.4% very steep. The dominant form of agriculture is subsistence farming and livestock keeping. The dominant crops include; wheat, barley and faba bean have been cultivated during the main rainy season. Livestock production is an essential part of the farming system. Most farm households keep cattle dominated by oxen and small stock including sheep, poultry, and equines.
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Figure 1: Location Map of the Study Area
2.2. Methods of data collection 2.2.1. Sampling field observation At the beginning, a general visual field survey of the area was carried out to have a general view of the variations in the study area. Global Positioning System (GPS) readings were used to identify the geographical locations and the coordinate system where samples were taken, and clinometers were used to identify slopes of the sampling sites. Representative soil sampling fields were then selected based on vegetation and cultivation history and they are categorized bush, grazing and cultivated lands.
2.2.2. Soil sampling Soil samples were collected from representative sampling sites with four replications (higher slope, middle slope, intermediate slope and lower slope positions) from two soil depths of the bush, grazing and cultivated lands representative fields using an auger (Ryan et al., 2001). Totally, twelve composite soil samples from surface (0-15 cm) and subsurface (15-30 cm) soil layers were collected using flexible grid survey method of 1:30,000 scales. Each composite sample was made from a pool of fifteen point samples and from the twelve composite soil samples major soil fertility parameters were analyzed. The samples were placed in a numbered calico bag with tightly fitting lid and labeled carefully with the location, representative field and depth of soil. The soil samples collected from representative fields’ were then air-dried, mixed well and passed through a 2 mm sieve for the analysis of selected soil physical and chemical properties. Before sampling, forest litter, grass, dead plants and any other materials on the soil surface were removed and during collection of samples, field/terrace edges, furrow, old manures, wet spots, areas near trees, compost pits, fields used as kitchen gardens and fertilizer bands were excluded.
2.3. Method of data analyses 2.3.1. Soil laboratory analysis The collected samples were air-dried, homogenized and sieved to pass a 2 mm mesh sieve for soil physical and chemical analyses. Particle-size distribution (sand, silt and clay) was determined using bouyoucos hydrometer method procedures (Black et al., 1965). Soil pH was determined using the method reported in McLean, (1982) as follows; 1g of soil was dissolved in 2.5ml of IM solution of potassium chloride. The mixture was stirred intermittently for 1 hour and the resultant pH was measured using a pH meter fitted with a glass electrode. The exchangeable acidity present in the soil
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 was determined by titration method using 0.01M sodium hydroxide (NaOH) after extraction with 1M potassium chloride (KCl) (Sumner and Stewart, 1992). Organic carbon was analyzed by Walkley - Black wet digestion method (Bremner and Mulvaney, 1982; Nelson and Sommers, 1982). Soil organic matter was computed by multiplying soil organic carbon by a factor of 1.724 (Baruah and Barthakur, 1997). Total nitrogen was determined using Kjeldahl method (Okalebo et al., 1993). Available phosphorous was analyzed using the Olsen sodium bicarbonate extraction solution (pH 8.5) method (Olsen et al., 1954) and the amount of available phosphorous was measured by spectrophotometer. The concentration of exchangeable cations (calcium, magnesium, potassium, and sodium) present in the soil was determined with the aid of AAS (atomic absorption spectrophotometer; Shimadzu AA-6800) after extraction with 1M Ammonium acetate (NH4OAc) buffered at pH 7. The cation exchange capacity of the soil was determined by 0.05M potassium sulphate (K2SO4) using the soil used for the basic exchangeable cation determination or by the neutral ammonium acetate (CH3COONH4) saturation method (Ryan et al., 2001). The exchangeable bases in the ammonium acetate filtrates collected above were measured by atomic absorption spectrophotometer (Ryan et al., 2001).
2.3.2. Data analysis Soil parameter readings were subjected to statistical analysis using; univariate statistics (plot design), interaction plot to view land-use and soil depth effect. On the statistical significance of land-use and soil depth on the soil physical and chemical properties, one way analysis of variance was done. The statistical analysis was implemented using R-studio. When there was statistically significant difference (alpha = 0.05 level) on single or interaction effect, mean separation was done using lm and cld functions with Tukey’s test.
3.0. Results and Discussion 3.1. Soil texture Results of the statistical analysis reveal that both silt and clay contents were significantly affected by the interaction of land uses and soil depths (P ≤ 0.05). Likewise, the sand fraction was varied significantly at (P ≤ 0.05) as a result of the interaction of land use and soil depth (Table 1and Figure 1). Considering the interaction effects of land use by soil depth on soil particle fraction distribution, the highest interaction mean of sand (67.25%), and silt (26.50%) fractions were observed in both surface (0-15cm) and subsurface (15-30cm) soils of the grazing land compared to cultivated and bush lands. On the other hand, the highest clay content (25.50%) was recorded at the subsurface layer of the cultivated land, whereas the lowest (56.00%) sand and (6.25%) clay contents were observed at the surface layer of cultivated and grazing lands, respectively. Silt content decreases while clay content increases across depth from surface to subsurface soils. The increase in clay contents with depth under all land use types may be due to translocation of clay from surface to subsurface layers, which ultimately increase the proportion of silt content in the surface soil layers (26.5% in surface layer of grazing land). The result is in agreement with the findings of Boke (2004) who reported high sand content in grass land soils in Southern Ethiopia. From the results, it was observed that; there were high differences in particle size distribution in the interaction of land use types with soil depth since these watersheds are highly affected by changes in land management. The result was in agreement with the results reported in Agoume and Birang (2009), who found that land-use systems and soil depths significantly affected the sand, the clay and the silt fractions of the soils size distributions in Cameroon. The clay content of the cultivated land increased with soil depth. This may be due to the intensive and continuous cultivation which might cause the surface that increases translocation of clay particles. This finding is similar that reported in Shiferaw (2004) who reported an increase in clay content with depth under cultivated lands due to long period of cultivation. The highest clay content observed in soils of the cultivated land could be
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 attributed to the mixing of soil during tillage activities as was also reported in Heluf and Wakene (2006), Tematio et al. (2011), Aminu et al. (2013) and Aung et al. (2013).This result contradicts with the result reported in Jaiyeoba (2001) were it was observed that the clay content of cultivated land reduces with depth due to the intensive and continuous cultivation which might cause compaction of the surface that reduces translocation of clay particles within the different layers coupled with profile mixing by tillage activities. The highest clay content in the bush land might be due to the effect of soil forming process which can be similar to the report by Buol (1997), that the accumulation of clay in the subsurface horizon could also be contributed by the in situ synthesis of secondary clays or the residual concentration of clays from the selective dissolution of more soluble minerals of coarser grain size in the B horizon.
Table 1: Interaction effect of land use and soil depth on particle size ((sand, silt and clay) distribution of the soils in Abuhoy Gara watershed
Soil depth Soil textural fraction (%) Soil textural class Land use types (cm) Sand Silt Clay (USDA) 0-15 56.0a 21.0b 23.0cd Sandy clay loam Cultivated 15-30 59.5ab 15.3a 25.5d Sandy clay loam 0-15 67.3c 26.5c 6.3a Sandy loam Grazing 15-30 65.3c 24.5c 10.3b Sandy loam Bush land (shrub & some 0-15 60.0ab 17.0a 23.0c Sandy clay loam trees) 15-30 60.0b 16.0a 24.0cd Sandy clay loam Land (F value) 50.16 119.8 913.3 Land -Pr(>F) 4.4e-08 *** 4.0e-11 *** < 2.2e-16 *** Soil depth (F value) 0.5 34.5 41.0 Soil depth -Pr(>F) 0.48ns 1.5e-05 *** 5.0e-06 *** Land use x Soil depth (F 4.58 8.124 7.37 value) Land use x Soil depth-Pr 0.02 * 0.00306 ** 0.005 ** (>F) SEM (+) 0.88 0.62 0.42 *Interaction means within a specific soil parameter followed by the same letter(s) are not significantly different from each other at P ≤ 0.05; ‘***’ 0.001; ‘**’ 0.01; ‘*’ 0.05; SEM = Standard Error of Mean
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 1: The effect of land uses and soil depths on particle size distribution
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3.2. Soil Chemical properties 3.2.1 Soil Reaction (pH)
The soils pH-H2O value was significantly affected by the interaction of land uses and soil depths (P ≤ 0.01). The lowest (5.69) pH-H2O was registered at the subsurface layer of the grazing land soils, while the highest (6.71) was recorded at the surface layer of the bush land soils (Table2 and Figure 2). The lowest pH at the subsurface layer of the grazing land could be the result of high organic matter content, while the highest pH in the surface layer of the bush land could be the result of accumulation of basic cations. The lowest value of pH under the surface layer of the cultivated land may be due to two major reasons. The first is the depletion of basic cations in crop harvest and drainage to streams in runoff generated from accelerated erosions. Secondly, it may be due to its highest microbial oxidation that produces organic acids, which provide H ions to the soil solution and thereby lowers the soil pH. In general, according to study report by Fu, (2000) and ZhaoQ (2008), continuous cultivation practices, excessive precipitation, and application of inorganic fertilizers could be some of the factors which are responsible for the variation in pH in the soil profiles. The highest pH observed at the subsurface layer of the cultivated land could be attributed to the leaching of basic cations and soil erosion through tillage as was also reported in Fungo et al. (2011) and Kumar et al. (2012). Table 2: Land use and soil depth effect on chemical properties of the soils in Abuhoy Gara watershed
Land use types Soil Selected soil chemical properties depth pH Total Organic matter Available Phosphorus (cm) (1:2.5 H2O) Nitrogen % % (PPM) Cultivated 0-15 5.93ab 0.121ab 0.920a 7.12c 15-30 6.03ab 0.104ab 1.110ab 7.31c Grazing 0-15 6.28bc 0.240c 2.343d 3.50ab 15-30 5.69a 0.103ab 1.475c 4.25b Bush land (shrub & some trees) 0-15 6.71c 0.132b 1.583c 3.84ab 15-30 5.93ab 0.045a 1.260b 2.46a Land (F value) 6.397 10.9888 175.133 75.8060 Land -Pr(>F) 0.0079662** 0.0007605*** 1.592e-12*** 1.707e-09*** Soil depth (F value) 22.661 29.5405 72.882 0.5393 Soil depth -Pr(>F) 0.0001564*** 3.656e-05*** 9.597e-08*** 0.47217 Land use x Soil depth (F value) 8.841 5.4932 61.147 4.3598 Land use x Soil depth Pr(>F) 0.0021155** 0.0137311* 9.421e-09*** 0.02857* SEM (+) 0.1095588 0.0182 0.04782056 0.3488249 *Interaction means within a specific soil parameter followed by the same letter(s) are not significantly different from each other at P ≤ 0.05; ‘***’ 0.001; ‘**’ 0.01; ‘*’ 0.05; SEM = Standard Error of Mean Generally, the pH values observed in the study area are within the ranges of moderately acidic to neutral soil reactions as indicated by Foth and Ellis (1997). In general, except at cultivated land, pH values decreased with increasing soil depth (Table 2). The reason can be attributed to the reduction of basic caions along soil depth which lowers soil pH from top to down the soil layers.
**LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 2: The effect of land uses and soil depths on soil pH
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3.2.2 Soil Organic Matter (OM): Soil organic matter content was significantly affected by the interaction of land uses with soil depth (P ≤ 0.01) (Table 2 and Figure 3). The interaction effect of land use by soil depth, on the variability of soil organic matter was significantly higher (2.343%) at surface layer of the grazing land and lower (0.920%) at surface layer of cultivated land (Table 2). Following this, the percentage changes in organic matter content of subsurface soil from surface soil were decreasing in grazing and bush lands uses unlike cultivated land use. This implies that the litter on the soil surface beneath different canopy layers and high biomass production caused high biological activity in the topsoil layers of grazing and bush lands, whereas the depletion organic matter due to intensive cultivation of the land which results the total removal of crop residues for animal feed and source of energy intensifies oxidation of organic matter at cultivated land. The low organic matter content in the study area might have resulted in insufficient inputs of organic substrate from the farming system due to deforestation, open grazing, residue removal and zero crop rotation as was also reported by Nega and Heluf (2009). The highest change of organic matter with depth under grazing land might be attributed to continuous accumulation of un-decayed and partially decomposed plant and animal residues mainly in the surface soils of forestland, in addition to high rate of interception and infiltration coupled with absence of erosion as reported in Morgan (2005). A similar finding reported in (Urioste et al. (2006) revealed that roots of the grass and fungal hyphae are probably responsible for the high amount of total organic matter in grass land. On the distribution of soil organic matter, Berhanu (1980), reported that the soils in the study area ranges from very low (0.92% in surface soil) in cultivated land to medium (2.343% surface soil) in grazing land.
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 3: The effect of land uses and soil depths on organic matter content
3.2.3. Soil Total Nitrogen Similar to organic matter content, the mean total nitrogen content of the soils was also affected by the interaction of land use and soil depth significantly (P ≤ 0.05) (Table 2 and Figure 4). Soil total nitrogen was the highest (0.240%) in surface layer of the grazing land, while it was lowest (0.045%) in subsurface layer of the bush land (Table 2). The percentage changes in total nitrogen content of subsurface soil from surface soil were decreasing in all land uses. This implies that the surface soil layer is the most biologically active of the soil profile. The highest change of organic matter with depth under bush land might be attributed to continuous accumulation of un-decayed and partially decomposed plant and animal residues mainly in the surface soils of bush land as reported in (Morgan, 2005). Similar to organic matter, the percentage changes in total nitrogen content of subsoil from topsoil were decreasing in all land uses. Thus, total nitrogen is higher in topsoil than in the subsoil probably due to losses in organic matter by mineralization in the subsoil. This is expected because organic matter is the major source of soil organic matter and total nitrogen contents. Results indicate that conversion of the grazing land into cultivated land has resulted in loss of 49.6% of total nitrogen from the soils. The considerable loss of total nitrogen from soils following conversion of
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 land from forest to cultivated land is reported in (Mulugeta et al., 2005; Eyayu et al., 2009; Mojiri et al., 2012). Moreover, as reported by Bahrami et al., (2010); Heshmati et al., (2011); Taye, (2011), lower total nitrogen content was observed in soils of cultivated lands as compared to soils of natural forest lands. According to the classification of soil total nitrogen as per the ranges suggested by Landon (1991) and Tekalign (1991), the soils of the study area are very low to low (0.103-0.240%) in total nitrogen content. All of the studied soils were less than 0.5% of total nitrogen which might be due to high rates of microbial decomposition and nitrogen transformation took place at the cultivated lands. The change in total nitrogen was highest under grazing this may be due to abundance of legume plants and Azotobacter algae (able to fix atmospheric nitrogen), decaying plant and animal matter, and nitrogen compounds produced by thunderstorms (Hall, 2008). The lowest change of total nitrogen under cultivated land compared to grazing land implies that fertilizer applications may not have replaced the total nitrogen lost due to harvest removal, leaching, and humus losses associated with cultivation (Eyayu et al., 2009).
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 4: The effect of land uses and soil depths on total nitrogen
3.2.4. Soil Available Phosphorus The available phosphorus was significantly (P ≤ 0.05) affected by the interaction of the two factors (Table 2 and Figure 5). The content of available phosphorus in the cultivated land appeared to be significantly higher than the other two land use types. Available phosphorus was highest (7.31ppm) in subsurface soil and (7.12 ppm) in surface soil of cultivated land, while it was the lowest (2.46 ppm) subsurface soil under bush land (Table 2). The higher in available phosphorus contents in soils of cultivated land were due to continuous application of mineral phosphorus fertilizer for few years as indicated by different farmers in the area. This was assured by Vander Eijk et al. (2006) that the high content of phosphorus under maize farms than of grass land soils could be due to the continuous application of phosphorus fertilizer applications. Similarly, Boke (2004) also found that high availability of phosphorus under enset farms which is due to rapid mineralization and additions of manure and crop residue. According to Landon (1991) available soil phosphorus level of < 5 mg/kg is rated as low, 5-15 mg/kg as medium and > 15 mg/kg is rated as high. Thus, the mean available phosphorus content of the soils of the study area, with the exception of both layers of the cultivated land, were less than 5 mg/kg qualifying for the low range. The soil of the study area are in agreement with the results reported by many authors Murphy (1968), Tekalign et al. (2002) and Abebe and Endalkachew (2012) that the availability of phosphorus under most soils of Ethiopia decline by the impacts of fixation, abundant crop harvest and erosion.
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.
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 5: The effect of land uses and soil depths on available phosphorus
3.2.5. Exchangeable Bases, Cation Exchange Capacity and Exchangeable Acidity The content of exchangeable calcium (Ca2+) was significantly (P ≤ 0.01) affected by the interaction of land uses by soil depths. Similarly, the content of exchangeable magnesium (Mg2) was significantly (P ≤ 0.001) affected by the interaction of land uses by soil depth (Table 3 and Figure 6).
Table 3. Land use and soil depth effect on chemical properties of the soils in Abuhoy Gara watershed
Land use types Depth Exchangeable bases, cation exchange capacity and exchangeable acidity (cmol(+)/kg) (cm) Ca+ Mg+ K+ Na+ CEC Ex. acidity Cultivated 0-15 4.73a 1.83a 0.47a 0.25a 13.94a 0.263c 15-30 5.40a 2.09ab 0.84b 0.30abc 15.15ab 0.200b Grazing 0-15 5.97a 2.90c 1.15c 0.32abc 15.81ab 0.043a 15-30 4.53a 2.47abc 0.85b 0.38c 17.19b 0.045a Bush land (shrub 0-15 11.43b 5.13d 2.08e 0.34bc 28.13d 0.042a & some trees) 15-30 7.20a 2.84bc 1.73d 0.26ab 25.20c 0.025a Land (F value) 29.2826 73.462 232.143 8.0728 381.8734 171.1957 Land -Pr(>F) 2.194e-06 *** 2.197e-09 *** 1.405e-13*** 0.003144** 1.819e-15*** 1.934e-12*** Soil depth (F 10.5346 51.764 3.375 2.5520 0.0818 6.8640 value) Soil depth - 0.004488 ** 1.073e-06 *** 0.08276 0.127562 0.7780748 0.01736 * Pr(>F) Land use x Soil 7.6235 22.279 22.378 7.1200 13.4140 3.8318 depth (F value) Land use x Soil 0.003997 ** 1.352e-05 *** 1.314e-05*** 0.005271** 0.0002713*** 0.04108 * depth Pr(>F) SEM (+) 0.6289 0.1692 0.06 0.0192 0.4709 0.0120 *Interaction means within a specific soil parameter followed by the same letter(s) are not significantly different from each other at P ≤ 0.05; ‘***’ 0.001; ‘**’ 0.01; ‘*’ 0.05; SEM = Standard Error of Mean; CEC = Cation Exchange Capacity; Ex.Acidity =Exchangeable Acidity
Exchangeable calcium (Ca2+) was the highest (11.43cmol(+)/kg in surface soil and 7.20cmol(+)/kg) in subsurface soil under bush land and the lowest (4.53cmol(+)/kg in subsurface soil and 4.73cmol(+)/kgin surface soil) under grazing and cultivated lands, respectively. Likewise, exchangeable magnesium (Mg2+) was highest (5.13cmol(+)/kg in surface soil) under bush land and lowest (1.83cmol(+)/kg in surface soil) under cultivated land (Table 3). The contents of both exchangeable Ca2+ and Mg2+were decreasing with soil depth in all land uses except bush land (Table 3). These indicate that there was higher down ward leaching of basic cations in the crop field than in the other land use practices. But in the subsurface soil, their values were declined probably due to leaching, decomposition, plant root uptake, runoff and erosion. The highest contents of Ca2+and Mg2+in bush land was may be attributed to leaves from plant falls, animal manures, macrofauna and soil microform and microbial activities common in this land use (Korkanc et al., 2008). The lowest
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 value obtained on the cultivated land could be also be related to influence of intensity of cultivation and abundant crop harvest with little or no use of input as reported by Singh et al. (1995) and He et al. (1999). According to the rating set by Landon (1991), the calcium and magnesium contents of soils in the study area ranged from high in surface cultivated land to very high in surface bush land (Table 3).
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 6: The effect of land uses and soil depths on exchangeable Ca2+ and Mg2+
Exchangeable potassium (K+) content was significantly (P ≤ 0.001) affected by the interaction of land uses by soil depths (Table 3). On the other hand, the content of exchangeable sodium (Na+) was significantly affected by interaction of land uses by soil depths (P ≤ 0.01).Exchangeable potassium + (K ) was highest (2.08 cmol(+)/kg in surface soil) under bush land and lowest (0.47cmol(+)/kg in surface soil under cultivated land (Table 3 and Figure 7). Similarly, the highest (0.38 cmol(+)/kg in + surface soil) and the lowest (0.25 cmol(+)/kg in surface soil) exchangeable Na contents were recorded at the bush and the cultivated lands, respectively. The percentage changes in K+ and Na+ contents of subsurface soil from surface soil were decreasing in all land uses. The highest content in the bush land was related with its high pH value and was in agreement with study results reported by Mesfin (1996) that high K+ was recorded under the high pH tropical soils. In addition, the highest variability of K+ with depth under grazing land may be attributed to cattle manure supplied to the surface soil. The low exchangeable K+ contents observed under cultivated land could probably due to continuous cultivations and inorganic farming practices in the study area which is supported by previous findings that indicate intensity of weathering, cultivation and use of acid forming inorganic fertilizers affect the distribution of K+ in the soil system and enhance its depletion Malo (2005) and(Baker et al., 1997). The ranges of mean exchangeable K+ values observed in this study show that K+ was above the critical levels (0.38 cmol(+)/kg) for the production of most crop plants as indicated by Barber (1984). According to the rating set by Landon (1991), the Na+ contents of soils in the study area is low.
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 7: The effect of land uses and soil depths on exchangeable K+ and Na+
The cation exchange capacity values of the soils in the study area were significantly (P ≤ 0.001) affected by land use and the interaction of land usewith soil depth (Table 3 and Figure 8). Significant difference in cation exchange capacity contents due to the interaction of land use and soil depth was observed in the study area as highest (28.13 cmol(+)/kg) in surface soils of the bush land and lowest (13.93cmol(+)/kg) in surface soils of the cultivated land. The cation exchange capacity values
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 increased from the surface to the subsurface layer under different land use types except the bush land (Table 3).The highest cation exchange capacity in the surface layers of bush land use could be the result of the high organic matter accumulation, whilst the lowest cation exchange capacity at the surface layer of cultivated land use could be the result of leaching and down ward movement of organic matter and clay particles as was also reported by Fassil and Yamoah (2009). According to Landon (1991), the top soils having cation exchange capacity of > 25, 15-25 cmol(+)/kg, 5-15 cmol(+)/kg and < 5 cmol(+)/kg are classified as high, medium, low and very low, respectively. Based on the above ratings, the surface soils of the bush, the grazing and the cultivated lands qualify for high, medium and low status of cation exchange capacity, respectively (Table 3).
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 8: The effect of land uses and soil depths on cation exchange capacity (CEC)
The exchangeable acidity was significantly the interaction of land uses by soil depths (Table 3 and Figure 9). The highest (0.263cmol(+)/kg surface) in the cultivated land and the lowest (0.025 cmol(+)/kg subsurface, 0.042 cmol(+)/kg in surface, 0.045 cmol(+)/kg in subsurface, 0.043 cmol(+)/kg in surface) exchangeable acidity were recorded under the cultivated, bush and the grazing lands, respectively (Table 3). These results show that deforestation, intensive cultivation and application of inorganic fertilizers leads to the higher exchangeable acidity content under the crop field than others land uses. The results of this study were in agreement with those reported by different researchers (Baligar et al., 1997; Wakene, 2001), who reported that inorganic fertilizer application is the root cause of soil acidity.
*LW= Subsurface layer; UP = Surface layer, CL = Cultivated land, FL = Bush land, GL = Grazing Land Figure 9: The effect of land uses and soil depths on exchangeable acidity
4.0. Conclusions The soil organic matter and total nitrogen contents of soils in the study area ranged from very low to low/medium. In other words, results of the study indicate that the soil conditions in the cultivated land
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 218 - 232 is getting below the condition of soils under bush and grazing lands. The interaction of land use with soil depth showed negative effects especially disturbance of soil nutrient status on cultivated land soils in surface soils. In general, the spatial variability of soil properties indicates the soil conditions were strongly affected by inappropriate land use, soil management practices and soil depth. Therefore, this study reinforces the sustainable land use by reducing intensity of cultivation, adopting integrated soil fertility management and application of organic fertilizers thereby maintaining the existing soil condition and replenish degraded soil properties.
Acknowledgement The author would like to express his sincere thanks to Woldia University for their financial and logistics support. The staffs of Amhara National Regional State Sirinka Agriculture Center Laboratory are greatly acknowledged for their cooperation during soil analysis. Apart from that, he wants to express his appreciation to the Gidan District Agriculture office staff members for their unlimited contribution from site selection all the way up to sample collection.
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Cite this article as:
Gebeyaw, T. Y., 2019. Impact of Land Use Types and Soil Depths on the Distribution of Soil Physical and Chemical Properties in Soils of Aboy Gara Watershed, at Gidan District, North Wollo Zone, Ethiopia. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 218-232. https://doi.org/10.36263/nijest.2019.02.0102
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501 Vol 3, No. 2 October 2019, pp 233 - 244
Implementation of Condition Equation Model in Geodetic Observation: A Case Study of Circular Reservoir Structure Oladosu S. O.1,*, Okonofua S. E.2 and Ehigiator-Irughe R.3 1,2,3Department of Geomatics, Faculty of Environmental Sciences, University of Benin, Nigeria Corresponding Author: *[email protected]
https://doi.org/10.36263/nijest.2019.02.0120 ABSTRACT
In engineering projects involving the construction of aboveground storage tank big enough to retain and/or accommodate large quantities of petroleum products such as crude oil and condensate, mathematical reduction of obtained field data using condition equation method is always appropriate for an onward monitoring of those structures. This paper demonstrates how condition equation method can be used to adjust geodetic surveying measurements in relation to aboveground storage tank. Accuracy is in the order of σa = 5.66e-4 and σb = 1.113e-3 while σsmax and σsmin are 0.0522 and -0.0511 respectively. The results obtained revealed that the method can be satisfactorily implemented for aboveground circular reservoir storage tank structural modelling and monitoring for a similar scenario.
Keywords: Crude oil, Condition equation, Observation, Storage tank
1.0. Introduction
Aboveground storage tanks (ASTs), are commonly used to store large quantities of petroleum products such as crude oil or condensate. Reservoirs used by oil companies in Nigeria are basically cylindrical in shape. In most cases due to age, non-uniformity of foundation, geological conditions loading and offloading, crude oil temperature, primary and secondary settlement of sediments results in radial deformation or out of roundness (Ehigiator-Irughe et al., 2012).
Aboveground storage tanks (ASTs) situated at the Forcados terminal were constructed between 1967 and 1970. Ten (10) of these crude oil storage reservoirs each spanning around 22m in height and of diameter 76.2m are presently in operation. Figures 1 and 2 show the study area and a typical example of the kind of cylindrical tank about which data collection were made.
Periodic monitoring of these tanks has been suggested by Ehigiator-Irughe and Ehigiator (2010). The structural integrity of these reservoirs has been of major concern to both local community and environmentalists especially in Niger delta area of the country. Although API 653 remain the industry standard relative to reservoir inspection and maintenance, the frequency of testing and inspection can also be affected by various State and Local regulations (Ehigiator-Irughe and Ehigiator, 2010).
The schedule of this inspection process depend on a number of factors as noted by Ehigiator-Irughe et al. (2011) which include the age of tank, their proximity to groundwater, the leak records, the date of the last integrity test, the construction material used, the product stored, soil condition, among others. Storage tanks (reservoirs) at Forcados farm are bounded with a bound wall measuring 250m by 150m and at a height of 12m respectively. These bound walls are intended to accommodate as well as contain any accidental spill that may result from failure of any of the reservoir as a temporary remedial means.
The objective of this paper is to determine the vertical movement or shift in the position of the tanks using a precise geodetic levelling instrument DL101C and to establish horizontal controls around the monitoring site by adopting a Total station (Sokkia SET1130R) instrument. Prior to the period of
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2.0. Materials and Methods
2.1. Study area The study area (Forcados) terminal is located in Burutu Local Government Area of Delta State, Nigeria, forming boundary with the Bight of Benin by the Atlantic Ocean with coordinates (759624.59 m E, 591614.74 m N and 760885.71 m E, 590242.51 m N) in UTM Zone 31 (Figures 1 and 2).
Figure 1: Location of the study area and a typical crude oil tank
Figure 2: Screen shot of the study area.
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2.2. Materials The materials used in this work include steel tape, Total station (Sokkia SET1130R), precise geodetic level DL101C, Staff, Computer set and accessories, etc. The circular cross section of each storage tanks was divided into 16 monitoring points distributed around the tanks. These monitoring points were fixed at equal intervals on the outer face of the tanks and placed at 2m high from the tanks base. These monitoring points were established in such a way that they remained fixed throughout the period of observation.
In order to ensure the reliability of the monitoring points, they were tied to higher order control points established in some stable ground and some distances away from the tanks. The total station instrument used for the measurement was mounted on these control points and observation taken to the monitoring station in the tank face. Measurements were made using a combination of angular and linear intersection with the aid of the total station instrument to reflectors held on the studs.
3.0. Results
Figure 3 is a typical model of the levelling networks adopted for the measurement of the height/elevation of the 16 studs, while Table 1 shows the difference in elevation obtained during the exercise.
BM_1A (2.43418)
Stud 1 16 2 15 3 2 14 4
Stud 13 Stud 5
12 6
11 7 10 8 Stud 9
Figure 3: Levelling observation networks
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Table 1: Differences in elevation before adjustment STUDS Diff. Elev. (m) STUD1 ∆h1=1.02036 STUD2 ∆h2=0.01157 STUD3 ∆h3=-0.00026 STUD4 ∆h4=0.00432 STUD5 ∆h5=-0.00363 STUD6 ∆h6=0.00352 STUD7 ∆h7=0.00482 STUD8 ∆h8=0.00406 STUD9 ∆h9=-0.00143 STUD10 ∆h10=0.00085 STUD11 ∆h11=-0.00238 STUD12 ∆h12=0.00209 STUD13 ∆h13=-0.00615 STUD14 ∆h14=-0.00290 STUD15 ∆h15=-0.00524 STUD16 ∆h16=-0.00151 BM_1A -1.02469
3.1. Implementation of condition equation The method of condition equations otherwise known as the method of correlates was described by (Ayeni, 2001; Ghilani, 2006) as one which establishes a set of equations which must be satisfied by the true values of observations, given certain geometrical conditions or physical laws of nature imposed by the configuration of the problem. This is because the true values of observations exist only in the metaphysical/supernatural world. It is only practicable to set up condition equations which relate together some adjusted (that is, most probable value of observations). Using the condition equation as follows:
BMAVh_1 11 Vh 22 VhVh 3344 Vh 55 Vh 66 +VhVhVhVh Vh Vh 7 7 8 8 9 9 10 10 11 11 12 12 (1) Vh13 13 Vh 14 14 Vh 15 15 Vh 16 16 VhBMA 17 17 _1
Substituting the value of the BM height we have: 2.43418 + (V1+∆h1) + (V2+∆h2) + (V3+∆h3) +(V4+∆h4) + (V5+∆h5) + (V6+∆h6) + (V7+∆h7) + (V8+∆h8) + (V9+∆h9) + (V10+∆h10) + (V11+∆h11) + (V12+∆h12) + (V13+∆h13) (2) + (V14+∆h14) + (V15+∆h15) + (V16+∆h16) + (V17+∆h17) = 2.43418.
By substituting the values of (∆hi) we have the following:
VVVVVVVVVVVVVVVVV1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 2.43418 – 2.43418 – 1.02036 – 0.01157 0.00026 – 0.00432 0.00363 – 0.00352 – 0.00482 – 0.00406 0.00143 – 0.00085 (3) 0.00238 – 0.00209 0.00615 0.0029 0.00524 0.00151 1.02469
VVVVVVVVVVVVVVVVV1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
0.00340 Note; Vi = Residual, ∆hi = Difference in elevation, BM_IA = Reference elevation.
The general form of condition equation is given as: BV (4) where B is the design Matrix and is given as: B 11111111111111111 , and V= the vector of Residuals; = 0.00340
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V1 V 2 V 3 V 4 V 5 V 6 V 7 V 8 V V 9 V10 V11 V12 V13 V14 V16 V17
The solution of the normal equation: T MBB (5)
1 1 1 1 1 1 1 1 1 M 11111111111111111 17 1 1 1 1 1 1 1 1
The solution of Lagrange Multiplier [K]: KM 1 1 K 17 0.00340 (6) K 2.0 1004 The residuals: T VBKi (7)
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2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 V 2.00 104 i 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 The variance: T 2 VVi (8) r Numbers of unknowns = 16, numbers of observations = 18.
Therefore, redundancy (degree of freedom) = 2, T 2 VVi 2 T 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 104 2.00 104 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2
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27 3.4 10
Table 2 shows the adjusted elevations for the sixteen tanks (studs) using condition equation model method respectively.
Table 2: The adjusted elevations Staff Set - Staff Readings Prov. Rise (+) Corr. Final Rise (+) Final Elev. (m) Station No Up Back Fore Prov. Fall (-) mm Final Fall (-) Datum----- BM_1A 1.49409 2.43418 P1 STUD1 0.46644 0.47373 1.02036 0.00020 1.02056 3.45474 P2 STUD2 0.55877 0.45487 0.01157 0.00020 0.01177 3.46651 P3 STUD3 0.56466 0.55903 -0.00026 0.00020 -0.00006 3.46645 P4 STUD4 0.54440 0.56034 0.00432 0.00020 0.00452 3.47103 P5 STUD5 0.59716 0.54803 -0.00363 0.00020 -0.00343 3.46760 P6 STUD6 0.37493 0.59364 0.00352 0.00020 0.00372 3.47475 P7 STUD7 0.62290 0.37011 0.00482 0.00020 0.00502 3.47605 P8 STUD8 0.63397 0.61884 0.00406 0.00020 0.00426 3.47529 P9 STUD9 0.32043 0.63540 -0.00143 0.00020 -0.00123 3.46980 P10 STUD10 0.37890 0.31958 0.00085 0.00020 0.00105 3.47208 P11 STUD11 0.45879 0.38128 -0.00238 0.00020 -0.00218 3.46885 P12 STUD12 0.49455 0.45670 0.00209 0.00020 0.00229 3.47332 P13 STUD13 0.26153 0.50070 -0.00615 0.00020 -0.00595 3.46508 P14 STUD14 0.39577 0.26443 -0.00290 0.00020 -0.00270 3.46833 P15 STUD15 0.81228 0.40101 -0.00524 0.00020 -0.00504 3.46599 P16 STUD16 0.50664 0.81379 -0.00151 0.00020 -0.00131 3.46468 BM_1A 1.53133 -1.02469 0.00020 -1.02449 2.43418
Table 3 is showing the studs and their adjusted difference in elevation in relation to the bench (reference) station used for the observation.
Table 3: Studs and their respective adjusted difference in elevation STUDS Adjusted Diff. Elev. (m) STUD1 ∆h1=1.02056 STUD2 ∆h2=0.01177 STUD3 ∆h3=-0.00006 STUD4 ∆h4=0.00452 STUD5 ∆h5=-0.00343 STUD6 ∆h6=0.00372 STUD7 ∆h7=0.00502 STUD8 ∆h8=0.00426 STUD9 ∆h9=-0.00123 STUD10 ∆h10=0.00105 STUD11 ∆h11=-0.00218 STUD12 ∆h12=0.00229 STUD13 ∆h13=-0.00595 STUD14 ∆h14=-0.00270 STUD15 ∆h15=-0.00504 STUD16 ∆h16=-0.00131 BM_1A -1.02469
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The Variance Covariance (V-C) matrix is given as: 21 CTWL 1 TWBMB 11T (9) CBMB 211 T L
1 Since W 1
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CL
Constructing Jacobian Matrix of post adjustment, we have: 휕퐻 휕퐻 휕퐻 휕퐻 1 1 1 … 1 휕∆ℎ1 휕∆ℎ2 휕∆ℎ3 휕∆ℎ푛 휕퐻 휕퐻 휕퐻 휕퐻 2 2 2 … 2 휕∆ℎ1 휕∆ℎ2 휕∆ℎ3 휕∆ℎ푛 휕퐻3 휕퐻3 휕퐻2 휕퐻3 ⋯ 퐽퐼17×17 = 휕∆ℎ 휕∆ℎ 휕∆ℎ 휕∆ℎ (10) 1 2 3 푛 . ⋮ ⋱ ⋮ . . ⋯ . . . . . 휕퐻푢 휕퐻푢 휕퐻푢 휕퐻푢 [휕∆ℎ1 휕∆ℎ2 휕∆ℎ3 휕∆ℎ푛]
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 −1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 −1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
1 1 −1 1 −1 0 0 0 0 0 0 0 0 0 0 0 0
1 1 −1 1 −1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 −1 1 −1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 −1 1 −1 1 1 1 0 0 0 0 0 0 0 0 0 퐽퐼17×17= 1 1 −1 1 −1 1 1 1 −1 0 0 0 0 0 0 0 0 1 1 −1 1 −1 1 1 1 −1 1 0 0 0 0 0 0 0 1 1 −1 1 −1 1 1 1 −1 1 −1 0 0 0 0 0 0 1 1 −1 1 −1 1 1 1 −1 1 −1 1 0 0 0 0 0 1 1 −1 1 −1 1 1 1 −1 1 −1 1 −1 0 0 0 0 1 1 −1 1 −1 1 1 1 −1 1 −1 1 −1 −1 0 0 0 1 1 −1 1 −1 1 1 1 −1 1 −1 1 −1 −1 −1 0 0 [1 1 −1 1 −1 1 1 1 −1 1 −1 1 −1 −1 −1 −1 0]
Post Adjustment V-C Matrix is the V-C matrix CH of the adjusted benchmarks H and is computed as follows: Because the products of both the Jacobian and V-C matrices are large, the first 3 rows and
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T C H J H CL J H s (11)
Where:
1 0 0 0 0 0 1 1 0 0 0 0
휕퐺(퐿) 1 1 −1 0 0 0 푱푯 = = 휕퐿 1 1 −1 1 0 0 1 1 −1 1 −1 0 [1 1 −1 1 −1 1]
3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20
3.20 3.20 3.20 3.20 3.20 3.20 퐶퐿 = × 10−7 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 3.20 [3.20 3.20 3.20 3.20 3.20 3.20]
The V-C matrix CH of the adjusted benchmarks H is then computed thus; 0.0320 0.0640 0.0320 0.0640 0.0320 0.0640 0.0640 0.1280 0.0640 0.1280 0.0640 0.1280
0.0320 0.0640 0.0320 0.0640 0.0320 0.0640 5 CH 10 0.0640 0.1280 0.0640 0.1280 0.0640 0.1280 0.0320 0.0640 0.0320 0.0640 0.0320 0.0640 0.0640 0.1280 0.0640 0.1280 0.0640 0.1280
54 accuracy : ( a ) 0.032 10 5.66 10 accuracy : ( ) 0.128 1053 1.113 10 b and 5 ( ab ) 0.0640 10
1 2 ab 2t tan 22 (12) ba
2 0.0640 2t tan15 10 0.1280 0.0320 2t 1.333 2t 530 07’46’’ t 260 33’ 53’’ 242 Oladosu et al., 2019
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The problem now is to develop a new covariance matrix from existing Q matrix which removes correlation between the unknowns; and the determination of semi-major axis and the semi-minor axis of error ellipse, from which we have:
T CRCRzz LL
sin(tt ) cos( ) R cos(tt ) sin( ) (12a, 12b, 12c)
2 sin(t ) cos( t ) a ab sin( t ) cos( t ) Czz 2 cos(t ) sin( t ) ba b cos( t ) sin( t )
2 a ab 0.0320 0.0640 5 CLL 2 10 ba b 0.0640 0.1280
2 7 4 3.4 10 ; 5.83 10
2 2 2 7 smax sin (t ) a 2cos( t )sin( t ) ab cos ( t ) b 5.85 10 2 2 2 7 (13a, 13b) smin cos (t ) a 2cos( t )sin( t ) ab sin ( t ) b 3.93 10
4 The semi-major axis of error ellipse was obtained as smax 7.65 10 , while the semi-minor axis 4 was obtained as smin 6.27 10
4.0. Discussion
The method of condition equation adopted in this work showed a promising result and can be adopted 4 3 in similar scenarios. Accuracy obtained is in the order of a 5.66 10 and b 1.113 10 before -5 σab=0.0640x10 for the adjusted bench marks heights while the error ellipse are and respectively, representing insignificant error and acceptable values. However, the values were obtained after the application of new covariance matrix from existing Q matrix which removes correlation between the unknowns. The determination of semi-major axis and the semi-minor axis error ellipse gave σ = 5.83x10-4 which is a way to ascertain the magnitude of error at a station.
5.0. Conclusion
In this work, attempt has been made to implement condition equation method in circular reservoir structures (above ground tanks) relying on geodata acquired and further preparation for onward analysis of the shift experienced by these structures at the Forcados crude oil tank farm. Since each condition equation must satisfy certain geometric conditions or physical laws. Suggestion is to adopt the process in similar scenarios across the country where such structures exist in order to buttress on the safety of lives of the inhabitants living close to their location.
References Ayeni, O. O. (2001). Statistical adjustment and analysis of data. A Manual, in the Department of Surveying & Geoinformatics, Faculty of Engineering, University of Lagos, Nigeria, 2001.
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Ehigiator – Irughe, R. and Ehigiator, M. O. (2010). Estimation of the centre coordinates and radius of Forcados Oil Tank from Total Station data using least square Analysis. International Journal of Pure and Applied Sciences. A pan – African Journal Series.
Ehigiator – Irughe, R. Ashraf, A. B., Ehiorobo, J. O. and Ehigiator, O. M. (2011). Modification of Geodetic Methods for Determining the Monitoring Station Coordinates on the Surface of Cylindrical Oil Storage Tank. Research Journal of Engineering and Applied Sciences (RJEAS), 1(1), pp. 58 - 63. A United State Academy publications USA.
Ehigiator-Irughe, R., Ehiorobo, J. O., Ashraf, A. B. and Ehigiator, M. O. (2012). Determination of the Ovality of Crude Oil Storage Tanks using Least Squares. Advanced Materials Research, 367, pp. 475- 483, Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMR.367.475.
Ghilani, C. D. and Wolf, P. R. (2006). Adjustment Computations: Spatial Data Analysis. Fourth Edition. John Wiley & Sons, Inc. ISBN: 978-0-471-69728-2.
Cite this article as: Oladosu, S. O., Okonofua, S. E. and Ehigiator-Irughe, R. (2019). Implementation of Condition Equation Model in Geodetic Observation: A Case Study of Circular Reservoir Structure. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 233-244. https://doi.org/10.36263/nijest. 2019.02.0120
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501 Vol 3, No. 2 October 2019, pp 245 - 255
Finite Element Application in Reservoir Deformation analysis (Pilot Phase 1) Ehigiator-Irughe R. Department of Geomatics, Faculty of Environmental Sciences, University of Benin, Nigeria Corresponding Author: *[email protected]
https://doi.org/10.36263/nijest.2019.02.0135 ABSTRACT
Finite element method (FEM) is a numerical technique for solving engineering problem and mathematical physics, useful problems with complicated geometries, loading, and material properties where analytical solutions may not be obtained. Some of the complicated problems involving load is a cylindrical reservoir structure where crude oil is stored in a tank farm. This paper demonstrates the use of Finite Element Analysis in above surface cylindrical reservoir engineering structure. The reservoir which has sixteen (16) monitoring station was monitored using reflectorless Total station. This paper is a pilot model and it is hoped to be developed further in two more phases to cover the entire reservoir under study. Only two studs in the North East and South East directions were selected to test the FEM forming a triangular shade (Truss) with three elements. The 2D horizontal displacement was found to be 0.02mm, while the vertical displacement was found to be -0.03mm.
Keywords: Crude oil, Finite element, Reservoir, Stiffness matrix, Strain and stress analysis
1.0. Introduction
The security of civil engineering structures demands periodical monitoring. In many civil structures like bridges, vertical oil storage tanks, tunnels and dams; deformations are the most critical parameters to be monitored. Monitoring the structural deformation and dynamic response to the large variety of external loadings has great importance for maintaining structures safety and economical design of man-made structures. One of the Mathematical methods of deformation analysis is Finite Element method (FEM). Thus, the investigated deformable object must be treated as a mechanical system, which undergoes deformation according to the laws of continuum mechanics (Chrzanowski et al., 2006). This requires the causative factors (loads) of the process and the physical characteristics of the object under investigation to be included in both the design and analysis of the deformation. This is achieved by using deterministic modelling of the load-deformation relationship using finite element method (FEM) (Chrzanowski et al., 2006).
For simplicity, at this point, we assume a two-dimensional case with a single field variable φ(x, y) to be determined at every point P(x, y) such that a known governing equation (or equations) is satisfied exactly at every such point. The basic idea in the finite element method is to find the solution of a complicated problem by replacing it by a simpler one. Since the actual problem is replaced by a simpler one in finding the solution, we will be able to find only an approximate solution rather than the exact solution (Yijun, 2003). The existing mathematical tools will not be sufficient to find the exact solution (and sometimes, even an approximate solution) of most of the practical problems (Sourabh et al., 2017). Thus, in the absence of any other convenient method to find even the approximate solution of a given problem, we have to prefer the finite element method. Moreover, in the finite element method, it will often be possible to improve or refine the approximate solution by spending more computational effort (Singiresu, 2005).
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2.0. Materials and Methods
2.1. Study area The Forcados Yokri field is located in OMLs 43 and 45 in Burutu Local Government Area of Delta State of Nigeria. It is bounded approximately by the coordinates 319453mE to 335236mE and 148355mN to 141626mN.
Figure 1: Reservoir no. 6
There are many severe consequences that could result from the failure of a large structure. In addition to jeopardizing public health and safety, environmental contamination and significant economic loss are also of major concern. It is for these reasons that any large deforming structure must be monitored to enable early detection of possible structural damage. Even a slight change of the object shape or changes to the surrounding area due to external factors (e.g. changes in ground water level or tectonic phenomena) no matter how insignificant they may appear could compromise the integrity of a large structure and could lead to disaster. Most deformation monitoring schemes consist of measurements made to the monitored object that are referred to several reference points (assumed to be stable). To obtain correct object point displacements (and thus deformations), the stability of the reference points must be ensured. The main conclusion from the many papers written on this topic states that every measurement made to a monitored object must be connected to stable control points. This is accomplished by creating a reference network of control points surrounding a particular structure (Ehigiator – Irughe et al., 2012).
2.2. Methods An effective approach is carried out to model the structure of oil storage tank by using well-chosen discrete monitoring points located on the surface of the structure at different levels which, when situated correctly, accurately depict the characteristics of the structure.
Any movements of the monitoring point locations (and thus deformations of the structure) can be detected by maintaining the same point locations over time and by performing measurements to them at specified time intervals enabling direct point displacement comparisons (Ehigiator – Irughe et al., 2011). A common approach for this method is to place physical targets on each chosen discrete point to which measurements can be made. However, there are certain situations in which monitoring the deformations of a large structure using direct displacement measurements of targeted points is uneconomical, unsafe, inefficient, or simply impossible. Reasons for this limitation vary, but it may be as simple as placement of permanent target prisms on the structure is too difficult or costly. Figure 2 below represent monitoring stations around the reservoir under study, Figure 3 shows the circular and triangular shape of the monitored stations, Figure 4 shows the 3D view of the reservoir, while Figure 5 represent two monitored station i.e. studs 1 and 5 as well as the centre of the reservoir.
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B. M. 1 D C 6
7 5
E 8 B 4
9 3
10 2 F
11 1 A
12 20
13 19
14 G 18 K
15 17
16
Y
H I
Z B. M. 3 B. M. 2 X
Figure 2: Design of monitoring scheme
Figure 3: Circular and triangular shape of monitored stations
Figure 4: 3D view of reservoir
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Figure 5: Triangular truss element for stud 1, 5 and centre of reservoir
3.0. Results and Discussion
Below are the reservoir parameters as presented in Tables 1 and 2. These parameters where used to determine the displacements, stress and strain of the Reservoir under study.
Table 1: The coordinates The coordinates Derived values X 148396.433m 52.975 1 1 Y 325049.747 -20.722 1 2 X 148428.686 -32.253 2 3
Y2 325069.258 1 -12.724
X3 148375.711 2 32.235
Y3 325081.982 3 -19.511
Table 2: Reservoir properties Length Angles Force at node 1 and 2 Poison (µ) L1=38.150m 0 1000kN 0.25 1= 31 29 14 L2=38.150m 0 2= 76 30 48 L3=54.490m 0 3= 2 02 41''
3.1. Determination of stiffness matrix for the elements The primary characteristics of a finite element are embodied in the element stiffness matrix. For a structural finite element, the stiffness matrix contains the geometric and material behaviour information that indicates the resistance of the element to deformation when subjected to loading. Such deformation may include axial, bending, shear, and torsional effects. For finite elements used in non-structural analyses, such as fluid flow and heat transfer, the term stiffness matrix is also used, since the matrix represents the resistance of the element to change when subjected to external influences. The equation for the local stiffness matrix is given by Equation (1) below.
l22 lm l lm AE lm m22 lm m k (1) l l22 lm l lm 22 lm m lm m
The directional cosines l and m is given as in Equation (2):
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lm1Cos 1, 1 Sin 1 0 1 31 29 14 (2) lm0.853, 0.522 1
The strain displacement matrix [B] is given by:
12003 0 1 B 00120 3 2A 121 2 3 3
where1 y 2 y 3,, 2 y 3 y 1 3 y 1 y 2 (3) and1 x 2 x 3,, 2 x 3 x 1 3 x 1 x 2
or1 y 23,, 2 y 31 3 y 12 and x,, x x 1 23 2 31 3 12
The structural stiffness matrix is assembled by using the element in Equation 1 above. The local stiffness for element (1) is determined by substituting the values in Table 2 into Equation 1, to get:
u1 v 1 u 2 v 2 0.728 0.445 0.728 0.445 u 744.556 210 109 1 k1 0.445 0.272 0.445 0.272 v1 38.150 0.728 0.445 0.728 0.445 u2 0.445 0.272 0.445 0.272 v2
By similar treatment for element 2, the directional cosine and the local stiffness matrix are given thus: lm2Cos 2, 2 Sin 2
0 2 76 30 48 lm2 0.233, 0.972
u2 v2 u3 v3 0.054 0.266 0.054 0.226 u 744.556 210109 2 k2 0.266 0.945 0.266 0.945 v2 54.490 0.054 0.226 0.054 0.226 u3 0.266 0.945 0.226 0.945 v3
Also, by similar treatment for element 3, the directional cosine and the local stiffness matrix, gives; lm3Cos 3, 3 Sin 3 0 3 32 02 41'' lm3 0.848, 0.531
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u3 v 3 u 1 v 1 0.719 0.450 0.719 0.450 u 744.556 210 109 3 kv330.450 0.281 0.450 0.281 38.150 0.719 0.450 0.719 0.450 u1 0.450 0.281 0.281 0.281 v1
By assembling the structural finite element thereby developing global matrix, it gives:
K K1 K 2 K3
u1 v 1 u 2 v 2 u 3 v 3 1.447 0.895 0.728 0.445 0.719 0.450 u1 0.895 0.553 0.445 0.270 0.450 0.281 v 744.556 210 109 1 K 0.728 0.445 0.782 0.671 0.054 0.226 u 38.150 38.150 54.49 2 0.445 0.270 0.671 1.217 0.226 0.945 v 2 0.719 0.450 0.054 0.226 0.773 0.676 u3 0.450 0.281 0.226 0.945 0.676 1.226 v3
3.1.1. Formulation of finite element equation KUF , and applying the boundary conditions, gives: uv110 f11 x0, f y 0 ,
3 f22 x54.069 10 f y
u1 v 1 u 2 v 2 u 3 v 3 u11 f x 1.447 0.895 0.728 0.445 0.719 0.450 u 1 v f y 21 12 0.895 0.553 0.445 0.270 0.450 0.281 v1 150 10 u22 f x 0.728 0.445 0.782 0.671 0.054 0.226 u 79.305 103 2 v f y 0.445 0.270 0.671 1.217 0.226 0.945 v 22 2 u33 f x 0.719 0.450 0.054 0.226 0.773 0.676 u3 v33 f y 0.450 0.281 0.226 0.945 0.676 1.226 v3
3.2. Pressure consideration and reservoir loading The reservoir under study is a cylinder shape with diameter 72.3m and height of 22m. There are 18 of such reservoirs in Forcados terminal. The circular cross section of each storage tank was divided into 16 monitoring points distributed around the tank. These monitoring points were fixed at equal intervals on the outer face of the tanks and placed at 0.5m high from the tanks base. These monitoring points were established in such a way that they remain fixed throughout the period of observation. During observations, the reservoir is first filled to a high of 3m oil level, and three sets of Geomatics observations are carried out at this oil level, which are ovality, subsidence and verticality. The oil level is again filled to 10m, and the three sets of Geodetics observations are carried out as stated above. The reservoir is again filled to 19m, and the three sets of observations are conducted. For the purpose of this pilot research project, the reservoir was filled to 19m oil level which is called reservoir full oil level. The pressure consideration for a reservoir at full oil level can be determined thus:
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Force ma Pr essure SurfaceArea Area m v mass v
Vol. cylinder r2 h 38.150 19 86874.55m3 Crude oil density 870 Kg m3 Mass 870 86874.55 75,580,856.798kg F m a 75,580,856.798 9.8 740,692,396.619 N Surface Area of a cylinder
2rh 2 r2 2 r h r 13,699.656m2 FN740,692,396.619 Pressure 54,068.864 N A 13699.056 54.069 103 N
The pressure value obtained will be used to determine the deformation in all other phases of subsequent studies. By substituting the pressure value and applying the boundary conditions, it becomes:
u2 v 2 u 3 v 3 0.782 0.671 0.054 0.226 uu 12 22 150 10 54.069 3 3 0.671 1.271 0.226 0.945vv22 10 79.305 10 54.069 0.054 0.226 0.773 0.676 uu33 0.226 0.945 0.676 1.226 vv33
Vertical displacement at nodes 2 and 3 = 0
630.782 0.054 u2 54.069 1891 10 10 0.054 0.773 u3 54.069
3 0.782 0.054 u2 54.069 1891 10 0.054 0.773 u3 54.069
1478762uu23 102114 54.069 102114uu23 14617436 54.069
1478762 102114 u2 54.069 102114 1461743 u3 54.069 1 u2 1478762 102114 54.069 u3 102114 1461743 54.069
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The 1D displacement at nodes 2 and 3 are:
u2 0.3931 4 10 u3 0.3974
3.3. Strain analysis When an object is subjected to external force, initially at equilibrium condition, the deformation effect is negligible. However, with a gradual increase in the magnitude of the applied load, the dimensions of the object will be altered, due to deformation. The ratio of change in the dimension due to deformation of the object to its original dimension is called strain. Strain is defined as the force tending to pull or stretch an object to an extreme or damaging degree. The finite element model for strain analysis is given as:
u1 v 1 x u2 B (4) y v 2 xy u 3 v3
where:
[B] is as defined in equation (1 – 3), u1,,,,, v 1 u 2 v 2 u 3 v 3 are the deformation at nodes 1, 2 and 3 respectively.
By substituting the derived values in Table 1 into Equation (3), it gives:
0 0 x 12.725 0 32.235 0 19.511 0 1 39.31 6 y 0 52.975 0 20.722 0 32.253 10 2 744.560 0 xy 52.975 12.725 20.722 32.235 32.253 19.511 39.74 0
The strain is given as:
x 0.0330 0 105 y xy 0.1408
3.4. Stress expression The intensity of the resisting force offered by the intermolecular bonding of the object per unit area towards the load applied before the failure of the object is called as stress. This is also defined as the force per cross – sectional area and the modulus of elasticity for this material under study is given as; 210Gpa 2101000 210,000N mm 2
x x 10v x E Dv 10 (5) y y 1 v2 y xy xy 0 0 1 xy
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By substituting into Equation 4, it becomes:
1 0.25 0 0.0330 210,000 5 0.25 1 00 10 2 1 (0.25) 0.1408 1 0.25 00 2
1 0.25 0 0.1178 224,000* 0.25 1 0 105 0 0 0 0.375 0.5035
x 0.0740 0.0185 y xy 0.1183
The principle of stress is given as: 2 x y x y 2 1,2 xy 22 (6)
2 0.0740 0.0185 0.0740 0.0185 2 0.1183 22
22 1,2 0.046 0.028 0.1183
7.8 1042 1.392 10
0.121
1,2 0.046 0.121
1,2 0.046 0.121 0.167 or
1,2 0.046 0.121 0.075
3.5. Determination of 2D horizontal and vertical displacement The horizontal and vertical displacement can the determined by assuming the following boundary conditions.
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3 f1x f 1 y 0, f 2 x f 2 y f 3 x f 3 y 54.069 10 N
u1 v 1 u 2 v 2 u 3 v 3 u11 f x 1.447 0.895 0.728 0.445 0.719 0.450 u 1 v f y 0 21 12 0.895 0.553 0.445 0.270 0.450 0.281 v1 150 10 u22 f x 0.728 0.445 0.782 0.671 0.054 0.226 u * 79.305 103 2 v f y 0.445 0.270 0.671 1.217 0.226 0.945 v 22 2 u33 f x 0.719 0.450 0.054 0.226 0.773 0.676 u3 v33 f y 0.450 0.281 0.226 0.945 0.676 1.226 v3
0.782 0.671 0.054 0.226 u2 54.069 12 0.671 1.217 0.226 0.945 v 54.069 150 10 2 3 3 10 79.305 10 0.054 0.226 0.773 0.676 u3 54.069 0.226 0.945 0.676 1.226 v3 54.069
1 u2 0.782 0.671 0.054 0.226 54.069 v 150 1012 0.671 1.217 0.226 0.945 54.069 2 103 3 u3 79.305 10 0.054 0.226 0.773 0.676 54.069 v3 0.226 0.945 0.676 1.226 54.069
1 u2 0.782 0.671 0.054 0.226 54.069 v 0.671 1.217 0.226 0.945 54.069 2 1891 103 u3 0.054 0.226 0.773 0.676 54.069 v3 0.226 0.945 0.676 1.226 54.069
The horizontal and the vertical displacement was found to be:
u2 0.0203 v 0.0332 2 u3 0.0209 v3 0.0333
4.0. Conclusion
This research is a pilot project for a reservoir with 72.3m diameter and height of 22m surrounded with 16 studs serving as monitoring stations. In this study, only two studs, i.e. stud 1 and 5 were used, and the centre of the reservoir with 38.15m as the radius. The reservoir is to be divided into three parts, with each part studied separately. The results presented here are for phase 1 i.e. the first part. The results for the second and third phases will be presented in subsequent studies. Based on the results presented, the following highlights are summarized: 1. It is possible to use finite element method to obtain the deformation of large surface reservoirs 2. Monitoring techniques of large circular oil storage tanks can provide valuable deformation data
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3. The suggested technique of analysis for the structural deformation observations can be used to identify and determine the values of deformation for any structure for one epoch of observation 4. The horizontal displacement at studs one and five are almost the same with values of 0.0203mm and 0.0209mm respectively 5. The vertical displacements for the same points are -0.0332mm and -0.0333mm. This indicates that the vertical displacement is downward, which may represent subsidence or settlement of the foundation at full load.
References
Ehigiator – Irughe, R., Ashraf, A. A. B., Ehiorobo, J. O. and Ehigiator, M. O. (2011). Modification of Geodetic Methods for Determining the Monitoring Station Coordinates on the Surface of Cylindrical Oil Storage Tank. Research Journal of Engineering and Applied Sciences (RJEAS), 1(1), pp. 58 - 63.
Ehigiator-Irughe, R., Ehiorobo, J. O., Ashraf, A. B. and. Ehigiator, M. O. (2012). Determination of the Ovality of Crude Oil Storage Tanks using Least Squares. Advanced Materials Research, 367, pp. 475-483, Trans Tech Publications, Switzerland. www.scientific.net/AMR.367.475
Yijun, L. (2003): Lecture note: Introduction to the Finite Element Method, CEA Research Laboratory, Department of Mechanical Engineering, University of Cincinnati, USA.
Chrzanowski, A. and Wilkins, R. (2006) Accuracy Evaluation of Geodetic Monitoring of Deformations in Large Open Pit Mines. Proceedings of the 3rd IAG Symposium on Geodesy for Geotechnical and Structural Engineering and 12-th FIG Symposium on Deformation Measurements.
Singiresu, S. Rao (2004). The finite element method in Engineering Fourth Edition
Sourabh, V., Jain, K. K. and Dave, R. K. (2017). Finite Element Analysis of Disc Brake Rotor for Different Material. International Journal of Information Technology & Mechanical Engineering – IJITME, 3(8), pp. 1-14.
Cite this article as: Ehigiator-Irughe, R. (2019). Finite Element Application in Reservoir Deformation analysis (Pilot Phase 1). Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 245-255. https://doi.org/10.36263/nijest.2019.02.0135
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501 Vol 3, No. 1 March 2019, pp 256 - 267
Analysis of Impact of Exposures and Hydrological Modelling of Flood Peak Zones in Adamawa Catchment, Nigeria
1 1 2, Nwilo P. C. , Olayinka N. D. and Adzandeh A. E. * 1Department of Surveying and Geoinformatics, University of Lagos, Akoka, Nigeria 2African Regional Institute for Geospatial Information Science and Technology (AFRIGIST), Obafemi Awolowo University, Ile-Ife, Nigeria Corresponding Author: *[email protected]
https://doi.org/10.36263/nijest.2019.02.0148 ABSTRACT
During the wet season, the Benue River overflows its banks and sometimes, extreme floods also occur in Adamawa catchment. Intensification of agriculture in some areas and urban growth in other areas has exposed a large population to flood risk. Little is known about localities or areas liable to flood at various peak flows and how land use and soil permeability affects the severity of flood in Adamawa catchment. This study seeks to analyse the exposures of land use/land cover and soil permeability to flood and model flood peak zones for three flow rates (2 years, 5 years and 10 years) using geospatial techniques and HEC-RAS model. Results of 2 years flood show that at least eight localities in the study area are highly prone to flood. This means that the probability of a flood of this calibre to occur and affect those localities in a given year is 50%. The number of localities prone to flood increases for Annual Exceedance Probability of 20% and 10%. The probability of 10% flood to occur and affect those localities in a given year is relatively low compared to both the 2yr and 5yr flood. Modelling results generated a curve number grid map which shows the permeability levels within the study area. Areas with more infiltration capacity recorded 50% (very high) and 20% (high). Moderate permeability score 16%. Very low and low levels account for 7.6% and 5.2% respectively. The implication is that 70% of the total area experience reduced surface runoff whereas 12.9% are more prone to water logging.
Keywords: Adamawa catchment, flood peak zones, Geospatial techniques, HEC-RAS model, land use/land cover, soil permeability to flood
1.0. Introduction
A number of notable researchers have defined floodplain. Floodplains are flat tract of land bordering a river, mainly in its lower reaches, subjected to recurrent flooding and consisting of alluvium deposited by the river (SURCON, 2004; Christopherson, 2012). Wolman and Leopold (1957) describe floodplains as relatively level and low relief landform periodically inundated by flow from adjacent river. Others opinion on what floodplain refers to are background oriented. The definition given for floodplains from several different perspectives, depending on goals in mind is documented by Schmudde (1968): “As a topographic category it is quite flat and lies adjacent to a stream; geomorphologically, it is a landform composed primarily of unconsolidated depositional material derived from sediments being transported by the related stream; hydrologically, it is best defined as a landform subject to periodic flooding by a parent stream. A combination of these characteristics perhaps comprises the essential criteria for defining the floodplain". Floodplain limits are defined by the peak water level of an appropriate return period event at the coast. Subhajit et al. (2010) explained that floodplains are formed by a complex interaction of fluvial processes. Christopherson (2012) reveal that, when river overflow its channel during times of high flow, floodplain is formed. Two types of floodplains are known. They are hydrologic and topographic floodplains. Hydrologic floodplains are floodplains along natural channels not affected by human activity (Schumm and Lichty, 1963; Burkham, 1972). Topographic floodplain is the area of land inundated by a flood of a specific magnitude and frequency, such as the 100-year flood (FISRWG, 1998). The topographic
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Floodplains are points of attraction for human activities because of its richness in nutrient for Fadama or wetland agriculture and availability of drinking water. They are species-rich environments often strongly impacted by human activities (Paillex et al. 2009; Tockner and Standford, 2002). According to Capon et al. (2009), ecologically, floodplains are areas of high productivity providing cover, shelter and food for biota in times of flooding and they hold high stores of plants and animals that can emerge during flooding. Floodplains constitute sinks for river-borne sediment and associated nutrients and contaminants; they are also sources of organic matter, nutrients and biota to the river during flooding (Capon et al., 2009). Contemporary floodplains are, in general, those lands most subject to recurring floods, situated adjacent to rivers and streams. They are therefore flood-prone and are hazardous to development activities if the vulnerability of those activities exceeds an acceptable level (OAS/DRDE, 1991). Floodplains exhibits dynamic pattern. OAS/DRDE (1991) observed that they are neither static nor stable. Fluvial processes (erosion and deposition) make a river to change its course and shift from one side of the floodplain to the other. The floodplain may be periodically modified by floods as the channel move back and forth across the floodplain. Strahler and Merali (2007) opined that when the floodplain is inundated, water spread from the main channel over floodplain deposits. As the current reduces, sand and silt are deposited in a zone next to the channel, creating natural levees-belt of higher land on either side of the river. Backswamp is a lower ground found between levees and bluffs that bound the floodplain. All these explain the characteristics of the dynamic pattern of floodplains.
The Benue River basin particularly Adamawa catchment is characterized by extensive fertile land which have led to intensification of agriculture in some areas and urban growth in other areas. For instance, in Adamawa, mid-sized cities like Jimeta and towns (such as Numan, Fufore, Demsa, Lamurde, Gombi and Ngurore in Adamawa State) situated along the Benue River floodplain are under the pressure of climate induced flood hazards. Seasonal floods in regions adjacent Major River like the Benue annually displaces thousands of people, many of them with no access to clean drinking water, leading to cholera outbreaks (Nwilo et al., 2012). The main concern is that little is known about localities or areas liable to flood at various peak flows. Also, there is dearth of information regarding how land use and land cover (LULC) and how soil permeability affects the severity of flood in Adamawa catchment. The purpose of this study is to analyse the exposures of land use/land cover and soil permeability to flood and delineation areas liable to flood for three flow rates (2 years, 5 years and 10 years) using geospatial techniques, HEC-GeoRAS and HEC-RAS model.
2.0. Methodology
2.1. Description of the study area The study area is Adamawa catchment. The site is along river Benue in the Upper Benue drainage basin of Nigeria. It cuts across the boundaries of six local governments’ areas in Adamawa State – Demsa, Funfore, Ngurore, Numan, Yola North, and Yola South. The major towns in the investigated area are Numan, Jimeta and Yola. The location occupies large floodplain zone in Nigeria. NFDP-II (2003) observed that about 30% of the lowlands in Nigeria are situated in the central part (Kogi, FCT, Nasarawa and Benue States) and about 55% in the eastern area (Plateau, Taraba and Adamawa States). The floodplain ecosystems are subjected to seasonal flooding and are naturally rich in nutrients deposited in the plains as the floodwaters recede. Large volumes of sediment are seasonally discharged into the floodplains and help to renew the fertility of the soils. The climate and weather of the study area are controlled largely by its location along the Benue trough, its position at the north of the Equator and the prevailing winds which follow the movement of thermal Equator. Adamawa has a tropical climate characterized by dry and wet seasons. Dry season lasts for a minimum of five months (November-March) while the wet season spans April to October. Temperature in the region can be as high as 40°C and as low as 18°C. The relief is nearly level to gentle undulating plain with few outcrops. The Sub-catchment border is approximately defined by longitudes 11° 46'E and 14°14'E and latitudes 8° 37' N and 9° 41'N (Figure 1). The land area is about 6,685km2.
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Figure 1: Reference map of the study area
2.2. Data collection Secondary data were sourced and used in this study. They include; Digital Elevation Model (DEM) sourced from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM with a resolution of 30 m, Landsat Operational Land Imager-Thermal Infrared Sensor (OLI- TIRS) image for 2018 with a resolution of 30 m downloaded from the United States Geological Survey (USGS) website, soil map from the 1996 compilation of soil map for Nigeria: a nationwide soil resource and land form inventory by Centre for World Food Studies (SOW-VU) with a resolution of 1: 1:300,000, and Precipitation. Based on the availability of data, predicted precipitation data is used in this study. It was obtained from the downscaled IPPC5 (CMIP5) data using Global Climate Model (GCM) CCSM4 under scenario representative concentration pathway (RCP) 6. There are two periods of time with available predicted precipitation in CMIP5 dataset. They are that of 2014 to 2060 and 2061 to 2080. That for 2014 to 2060 was chosen since it is the available data for the nearest future.
2.2 Description of procedure 2.2.1 Processing of land use/land cover, soil and precipitation datasets Datasets acquired were processed at this stage to generate map layers. Land use and land cover (LULC) map of the investigated area was derived using the 30 m resolution Landsat OLI-TIRS of 2018. The topographic sheets with a scale of 1:50,000 and land cover shapefile from National Space Research and Development Agency (NARSDA) and Google Earth image were used to generate base layers of the catchment boundary, etc. Supervised image classification using maximum likelihood algorithm was applied in ENVI software environment because of its popularity and wide acceptance. Duda et al. (2000) and Akintunde et al. (2016) opined that the maximum likelihood algorithm classification method is one of the superior methods of classification, because it uses various classification decisions using probability and cost functions in categorizing pixels into its corresponding class. The LandSat image was classified into fourteen feature classes based on Afri- cover land cover classification system (FAO, 2005; FAO, 1997) namely; alluvial, grassland, forest, gullies, settlement irrigation project, floodplain, shrub/freshwater marsh, water bodies, riparian forest,
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 256 - 267 rainfed agriculture, reservoir, arable crop plantation and tree crop plantation. Error matrix was performed for classification accuracy assessment, and the overall accuracy and Kappa coefficient were determined. Predicted precipitation data was used in this study to generate precipitation distribution map for the catchment in ArcGIS software. This was also used in the work of Xinyi (2016) to produce similar map. Soil layer characteristics of the study area were derived from the soil map of Nigeria through on-screen digitizing in ArcGIS environment. The LULC, soil and precipitation layers/maps produced were further used as input for floodplain analysis.
2.2.2 Floodplain analysis Floodplain analysis conducted here concentrates on two aspects. The first aspect is to analyze the impact of exposures on the floodplain. The task entails developing hydrologic model for the study basin in HEC-HMS and hydraulic modelling (HEC-RAS modelling) (US-ACE, 2011) to predict the movement of the runoff water over the surface. The second aspect focused on flood inundation mapping at various flow rates.
2.2.2.1 Analysis of impact of exposures: Impact of exposures in this study focuses on land use pattern and soil drainage characteristics (permeability). Information from exposures of land use and soil permeability to flood gives insight in the interpretation of how land use and soil permeability affects the severity of flood in the investigated area. HEC-GeoHMS preprocessing of the LULC was carried out in ArcGIS environment. HEC- GeoHMS was used to define some distributed hydrological parameters and inputs for the project area. To define excess rainfall water volume, the SCS method was selected. This method, according to US- SCS (1986) uses the Curve Number (CN) Grid- a hydrological parameter- to calculate hydrological properties for the whole basin. The CN is the most important parameter for the hydrological model, because of the methods used to accomplish it (US-SCS, 1986). For the creation of the CN grid, the composite land use/land cover polygon shapefile created together with soil type information were used. For the CN method, all the types of soil were classified into four categories. In the composite land use attribute table, some fields were added to create CNLookup table with the Curve Number corresponding to the land cover for each class of soil (A- D). The CN Grid was finally created by defining the hydrologically corrected DEM, the composite LULC and the CNLook up table in ArcGIS.
2.2.2.2 Maping of flood peak zones: Going further, a hydraulic model (HEC-RAS modelling) was used to predict the movement of the runoff water over a surface. HEC HMS hydrological model was used to create rainfall-runoff volume which serves as input for the HEC-RAS modelling and the model analyses the way the water moves on the project area and the places where it concentrates creating inundation problems. HEC-RAS is designed to perform 1-dimensional and 2-dimensional hydraulic calculations for a full network of natural and constructed channel, overbank/floodplain areas, and so on. The geometrical data needed for the hydraulic model that would be developed in HECRAS, was extracted from the terrain model (DEM) by use of the HEC-GeoRAS extension. The work flow is explained under the following sub heading.
(a) HEC-GeoRAS preprocessing: HEC-GeoRAS is a set of ArcGIS tools specifically designed to process geospatial data for use with the HEC-RAS. It is an extension that allows one to create an HEC-RAS import file containing geometric data from an existing digital terrain model (DTM) and complimentary data sets. The processes involved are: (1) Definition of geometrical data extraction operations (2) Stream centreline (3) Bank lines (4) Flowpath centrelines (5) XS (Cross-sectional) cutlines (6) Assigning Manning’s n values (7) Layer setup. The geometric data was then imported into HEC-RAS.
(b) Steady flow data: The next step in the hydraulic model development was adding steady flow data. The assumption that we deal with a steady flow situation was made. The function of steady flow analysis is to apply a time series of discharge rates at each river reach in the computation of cross sectional hydraulic flow. The discharge rates were fed into columns termed as profiles in the steady flow data workspace. The profiles would read information from the HMS discharge model results at specified time steps. To do this, a DSS (data store) connection was made to the location of the data store of results from the HMS model run. Next was to return to the Steady Flow Data page to load
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HMS discharges for the reaches at the specified time window. Reach boundary conditions was defined using the Reach Boundary Conditions button which opens a new tab. There, the boundary for each downstream reach, where there was no junction, was defined. The Normal Depth button was selected and 0.0004 served as input. Finally, the datasets were ready and the model was ready to be run. The result of the described steps was the population of discharge profiles for each element in the geometric model. The profiles were assigned to individual columns for each time step in the HMS model run. The profile names were edited to the time interval needed for floodplain delineation. To run the Steady flow analysis, a computation plan was created. The subcritical flow method was chosen. Flow distribution locations were specified in order for flow velocity to be computed. The Flow distribution location window defined the number of subsections for Channel, Left Overbank and Right Overbank breaks that are required in flow energy levels computation. Other options that were applied were Encroachment and Conveyance Calculations. For the latter, the break points or change stations of Manning’s n coefficients were used in the analysis.
The steady flow computation determines water surface levels of the flood inundation. Several interfaces exist in the HEC-RAS application for visualizing water levels as they change over time. These were viewed for each cross section, stream reaches and also as X-Y-Z Perspective profile plots. To visualise the results, they were exported to a GIS format so it can be opened in a GIS environment.
(c) Post-processing and flood mapping: The post-processing and mapping of the model results were performed in ArcGIS using the HEC-GeoRAS extension. The steps are as follows: (1) Convert to XML format, (2) Layer setup, (3) Water surface TIN generation, and (4) Floodplain delineation: This used the water surface TIN generated and the terrain model to calculate the floodplain boundary and inundation depths.
3.0. Results and Discussion
3.1. Land use/land cover, soil and precipitation mapping Map layers such as land use/land cover (LULC), soil and precipitation were created in this study. Predicted precipitation data was used to generate precipitation distribution map for the catchment. The map (Figure 2) indicates that, rainfall throughout the year ranges from 237 mm to 271 mm. Adamawa in general is naturally divided into two ecological zones; the guinea and Sudan savannah zones. Majority of the population living in the area depends on agriculture as means of livelihood.
Figure 2: Reference map of precipitation
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Agriculture is the mainstay of about 80% of the inhabitants of the area (Adebayo, 1997). Irrigation projects along the Benue and its tributaries in the study area have provided a year round agricultural practice. Also, the ecological condition of the area permits cultivation of root crops, cereals and rearing of livestock in large numbers.
Results of soil mapping shows that there are different types of soils within the study areas (Figure 3) but loamy sandy soils were predominant. Other soils observed in the area are: clay loamy, sandy clay, and sandy loam. Soil has impact on flooding. Nicholls and Wong (1990) observed that the soil types in an area is important as they control the amount of water that can infiltrate into the ground, and hence the amount of water which becomes flow. When the amount of flow is high such that the capacity of the soils could not contain, flood occur. The chance of flood hazard increases with decrease in soil infiltration capacity, which causes increase in surface runoff. When water is supplied at a rate that exceeds the soil’s infiltration capacity, it moves down slope as runoff on sloping land, and can lead to flooding (Lowery et al., 1996).
Figure 3: Soil map of the study area
Land use/ land cover analysis was conducted using Landsat 8 image of 2018. The LandSat image was classified into fourteen feature classes namely; alluvial, grassland, forest, gullies, settlement irrigation project, floodplain, shrub/freshwater marsh, water bodies, riparian forest, rainfed agriculture reservoir, arable crop plantation and tree crop plantation. Error matrix was performed to determine the classification accuracy, and the overall accuracy of 98% and Kappa coefficient of 0,994 were obtained. The LULC map produced is shown in Figure 4. The analysis reveals that rainfed agriculture occupies the highest area (53%). Tree crop plantation was seen to have least coverage (0.06%). Settlement and floodplain agriculture occupy 1.67% and 10.2% of the area respectively. Table 1 captures details of the LULC distribution in the case study area.
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Figure 4: LULC map
Table 1: Distribution of land use and land cover Area Land Use/ Land Cover km2 % Alluvial 25.41 0.38 Grassland 135.27 2.02 Forest 148.12 2.22 Gullies 9.41 0.14 Settlement 111.62 1.67 Irrigation Project 28.61 0.43 Floodplain Agriculture 687.64 10.29 Shrub/Freshwater Marsh 1723.71 25.79 Water bodies 139.93 2.09 Riparian Forest 27.70 0.41 Rainfed Agriculture 3573.03 53.45 Arable Crop Plantation 64.32 0.96 Tree Crop Plantation 4.28 0.06 Reservoir 5.68 0.09 Total 6684.74 100.00 Overall accuracy = 98.866 Kappa coefficient = 0.994.
3.2 Impact of exposure Impact of exposures was investigated in the study area. The outcome (maps) of LULC alongside soil information was used as parameters for generating a permeability map. Exposures of land use/land cover and soil permeability to flood denote how land use and soil permeability affects the severity of flood. Urban land use pattern results in an impervious soil layer increasing the severity of flood and thus, the exposure of land use pattern to flood in an urban area is high. Exposure of soil permeability to flood have direct link to flood flow. Soil permeability refers to the hydrological drainage characteristic of soil to allow water movement through its pores, which is inversely proportional to soil density (Subhankar et al., 2010). The more permeable soil has more infiltration capacity and therefore, reduces surface runoff, whereas less permeable soil has less infiltration capacity and is more prone to water logging (Grosshans et al., 2005). The Curve number (CN) grid map which show the permeability level within the study area (Figure 5) and a background basin map (Figure 6) were generated as thoroughly explained in the methodology. The CN relies mainly on soil data and LULC data. The breakdown of the permeability level within the study area is as shown in Table 2. About
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50% of the investigated area is seen with very high permeability level. Only a total of 293.64 km2 (5.2%) of the area have low level. Moderate and high permeability levels score 16% and 20% respectively. About 7.6% recorded very low level.
Table 2: Breakdown of permeability level Area Permeability level km2 % Very low 432.11 7.69 Low 293.64 5.23 Moderate 906.51 16.13 High 1134.73 20.20 Very high 2851.63 50.75 Total 5618.62 100.00
The more permeable the soil is, the more water can be transmitted through it. A soil with low permeability, such as clay, doesn’t permit much water flow. This could cause “pudding” of water and thus higher accumulation of water on the soil surface. Regions which are composed primarily of these types of soils are prone to a higher flood risk because the water requires a longer time to drain or infiltrate into the ground (Grosshans et al., 2005).
Figure 5: CN grid map
3.3 Hydrological modelling of peak flows Hydrological modelling of peak flows was carried out using HECRAS. The purpose is to have insight about localities or areas liable to flood at various peak flows for River Benue which is the major river in the study area. Three flow rates were specifically analyzed (2 years, 5 years and 10 years) based on availability of flow data, and the resulting floodplains were mapped using HEC-GeoRAS on ArcMap. The delineation and analysis of the floodplain and areas liable to flood for peak flows of the 2 years flood, or Annual Exceedance Probability (AEP) of 50%, revealed that Eight (8) localities in the study area are highly prone to flood (Figure 6). They include: Rumude, Njaredi, Kabawa Changala, Rugange, Sabon Gari Rugange, Yola, Rumude Mallum Yolde Pate, and Modire Yolde Pate (Figure 6). This means that the probability of a flood of this calibre to occur and affect those localities in a given year is 50% or 0.5. The chances of this flood occurring is very high. Results of the 5 years flood, or AEP of 20%, recorded a total of ten (10) areas as highly prone to flood (Figure 7). Two more localities in addition to the eight mentioned earlier are now included. The two additional localities are Nambare and Dumdere. Since, the probability of a flood of this calibre to occur and affect those
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Figure 6: Floodplain for 2 years flow rate on study area
Figure 7: Floodplain for 5 years flow rate on study area
Analysis of 10 years flood (Figure 8) or AEP of 10% shows that the total number of areas highly prone to flood is eleven (11). The specific localities include: Nambare, Rumude, Dumdere, Njaredi, Kabawa Changala, Rugange, Sabon Gari Rugange, Yola, Shagari, Rumude Mallum Yolde Pate, and Modire Yolde Pate (Figure 8). The probability of a flood of this calibre (10% or 0.1) to occur and affect those localities in a given year is relatively low compared to both the 2yr and 5yr flood. The results show that as the recurrence interval (RI), being 2yr, 5yr and 10yr flood, keep increasing, their
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Annual Exceedance Probability or chances of occurrence keep decreasing. In worst case scenario, there could be 100 yr flood (1% AEP), 200 yr flood (0.5% AEP) and 500 yr flood (0.2% AEP). This study has provided information on the extent of flooding and floodwater inundation.
Figure 8: Floodplain for 10 years flow rate on study area
4.0. Conclusions
This present study has provided information regarding localities or areas prone to flood at various peak flows and how land use and soil permeability affects the severity of flood in Adamawa catchment, Nigeria. Geospatial techniques, HEC-GeoRAS and HEC-RAS model have thus been applied. The Benue River basin particularly Adamawa catchment is characterized by extensive fertile land which have led to intensification of agriculture in some areas and urban growth in other areas. These have exposed a large population to flood risk during the wet season, as the Benue River usually overflows its banks and sometimes, extreme floods also occur in the catchment. Three flow rates were specifically analyzed (2 years, 5 years and 10 years) based on availability of flow data, and the resulting floodplains were mapped. Results of 2 years flood show that eight localities in the study area are highly prone to flood. The number of localities prone to flood increases for Annual Exceedance Probability of 20% and 10%. Modelling results generated a curve number grid map which shows the permeability levels within the study area. Findings reveal that larger parts of the catchment have more infiltration capacity which implies reduced surface runoff whereas areas more prone to water logging are about 12.9% of the total catchment.
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Cite this article as: Nwilo P. C., Olayinka N. D. and Adzandeh A. E., 2019. Analysis of Impact of Exposures and Hydrological Modelling of Flood Peak Zones in Adamawa Catchment, Nigeria. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 256-267. https://doi.org/10.36263/nijest.2019.02.0148
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 268 - 291
The Impacts of Climate Change on Nigerian Ecosystems: A Review
Ikumbur B.* and Iornumbe S. Department of Geology, Benue State Polytechnic Ugbokolo, Nigeria Corresponding Author: * [email protected]
https://doi.org/10.36263/nijest.2019.02.0128
ABSTRACT
Climate change is the single biggest environmental issue facing the world today. It has become a great challenge to our generation and its impact is felt in almost every society in the world. Nigeria is one of the most vulnerable countries in Africa. Nigeria as a developing nation with a population of about 200 million people is likely to be adversely impacted by climate change due to its vulnerability and low coping capabilities. Climate change is evidently linked to human actions, and in particular from the burning of fossil fuels and changes in global patterns of land use. The impacts of human activities, as well as those of natural phenomena on global warming, climate change, and the environment, were presented and discussed. Various manifestations of its impact are evident in Nigeria, which includes temperature rise, increase in draught, and scarcity of food instigated by irregularities in rainfall, over flooding, and so on. This paper examines the concepts of global warming and climate change; its impact on the Nigeria ecosystems. It highlights the climate change-related risks and hazards the nation could face if best practices are not employed to prevent and mitigate its impact. Two sets of measures have been advocated for confronting climate change, these are mitigation and adaptation measures. The review explores possible adaptation strategies that are required to respond to the climatic variations and suggests ways that these adaptation strategies can be implemented.
Keywords: Climate change, Impact, ecosystems, global warming, mitigation, adaptation, greenhouse effects
1.0. Introduction
An ecosystem is a community of living organisms in conjunction with non-living components of their environment, interacting as a system (an entity). These biotic and abiotic components are linked together through nutrient cycles and energy flows. Climate change refers to an increase in mean (average) temperatures. Human activities and natural variations are believed to be contributing factors to an increase in mean global temperatures. The increase in average global temperatures is caused primarily by an increase in greenhouse gases such as Carbon Monoxide, Carbon dioxide, Water vapour, Methane, Nitrous Oxide, and Ozone. There is a new damaging greenhouse gas that has been discovered called Sulfuryl Fluoride. It was first used as a fumigant to kill termites. This chemical can last for up to 40 years and traps significant amounts of heat more than Carbon dioxide (Reigart and Roberts, 2013). Human lives are directly linked to the climate. Climate change of course has great impact on the ecosystems. There has been a continuous rise in global temperature in the last 130 years, which has huge consequences on a wide-range of climate related factors. It is evident that carbon dioxide (CO2) and Methane are being dumped in the atmosphere at an alarming rate as a result of the advent of industrial revolution (Nwankwoala, 2015). There are oil spillage and gas flaring all over the environment. Fossil fuels burning and deforestation which produce greenhouse gases are on the increase. This phenomenon is called greenhouse effect. Greenhouse gases act like blanket around the earth, wrapping energy into the atmosphere. This is the cause of the earth warming. As such our
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 earth’s average temperature has risen by 10C over the past century, and is projected to raise another 1.10C to 6.40C over the next hundred years (Nwankwoala, 2015). This rise in temperature of the planet can bring about ice caps melting, sea levels rising and other environmental challenges. The build-up of greenhouse gases can change Earth’s climate and result in dangerous effects to human health, safety, welfare and to the ecosystems. There are distortions and pollutions in our water supplies, agriculture, weather, seasons, power, transportation system, and so on. However, it is important to state that, some changes in the climate are unavoidable; carbon dioxide can stay in the atmosphere for nearly a century. As such, the earth will continue warming, and the warmer it becomes, the greater the risk for more adverse changes to the climate and the Earth’s system. Even though it is difficult to predict or forecast the impact of climate change, yet, what is certain is that the climate we are used to is no longer a reliable guide for what to expect in future. In view of the adverse effects of certain human activities, that cause earth warming and climate change, it is important that we begin to make choices that will reduce greenhouse gas pollution, and the best way out of this is to get ourselves and the younger generations educated through our education systems and other avenues of public enlightenment (Nwankwoala, 2015). Global warming is causing the glaciers and arctic ice cap that has been preserved for millions of years to melt faster, and this can affect many different ecosystems. The flow of colder water from the melting ice is flowing into the sea much faster, and this can cool the warm water flows that are necessary for tropical marine life. Tropical fish and animals may not be able to survive if the water temperature changes drastically and marine life that can absorb may do so increasingly and become threatened. The Pristine lands and habits that are around the melting ice can also be adversely affected. Greenhouse gases pose a very real and significant threat to the world ecosystems. Greenhouse gases are gases present in the atmosphere that have a greenhouse effect, trapping heat in the atmosphere and close to the surface of the earth rather than allowing the heat to go back into space. Emissions of greenhouse gases can be as a result of burning fossil fuels, and also of the pollution of the air from many different chemicals. This causes the air in the atmosphere to stay warmer and can have a devastating effect on all the ecosystems of the world (Nwafor, 2007; IPCC, 2007; Odjugo, 2009). Global warming due to increased greenhouse gases has already had a great impact on the earth and many of the ecosystems. The weather around the world is slowly warming, and tropical storms, devastating hurricanes, typhoons, and other severe weather patterns are on the increase. The climate and temperature of areas are changing, leading to an increase in unknown and unusual bacteria and viruses to be found. This can pose a very serious problem since this can lead to a global threat that is worldwide from climate-related diseases and other life-threatening challenges (UNFCC, 2006; FAO, 2008; Hans-Peter et al., 2009; Osman-Elasha, 2010; Raheem, 2011; UNDP, 2013). As global warming from greenhouse gases affects the world ecosystems, the ocean is one of those affected greatly. Tropical storms and hurricanes, as well as some other weather-related events depend on the warm water. Warmer water means an increase in tropical storms and worse, both in intensity and frequency. Hurricanes and tropical storms need warm water to derive their energy from, and global warming is providing this. In the last ten years, storms that are more powerful have been occurring frequently, and if greenhouse gases continue to contribute to global warming it will only get worse because of the great damage done to the world ecosystems (UNFCC, 2007). It is crucial that we try and slow down or completely eliminate the emission of greenhouse gases so that there is no longer a threat to the world ecosystems from them. This means lowering and/or stopping our dependence on fossil fuels because these gases are mostly responsible for the greenhouse gases that are damaging the world ecosystems (UNFCC, 2007). Using alternative and renewable fuel sources instead of fossil fuels is the way to prevent global warming from becoming worse. By controlling and reducing the greenhouse gases that are released, by minimizing the use of fuels that contribute to the emission of these gases, we can help preserve the world ecosystems and prevent them from suffering more damage. This can be done by using biofuels and alternative energy sources (such as solar energy, geothermal energy, wind energy, hydropower energy, biomass energy and energy from waste) whenever possible instead of using fossil fuels (UNDP, 2013). This will keep the
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 world ecosystems in good shape and prevent the emissions of large amounts of greenhouse gases. The renewable energy world is a safer world to live in since it does not have a harmful nature. Climate change impacts ecosystems, livelihoods, human security and socio-economic development of societies, and has been defining the direction of human wellbeing and development (UNDP, 2008). The world, especially the developing nations will be faced with shortages of necessities of life such as water and food. Climate change affects health, shelter, livelihood, and life in general. The negative impacts of climate change currently reflect on dwindling natural resources, including food, which generally affects the human environment, economy, and health (Onyenechere, 2010). Oladipo (1995) noted that as the planet gets warmer, the pattern of rainfall alters, extreme weather events such as floods, droughts, and forest fires turn out to be recurrent. The world ecosystems, economy, and a healthy environment are at the mercy of variations of the earth's climate, which is moving at a pace that seems beyond recovery (Olusola, 2012). Researches have shown that Nigeria is already being plagued with diverse ecological problems, which have been directly linked to the on-going climate change (Odjugo 2001a; 2005; Odjugo and Ikhuoria 2003; NEST 2003; Chindu and Nyelong 2005; Mshelia 2005; Ayuba et al., 2007). While Odjugo (2001a, 2005) observes erratic pattern of weather elements in Nigeria, Odjugo and Ikhuoria (2003) show that climate change has started impacting on desertification and Ayuba et al., (2007) show that climate change is impacting negatively on plant species composition in North-eastern Nigeria. These may not be the only impacts of climate change in Nigeria. It is on this premise that this study took an overview of the impacts of climate change in Nigeria with the aim of compiling and synthesizing them holistically. Africa is already a continent under pressure from climate-related stresses and is highly vulnerable to the impact of climate (Jagtap, 2007; Nwafor, 2007). Available evidence suggests that the negative impact of climate change on our world today is prominent in Africa (Jagtap, 2007; Nwafor, 2007). Given that most dry lands in Africa are poverty hot spots as well, the risk of desertification is high in many of these areas and the poor Africans have inevitably become both the victims and willing agents of environmental damage and desertification (Adefalolu, D., 2007). In Sub- Saharan Africa, persistent drought and desertification have been the order in recent times, which may likely persist (Onyenechere, 2010). Nigeria is experiencing adverse climatic conditions with negative impacts on the welfare of millions of people. Persistent droughts and over flooding, off-season rains and dry spells have sent growing seasons out of orbit, on a country dependent on rain-fed agriculture. There is an indication of the possible danger with lakes drying up and a reduction in river flow in arid and semi-arid regions. The possible result is inadequate water supplies for use in agriculture, hydropower generation and other users. The main suspect for all these havoc is climate change. Scientific studies show that snows are disappearing rapidly (UNFCC, 2006). Climate change has been confirmed following the release of the 5th IPCC Assessment Report (IPCC, 2014). Human influence on the climate system is clear, and recent anthropogenic emissions of greenhouse gases are the highest in history. Recent climate changes have had widespread impacts on human and natural systems (IPCC, 2014). Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, and sea level has risen (IPCC, 2014). Africa will be worst hit by the effects of climate change which Nigeria is part of (Olaniyi et al., 2014).In Nigeria, the increase in drought, scarcity of food caused by irregular rainfall, over flooding, to mention but a few, are all evidence of the impact of climate change in the country. Vulnerable communities like the coastal and delta regions are largely suffering the consequences such as over flooding leading to a drift of many individuals in the Niger Delta region (Olmos, 2001). Atilola, (2012) notes that “while the industrialized countries of the world, the major contributors to climate change have the capacity to respond to the impact of climate change, most developing countries do not have adaptive capacity to global warming”. Watson, et al., 1998) argued that the "vulnerability of a region depends to a great extent on its wealth, and the poverty limits adaptive capabilities”.
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This paper discusses the issue of global warming and climate change; its impact on the ecosystems in Nigeria. It highlights the climate change-related risks and hazards the nation could face if best practices are not employed to prevent and mitigate its impact. It explores possible adaptation strategies that are required to respond to the climatic variations and suggests ways that these adaptation strategies can be implemented.
2.0. Concepts of Climate Change 2.1. Greenhouse effect This is simply the process by which radiative energy leaving the earth’s surface is absorbed by some atmospheric gases, called greenhouse gases. Some examples of these greenhouse gases are carbon monoxide, carbon dioxide, methane, nitrous oxide, fluorinated gases, and chlorofluorocarbons. Carbon dioxide is the most common of greenhouse gases but there are greenhouse gases that are more potent than carbon dioxide. The methane gas is estimated to be 21 times more potent than carbon dioxide with an atmospheric lifespan of about 12 years (EPA, 2009a). The nitrous oxide is 310 times more potent as a greenhouse gas than carbon dioxide and has an atmospheric lifespan of 120 years (EPA, 2009b). It is also worthy to note that methane and carbon dioxide are emitted largely during the burning of fossil fuels, and nitrous oxide is produced during agricultural activities, as well as the burning of solid waste; while fluorinated gases are mostly obtained from industrial activities. OECD (2008) notes that quantitatively, the largest share is accounted for by power generation (electricity production and transmission were responsible for 26% of global emissions in 2004), followed by industry, generally (about 19%) and transportation (13%). It is important to note that deforestation and forest degradation (about 17%) are estimated to account for more emissions globally than the entire transport sector. More so, it is the increasing temperature of the globe that culminates into other changes around the world, such as strong winds (hurricanes), melting glaciers, and the loss of biodiversity. This process makes the temperature rise in the atmosphere just as it does in the artificial greenhouse, and is called global warming (Ayuba et al., 2007). It is now clear that global warming is mostly due to man-made emissions of greenhouse gases (mostly CO2).
2.2. Global warming Global warming is “the increase in the average temperature of the earth’s near-surface air and the oceans since the mid-twentieth century and its projected continuation”. The scientific community has reached a consensus that global warming is real and that human activities are causing the warming trend. Global temperatures have steadily risen over the last century, and according to scientists, 2005 was the warmest year on record and the warming trend is expected to continue through the 21st century and beyond (Olaniyi et al., 2014). From various scientific researches, it has been estimated that average global temperatures of the earth surface increased 0.740C ± 0.180C during the 100 years ending in 2005 (Olaniyi et al., 2014). Scientific climate modelling projections recently summarized by the Intergovernmental Panel on climate change (IPCC) indicate that global surface temperature will likely rise a further 1.10C to 6.40C during the 21st century (IPCC, 2007); while Nebedum and Nnaemeka, (2016) estimated an average rise in temperature ranging from 1.50C to 4.50C on the earth if the greenhouse gas emissions continue through 2030. Climate is the average state of the weather; it is fairly stable and predictable, while the weather is the day to day state of the atmosphere; it is a chaotic non-linear dynamic system (Olaniyi et al., 2014). In general terms, climate means the pattern of weather which involves averages of variables such as cold and hot, drizzles and rain, cloudy and clear, breeze and blizzard, humid and dry, and other variables that can be measured at any time. The major effect of global warming is climate change, which is the sudden change of climate patterns and the resultant effects on the environment and human life. Climate change is the change in the state of the climate that can be identified by changes in day to day state of the atmospheric properties which persists for very long periods. Climate change occurs when the amount of energy stored by the “climate system” is varied (Olaniyi, et al., 2014). The variation takes place when the balance between
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 energy received from the sun and the radiated energy is disturbed. The disturbance can be caused by several natural systems like changes in earth’s composition, variation in earth’s orbit, variation in ocean circulation, and changes in sea level. In recent times, human activities are the cause of the disturbance (Olaniyi et al., 2014).
2.3. Climate change Climate change simply refers to the climatic condition of a place after a given period of time. These include temperature, humidity, precipitation, and wind. Natural events and human activities are believed to be contributing to an increase in average global temperature (Anyadike, 2009). The reasons for climate change may be natural; however, it is mainly caused by human activities. Human activities often lead to the release of greenhouse gases into the air which has the ability to easily retain excessive heat in the earth space. Activities that involve the burning of fossil fuels, including transportation and energy production, are increasing the concentrations of greenhouse gases in the atmosphere, trapping heat and causing global warming (Ayuba et al., 2007). Ogbo and Onyedinma, (2012) noted that “The extra-terrestrial factors include solar radiation (quantity and quality), while the anthropogenic factors involve human activities that either emit large amounts of greenhouse gases into the atmosphere that depletes the ozone layer or activities that reduces the amount of carbon absorbed from the atmosphere”. The reaction of some greenhouse gases with rainwater produces acid rain during fossil fuel combustion and this contributes to climate change. Greenhouse gases cause the greenhouse effect, which is the reduction of the amount of infrared radiation emitted by the earth surface which escapes to outer space by these gases (Uyigue, et al., 2010).
2.4. Vulnerability The IPCC (2001) defines vulnerability as "the degree to which a system is susceptible, or unable to cope with adverse effects of climate change, including climate variability and extremes". The vulnerability could mean the potential of a population to be negatively affected by the impact of climate change, whether small or high intensity. Nigeria, like every other developing nation, faces the risk of the impacts of climate change. This risk, directly or indirectly, will be detrimental to the nation's economy if it is not effectively addressed. The vulnerability of a group can be affected by features that are both socioeconomic and physical. Among the populations that are particularly vulnerable to climate-shocks are those living in particularly dangerous locations, such as those living in floodplains, settlements that lack protective infrastructure and poor quality housing (Satterthwaite et al., 2007). It is worthy to note that vulnerable groups differ in the magnitude of climate change impacts on their general wellbeing and adaptive abilities, such as health condition, age, income, knowledge, and resources. It has been noted that households that have meaningful access to economic resources and maintain effective social networks tend to be less vulnerable but can experience a larger share of losses (in absolute terms) than households with meagre resources and poor social networks. The more affluent households tend to be more resilient and more likely to recover quickly from climate-related stress and stimulus than the poorer ones (Blaiki et al., 1994; Wisner et al., 2003; Fatile et al., 2012). Similarly, vulnerability varies across regions, continents, and countries. This can be noticed in the uneven distribution of rainfall and temperature, as well as resources. Though vulnerability differs substantially across regions, it is also recognized that even within regions, degrees of vulnerability vary (IPCC, 2001).
3.0. Causes and Evidence of Climate Change in Nigeria 3.1. Causes of climate change Climate change is caused by two basic factors which include natural processes (bio-geographical) and human activities (also known as anthropogenic factors). The earth’s climate can be affected by natural
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 factors that are external to the climate system such as changes in volcanic activity, solar radiation and earth’s orbit around the sun; these factors and its effects have relatively short term effects on climate (Nebedum and Nnaemeka, 2016). Climate change is caused by a change in global energy balance owing to fluctuations in the earth's orbit, ocean circulation, and atmospheric composition (Olaniyi, et al., 2014). The United Nations Framework on Climate Change (UNFCC) uses the term ”Climate Change” only for human induced change, while the term “Climate Variability” applied for changes due to external forcing. External forcing is climate change caused by change in the global energy balance owing to fluctuations in the earth’s orbit, ocean circulation and atmospheric composition (Olaniyi et al., 2014) The anthropogenic factors which are human activities that emit large amount of greenhouse gases into the atmosphere that depletes the ozone layer or activities that reduce the amount of carbon absorbed from the atmosphere. Human activities such as burning of fossil fuels, gas flaring, urbanization, agriculture (fertilizer application, fermentation among others), cement production and changes in land use like deforestation and desertification release greenhouse gases (GHGs) into the atmosphere which increase the already existing concentration of these gases. The human factors have been proven to be responsible for the ongoing unequivocal climate change or global warming (IPCC, 2007; IPCC, 2014). Industrial activities are other causes of climate change. For example, the activities of automobiles and other industries have led to the emission of several gases like carbon dioxide into the atmosphere which over time affects the composition of greenhouse gases leading to altered climate (Kadafa, 2012). According to the South African Confederation of Agricultural Union, the main greenhouse gases are carbon dioxide, methane and nitrous oxide which accounts for 80%, 14% and 6% of the total greenhouse gas emissions respectively (South African Confederation of Agricultural Union, SACAU, 2009). Greenhouse gases are good absorbers of heat radiation coming from the earth surface and acting like a blanket over the atmosphere keeping it warmer than it would be. It has been suggested that if the current trends of anthropogenic greenhouse gas emissions continue to 2030, the earth is likely to experience an average rise in temperature ranging from 1.50C to 4.50C (Porter and Brown, 1991). It is well established that the activities of developed nations are mostly accounted for climate change but the developing nations are those suffering more due to instability to cope as a result of poverty and low technological development (Odjugo, 2010). The intergovernmental Panel on Climate Change (IPCC) and major scientific organizations of industrialized countries have concluded that the increase in global temperature since the middle of twentieth century has been due mainly to human induced (anthropogenic) greenhouse gases concentration via the greenhouse effect, while the warming effect caused by natural phenomenon such as solar variation contributed a small warming effect from pre- industrial times to 1950s and from then a reverse cooling effect began (Olaniyi et al., 2014; IPCC, 2007 and IPCC, 2014). Climate and environmental changes are also as a result of human activities. Thus, Barade (2009) stated that our planet is unique to support life. However, within the limitations of our understanding of the terms, evolution and progress, human beings contributed a number of disastrous climate change triggers. Some of them are increased carbon dioxide emission, increase in greenhouse gas levels, and increase in land, water and air pollution levels. He is therefore of the view that the high level of industrial pollution and a number of human induced processes have resulted in climate change and environmental hazards. Kwan et al., (2011) are of the opinion that pollution is the process by which substances are added to the environment or the addition of materials to the environment that damages or defiles it, making it undesirable or unfit for life. These materials according to them are called pollutants. They further explained that as human populations increase and as society become more industrialized and urbanized; the problem of pollution has become more serious. Obviously, many of the products of modern technology which find their ways into the air and water are toxic and harmful to life of organisms and the entire ecosystem. Below are outlines of environmental pollutants caused by human activities.
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Air pollutants - air pollution occurs as a result of incomplete burning of fuels such as coal, oil, petrol and wood (Kwan et al., 2011). Apart from human activities, the gaseous pollutants emitted into the air can also be by natural occurrences such as biological decay, forest fires or volcanic eruptions as mentioned earlier. These harmful gaseous pollutants include; sulphur dioxide, nitrogen oxides, carbon dioxide, carbon monoxide and lead. Sulphur dioxide and nitrogen oxides- these occur as a result of the burning of fossil such as coal, oil and natural gases. Sulphur dioxide at a very high concentration has damaging effects on both plants and animal lives. In the case of plants, it penetrates the leaves through the stomata (tiny opening in the cells of the leaves) and kills the plants. In the case of humans, sulphur dioxide causes irritation and damaging of the sensitive lining of the eyes, air passages and lungs. When this occurs for long time in an environment, it causes respiratory diseases. Furthermore, it is also important to state that, when sulphur dioxide and nitrogen oxide react with oxygen and rain water, they form sulphuric acid and nitric acid respectively. Rain water containing these acids is called acid rain. The presence of acid rains in lakes and rivers causes the death of fish and other creatures in so many countries of the world today. Kwan et al., (2011) also opined that sulphur dioxide is the main component of killer smog; which is a mixture of smoke and fog. Normally when smoke is emitted during burning, it is blown by the wind, and it goes to mix with the cool air. This mixture is prevented from escaping by a layer of warm air which acts like a cover above it. The mixture of the cool air and the pollutant remains stagnant air until it forms high concentration to produce lethal results. This causes respiratory problems (Kwan et al., 2011). Lead –it is possible to find the presence of lead in the food we eat, the water we drink and the air we breathe in. A long time accumulation of lead in the body system could lead to high concentration of lead which may result to cramps, loss of control of hands and feet, and sometimes coma and death. Air in cities has higher presence of lead than the air in rural areas. Carbon monoxide - the exhaust of motor vehicles, generators, air crafts, motorcycles and other forms of engines that emit such gases are the sources of carbon monoxide. When carbon monoxide is breathed in, it combines with haemoglobin in the red blood cells to form “carboxyhaemoglobin” which reduces the capacity of the blood to transport oxygen round the body. The may be very harmful when it occurs in high concentration and could be attributed to most deaths that occur when people confine themselves to areas where carbon monoxide is emitted without cross ventilation. Carbon dioxide - this factor though primarily caused by human activities through the burning of organic compounds which results to the releasing of carbon dioxide into the air, yet has some natural implications. As such, carbon dioxide is the most important gases that cause “Greenhouse effects”. This occurs when the sun rays hit the earth surface, but when they are reflected back into space, they are trapped in the atmosphere. The sun rays cannot escape from the earth’s atmosphere, and the earth heats up; in other words, certain atmospheric gases like carbon dioxide, water vapour, and methane have the ability to change the energy balance of the earth by being able to absorb “long wave radiation” emitted from the earth’s surface. The result of this may be global warming. The possible effect is that the world temperature may rise; Icebergs may melt, leading to an increase in quantity of water in the oceans. Chlorofluorocarbons (CFC3) - These are non-toxic, unreactive chemicals. They are used as aerosol propellants, as cooling agents in refrigerators and air conditioners, and in foam packaging. Chlorofluorocarbon is released into the atmosphere from aerosols and other sources break down the Ozone layer of the atmosphere. The Ozone is a gas that forms a layer over the Earth and it absorbs much of the ultraviolet rays from sunlight. So when the Ozone is broken down; more ultraviolet light reaches the Earth. This increases the risk of skin cancer (Kwan et al., 2011). Dust - these are smooth, fine dry particles of matter. So much dust is released into the atmosphere due to human activities like, construction, sweeping, mining, cement industrial sites and other sites. Industrial processes produce a lot of toxic materials. For instance, asbestos dust is believed to be the major cause of lung cancer in industrial worker who inhale them for long period of time. Natural
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 phenomenon such as volcanic eruption, burning of garbage, chimney fumes, also causes the release of dust into the atmosphere. Fumes – these are gaseous products or anything which contains airborne solid particles that are smaller than dust fumes are normally generated by incineration plants and industrial plants and can remain in the atmosphere even far from the place where it was released from. These fumes cause severe irritation of the respiratory system in human beings. Pollen grains- these are usually released by flowers. These pollen grains are very small in size and as such can travel a very long distance. When they are inhaled, they can trigger allergic reactions in humans. Water pollutants - Rivers, streams and lakes are polluted by waste materials dumped into them by humans. These affect communities that live in such areas. The following are the various ways water can be polluted; Sewage- when untreated sewage is discharged into rivers and lakes, they cause the breathing of bacteria. Bacteria grow and multiply using up the oxygen in the water, thereby causing fishes and other organisms in the water to die. These bacteria can also continue to break down the organic wastes, thereby releasing foul-smelling gases like hydrogen sulphide and ammonia. Untreated sewage also causes diseases like cholera and typhoid which sometimes get into wells, bore-wholes and sources of drinking water, which may result to epidemics. Fertilizers- these are chemicals used by farmers to increase yields of crops. The fertilizers contain nitrates and phosphates which are useful nutrients for the growth of algae and plants. However the over use of chemical fertilizers may cause water pollution in the sense that fertilizers that are not absorbed by crops may be washed away by rainwater into nearby rivers and lakes. These are harmful to water organisms. Inorganic wastes- these include industrial wastes such as poisonous metals like, mercury, arsenic and cadmium. These can be disposed of into rivers, streams and lakes. This can be illustrated by what happened in Minamata, a coastal town in Japan in 1972. A plastic factory had discharged waste water containing high concentration of mercury. About 40 people who eat the contaminated fish and shellfish died of mercury poisoning. About 70 people were crippled; blinded or paralyzed (Nwankwoala, 2015). Pesticides – these are substances used to kill pests that destroy crops in farms. They include insecticides and herbicides. Insecticides are specifically used to kill insects. When applied to farms, they can be carried by rain water into rivers, streams and lakes. When they are in high concentration they may poison fish or animals that drink the water or feed on the contaminated fish. Again, insecticides DDT (Dichlorodiphenyltrichloroethane) are insoluble, and as such are stored in the fatty tissues of animals that consume them, and as such may result to serious health hazards. Also herbicides are substances used to kill weeds. Agriculturists are of the view that herbicides like “2, 4, 5-T”, contain an impurity called dioxin, which is harmful to human beings (Kwan et al., 2011).
Noise pollution - this is a type of pollution whereby excessively loud and unpleasant sounds of more than 80 decibels are produced. The world, especially African nations have become very noisy. There are heavy machineries, construction sites, mining activities that produce noise. Electrical gargets that produce noisy sounds like microphones, radios, megaphones, televisions, etc. are indiscriminately used in homes, cities, market places, streets, churches, mosques, hotels, club houses etc. Drivers of cars and Lorries blow horns of their vehicles at random. All these causes noise pollution which cause harm to humans. Prolonged exposure to noise can result in severe loss of hearing. Noise pollution in any environment can also cause emotional stress, irritability, lack of sleep or insomnia, high blood pressure psychological disturbances and low work productivity (Onuoha, 2012).
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Soil pollution - these are the build-up of chemical substances and other waste materials from factories in the soil. The presence of these substances makes the soil to lose its fertility and lead to the leaching of nutrients into water, and death of plants, crops or even animals. Other causes of soil pollution include (Kwan et al., 2011); i. Inorganic nutrients like nitrates and phosphorous from the use of fertilizers; ii. Toxic chemicals from the indiscriminate use of pesticides; iii. Oil spill from oil pipes; iv. Heavy metals such as chromium, cadmium and copper from smelting industries; v. Liquid sewage wastes; vi. Solid wastes such as rubbish, domestic refuse, paper, plastic and glass.
3.2. Evidence of climate change in Nigeria Human influence on the climate system is clear, and recent anthropogenic emissions of the greenhouse are highest in history. Recent climate changes have had widespread impacts on human and natural systems. Climate change is already happening and small changes in average conditions such as sea level, or temperature can result in large changes in frequency of extreme events which are highly detrimental to our society. A 20 cm rise in sea level will inundate 3,400 km of Nigerian coast- land and 100 cm rise in sea level will cover 18,400 km and submerge the Delta’s entire oil and gas infrastructure (Onofeghara, 1995). Nigeria is experiencing adverse climate conditions with negative impacts on the welfare of the citizens. It is estimated that between 75 million and 250 million people of Africa may be exposed to increased stress such as scarcity of water, environmental stress and food security stress, due to climate change by 2022 (IPCC, 2014). Due to climate change, the areas suitable for agriculture, the length of farming seasons and yield potentials are expected to decrease. Climate change has been confirmed following release of the by 4th IPCC Assessment report, Africa will be worst hit by the effect of climate change where Nigeria is part of. As a result of this Nigeria is vulnerable to the effects of climate change. Available evidence show that climate change will be global, likewise its impact, but the biting effects will be felt more by the developing countries, especially those in Africa due to their low level of coping capabilities (Nwafor, 2007; Jagtap, 2007). Researchers have shown that Nigeria is already plagued with ecological problems which have been linked to ongoing climate change (Adefolalu, 2007; Ikhili, 2007). Recent evidence indicates that the world has already warmed by 0.80C since pre-industrial era and under a Business as Usual (BAU) scenario, global mean temperature could reach about 20C by 2060 (PACJA, 2009). Climate change and global warming if left unchecked will cause adverse effects on livelihoods in Nigeria such as forestry, crop production, livestock production and fisheries because the rainfall regimes and patterns will be altered, floods which devastate farmlands will occur. The intensity and seasonal nature of the rains cause drastic changes in rainfall patterns with rising temperatures introduce unfavourable growing conditions. Climate change modifies growing seasons which could subsequently reduce productivity. Elevation of average annual temperatures causes the warming of the atmosphere known as global warming Increase in temperate and humidity would cause increase in pests and diseases. Natural disasters like sea level rise, floods, drought and storms surges are anticipated which may cause great havoc to lives and properties. In areas such as the Niger Delta and the North-east, these sequences of events are already unfolding on a limited scale (Nebedum and Nnaemeka, 2016). The above evidences confirm that the effects of climate change have already been felt in many parts of the country.
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4.0. Impacts of Climate Change in Nigeria Nigeria is indeed at risk to the effect of climate change in diverse spheres. Raheem, (2011) notes that Nigeria is particularly vulnerable to the impact of climate change on many fronts considering its geography, climate, vegetation, soils, economic structure, population and settlement, energy demands and agricultural activities. Watson et al., (1998) suggest that vulnerability is highest where there is an utmost sensitivity to climate change as well as the least adaptability. According to the OECD report in 2008, many of the poorest countries in the world, in Africa and South Asia, are likely to be hardest hit by climate change. This could be attributed to the prevailing less-adaptive capacity, which cut across several sectors including policy, government, and infrastructure. Nigeria's vulnerability to the impact of climate change has been documented in diverse sectors of the country (Oladipo, 2010). Although Nigeria has a strong economy relative to other countries in Sub-Saharan Africa, a significant part of its population and economy are linked to activities that are climate sensitive, such as gas flaring, rain- fed agriculture, and inefficient transport system amongst others. Considering the low-level adaptive capacities and various negative impacts of climate change that have been recorded, scholars are in agreement that poorer nations are much more vulnerable to climate change than economically advanced countries. This is due to poor countries dependence on rain-fed agriculture, scarcity of resources needed to pursue adaptation measures (Fischer, et al., 2005; Okolie, et al., 2012). Available data has shown that the "Earth's average surface temperature has risen by 0.75 0C (1.33 0F) since the 1880s". The ecological effect of climate change in Nigeria is seen in the disturbing patterns of rainfall, a decrease in some region and an increase in other regions and sea level rise. Existing indicators are also present in Nigeria and heralding the potentials of further damage. The fluctuating weather patterns, sea level rise, disturbing seasonal cycles, and atmospheric conditions, as well as water supply, are some of such indicators (Odjugo, 2005; Chindo and Nyelong, 2004; NEST, 2003). Already existing data have shown that there has been a change in the pattern of rainfall over the past decades, which is an indication of a rapid change in the climate (Oladipo, 1995; Anyadike, 2009) Anyadike (2009) suggests that the impact of climate change on human environment is evident in the changes in the inception and completion of rainfall, melting of ice caps which is caused by rising in sea level, extreme patterns in distribution of rainfall (extreme or deficient), which leads to flooding and increased intense atmospheric disturbances such as thunderstorms.
4.1. Environmental impact As earlier noted, coastal and desert-prone regions experiences climate change-related challenges more than other areas. Coastal towns are usually populated and crowded. The sea level rise could disrupt social and economic activities and physically endanger teaming inhabitants of the area. According to Oladipo (2010), sea level increase of 0.5-cm for Nigeria coastlines is been predicted, and this will affect the environmental and socioeconomic activities going on in those regions. The surge in rainfall in the coastal cities of Warri, Port Harcourt and Calabar has been the reason for the increasing floods, ravaging those areas. In some coastal localities in the Niger Delta region, settlements have been uprooted while some oil wells have been lost to the ocean due to erosion (Ogundebi, 2004; Ikhile, 2007; Nwafor, 2007; Umoh, 2007; Odjugo, 2010). In addition to this, available report highlights that sea-level rise and repeated ocean surges can worsen coastal erosion problems that are currently a serious challenge in the coastal areas (NEST, 2004; Uyigue, et al., 2007). More so, the economy of the nation is hugely dependent upon the economic resources that are located in the coastal regions. A very substantial land mass of Nigeria is already prone to desertification. In some northern parts of Nigeria "expanding desertification, which refers to the degradation of land productivity in dry land areas has caused 200 villages to disappear"(Werz and Conley, 2012). The Savannah area in Nigeria is highly susceptible to a continuous reduction in rainfall, thus, it could lead to widespread degradation of the habitat. It has been projected that the amount of rainfall in the savannah is likely to decrease (FME, 2011; Ajibola, 2014). The decrease in output from the upsurge of desertification will indeed perpetuate our susceptibility to climate change and thus deepen the hitches of climate change, especially in a scenario where there is a heavy dependence on nature for productivity. Water, which is
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 an important resource in the country, used in hydro-power stations such as dams are affected by drought. Besides, while they serve as good water supply and are renewable energy they also emit greenhouse gases (Bryson et al., 2008). The mangroves that support the ecosystem of the coastlines are disappearing. The implication is that there is a surge in the salinization of upland groundwater.
4.2. Health impact Climate change impacts on health in many ways. Africa is particularly known for its vulnerability to many climate-sensitive diseases such as malaria, tuberculosis, and diarrhea (Thomson, et al., 2004; Guernier, et al., 2004). The health impacts of climate change include heat-related illnesses, extreme weather-related injuries, the spread of infectious diseases such as water- and food-borne diseases, upsurge of respiratory disorders, vector-borne diseases and, stress-related and mental health disorders (Costello, et al., 2009). Mshelia (2005) and Adefolalu (2007) claim that climate change has affected agriculture and health in Nigeria. A swing in the cycle of rainfall and weather conditions will promote the prevalence of some diseases such as malaria, due to the increased incidence of pools and standing waters. Floods are also increasing in frequency and intensity in the region and may contaminate freshwater supplies, heighten the risk of water-borne diseases and create breeding grounds for disease-carrying insects such as mosquitoes. Climate change is likely to trigger the prevalence of diarrhea, epidemics like cholera and other vector-borne diseases. It also impacts the environmental basis of good health including clean air. Toxicity is common and caused by air pollution via the burning of fossil fuels from generators and transportation industries. In relation to geographical distribution, organisms that ordinarily do not survive in colder regions are fast moving to those regions, presuming their survival and endangering humanity in those areas. Rising temperatures may mean that a vector becomes sustainable at different latitudes and altitudes, exposing new populations to the disease. Warmer oceans may result in outbreaks of diseases. More so, warmer temperatures are associated with increased allergy-related diseases like asthma. Changes in climate are likely to lengthen the transmission seasons of important vector-borne diseases and alter their geographic range (Mshelia, 2005).
4.3. Economic impact The sensitivity of climate change in Nigeria's agricultural productivity is quite imminent. Agriculture in Nigeria has already been altered by climate change (Mshelia, 2005; Adefolalu, 2007). For centuries, agriculture has been a source of income and livelihood to individuals and communities. Climatic changes, however, threatens this means of livelihood and nutrition of the nation. It also threatens food security and programmes aimed at the elimination of poverty (Onyenechere and Igbozurike, 2008). Agricultural practice in the country is predominantly rain-fed and therefore particularly vulnerable to the impacts of climate change. The unreliability in the onset of rainfall in recent times, which determines the inception of agro-business, due to fluctuations in the pattern of rainfall often leads to a minimal harvest. Since Nigerians are largely involved in the rain-fed agricultural system, climatic changes will adversely impact the amount and timing of rainfall in subsequent times. Invariably, climate change is likely to decrease the production of the arid regions as a result of desertification. Ayuba et al., (2007) reveals that continuous loss of forest cover and biodiversity in Nigeria is linked to climate change. Onyenechere (2011) suggests that coastal regions that rely heavily on fishing may also be hit as climate change upsets ocean currents and fisheries. Climate change equally increases the incidence of pests and diseases that attack and decimate forest trees. The incidence of pest and diseases of crops are also heightened in the arid zones as a result of climate change. Climate change is likely to create pressure on food supplies thereby, heightening malnutrition. Generally, the effect of climate variations on agro-business may have an enormous impact on food production, revenue, and employment. Deviations in the strength and pattern of storms are dynamics that may have an impact and increase the risk of flooding. Flooding plays a number of roles in affecting the lives and activities of the
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5.0. Measures to Reduce High Risk of Climate Change The main challenge, the world over, is to keep climate change from becoming a catastrophe. Generally, there are two broad major approaches to dealing with climate change-related challenges; these are mitigation (which means to tone down, diminish or lessen human activities that may aggravate the increase of greenhouse emissions) and adaptation (which refers to the modification and changes to reduce the impact of climatic variations in the environment). While mitigation seeks to limit climate change by reducing climate change through the reduction of the emissions of greenhouse gases and by enhancing ‘sink’ opportunities, adaptation aims to alleviate the adverse impacts through a wide-range of system-specific actions. Overcoming the development challenge of climate change requires that more extensive adaptation and mitigation measures that are currently being applied are necessary to reduce vulnerability to future climate change. Future vulnerability will depend not only on the degree of climate change but also on the development “pathway” taken, as well as capacity put in place to cope with the climate change stress. Mitigating greenhouse gas emissions and enhancing the adaptive capacity to increase resilience can accelerate the pace of progress towards sustainable development. Adapting to climate change involves reducing exposure and sensitivity, and increasing adaptive capacity to build a climate- resilient society. This will be a society that is able to withstand or recover fast from difficult conditions caused by the adverse effects of climate change, including climate-related hazards and disasters (Ifeanyi-Obi et al., 2012). Climate change is a threat to sustainable development. Nonetheless, there are many opportunities to link mitigation, adaptation and the pursuit of other societal objectives through integrated responses (high confidence). Successful implementation relies on relevant tools, suitable governance structures and an enhanced capacity to respond (medium confidence). Effective adaptation and mitigation responses will depend on policies and measures across multiple scales: international, regional, national and sub-national. Policies across all scales supporting technology development, diffusion, and transfer, as well as finance for responses to climate change, can complement and enhance the effectiveness of policies that directly promote adaptation and mitigation. Adaptation and mitigation are complementary strategies for reducing and managing the risks of climate change. Substantial emissions reductions over the next few decades can reduce climate risks in the 21st century and beyond, increase prospects for effective adaptation, reduce the costs and challenges of mitigation in the longer term and contribute to climate-resilient pathways for sustainable development (Olaniyi, et al., 2014; Chuku and Asiegbu, 2010; Nebedum and Nnaemeka, 2016).
5.1. Mitigation This is a means through which the causation of climate change can be stopped. It is about reducing human activities that intensifies the emission of the gases which perpetuates global warming. According to IPCC (2001), the mitigation options include a reduction in the burning of fossil fuels and reduction of greenhouse gases; reduction of deforestation, an increase in reforestation and
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 268 - 291 afforestation; modification of agricultural practices to reduce the emission of greenhouse gases and build up soil carbon. There still exist other routes of mitigation such as the use of GIS and remote sensing in monitoring the environment. Atilola (2012) suggests that "another mitigation option which is geoengineering to reverse the effect of global warming by creating cooling effects which will offset greenhouse heating and conceiving the development of technology for cleaning the greenhouse gases from the atmosphere". Sharma and Kumar (1998) and Kates (2000) among others, state that greater consideration has been given to climate change mitigation than to adaptation measures. The multidimensional mitigation methodology is aimed at achieving a low-carbon society. OECD, (2008) asserts that ''Mitigation is achieved by reducing both the energy intensity of GDP and the carbon intensity of energy used''. A number of researches have been made by organizations and individuals on best mitigation practices and policies. According to IPCC (2007), ''some mitigation practices that can be employed are use of renewable heat and power (hydropower, solar, wind, bioenergy), non-motorised transport, for example, walking and cycling, improved cook stoves, alternative refrigeration fluids, deforestation, improved crop and grazing land management and so on, other measures that can be taken up as mitigation practices includes: waste recycling and reforestation. Many adaptations and mitigation options can help address climate change, but no single option is sufficient by itself. Effective implementation depends on policies and cooperation at all scales and can be enhanced through integrated responses that link adaptation and mitigation with other societal objectives (Onyenechere, 2010). Adaptation and mitigation responses are underpinned by common enabling factors. These include effective institutions and governance, innovation and investments in environmentally sound technologies and infrastructure, sustainable livelihoods and behavioural and lifestyle choices. Mitigation options are available in every major sector. Mitigation can be more cost- effective if using an integrated approach that combines measures to reduce energy use and the greenhouse gas intensity of end-use sectors, decarbonize energy supply, reduce net emissions and enhance carbon sinks in land-based sectors (Ogbo and Onyedinma (2012). Agriculture is a significant contributor to greenhouse gases, particularly in a developing country like Nigeria. It is estimated that about 10-12 % of total anthropogenic emissions of greenhouse gases are directly generated in agriculture (mostly nitrous oxide from fertilized soils and methane from livestock). If indirect emissions from the fertilizer industry and emissions from deforestation and land conversion are added, the total contribution of the agriculture sector is increased to about 26-35 %. A variety of options for mitigation (reduction of greenhouse gases) exist in agriculture. They fall into three broad categories: i. Reducing emissions of methane, carbon dioxide, and nitrous oxide through efficient management of the flows of these gases in agricultural ecosystems for example, through managing livestock to make more efficient use of feed (Atitola, 2012; Ifeanyi-Obi et al., 2012). ii. Enhancing the removals of carbon dioxide through improved management of forestry and agro ecosystems for enhanced carbon recovery and carbon storage. Afforestation and reforestation are measures that can be taken to enhance biological carbon sequestration. Nigeria can focus on the potential to use forests as one of the strategies towards becoming carbon-free (Adejuwon, 2016). iii. Avoiding emissions using crops and residues from agricultural lands as a source of fuel, either directly or after conversion to fuels such as ethanol or diesel. Greenhouse gases emissions, notably carbon dioxide, can also be avoided by agricultural management practices that forestall the cultivations of new lands now under forest, grassland or other non-agricultural vegetation (Apata, et al., 2009; Ozor, 2009; Ifeanyi-Obi et al., 2012).
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5.2. Adaptation Adaptation is simply an attempt to limit susceptibility to climate change impact. According to Ogbo and Onyedinma (2012), "adaptation involves the action that people take in response to, or in anticipation of projected or actual changes in climate to reduce adverse impacts or take advantage of the opportunities posed by climate change". It is a method of dealing with the symptoms to reduce the vulnerability of ecosystems to climate change and not the underlying causative factors. Basically, adaptation is a means by which individuals lessen the negative effect of climate variations on their wellbeing. It helps to shrink the susceptibility of ecosystems to the impact of climate change. According to Onyenechere (2010), "adaptation to climate change is a response to climate change that seeks to reduce the vulnerability of natural and human systems to climate change effects". The need to adapt to the variability of the climate is a basic one. It is important that states and individuals engage new methods for living a positive impact on the climate. The adoption of adaptation strategies is most important for developing countries, including Nigeria, as they suffer the impact of climatic variations that has serious implications for their socio-economic development. Slobodan (2012) has also suggested that adaptive capacity is closely linked to social and economic development. Adaptation options exist in all sectors, but their context for implementation and potential to reduce climate-related risks differs across sectors and regions. Some adaptation responses involve significant co-benefits, synergies, and trade-offs. Increasing climate change will increase the challenges for many adaptation options (IPCC, 2007).
5.3. Adaptation strategies for Nigeria Adaptation strategies are steps that can be taken to cushion or decline the effect of active or presumed climate fluctuations in the ecosystem. Climate change adaptation is basically a process that involved ecological, social and economic systems adjustment to likely and actual climatic stimulus and their respective impact (Nzeadibe et al., 2011). Nigeria may need to employ more of adaptation strategies because, like other developing nations, the country is not largely involved in climate threatening industrialization when compared with most developed countries. Furthermore, the country is not yet technologically advanced to engage the needed infrastructure necessary for many forms of mitigation practices. The harmful effect of climate change can be reduced if the necessary adaptation measures are employed (Ogbo and Onyedinma, 2012).
(i) Health care Due to the increased temperature of the earth, water-borne diseases such as malaria have increased. Rural communities in Nigeria are hugely susceptible to cholera outbreaks. It has been therefore suggested that rainwater harvesting tanks should be encouraged in homes instead of salinized groundwater which may have been subjected to contamination. Health surveillance systems should be encouraged by the government and local communities. Technologies that reduce our exposure to extreme heat should be adopted. The efficient health care system should be pursued and the primary health care system should be strengthened, restructured and expanded local communities. Improvement in housing conditions for the masses is also needed (Nzeadibe et al., 2011)..
(ii) Desertification For the arid zones where desertification threatens, an innovative project like the great green wall which is on-going is encouraged. Improved species that have the adaptive capacity should be made accessible to farmers for planting. Soil and water conservation technologies should be pursued. The pit planting technique will be of immense benefit for collecting surface runoff water and making them available for agriculture. The use of irrigation should be improved and widely promoted in the arid zones (Odjugo, 2008).
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(iii) Flood control The construction of efficient drainages that create an effective pathway for the movement of flood in erosion-prone areas in local communities will be of immense help. The erection of canals and guardrails is required in both local and urban communities. It will also help to reduce pollution, waterborne disease and vectors that breed and incubates in standing waters. Flood control mechanisms are required to salvage coastal communities and crops from torrents and over flooding. More so, the construction of a sea wall would be an additional advantage in the management of flood in flood-prone areas (Nwafor, 2007).
(iv) Human settlement Some urban and coastal regions have been displaced by the upsurge of floods in those areas. The employment of spatial planning an adaptation strategy in the planning of cities and urban areas is quite crucial. The flooding of local communities in some parts of the Niger Delta region caused a mass relocation farther into the inland areas in temporal and permanent terms, which contributes to the over-population of the area (Kyuba, 2012). The climate change adaptation demands infrastructure like protective barriers which helps to counter a rise in sea help in the management and retention of water. Efficient building strategies should be employed by construction firms to step up with the challenge. Innovative flood control and monitoring of drought are also encouraged. Efforts should be made by the government to construct cities in higher plains rather than closer to the floodplains which are more vulnerable (Kyuba, 2012).. A good and fitting water management approach should be employed Avenues for water provision in the arid regions should be explored. Best practices on water management via the utilization of relevant technology can be used to conserve soil moisture. Efforts should be made by the government and relevant stakeholders to ensure the desalination of groundwater sources which is leading to the decline of life. Appropriate desalination technology should be engaged. Increased management of water supply and security of the coastal zones is also needed. Relevant laws and policies should be enacted by regulatory agencies to promote the safety of these coastal regions.
(v) Meteorology and weather monitoring techniques Additional efforts should be made by the meteorological agencies on how to effectively predict changing weather conditions and zones to equip the government and the people with relevant information that is needed to escape, prevent and reduce losses that may result from climate change. Efforts should be made to engage weather monitoring technologies that give early warning signs and are better able to predict envisaged risk of weather variations. Capacities building of relevant stakeholders and institutions to better adapt to climate change at the national and local levels is essential (Atitola, 2010). Adaptation can be both autonomous and planned. Autonomous adaptation is the ongoing implementation of existing knowledge and technology in response to the changes in climate experienced, while planned adaptation is the increase in adaptive capacity by mobilizing institutions and policies to establish or strengthen conditions that are favourable to effective adaptation and investment in new technologies and infrastructure. Various sectors will have their adaption measures.
5.4. Best practice principles Whatever mitigation and adaptation measures are being considered for adoption or implementation, they must be guided by good practice principles. Good practices are actions that are effective in meeting established goals and deemed to be appropriate and acceptable by a broad range of stakeholders. In climate change response, these may include:
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(i) Building local capacity The most important variable that determines whether the State is able to address the challenge of climate change and achieve sustainable development is human and institutional capacity and appropriate regulatory and legal framework. Projects designed to mitigate or adapt to climate change in the State should, therefore, ensure that local capacity is built during their implementation. In this regard, mitigation and adaptation projects must integrate training programmes into core project activities and measures taken to assure that built human capacity is maintained and replicated beyond the project’s lifetime (Osman-Elasha, 2010; Ogbo and Onyedinma, 2012).
(ii) Knowledge building The complex and dynamic nature of climate change makes it imperative for the need to undertake research into its physical and socio-economic basis for an improved national understanding of the global dimensions of climate change and to be able to communicate the issues to the general populace through a coordinated advocacy and awareness creation strategy. Empowering the populace through improved knowledge about the climate change challenge will put them in a better position to identify, plan and implement adaptive measures that will enhance their resilience. In this regard, the designing of climate change projects must be built upon or applied to the findings of specific research projects and/or vulnerability studies. Also, there is a need to ensure that the projects actively contribute to national and international understanding of a specific topic or area of research (Osman-Elasha, 2010; Ogbo and Onyedinma, 2012).
(iii) Integrated programme approach Climate change is a complex multi-sectoral environmental and development challenge. Fragmentation of issues across multiple policy platforms and narrowly bounded institutional mandates encourages unilateral, single-sector responses, discourages innovative leadership and inhibits the development of policy actions informed by the full complexity of climate change challenges. Thus, sectoral and small- scale uncoordinated interventions will not adequately address the challenge of climate change in the State for impact. A multi-sectoral national programme, financed and implemented in a coherent and integrated manner over a period of time is imperative for an effective state response to the challenge of climate change, within a national framework. What is required is a state programme of action (minimum 10 years’ timeframe), developed through stakeholders’ consultations, properly financed and implemented in an integrated manner through various institutions, but led by the Ministry of Environment, particularly the Climate Change Unit (IPCC, 2007; IPCC, 2014).
(iv) Transferable to other context or regions Projects designed to mitigate or adapt to climate change must ensure that their activities can be transferred beyond the specific contexts in which they were implemented. Particular project measures, activities or concepts should be easily applied in another context or region (IPCC, 2007).
(v) Community participation and inclusiveness Climate change management in Nigeria requires a shift to an integrated approach that advances change responses which are closely intertwined with development choices and driven by multi- stakeholder identification (up to community level) and implementation of priority mitigation and adaptation measures. In this regard, the State Ministry of Environment, particularly the Climate Change Unit, will have to lead a process of collaborating with relevant MDAs to formulate and mobilize resources for the implementation of sectoral programmes and projects, particularly in climate-sensitive sectors such as agriculture, water, health, energy, infrastructure and so on. In other words, projects designed to mitigate or adapt to climate change in the State must result from
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consultation with local communities in the formulation, implementation, and decision-making process, with the incorporation of gender issues (IPCC, 2007; IPCC, 2014).
(vi) Political ownership, collaboration, and approval Projects designed to mitigate or adapt to climate change need to secure high-level political support for their activities and be aligned with wider development agendas to ensure success. Thus, the Ministry of Environment will need the support of the high-level governance in the State for the establishment of an enabling policy, legal and regulatory framework for the state’s response to climate change in order to be able to develop and implement a comprehensive mitigation and adaptation programme measures (IPCC, 2007; IPCC, 2014).
(vii) Financial sustainability Financing for climate change mitigation and adaptation activities will be costly if the State is to fully address the challenge of climate change. Annual budget allocations will be extremely inadequate to enable states implement an integrated response to the challenge of climate change. What is required is a pool of resources into which state and external funds can be made available on a sustainable basis to upscale state response for effectiveness. This will ensure that projects designed to mitigate or adapt to climate change in the state secure financing for sustaining and/or expanding the project’s impacts beyond the initial project lifetime (Ajibola, 2014).
(viii) Achieving co-benefits and balancing the trade-off Projects designed to mitigate or adapt to climate change must take into consideration the costs and benefits external to the project such as employment, environment, health, poverty levels and food security. Projects must aim to maximize external co-benefits from project activities and avoid/minimize external costs and damages (Ajibola, 2014).
(ix) Monitoring and evaluation Projects designed to mitigate or adapt to climate change in the State must demonstrate their impacts in terms of achieving the project objectives, outcomes, and outputs, as well as developing indicators to measure success and effectiveness. In other words, good mitigation and adaptation projects must have an explicit logical framework with appropriate monitoring and evaluation mechanisms (Ajibola, 2014).
(x) Improving energy efficiency This includes the use of efficient production technologies and a behavioural change in energy use. Renewable energy use is therefore the best option because of its efficiency (Uyigue et al., 2010).
(xi) Reducing vehicle emissions Through a number of policies that encourage cleaner fuel use and promotion of mass transit schemes, including bus rapid transit (BRT) coupled with the integration of non-motorized transport in urban areas while shifting freight from road to rail and water transport (Osman-Elasha, 2010; Ogbo and Onyedinma, 2012).
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(xii) Reducing greenhouse gases emissions in agriculture Through the use of improved technologies, including (i) applying modern irrigation and water management practices; (ii) applying fertilizers tailored to the condition of the soil; (iii) strengthening the management of animal waste, the treatment of solid and liquid waste, and using methane emissions to produce renewable energy (Adejuwon, 2006, Ajibola, 2014).
(xiii) Managing waste to reduce methane emissions This includes conversion of solid waste into compost and organic fertilizer; recovering methane from landfills, recovering energy during waste incineration and controlling wastewater treatment (Nzeadibe et al., 2010).
(xiv) Response to climate change as a shared responsibility This means that every individual, firm, and government has a responsibility to protect the environment to make it more climate-friendly (Oladipo, 2010).
(xv) Promoting carbon-neutral lifestyles Carbon-neutral lifestyles among individuals must be promoted and promoting carbon-neutral products or services for government support (Osman-Elasha, 2010; Ogbo and Onyedinma, 2012).
(xvi) Reversing deforestation
Deforestation accounts for between 20 and 25% of global carbon dioxide Agroforestry systems; in particular, contribute simultaneously to buffering farmers against climate variability and changing climates, and to reducing atmospheric loads of greenhouse gases. Thus, reversing deforestation, through appropriate policies and programmes, is critical for climate change mitigation; it is also a relatively low-cost strategy (Adejuwon, 2006).
6.0. Conclusion and Policy Recommendations 6.1. Conclusion The paper examined the impacts of climate change on Nigeria ecosystems. The impact of climate change on ecosystems is extensive. Climate change is a driving force that can weaken sustainable economic and environmental development; and inhibit the realization of the millennium development goals. Some of the characteristic features of these climatic alterations are seen in the changes in temperature, rainfall, and precipitation, global warming, desertification, drought, increased melting ice caps and glaciers, which causes sea level rise and in turn flooding. These challenges are already evident in Nigeria. The country, therefore, needs to increase and improve on its adaptation strategies to forestall further degradation and associated challenges on the human and national economy. Integration and mainstreaming of various adaptive measures outlined above need to be consciously and effectively drawn into the national plan and pursued vigorously in order to reduce the negative impact of climate change and ensure sustainable development of Nigeria. The government and people of Nigeria should take up the challenge and seek cooperation and collaboration with international agencies in order to reverse these undesirable outcomes. In the final analysis, stopping climate change is up to us. Our actions today will determine the climate tomorrow. By choosing to take action now will limit future damage. Government, of course, needs the active support of individuals, non- governmental organizations and the private sector operators to enhance the state institutional and financial capacities imperative to effectively address the challenge of climate change in the country. Together the battle against the impact of climate change can be won.
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6.2. Policy recommendations Nigeria is highly vulnerable to the impacts of climate change and must as a matter of urgency take drastic steps to reduce its vulnerability, build its resilience and its adaptive capacity. Henceforth, in order to deal with the adverse impact of climate change on the Nigerian ecosystems that affect the economy and society, certain mitigation and adaptation strategies have to be employed. The following recommendations are proposed: i. There is a need for improved computer models of climate change over Nigeria which must include downscaling global circulation models using appropriate methods for understanding economic and social impacts, vulnerabilities and adaptation requirements. ii. Sufficient attention must be paid to the impacts of climate change in Nigeria with a view to formulating adaptive strategies, resilience, and coping mechanisms. iii. Renewable energy sources such as solar energy, hydro-power energy, wind energy, geothermal energy, etc. should be adopted and encouraged as alternatives to fossil fuel. iv. Oil spillage and gas flaring in the coastal regions should be checked to help enhance carbon sink and depletion of the ozone layer. v. The use of climate forecasting should be increased to reduce production risk. vi. Encouraging the use of low-cost solar energy cookers instead of wood-burning devices which cause deforestation. vii. Mass transport system including rail transport should be developed to reduce the proliferation of cars and motorcycles on our roads. viii. An extensive study for an up-to-date greenhouse gas inventory, projection, mitigation, and adaptation strategies should be encouraged. ix. The agricultural and research institutions should commence research into crops that are heat and drought resistance. x. Building and developing plans for both urban and rural area development for proper settlement so as to reduce the vulnerability of the environment. xi. Relocation of settlers in areas vulnerable to sea level rise and flooding, protection of natural barriers, the building of sea walls and dune reinforcement. xii. Terrestrial and marine ecosystems that act as carbon sink reservoir to greenhouse gases should be protected and sustained by reducing bush burning and encourage afforestation. xiii. The Ministry of Environment should check the erosion problem by the construction of dykes and storm surge barriers against sea level. xiv. Trans-boundary water resources management, particularly across the West African sub- region should be initiated. xv. The existing government agencies and commissions saddled with the responsibilities for the strategic planning and coordination of national policies related to climate variability and climate change in Nigeria should be sufficiently strengthened to achieve the desired goals and objectives. xvi. Improved understanding of the key drivers of climate variability and climate change in Nigeria.Consistent public engagement on climate change issues, to ensure that people appreciate the risks, understand policy decisions and have a voice in how they are implemented.
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xvii. To enhance public access to relevant information (e.g. weather data) that can be used effectively to make informed decisions at different time periods.
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Cite this article as:
Ikumbur B. and Iornumbe S., 2019. The Impacts of Climate Change on Nigerian Ecosystems: A Review. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 268-291. https://doi.org/10.36263/nijest.2019.02.0128
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Nigerian Journal of Environmental Sciences and Technology (NIJEST)
www.nijest.com
ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 292 - 297
Macroinvertebrates’ Pollution Tolerance Index in Calabar River, Cross River State, Nigeria
Bate G.B.1,* and Sam–Uket N.O.2 1Environmental Science Department, Federal University Dutse, Jigawa state, Nigeria 2Animal and Environmental Biology Department, Cross River University of Technology, Calabar, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0154
ABSTRACT
A study was undertaken to determine the macroinvertebrates pollution tolerance index (PTI) in Calabar River, Cross River state, Nigeria. Five sampling stations were chosen along the river course: Ikot Okon Abasi, Tinapa, Unicem, Marina resort and Nsidung beach which were labeled stations 1, 2, 3, 4 and 5 respectively. Physico-chemical parameters; surface water temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), total dissolved solids (TDS) and total suspended solids (TSS) were measured using their respective meters while macroinvertebrates were sampled using a Van Veen grab, stained with Rose Bengal solution and identified under microscope. Macroinvertebrates pollution tolerance index was obtained using online software designed by Northern Kentucky Univeristy and Leaf Pack Network Biotic and Water Quality Calculator. The results obtained for physicochemical parameters showed the highest temperature as 29.90C in station five while the lowest was 26.40C in station one. pH was highest (6.60) in station five and lowest (5.52) in station one. DO was highest (4.4mg/L) in station four and lowest (3.0 mg/L) in station five while BOD was highest (3.2 mg/L) in station three and lowest (0.3 mg/L) in station one. An average total of 5366 macroinvertebrate individuals were encountered belonging to nine families and eleven species. Tubificidae had the lowest occurrence with 18 individuals which made up 0.3% of the total macroinvertebrates while Penaeidae had the highest occurrence with 2,455 individuals constituting 45.8% of the total count. Pollution tolerance index was highest (21) in station five and lowest (9) in station four with the water quality being generally poor. Hence, it is suggested that anthropogenic activities should be regulated and continuous monitoring of the river course should be carried out.
Keywords: Macro-invertebrates, Pollution tolerance index, Calabar River, Physicochemical parameters, Sensitivity factor, Abundance code.
1.0. Introduction
Macroinvertebrates are organisms without backbones, which are visible to the eye without the aid of a hand lens or microscope. They consist of the immature stages of many flies, beetles (adult and immature), mayflies, caddis flies, stoneflies, dragonflies, aquatic worms, snails, and numerous other organisms (Idowu and Ugwumba, 2005). They serve as useful bioindicators of aquatic health status due to their high functional and taxonomic diversity, ubiquity, tolerance of wide environmental gradients, rapid, and often predictable response to environmental changes of natural and anthropogenic origin. They are generally sessile or sedentary, have relatively long life spans and are thus indicative of changing water qualities by reflecting cumulative effects of the present and past conditions of short and long term environmental stressors (Meyer et al., 2007; Olomukoro and Dirisu, 2014). The use of macroinvertebrates in monitoring the overall health status of an environment is more efficient than using chemical and microbiological data, which give short-term fluctuations while macroinvertebrates give a better representation of the environmental quality (George et. al., 2009).
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Certain taxa or groups of organisms are known to be more or less tolerant of polluted conditions of an environment and the presence or absence of these organisms can be used to evaluate the level of pollution or human disturbance of that environment and is assigned a value used in calculating the pollution tolerance index (PTI). The use of pollution tolerance index (PTI) as a method of measuring the overall health status of aquatic bodies through the use of macro-invertebrates remains the most reliable and effective method (Andem et. al., 2015). Macroinvertebrates which are used in aquatic pollution studies include: Mayflies (Ephemeroptera), caddisflies (Trichoptera), stoneflies (Plecoptera), beetles (Coleoptera), crayfish and amphipods (Crustaceans), aquatic snails (Mollusca), biting midges (Chironomids) and leeches (Hirudinea) among others (Oku et al., 2014). Several studies reported signs of pollution from untreated industrial effluents, municipal wastewater, run-off from agricultural chemical fertilizers and pesticides, as well as spillage of petroleum products in Calabar River (Okoroafor et al., 2013; Reuben et al., 2016). This study is undertaken to evaluate the pollution tolerance index of macroinvertebrates in Calabar River, Nigeria.
2.0. Materials and Methods 2.1. Study area The Calabar River in Cross River State, Nigeria is located between latitude 040 55’ 55” to 050 02’ 50”N and longitude 0080 16’ 35” to 0080 18’ 13.8” E. It flows from the north through the city of Calabar, joining the larger Cross River to the south (Figure 1). Five sampling stations with an average distance of 4.5 km from one another were chosen along the river course: Ikot Okon Abasi, Tinapa, Unicem, Marina resort and Nsidung beach which were labeled stations 1, 2, 3, 4 and 5 respectively. This choice was from upstream downwards at points where human activities such as fishing, tourism, bathing and discharge of wastes take place.
Figure 1: Map of study area showing Calabar River and sampling stations
2.2. Physico-chemical parameters measurement The physico-chemical parameters measured are; surface water temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), total dissolved solids (TDS) and total suspended solids (TSS) were measured using their respective meters during the period of this study.
2.3. Macroinvertebrates collection A Van Veen grab was used for each sampling, 3 or 4 hauls were made by sending the grab down into the bottom of the river at random locations. The sediment collected were poured into a labeled white plastic can of about 20 cm3 in volume and taken to the laboratory for analysis. In the laboratory, the sediment was passed through three sieves of 2 mm, 1 mm and 0.5 mm mesh sizes to collect the benthos. The benthos were poured into a white enamel tray, stained with Rose Bengal solution to
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 292 - 297 highlight the hidden features and sorted using forceps. They were sorted out into different taxa and preserved in 4% formalin. They were then identified under a stereoscope microscope using identification guides of Pennak (1978) and EPA (1998) and counted. In case of stony substrate, stones were lifted to remove the animals that are hidden in between and a sweep net of mesh size 0.5 – 1 mm was used to collect flying macro-invertebrates.
2.4. Pollution Tolerance Index Pollution Tolerance Index (PTI) of macroinvertebrates from the five sampling stations in Calabar River was obtained using online software designed by Northern Kentucky Univeristy and Leaf Pack Network Biotic and Water Quality Calculator. Macroinvertebrate families were assigned into three groups, namely pollution intolerant, moderately tolerant, and tolerant. Each category was then scored with a sensitivity factor; a factor of 3 was given to the pollution sensitive (intolerant) group, a factor of 2 to the moderately tolerant group, and a factor of 1 to the pollution tolerant group. The total number of each macroinvertebrate family was assigned an abundance code viz: R (rare) = 1–9 organisms, C (common) = 10–99 organisms and D (dominant) = ≥100 organisms. Pollution tolerance index is the sum of abundance codes multiplied by the indicated sensitivity factors. Values obtained were thereafter compared with established standard values in accordance with George et al., (2017). A PTI value of 22 and above is rated excellent, 16–21 is good, 11–15 is fair while 10 or less is poor.
3.0. Results and Discussion 3.1. Physico–chemical parameters The highest temperature was 29.90C in station five, the lowest was 26.40C in station one. pH was also highest in station five and lowest in station one with 6.60 and 5.52 respectively while dissolved oxygen (DO) ranged from 3.0 to 4.4 mg/l. Biochemical oxygen demand (BOD) was lowest in station one and highest in station three. Mean measures of physico–chemical parameters during the study are shown in table one.
Table 1: Mean Physico–chemical parameters of Calabar River during the study
Parameters S1 S2 S3 S4 S5 NESREA Limits 0 Surface Water temperature ( C) 26.40 27.4 27.8 28.7 29.9 20-40 pH 5.52 5.67 5.97 6.22 6.60 6.0–9.0 Dissolved Oxygen (DO) mg/L 4.3 4.3 4.2 4.4 3.0 5.0 Biochemical Oxygen Demand (BOD5) mg/L 0.3 2.3 3.2 1.7 1.7 10 Total suspended solids (mg/L) 13.0 16.0 14.0 15.0 23.5 <10 Total Dissolved Solids (mg/L) 24.12 26.58 44.73 50.02 95.76 500
Physicochemical parameters give some clue about the overall pollution status of a water body as they are influenced by effluents from industries or domestic and agricultural wastes (Kidu et al., 2015). pH was generally low in all the sampling stations and meet the NESREA standard only in stations four and five. Dirisu et al. (2016) found out that decomposition of organic matter within a body of water, releases carbon dioxide, which combines with water to form carbonic acid. Also, the presence of some metals such as aluminum, copper and zinc as well as releasing acidifying pollutants into the atmosphere and water bodies bring about low pH. Dissolved oxygen (DO) was below the NESREA standard which indicates moderate pollution of the river while Biochemical oxygen demand (BOD) was within the standard during the study.
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3.2. Macroinvertebrates abundance, composition and distribution An average total of 5366 individual macroinvertebrates made up of nine families and eleven species were encountered in all the sampling stations from Calabar River during the study. The macroinvertebrate taxon with the lowest occurrence was Tubificidae which constitute 0.3% of the total population while Penaeidae was the highest with about 45.8%. Table two shows the macroinvertebrates composition and distribution during the study. Table 2: Composition and relative abundance of macroinvertebrates of Calabar River during the study
Family Species S1 (%) S2 (%) S3 (%) S4 (%) S5 (%) Total (%) Palaenomidae Macrobrachium vellenhovenii 87 (10.0) 102 (9.2) 87 (6.9) 68 (13.1) 140 (8.6) 484 (9.1) Penaeidae Peneaus notalis 295 (33.9) 472 (42.5) 701 (56.3) 146 (28.1) 841 (51.8) 2,455 ((45.8) Ocypodidae Uca tangeri 73 (8.4) 92 (8.3) 102 (8.2) 66 (12.7) 113 (6.9) 446 (8.3) Portunidae Callinates amnicola 58 (6.7) 64 (5.8) 59 (4.7) 43 (8.3) 90 (5.5) 314 (5.9) Limnephilidae Pycnopsyche species 12 (1.4) 10 (0.9) 5 (0.4) 13 (2.5) 4 (0.3) 44 (0.8) Libellulidae Crocothemis erythra 11(1.2) 8 (0.7) 7 (0.6) 10 (1.9) 3 (0.2) 39 (0.7) Neritidae Neritina afra 116 (13.3) 134 (12.1) 71 (5.7) 42 (8.1) 72 (4.4) 435 (8.1) Thiaridae Pachymelania fusca 89 (10.2) 95 (8.6) 105 (8.4) 61 (11.7) 127 (7.8) 477 (8.9) Melanoides tubercula 63 (7.2) 70 (6.3) 58 (4.7) 31 (5.9) 126 (7.8) 348 (6.5) Pachymalenia byronensis 57 (6.5) 59 (5.3) 49 (3.9) 35 (6.7) 106 (6.5) 306 (5.7) Tubificidae Tubifex tubifex 8 (0.9) 4 (0.4) 1 (0.1) 4 (0.7) 1 (0.1) 18 (0.3) Total No of Individuals 869 1110 1245 519 1623 5366
Macroinvertebrates composition, abundance and distribution as presented in table two are highly influenced by the pollution status of a water body. About 73% of the total macroinvertebrates encountered in this study were pollution tolerant. James et al. (2018) assessed Zambezi River water quality using macroinvertebrates population diversity and the measured pH, temperature, dissolved oxygen and conductivities suggested varying degrees of contamination where sixty-two macro- invertebrates made up of nine different species were recorded at two sampling points with 54.84% of them being highly pollution tolerant. Macroinvertebrates tend to move away from an unfavourable environment though they are slow or sessile in nature. Akindele and Liadi (2014) stated that these organisms reside in an aquatic system long enough to reflect the chronic effects of pollutants, and yet short enough to respond to relatively acute changes in water quality.
3.3. Pollution Tolerance Index Station four had the lowest pollution tolerance index of 9 while the highest was 21 in station five. Figure 2 shows the pollution tolerance indices of the sampling stations during the study.
25
20 21 20 15 15 10 10 9
5 Pollution Tolerance Index (PTI) Tolerance Pollution 0 S1 S2 S3 S4 S5 Sampling stations Figure 2: A Chart showing macroinvertebrate Pollution Tolerance Indices (PTIs) of Calabar River at various sampling stations
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Stations one and four had pollution tolerances indices (PTIs) of less than or equal to 10 (≤ 10) which is an indication of poor water quality. Station two had a PTI of 15 which is fair while stations three and five had good water qualities. This further confirms that the river has been contaminated especially at those sampling stations with low PTIs. Several cases of pollution such as heavy metals, petroleum hydrocarbons, pesticides and solid wastes were reported in Calabar River and its surrounding (Agbaji and Ejemot-Nwadiaro, 2019; Eddy et al., 2004; Nsikak and Joseph, 2009). Andem et al., (2015) found a similar result in their study on Ediba River, Cross River state, Nigeria where two out of the three sampling stations had PTIs < 10 which indicates very poor water quality. 4.0. Conclusion This study, from physicochemical parameters to the macroinvertebrates pollution tolerance index found out that Calabar River is moderately polluted. It is therefore recommended that anthropogenic activities should be regulated and continuous monitoring of the river course should be carried out.
References Agbaji D. A. and Ejemot-NwadiaroR. (2019). Solid Waste Management in Calabar Metropolis: Case Study of Calabar Urban Development Authority (2008 – 2017). Greener Journal of Medical Sciences, 9(1): 17-31. Akindele E. O. and Liadi A. A. (2014). Diversity and Response of Benthic Macroinvertebrates to Natural and Induced Environmental Stresses in Aiba Stream, Iwo, Southern Nigeria. West African Journal of Applied Ecology, 22(1):101–111. AndemA. B., Esenowo I. K. and Bassey D. O. (2015). Application of Biotic Indices and Pollution Tolerance Index in Assessing Macro-Invertebrate Assemblage of Ediba River, Cross River State, Nigeria. Journal of Environmental and Analytical Toxicology, 37: 1-9. Dipankar G., Jayanta K. B. and Juan C. S. (2017). Efficiency of Pollution Tolerance Index (PTI) of Macroinvertebrates in Detecting Aquatic Pollution in Oxbow Lake, India. Universitas Scientiarum, 22 (3): 237-261. Dirisu C. G., Mafiana M. O., Dirisu G. B. and Amodu R. (2016). Level of pH in Drinking Water of an Oil and Gas Producing Community and Perceived Biological and Health Implications. European Journal of Basic and Applied Sciences, 3(3): 53–60. Environmental Protection Agency (EPA) (1998). Lake and Reservoir Bioassessment and Biocriteria. Technical Guidance Document, 841: 98-107. Eddy N. O., Udo C. L. and Ukpong I. J. (2004). Heavy Metals in the Sediment of Cross River Estuary at Oron, South Eastern Nigeria. African Journal of Environmental Pollution and Health, 3(1): 6–10. George A. D., Abowei J. F. and Alfred-Ockiya J.F. (2009). The Distribution, Abundance and Seasonality of Benthic Macro-invertebrates in Okpoka Creek Sediment, Niger Delta, Nigeria. Resource Journal of Applied Science and Engineering Technology, 2: 11-18. George U., Inyang-Etor A. and Friday E. (2017). Biotic Index Assessment of Human Perturbations in Qua Iboe River Estuary Using Macro-Benthic Invertebrate as Indicator Organisms. Journal of American Science, 13(9): 98–107. Idowu, E. O. & Ugwumba, A. A. (2005). Physical, Chemical and Benthic Faunal Characteristics of a Southern Nigeria Reservoir. The Zoologist, 3:15-25. James A., Evans K. S. and Dietlinde N. N. (2018). Assessment of Zambezi River Water Quality using Macroinvertebrates Population Diversity. Journal of Fisheries and Aquatic Science, 13(1): 12–20.
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Kidu M., Abraha G., Amanual H. and Yirgaalem W. (2015). Assessment of Physico–chemical Parameters of Tsaeda Agam River in Makelle City, Tigram, Ethiopia. Bulletin of Chemical Society of Ethiopia, 29(3): 377-385. Leaf Pack Network® Biotic and Water Quality Calculator, https://leafpacknetwork.org/biotic-index/ Meyer J. L., Strayer D. L., Wallace J. B., Eggert S. L., Helfman G. S. and Leonard N. E. (2007). The contribution of headwater streams to biodiversity in river networks, Journal of the American Water Resources Association, 43: 86-103. National Environmental Standards and Regulations Enforcement Agency (NESREA) (2011). National Environmental (Surface and Ground Water Quality): 693-727. Nsikak U. B. and Joseph P. E. (2009). Petroleum HydrocarbonContamination of Sediments and Accumulation in Tympanotonusfuscatusvar. radula from the Qua Iboe Mangrove Ecosystem, Nigeria. Current Science, 96(2): 238-244. Okoroafor K. A., Effanga E. O., Andem A. B., George U. U. and Amos D. I. (2013). Spatial Variation in Physical and Chemical Parameters and Macro-Invertebrates in the Intertidal Regions of Calabar River, Nigeria. Greener Journal of Geology and Earth Sciences, 1(2): 62-72. Oku E. E., Andem A. B., Arong B. G. and Odjadjare E. (2014) Effect of Water Quality on the Distribution of Aquatic Entomofauna of Great Kwa River, Southern Nigeria. American Journal of Engineering Research 3: 265-270. Olomukoro J. O. and Dirisu A. R. (2014). Macroinvertebrate Community and Pollution Tolerance Index in Edion and Omodo Rivers in Derived Savannah Wetlands in Southern Nigeria. Jordan Journal of Biological Sciences, 7(1): 19-24. Pennak, E. (1978). A field guide to Africa fresh water snails. West African species, WHO snail identification centre. Danish Bilharziasis Laboratory, 34: 5-15. Reuben N. O., Raphael B. J. and Faith N. C. (2016). Combined Effects of Municipal and Industrial Wastes on the Quality of the New Northern Calabar River, Nigeria. International Journal of Water Resources and Environmental Engineering, 8(8): 103-112. WHO (2004). Guidelines for Drinking-water Quality.Geneva: World Health Organization.
Cite this article as:
Bate, G.B. and Sam–Uket, N.O., 2019. Macroinvertebrates’ Pollution Tolerance Index in Calabar River, Cross River State, Nigeria. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 292-297. https://doi.org/10.36263/nijest.2019.02.0154
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Solid Waste Management Practice and Challenges in Gashua, Yobe State, Nigeria
Saleh A.*,1 and Ahmed A.2 1Department of Geography, Federal University Gashua, Nigeria 2School of Preliminary Studies, Sule Lamido University, Kafin Hausa, Nigeria *Corresponding Author: [email protected], [email protected]
https://doi.org/10.36263/nijest.2019.02.0139 ABSTRACT
This paper presents an overview of the current solid waste management practices in Gashua town and provides a brief discussion on future challenges. Gashua town the headquarters of Bade Local Government Area since 1949. Since then the population has mainly due to the influx of people and its strategic location along the axial route to significant towns in the state. Wastes are generated mainly from residential, commercial and institutional land uses. Waste collection sites are strategically situated as identified by the agency and designated as high waste generating points, metal waste bins and constructed waste bunkers. The contents of these bins are finally disposed of at a location 6kilometres away from the generating points. Spatial data on waste distribution was collected using a global positioning system (GPS). The data was manipulated and processed using a Geographic information system (GIS) to produce the waste distribution map. Findings revealed that the existing solid waste management system is inefficient as the present practice relies on monthly collection and disposal of waste using an open dumpsite.
Keywords: Practice and Challenges, Solid Waste Management, Gashua, GIS, GPS
1.0. Introduction
The generation and management of solid waste is currently a global issue of interest, specifically in the developing nations universally (Chukwuemeka et al, 2012). The recurrent widespread of communicable diseases in both more prominent cities and medium towns are not unconnected with numerous huge garbage littering the streets, dumping of refuse near water bodies and drainage and in vacant plots in Nigeria (United Nations, Department of Economic and Social Affairs, 2014; Birma et al., 2016). Urbanization, population growth, enhanced lifestyle, inadequate planning and inadequate funding are the factors responsible for the increased solid waste management issues (Abila and Kantola, 2013). Nigeria’s population growth rate was 3.0%, and the urban growth rate was at about 5.5% while waste generation rate was at 0.49 kg per day as indicated by the National Bureau of Statistics (Afun, 2006). Urban centres in Nigeria are continuously experiencing population increase as well as a steady rise in waste generation due to urbanization (Kula and Gukop, 2012). A city like Abuja, which is the nation’s capital, generates a daily waste per person between 0.55-0.58 kg (Metropolis eta al, 201). In 1995 0.55-0.58 million tons of waste is generated in Lagos state one of the most densely settled cities in the world and 998.08 tons of municipal solid waste is generated in Lagos in 2000 whereas 90 tons of solid waste was generated per day in Minna, the capital of Niger State among others (Amuda et al., 2014; Adetunji et al., 2015).
Most industrialized nations have adopted the "Waste Management Hierarchy" (minimization, recovery and transformation, and disposal) as the list of options for developing solid waste management approaches (El-Haggar, 2007). The extent to which anyone option is used within a given country however varies, depending on some factors, such as topography, population density, and transportation infrastructure, socioeconomic and environmental code of practice (Babalola et al., 2010). One of the most analytical vital instruments for appropriate land use planning in the current dynamic world is waste monitoring and management (Anestina et al, 2014)
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Essentially, solid waste management in Nigeria is under the responsibility of the Local Environmental Protection Agency as stipulated by the 1988 decree which established the Federal Environmental Protection Agency (FEPA) (Agunwamba, 1998; Amasuomo, 2017). The collection of waste in Gashua is carried out by the Yobe State Environmental Protection Agency, (YOSEPA) Sanitary Board and Metropolitan Council. However; these local authorities have been overwhelmed by the increasing rate of waste generation, collection and transportation problems primarily due to overstretched facilities, shortages of the workforce and lean budget (Ogwuleka, 2012).
2.0. Materials and Methods
Gashua is a community in Yobe State located in the northeastern region of Nigeria, on the Yobe River, a few miles below the convergence of the Hadejia River and the Jama'are River. The average elevation is about 299 m. The population in 2006 was about 125,000 (Yobe State Government, 2016). The hottest months are March and April, with temperature ranges of 38°-43° Celsius. In the rainy season, June-September, temperatures fall to 23-28° Celsius, with rainfall of 500 to 800 mm. Gashua is one of the largest and most developed towns in Yobe State. Since 1949 it has been headquarters of the Bade Local Government Area. The Bade language is spoken in Gashua, and an area is fanning out east and south of Gashua. Bade is one of seven languages of the Chadic family indigenous to Yobe State (Abbas, 2016; Yobe State Government, 2016). The town lies near the Nguru-Gashua Wetlands, an economically and ecologically crucial ecological system. The town is the location of the court of Mai Bade, the Emir of Bade (Schuh and Languages, 2015; Djurfeldt et al., 2017).
Figure 1: Map of the study area (Source: Adopted and Modified from the Political Map of Yobe State, 2019)
Gashua town rose from an obscure native authority headquarters to the status of the local government headquarters in 1976. The sudden change in status brought about the increase in population from less than Ten thousand (10,000) persons before 1991 to a Population of about 139, 804 with 73, 709 males and 66, 095 females in 2006 (National population Commission, 2006; WFP, 2016). The rise in the population levels also brought about with it rapid economic growth and consequently the rise in the living standards of the people. Wastes and other contaminants from residential and other land use land uses in Gashua town are highly visible. Currently, domestic solid waste management in Gashua has severe problems, involving low collection rate, unscientific disposal method (open dumping), lack of separation and treatment mechanism in place, and burning of waste dumps without air pollution
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 298 - 303 control measures in place. For a better understanding of the present solid waste management scenario in the study area, the paper is structured as follows.
Waste collection bins are placed at strategic locations identified by the agency and termed as high waste generating points with wheeled plastic waste bins, metal waste bins and constructed waste bunkers (Uwadiegwu and Chukwu, 2013). The contents of these bins are finally disposed at a location 6 kilometers away from the generating points (Imam et al., 2008). This method adopted shows that the waste collections are sourced specified the approach in which the individual components of the waste stream are sampled, sorted and weighed. This method is useful for defining a local waste stream. The system adopted by the agency is the public bin collection system. This comprises of the collection from different sources like residential and commercial areas and deposited in the public bins located strategically along street corners of the town. Wastes are not treated before disposal at the final dumping sites. Waste minimization and recycling have not gone beyond the practice of picking and sorting through heaps of refuse or garbage. A retrospective study involves the collection of information from (YOSEPA), the agency responsible for the management of solid waste in the town. Other sources of information include personal observations, interviews with staff of the agency. Relevant information was also sourced from reports, books and journals.
Field surveys were carried out in some areas and the existing official dumpsite on the various samples of waste generated. The field survey involved the use of global positioning system to determine the position of dumpsters in the town. After that, the spatial positions of the waste collection points were produced from the integration of Geographic information system (GIS) and global positioning system (GPS) data. The names and locations (Easting and Northing coordinates) were recorded and stored in Microsoft Excel and converted into a database format and after that exported into Arc info GIS which is concerned with the manipulation of spatial and non-spatial data for processing. A layer of these points was created and then combined with a map layer digitized from the satellite imagery of the study area. Figure 1 shows the spatial distribution of waste collection points. Data on monthly waste collection for the period 2012-2018 were also obtained from the agency responsible for waste management. This served as the basis for comparison and testing the hypothesis.
Other method adopted is site Specific Study Approach which involves dumping sites identification, sorting and weighing of the components of waste products. This methodology is useful in defining a local waste especially when larger samples are taken for several seasons (Walling et al, 2004).
Figure 2: Refuse dump sites in Gashua (Source: Authors’ GIS analysis, 2019)
3.0. Results and Discussion
The waste compositions are as follows: Polythene and Plastic materials, 40% Metal and tins, 5.2% Organic matter, 54.8%. Table 1 below revealed the waste collected in Gashua from 2012-2018 On the whole, the agency collected 132, 685 tons of solid waste between the periods under review, considering the average waste generation of 0.3 kg/person/day. Moreover, the population of Gashua
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 298 - 303 of 76,000 persons in 2006 (NPC, 2006) and estimated to be 96,448 persons in 2018(NBS, 2018). It can be seen from Table 2 that virtually every month, the agency collected and disposed of waste within the town, but the amount collected remained very little compared to what is seen in the dumpsters. The amount of waste collected stood at 23, 198 tons in 2012 and 21, 483 tons in 2018. This implies that there was a decline in the amount of waste collected over seven years. Table 2 below shows the descriptive statistics used in the calculating mean monthly waste collection of 95% significant level. The analysis of variance (ANOVA) was used to test whether the mean weight of solid waste collected is the same for the year 2012, 2013, 2014, 2015 and 2016, 2017 and 2018. The hypothesis can be written as [H0: μ1 = μ2 = μ3= μ4 = μ5 = μ6 = μ7 = μ8] versus [H1: μ: ≠ μj] H0: μ1 =μ2 = μ3 = μ4 = μ5 = μ6 = μ7 = μ8 all mean weight is not the same while, H1: μ: ≠ μj for at least one of the mean weight is the same. H0 is rejected at the level significance of 0.05 since the value of the F statistic (4.038) is greater than the critical value of the F statistic, F critical value (2.219). This indicates that there is a significant difference in the amount of waste collected from 2012-2018 at the 0.05 level of significance. From the preceding, it becomes clear that the agency performed below average as heaps of garbage have taken over the access road and thereby causing traffic problems in some parts of the town while the drainage system has been blocked as a result of poor management practices.
Table 1: Solid waste collection from 2012-2018 in Gashua town Month/years 2012 2013 2014 2015 2016 2017 2018 January 260 287 182 111 287 285 182 February 239 342 116 302 216 321 202 March 122 435 132 175 229 213 185 April 204 200 245 112 110 172 97 May 345 321 125 195 256 562 345 June 376 431 114 201 243 210 132 July 301 298 98 113 265 267 344 August 302 211 112 50 179 180 283 September 237 154 215 85 150 207 152 October 285 114 154 186 115 162 573 November 343 170 176 168 90 321 287 December 300 318 321 211 67 285 287 Total no. of trips 3314 3281 1990 1909 2207 3185 3069 Total tons 23198 22967 13930 13363 15449 22295 21483 Source: Yobe State Environmental Protection Agency, 2012-2018. Note 1trip = 7 tons
Table 2: Descriptive statistics on solid waste collection from the year 2012-2018 No of Mean Years Standard Standard Sample 95% CI for mean collection Monthly deviation Error variance months collection Max. Min. 2012 12 276.16 486.0206 134.7979 236216.1 376 122 2013 12 273.41 492.7567 136.6661 242809.2 435 114 2014 12 165.83 516.5365 143.2615 266810 321 98 2015 12 159.08 518.8718 143.9092 269228 302 50 2016 12 183.91 513.2545 142.3512 263430.1 287 67 2017 12 265.41 496.8987 137.8149 246908.3 562 162 2018 12 255,75 504.1783 139.8339 254195.7 573 97 Source: Yobe State Environmental Protection Agency, 2012-2018
Table 3: Output generated by the ANOVA Sum of Mean Source of variance df F P value F Crit. Squares Squares Between Groups 204861.7 6 34143.62 4.038473 0.001432 2.218817 Within Groups 651003.3 77 8454.588 Total 855865 83 Source: Yobe State Environmental Protection Agency, 2012-2018
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4.0 Conclusions
The analysis of waste collected shows that there was a decrease in the amount of waste collected from 23198 tons in 2012 to 21483 tons in 2018 during the period under review. The uncontrolled waste generation has led to the loss of the appealing nature of the urban landscape. Gashua town faces the same challenges as many other urban centers in Nigeria regarding infrastructure deficiency, population growth and lack of public awareness on the issue of waste management. This study revealed that inadequate infrastructure and funding are some of the most significant obstacles to successful waste management practices. Even though waste can be recycled to produce new products, these wastes are currently littering every available open space. The biodegradable waste could be composted to organic manure and could be used on the farms as manures. The agency is grossly understaffed as the so-called laborers are hired temporarily. Finally, the public attitude towards waste disposal is not helping matters. Despite the presence of waste collection bins, children especially dump their waste outside these bins. Enlightenment campaigns should be carried to educate the public.
References
Abbas, A. I. (2016). Between policy expectations and realities of poverty reduction efforts: An assessment of National Poverty Eradication Programme (NAPEP) in Yobe State, Nigeria. Journal of Social Science for Policy Implications, 4(1), pp. 37–62.
Abila, B. and Kantola, J. (2013). In Nigeria: Evolving Knowledge Management Solution. International Journal of Environmental, Ecological, Geological and Mining Engineering, 7(6), pp. 169–174.
Adetunji, M. A., Atomode, T. I. and Isah, I. O. (2015). Assessment of Solid Waste Management in Lokoja, Nigeria, 7(2), 103–108.
Afun, S. (2006). Government Regulations and Legislations Will Ensure Sustainable Waste Management in Nigeria. International Solid Waste Association, 1–10.
Agunwamba, J. C. (1998). Solid waste management in Nigeria: Problems and issues. Environmental Management, 22(6), pp. 849–856.
Amasuomo, E. (2017). Solid Waste Management Trends in Nigeria Ebikapade Amasuomo and Jim Baird SEBE, Glasgow Caledonian University, Cowcaddens Road, G4 0BA, Glasgow, UK, 5(6), pp. 25–37.
Amuda, O. S., Adebisi, S. A., Jimoda, L. A. and Alade, A. O. (2014). Challenges and Possible Panacea to the Municipal Solid Wastes Management in Nigeria. Journal of Sustainable Development Studies, 6(1), pp. 64–70.
Anestina, A. I., Adetola, A. and Odafe, I. B. (2014). Performance Assessment of Solid Waste Management following Private Partnership Operations in Lagos State, Nigeria. Journal of Waste Management, 2014, pp. 1–8.
Babalola, A., Ishaku, H. T., Busu, I. and Majid, M. R. (2010). The Practice and Challenges of Solid Waste Management in Damaturu, Yobe State, Nigeria. Journal of Environmental Protection, 01(04), pp. 384–388.
Birma, B.H. (2016). Assessment of Household Solid Waste Management in Gombe, Nigeria. Unpublished M.Sc Thesis, Department of Urban and Regional Planning, Ahmadu Bello University, Zaria, Nigeria
Chukwuemeka, E., Ugwu, J. and Igwegbe, D. (2012). Management and Development Implications of Solid Waste Management in Nigeria. Asian Journal of Business Management, 4(4), pp, 352–358.
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Djurfeldt, A. A., Sircar, S., Okonkwo, S. O., Orebiyi, J. S., Kadiri, F. A., Johnson, I. U. and Draft, F. (2017). Land fragmentation effects on technical efficiency of cassava farmers in South-West geopolitical zone, Nigeria. Cogent Social Sciences, 3(2), pp. 1–10.
El-Haggar, D. S. M. (2007). Sustainability of Municipal Solid Waste Management. Sustainable Industrial Design and Waste Management, pp. 149–196.
Imam, A., Mohammed, B., Wilson, D. C. and Cheeseman, C. R. (2008). Solid waste management in Abuja, Nigeria. Waste Management, 28(2), pp. 468–472.
Kulla, D. M. and Gukop, N. (2012). Municipal Waste in Nigeria Generation , Characteristics and Energy Potential of Solid, 2(2), pp. 84–88.
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Cite this article as: Saleh A. and Ahmed A., 2019. Solid Waste Management Practice and Challenges in Gashua, Yobe State, Nigeria. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 298-303. https://doi.org/10.36263/nijest.2019.02.0139
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Vol 3, No. 2 October 2019, pp 304 - 316
Subsurface Structural Mapping over Koton Karifi and Adjoining Areas, Southern Bida Basin, Nigeria, using High-Resolution Aeromagnetic Data
Ikumbur E.B.1,*, Ogah V.E.1 and Akiishi M.2 1Department of Geology, Benue State Polytechnic Ugbokolo, Nigeria 2Department of Physics, College of Education Oju, Benue State, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0151
ABSTRACT
In this current work, we aim to delineate the subsurface structural trends, determine the depth to basement surface, and provide an illustrative 3D model for its subsurface structure. Four digitized aeromagnetic maps were acquired from the Nigerian Geological Survey Agency, Abuja. The total field aeromagnetic anomalies over Koton Karifi and adjoining areas have been evaluated. In order to map the subsurface structures and estimate the depth to basement surface the spectral analysis method was applied. To achieve such goals, a detailed analysis of the aeromagnetic data for the study area was performed. 2D interpretation was carried out for the aeromagnetic data. The processes used include contouring of the Total Magnetic Intensity (TMI) data, separation of regional and residual anomalies, structural detection methods such as analytic signal, vertical derivatives, and magnetic lineament mapping were used to map the contacts and faults within the study area. The first vertical derivative and the magnetic lineament maps show major geologic lineaments trending in East-West with minor ones trending Northeast-Southwest. In the south- eastern part of the study area, there is a dome-shaped linear feature. The result obtained using the spectral analysis method reveals two source depth models. The depths to deeper magnetic sources range from 2.81 km to 3.24 km with an average depth of 2.90 km. The deeper magnetic source bodies are identified with the magnetic basement. The shallower magnetic sources which range from 0.45 km to 1.81 km with an average depth of 1.13 km could be attributed to near surface magnetic sources which are magnetic rocks that intruded into the sedimentary formations or magnetised bodies within the sedimentary cover. Based on the sedimentary thickness range of 0.45 to 3.24 km, there is an indication that the possibility of hydrocarbon generation in the study area is feasible.
Keywords: Spectral analysis, aeromagnetic anomalies, analytic signal, vertical derivative, depths- to-basement, subsurface structures.
1.0. Introduction Magnetic lineaments over sedimentary basins are zones of gradient interruptions or zones marked by sharp changes of the orientation of anomalies. These anomalies may be as a result of the faults affecting the underlying basement alone or both the basement and the sedimentary formations. Lineament is a mappable linear or curvilinear feature of a surface whose parts align in a straight or slightly curving relationship (Hung et al., 2005). Magnetic anomalies depend on rock magnetism (Telfold et al., 1990). Most sedimentary rocks and surface cover are non-magnetic so the observed anomalies are related to the underlying igneous and metamorphic rocks. Potential field data especially aeromagnetic surveys are used commonly to map basement structure beneath sediment cover. We used the term ‘subsurface structure’ as defined by Ross et al., 2017, which is described as structural fabrics within the crystalline basement. Some of these are shear zones that have maintained their coherence during ductile deformation and some are faults or fault zones where coherence has been
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 304 - 316 lost and slip in the brittle regime has occurred. Such structures can be identified and delineated accurately by using regional magnetic field data sets. Magnetic survey is aimed at investigating the subsurface geology on the basis of magnetic anomalies in the earth’s magnetic field resulting from the magnetic properties of the underlying rocks (Ikumbur et al., 2013). Aeromagnetic survey is one of the most important tools used in modern geological mapping. The aeromagnetic survey is applied in mapping the magnetic anomalies in the earth’s magnetic field and this is correlated with the subsurface geological structure (Chinwuko et al., 2012; Onuba et al., 2012; Udensi and Osazuwa, 2004). In addition, aeromagnetic surveys are used to determine depth and structure of crystalline basement rocks underlying sedimentary basins (Abdulsalam et al., 2011; Akanbi and Udensi, 2006). Previous studies on spectral analysis of aeromagnetic data were carried out in other parts Nigeria. Such works include that of Onwuemesi (1997) who applied 1D spectral analysis to aeromagnetic anomalies in the Anambra basin; Anakwuba et al., (2011) used spectral methods to interpret aeromagnetic anomalies over Maiduguri-Dikwa depression of Chad basin. Onuba et al., (2012) applied spectral analysis to evaluate aeromagnetic anomalies over Okigwe area, South-eastern Nigeria; while Chinwuko et al., (2012) also applied spectral analysis to evaluate aeromagnetic anomalies over parts of Upper Benue Trough/Southern Chad basin, Nigeria. Aeromagnetic method been recognized as an effective tool for mapping structures within basement rocks where measured magnetic anomalies usually indicate magnetic susceptibility contrasts within crystalline basement (Elebiju et al., 2010; Sunmonu et al., 2000). The present study involves the mapping of subsurface structures over Koton Karifi and Adjoining areas using high-resolution aeromagnetic data. The objectives of this study are to delineate the possible subsurface structural trends, to determine the approximate depth to basement, and to provide a 3D structural model to illustrate the subsurface structures found in the study area.
1.1. Location and geology The area of study, which is part of the southern Bida basin, is bounded by latitude 80001 N and 90001N, and longitude 60001E and 70001E. It is an area of about 12,000 km2 situated at the West- Central Nigeria (Figure 1). The Bida Basin is an elongated NW-SE trending depression perpendicular to the main axis of the Benue Trough of Nigeria. The entire basin is bounded by latitudes 80001N and 100301N and longitudes 40301E and 70301E. It covers an area of about 90,760 km2 (Nwankwo et al., 2008). The basin is a gentle down-warped shallow trough filled with Campanian-Maastrichtian marine to fluviatle strata believed to be more than 300m thick (Jones, 1958; Adeleye, 1976). The Basin might be regarded as north-western extension of Anambra basin and is found in the western part of central Nigeria. Both the Anambra and Bida basin were major depocenters during the second major sedimentary cycle of southern Nigeria in the Upper Cretaceous time (Obaje, 2009).
STUDY AREA
Figure 1: Map of study area showing its location and geology (After Obaje, 2009)
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The original rock of the area could have been subjected to considerable erosion before the Upper Cretaceous beds were laid down. Tertiary earth movements impacted low dips to this Formation leading to erosion over wider areas. The youngest rocks of the area are laterites and alluvial, terrace and terrestrial deposits of tertiary and recent age (Russ, 1957). Both surface and subsurface information available is suggestive of Post-Santonian origin as sediments in Bida basin are generally undisturbed (Agyingi, 1991). Maximum sedimentary thickness of up to 3.30km has been recorded in the basin from aeromagnetic interpretation (Agyingi, 1991). Unconformity surface, different form of beddings (cross, parallel and graded), deformation and diagenetic features, such as fractures, slumps and concretions are prominent features in the basin. The features show characteristics of continental rift basin development (Obaje, 2009). The geological map of the southern part of Bida basin shown in Figure 1 consists of Lokoja, Patti and Agbaja Formations. According to Akande et al., (2005), the Patti Formation which is the only stratigraphic unit containing carbonaceous shale in the Bida basin is sand-witched between the order Campanian-Maastrichtian Lokoja Formation (conglomerates, sandstones and claystones) and younger Agbaja Formation (mainly ironstones).
2.0. Materials and Methods Four digitized high-resolution aeromagnetic maps (sheets 205, 206, 226 and 227) were acquired from Nigerian Geological Survey Agency, Abuja; assembled and interpreted. The data set is from the new high-resolution airborne survey coverage in Nigeria carried out by Fugro Airborne Surveys between 2006 and 2009. The aeromagnetic surveys were flown along a series of NW-SE flight lines, spaced 500m, with 2000m tie-line spacing in a NE-SW direction and 80m nominal flight height. The data were recorded at 0.1 second interval. Since the survey was flown closer to ground (80m flight height) with narrow line spacing and very small recording interval, the resolution of anomalies is more superior to that of conventional high-altitude surveys. The first step in the present study was to assemble the four maps covering the study area. The next was to re-contour the map to produce the total field aeromagnetic intensity map (Figure 2). The contoured total-field intensity map contains both the regional and residual anomaly. The regional gradient was removed from the map by fitting a linear surface to the digitized aeromagnetic data using the least square method. The surface linear equation on the data can be given according to Likkason (1993) as; 푝(푥, 푦) = 푎푥 + 푏푦 + 푐 (1) Where, a, b and c are constants; x and y are distances in x and y axes; 푝(푥, 푦) is the magnetic value at 푥 and 푦 co-ordinates. The Least squares method of statistical analysis was used to obtain the constants (a, b and c) and the trend surface equation (regional gradient) becomes; 푝(푥, 푦) = 1.8013푥 − 0.4575푦 + 7989.78 (2) The trend surface equation (eq. 2) was then subtracted from the aeromagnetic (observed) data and the resultant residual aeromagnetic anomaly data was obtained and contoured (Figure 3) using contouring software (Surfer Version 32). The analytical signal and first vertical derivative maps of the study area were produced using Geosoft software-Oasis Montaj (Figures 4 and 5).
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Figure 2: Total Magnetic Intensity map of the study area (Contour Interval ≈ 30nT)
Baro Gulu
Kirri Koton karifi
Figure 3: Residual Anomaly Map of the study area with cross-sections
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Baro Gulu
Kirri Kotonkarifi
Figure 4: Analytical Signal Map of the Study Area
Baro Gulu
Kirri Kotonkarifi
Figure 5: First Vertical Derivative Map of the Study Area
The lineament map was produced by drawing the lines parallel to the structures (faults and contact systems). Contact location and their trends were traced from the analysis and interpretation of analytical signal and first vertical derivative maps (figures 4 and 5). The traced magnetic structural lineaments map (figure 6) represents faults and / or contacts between rocks type with different magnetic susceptibilities.
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Figure 6: Magnetic Lineament map of the study area
3.0. Results and Discussion 3.1. Qualitative interpretation The qualitative interpretation was done by visual inspection of the total magnetic intensity, residual magnetic anomaly, analytic signal, first vertical derivative and magnetic lineament maps. The residual magnetic anomaly map was produced by subtracting the regional magnetic field from the total magnetic intensity field. The total magnetic field range from 7600 to 8380 nanotesla (nT) in the study area, where higher values are found in the northern and southern parts, and lower values in the central region (Figures 2 and 4).The closely spaced linear sub-parallel orientation of contours in the northern and southern parts of the study area suggests the presence of faults or local fractured zones in the study area (Figure 5). Most of the anomalous features trend in the East-West direction, while minor ones trend Northeast-Southwest. Such geologic features may appear as thin elliptical closures or nosing on an aeromagnetic map. These features represent geologic lineaments and their positions are indicated by lines drawn parallel to the elongation and through the centre of the anomalies represented in Figure 6. The main trend of the lineaments is East-West, while few trend Northeast-Southwest. A visual inspection of aeromagnetic map over the study area shows that the contour lines are widely spaced in the central part which shows thicker sediments in the region indicating that the depth to basement is higher compared to the closely spaced contours in the northern and southern parts which suggest shallow sedimentary thickness (Figure 3). The analytic signal map shows areas of higher intensity (high signal) in the north and south of the study area, while the central region has lower intensity (low signal) (Figure 4). Also, the residual anomaly map shows positive magnetic anomaly and larger sedimentary thickness indicating deeper depths at the central region, while the northern and southern portions show negative anomaly with smaller sediment thickness indicating shallower depths. In the south-eastern part of the study area (Koton-Karifi), there is a dome-shaped linear feature (Figures 2, 3 and 5). The general indication is that this linear feature is of intermediate depth and seems to be hosted in the basement structure and is thought to be a major divide (fault or fracture) making a boundary (Abdulsalam et al., 2011). Several contour closures are found south of this lineament, which indicate shallow basement. This may be due to the fact that the Niger-Benue River confluence is an uplifted area, similar to a model earlier proposed by Wright (1976) and Likkason (1993).
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3.2. Quantitative interpretation 3.2.1. Depth estimation In order to estimate depths to basement across the study area using spectral methods, five profiles were taken cutting across anomalous features for the interpretation of the geophysical anomalies in the area under study (Figure 3). The anomalies identified on these profiles were then subjected to the spectral analysis. The Spectral analysis method is represented mathematically (according to Onwuemesi, 1997) as:
2휋푛푥 2휋푛푥 푌 ∑푁 [푎 푐표푠 푐표푠 ( 푖) + 푏 푠푖푛 푠푖푛 ( 푖) ] (3) 푖(푥)= 푛=1 푛 퐿 푛 퐿
where: 푌푖(푥) = Reading at 푥푖 position L = length of the cross-section of the anomaly n = harmonic number of the partial wave N = number of data points
푎푛= real part of the amplitude spectrum Partial Amplitude 푏푛= imaginary part of the amplitude spectrum i = 0, 1, 2, 3, ------, n Figure 7 shows the magnetic anomaly graphs drawn from five cross-sections. Graphs of the natural logarithms of the amplitude (An) against frequency (n) were plotted and the linear segments from the low frequency portion of the spectral were drawn from the graphs (Figure 8). The gradient of the linear segments were computed and the depths to the basement were determined using the equation according to Negi et al., (1983), given as; Z = -ML/2п (4) where, Z = depth to the basement M = gradient of the linear segment L = length of the cross-section of the anomaly
Figure 7: Anomaly graphs drawn from the cross-sections AAl-EEl
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Graphs of the natural logarithms of the amplitude against frequencies for the selected profiles are shown in Figure 8 (a) – (d). The gradient of the linear segments were computed by dividing the change in values of y by change in values of x (i.e. Δy/Δx) and used to estimate the depth to magnetic sources. The depths to magnetic sources range from 0.45 to 3.24 km (Table 1).
Figure 8 (a): Amplitude spectral graphs for cross-sections AAl
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Figure 8 (b): Amplitude spectral graphs for cross-sections BBl
Figure 8 (c): Amplitude spectral graphs for cross-sections CCl
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Figure 8 (d): Amplitude spectral graphs for cross-sections DDl
Table 1: Basement Depths (in km) obtained from Spectral Analysis
Profile name Profile direction Anomaly Gradients Depth(km) NW-SE 1 -0.79224 0.45 AAl NW-SE 2 -2.77850 0.88 Along Kirri NW-SE 3 -4.10821 1.31 NW-SE 4 -1.40014 0.45 BBl NW-SE 5 -0.48680 1.08 Along Kirri & Kotonkarfi NW-SE 6 -0.80529 0.90 CCl NW-SE 7 -1.37781 3.07 Along Baro, Kirri & NW-SE 8 -2.94263 2.81 Kotonkarfi NW-SE 9 -2.03576 3.24 NW-SE 10 -2.25295 2.82 DDl NW-SE 11 -0.55996 0.62 Along Baro & Gulu NW-SE 12 -1.33840 1.49 NW-SE 13 -0.59960 0.67 NW-SE 14 -0.55870 0.56 EEl NW-SE 15 -0.67950 0.76 Along Gulu NW-SE 16 -0.98914 1.10
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3.3. Basement topography The computed depths to basement were used to construct both the basement map and 3-D surface map for the basement topography of the area (Figures 9 and 10). The two maps show that the depth to basement is deeper in the central region and shallower in the northern and southern parts of the study area. The 3-D surface map also shows a linear depression with thicker sediments at the central region of the study area trending E-W direction. Km
Figure 9: Depth to basement map of the study area
Km Gulu S Koton-Karifi
Baro Kirri
Figure 10: 3D Surface Plot for the basement topography of the study area
4.0. Conclusions Spectral analysis method has been applied to a set of high-resolution aeromagnetic data over Koton- Karifi and Adjoining Areas. The result shows that two depth sources were obtained in the study area; the deeper sources range from 2.81-3.24km, while the shallower sources range from 0.45-1.49km. The depths to basement are deeper in the central part trending East-West direction and shallower in the northern and southern parts of the study area. The deeper magnetic source bodies are identified with the magnetic basement, while the shallower magnetic sources may be attributed to near surface magnetic sources which are magnetic rocks that intruded into the sedimentary formations or
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References Abdulsalam, N.N., Mallam, A., and Likkason, K.O., (2011). Identification of linear Features using continuation filters over Koton-Karifi Area, Nigeria, from Aeromagnetic Data, World Rural Observations, vol. 3, No.1, pp. 1-8. Adeleye, D.R., (1976). The geology of the Middle Niger Basin, In: Geology of Nigeria (C. Kogbe, Ed.) Elizabethan Publishing Co. Lagos, pp. 283-287. Agyingi, C.M., (1991). Geology of Upper Cretaceous rocks in the eastern Bida Basin, Central Nigeria, Unpublished PhD Thesis, University of Ibadan, Nigeria, 501p. Akanbi, E.S. and Udensi, E.E., (2006). Structural trends and spectral depth analysis of the residual field of Pategi Area, Nigeria, using aeromagnetic data, Nigerian Journal of physics, vol. 18, No.2, pp. 271- 276. Akande, S.O., Ojo, O.J. and Ladipo, K., (2005). Upper Cretaceous sequences in the Southern Bida Basin, Nigeria. A Field guide book, Mosuro Publishers, Ibadan, 60p. Anakwuba, E.K., Onwuemesi, A.G., Chinwuko, A. I. and Onuba, L. N., (2011). The Interpretation of Aeromagnetic anomalies over Maiduguri-Dikwa depression, Chad Basin Nigeria: A Structural View, Scholars research library, Archives of Applied Science Research, vol. 3, No. 4, pp. 499-508. Chinwuko, A. I., Onwuemesi, A.G., Anakwuba, E.K. and Nwokeabia, N.C., (2012). Interpretation of aeromagnetic anomalies over parts of Upper Benue Trough and Southern Chad Basin, Nigeria, Advances in Applied Science Research, vol. 3, No. 3, pp. 1757-1766. Elebiju, O.O., Keller, G.R. and Marfurt, K.J., (2010). Investigation of links between Precambrian basement structure and Paleozoic strata in the Fort Worth basin, Texas, U.S.A., using high-resolution aeromagnetic (HRAM) data and seismic attributes: Geophysics, vol. 75, No.4, pp.157-168. Hung L.Q., Batelaan O., and De Smedt F., (2005). Lineament extraction and analysis, comparison of LANDSAT ETM and ASTER imagery, Case study: Suoimuoi tropical karst catchment, Vietnam, Proceedings of SPIE - The International Society for Optical Engineering. Ikumbur, E. B., Onwuemesi, A. G., Anakwuba, E. K., Chinwuko, A. I., Usman, A. O., Okonkwo, C. C., (2013). Spectral Analysis of Aeromagnetic data over part of the Southern Bida Basin, west-central Nigeria, International Journal of Fundamental Physical Sciences, vol. 3, No. 2, pp. 27-31. Jones, H. A., (1958). The occurrence of Oolitic Ironstones in Nigeria: Their Origin, Geological history and Petrology, Oxford, D.Phil. Thesis. Likkason, O.K., (1993). Application of Trend Surface analysis gravity data over the Middle Niger Basin, Nigeria, Journal of Mining and Geology, vol. 29, No.2, pp. 11-19. Negi, J.G., Agrawal, P.K. and Rao, K. N.N., (1983). Three dimensional Model of the Moyan area of Maharshiatra state (India) based on the spectral analysis of aeromagnetic data, Geophysics, vol. 48, No.7, pp. 964-974. Nwankwo, L.I., Olasehinde, P.I and Akoshile, C.O., (2008). Spectral Analysis of Aeromagnetic Anomalies of the Northern Nupe Basin, West-central Nigeria, Global Journal of Pure and Applied Science, vol. 14, No. 2, pp. 247-252.
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Obaje N.G., (2009). Geology and Mineral Resources of Nigeria, Springer, Heidelberg, 221p. Onuba, L. O., Chinwuko, A. I. , Onwuemesi, A. G., Anakwuba, E. K., and Nwokeabia, N .C., (2012). Interpretation of Aeromagnetic Anomalies over parts of Upper Benue Trough and Southern Chad Basin, Nigeria, Pelagia Research Library, Advances in Applied Science Research, vol. 3, No. 3, pp. 1757-1766. Onwuemesi, A.G., (1997). One Dimensional Spectral Analysis of Aeromagnetic Anomalies and Curie Depth Isotherm in the Anambra Basin of Nigeria, Journal of Geodynamics, vol. 23, No.2, pp. 95-107. Ross, Z.E., Hauksson, E. and Ben-Zion, Y., (2017). Abundant off-fault seismicity and orthogonal structures in the San Jacinto fault zone, Sci. Adv., vol. 3, pp. 1-9. Russ, W., (1957). The geology of parts of Niger, Zaria and Sokoto Provinces: Geological Survey of Nigeria Bulletin No.27, 31p. Sunmonru, L.A., Adabanija, M.A. and Olowofela, J.A., (2000). 2 - Dimensional Spectral Analysis of magnetic Anomalies of South-eastern part of middle - Niger Basin, Central Nigeria, Nigeria Journal of physics, vol. 12, pp. 39 - 44. Telfold, W.M., Geldart, L.P. and Sheriff, R.E., (1990). Applied Geophysics, Second edition, Cambridge University Press, 772p. Udensi, E. E. and Osazuwa, I. B., (2004). Spectral determination of depth to Buried magnetic rocks under the Nupe Basin, Nigeria; Nigeria Association of Petroleum Explorationists, Bulletin, vol. 17, No.1, pp. 22 - 27. Wright, J.B., (1976). Fracture systems in Nigeria and initiation of fracture Zones in The South Atlantic, Tectonophysics, vol. 34, pp. 43 - 47.
Cite this article as:
Ikumbur, E.B., Ogah, V.E. and Akiishi, M., 2019. Subsurface Structural Mapping over Koton Karifi and Adjoining Areas, Southern Bida Basin, Nigeria, using High-Resolution Aeromagnetic Data. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 304-316. https://doi.org/10.36263/nijest.2019.02.0151
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 317 - 330
Mapping the Impact of Land Use and Land Cover Change on Urban Land and Vegetation in Osun State, Nigeria
Abiodun O.E.1,* and Akinola D.J.1 1Department of Surveying and Geoinformatics, University of Lagos, Akoka, Nigeria Corresponding Author: *[email protected]
https://doi.org/10.36263/nijest.2019.02.0146
ABSTRACT Urban expansion along with other changes in land use and land cover is a global phenomenon and most parts of Western Nigeria have experienced tremendous changes in recent past. Osun state, located in Western Nigeria, was originally made up of mostly traditional farming communities. These communities have witnessed rapid urbanisation in the last few decades and most of the communities previously known to be farming communities have transformed to modern well-known cities. This project examines the use of Remote Sensing in mapping of Land Use Land Cover in Osun state over a period of 30 years (1986 to 2016) using Landsat (MSS, TM, and ETM+) images. The aim of this study is to produce a land use/land cover map of Osun state at three epochs in order to detect the changes that have taken place particularly in the built up and Vegetation areas. Landsat Images of Osun state in 1986, 2006 and 2016 were processed into five land use classes namely: Water body, Vegetation, Wetland, Built-up and Bare land. Total area of land use in each class were determined along with percentage change area, Land Consumption Rate and Land Absorption Coefficients. The result of the work shows that built-up area changed from 20.52% in 1986 to 30.71% in 2006 and then 34.45% in 2016. Land Consumption rate was 0.068 in 2016 which is indication of highly compacted living environment. The minimum Land Absorption Coefficient observed was 0.027 in between 2006 and 2016, which indicates that land is acquired for built-up development at very high rate. The resultant effect of these observed changes was a reduction of the vegetation class from 35.82% in 1986 to 31.14% in 2006 and then 23.83% in 2016. The results in this study may influence new land policy that will enhance sustainable use of land in Osun state. Keywords: Land Use, Epoch, Changes, Vegetation, Environment.
1.0. Introduction
In change detection analysis, it is required to identify differences in the state of an object or phenomenon by observing it at different times (Singh, 1989). This provides the foundation for a better understanding of the development an interaction between human and natural phenomena for a better utilisation of resources. Repetitive data, especially in the GIS environment provides the advantage of a synoptic view of the environment, and a digital data format suitable for computer processing, management and storage (Lu et al., 2004; Kennedy et al., 2009). In general, change detection involves the application of multi-temporal data sets to quantitatively analyse the temporal effects of the phenomena of interest. Air and space-borne remote sensing data has, in the last few decades, made it possible to analyse land use and land cover information consistently. In addition, GIS tools and applications has now made it possible to easily manipulate and analyse multiple land use information simultaneously. Therefore, information such as the trend, rate, nature, location and magnitude and sometimes direction of these changes are now possible (Adeniyi et al., 1999). Land is a very important natural resource for man since life and development activities depends on it. Land use is generally used to refer to the purpose
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2.0. Methodology 2.1. Study area Osun state is Located at approximately latitude 7°10’ to 7°55’ North and longitude 4°30’ to 5°00’ East. Osun is located in the south-western part of Nigeria with capital city located at Osogbo. It is bounded in the north by Kwara State, in the east by both Ekiti and Ondo State, in the south by Ogun State and in the west by Oyo State. The sub-ethnic groups found in Ọsun could be classified into Ife, Ijesha, Oyo and Igbomina which formed the basis for its political divisions,although there are also people from other parts of Nigeria. Yoruba and English are the major languages spoken in Osun. People of Osun State could be classified based on their religion and beliefs into Islam, Christianity and traditional faith. The ancient town of Ile-Ifẹ, an important and acclaimed “origin” of the Yorubas is located in Osun state. Other important cities and ancient towns include Ilesha, Oke-Ila Orangun, Ila Orangun, Ede, Iwo, Ejigbo, Ikirun, Owena and Ikire. Figure 1 shows the administrative boundaries of Osun State with its major cities and towns.
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Figure 1: Map of study area
2.2. Data acquisition The digitized map of Osun state was acquired from the office of the Surveyor General of Osun state. Landsat images of the study area for 1986, 2006 and 2016 were acquired from United States Geological Survey (USGS). It was difficult to secure quality images of Osun state between 1986 and 2016 except images in those epochs close to 1986 and 2016. The use of very close data epochs for a study that spans thirty years where a wide gap between the epochs is not covered may not offer an appreciable analysis of results. Therefore, although 2006 image is of low quality, it was used to at least give the idea of land use trends between 1986 and 2006. The results obtained from 1986 and 2016 will also serve as a check to inaccuracy that may be recorded from 2006 image. Table 1 below show the list of data obtained for this project and their various sources. Table 2 contain the imagery dataset details.
Table 1: Data Type
S/N Data type Source
1 Digitized Administrative map of Osun state
2 Landsat 4 TM satellite imagery of 1984 with 30.0m resolution USGS
3 Landsat 7 ETM+ satellite imagery of 2006 with 30.0m resolution USGS
4 Landsat 8 OLI satellite imagery of 2015 with 30.0m resolution USGS
Table 2: Imagery dataset details
Year Sensor Scene ID # Path / Row Date acquired Resolution 1986 TM LM51910551986358AAA03, 191/055 1986-12-18 30m LM51900551986351AAA03, 190/055 LM51900541986351AAA03 190/054 2006 ETM+ LE71900542006334ASN00, 190/054 2006-12-28 30m LE71900552006334ASN00, 190/055 LE71910552006341ASN00 191/055 2016 OLI / LC81900542016322LGN00, 190/054 2016-12-18 30m TIRS LC81900552016002LGN00, 190/055 LC81910552016041LGN00 191/055
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2.3. Preprocessing Image pre-processing is also called image restoration and generally involves the correction of distortion, degradation and noise introduced during the imaging process. This process produces a corrected image that is as close as possible, both geometrically and radiometrically, to the radiant energy characteristics of the original scene. Radiometric and geometric errors are the most common types of errors encountered in remotely sensed imagery (Image Pre-processing, 1997). Since Landsat data are currently corrected by USGS/EROS to level 1T which includes the following: geometric correction with ground control points for accurate ground location and radiometric correction for accurate measurements at the sensor and no data loss, a separate pre-processing is therefore unnecessary.
2.4. Data processing The extracted individual bands that make up each of the Landsat scenes acquired were stacked together into a single multispectral image using ERDAS Imagine.Figure 2 below shows the diagrammatic scheme of image staking for the 1984 image.
Figure 2: Diagrammatic scheme of image staking for the 1984 image.
The boundary shape file (.shp) of Osun state was converted to an area of interest file (.aoi) which was used in the clipping of the stacked multispectral Landsat imageries.The LANDSAT 7 uses the Worldwide Reference System-2 (WRS) which index orbits (paths) and scene centers (rows) into a global grid system comprising 233 paths by 248 rows (Barsi et al., 2003). Figure 3 shows the WRS imposed on the Nigerian map while the stages involved in the clipping of the study area from the stacked image is displayed in Figure 4.
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Figure 3: World Reference System (Source: www.yale.edu/ceo/DataArchive/nigeria.html)
Figure 4: Clipping of the Study area from the stacked multispectra images
2.5. Image classification Training of classes was done in ERDAS Imagine with the use of Area of Interest (AOI) tool combined with the Author’s experience from ground truthing and visual interpretation. Maximum Likelihood – a type of supervised classification technique was used in classifying the three (3) Landsat imageries. Maximum likelihood classification assumes that the statistics for each class in each band are normally distributed and calculates the probability that a given pixel belongs to a specific class. Unless the probability threshold is selected, all pixels are classified. Each pixel is assigned to the class that has the highest probability (that is, the maximum likelihood). If the highest probability is smaller than a threshold specified, the pixel remains unclassified (Richards, 1999). The images were classified into Water body, vegetation, wetland, built-up and bare land, the description of each classes are as contained in Table 3.
Table 3: The Classification Schemes used for the study
S/No Classes Description
1 Water Body River, permanent open water, lakes, ponds, canals and reserviors.
2 Vegetation Trees, shrub land and semi natural vegetation, decidous, caniferous and mixed forests, palms, orchads, herbs, climbers, gardens and grasslands.
3 Wetland Marshy areas susceptible to flooding
4 Built-up All residential, commercial and industrial areas, villages settlements and transportation infrastructure
5 Bare land Fallow land, earth and sand infillings, construction and excavation sites, solid waste landfills and open space.
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2.6. Accuracy assessment Accuracy assessment was carried out in order to check the correctness of the supervised classification performed on each of the Landsat Imageries. This was done in ERDAS Imagine using the Accuracy Assessment tool. The positional accuracy assessment technique was applied using 400 randomly generated reference points for each image. The multispectral images of each epoch was used as reference data. Accuracy assessment of processed images were done in two ways: the overall accuracy and the Kappa Statistics. The overall accuracy of processed images was calculated using Equation 1.
1 푃 = ∑푚 푛 (1) 0 푁 푖=1 푖푖
Where nii= the total number of correctly classified points by class along the diagonal of the error matrix
P0 = Overall processing accuracy N = the total number of sampled points (Lo & Yeung, 2007). In the Kappa Statistics approach, the Kappa coefficient was computed using Equation 2.
푃 −푃 퐾푃 = 0 푐 (2) 1−푃푐
Where P0 = Overall processing accuracy given in Equation 1.
Pc= Expected accuracy, KP= Kappa Coefficient,
1 푃 = ∑푚 (푛 × 푛 ) (3) 푐 푁2 푖=1 푖+ +푖
Where ni+ = row sum by class
n+i = column sum by class m = the total number of classes (Lo & Yeung, 2007).
2.7. Methods of data analysis The methods of data analysis adopted include: (a) Total land use area, (b) Percentage land use area (c) Land use dynamics degree determined by percentage change, Land Consumption rate (LCR) and Land Absorption Coefficient (LAC). Total land use area (Km2) for each land use type in each epoch was obtained by the total sum of individual land use types in the study area. Equation 4 below shows how each Land use type area at each epoch was calculated:
퐿푈〗_(푎(푡)) = ((∑_(푖 = 1)^푛 (푥_푎퐸푖(푡) 푦_(푎퐸푖 + 1(푡) ) + 푥_(푎퐸푖 + 1(푡) ) 푦_(푎퐸푖 + 2(푡) ) + ⋯ 푥_(푎퐸푛 − 1(푡) ) 푦_푎퐸푛 ) − ∑ (푥_(푎퐸푖 + 1(푡)) 푦_(푎퐸푖(푡)) + 푥_(푎퐸푖 + 2(푡)) 푦_(푎퐸푖 + 1(푡)) − ⋯ 푥_푎퐸푖(푡) 푦_(푎퐸푛 − 1(푡)) ) ))/2 (4)
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From Equation 4, 퐿푈푎(푡) is the land use type (a) at epoch (t); 푥푎퐸푖…푛(푡) and 푦푎퐸푖…푛(푡) are the coordinates of each of the land use polygon in the study area. The percentage land use area was determined by a dynamic degree model that was expressed by Equation 5.
퐿푈푎푡 퐿푈% = ( 푛 ) × 100% (5) ∑푖=1 퐿푈푡
푛 Where, 퐿푈% is the percentage land use, 퐿푈푎푡 is land use type (a) at epoch (t) and ∑푖=1 퐿푈푡 is the summation of all types of land use at epoch (t). Percentage land use change was computed using Equation 6.
푛 퐿푈푡푘−퐿푈푡푚 퐿푈푅 = ∑푖=1 ( ) × 100% (6) 퐿푈푡푚
Where 퐿푈푅 is the land use rate, 퐿푈푡푘is the land use type at the end of monitoring period and 퐿푈푡푚 is the land use type at the beginning of monitoring period. Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) were determined using Equations 7 and 8. LCR and LAC analysis is applied only to the built-up land use. Built-up land use is the measure of urban development in the study area, LCR is equal to the measure of progressive spatial urbanization of a study area and LAC is equal to the measure of change of urban land by each unit increase in urban population (Olaleye et al., 2012).
퐴 퐿퐶푅 = (7) 푃
퐴 −퐴 퐿퐴퐶 = 푡푘 푡푚 (8) 푃푡푘−푃푡푚
Where A is the built-up areal extent (in hectares); P is the human population; 퐴푡푚 and 퐴푡푘 are the built-up area extents for early and later years while 푃푡푚 and 푃푡푘 are human population figure for early and later years respectively (Dadhich et al., 2017). In estimating human population at the required epoch, Equations 9 and 10 were used.
(푟푡) 푃16 = 푃06푒 (9)
푃 푃 = 91 (10) 86 푒(푟푡)
Where 푃86, 푃91, 푃06and 푃16are human population for 1986, 1991, 2006 and 2016 respectively; t is the time (years) between the base year and forecast year and r is the annual population growth rate. Osun state population data made available for 1991 and 2006 by National Bureau of Statistics (NBC, 2011) were used. In forecasting, human population for 1986, 1991 census data was used as data for base year, 2006 census data was used as base year data to forecast population for 2016. The population growth rate of 3.2% as published by NBC (2018) was used in this study.
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3.0. Results and Discussion 3.1. Accuracy assessment results Kappa coefficient of between 0.61 and 0.80 are interpreted to be of “substantial agreement” while between 0.41 and 0.60 are interpreted as “moderate agreement” (Landis and Koch, 1977).The results of the accuracy assessment presented in Table 4 shows that 1986 and 2016 results fall within the category of substantial agreement where result of 2006 is only of moderate agreement. This again confirms the poor quality of 2006 image as earlier observed. However, with moderate agreement, 2006 results are still suitable for analysis of land use changes, although results of 1986 and 2006 would be more reliable.
Table 4: Results of accuracy assessment
Year 1986 2006 2016 Accuracy (%) 69.67 63.18 76.67
Kappa Statistic 0.6182 0.5836 0.7083
3.2. Land use Change Results and Analysis The results are presented in form of maps, charts and statistical tables. They include the static, change and projected land use land cover of each class. Figures 4, 5 and 6 are the results of static land use maps for 1986, 2006 and 2016.
Figure 5: Thematic land use map of Osun state for 1986.
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Figure 6: Thematic land use map of Osun state for 2006
Figure 7: Thematic land use map of Osun state for 2016.
It could be observed from Figures 5, 6 and 7 that the built-up area experienced steady growth from one epoch to another while vegetation reduced. The area of land use classes in each epoch and the percentages area computed from Equation 5 is presented in Table 5.Area coverage for each land use type and the changes observed could be better appreciated using Figure 8.
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Table 5: Land use area and percentage of land use area in each epoch
2 Land use Land use area (km ) Percentage land area classes 1986 2006 2016 1986 2006 2016
Waterbody 226 223 224 2.44 2.41 2.42
Vegetation 3317 2883 2206 35.82 31.14 23.83
Wetland 1853 1854 1852 20.01 20.03 20.01
Built up 1900 2843 3190 20.52 30.71 34.45
Bare land 1963 1455 1787 21.20 15.72 19.30
3500 ) 2 3000 2500 2000 1500 1000
500 Land Use LandUse Area (Km 0 Waterbody Vegetation Wetland Built up Bare land
Land Use Classes 1986 2006 2016
Figure 8: Land use area in each epoch
From Table 5, the poor quality of 2006 image appear to affect some of the results obtained. For example, Waterbody reduced from 226Km2 in 1986 to 223Km2 in 2006 and then increased to 224Km2 in 2016. This trend of change in water area is uncommon especially when the images used were captured in the same season. However, it is possible to ignore this since the changes under reference are marginal and error can equally be attributed to sources other than the image quality. From Figure 8, changes in waterbody and wetland appear to be insignificant as compared to changes observed in other land use types such as built-up. This could be attributed to the fact that the images were acquired in the same season, although marginal reduction in waterbody and wetland are recorded. Changes in all the land use types and the percentage change as computed by using Equation 6 are as tabulated in Table 6. From Table 6, it can be observed that the majour changes observed from one epoch to the other are principally in built-up and vegetation classes. These changes are clearly seen in Figure 9.
Table 6: Area and percentage changes in land use (km2)
Area change in land use (km2) Percentage of land use change Classes 1986–2006 2006-2016 1986-2016 1986–2006 2006-2016 1986-2016 Waterbody -3 1 -2 -1.33 0.45 -0.88 Vegetation -434 -677 -1111 -13.08 -23.48 -33.49 Wetland 1 -2 -1 0.05 -0.11 -0.05 Built up 943 347 1290 49.63 12.21 67.89 Bare land -508 332 -176 -25.88 22.82 -8.97
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1500
) 2 1000
500
0 Waterbody Vegetation Wetland Built up Bare land -500
-1000 Changes Changes inLamd use types(Km -1500 Land use classes
1986-2006 2006-2016 1986-2016
Figure 9: Changes in Land use types from one epoch to another
Results for Land Consumption rate and Land Absorption coefficient are presented in Table 7.
Table 7: Land consumption rate and land absorption coefficient
S/N Year Population Land consumption rate Year Land absorption coefficient
1 1986 1,904,555 0.099760837 1986/2006 0.062351
2 2006 3,416,959 0.083202637 2006/2016 0.026928
3 2016 4,705,589 0.067791726
Land consumption rate (LCR) is a measure of compactness of urban developments in an area or city. The results of LCR was 0.099 in 1986, 0.083 in 2006 and 0.068 in 2016. LCR decreases from 1986 to 2016, this means that the cities in Osun state are becoming less compacted from 1986 to 2016. This decrease can be attributed to the fact that new areas are being developed with far less level of compactness and thus, reduces the general results of LCR in later years. It is important to note that most cities in Osun state are ancient and traditional where people with common progenitor lives together in what are referred to as “compounds”. It is a recent development to have someone live in a secluded environment, away from members of his/her extended family, which could be referred to as an adaptation from the colonial masters. These results therefore suggest that more people are building homes and living away from members of their extended family. However, the LCR values are still very high using LCR classes suggested by Dadhich et al., (2017) where LCR value of above 0.012 are classed to “very high” category. This result could justify the report by Encyclopaedia Britannica (2015) that Osun has highest number of cities (10 cities) in Nigeria, followed only by Lagos and Niger with 7 cities each. It is a typical occurrence in Osun State to find two to three towns as one large city such as Ikirun/Iragbiji/Aagba/Ororuwo and Ikire/Apomu/Ikoyi. Althogh these towns may see themselves as separate entities, its effect on the global environment is that of one large city. Secondly, these cities are close to one another. For instance, Ikirun, Osogbo and Ede are cities where one can live in one of the cities and work in the other because travelling from any of these cities to the other takes not more than half an hour. The Land Absorption Coefficient (LAC) computed for 1986/2006 and 2006/2016 are 0.062 and 0.027 respectively. This result suggests that the rate at which new land is acquired for development is very high. The high rate of LAC could partly explain the
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4.0. Conclusions i. Built-up and Vegetation land use types experienced tremendous changes in the thirty-year period considered in this study. Other land use types experienced far less changes within the same period (Table 6). ii. The rate of change in built-up class is positively high (67.89%) within the 30 year period under consideration (Table 6). Should this rate remain for another thirty years, this could mean that the larger percentage of vegetated land would have been converted to built-up. iii. It could be suggested that bare land is significantly a transition stage between built-up and vegetation since what constitutes bare land at a previous epoch could be significantly obtained from what constitutes built-up class in the following epoch (Table 5). iv. There is generally a high level of crowdedness in Osun state based on the LCR value obtained in each epoch (Table 7). This could be attributed to the presence of many more cities in the state. v. The high rate of increase in built-up class along with highly compacted cities could lead to drastic reduction in arable land for agricultural purposes which in turn could result to threat to food security and negative environmental implications.
Based on the results obtained from this study, the following are hereby recommended: i. A new policy on urban renewal is urgently required across Osun state which will transform the old residential areas into modern settlements with desirable facilities. This will reduce the rate of city expansion that could consume substantial part of the vegetation cover; ii. There is the need for a renewed reforestation effort to cushion the effects of high rate of city expansion.
References Adeniyi, P.O and Omojola, A. (1999). Landuse/landcover change evaluation in SokotoRima basin of north-western Nigeria on archival remote sensing and GIS techniques, Journal of African Association of Remote Sensing of the Environment (AARSE), 1, pp. 142-146 Ajala, O. A and Olayiwola, A. M. (2013). An assessment of the growth of Ile-Ife, Osun state Nigeria, using multi-temporal imageries, Journal of Geography and Geology, 5(2), pp. 43-54.
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Arshad, A. and Shahab, F. (2012). Quantification of Land Transformation Using Remote Sensing and GIS Techniques, American Journal of Geographic Information System, 1(2), pp. 17-28. Barsi J. A., Schott J. R., Palluconi F. D., Helder D. L., Hook S. J., Markham B. L., Chander G. and O'Donnell E. M. (2003). +“Landsat TM and ETM thermal band calibration, Canadian Journal of Remote Sensing, 29(2), pp. 141-153. Dadhich, A. P., Goyal, R. and Pran N. D. (2017). An Assessment of Urban Space Expansion and Its Impact on Air Quality Using Geospatial Approach, Journal of Urban and Environmental Engineering, 11(1), pp. 79-87. Ezeomedo, I.C. (2006). Change analysis of land use/land cover of Yola Metropolis to aid planning for a sustainable development. B.Tech. Project Submitted to the Department of Surveying and Geoinformatics, Federal (Moddibo-Adama) University of Technology Yola, Nigeria. Fatusin, A.F., Oladehinde, G.J. and Ojo, V. (2019). Urban Expansion and Loss of Agricultural Land in Osogbo, Osun State Nigeria, using Multi-Temporal Imageries. Journal of African Real Estate Research, 4(1), pp.139-156 Gasu, M. B. Ebehikhalu, N, Bidmus, M. A. and Dawam, P. D. (2016), Geospatial analysis of land use dynamics in Osogbo between 1986 and 2012, Abuja Journal of Geography and Development, 4(1), pp. 52-68. Landis, J. R. and Koch, G. G (1977). The measurement of observer agreement for categorical data. Biometrics, 33, pp. 159-174. Lo, C. P. and Yeung, A. K. W. (Eds.) (2007). Concepts and Techniques of Geographic Information Systems (2nd ed.), Pearson Prentice Hall, Upper Saddle River, NJ. Lu, D., Mausel, P., Brondizio, E., and Moran, E. (2004). Change detection techniques. International journal of remote sensing, 25(12), pp. 2365-2401. National Bureau of Statistics (NBC, 2018). Demographic Statistics Bulletin 2017. Available at https://nigerianstat.gov.ng Ndukwe, N. K. (1997). Principles of environmental remote sensing and photo Interpretation, New Concept Publishers, Lagos Oladejo, S. O and Morenikeji, O. A, (2019). Assessment of Land Use Change using Remote Sensing and GIS Techniques in South Western Nigeria, Environmental Technology and Science Journal, 9(2), pp. 114-122. Olaleye, J.B., Abiodun, O. E. and Asonibare, R. O. (2012). Land-use and land-cover analysis of Ilorin Emirate between 1986 and 2006 using landsat imageries, African Journal of Environmental Science and Technology, 6(4), pp. 189 – 198. Omollo, W. O., Hayombe, P. O. and Owino, F. O. (2018). Spatio-Temporal Implications of Land Use Change in Kisii Town, Kenya, American Journal of Geographic Information System, 7(2), pp. 49-57 Orimoogunje, O. O. I., Oyinloye, R. O. and Soumah. M. (2009). Geospatial Mapping of Wetlands Potential in Ilesa, Southwestern Nigeria, FIG Working Week on Surveyors Key Role in Accelerated Development, Eilat, Israel. Oyinloye, R.O. and Oloukoi, J. (2012). Spatio-Temporal Assessment and Mapping of the Landuse Landcover Dynamics in The Central Forest Belt of Southwestern Nigeria, Research Journal of Environmental and Earth Sciences, 4(7), pp. 720-730. Richards, J.A. and Jia, X. (2006). Remote sensing digital image analysis, an analysis (Fourth Edition), Springer-Verlag, Berlin Heidelberg.
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Singh, A. (1989), Digital Change Detection Techniques Using Remotely Sensed Data. International Journal of Remote Sensing. Vol. 10, No. 6, p. 989-1003. Turner, B.L. II, Skole, D., Sanderson, S., Fischer, G., Fresco, L. and Leemans, R. (1995). Land-Use and Land-Cover Change; Science/Research Plan, IGBP Report No.35, HDP Report No.7. IGBP and HDP, Stockholm and Geneva, pp. 188. Zubair, A.O., (2006). Change detection in land use and Land cover using remote sensing data and GIS: a case study of Ilorin and its environs in Kwara State, Msc Thesis, University of Ibadan, Nigeria.
Cite this article as:
Abiodun, O.E. and Akinola, D.J., 2019. Mapping the Impact of Land Use and Land Cover Change on Urban Land and Vegetation in Osun State, Nigeria. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 317-330. https://doi.org/10.36263/nijest.2019.02.0146
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Nigerian Journal of Environmental Sciences and Technology (NIJEST)
www.nijest.com
ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 331 - 341
Studies on the effect of Cold Plastic Deformation and Heat Treatment on the Microstructural Arrangement and Corrosion Behaviour of Mild Steel in Acidic Media
Obayi C.S.1, 2,*, Nwobodo J.C.1, Neife S.I.2 and Daniel-Mkpume C.C.1
1Department of Metallurgical and Materials Engineering, University of Nigeria, Nsukka, Nigeria 2Department of Mechanical and Mechatronic Engineering, Alex Ekwueme Federal University, Ndufu-Alike, Ebonyi State, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0132
ABSTRACT
Mild steel is the most extensively used carbon steel for numerous industrial applications, where it is exposed to various service environments containing acids, bases and salt solutions. From industrial point of view, plastic deformation and heat treatment are among the essential manufacturing steps in mild steel processing and these steps can implicate its corrosion behaviour. This work investigated the effect of cold plastic deformation and subsequent high temperature heat treatment on the microstructure and corrosion behaviour of mild steel in two different concentrations (0.5M and 1.0M) of sulphuric acid (H2SO4), using the weight loss method. Mild steel samples were cold pressed to thickness reduction of 20%, 40% and 50% and subsequently heat treated at 700oC and 900°C and then air-cooled. The test duration lasted for 25 days and the weight loss measurements were taken at intervals of 5 days. It was observed that corrosion rates of the samples were generally higher in the 1.0M than in 0.5M acid solution. The as-received and heat-treated mild steel samples exhibited higher corrosion rates than the cold-pressed and heat-treated samples. The results indicated strongly that cold working accompanied by heat treatment improves corrosion resistance of mild steel in acidic media.
Keywords: Microstructure, corrosion behaviour, plastic deformation, heat treatment, mild steel, acidic media
1.0. Introduction
The study of corrosion of mild steel is of tremendous theoretical and practical concern due to its wide industrial applications and the need to prolong its life span in various service environments. Mild steel or low carbon steel is the most widely used carbon steel in various industries due to its availability, relative low cost, ease of fabrication, and adequate strength (Singh, et al., 2016; Zaafarany, 2013). For several years, mild steel in the form of plates and rods have found numerous applications as structural members in buildings, bridges, pipelines, ships, heavy vehicles and storage vessels (Osarolube, 1998; Clark and Varney, 1987). In these areas of application, mild steel is exposed to various service environments containing acids, bases and salt solutions, where it is prone to corrosion of the exposed surface. Mild steel has a major limitation of low corrosion resistance in various service environments containing acids and alkalis. Furthermore, from manufacturing point of view, plastic deformation and heat treatment or thermomechanical processing are among the inherent and essential steps in fabrication of mild steel structures (Giuseppe, et al., 2009) and these steps further affect its corrosion behaviour in the service environments. Thermomechanical processing modifies microstructure and the microstructural
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2.0. Materials and Methods 2.1. Materials The mild steel material in the form of plate of 5 mm thick was supplied by Auskan Co. Ltd, Kaduna State, Nigeria. The chemical composition of the mild steel determined via spectrometric analysis at Universal Steel, Ogba, Lagos State. is shown in Table 1. The corrosive media were 0.5M H2SO4 and 1.0M H2SO4. The solutions were prepared in the analytical laboratory of the Department of Pure and Applied Chemistry, University of Nigeria, Nsukka, Nigeria. Other materials were abrasive papers for grinding operations, glass beakers for containing the corrosive media, distilled water, and nylon threads for suspending the test specimens. The experimental setup was located at the Liquefied Natural gas (LNG) laboratory, University of Nigeria, Nsukka, Nigeria.
2.2. Methods 2.2.1. Cold pressing, heat treatment and microstructural examination Specimens were cut from the 5 mm-thick mild steel sheet and cold pressed to 20% (CP20%), 40% (CP40%) and 50% (CP50%) thickness reduction to achieve 4.0 mm, 3.0 mm and 2.5 mm thicknesses, respectively, using pneumatic hammer (MASSEY; England), at the Nigerian Railway Corporation, Enugu. The as-received and cold-pressed samples were heat-treated at 700°C and 900°C in a heat-treatment furnace (LABE 1210 Model, Delhi, India), soaked for one hour and air cooled. The samples were code named as follows: AR-700 and AR-900 for the as-received samples heat treated at 700°C and 900°C, respectively; CP20%-700, CP20%C-900, CP40%-700, CP40%-900, CP50%-700, and CP50%-900 for the samples cold pressed to 20%, 40% and 50% reduction, heat treated at 700°C and 900°C, respectively.
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The microstructure of the as-received mild steel, cold-pressed and heat-treated mild steel samples were examined using computerized metallurgical microscope equipped with digital camera and image analyser (Model mm39a00m, Labomed. Inc., USA). Prior to microstructural examination, the as- received, cold-pressed and heat-treated samples were cut and mounted in acrylic resin and wet ground with 320-1000 grit SiC papers and finally polished with 6µm and 1µm diamond suspension and 0.05 µm alumina paste. They were then etched using a 2% Nital solution to expose the grains and grain boundaries. The average grain diameters on the surfaces of the as-received and deformed samples annealed at 700°C and 900°C were obtained using the image analyzer. 2.2.2. Corrosion testing The corrosion behaviour of the as-received, cold-pressed and heat-treated mild steel samples was determined using weight loss or static immersion corrosion test method in two different concentrations of sulphuric acids (0.5 M and 1 M solutions), prepared from 98% analytical grade concentrated sulphuric acid using distilled water.The weight-loss tests were performed following ASTM G31-72 standard.The mild steel samples were cut into test size of 5x5x5 mm3for the as- received or control sample and test sizes of 5x5x4 mm3, 5x5x3 mm3 and 5x5x2.5 mm3 for 20%, 40% and 50% cold-pressed samples, respectively. The cut samples were polished with SiC papers up to 1000 grit, and then cleaned with ethanol, dried and weighed. The weighed specimens were fully and separately immersed in 200 mL of H2SO4 solution for 25 days at room temperature. Three test specimens of each subset were taken out every 5 days, washed with distilled water, rinsed with ethanol, dried and re-weighed.The weight-loss corrosion test set up is shown in Figure 1. The corrosion rate (CR) was determined based on the weight loss using Equation (1).
87.6푊 퐶푅 = (1) 푑퐴푡
Where CR is the corrosion rate in millimetre per year (mm/yr), W is the weight loss in grams (g), A is the exposed surface area (cm2), t is the time of exposure in hours, and d is the density of the specimen (7.85 g/cm3).
Wooden suspender
Nylon rope Beaker
Mild steel specimen H2SO4 solution
Figure 1: Weight-loss corrosion test set up
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3.0. Results and Discussion 3.1. Chemical composition of the mild steel The chemical composition of the mild steel determined via spectrometric analysis is shown in Table 1.
Table 1: Chemical composition of the mild steel Element C Ni Cr Mn Cu Mo S P
Weight % 0.1420 0.0410 0.0800 0.7090 0.0850 0.0001 0.0300 0.0300
Element Si Al Nb B Ti W V Fe
Weight % 0.2500 0.0080 0.0001 0.0001 0.0090 0.0001 0.0001 balance
3.2. Microstructure of the as-received, cold-pressed and heat-treated mild steel samples Figure 2 (a-l) shows microstructural evolution of the as-received, cold-pressed and heat treated mild steel samples, while Table 2 shows the average grain diametres of as-received and deformed samples annealed at 700°C and 900°C. The increase in average grain diametre as the heat treatment temperature increased can be observed in Figure 2 and in Table 2. The grain size evolution was also dependent on the degree of cold pressing and the higher the degree of cold pressing, the smaller the grain size. The as-received has the biggest grain size while the cold-pressed to 50% reduction has the smallest grain size at the heat treatment temperatures. The microstructure was considered in an attempt to correlate the corrosion behaviour with microstructural evolution.
Table 2: Average grain sizes for some of the mild steel samples
Materials code AR AR-700 AR-900 CP20%-700 CP20%-900 CP40%-700 CP40%-900 CP50%-700 CP50%-700
Average grain 30.2±3.3 37.1±2.5 49.1±2.2 32.1±2.2 38.8±3.9 24.2±1.8 29.6±3.2 21.4±2.7 26.8±1.9 size (µm)
Heat treatment of the as-received mild steel at 700°C and 900°C resulted in an increase in grain diameter as can be seen in Figure 1. The as-received grain structure was also diffuse at 900°C and was accompanied by initiation of carbide precipitation at the grain boundaries. For the as-cold pressed and heat-treated mild steel samples, the grain diameters were smaller than that of the as-received at the heat treatment temperatures. The grain size varied with the degree of cold work and heat treatment temperatures. The higher the degree of cold work, the smaller the grain size at each heat treatment temperature. This phenomenon might be attributed to the following reasons: An average grain size obtained after heat treatment is a function of prior strain (Priestner and Ibraheem, 2000). The amount of strain determines the rates of nucleation and subsequent grain growth of the recrystallized grains in a deformed state (Humphreys and Hatherly, 2004). Cold plastic deformation hastens grain subdivision due to the relatively higher dislocation density and substantial microstructural inhomogeneities introduced during deformation (Song, et al., 2006). The higher the degree of cold work, the higher the nucleation rate and the smaller the final recrystallized grain size (Humphreys and Hatherly, 2004; Anthonione, et al., 1977). That is why the mild steel sample cold pressed to the highest degree (50%) has the smallest grain size.
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Figure 2: Microstructure of the as-received and cold-pressed mild steel samples heat treated at 700°C and 900°C. 3.2. Corrosion behaviour of as-received, cold pressed and heat-treated mild steel samples Figures 3 and 4 are plots of weight loss and corrosion rate against corrosion test duration for the as- received mild steel and cold pressed mild steel samples heat treated at 700oC and immersed in 0.5M H2SO4 solution, respectively. Figures 5 and 6 show the weight loss and corrosion rate versus o corrosion test duration for the same set of samples heat treated at 900 C and immersed in 0.5M H2SO4 o o solution. These sets of samples heat treated at 700 C, 900 C and immersed in 0.5M H2SO4 solution exhibited similar corrosion behaviour. The maximum weight losses and corrosion rates of the samples occurred on the 5th day. However, the as-received mild steel (AR) has the highest weight loss and corrosion rate while the cold-pressed mild steel to 50% (CP50%) degree has the lowest weight loss and corrosion rate. The weight losses and corrosion rates of the mild steel samples cold pressed to 20% (CP20%) and 40% (CP40%) reduction lie between that of AR and (CP50%). It can also be
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observed in Figures 4 and 6 that corrosion rates of all the samples immersed in 0.5M H2SO4 solution consistently decreased after the 5th day to the 25th day. The weight loss and corrosion rate against corrosion test duration for the as-received mild steel and o cold pressed mild steel samples heat treated at 700 C and immersed in 1.0 M H2SO4 solution are shown in Figures 7 and 8 while Figures 9and 10 show the weight loss and corrosion rate against corrosion test duration for the as-received mild steel and cold pressed mild steel samples heat treated at 900°C and immersed 1.0M H2SO4 solution. These sets of samples immersed in 1.0M H2SO4 solution exhibited similar corrosion behaviour to those immersed in 0.5M H2SO4 solution. However, weight losses and corrosion rates were higher in 1.0M H2SO4 solution than in 0.5M H2SO4 solution. It is also noteworthy that the corrosion behaviour of the samples appears to be grain dependent as the as- received mild steel having the biggest grain size has the highest corrosion rate while the 50% cold- pressed sample which has the smallest grain size has the least corrosion rate in both acidic concentrations.
2.5
2.0
1.5
1.0 AR-700 CP20%-700 Weight loss(g) CP40%-700 0.5 CP50%-700
0.0 0 5 10 15 20 25 Duration (days) Figure 3: Weight loss vs corrosion test duration for the mild steel samples heat treated at 700oC and immersed in 0.5M H2SO4 solution.
2.0 1.8 AR-700 CP20%-700 1.6 CP40%-700 1.4 CP50%-700
1.2
1.0 0.8 0.6 Corrosionrate (mm/yr) 0.4 0.2 0.0 0 5 10 15 20 25 Duration (days)
Figure 4: Corrosion rate vs corrosion test duration for the mild steel samples heat treated at 700oC and immersed in 0.5M H2SO4 solution.
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3.5
3.0
2.5
2.0
AR-900 1.5 Weight loss(g) CP20%-900 1.0 CP40%-900 CP50%-900 0.5
0.0 0 5 10 15 20 25 Duration (days) Figure 5: Weight loss vs corrosion test duration for the mild steel samples heat treated at 900oC and immersed in 0.5 M H2SO4 solution.
3.0
2.5 AR-900 2.0 CP20%-900 CP40%-900 CP50%-900
1.5
1.0
Corrosionrate (mm/yr) 0.5
0.0 0 5 10 15 20 25 Duration (days) Figure 6: Corrosion rate vs corrosion test duration for the mild steel samples heat treated at 900oC and immersed in 0.5 M H2SO4 solution.
3.0
2.5
2.0
1.5
AR-700
Weight loss (g) loss Weight CP20%-700 1.0 CP40%-700 CP50%-700 0.5
0.0 0 5 10 15 20 25
Duration (days) Figure 7: Corrosion rate vs corrosion test duration for the mild steel samples heat treated at 700oC and immersed in 1.0M H2SO4 solution.
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2.5 AR-700 CP20%-700 2.0 CP40%-700 CP50%-700 1.5
1.0
Corrosionrate (mm/yr) 0.5
0.0 0 5 10 15 20 25 Duration (days) Figure 8: Corrosion rate vs corrosion test duration for the mild steel samples heat treated at 700oC and immersed in 1.0 M H2SO4 solution.
4.5 4.0 3.5 3.0 2.5 2.0 AR-900 1.5 CP20%-900 (g) loss Weight CP40%-900 1.0 CP50%-900
0.5 0.0 0 5 10 15 20 25 Duration (days) Figure 9: Weight loss vs corrosion test duration for the mild steel samples heat treated at 900oC and immersed in 1.0 M H2SO4 solution.
3.5 AR-900 3.0 CP20%-900 CP40%-900 2.5 CP50%-900
2.0
1.5
1.0 Corrosionrate (mm/yr) 0.5
0.0 0 5 10 15 20 25 Duration (days) Figure 10: Corrosion rate vs corrosion test duration for the mild steel samples heat treated at 900oC and immersed in 1.0 M H2SO4 solution.
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Generally, the weight losses and corrosion rates of as-received, cold pressed and heat-treated mild steel samples were higher in 1.0 M H2SO4 than in 0.5 M H2SO4 solutions. This is expected and is in agreement with the work of (Noor and Al-Moubaraki, 2008) who found out that the corrosion rates of mild steel increase with the increase in acid concentration. The weight losses and corrosion rates of cold pressed and heat-treated mild steel samples are also generally lower in both 0.5 M H2SO4and 1.0 M H2SO4 solutions than the as-received and heat-treated mild steel. This result suggests that cold work followed by heat treatment at high temperatures reduces dissolution rate in acid solution. Extreme cold work has been suggested to slightly improve the corrosion resistance of steel (Shamseldin et al., 1983). This result could be explained by considering that cold work followed by heat treatment refines microstructure and finer grain drives passivation kinetics or oxide formation (Ralston, et al., 2010) and enables the formation of more compact and stable passive films or oxides on the corroding surface (Ralston and Birbilis, 2010). The compact oxide films impede further dissolution of the cold pressed and annealed samples, especially the (CP50%) that possessed smaller grain structure as can be seen in Figure 2.
The corrosion rates of all the samples in both 0.5 M H2SO4 and 1.0 M H2SO4 solutions consistently decreased after the 5th day to the 25th day. This could be attributed to the initial aggressive effect of the acid on the surface of the mild steel specimens for the first five days, which decreased afterwards due to the formation of iron oxide (FeO) and accumulation of corrosion products, which somewhat impeded further dissolution of the samples in the acid solutions. The as-received and heat-treated mild steel had the highest weight loss and corrosion rate among other samples. This could be attributed to the fact that the heat treatment of low carbon steel at temperatures greater 850°Cleads to carbide precipitation along grain boundaries, thereby forming active galvanic cells and increasing anodic dissolution (El Din, et al., 1983; Shamseldin, et al., 1983).This could also be due to poor adsorption of oxides on the mild steel surface according (Iofa, et al., 1968) who has confirmed that annealing iron at higher temperatures (≥750°C) makes it less corrosion resistant due to reduced adsorption of passive oxides. Since nucleation and growth of oxide films on metals that exhibit some level of passivity increase with decrease in grain size (Ralston, et al., 2010), it follows that as-received and heat-treated mild steel which has bigger grain size than other samples would be less corrosion resistant due to poor oxide film adsorption on the surface.
4.0. Conclusion The effect of cold plastic deformation and heat treatment on the microstructure and corrosion behaviour of mild steel in two molar concentrations (0.5M and 1.0M) of sulphuric acid (H2SO4) solutions, using the weight loss method has been investigated. The key results of this investigation are as follows: i. Heat treatment of the as-received and cold pressed mild steel specimens at 700°C and 900°C modified their microstructures and resulted in an increase in their grain diameters, but grain diameter of the as-received was bigger than that of the cold-pressed samples at the heat treatment temperatures. ii. As expected, the corrosion rates of the samples were generally higher in the 1.0M than in 0.5M acid solution because corrosion rates of mild steel increase with the increase in acid concentration.
iii. The corrosion rates of all the samples in both 0.5 M H2SO4 and 1.0 M H2SO4 solutions consistently decreased from the 5th day to the 25th day, showing clearly that there was some level of oxide formation or passivation which impeded further dissolution of the samples in the acid solutions.
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iv. Noteworthy is the fact that the corrosion rates of cold pressed and heat-treated mild steel samples were generally lower in both 0.5 M H2SO4and 1.0 M H2SO4 solutions than that of the as-received and heat-treated mild steel sample. The result indicated strongly that cold work followed with annealing heat treatment improves corrosion resistance of mild steel in acidic media. v. Corrosion rates of the samples appeared to be grain size dependent as the as-received and heat- treated mild steel which had the biggest grain size had the highest corrosion rate, while the sample cold pressed to 50% (CP50%) and heat-treated had the smallest grain size and was the most corrosion resistant.
References Abbaschian R., Abbaschian L., Reed-Hill R.E., (2009). Physical metallurgy principles (4th ed.), CENAGE Learning, Australia. Anthonione C., Marino F., Riontino G., Tabasso M.C., (1977). Effect of slight deformations on grain growth in iron. Journal of Materials Science, 12, PP. 747-750. Clark D.S. and Varney W.R. (1987). Physical metallurgy for engineers. Van Nostrand Reinhold Ltd., Canada. El Din, A.S., El Kader, J.A., El Wahab, F.A., Hegazy, H., (1983). Effect of cold work on anodic polarization of low carbon steel. Journal of Materials science, 18, pp. 2732-2742. Finley, T.C. and Meyers, J.R., (1970). Effect of cold work on anodic polarization of Fe in sulphuric acid. Corrosion, 26(4), pp. 150-152. Foroulis, Z.A.; Uhlig, H.H., (1964). Effect of cold-work on corrosion of iron and steel in hydrochloric acid. Journal of the Electrochemical Society, 111(5), pp. 522-528. Giuseppe P.P.A., De Camargo B., Marcelo A. F., (2009). Plastic deformation analysis of low carbon steel due to metal hole punching using coated and uncoated tools. Journal of Brazil Society of Mechanical Science & Engineering, 3I (1), pp. 52 - 56. Greene N. and Saltzman G., (1964). Effect of plastic deformation on the corrosion of Iron and steel. Corrosion, 20, pp. 293t – 298t. Hodowany, J., et al., (2000). Partition of plastic work into heat and stored energy in metals. Experimental Mechanics, 40(2), p. 113-123. Humphreys, F.J. and Hatherly, M., (2004). Recrystallization and related annealing phenomena (2nd ed.). ELSVIER, United Kingdom. Iofa Z., Batrakov, V., Nikiforova, Y.A., (1968). On the influence of deformation and heat treatment of Fe on adsorption and action of corrosion inhibitors. Corrosion Science, 8, pp. 573-582. Noor, E. A. Al-Moubaraki A. H., (2008). Corrosion behaviour of mild steel in hydrochloric acid solutions, International Journal of Electrochemical Science, 3, pp. 806-818. Obayi C.S., Nnamchi P.S., Tolouel R., Okorie B.A., Mantovani D., (2018). Crystallographic texture- dependent dissolution of thermomechanically processed biodegradable pure iron, Journal of Metallurgy & Materials Engineering, 11(1), pp. 77-86. Osarolube E., (1998). Effect of prior cold reduction on the properties of heat treated low carbon steel. Nigerian Journal of Physics, 10, pp. 133-136. Priestner R. and Ibraheem A.K., (2000). Processing of steel for ultrafine ferrite grain structures. Materials Science. Technology, 16 pp. 1267-1272.
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Ralston K. and Birbilis N., (2010). Effect of grain size on corrosion: a review. Corrosion, 66, pp. 075005-075013. Ralston K., Birbilis N., Davies C., (2010). Revealing the relationship between grain size and corrosion rate of metals. Scripta Mater, 63, pp. 1201-1204. Shamseldin, A.M., ABD Elkader, J.M., ABD EL Wahab, F.M., Hegazy, H.S., (1983). Effect of cold work on anodic polarization of low carbon steel. Journal of Materials Science, 18, pp. 2732 – 2742. Singh, D.K., Kumar S., Dayabhanu G.U., John R.P., (2016). 4(N,Ndimethylamino)benzaldehyde nicotinic hydrazone as corrosion inhibitor for mild steel in 1M HCl solution: An experimental and theoretical study. Journal of Molecular Liquids, 216, pp. 738-746. Song, R., Ponge, D., Raabe, D., Speer, J.G., Matlock, D.K., (2006). Overview of processing, microstructure and mechanical properties of ultrafine grained bcc steels. Materials Science and Engineering A, 441, pp. 1-17. Zaafarany I.A., (2013). Corrosion inhibition of mild steel in hydrochloric acid solution using cationic surfactant olyel-amido derivatives. International Journal of Electrochemical Science, 8, pp. 9531- 9542.
Cite this article as:
Obayi C.S., Nwobodo J.C., Neife S.I. and Daniel-Mkpume C.C., 2019. Studies on the effect of Cold Plastic Deformation and Heat Treatment on the Microstructural Arrangement and Corrosion Behaviour of Mild Steel in Acidic Media. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 331-341. https://doi.org/10.36263/nijest.2019.02.0132
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501 Vol 3, No. 2 October 2019, pp 342 - 351
Development of Asbestos-free Brake Pads Using Bamboo Leaves
Adekunle N. O.1, Oladejo K. A.2,*, Kuye S. I.3 and Aikulola A. D.4 1,3,4Department of Mechanical Engineering, Federal University of Agriculture, Abeokuta, Nigeria 2Department of Mechanical Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0126 ABSTRACT
Asbestos-based brake pads are not desirable due to the carcinogenic nature of asbestos. Organic asbestos-free brake automotive brake pad produced from bamboo leaves was evaluated in this study. Ground bamboo leaves were sieved into sieve grades of 100, 200, and 350 μm. The sieved bamboo leaves particles were then combined with 15 % steel dust, 10% graphite, 20% resin, Silicon Carbide varied five (5) times between 35-55 % and 0-20% respectively for each sieve grade to make brake pads of different ratios. The mechanical properties (hardness, compressive strength, density, porosity, wear rate, and flame resistance) of the produced samples were investigated. The results showed that the finer the particle size of the bamboo leaves, the better the mechanical properties of the produced samples. The results of this work when compared with those of the commercial (asbestos based) brake pad showed they were in close agreement except for the wear rate and porosity property. Therefore, bamboo leaves could be used in the production of asbestos free brake pads if the wear rate and porosity properties of the produced samples could be improved.
Keywords: bamboo leaves, compressive strength, density, flame resistance, hardness, porosity, swell, wear
1.0. Introduction
Brake pads are important component of disc brakes used in automotive and other applications (Elakhame et al., 2014). Brake pads are steel backing plates with friction material bound to the surface that faces the disk brake rotor (Aigbodion et al., 2010). The part of the brake pad that makes contact with the rotor is called the friction lining which is a composite material of four main components comprising frictional additives which determine the frictional properties of the brake pads and comprise a mixture of abrasives and lubricants; reinforcing fibre or structural materials that provide strength e.g. metal, glass, kevlar, and carbon, ceramic or natural fibres; fillers which reduce the cost and improve the manufacturability of brake pads; and binder that holds the components together (Chrysoula, 2014).
It is reported that asbestos is carcinogenic (Dagwa and Ibhadode, 2005; Aigbodion et al., 2010; Idris et al., 2015). By the arrangements, particulate materials that gradually wear from brake pads, especially those from disc brakes are carried away by air into the environment. The health risks that the use of asbestos based brake pads pose have brought about the need to explore other non-asbestos based alternatives that would not expose users to any health risks as well as meeting the basic requirements of selecting materials for the friction lining of brake pads (Chand et al., 2012). Various agro-waste products have been used over the years to replace the asbestos content in brake pads; some of them are maize husk, palm kernel, bamboo stem, banana peelings, palm slag, periwinkle shell, coconut shell, oil palm shell, bagasse, etc.
Bashar et al. (2012) formulated brake pad with multi composite including ground coconut shell filler, epoxy resin binder matrix, iron chips reinforcement, methyl ethyl ketone peroxide
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Fono and Koya (2013); Oladejo et al. (2007); developed automotive brake pad using palm kernel shell following the standard procedures employed by commercial manufacturers and the results obtained showed that the properties of palm kernel shell based brake pad satisfied the specifications of the Standard Organization of Nigeria (SON). Evaluation of brake pads developed from palm kernel fibres (PKFs) showed that the wear rate, coefficient of friction, noise level, temperature, and stopping time of the produced brake pads increased as the speed increases. The results also show that porosity, hardness, moisture content, specific gravity, surface roughness, and oil and water absorption rates remained constant with increase in speed.
Ikpambese et al. (2014) this review showed that researches all over the world today are focusing on ways of utilizing either industrial or agricultural wastes as sources of raw materials in the industry. These wastes utilization will not only be economical, but may also result in improved foreign exchange earnings and environmental control (Aigbodion et al. 2010). This research work evaluated bamboo leaf as a viable alternative to asbestos in brake pad production since bamboo has a higher compressive strength than wood, brick, or concrete and a tensile strength that rivals steel. It also contains element such as Calcium, Potassium and Iron in large quantity that are not harmful, in view of this it can be used to produce an eco-friendly and non- hazardous brake pad.
2.0. Materials and Methods
2.1. Materials The raw materials used in the production of bamboo leaves brake pads were: filler (bamboo leaves), binder (epoxy resin and hardener), reinforcement (steel dust), solid lubricant (graphite), and frictional additive/modifier (silicon carbide, SiC).
2.2. Equipment The laboratory equipment used for the production of the test-samples are hammer milling machine (Model 000T), sieves (grade sizes 100µm, 200 µm, and 350 µm), digital weighing scale, mixing pan, spatula, electric heater (220/240 Volts) and hydraulic press (maximum of 120 kN/cm2 capacity) (Model Pi00eh-Type, 100T-Capacity, Serial No-38280) located at Federal Institute of Industrial Research Oshodi (FIIRO) F.I.I.R.O Rd, Papa Ajao, Lagos, Nigeria.
2.3. Chemical analysis of Bamboo leaves Chemical analysis of bamboo leaves was carried out to determine the proportion of the elements. Chemical analysis of bamboo leaves shows that larger percentage of Calcium (205.57), Potassium (680.33) and Iron (70.57) mg/kg are present while other trace elements are Copper (8.32), Manganese (3.17) and Chromium (0.19) mg/kg.
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2.4. Preparation of raw samples Fresh leaves from a bamboo tree were collected and washed in order to remove contaminants and impurities. They were sun dried for four (4) weeks and cleaned. The leaves were ground into powder using a hammer mill and then sieved into different sieve sizes of aperture 100 μm, 200 μm, and 350 μm in the brake lining formulation as shown in Figure 1 below.
Figure 1: Ground and sieved sample of bamboo leaves.
2.5. Method of production of brake pad samples Production of brake pad consists of a series of unit operations including mixing, cold and hot pressing, cooling, post-curing and finishing (Gurunath, 2007). The constituent ingredients, bamboo leaves, steel dust, graphite, silicon carbide, and resin. Different composition and sieve grades (i.e. 100휇푚, 200휇푚, 350휇푚) of bamboo leaves, steel dust, graphite, silicon carbide powder and resin were added together in the ratio shown in Table 2 below. The combination was properly dry mixed in a mixer (Model 89.2 Ridsdale and Co ltd, Middlesbrough. Eng.) for 20 minutes until a homogenous component was formed and the mixture was transferred into a mould for cold pressing with a hydraulic press at 80 kN/cm2 and then conveyed into electric oven (Model Memmert, Western Germany) at a temperature of 150°C after which it was hot pressed at 100 kN/cm2 pressure for 2 minutes. After removing from hot mould, the brake pad was cured in an oven at a temperature of 120°C for 8 hours. The different composition variations led to the production of various samples with each sample weighing 100 g (i.e. samples A-E). Table 1 below shows the various compositions by mass of the various samples.
Table 1: Percentage composition (by mass) used in the production of samples of Bamboo leaves brake pads Percentage composition (%) by mass of material S/N Material A B C D E 1. Bamboo leaves 35 40 45 50 55 2. Epoxy resin 20 20 20 20 20 3. Steel dust 15 15 15 15 15 4. Graphite 10 10 10 10 10 5. Silicon carbide (SiC). 20 15 10 5 0
Figure 2: Plate of finished brake pad samples
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2.6. Method of sample characterization 2.6.1. Brinell hardness Test The Brinell hardness values of the samples were obtained using a manual analog hardness tester. Four (4) disc-shaped samples of diameter 22.70 mm from each of the mixtures were tested under the Brinell hardness testing machine using a 10 mm diameter steel ball indenter with a load of 3000 kgf. The Brinell hardness number (HBN) of each of the samples was then calculated using the formula proposed by (Elakhame et al., 2014)
2푃 퐻퐵푁 = (1) 휋퐷[퐷 − √퐷2 − 푑2]
2.6.2 Compressive strength test The compressive strength was carried out using Hounsfield Tensometer. The four samples of diameter 22.70 mm were subjected to compressive force by loading them continuously until failure occurred. The loads at which each failure occurred were recorded while both the tensile stress and strain at this point were calculated using Equation (2) according to Elakhame et al. (2014).
퐹 휎푒 = (2) 퐴0
2.6.3. Wear rate test The wear rate for the samples was measured using pin on disc machine by sliding it over a cast iron surface at loads of 10 N and 20 N, sliding speed of 125 rev/min and sliding distance of 2000 m. All tests were conducted at room temperature. The initial weight of the samples was measured using a single pan electronic weighing machine with an accuracy of 0.01 g. During the test, the pin was pressed against the counterpart rotating against a cast iron disc (hardness 65 HRC) of counter surface roughness of 0.3 μm by applying the load. A friction detecting arm was connected to a strain gauge held and the pin samples were vertically loaded into the rotating hardened cast iron disc. After running through a fixed sliding distance, the samples were removed, cleaned with acetone, dried, and weighed to determine the weight loss due to wear. The difference in weights measured before and after tests gave the wear of the samples (Aigbodion et al., 2010):
∆s Wear rate = (3) w
where: ∆w Weight difference of the sample before and after the test in milligrams (mg) S Total sliding distance in metres (m)
2.6.4. Density test The true density of the samples was determined by weighing the samples mass on a digital weighing machine and dividing by measuring their volume by liquid displacement method in accordance with Shehu et al. (2014).
푀 휌 = ⁄푉 (4)
2.6.5. Porosity A sample of diameter 29.40 mm with a different height thickness of as thick as possible was used. The mass of specimen was weighed to the nearest mg, and then soaked in oil and water container at 90-100oC for 8 hours. The samples were left for 24 hours and then taken out. Finally, the test samples were weighed to the nearest mg. The porosity was determined as suggested by Elakhame et al. (2014).
푀 − 푀 100 휌 = 2 1 × (5) 퐷 푉
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2.6.6. Flame resistance test About 1.20g ± 0.1g of the samples were weighed in a cooled crucible previously oven dried by heating in a furnace at 550°C for 1 hour. Then the samples were charred by heating in a hot plate, thereafter the charred samples were taken into the furnace and heated at 550°C for 1 hour. It was then cooled in a desiccator and weighed. This process of heating, cooling and reweighing was repeated until a constant weight was obtained.
푊 − 푊 %푎푠ℎ = 2 0 × 100 (6) 푊1 − 푊0 Where: W0 Weight of empty crucible W1 Weight of crucible + sample, and W2 Weight of crucible and residue i.e. after cooling.
3.0. Results and Discussion
3.1. Chemical analysis of bamboo leaves The result of chemical analysis of bamboo leaves indicating the elements present is shown in Table 2. It shows that the major element in the bamboo leaves used is potassium followed by calcium, iron, while the trace elements present are manganese, copper and chromium.
Table 2: Chemical composition (by mass) of constituent element in bamboo leaves particles Metals Values (mg/kg) Calcium (Cu) 205.57 Potassium (K) 680.33 Manganese (Mn) 3.17 Iron (Fe) 70.57 Copper (Cu) 8.32 Chromium (Cr) 0.19 Nickel (Ni) 0.00
3.2. Brinell hardness test Figure 3, shows the results of Brinell hardness test carried out. It can be seen that as the sieve grade decreases, the hardness values of each sample increase. Sample size of 100휇푚 had the highest hardness value of 258, 237, 231, 226, and 210 BHN for samples A, B, C, D, and E respectively. This can be attributed to increase in surface area due to reduced particle size which allowed for increased binding ability with the resin. There is also a significant decrease in hardness values (as seen from Figure 2) of the samples of higher sieve grades (i.e. 200휇푚 and 350휇푚). The results obtained from the hardness test for this material (i.e. bamboo leaves) were better when compared with the standard, commercial (asbestos based) brake pads as shown in Table 3. As result of this 100μm or lower sieve grades are recommended for the production of the brake pad.
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300
250
200 Sample A Sample B 150 Sample C 100 Sample D
Hardness Hardness Value,(HRB) Sample E 50
0 0 100 200 300 400 Sieve Grade, (μm) Figure 3: Variation of hardness values with sieve grades
3.3. Compressive strength test Figure 4 shows the result of the compressive strength and peak values respectively for the produced samples with the sieve sizes. The 100 휇푚 sieve grade had the highest compressive strengths of 111, 109, 107, 106 and 101 Mpa for samples A, B, C, D, and E respectively; and the highest peak values of 23.181, 25.614, 22.598, 22.287, and 21.293푁⁄푚푚2 for samples A, B, C, D, and E respectively. It can be observed that the peak values and compressive strengths of each sample decreases gradually as the sieve size increases; this is so because the surface area and pore packaging capability of the bamboo leaves particles in the resin are decreasing with increasing particle size. It can be clearly seen in the Figure 4 that 100μm sieve grade gives a better compressive strength.
120
100
80 Sample A Sample B 60 Sample C 40 Sample D Sample E 20
Compressive Compressive Strength,(N/mm2) 0 0 100 200 300 400 Sieve Grade, (μm) Figure 4: Variation of compressive strength with sieve grades
3.4. Wear Rate Test The wear rates for the samples are presented in Figure 5 below, it can be seen that the sample wear rates increased as the particle size of the bamboo leaves increased and that the 100휇푚 samples had the least wear rate values. This is due to the fact that smaller particles allow for higher or closer packaging which led to stronger binding of the bamboo leaves particles within the composition. This may also be due to the high hardness values and compressive strength of the samples obtained as the sieve size decreased which was in agreement with what was observed in Elakhame et al., 2014. In order to produce a durable and acceptable brake pad that will not fade away quickly, it is advisable to use 100휇푚 samples with least wear property.
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14.2 14 13.8
2 13.6 13.4 Sample A 13.2 Sample B 13 Sample C 12.8 Sample D 12.6 Wear Wear Rate (.g/km) x 10 Sample E 12.4 12.2 12 0 50 100 150 200 250 300 350 400 Sieve Grade (m) Figure 5: Variation of wear rates of samples produced with different sieve grade.
3.5. Density Test Figure 6 shows graphical illustration of the plot of density against sieve grades of the samples and the density values generally increased as the percentage composition of bamboo leaves increased, this is due to the fact that the density of bamboo leaves increases as more and more of it is added to the composition of each sample which in turn increases the overall density of the samples. Furthermore, it was also observed that as the particle size of bamboo leaves increased, the density values decreased except for some isolated cases as seen in Figure 6. This is due to the fact that for smaller particles, the compressibility was higher because they were more porous i.e. the decrease in density can be attributed to the increase in particle size which allowed for increased packing. The 100 μm had the highest density which was as a result of closer packing of bamboo leaves particles creating more homogeneity in the entire phase of the composite body. This result agrees with what was observed in Aigbodion et al. (2010). Due to better performance of sample produced with 100 μm sieve grade, it is recommended that 100 μm sieve grade can be considered in the production of brake pad using bamboo leaves.
2.5
2
3) Sample A 1.5
g/cm Sample B Sample C
1 Sample D Density ( Density Sample E 0.5
0 0 50 100 150 200 250 300 350 400 Sieve Grade (m) Figure 6: Variation of density with sieve grades
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3.6. Flame resistance test The ash content properties of the produced samples increased as the sieve grade increased as shown in Figures 7. This can be attributed to the fact that as the particle size increases there is a corresponding increase in the pore sizes of the sample hence, for safety of vehicle, the brake pad should be made of smaller particles such as 100 μm sieve grade or lesser grade particle sizes. . 60
50
40 Sample A Sample B 30 Sample C 20
Ash Ash Content (%) Sample D
10 Sample E
0 0 50 100 150 200 250 300 350 400 Sieve Grade (m) Figure 7: Variation of ash content with sieve grades
3.7. Porosity Test Figure 8 shows the porosity test curves for the samples, the porosity of the produced samples increased as the sieve grade increased, this can be traced to the fact that there is an increase in the number and size of pores in the samples as the sieve size increases. It can be observed from Figures 8, that sample with 100휇m gave the best properties as a result of a very good dispersion of the bamboo leaves particles as seen in subsequent samples.
10 9 8 7 Sample A 6 Sample B 5 Sample C 4 Porousity(%) Sample D 3 Sample E 2 1 0 0 50 100 150 200 250 300 350 400 Sieve Grade (m) Figure 8: Variation of porosity (in water) with sieve grades.
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Table 3: Comparison between properties of asbestos brake pad and bamboo leaves brake pad produced. Properties Commercial Brake Pads Sample A Sample B Sample C Sample D Sample E Hardness (at 3000kgH) 101 258 237 231 226 210 Compressive strength (MPa) 110 111 109 107 106 101 Average wear rate (g/km× 10-2) 3.800 12.211 12.231 12.263 12.561 13.782 Density (g/cm3) 1.320 1.746 1.519 1.964 1.806 1.346 Porosity (%) in water 0.52 7.37 7.41 7.56 8.11 8.89 Flame resistance (%) Charred with 54% ash 46% ash 46% ash 45% ash 43% ash 43% ash
4.0. Conclusions
It could be concluded that samples with 100 μm sieve grade of bamboo leaves generally gave the best properties in terms of compressive strength, hardness, and density. Based on the above test properties of these brake pads composite using bamboo leaves as filler, bamboo leaves could be used in the production of asbestos free brake pads if the wear rate and porosity properties of the produced samples could be improved.
Acknowledgements The authors would like to acknowledge Department of Mechanical Engineering, Obafemi Awolowo University, and Department of Mechanical Engineering, Federal University of Agriculture, Abeokuta, Nigeria, for supporting the present work through Research Fund.
References Abiodun, M. O., Adetan, D. A. and Oladejo, K. A, (2011), A Study of the Performance of Maize Starch based Cutting Fluids in the Turning of AISI 304 Stainless Steel, International Journal of Engineering Research in Africa, (JERA), 6, pp. 13–24, Switzerland.
Adetan, D. A. Adekoya, L. O. and Oladejo, K. A, (2007), An Improved Pole-and Knife Method of Harvesting Oil Palm, Agricultural Engineering International: the CIGR Ejournal, Vol. IX, Manuscript PM 06027. USA.
Aigbodion, V. S. Akadike, U., Hassan, S. B. Asuke, F. and Agunsoye, J. O, (2010). Development of Asbestos - Free Brake Pad Using Bagasse, Tribology in industry, 32(1), pp. 12-18.
Chand, N. Hashmi, A. R. Lomash, S. S. and Naik, A. (2012), Development of asbestos free brake pad JMC, 85, pp. 13–16.
Chrysoula, A. A., (2014). Composites in Automotive Applications: Review on brake pads and discs, Research Development: Literature Review, University of Bristol; November 12, pp. 1-13.
Bashar, D. A, Peter, B. M. and Joseph M., (2012), Material selection and production of a cold worked composite brake pad, World Journal of Engineering and Pure and Applied Sciences, 2(3), pp. 92-97.
Dagwa, I. M. and Ibhadode, A. O. A. (2005). Design and manufacture of experimental brake pad test rig, Nigerian Journal of Engineering Research and Development, 4(3), pp. 15–24.
Edokpai, R. O. Aigbodion, V. S. Obiorah, O. B. and Atuanya C. U. (2014), Evaluation of the Properties of Ecofriendly Brake Pad Using Egg Shell Particles–Gum Arabic, Science Direct, Elsevier B.V. DOI: 10.1016/j.rinp.2014.06.003.
Elakhame, Z. U., Alhassan, O. A. and Samuel; A. E. (2014). Development and Production of Brake Pads from Palm Kernel Shell Composites. International Journal of Scientific and Engineering Research, 5(10), pp. 735-744.
Fono-Tamo, R. S. and Koya, O. A. (2013). Characterization of Pulverized Palm Kernel Shell for Sustainable Waste Diversification, International Journal of Scientific and Engineering Research, 4(4), pp. 6-10.
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Idris, U. D. Aigbodion, V. S. Abubakar, I. J. and Nwoye, C. I, (2015). Eco-friendly asbestos free brake-pad: Using banana peels, Journal of King Saud University – Engineering Sciences, 27, pp. 185– 192.
Ikpambese, K. K. Gundu, D. T. and Tuleun; L. T. (2014). Evaluation of palm kernel fibers (PKFs) for production of asbestos-free automotive brake pads, Journal of King Saud University – Engineering Sciences, pp. 1-9
Oladejo, K. A, Olaniyan, A, Obayopo, S. O, and Abu, R, (2007), Computer-Based Simulation in Thermal Energy Education and Research, Proceedings of the 20th National Mechanical Engineering Conference, pp. 81 – 89, Kaduna, Nigeria.
Shehu, U., Aponbiede, O., Ause, T. E. and Obiodunukwe, F., (2014). Effect of particle size on the properties of Polyester/Palm Kernel Shell (PKS) Particulate Composites, J. Mater. Environ. Sci., 5(2), pp. 366-373.
Osterle, W., Griepentrog, M., Gross, T. and Urban. I (2001) Chemical and microstructural changes induced by friction and wear of brakes, Wear, 251, pp. 1469–1476.
Cite this article as: Adekunle N. O., Oladejo K. A., Kuye S. I. and Aikulola A. D. Development of Asbestos-free Brake Pads Using Bamboo Leaves. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 342-351. https://doi.org/10.36263/nijest.2019.02.0126
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Strength and Workability Assessment of Concrete Produced by Partial Replacement of Cement with Waste Clay Bricks
Nwankwo E.1,* and John A. T.1 1Department of Civil Engineering, University of Benin, Benin City, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0137
ABSTRACT The use of waste clay bricks—which are abundant in the Niger Delta Region of Nigeria – as supplementary cementitious material, would enable the construction industry utilize thousands of tons of brick blocks that would have ended up as waste or landfill materials. This paper establishes the pozzolanic properties of these waste clay bricks in terms of strength and workability. Waste clay brick powders are introduced as partial replacement for cement in this research. All tests were done in accordance with relevant British Standards. It was observed that waste clay brick, as an admixture, increases the workability and consistency of fresh concrete. Also, an 11 percent increase in compressive strength was observed with a 10 percent partial replacement of cement with waste clay brick powders. An equation is developed to capture the marginal increase in compressive strength of concrete produced with waste clay bricks, even after 28 days, for a 10% partial replacement of cement. Keywords: Cement, Strength, Compression, Aggregate and Regression.
1.0. Introduction
To preserve the environment, attempts have been made to employ waste materials in the production of concrete and in the construction of cost-effective housing. Proper utilization of discarded or waste materials in concrete production results in less expensive concrete and also offers a cost-effective ecological solution to waste management and disposal (Bahoria et al., 2013). Concrete comprises of cement, aggregates and water (Devi and Gnanavel, 2014 and Naik, 2008) – with cement as the binder material and the most expensive component. Cement production emits a green-house gas known as carbon dioxide (CO2). Imbabi et al (2012) estimated that cement production contributes 5% of the global green-house gas emissions. However, more recent works estimates that the total CO2 produced by the production of cement clinkers and the combustion of fossil fuel required to heat raw materials during cement production could contribute to as much as 8.6% of global CO2 emission (IEA, 2007 Miller et al, 2016). To manage the environmental effects of concrete production, modern techniques such as using milled brick blocks as an admixture or applying it directly to replace a portion of cement has become common practice and broadly viewed as acceptable in concrete works. It is important to note that supplementary cementitious materials reduce the amount of cement in concrete and thus reduces concrete’s susceptibility to cracking, heat generation and carbon dioxide emission. Research has confirmed the viability of certain construction waste products as suitable for use as supplementary cementitious materials, such as silica fume, blast furnace slag, fly ash, foundry sand, palm oil clinker (Rashad, 2016; Valcuende et al., 2015; Imbabi et al., 2012; Prabhu et al., 2014). These supplementary materials are grounded and heated to controlled temperatures to produce blended cements with improved economic and physical properties (Detwiler et al., 1996).
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Elinwa et al (2005) reported that the use of sawdust ash or wood ash as partial substitute in the matrix for mortar and concrete work not only acts as an economic substitute but also a reliable disposal method of said waste. Ranjodh et al. (2013) reported that brick dust can be used effectively to develop good quality selfcompacting fresh concrete with satisfactorily slump and setting time. The hardened properties of the self-compacting concrete improved daily till 28 days because of greater hydration of cement. Nassar and Soroushian (2012) reported that the chemical composition of glass powder makes it comparable to other cementitious materials. Hemraj and Kumavat, (2013) examined brick waste and inferred that it performs as a pozzolana and his results show that richer mixes give lower value of bulk density and higher values of compressive strength at replacement level up to 40% of sand, his findings contribute to the minimizing the impact waste using eco-efficient resources. Hasanpour (2013) also examined the possibility of using bricks powder/dust as replacement until 40%, he further established in his findings that although concrete developed may suffer slightly a loss in strength, his research confirmed brick powder has the potential to serve as pozzolana. The performance of grinded brick blocks powder in concrete works was researched experimentally. Some recent studies have attempted to investigate the pozzolanicity of clay bricks. Ulukaya and Yüzer (2016) examined the pozzolanicity of clay fired bricks using direct and indirect methods. Their investigation revealed that clay treated at 850°C can be regarded as the best pozzolan, and the pozzolanicity of clay bricks significantly changes the mechanical properties of crushed brick-lime mortars. Bediako (2018) examined that optimum cement replacement in concrete, where cement is replaced with Ground Waste Clay Bricks (GWCB. Bediako (2018) observed that compressive strength results indicated that the optimum Portland cement replacement with Ground Waste Clay Bricks (GWCB) was at 30 wt.%. Bricks, when milled to powder, can serve as a supplementary cementitious material, although it has not yet acclaimed the same status commercially (Rashed, 2014). Thus, this work attempts to investigate the pozzolanic properties of waste brick blocks, especially those produced with clays from Bayelsa State, Nigeria.
2.0. Materials and Method 2.1. Materials The materials used in this study are Portland cement, ground waste clay brick, aggregates, water. The Portland cement was a type I/II cement and Table 1 shows the chemical composition of the cement used in this research. The clay bricks, which were used as refractory surfaces for decommissioned kilns, were obtained in waste dumps in Bayelsa State but were manufactured in Warri, Delta states, using local clays. Table 2 shows the chemical composition of the waste brick clays used in this research. The studied potential pozzolan meets the ASTM C618 (ASTM, 2015) recommendation that for a suitable pozzolan, the summation of the SiO2, Al2O3 and Fe2O3 must not be less than 70%. The waste clay bricks obtained for this research were crushed to dust and processed into powdered form (see Figure 1). The aggregates (fine and coarse) used were obtained from the Wilberforce Islands in Bayelsa State in accordance with British Standards BS EN 12620:2013 (BSI, 2013). The maximum size of the coarse aggregate was 20mm. Clear portable water free from all harmful and extraneous matter was used for all the experiments as specified by the British Standards BS EN 1008:2002 (BSI, 2002).
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Table 1: Major components of cement (Oriji and Dulu, 2015)
Oxide Weight % CaO 59.60%
Fe2O3 3.22%
SiO2 20.62%
Al2O3 6.01% MgO 3.65%
SO3 2.46%
K2O 0.71%
Table 2: Major components of clay bricks (Osarenmwinda and Abel, 2014)
Oxide Weight % CaO 0.72%
Fe2O3 11.8%
SiO2 53.9%
Al2O3 17.75% MgO 0.6% ZnO 0.9%
Na2O 0.8% MnO 0.03
Cr2O3 0.04
K2O 3.3%
Figure 1: Waste bricks in crushed and powder forms
The locally obtained waste clay bricks, along with some fine and coarse aggregates were packed in bags and were transported from the Wilberforce Islands to the laboratory of Civil Engineering in Niger Delta University. The brick samples were crushed and ground to powder form, while the coarse aggregates were washed clean of mud traces. Finally, sieve analysis and specific gravity test on the samples were carried out after 12 hours of sun drying. The coarse and fine aggregates (max. size of 20mm) were uniformly graded in accordance with British Standards BS EN 12620:2013 (BSI, 2013).
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2.2. Method The concrete samples were produced by batching by volume for compressive tests. A nominal mix ratio of 1:2:4 was adopted for concrete production using Portland cement. Produced concrete using this mix ratio was used as the control. The brick powder as a partial replacement for cement weights, i.e. a partial replacement of cement from 0 to 20 percent by weight was adopted. A water/cement ratio of 0.45 was adopted for the research work. Slump tests were conducted for every batch of concrete produced. 150mm x 150mm x 150mm cube moulds were employed to be placeholders for the concrete, while the required tamping continued until adequate compaction on each cube mould was obtained, then the surface was finished with a trowel. The cubes remained stationary for 24 hours before they were demolded and placed in a curing tank. A total of 80 concrete cubes were cast. Table 3 shows the quantity of constituents required to produce 1 cubic metre of each sample used in this experiment using a water to cement ratio of 0.55.
Table 3: Mix quantities for 1 cubic metre of samples
Cement Brick powder Fine aggregate Coarse aggregate Mix name (kg) (kg) (kg) (kg) CON (Control) 300 0 690 1250 SAMPLE 1 (2% Cement replacement) 294 6 690 1250 SAMPLE 2 (5% Cement replacement) 285 15 690 1250 SAMPLE 3 (7% Cement replacement) 279 21 690 1250 SAMPLE 4 (8 % Cement replacement) 276 24 690 1250 SAMPLE 5 (10 % Cement replacement) 270 30 690 1250 SAMPLE 6 (12% Cement replacement) 264 36 690 1250 SAMPLE 7 (15 % Cement replacement) 255 45 690 1250 SAMPLE 8 (18 % Cement replacement) 246 54 690 1250 SAMPLE 9 (20% Cement replacement) 240 60 690 1250
2.2.1. Compressive Strength Test An Avery compression machine was used for the compression test experiment. The cast cubes are placed in the Avery compressive testing machine and loaded until their various compressive strengths were obtained. The cube strengths were obtained at 7, 14, 21, 28, 52 and 90 days. These tests performed were in accordance with the specifications in BS EN 12390-3:2019 (BSI, 2019a).
2.2.2. Workability test The workability of the fresh concrete for all the samples was determined by the slump test. These tests were performed in accordance with the specifications in BS EN 12350-2:2019 (BSI, 2019b).
3.0. Results and Discussion Experimental results showed that there was a marginal strength gain in concrete with a 10 percent partial replacement of cement with the waste clay bricks studied. An average of 11% increase in compressive strength was achieved with 10 percent partial replacement of cement with the waste clay bricks studied. However, as percentage replacement exceeds 10 percent, the positive impact of the pozzolan on the strength of concrete diminished. Interestingly, at 20 percent partial replacement of cement, there was no substantial strength loss in concrete, when compared with concrete made without partial replacement of cement. These results are similar to Bediako’s (2018) findings. Bediako (2018) observed that the compressive strength performance of the control mortar, in his work, and mortars that contained 10 wt.% and 20 wt.% of Ground Waste Clay Bricks (GWCB) were
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 352 - 360 statistically insignificant at 3, 7 and 28 days. In his work, the strength performance observed indicated that the optimum mortar mix was at Portland cement replacement with GWCB at 30 wt.%. This mix was approximately 11% higher in strength at the curing periods when compared with the control mortar. The optimal replacement level which improved the strength of mortar much better than the control mortar could be attributed to the degree of pozzolanic reaction. Bediako (2018) also mentioned that the achievement of maximum strength means that the cement replacement content with a pozzolan is sufficient to convert cement hydration product i.e. calcium hydroxide into calcium silicate and aluminate hydrates which enhance strength properties. This result of this work aligns with the findings of Bediako (2018). Bediako (2018) observed that the compressive strength performance of the control mortar, in his work, and mortars that contained 10 wt.% and 20 wt. of Ground Waste Clay Bricks (GWCB) at 3, 7 and 28 days were statistically insignificant. This work shows that despite the composition of local waste clay bricks used in this work, it is able to react cement hydration products i.e. calcium hydroxide, into calcium silicate and aluminate hydrates which enhance strength properties. Hence, a marginal increase in strength is observed. However, further work is required to understand the hydration process and chemistry of the reaction. Figures 2 and 3 present a comparison of strength developed with the partial replacement of cement with waste clay bricks. It is also observed that while the long-term strengths of normal concrete did not significantly increase from its value at 28 days up to 90 days (See Figures 4 and 5), the strength of concrete made with waste clay bricks increased by 10 percent at 90 days, when compared to its 28day strength.
Using least square regression approach, as shown in Equations 1, where fcu and x are dependent and independent variables, respectively; ri is the residual; β is a vector in the model function f (x, β)
푟푖 = 푓푐푢 − 푓(푥, 훽) (1)
And by minimizing the sum, S, of the squared residual, ri, in Equation (2), we obtain the relationship in Equation (3)
2 푆 = ∑ 푟푖 (2)
푓푐푢 = 19.8퐼푛(푥) + 16.4 (3) Equation 3 represents the relationship between strength development and duration for a 10 % partial replacement of sand with brick blocks. fcu represents the compressive strength and x represents duration in days. This equation predicts the compressive strength development between 0 to 90 days.
25
20
15 0 % Cement Replacement 10 5 % Cement Replacement 10% Cement Replacement 5
0 0 10 20 30 40 50 60 70 80 90 Duration (Days) Figure 2: Strength development with 0 – 10 percent partial replacement of cement with brick blocks
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25
20
10% Cement Replacement 15 15% Cement Replacement 20% Cement Replacement 10 0 % Cement Replacement
5
0 0 10 20 30 40 50 60 70 80 90 Duration (Days) Figure 3: Strength development with 10 – 20 percent partial replacement of cement with brick blocks
30
25 )
2 y = 1.9832ln(x) + 16.367 20 R² = 0.9566
15
10 Strength(N/mm
5
0 0 10 20 30 40 50 60 70 80 90 Duration (Days) Figure 4: Regression curve showing relationship between strength and duration for 10% cement replacement with brick blocks
25
20
15
10
5
0 0 10 20 30 40 50 60 70 80 90 Duration (Days) Figure 5: Regression curve showing relationship between strength and duration for 0% cement replacement with brick blocks
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Slump test results shown in Table 4 for the various concretes produced show that an increasing slump is achieved with an increasing cement replacement with brick blocks. This implies that with additional volume of fines from the brick blocks, consistency and workability increased in produced concrete. This result is indicative of a reduced water demand with increasing brick content.
Table 4: Slump test results
Percentage Replacement Slump (in mm) 0% 50 5% 55 10% 58 15% 63 20% 75
4.0. Conclusions Based on the outcome of the present investigation on the suitability of waste clay bricks as admixture in concrete works, the following conclusion can be drawn: i. Waste clay brick studied possess sufficient pozzolanic properties and can be used effectively as a supplementary cementitious material. ii. By replacing cement with waste clay bricks, in concrete production, a marginal increase in compressive strength can be achieved. iii. Waste clay bricks increases the durability of concrete with marginal increase in compressive strength, even after 28 day iv. An optimum strength of concrete is achieved with a 10 percent cement replacement with waste clay bricks. v. The workability and constituency of concrete is improved with the addition of waste clay bricks to cement in concrete production. It is recommended that a further study on the microscopic interaction of waste clay bricks and cement during hydration process be undertaken in order to fully understand the process of strength increase associated with the addition of bricks in concrete production.
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BSI (2002). BS EN 1008:2002. Mixing water for concrete. Specification for sampling, testing and assessing the suitability of water, including water recovered from processes in the concrete industry, as mixing water for concrete. British Standards Institution, UK. BSI (2011). BS EN 197-1:2011 Cement. Composition, specifications and conformity criteria for common cements. British Standards Institution, UK. BSI (2013). BS EN 12620:2013: Aggregates for concrete. British Standards Institution, UK. BSI (2019a). BS EN 12390-3:2019: Testing hardened concrete. Compressive strength of test specimens. British Standards Institution, UK. BSI (2019b). BS EN 12350-2:2019. Testing fresh concrete. Slump test. British Standards Institution, UK Detwiler, R., Bhatty, J.I and Bhattacharja, S., (1996). Supplementary Cementing Materials for Use in Blended Cements. Research and Development Bulletin Rd112t, Portland Cement Association, Skokie, Illinois, USA. Devi, V.S. and Gnanavel, B.K. (2014). Properties of concrete manufactured using steel slag. Procedia Eng. 97, 95–104. Elinwa, A.U. and Mahmood, Y.A (2002). Ash from timber waste as cement replacement material. Cement and Concrete Composites, vol. 24, no. 2, pp. 219-222. Elinwa, U, S. P. Ejeh and Akpabio, I.O (2005). Using metakaolin to improve sawdust ash concrete. Concrete International, vol. 27, no. 11, pp. 49-52 Hasanpour, A. H. (2013). Effects of waste bricks powder of Gachsaran company as a pozzolanic material in concrete. Asian journal of civil engineering (BHRC) VOL. 14, NO.5 (2013), 755-763. Hemraj R. and Kumavat, Y.N (2013). Feasibility Study of Partial Replacement of Cement and Sand in Mortar by Brick Waste Material. International Journal of Innovative Technology and Exploring Engineering, 17-20. IEA, 2007. International Energy Agency,’ Tracking Industrial Energy Efficiency and CO2 Emissions’. Paris, OECD/IEA. Available http://www.iea.org/publications/freepublications/.Mark Imbabi, M.S., Carrigan, C. and McKenna, S., (2012). Trends and developments in green cement and concrete technology. Int. J. Sustain. Built Environ. 1, 194–216. IPCC: 2006 IPCC Guidelines for National Greenhouse Gas Inventories, prepared by the National Greenhouse Gas Inventories Programme, edited by: Eggleston, H. S., Buendia, L., Miwa, K. Ngara, T., and Tanabe, K., IGES, Hayama, Japan, available at: http://www.ipcc- nggip.iges.or.jp/public/2006gl/index.html (last access: 21 May 2017), 2006 Miller, S.A, Horvath, A and Monteiro, Paulo J M (2016). Readily implementable techniques can cut annual CO2 emissions from the production of concrete by over 20%. Environmental Research Letters, Volume 11, Number 7 Naik, T.R. (2008). Sustainability of concrete construction. Part. Period. Struct. Des. Constr. 13 (2), 98–103. Nassar, R.U.D. and Soroushian, P. (2012). Strength and durability of recycled aggregate concrete containing milled glass as partial replacement for cement. Constr. Build. Mater. 29, 368–377. Osarenmwinda, J. O. and Abel, C.P (2014) Performance Evaluation of Refractory Bricks produced from locally sourced Clay Materials. J. Appl. Sci. Environ. Manage, Vol. 18 (2) 151-15 Prabhu, G.G., J.H. Hyun, Y.Y. Kim (2014). Effects of foundry sand as a fine aggregate in concrete production. Constr. Build. Mater. 70, 514– 521.
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Rashed, A.M., (2014). Recycled waste glass as fine aggregate replacement in cementitious materials based on Portland cement. Constr. Build. Mater. 72, 340–357. Ulukaya, S and Yüzer, N (2016). Assessment of pozzolanicity of clay bricks fired at different temperatures for use in repair mortar. Journal of Materials in Civil Engineering, Volume 28, Issue 8 Valcuende, M., Benito, F., Parra, C., Minano, I., (2015). Shrinkage of self-compacting concrete made with blast furnace slag as fine aggregate. Constr. Build. Mater. 76, 1–9. Yahaya, M.D. (2009). Physico-Chemical Classification of Nigerian Cement. AU J.T. 12(3): 164-174
Cite this article as:
Nwankwo E. and John A. T., 2019. Strength and Workability Assessment of Concrete Produced by Partial Replacement of Cement with Waste Clay Bricks. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 352-360. https://doi.org/10.36263/nijest.2019.02.0137
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Vol 3, No. 2 October 2019, pp 361 - 369
Assessment of Hospital Wastes Management Practices in Lagos, Nigeria, using Two Health Care Centres as Case Studies
Alani R.*,1, Nwude D.2 and Adeniyi O.1 1Chemistry Department, University of Lagos, Akoka, Lagos State, Nigeria 2Department of Chemical Sciences, Bells University of Technology, Otta, Ogun State, Nigeria *Corresponding Author: [email protected] https://doi.org/10.36263/nijest.2019.02.0121
ABSTRACT
Hospital wastes are highly infectious and can pose serious threat to human health. As the rate at which these wastes are generated is getting rapidly higher because of rapid urbanization and population growth, also the problem of disposal of these wastes is becoming more serious. It is of utmost importance that these wastes receive specialized treatment and management prior to their final disposal. Some of these wastes are mixed with household wastes, and the entire pile becomes a great public health hazard. Scavengers search through the piles for salable items, which they wash, repack and resell to the public, endangering their lives, and that of the entire public. Until recently, the management of medical wastes has received little attention despite their potential environmental hazards and public health risks. The collection, storage and disposal of medical wastes in Lagos are of growing environmental problem which needs immediate attention. This study was carried out to assess the current waste management practices in terms of type of wastes and quantities of waste generated in the healthcare facilities and the waste handling and disposal practices; also, to assess the level of awareness of health workers regarding hospital and clinical waste management. Two health care facilities in Lagos state were used as case studies. These hospitals are secondary facilities providing emergency, surgical, material and child health services. The methodology design was mainly of qualitative and involved physical observation, questionnaire administration, quantitative data collection procedures and manipulation, data analysis and interpretation. The findings showed that there was almost no knowledge of hospital waste management policy in the two health care facilities among the management staff, which seemed to confirm the premium on hospital wastes and their poor management.
Keywords: Lagos, Healthcare facilities, Hospital wastes, Waste management, Environmental health.
1.0. Introduction
Lagos is a mega city in Nigeria, which is highly populated with over 15 million of the total 150 million people in the country. The population is still growing at a very fast rate due to industrialization and urbanization. Environmental issues in such a city have to be properly managed to avoid outbreak of diseases, which could be very disastrous. As it is the case in other developing countries, health concerns in Nigeria are more on placing priorities on utilizing the available limited resources, rather than giving the well deserved attention to the management of healthcare wastes. The proper management of hospital or clinical wastes commonly referred to as health care wastes (HCW) is of great importance for the safety of the general public. HCW which comprise mostly of biological products are highly infectious and can be a serious threat to human health. Babatola (2008) reported an estimate of at least 1kg of infected wastes from every 4kg of waste generated in a hospital. It is good that more hospitals are springing up to cope with the growing populations in our country but it is of utmost importance that waste treatment facilities be put in place in all these hospitals for the protection of public health. There is a very low level of awareness of the health workers regarding healthcare waste, as well as lack of skills by the institutions engaged in hospital waste generation and disposal in the city. The world health
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 361 - 369 organization estimates that 15% of the waste generated at the health care facilities (HCFs) will be pathological and infectious waste which needs to be managed through the contracted medical waste management service (WHO, 2005a). Inappropriate handling and disposal of healthcare wastes poses health risks (that is a higher risk of disease like hepatitis and HIV/AIDS (Coker et al., 2008)) to health workers and to people near the health facilities, particularly children and scavengers to infectious wastes. It is not certain that there is much difference between how general wastes and HCW are managed in Nigeria. In a study in Lagos, Olubukola (2009) reported that the similarity in waste data and HCW management practices in two general hospitals is showing the similarity of lack of waste minimization or waste reduction strategies, poor waste segregation practices, lack of instructive posters on waste segregation and disposal of HCW with general waste. In the investigation on the medical waste categories and its management practices in five different hospitals as representative health care institutions in Port Harcourt city, Nigeria, Ogbonna et al., (2007) discovered that solid waste disposal method adopted by health institutions are preferably open dumpsites disposal methods while liquid wastes are mostly disposed of by flushing through drains/sinks. According to WHO Fact sheet No 253: Wastes from Healthcare Activities (WHO, 2007), the various reasons towards the poor waste management practices around the globe include the absence of waste management plan, lack of awareness about the health hazards, insufficient financial and human resources including poor control of waste disposal, lack of strict and appropriate regulations and the clear attribution of responsibility of appropriate handling and disposal of waste. This is the situation in Nigeria where the power to enforce activities that might impact the environment is vested in the federal ministry of environment (FMEnv) and the Federal Ministry of Health. There are national policies and legislations that have been put in place to take care of all kinds of environmental issues but the same reasons stated in the WHO fact sheet 253 (WHO, 2007) are the likely reasons for failure. Such national policies and legislations include the National Health Policy (NHP) (1988), National Policy on Environmental (1988), Environmental Protection Agency Decrees No 58 (1988), Anatomy Act (1990), National Policy on Injection Safety and Healthcare Waste Management 2007. So many reports of improper methods of disposal of HCW have been reported in Nigeria. A near total absence of institutional arrangements for HCW in Nigeria has also been reported by others (Coker et al., 1998). This study was therefore carried out to assess hospital waste management practice in two health care facilities in Lagos, Nigeria, as proper medical waste management is essential for the minimization of the health risk developed from health care facilities. This research is important as it will add to the limited practical information on healthcare waste management and the public health implications of inadequate management of health care wastes in our society.
2.0. Materials and Methods This study was carried out on two different health care facilities in Lagos state, which are secondary facilities providing emergency, surgical, material and child health services. These two secondary facilities which are located in the mainland part of Lagos have 55 and 15 bed spaces respectively. Wastes were generated from different sections of health care facilities including, laboratory, out patients unit, theatres, pharmacy, emergency, accidents wards etc.
2.1. Field survey design The field survey for this project was based on aims and objectives. The investigation of medical wastes employed multiple methods. This strategy provided a mix of both quantitative and qualitative data, with the extensive questionnaire survey providing breadth of coverage; while the interviews with nurses in the hospitals and in-depth interviews with different respondents (medical technicians, hospital cleaners, doctors and environmental health attendants) allowed greater depth of understanding of waste management system within which each of the hospitals operate. The survey design composed mainly of qualitative and quantitative data collection procedures and manipulation, data analysis and
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 361 - 369 interpretation. Other studies including the study by Adegbite et al., (2010) also made use of physical observation, questionnaire administration and quantification in their studies.
2.2. Method of data collection A reconnaissance survey was made to the two healthcare facilities, prior to the period of data collection for the purpose of familiarization with the hospital system and the existing situation of the waste management practices. Several methods were used to collect data, namely site visits, questionnaires, interviews and survey. Data collection regarding waste generation, separation, collection, storage, transportation and disposal of medical wastes were carried out during site visits to the hospitals. These visits were conducted to provide information about the medical waste management and its working condition. Both primary and secondary sources of data were collected in the course of this study. The secondary data were obtained from literature review on documents (printed research thesis, journals, books, hospital waste management manuals etc) which provided background information regarding the medical operations and services of the two hospitals, nature of hospital waste and management plan etc. The primary data constituted the relevant information required for the empirical analysis of the study with reference to the two hospitals in particular. These included the identification of the types of waste generated, the waste management procedures of generation, collection, transportation, treatment and disposal, and the management system adopted for each category of waste, and the assessment of the effectiveness of the waste management practices of the two hospitals. A weight measuring scale was used to determine the amount of waste generated per bed/day by the hospital prior to disposal. The quantity of different categories of waste was deduced by estimation while the type of waste was identified through direct observation. Different medical units were identified in the hospitals including the environmental health department. Questionnaires were distributed to different health facility workers in different departments of the selected health facilities mainly nurse, doctors and environmental health attendants. Data collection also involved using the techniques of oral interviews, researcher’s observation strategy and physical involvement. Involvement of nurses and cleaners was simple enough but interactions with the hospital management and health professionals needed care to confirm the credibility of stories and understand the empirical reality in the face of pre-determined answers. At the HCFs, bins containing colored bags were supplied to the departments treating patients and the laboratories, they were labeled ‘hazardous waste’, ‘highly hazardous waste’, while safety boxes were provided for sharps. The weight of each was recorded before they were transferred to bigger bins outside the building. These wastes were monitored from the point of storage to collection, transportation and final disposal. The result from the questionnaires and field study were analyzed with simple descriptive statistics to arrive at the quantities and types of waste generated. The methods of handling were assessed to document proper containment as well as any evidence of spillage. To obtain information about the final disposal techniques of health care waste, a formal interview was conducted with a representative of Lagos State Waste Management Authority (LAWMA) and a visit to their website was also done.
2.3. Sample survey A total of 30 questionnaires were sampled, of which 20 were sampled in the healthcare facility A (with 55 bed spaces), and 10 in the healthcare facility B (with 15 bed spaces). The issues addressed in the questionnaire included types of waste, sources of wastes, amount of wastes generated, existing waste management and qualitative aspects for management views. Moreover, informal interviews with some hospital cleaners were also employed. A total of 20 respondents from facility A were interviewed for this project. The respondents were selected from all the wards, operating theatres, laboratories, accidents and emergency and other departments. Among the interviewee in facility A, 14 (70%) were female and 6 (30%) were male respondents. All the female respondents were nurses, while all the male
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 361 - 369 respondents were doctors, environmental officers and medical technicians. The average age of the respondents was about 42 years and the average length of service was about 12 years. In facility B, 10 respondents provided information through the questionnaire survey. Of the 10, 8 were female (nurses, medical technicians, hospital cleaners) and 2 were male (doctors) and their average age and service length were 32 and 7 years respectively.
3.0. Results and Discussion In the two healthcare facilities, nurses were the group that answered more to the questionnaires and the doctors were the group that answered less to the questionnaires. Nurses and hospital cleaners were the medical groups with a higher daily contact with medical waste. Medical technicians showed relatively daily contact. In the hospitals, the total medical staff that answered to the questionnaires (45), 82.2% were daily in contact with medical waste.
3.1. Characteristics of waste generated in HCFs A and B Table 1 indicates the types of waste found in the two HCFs. The wastes were characterized as HCWs in the two HCFs. HCWs include discarded biological product such as blood or tissue (removed from operating rooms, morgues, laboratories or other medical facilities).Other HCWs waste include; Sharp waste, anatomical waste, cultures, discarded medicines, chemical wastes, disposable syringes, swabs, bandages, body fluids, human excreta, bedding, and similar materials that have been used in treating patients and animal carcasses or body parts used in research (Babanyara et al., 2013). The characteristic of waste generated between the two HCFs varied. However, the two HCFs are full-fledged hospitals but they do not practice routine teaching, and they are equipped to carry out minor surgeries only. The difference in services they rendered was responsible for the differences in characteristics of the medical wastes observed in this study.
Table 1: Characteristics of healthcare wastes generated in facilities A and B in Lagos
Characteristics of waste HCF A HCF B
Body parts removed during surgery e.g. flesh cut off, teeth, placenta, Present Present tissues, organs etc
Infectious waste during treatments, e.g. gauze bandages, plasters, Present Present cotton wool, syringes, razor blades, needles etc
Highly infectious waste e.g. blood samples, stool, urine etc Present Present
As shown on Table 2, it was observed that HCF A generated higher HCW than HCF B because of the type and frequency of medical services rendered. It was also observed that the high number of bed spaces contribute to the higher amount of waste generated by HCF A. HCF B performs similar medical services but in a lesser capacity when compared to HCF A. The difference in the quantity of waste generated in both secondary health facilities was because of the number of bed spaces, number of in- patients and the number of units where these waste were generated since the type and frequency of medical services rendered in the two HCFs were similar. We were not able to obtain the information on the exact number of inpatients and outpatients in HCF A, during our six months study period, but the numbers were much higher than in HCF B, judging from the activities and the crowds of patients observed throughout the study period. A previous study on HCW management in a HCF (teaching hospital having 52 health workers) in Nigeria by Abah and Ohimsain (2008) reported 0.62kg/person/day at the outpatient units and 0.81kg/bed/day in the inpatient wards. Their study showed a proportion of respondents who had received specific training in the management of HCW to be 11.5%, and the
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 361 - 369 number who understood the importance of HCW management in the provision of safety to the public to be 46%. This report shows how training could create reasonable awareness of HCW management, and this was probably done because it was a teaching hospital. This was better compared to our present study of the two HCFs A and B, also in Nigeria (but not teaching hospitals) having on the average a total of 3.11kg/bed/day and 0.76kg/bed/day respectively, with no training of the health care workers, except doctors that received training as part of their professional training. According with DGS (2006) the national average is 3.5kg/bed/day for the total of medical wastes and 1.38kg/bed/day for the hazardous wastes in Portugal. The waste size from Portugal, a developed country, is quite comparable to the size obtained in our study on the two HCFs in Nigeria.
3.2. Amount of health care waste generated in HCFs A and B Table 2: Amount of HCW generated in facilities A and B in Lagos
Amount of waste generated per bed per day HCF In-patients Out-patients Bed spaces Sharps Infectious waste Highly infectious waste
A 55 0.6kg/bed/day 1.38ky/bed/day 1.13kg/bed/day B 12 40 15 0.2kg/bed/day 0.35kg/bed/day 0.21kg/bed/day
The amounts and type of wastes generated by the individual HCF were established to determine the column generated by them. This was essential for recommendations for the establishment of a good waste management system for these facilities, in terms of the waste transportation and disposal system, the container sizes at the storage place prior to collection and the size of the vehicle to collect the waste. Mismanagement of healthcare waste can pollute the air, soil and water resources, thereby posing health risk to the people and the environment. The percentages of wastes types generated by the individual HCF, as shown in figure 1, reveals that infectious wastes had the highest values in both HCFs, with almost same values (44.37% and 46.05% in HCF A and HCF B respectively). The percent of sharp wastes in HCF A was smaller than in HCF B, though the former facility A is much bigger than B. The percentages of sharp wastes and highly infectious wastes in HCF B were almost same values (26.32% and 27.63% respectively), whereas in HCF A the percentage of highly infectious wastes was almost double (36.33%) that of the sharp wastes (19.29%). These indicated that highly infected wastes are more generated in bigger HCFs than in smaller HCFs. WHO has identified that the percentage of infectious waste in health care wastes is between 10-25% (Pruss, 1999).
Sharp Sharp Highly infectious Highly infectious wastes, wastes, wastes, 36.33 wastes, 27.63 19.29 26.32
Infectious Infectious wastes, 44.37 wastes, 46.05
Figure 1: Percent distribution of waste types in HCFs A and B
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3.3. Units that generated HCW in HCFs A and B During the study period, it was observed that wastes were generated from all the units in HCF A, whereas there were no wastes from the maternity ward and the accidents/emergency unit of HCF B, as shown on Table 3. The two units, maternity ward and accidents/emergency contribute significant amounts of HCWs in a HCF as shown in the difference in the average waste sizes in HCF A (3.11kg/bed/day) and B (0.76kg/bed/day). HCWs such as soiled clothing, swabs, hand gloves, used dressing materials, used infusion, used blood transfusion sets, needles and syringes are generated from the accidents/emergency units. From the maternity units, HCWs such as found in the accidents/emergency units are present with other additions like placenta, papers, and empty medicine bottles and packaging.
Table 3: The various units where waste are generated in HCFs A and B in Lagos
Units HCF A HCF B Nursing room Present Present Injection room Present Present Laboratory Present Present Operating theater Present Present Pharmacy Present Present Maternity ward Present Absent Accidents/emergency Present Absent Isolation ward Present Present
3.4. Healthcare Waste Management (HCWM) practices at HCFs A and B As indicated on Table 4, both HCFs practiced segregation of waste. Colored nylon bags were provided for every unit where wastes were generated. All sharps (razor blades, needles, syringes) were collected in a yellow safety box. Infectious waste like cotton wool, bandages, gauze, hand gloves, plasters, sanitary pads, wipes and tubing were collected in yellow nylon bags while highly infectious waste like blood samples, body tissues, blood bags, stool etc. were collected in red nylon bags. All the steps in a proper waste management system are very essential; once a step is missed, the whole system is faulted. Waste segregation is the key step to efficient waste management system, but the segregation becomes meaningless when the proper waste handlers are not used. Also, the segregation is to no effect because the untrained waste handlers mix the wastes at the temporary point of storage. HCF A used Environmental health attendants to handle their wastes, whereas HCF B used hospital cleaners to handle their own wastes. In both cases, the waste handlers were not trained on handling such wastes. There was no proper management of the HCWs in the two HCFs. There are six steps of focus recommended by WHO for the proper HCWM plan (WHO 2002). These steps include (1) designate a responsible person; (2) conduct an HCWM survey and invite suggestions; (3) recommend HCWM improvements and prepare a set of arrangements for their implementation; (4) draft the HCWM plan; (5) approve the HCWM plan and start implementation; and (6) review the HCWM plan. There are also some technical guidelines formulated by UNEP on the environmentally sound management of bio medical and health care waste (UNEP 2003), which can be followed.
Table 4: Waste management practices in HCFs A and B in Lagos
Types of Labeling on Training for Method of HCF Segregation Handlers of waste containers containers waste handlers disposal Plastic dustbins Black, yellow Environmental LAWMA A Yes No with nylon bags. and red health attendants medical Plastic dustbins Black, yellow LAWMA B Yes Hospital cleaners No with nylon bags. and red medical
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3.5. Training of waste handlers of wastes in HCFs A and B The questionnaire and oral interview indicated that in all the three HCFs, training was not provided for doctors, nurses, hospital cleaners, and other personnel about hospital waste management and their potential hazards except for a few. This is reflected in the information in table 4. In both facilities newly employed hospital cleaners that are in charge of taking the waste bags from various units of generation to the temporary storage point are often instructed on what to do on spot. They have no formal training on waste handling before they start work. Some doctors and nurses revealed that they got their training on medical waste as a part of their professional training, accepting that on spot training for hospital cleaners was the major cause for the observed mixing up of infectious waste with non-infectious waste. These were strong evident that these unskilled wastes handlers, with lack of awareness of the hazards attached to such wastes, could be disposing these wastes into dustbins, drains and canals and other locations where they would pose serious public health hazard. Poor management of clinical wastes exposes health workers, waste handlers and the community to infections, toxic effects and injuries (Ecoaccess, 2004). This seems to confirm the report by Abah and Ohimain, (2010) that it is believed that several hundreds of tons of healthcare wastes are deposited openly in waste dumps and surrounding environments, often alongside with non-hazardous solid waste. Obviously, such open dumpsites become breeding ground for insects, rodents and other disease vectors and a gathering place for dogs, wild animals and poisonous reptile. The frequency with which HCW collection points are serviced is also important to the limit negative environmental consequences of HCW exposure. Lack of training for the medical waste handlers in the HCFs expose them directly to infectious wastes and place them at high risks of contacting the associated diseases.
3.6. Disposal of health care wastes in HCF s A and B Well, the table shows that the waste disposals were carried out by LAWMA medical. A lot of damage could have taken place before the arrival of the LAWMA team for the disposal of what remains of the wastes, knowing very well that these untrained waste handlers, apart from themselves being exposed to the dangers from such wastes, could expose those wastes to scavengers prior to the arrival of the LAWMA medical team. During this study, it was discovered that the contractor (LAWMA medical) visits the HCFs once a week to collect the wastes. According to Babanyara et al., (2013), healthcare wastes if not properly managed can pose an even greater threat than the original diseases themselves. From this study, HCW in Lagos are disposed of by LAWMA but without the direct involvement of the HFCs in the final disposal of their medical wastes. LAWMA medical is saddled with the responsibility of medical waste management by providing skilled, effective, safe and enduring medical waste management and disposal services to hospitals, health centers, clinics and laboratory in Lagos state. The treatment and disposal done by LAWMA medical to waste collected from such facilities include: 1. Disinfection, treatment and burying of non-recyclable waste and covering with laterite. This is done in three dumpsites in Lagos, Epe, Alimosho (solous), Owutu in Ikorodu. 2. The use of hydroclave machine, this machine shreds and detoxify. The action of which reduces the waste to 80% of its initial volume, and 3. Incineration of medical waste is the controlled burning of such waste in a dedicated waste incinerator. Incineration has the advantage of reducing the volume of the waste; sterilize the waste and eliminating the need for pre-processing of the waste before treatment. The resulting incinerated waste (ash) is disposed of in landfills.
3.7. Health care waste handling in HCFs A and B The result on Table 5 reveals the waste management practice observed during the study on the two health care facilities in Lagos. One of the most important aspects of handling healthcare waste is storage at the place of origin. As shown on table 5, the wastes from both facilities were stored outside the facility but open to the public. One week is long enough time for scavengers to go through the wastes repeatedly before the arrival of the LAWMA medical team for the disposal. Proper waste storage is important because this would determine the spread and prevention of diseases. Each HCF should shoulder that responsibility of proper management of the HCW generated by them such that they do not
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 361 - 369 impact negatively on humans and the environment. Some people in the immediate environment might have experienced many illnesses linking to the exposure of these wastes but a common African might not attribute it to this practice but to other things. The common person is not aware of the dangers these exposed wastes could cause, instead they see the benefits of having access to the wastes for whatever they can extract from it. It is therefore of a necessity that the HCFs lock away these wastes from the public while LAWMA, Federal Ministry of Environment, the Ministry of Health and all authorities concerned team up together to educate the public on why they should not be exposed to these wastes. HCM in the developing countries seem to be generally poor compared to the developed countries because the technology, regulations, education and training waste management policies in developed countries are at an advanced stage than in developing countries (WHO 2007). This is evident in the findings from our study, as well as from other developing countries. For instance, Mato and Kassenga (1999) in their study, pointed out there is a serious inadequacy in handling medical solid wastes in Dares Salaam of Tanzania and improper waste disposition is increasingly becoming a potential public health risk and an environmental burden in Tanzania. Similar poor HCW managements have been reported in Tanzania by Manyele (2004), in South Africa by Leonard l (2003), in Bangladesh by Rahaman and Ali, (2000), and more.
Table 5: Waste management practices in the two health care facilities
Variables HCF A HCF B Waste management plan Present Present Waste management team Present Present Waste segregation practice Present Present Place of waste segregation At source At source Temporary waste storage facility Present Present Location of the temporary waste facility Outside the facility Outside the facility Length of stay of waste at the temporary waste storage site One week One week
4.0. Conclusion From this study it can be concluded that there was little or no knowledge of hospital waste management policy in the two HCFs, which seems to confirm the poor healthcare waste management in Nigeria. No evidence of enough attention to healthcare waste management was found in the two HCFs as any policy or plan existed. This situation has exposed many Nigerians to risks of contacting diseases associated with poor healthcare wastes management.
References Abah S.O Ohimain E.I (2008). Healthcare waste management in Nigeria: A case study. Journal of Public Health and Epidermiology. Vol 3(3), pp. 99-110. Abah S.O Ohimain E.I (2010). Assessment Of Dumpsite Rehabilitation Potential Using The Integrated Risk Based Approach: A Case Study of Eneka, Nigeria. World Appl. Sci .J. 8(4): 436-442 Adegbite M.A., Nwafor S.O, Afon A, Abegunde A. A. and Bamise C. T. (2010). Assessment of Dental Waste Management in a Nigeria Tertiary Hospital. Waste Manag. Res., 28:769-777 Babanyara, Y. Y., Ibrahim, D. B., Garba, T., Bogoro, A. G., Abubakar, M. Y. (2013). Poor Medical Waste Management (MWM) Practices and ItsRisks to Human Health and the Environment: A Literature Review. World Academy of Science, Engineering and Technology, Vol: 7 (11) 780-787. Babatola, J. O. (2008). A study of hospital waste generation and management practice in Akure, Nigeria. African Journals Online. Pages 292-305.
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Coker A O., Ogunlowo O.O and Sangodoyin A.Y (1998). Managing Hospital Waste in Nigeria. 24thWedc Conference: Sanitation and Water for All Coker, A., Nsangodoyin, A., Sridhar, M., Booth, C., Olomolaiye, P., Hammond, F. (2008). Medical Waste Management in the South of Brazil. Wastes Manage, 25: 600-605. Draft of the National Health Care Waste Management Plan in Nigeria (2007), prepared for the Federal Ministry of Environment (FMEnv). In collaboration with John Snow Incorporation (JSI), Nigeria DGS (2006). Residous hospitalares 2005- Relatorio. Direccao Geral da saudedivisao da Saude, Divisao de Saude Ambiental. Ecoaccess. (2004) information sheet on waste management: determining whether waste is “clinical waste” [www.epa.qld.gov.au] Leonard I. (2003). Healthcare waste in Southern Africa: A civil society perspective. Proceedings of International Healthcare Waste Management Conference and Exhibition, Johannesburg, S. Africa Manyele, S. V. (2004) Medical waste management in Tanzania: current situation and the way forward. Afr. J Environ. Assess. and Manage. pp. 6-10 Ogbonna, D. N., Amangabara, G. T., Ekerete, O. (2007). Urban Solid Waste Generation in Port Harcourt metropolis and its implication for waste management. Management of environmental quality An International Journal 18 (1) 71-88. Olubukola, B. O. (2009). Comparative Analysis of Health Care Waste Management Practice in two general hospitals in Nigeria available at http://www.ecoweb.com/edi/index.htm accessed january 28 2011 Pruss, A., Giroult, E., Rushbroo, P. (1999) Safer management of wastes from health care activities world health organization (WHO) Geneva Rahaman, H. and Ali, M (2000). Healthcare Waste Management of wastes in developing countries 26th WEDC Conference – water sanitation and hygiene challenges of the millennium Dhaka Bangladesh Townend, W. K., Cheeseman, C. R. (2005). Guidelines for the evaluation and assessment of the sustainable use of resources and of wastes management at healthcare facilities. Waste manag. Res 23:398-408 UNEP (2003) Technical guidelines on the environmentally sound management of biomedical and healthcare waste (Y1; Y3) Chatelaine UNEP. WHO (2002) Waste from healthcare acitivities. Facxt sheet no 231 april 2002. Available at (http/www.who.int/mediacentre/factsheet/fs231/en/). Accessed 12 september 2009 WHO (2005). Management of solid health care waste at primary health care centres: A decision-making guide.World health organization, Geneva. www.lawma.org.ng WHO (2007). Health care activities Fact sheet 253. Reviewd November 2007 at http//www.who.int/mediacentre/factsheets/fs253/en/index.html
Cite this article as:
Alani R., Nwude D. and Adeniyi O., 2019. Assessment of Hospital Wastes Management Practices in Lagos, Nigeria, using Two Health Care Centres as Case Studies. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 361-369. https://doi.org/10.36263/nijest.2019.02.0121
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Nigerian Journal of Environmental Sciences and Technology (NIJEST)
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 370 - 385
Application of Remote Sensing, GIS and Hydrogeophysics to Groundwater Exploration in Ogun State: A case study of OGD- Sparklight Estate
Epuh E.E.*, Jimoh N.O, Orji M.J. and Daramola O.E. Department of Surveying and Geoinformatics, University of Lagos, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0159
ABSTRACT With the increase in population of Ogun state, the necessity to provide water to the populace has become a disturbing problem. In this study, a systematic approach to delineate the groundwater potential zones of the state was carried out using Remote Sensing, Geographic Information Systems (GIS) and Hydrogeophysics as a tool. Vertical Electrical Sounding (VES) observations were also carried out in OGD Sparklight Estate to validate the results obtained from the integrated remote sensing and GIS observation and also determine the aquifer depth and possible pollution. The various thematic maps such as: soil map, land use/Land, geological map, rainfall map, lineaments map were obtained from enhanced satellite imagery and Slope map was generated from Shuttle Radar Topographic Mission elevation model (SRTM DEM). These maps were overlaid in terms of weighed overlay method using Spatial Analysis tool in Arc GIS 10.4. During weighed overlay analysis, different ranks were given to each individual parameter of each thematic map and weights were assigned according to their influence. The groundwater potential map obtained from the study area showed that 47% of the total study area (Ogun state) lie within the “very high” potential zone, 15% of the area falls within the “high”, 30% lies within the of “moderate” zone, 5% lies within the “low “potential zone while “2% “ lies within the very low potential zone. The very high potential areas lie within the sedimentary zone in the southern part of the study area with high alluvial deposits, while the “very low” prospect zone lies majorly within the basement complex zone in the northern part of the study area. The boreholes susceptible to salt water intrusion were identified and the best drilling point with respect to depth were also determined. Keywords: Groundwater, Remote sensing, GIS, Hydrogeophysics, VES
1.0. Introduction
Human activities cause changes in groundwater by change in land use/land cover, soil cover, and reduction in groundwater recharge. Although best methods to estimate aquifer thickness and preferable location of borehole are groundwater pumping test/drilling test and stratigraphy analysis, they are cost and time intensive (Moss & Moss, 1990; Fetter, 1994; Madan et al. 2010; Mukherjee et al. 2012; Mallick et al. 2015). On the other hand, the integration of Remote Sensing, GIS, and geophysical data is a time and cost-effective means of assessing and managing groundwater resources over a large area (Adiat et al. 2012; Verma & Singh, 2013). Groundwater prospecting has employed the technology of remote sensing (RS) and geographic information system (GIS) over the years. GIS has become an indispensable tool for handling spatial information for the exploration, development and management of the earth’s resources. This method has a significant potential to monitor the information about various phenomena and changes on the earth’s surface, such as soil type, land use/land cover, elevation, slope, etc., based on spectral reflectance of earth’s surface (Scanlon et al. 2005; Verbesselt et al. 2006; Avtar et al. 2010).
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Several scientific communities have already reported the importance of different hydrogeological factors, viz., geomorphology, geology, land use/land cover, slope, soil cover, lineament density, surface temperature, etc., controlling groundwater potential of any area (Bera et al. 2012; Javed & Wani, 2009). However, the extent to which they affect groundwater may differ from place and time (Sener et al. 2005; Sreedhar et al. 2009; Avtar et al. 2010). The studies conducted by Godebo (2005), Kamaraju et al. (1996), Sajikumar & Pulikkottil (2013) and Epuh et al., (2018) have also proven the suitability of GIS and RS techniques for determining potential ground water zones as well as its ability to reduce the time, cost and human power the traditional methods. Researches have been carried out in the zonation of Groundwater potential using Vertical Electrical Sounding (VES) in some parts of Ogun State such as Egbe-Mopa (Okogbue, et al. 2013), Mowe (Adeoti, et al. 2012), Odeda Local Government Area (Makinde, et al. 2016). Groundwater contamination by toxic metals was assessed for Ifo community of Ogun state where OGD-Sparklight estate is located (Ayedun, et al. 2011). Several settlements in Ogun State such as Abeokuta, Ifo, Odeda, Ewekoro and Owode depend largely on the surface water, which is supplied by the water corporations from Ogun river, Osun river and Yewa river. This source of water supply is not sufficient and therefore does not meet the demand of the populace. For this reason, groundwater should be an alternative source of water which can be mapped using remote sensing and GIS technique through the application of multi-criteria analysis of certain hydrological and geological factors before the actual VES observations for the siting of boreholes and wells Epuh et al., (2018). Hence, this study aims at delineating groundwater potential zones (GWPZs) in Ogun State considering five factors expressed in thematic layers which include lineament, geology, soil texture, slope and land cover
2.0. Description of the Study Area and its Geology 2.1. Description of the study area Ogun state is entirely in the tropics. It is located in the Southwest Zone of Nigeria with a total land area of 16,409.26Square kilometers, bounded on the west by the Benin Republic, on the south by Lagos State and the Atlantic Ocean, on the east by Ondo State, and on the north by Oyo and Osun States. It is situated between Latitude 6.2oN and 7.8oN and Longitude 3.0oE and 5.0oE. The study area is OGD Sparklight Estate, opposite Mountain of Fire and Ministry Headquarters, along Lagos-Ibadan expressway, Ifo Local government Area 74km North of Lagos state.
Figure 1: Map showing Ogun State and the study area base map.
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2.2. Hydrogeology of the study area The study area is underlain by part of the sedimentary deposits of south western Nigeria. Generally, it falls within the post-cretaceous parts of Nigeria. The geological sequence expected in the area is Oshosun formation, Akimbo formation, Ewekoro formation and Abeokuta formation. The geology of Ogun State is made up of the basement complex and the sedimentary layers. The basement complex is essentially non-porous and water can only be contained in the cervices of the complex. This basement complex primarily underlines the sedimentary layers which consist of Cretaceous, Tertiary and Quaternary sediments deposited in the coastal basin. The climate is characterized by consistently high temperature ranging between 22 and 35oC for most of the year. The South-westerly winds dominate the area between April and October bringing heavy rains and the north-easterlies dominate between November and March bringing dry dusts and harmattan haze in December and January. With no barrier to the prevailing winds, the south westerly wind is able to penetrate deep into the State and beyond bringing a lot of rain. Given the location. Physical Characteristics Ogun state is located in the south-west of Nigeria. The land area is 16,409.26 square kilometers. The eastern basin is made up of mainly of sand, and sandstones, clay limestone. Topography of the State is characterized by high lands to the north and sloping downwards to the south. The highest region is in the north-west and rises to just over 300 meters above sea level. The lowest level is to the south terminating in a long 20 kilometer stretch of the Atlantic Ocean, to the east by Ondo and Osun states, and to the north by Oyo State (Jones & Hockey, 1964). This bounded on the west by the Republic of Benin, to the south by Lagos State and a chain of lagoons. The only window to the Atlantic Ocean is to the South east of the State in Ogun Waterside LGA. With the general topography sloping from the north to the south, all the main rivers in the state flow from the north to the south. There are five major basins: the Yewa, Ogun, Ona, Osun and Sasa basins.
3.0. Materials and Methods 3.1. Datasets Table 1 contains the attribute of the datasets, while Table 2 contains the satellite derived and datasets used for the study. Table 4 contains the assigned Weights and Scores to different Themes and Features respectively Table 1: Attributes of Datasets
Data Spatial S/N Image data Epoch Path/Row Bands Data source format resolution 1 Landsat 7 ETM+ GeoTIFF 2016 190/56 8 30m https://earthexplorer.usgs.gov 2 Landsat 8 OLI/TIRS GeoTIFF 2016 191/55 11 30m https://earthexplorer.usgs.gov 3 Landsat 8 OLI/TIRS GeoTIFF 2017 190/55 11 30m https://glovis.usgs.gov
Table 2: Datasets Used
Remote sensing data Publisher/source Year
Landsat imageries (Path191/ Row 55) Downloaded from USGS https://earthexplorer.usgs.gov/ 2016
Rainfall data Nigerian Meteorological Agency (NIMET) Annual Report 2016
SRTM DEM Downloaded from https://earthexplorer.usgs.gov/ 2018
Geological map Published by Nigeria Geological Survey Agency (NGSA) 2004
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Soil map Published by Soil Survey Division, Fed. Dept. of Agric. 1990 Land Resources (FDALR) 3.2. Hydrogeophysics The purpose of Vertical Electrical sounding (VES) is to investigate the changes in subsurface formation resistivity with depth. It shows apparent resistivity (pa) variation with depth with sample use of electric sounding which provides an estimate of the resistivities of the first and last layers and indicates the relative resistivities of intermediate layers. Hence the method is useful in determining and delineation of the aquifer depth. Table 3 shows the acquisition Hydrogeophysics acquisition process.
Table 3: Datasets used
Hydrogeophysics data Source Year
Vertical Electrical Sounding and Data Primary field data acquired using Vertical Electrical 2018 Sounding Schlumberger array Method. Twelve (12) VES stations were observed within the study area
Table 4: The assigned weights and scores to different themes and features respectively (Source: Epuh et al. 2018)
Weightage S/N Themes Each class of themes (features) Score influence (%) River Alluvium 10 1 Geology 30 Amphibole, schist 8 Sand and clay 6 1387-1554 10 1554-1661 20 2 Rainfall (mm) 22 1661-1715 30 1715-1742 40 1742-1780 50 Soil map Swamp soils 40 3 18 Reddish Friable Porous Sand 24 0-1 9 4 Lineament density 15 2-4 18 5-7 24 0-2 40 2-5 32 5 Slope (%) 10 5-10 24 10-17 16 17-67 8 Waterbody 10 Built-up 8 6 Land cover 5 Wetlands 6 Vegetation 4 Bareland 2
3.3. Data processing The Landsat satellite image, path and row 191/55 was used. Figure 2 shows the flow chart for the project execution. Table 5 shows the classification of the groundwater potential zones.
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Remote Sensing Existing Maps Data & Literatures
LANDSAT 8 SRTM (DEM) GEOLOGY SOIL RAINFALL REPORT IMAGERY
SATELLITE DATA ANALYSIS GEOCORRECTION GEOREFERENCE ENHANCEMENT DIGITIZATION FILTERING
THEMATIC LAYERS
LAND USE SLOPE LINEAMENT SOIL GEOMORPHOLOGY RAINFALL
LINEAMENT DENSITY
INTEGRATION OF ALL THEMATIC MAPS Weightage Overlay Method GIS PROCESSING
GROUND WATER POTENTIAL ZONE Figure 2: Flowchart for Project Execution
Table 5: Groundwater Potential Zoning
Zone Groundwater Category 10-13 Very High Potential 9-10 High Potential 7-9 Moderate Potential 6-7 Low Potential 4-6 Very Low Potential
The weights and rank have been taken considering the works carried out by researchers such as (Krishnamurthy et al. 1996; Saraf & Chowdhary, 1998). All the thematic layers were converted into raster format and superimposed by weighted overlay method (rank and weight wise thematic maps were integrated with one another through GIS ArcInfo grid environment). For assigning the weight, the geology and rainfall map were assigned higher weight due to their high-water infiltration, whereas the slope and land use/land cover were assigned lower weight. After assigning weights to different parameters, as shown in Table 4, individual ranks are given for sub-variable. Then, each of the individual themes were overlaid one at a time to get the final composite map such that each polygon in the final composite map is associated with a particular set of information of all thematic layers. Also, the evaluation of ground water prospect for each polygon in the output is based on the added values of scores of various themes as described in the Equation 1.
GWPI()()()()(()()()() Gw x G T LULC w xLULC T ST w x ST T DD w x DD T RD w x RD T
(SLw )x ( SLT ) LD w ) x ( LW T ) (1)
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Where GWPI = Groundwater Potential Index, G = Geology, LULC = Land Use land Cover, ST = Soil, SL = Slope, DD = drainage density, RD = Rainfall Distribution, LD = Lineament Distribution, w = weighting coefficient and T = Thematic Layers. The range of GWPI values (score value) were divided into five classes (called zones) and the GWPI of different polygons falling under different range were grouped into one class. Thus, the entire study area was qualitatively divided into five ground water potential zones namely; very high potential, high potential, moderate, low potential and very low potential for groundwater as shown in the Figure 10.
3.3. Hydrogeophysics (VES interpretation, scaling and gridding of geoelectric sections) The VES Curves were quantitatively interpreted by partial curve matching using two-layer model curves and the corresponding auxiliary curves. multi-layered field curves were matched segment by segment starting from the small electrode spacing. The theoretical VES curves were generated from partial curve matching interpretation results (layer, thickness and resistivities) using a computer programme based on the inputted data. The field curves were then compared with the computer- generated curves, where a good fit was obtained het\en a field and computer—generated curve. The scaling and gridding of the geoelectric section involves the construction of a digital file suitable for aquifer reservoir mapping and gridding. The geoelectric sections were digitized with respect to their differential lithostratigraphic thickness. The modules in the reservoir scaling were designed to produce chains of cells for visual representation of beds, bed sets, lamina, and lamina sets in a two- dimensional outlook. Each lithologic unit was assigned its own interpreted geologic parameters and this process was carried out in all the fifteen geoelectric sections used in the research. The extended entity relational model was utilized in the creation of the Hydrogeophysics database.
4.0. Results and Discussion 4.1. Results 4.1.1. Soil map The result of the soil type reveals that the study area is predominantly covered by three main soil types namely: sandy loam is predominant soil group, followed by clay soil group and sandy clay (Figure 3). According to their influence on groundwater occurrence, sandy loam soil is considered as very good, whereas sandy clay is being considered as moderately better than other soil type. Result shows that most part of the study area is covered with sandy loam, which is considered a good groundwater potential zone. The movement and infiltration of water in these three types of soil is not same so based on its property the weightages have been assigned.
Figure 3: Soil map of Ogun state
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4.1.2. Slope map Slope is one of the important terrain parameters expressing the steepness from the ground surface which provide important information on the nature of geologic and geodynamic processes operating at that regional scale. In general, in the vector form closely spaced contours represent steeper slopes and sparse contours exhibit gentle slope whereas in the elevation output raster every cell has a slope value. Here, the lower slope values indicate the flatter terrain (gentle slope) and higher slope values correspond to steeper slope of the terrain. In the elevation raster, slope is measured by the identification of maximum rate of change in value from each cell to neighboring cells. The slope amount derived from digitized contours and spot heights have shown that elevation decreases from the southern part to the northern part with slope in the study area. Result shows that although slope angle of the study area varies from 0 to 47, most of the part lie within slope angle between 0 and 7 (Figure 4). In the nearly level slope area (0-1) degree, the surface runoff is slow allowing more time for rainwater to percolate and consider good groundwater potential zone, where as strong slope area (30-47) degree, facilitate high runoff allowing less residence time for rainwater hence comparatively less infiltration and poor groundwater potential. The entire slope map is divided into eight categories. Table 6 shows the slope categories.
Table 6: Slope gradient and category
Class Percentage Slope category
1 0-7 Nearly Level 2 7-16 Gentle Slope 3 16-30 Moderate Slope 4 >30 Steep Slope
Figure 5: Slope map
4.1.3. Rainfall map The present study has been considering the annual mean rainfall of Ogun state. Figure 6 shows the rainfall map of Nigeria. The area is divided into six ranges which are varying from 1,007-2,519mm.
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The result shows that the study area lies within 1,247-1,474mm of rainfall which shows that annual rainfall in the area is moderately high.
Figure 6: Rainfall Map
4.1.4. Geology map The major rocks found in study area are Alluvial shales, mudstone, silt stone, granites and gneisses. Geology also plays major role in groundwater occurrence in any area. Here, the study area is occupied by six major features such as Alluvial, shales, mudstone, silt stone, granites, and gneisses (Figure 7). Alluvial is the depositional structure formed by running water. Shales are soft finely stratified sedimentary rock that formed from consolidated mud or clay and can be split easily into fragile plates. One is an extremely fine-grained sedimentary rock consisting of a mixture of clay and silt-sized particles. The rocks in the study Area are considered highly good for groundwater occurrence.
Figure 7: Geological map of the Ogun State
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4.1.5. Lineament map Structural faults (Lineaments) are the irregular earth features that can easily identified on the ground. These feature reveals the surface and underlying structural features. Lineaments are indicators of subsurface faults and fractures influencing the occurrence of ground water acting as canals and reservoirs. Lineament density of an area can ultimately expose the groundwater potential, since the presence of lineaments usually signifies a permeable zone. Areas with high lineament density are good for groundwater potential zones (Haridas et al. 1998). So, the lineaments play a major role in groundwater potential zoning. For the present study 0-7 meters buffers were created from the lineament and suitable weightage have given based on the infiltration of groundwater (Figure 8). Table 4 shows the lineament density classification
Figure 8: Lineament density map
Table 7: Lineament density classification by weight
Lineament density Weight 0-1 20 1-2 40 2-3 60 3-5 80 5-7 100
4.1.6. Land cover map The surface covered by vegetation like forests and agriculture traps and holds the water in root of plants whereas the built-up and rocky land use affects the recharge of groundwater by increasing runoff during the rain, so it is necessary to study what kind of features are covered the study area’s land surface. The Landsat 8 satellite image has been used for the study to find out the land use and land cover of study area. The supervised classification method has been used with level – I classification. The result of the study found the study area is covered by five different classes such as:
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Figure 9: Land Cover Map
4.1.7. Integration of thematic layers using GIS (weighted overlay method) The ground water potential zones were obtained by overlaying all the six thematic maps in terms of weighted overlay method using the spatial analysis tool in Arc GIS 10.4. Integration of thematic layers and modeling through GIS yielded the groundwater potential mapping, which was classified as very high potential, high potential, moderate potential, low potential and very low potential according to Lubang et al. (2008). The result shown in Figure 10 shows that the study area is located at a place of very high ground water potential. Figure 11 shows a bar Chart depicting the percentage of Groundwater Potential distribution of the study area.
Figure 10: Groundwater potential Map of Ogun State
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Figure 11: Pie chart showing the Spatial distribution of groundwater potentials in Ogun State in percentage.
Figure 12: Map showing VES points fall in the area of very high ground water potential
Figure 13: All the VES points fall in the class of ‘Very High Potential’.
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4.1.8. Digitized geoelectrical sections and queries The VES points were all located within the low groundwater potential of the study area as shown in Figure 10. The queries were carried out on base map to determine the VES locations with various groundwater conditions. The queries show the location, depth, layer thickness and coordinates. The identified points of the queries on the geoelectric section and base map are shown in yellow colour. The queries include the following: i. The location and depth for Fresh water (Figure 14) ii. The location and depth for Brackish water (Figure 15). iii. The location and depth for Saline water (Figure 16) iv. The location and depth for Fresh water (Figure 17)
Figure 14: "INTERPRETA" = 'Good Fresh Water' VES points 1,2,3,5,6,7,8,9,10,11
Figure 15: "INTERPRETA" = 'Brackish Water' VES points 1,2,4,5,8,10
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Figure 16: "INTERPRETA" = 'Saline Water' VES points 1,2,3,4,5,6,7,8,9,10,11,12
Figure 17: Query performed; "THICKNESS" >= 10.5 AND "THICKNESS"<= 26.960000000000001. (This highlights layers whose thickness is between 10.5 and 26.9.)
4.2. Discussion The ground water potential zones map given in Figure 10 show that 47% of the total study area (Ogun state) lie within the very high potential zone, 15% of the area falls within the high, 30% lies within the of moderate zone, 5% lies within the low potential zone while and 2% very low potential zone as shown in Figure 11. The very high potential areas are mainly concentrated along the Alluvial deposit zone of the lower part of the study area. While the “very low potential” prospect zone lies within the area with dominant granite and gneiss deposits (the basement complex zone) of the study area. Four different formations were found in the interpreted VES data. They are: top soil, sand, clay sand and clay formations respectively. The sand formations contain fresh water suitable for domestic use. Fresh water is generally characterized by having low concentrations of dissolved salts and other total
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5.0. Conclusion From the ground water potential map obtained, the study area is located at a place of very high ground water potential. Integrated use of Remote Sensing, GIS and Hydrogeophysics for delineation of the groundwater potential zones in this study proved efficient in terms of minimizing cost, time, and labor. The result depicts the groundwater potential zones in the study area and found to be helpful in better planning and management of groundwater resources and also demonstrate that the integration of Remote Sensing, and GIS provide a powerful tool in the assessment and management of water resources and development of groundwater exploration plans. Integration of different data layers such as Remote Sensing, geomorphology and field data in a GIS environment provide means to unravel the nature of hard rock aquifers. Spatial and statistical analysis allows to understand the correlation between different parameters. In a developing state like Ogun state with weak infrastructure as well as scarce information/data, finding from this study is a good tool which enables policy makers for quick decision-making in sustainable water resources management, suitable for groundwater exploration. The result can also serve as guidelines to determine the region or zone with no water or polluted aquifer.
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Cite this article as:
Epuh E.E., Jimoh N.O, Orji M.J. and Daramola O.E., 2019. Application of Remote Sensing, GIS and Hydrogeophysics to Groundwater Exploration in Ogun State: A case study of OGD-Sparklight Estate. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 370-385. https://doi.org/10.36263/nijest.2019.02.0159
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 386 - 397
Geometric and Dynamic Application of Satellite Geodesy in Environmental Mapping: A Conceptual Review
Hart L.1,*, Oba T.1 and Babalola A.2 1Department of Surveying and Geomatics, Rivers State University, Port Harcourt, Nigeria 2Department of Surveying and Geoinformatics, University of Ilorin, Ilorin, Nigeria *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0153
ABSTRACT
The impacts of satellite geodesy are being felt in all aspects of human development and environmental management. Its principal advantages stem from the global nature of its scope, the diversity of its sensors and the realtime capabilities to capture both visual, numerical and other data types for as long as desired and in all weather conditions. The capacity to pinpoint locations to high precision in fractions of a second and provide detailed geometric and graphical definitions of large swaths are proving useful for meeting the needs of a people desirous for automation in all aspects of human endeavours and for confronting the increasing challenges of sustainable development and environmental degradation. The most innovative facility provided by satellite geodesy is the technology of remote sensing which enables measurements of objects without physical contact for interpretative and mensurative analysis and mapping in static or kinematic modes. The aim of this paper is to showcase the contributions of satellite geodesy to sustainable environmental management its basic concepts and a brief exploration of some of its applications. The overall objective is to underscore its critical role in socio-economic development. The paper posits therefore that today’s rapidly changing environmental problems requiring static and realtime locational and graphical solutions can be solved through the facilities of satellite geodesy.
Keywords: Satellite, geodesy, dynamic, environment, geometric, technology.
1.0. Introduction Traditional geodesy has been known to be a means of defining the physical features of the global earth in mathematical, numerical and graphical forms for purposes of understanding and portraying the geographical distribution of its resources and their influence on socio-economic development. The Global Navigation Satellite System (GNSS) and other types of satellite systems with diverse sensors constitute one of the most recent innovations of geodesy which when used in combination with the equally new and intelligent software packages that can manage large spatial data in both real time and offline modes, can support a wide range of innovative applications in environmental management with optimal precision. Nonetheless, the application of satellite geodesy for mapping, positioning, navigation and sub-surface monitoring in emerging geodetic and geodynamical problems has created a wide range of need for geodata integration. For instance, the use of the GNSS for navigation or tracking on the earth or near the earth surface requires accurate positions to be supplied to a software package that can process map-based data in realtime – an activity that requires data integration. Routinely, numerous data sets such as geographical coordinates, time, earth rotational velocity, polar motion parameters etc., need to be integrated for spatial data analysis tasks, which may include among other things: to investigate environmental change, manage national security and contribute to hazard mitigation and emergency management (Fubara, 2011). Mapping the environment has always been an intricate exercise in the face of its changing nature and attributes through climate change, geodynamical phenomena, human
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 386 - 397 and anthropogenic activities with emerging challenges in methodology, instrumentation and skill gap required. Yet, it is pertinent to note that Satellite geodetic outputs are not only contributing to our appreciation of the earth, but they also benefit many societal activities, ranging from disaster prevention and mitigation to the protection of the biosphere and the environment. Therefore, geodesy contributes in countless ways to increased security, a better use of natural resources and, ultimately, to achieving the goal of sustainable development on our fragile planet. Theoretically, Satellite geodesy is based on the observation of artificial earth satellites, natural celestial bodies (moon) and other extra-galactic radio sources enclosed in a defined orbital path with its associated orbital parameters. Directions range and range-rates are determined between earth surface location and the satellite or between satellites. Some measurements, for instant accelerations, are taken within the satellites themselves. The thrust of this work is to review and bring to the fore the relevant basic conceptual and mathematical models which underpin the operations of satellite geodesy; the geometric and dynamic nature of its practical realizations which enable it to create solutions to emerging human and environmental challenges are also introduced. The work is also to dispel the commonly held narrow view of geodesy as a discipline that only provides the size, shape and gravity field of the earth by demonstrating the huge relevance and wide applicability of satellite geodesy in the geoscience and engineering solutions of resource mapping, exploitation and position-dependent measurement, calculation, analysis including visualization studies. The need to have a better and deep understanding of the theoretical frame and the practical demonstration of the science of satellite geodesy in all of its ramification is urgent and strong. This will go a long way to stimulate and deploy its capability to confront the emerging environmental issues in its existential and/or developmental form. Secondly, and in addition, to its adaptability to modern technology and its potential to be practiced within the confines of contemporary technology, it will stimulate interest to upcoming scholars and policy managers to understand the infinite strength of satellite geodesy in geosolution provision to our environment.
2.0. Overview of Satellite Geodesy Geodesy from a general perspective and aptly captured by Agajelu, (2018); is the scientific discipline that deals with the determination of the exact figure and the external gravity field of the earth and their variations with time, as well as, the mean earth ellipsoid, using terrestrial and extra-terrestrial observations. It demonstrates the application of determining the size, shape of the entire earth, dimensions as well as location of points on it. It enables the actual representation of the earth as a geometric figure that is supported by an equatorial radius, flattening of the figure, in addition to equatorial and polar gravity. In practice, we have different approaches in demonstrating the applicability of geodesy as a geosolution discipline of which the satellite or space geodesy has become a veritable approach. Satellite geodesy comprises the observational and computational technique which allows the solution of geodetic and geodynamical problems by the use of precise measurement to, from, or between artificial satellites, mostly near-earth, satellites. In relation to Helmert’s classical definition (1880) of geodesy, which is basically still valid, the objectives of satellite geodesy are today mainly considered in an efficient way as indispensable to virtually all human sphere for socio-economic development, space science and technology, (Fubara, 2006). This branch of geodesy adopts observations connecting points on the earth’s surface to dynamic or stationary spatial points and uses the theories of celestial mechanics, dynamical and spherical astronomy to fix the points in space and on the earth surface. They also include, because of the increasing observational accuracy, time-dependent variations which impacts on various astro- dynamical, geological and geophysical processes affected by gravity on the earth or near the earth surface. These associated applications underscores the usefulness of the capabilities of this branch of
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 386 - 397 geodesy: the determination of geometrical 3-dimensional positions and velocities in global, regional and local reference frames, the determination of the earth’s gravity field and its temporal variations and modelling and observing of geodynamical phenomena (tectonic plates, loading crustal deformations) including the rotation and orientation of the earth (polar motion, length of day, precession and nutation. In addition, the orientation of the earth’s axis and its rotation speed and time with respect to length of day, designated as earth’s rotation. (Fubara, 2006) The use of satellite geodesy has some prerequisites; these are basically a comprehensive knowledge of the satellite motion under the influences of all acting forces as well as the description of the positions of the satellites, orbital parameters and ground stations in suitable references frames. This method is an accurate means of relative-position determination of points on the earth's surface as shown in figure 1, which are separated by thousands of kilometres. It is the most powerful means of precise- position fixation, air, land, sea navigation capability and precise timing on a global scale. It also serves as an indispensable tool in the oil and gas industry, mapping of socio-economic development, telecommunication activities, satellite orbit determination and tracking of space borne vehicles.
Figure 1: The global positioning system (GPS), 24 satellites configuration
The results of geodetic- astronomic, space-based gravimetric observations are used within the field of astronomy and physical geodesy for the determination of the gravity field of the earth (Torge, 1991).
2.1. An overview of theoretical and mathematical framework of satellite geodesy The fundamental frame on which satellite geodesy is premised is in relation to the concept of the perturbed orbit and its attendant orbital motion influenced by the spherical symmetric earth’s gravitational attraction as well as other forces acting on the satellite. It supposes the remaining portion of the satellite orbit that recognizes the effect of the luni-solar gravitation, atmospheric drag, solar radiation pressure, earth-tide and ocean tide effect and such like. In another vein, the normal orbit determination which is referred to as the two-body problem which assumes that there are only the earth and the satellite in space. This can be solved analytically if they are represented in elliptical elements, thereby providing complete solution for a space fixed orbit. (King et al., 1985; Agajelu, 2018) The Kepler’s laws describe the satellite’s orbit as an ellipse with the geocenter at one of the foci, which means the satellite and its geocenter are on the same plane, similarly the geocenter-satellite straight line sweeps out area in equal time and finally, the square of the mean motion of the satellite is inversely proportional to the cube of the average distance of the satellite from the geocenter. These laws underscore the theoretical frame for which the satellite orbits are modelled and determined
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 386 - 397 within the Newtonian principles of motion and attraction. Hence, the following mathematical models give insight on the satellite behaviour: i. To know the size and shape of the satellite orbit and the position of the earth in the ellipse (Smart, 1960; Escobal, 1965; Leick 1995; Agajelu, 2018). a(1− e2 ) r = 1+ ecos f (1) Where, r is radius vector of satellite (i.e. geocenter-satellite distance); e is Eccentricity of the orbit; f is true anomaly and a is semi-major axis of the orbital ellipse. ii. To indicate the speed of satellite when close or far from the earth. The radius vector sweeps out areas at constant rate.
dA 1 A = = Gma(1− e2 ) = k dt 2 (2)
Where, A is area rate (dA), dt is change in Area & Time; m is mass of body; a is acceleration; G is gravitational constant. iii. To determine the average motion of the satellite along its orbital path.
2 1 n 3 a (3)
If geocentric gravitational constant, GM to be the constant of proportionality, then Equation 3 can be written as:
2 3 n a = GM (4a) where, n is mean motion in radians. D n = (T ) (4b) Where, D is total distance of the circumference; T is period d + d a = 1 2 2 (4c)
Where, d1 is distance to apogee; d2 is distance to perigee.
1 4 2a3 2 T = GM (4d) The equation of motion of a satellite
→ F = ma (5a)
Where, 퐹⃗ is force acting on a body; m is mass of satellite (body); a is acceleration of the body. If Equation 5 is expressed in terms of position vector and time, then we can represent the equation as:
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→ → d 2 r F = m 2 dt (5b) where,
→ d 2 r a = 2 = r dt (5c) The essential value of the satellite is that it is a moving body within Earth’s gravity field. This view leads to the dynamical method of satellite geodesy. In dynamical satellite geodesy orbital arcs of different lengths are considered in view of the short time of data tracking, relative position of observing stations can be determined and corresponding orbital elements of each passing satellite. When arc lengths between a few minutes and up to several revolutions around earth are used, we speak of short arc techniques; the term for the use of longer arcs, up to around 30 days and more, is long arc techniques. The orbits are described in suitable geocentric reference frames, determination of zonal harmonics required to model the perturbations caused by the earth’s gravitational field on the orbital path of the satellite (Vaníc˘ ek and Krakiwsky, 1986; Wolf and Ghilani, 2006).
3.0. Applications of Satellite Geodesy 3.1. Acquiring data for DTM creation Digital Terrain Model (DTM), is a digital representation of the terrain surface using a set of heights over 2D points residing on a reference surface. In other words, it approximates a part or the whole of the continuous terrain surface by a set of discrete points with unique height values over 2D points (Hirt, 2015). Digital Terrain Models (DTM) plays a pivotal role in diverse disciplines. Its application can be greatly felt in planning of engineering structures such as roads, railways, canals, large reservoirs, hydro dams, rendering visualisations, topographic and thematic maps. In gravity field modelling and physical geodesy, it provides geometry information of the topographic masses. DTM is based on topographical information which is commonly obtained by classical terrestrial survey. However, the process of data acquisition of the terrestrial survey is costly, time consuming, tedious and poses a greater challenge of intervisibility between stations. To this effect, the technology of GNSS in satellite geodesy can be deployed in acquiring accurate data for high-resolution DTM creation using the real-time kinematic method of Global Positioning System (GPS) based on either a reference global and/or local geoid model. The GPS does not only provide the 3-dimensional geographical (φ, λ, h) and/or projected coordinates in UTM (E, N, h) which may be transformed to the earth-fixed centered cartesian coordinate (x,y,z) information needed for the DTM creation but offers an ease, quick and comparatively cheap alternative as less personnel are needed for the survey and intervisibility between stations are not required. Figure 2 shows a 2-dimensional representation of topographic characteristics of part of the environment identifying relative positions of natural and cultural features. It describes space features and vegetation as depicted. Similarly, Figure 3, depicts a 3-dimensional terrain model with contour. This is a critical geospatial information required for sustainable engineering design and environmental management.
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Figure 2: Map showing topographic characteristics of part of the environment (Source: Ezeomedo et al, 2017)
Figure 3: DTM Model. (Source: Katarzyna, 2009)
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Figure 4: DTM with contours. (Source: Katarzyna, 2009)
3.2. Oil and Gas platform deformation monitoring Platforms are built around onshore and offshore oil and gas natural reservoirs. As a result of continued extraction and exploration of oil and gas from these reservoirs, the reservoirs could start depleting due to lack of pore pressure and this in turn could result to platform deformation (subsidence). If the rate at which the subsidence occurs is not monitored and a control measure put in place, it could lead to disaster (Fubara, 2011). Hence, this subsidence information becomes imperative as to assess its risk level and safety requirements in that a possible disaster could arise from such situation. Through the use of GNSS (GPS) technology, reliable and accurate information of subsidence on the platform can be achieved. Figure 6 shows an offshore location of an oil drilling facilities that undergoes subsidence. Other allied applications of satellite geodesy include rig movement and positioning, geohazard mapping in offshore locations, prospecting and exploration activities. Furthermore, Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the most used remote sensing techniques for the investigation of Earth's surface deformation phenomena, (Massonnet and Feigl, 1998). It permits the retrieval of surface deformation maps with centimeter to millimeter accuracy, starting from the phase difference (Interferogram) of SAR image pairs relevant to the same area of interest but acquired at different epochs and with a significantly small orbital spatial separation (baseline) (Okeke and Moka, 2004; Okeke, 2005)
The change in the phase shift can be expressed in the form of the following simple equation: = R + (6)
Where λ is the wavelength, R is the displacement, is a phase shift due to different atmospheric conditions at the time of the two Radar acquisitions. As a consequence, any displacement of a Radar target along the satellite line of sight creates a phase shift in the Radar signal that can be detected by comparing the phase values of two SAR images acquired at different times (Okeke and Moka, 2004; Okeke, 2005).
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Figure 5: Differential SAR Interferometry (DInSAR) (Casu et al., 2016)
Figure 6: Offshore oil and gas platform (Source: Heri, et al, 2018) Similarly, Figure 7 shows a crude oil storage tank undergoing subsidence monitoring using laser scanning technology. This process indicates deviations axially horizontally and vertically over a period of time in the event of loading or changes in the earth crust. The current methodology is to use a total station to measure the position of pre-fixed studs around the top and bottom of a storage tank. The advantage of laser scanning is that instead of measuring a limited number of pre-defined points, the whole surface of the storage tank can be analysed at all levels - rather than just at the top and bottom of the tank. The environmental monitoring of these storage facilities underscores environmental sustainability through the principles of ground-based remote sensing which are being used in real time as an attribute of satellite geodesy, (Hart et al., 2018).
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Figure 7: Scan view of oil storage tank subsidence monitoring (Hart et al., 2018) The advantages of using GNSS (GPS) survey method is that it provides the three-dimensional displacement vector with two horizontal and one vertical components, so it will give not only land subsidence information but also land motion in horizontal direction; it provides the displacement vectors in a unique coordinate reference system, so it can be used to effectively monitor land subsidence in a relatively large area like in offshore oil and gas field; this space-based measurement techniques can yield the displacement vectors with a several millimetre precision level which is relatively consistent in temporal and spatial domain, so it can be used to detect even a relatively small subsidence signal; and the GPS can be utilized in a continuous manner, day and night, independent of weather condition, so its field operation can be flexibly optimized (Heri et al., 2018). Furthermore, the phenomenon of land subsidence and crustal motion has received a great deal of attention, since it can have a wide range of negative consequences, such as oil well failures, damage to surface infrastructures, or impact on the environment. Okeke et al, (2018) asserts that in the context of space-borne geodetic techniques, Differential Synthetic Aperture Radar Interferometry (DInSAR) has been considered as an efficient and cost-effective technique for monitoring land subsidence due to its large spatial coverage and high accuracy provided and in different conditions and scenarios, both natural and anthropogenic.
3.3. Early warning for natural hazard Natural hazards such as tremors, earthquakes, volcanic eruptions and tsunamis occur as a result of earth crust deformation due to the expansion and contraction of the fault plain. Recent tremors in Mbape in Abuja, Igbogene in Bayelsa and other locations in north central and south west locations in the country underscore the need to deploy satellite techniques to monitor and determine its extent in the event of occurrence. When this phenomenon occurs, it causes some devastating effect on the earth’s surface. The magnitude of the effect can be determined using the satellite technique in combination with some seismological instrument to record the vibration of the waves that occur beneath the earth crust. To this end, the period between data acquisition and the distribution of the information obtained from such data becomes an important consideration. For quick, ease and precise acquisition of such data, GNSS (GPS) technology can be deployed to acquire data that can be used to rapidly determine earthquake location, size, and potential for damage. As a result of the physics of seismic wave generation and propagation, when seismologists sense any seismic activity, they cannot be determined if it is a small or large earthquake with seismic data alone but with real-time geodetic data, this can be determined. Figure 9 depicts modelling dynamics using Remote Sensing and Geospatial Information System (GIS) techniques which provide a platform for the prediction of earth crustal changes both at sea and on land.
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Figure 8 7:: Environmental Schematic Diagram modelling of using image remote classification sensing and and GIS GIS technology layering (Adapted from Ezeomedo, et al (2017))
4.0. Conclusion GNSS technology the operational component of satellite geodesy supports the efforts to understand and forecast changes in our environment by integrating GPS measurement into active methods used by scientist in the field of geodesy and geosciences to study the environment and its corresponding changes that occur over a long period of time, (Hart, 2015). The satellite and Remote Sensing technology have played a vital role in positioning and navigation application which has emerged as a fundamental component of geodetic infrastructure and services worldwide. These technologies have all weather capability, high temporal and spatial resolution and high accuracy. Areas where these technologies could be deployed includes; weather forecast, climate research, high technology agricultural projects, soil research, crustal motion and tectonic plate changes in real time. This has become imperative with the current trends of earth tremor in different parts of Nigeria. In another vein, atmospheric water content, an important component in terms of weather forecasts, can be accurately determined using this technology. Also, the proliferation of GPS tidal tracking site can improve the estimation of the vertical component of sites position from GPS measurement, which uniquely present an opportunity to directly observe the effects of ocean tides especially in the continental shelves and in particular the Niger Delta region of Nigeria. Geometric and Dynamic Application of Satellite Geodesy applications in environmental mapping is well established in many countries. However, there has been low progress in its research and application in Nigeria. To stimulate a knowledge-based exploration of this new techniques in Nigeria, this paper presents a conceptual review of the application of GNSS technology as a technique of satellite geodesy in Environmental mapping. Its adaptability to contemporary technological changes is in the threshold of evolving as a discipline that is poised to solving earth related and emerging problems due to the interaction of man and the environment.
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Bassey U. (2003). An Introduction to Geographic Information Technology. Tobistics Printing and Publishing Ventures, Oyo State. Casu, F., Elefante, E., Imperatore, P., Zinno, I., Manunta, M., et al. (2014). “SBAS-DInSAR Parallel Processing for Deformation Time Series Computation”, IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing 7(8), pp 20-26 Casu, F., Manunta, M., & Zinno, I. (2016). AGU 2015 Training on the SBAS-DInSAR web tool for Earth surface deformation analysis through the ESA Geohazard Exploitation Platform (online) Zenodo. http://doi.org/10.5281/zenodo.44624 (last accessed 10th October, 2017) Dedi Atungal Sp, Bambang Kun Cahyono, and Abdul Nasir Matori (2014). Digital Terrain Modelling by Real Time Kinematic GPS. An unpublished lecture note, Department of Geodetic Engineering, Universitas Gadjah Mada, JI. Grafika no.2, 55281, Yogyakarta, Indonesia. Escobal, P.R (1965). Methods of Orbit Determination. Wiley, New York Ezeomedo I.C, Anukwonke C.C and Ono M.N (2017). Space Science and Technologies in Environmental Geodesy. A paper presented at the Nigeria Association of Geodesy General Assemble/Scientific Conference, Garden City 2017, Port Harcourt, Rivers State. Francis I. Okeke, Nosa O. Alohan and Lawrence Hart (2018). Land Subsidence Mapping and Monitoring of Part of Niger Delta Region of Nigeria Using SBAS-DInSar Technique Within the ESA Geohazard Exploitation Platform (GEP). Nigerian Journal of Geodesy, vol 2(2), pp75-85 Fubara D.M.J. (2006). Improved Determination of Nigerian Geodetic Datum Transformation Parameters for Effective use of GPS. Quality Control Report for Shell Petroleum Development Company of Nigeria Limited, Port Harcourt. Fubara, D.M.J., 2011. Space Geodesy in Coastal and Marine Environment. Union lecture, Nigeria Association of Geodesy 2011 Conference/ General Assembly, University of Nigeria Enugu, 14th to 16th September, 2011). Hart, Lawrence; Udeh, Kenneth; Oba, Tamunobelema (2018). A Comparative Study of the Classical and High Definition Survey Approaches in Subsidence Monitoring of Crude Oil Storage Tanks. A Conference paper presented at the 54th Annual General Meeting (AGM) and Conference of the Nigerian Institution of Surveyors 17th to 21st June, 2019 at Awka, Anambra State. Hart, L (2015). Development of Datum Transformation Procedure for Nigeria Based on National Transformation Version 2 (NTv2) Model. An Unpublished Ph.D Thesis, submitted to the Department of Geoinformatics and Surveying, University of Nigeria, Enugu Campus, Nigeria. Heri Andreas, Hasanuddin Z. Abidin, Irwan Gumilar, Dina A. et al. (2018). The Use of GNSS GPS Technology for Offshore Oil and Gas Platform Subsidence Monitoring, in Multipurposeful Application of Geospatial Data edited by Rustam B. Rustamov IntechOpen Limited, London. Hirt, C. (2015). Digital Terrain Models. In: Encyclopedia of Geodesy (Ed. E.W. Grafarend), Springer, Berlin, Heidelberg. Jatau, B. (1990). Space Technology for Progress and the Environment. Workshop Proceedings of the Annual General Meeting and Conference of Nigerian Institution of Surveyors, Kano, Nigeria. Katarzyna P. (2009). Analysis of Compilation Technology of Digital Terrain Model Based on Satellite, Tacheometric and Photogrametric Data. Lecture Notes in the Department of Surveying, University of Warmia and Mazury in Olsztyn. King R. W, Masters, E.G, Rizos, C, Stolz, A. and Collins, J (1985). Surveying with GPS, Monograph 9, School of Surveying, University of New South Wales, Kensington, Australia. Leick, A (1995). GPS Satellite Surveying 2nd ed. John Wiley & Sons, Inc. New York
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Massonnet, D.; Feigl, K.L. (1998) Radar Interferometry and its application to changes in the Earth’s surface. Rev. Geophys., 36(2), 441–500 Okeke, F. I. and Moka E. C. (2004). Detection and Monitoring of Land Subsidence caused by anthropogenic activities in Nigeria (Niger Delta) using InSAR Technique, Proceedings of the Nigerian Institution of Surveyors AGM, Conference, May 2004, Port Harcourt, Nigeria. Okeke, F. I. (2005). Application of InSAR Techniques for Topographic Mapping and Earth Surface Deformation Monitoring for Nigeria, Nigerian Journal of Space Research, 1(1) pp 175 – 199. Smart, W. M (1960). Spherical Astronomy. Cambridge University Press, London. Torge, Wolfgang (1991). Geodesy 2nd Ed, Walter de Gruyter Berlin. New York. Vaníc˘ ek, P., and E.J. Krakiwsky (1986). Geodesy: The Concepts. 2nd ed., Elsevier Science Publishers, Amsterdam, North Holland, Netherlands. Wolf P.R. & Ghilani C.D. (2006). Elementary Surveying: An Introduction to Geomatics. Pearson Prentice Hall, Pearson Education, Inc., United States of America.
Cite this article as:
Hart L., Oba T. and Babalola A., 2019. Geometric and Dynamic Application of Satellite Geodesy in Environmental Mapping: A Conceptual Review. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 386-397. https://doi.org/10.36263/nijest.2019.02.0153
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Nigerian Journal of Environmental Sciences and Technology (NIJEST)
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501
Vol 3, No. 2 October 2019, pp 398 - 409
Residents’ Perception of Importance and Satisfaction with Infrastructure in Selected Public Housing Estates in Osun State, Nigeria
Oyedele J.B.* and Oyesode M.F. Department of Estate Management, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria. *Corresponding Author: [email protected]
https://doi.org/10.36263/nijest.2019.02.0152 ABSTRACT
This study examined residents’ level of satisfaction with the available infrastructure in Moremi, Oroki and Akoda Estates in Osun State, with a view to enhancing provision of infrastructure. Primary data was used for the study. Questionnaire was used to elicit information from the residents of the three selected public housing estates from the three senatorial districts in Osun State, each public housing estate representing one senatorial district. These public housing estates are under the portfolio of Osun State Property Development Corporation (OSPDC), Osogbo. The public estates include, Moremi Estate in Osun east senatorial district with 416 residential buildings, Oroki Estate in Osun central senatorial district with 816 residential buildings and Akoda estate in Osun West senatorial district with 46 residential buildings. These reflect a total of 1,278 residential buildings where systematic random sampling was adopted in selecting 20% of the residential buildings in the three selected public housing estates. A total of 255 residential buildings were selected, from which a resident was selected for questionnaire administration. The data collected were analyzed using relative importance index (RII) and Residents' Satisfaction Index (RSI) analysis. The result showed that the average Residents' Satisfaction Index (RSI) for the level of satisfaction derived from the infrastructure in the study area was 2.49 which showed that the residents were not satisfied. This study concluded that the residents were not deriving adequate satisfaction from the infrastructure available in the public housing estates. The study recommends that there is need to integrate residents’ preferred infrastructure into development policies: The residents’ preferred infrastructure identified in this study should be linked and integrated into the development policy designs for the estates.
Keywords: Infrastructure, public housing estates, residents, satisfaction.
1.0. Introduction Infrastructure is a key factor in achieving the economic and social objectives of a society (Iseh, 2003). It is imperative for enhancing economic growth and development. Infrastructure refers to the summation of all amenities which enable a city to function effectively (Nubi, 2002). These infrastructures include electricity, waste water disposal, road, sewage disposal, drainage, pipe-borne water, health, security, schools among others. It is the framework of services that provide the essential well-being and determine the quality of life of citizens. Infrastructure are the necessary installations on which the growth and continuity of a community depends (Zaira and Ayyub, 1999). No nation can brag of notable development or an improved economy without adequate provision of basic infrastructure for its citizens’ well-being. Developing an understanding of residents’ satisfaction is necessary in determining how infrastructure has fulfilled the expectations of the residents. This will help to know the extent to which satisfaction with the available infrastructure has affected citizens’ wellbeing. Satisfaction can be defined as a measure of the difference between the actual and expected performances of the services aimed at
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 398 - 409 meeting the expectations and needs of the end users during or after the consumption or use (Ibem, 2013). Therefore, residents’ satisfaction is described as a means whereby there are no complaints about the infrastructure and living conditions since the needs and target of the residents are met; therefore, it is the extent to which individuals’ needs are fulfilled (Salleh, 2008). Contrary to the definition of residents’ satisfaction, the condition of infrastructure in conjunction with housing situation has been in a sorry state both quantitatively and qualitatively, which is evident on most infrastructure that are now decayed and damaged, need repair, refurbishment, rehabilitation or replacement (Ajanlekoko, 2001; Nubi, 2000; Oyedele, 2012). This has resulted in adverse effect on human health, security, privacy and the social status of the residents, which can lead to their dissatisfaction. For instance; diseases associated with the intake of poor quality water such as dysentery and diarrhea; poor electricity supply, and wear and tear of cars as a result of bad road network. All these can be avoided if there is adequate provision of quality infrastructure. Studies on the satisfactory level of tenants with management practices have been documented. For instance, Che-Ani, et al. (2009) examined the level of satisfaction of the management of high-rise residential buildings in Malaysia. The study posited that the level of satisfaction was very low with the quality of management provided. Ayarkwa and Agyekum (2013) evaluated the level of satisfaction of residents with the management of Social Security and National Insurance Trust housing (SSNIT) in Ghana. The study found that the residents were dissatisfied with the management in the areas of maintenance and accessibility to management and therefore requested for routine maintenance. These studies were on the residents’ satisfaction with the level of management practice in residential property but not on the infrastructure provided, which will be the focus of this study. Oloyede (2016) examined residents’ satisfaction with public housing estate in Osun State, Nigeria. However, the study did not examine the condition of the available infrastructure and the importance the residents attached to the available infrastructure. The study posited that residents were satisfied with the management of the estates with respect to the level of privacy and the method of collection and allocation of ground rent and they were satisfied with only electricity, security and water supply among other infrastructure in the estates. Furthermore, studies were carried out on the residential satisfaction with private housing estates and organized private sectors. These included Waziri, Yusof and Salleh (2013), and Agbola and Adegoke (2017). Waziri, Yusof and Salleh (2013) examined residential satisfaction with private housing estate development in Abuja, Nigeria where residents generally expressed low satisfaction with their dwelling unit features but were neither satisfied nor dissatisfied with the overall housing. Agbola and Adegoke (2017) investigated the residential satisfaction and the organised private sector housing in Nigeria and it was revealed that residents of organised private sector housing estates in Nigeria had high level of satisfaction with most of their building components, in-house services and neighbourhood infrastructure. In addition, studies outside Nigeria have been carried out on the satisfaction of the residents. These include Karim (2008); Lee, You and Huang (2013) and Lundgren (2013). Karim (2008) examined the satisfaction of residents on community infrastructure in Shah Alam, Malaysia. The study posited that availability and accessibility of infrastructure are important factors that can determine the level of satisfaction of residents. In another dimension, Lee et al. (2013) investigated the influence of public infrastructure and environmental quality on residential satisfaction in Taiwan. These studies are offshore, as such; their findings may not be immediately applicable to the Nigerian environment. Apart from the broad importance of infrastructure to the economy, the importance attached to infrastructure is also reflected in businesses and households. For businesses, infrastructure can help to lower fixed costs of production, especially transportation costs, which are often a central determinant of where businesses are located (Romp and de Haan, (2007). For households, a wide variety of final goods and services are provided through infrastructure services, such as water, energy, and telecommunications (Straub, 2011). Hence, infrastructure is generally understood to be a key driver in
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 398 - 409 the economic well-being of not just the country, but also a critical factor in attracting businesses and enhancing property values within a given neighbourhood. This is particularly germane to the overall business concerns within the study area (Moremi, Oroki and Akoda housing estates in Osun State). Apparent from the foregoing, there is a compelling need to examine the importance of infrastructure within the selected public estate for the reason that the quality of infrastructure has influence on property investment. It is also evident that residents’ satisfaction with the quality of infrastructure provided in public estates under the portfolio of Osun State Property Development Corporation (OSPDC) has not been sufficiently empirically documented; hence this study.
2.0. Review of Literature 2.1. Importance of infrastructure Infrastructure is of great importance ranging from promoting economic growth to poverty alleviation. It allows the unit to perform its function of creating an efficient platform for the occupants to organize themselves (Akinloye, 2009). Road infrastructure helps in fast accessibility to destinations and increased productivity in the economy. It also helps in reducing poverty in the sense that it provides reliable access to markets for goods to be sold in their fresh state and at lower prices. This also reduces the rate of accidents. In case of Water and Sanitation, economic growths are enhanced at the long run and reduced poverty through improved health, reduction in health-related spending and thereby have the potential to increase the income savings of the residents. Telecommunication as part of infrastructure helps in the improvement of access and transfer of data which leads to reduction in travel times and increased productivity, information which help in decision making are accessed easily thereby reducing poverty. Infrastructure is important for the services it provides rather than for its own sake, it is the main factor behind cultural, social and economic opportunities and quality of life. It is the major pointer to the desired utility derived by occupiers in residential property. The availability of quality infrastructure such as electricity, water supply, road, security and other types of infrastructure is very important as it raise the quality and standard of living of the residents which will enhance the socio-economic characteristics of the residents leading to creativity in the mind, innovations, gainful employment, comfortability, self-reliance, create wealth and above all ensure reduction in crime and security issues (Anthony and Pre-ebi, 2017).
2.2. Types of infrastructure Zakout (2006) classified infrastructure into basic infrastructure components (BIC) and the supportive infrastructure components (SIC). The examples of the basic infrastructure components are storm water drainage, access and paving, water supply, power supply, wastewater treatment and disposal, sewage system, security lighting and telecommunication; and the examples of supportive infrastructure components are community market, Parks and green spaces, Health infrastructure, educational infrastructure and religious center. Infrastructure was classified into two in the study of Okoye (2014) which are Basic Infrastructure which consists of roads, water supply, non- sanitary facilities which are known as drainage, sanitary facilities known as sewerage, waste and disposal system, transport, electric supply; and Non-Basic Infrastructure comprising of education, hospital, telecommunication, security, fire-fighting services, social-cultural recreation parks, banks. The major human needs that sustain life is the Basic Infrastructure. Other classifications of infrastructures are Economic Infrastructure according to Torissi (2009) which gives direct support and help in having productive performance these are roads transport, highways, airports, marine transport, sewer networks, aqueducts, gas networks etc; Social Infrastructure
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 398 - 409 according to Hansen (1965 ), which increase the social comfort and act on the economic productivity this include schools, structures for public safety, hospitals; Aschauer (1989) & Mastromarco (2006) classified infrastructure into core and not-core infrastructures; core infrastructures include roads and highways, airports, public transport, electric and gas networks, network for water distributions and sewer network while the not-core residual component. Infrastructure is divided into two types according to Kumar (2005) these are Hard infrastructure and Soft infrastructure. Hard infrastructure refers to the physical networks that are large and necessary for the modern industrial nation to function well and soft infrastructure refer to the institutions needed to maintain the economic, health and cultural and social standards of the country which include the health, education, judiciary systems and security. Infrastructure can also be classified into horizontal and vertical. Roads, bridges, dams, buildings, rail and telecommunication are horizontal, while policies, laws, rules and orders are vertical. Despite the roles of infrastructure in nation building, developing countries are still backward in provision of infrastructures.
2.3. Residents’ satisfaction with housing infrastructure Parker and Mathews, (2001), Ueltschy, Laroche, Eggert and Bindl (2007) and Hanif, Hafeez and Riaz (2010), d escribed satisfaction as the evaluation (that is based on individual judgement and perspective) of the products and services’ performance in meeting the expectations and needs of the users or residents. Salleh (2008) described satisfaction as state whereby there are no complaints about the infrastructure and living conditions since the needs and target of the residents are met. The quality of neighbourhood where people live in have influence on the manners and experience of its residents (Danquah and Afram, 2014), this will also enhance their satisfaction. Such satisfaction in a residential property includes shelter, health, privacy, protection, comfort, convenience, and dignity (Oladapo & Adebayo 2014). Residents should be able to withdraw and rest from the day to day stressful demands of life. This is a reflection of a conducive housing unit (Ndubueze , 2001). Therefore, the economic, physical and environmental needs of the occupants should be satisfied by habitable housing units. However, when the needs of the residents in terms of quality infrastructure are not met, this result to dissatisfaction and this will cause a negative impact on the well-being of the residents (Husna and Nurizan, 1987). Ramdane and Abdullah (2000) and Galster (1985) established four major objectives of which satisfaction on housing has been used these are; first, for prediction of the quality of life’s perception of the individual generally. Second, influences the changes in the surrounding areas as a result of residents’ mobility. Third, the success of the development of the private sector can be measured through it. Fourth, to measure the individual’s acceptance based on the existing inadequacies in the development of surrounding area and to determine the relationship between the background of the residents and their attitude towards movement. Mohit, Ibrahim and Rashid (2010) found that in Malaysia, most of the households in the public low- cost housing that were newly constructed were most satisfied with the estates’ social environment and the housing units’ support services, while based on their housing conditions and it environ, they were moderately satisfied. Findings from the study of Mohit and Azim (2012) revealed that more than half of the Hulhumale and Maldavies public housing residents were not that satisfied based on their present buildings but they have higher satisfaction level with the services and public facilities than the housing estates social environment and dwelling units’ physical space.
3.0. Materials and methods Primary data was collected from the residents in respect of their socio-economic characteristics such as importance the residents attached to the available infrastructure and the level of residents’ satisfaction with the available infrastructure. This was obtained through questionnaire administration.
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The Study population for this research consists of the selected public housing estates under the portfolio of Osun State Property Development Corporation (OSPDC). The multistage sampling technique was adopted in this study. The first stage involved the identification of the public estates under the portfolio of Osun State Property Development Corporation. There are fifteen estates under the portfolio of Osun State Property Development Corporation (Table 1). The second stage involved the selection of the public estates where the research was carried out. In this regard one public estate was purposively selected in each senatorial district using purposive sampling. In this wise, three estates were surveyed which include Moremi Estate, Ile-Ife in Osun East, Oroki Estate, Osogbo in Osun Central and Akoda Estate, Ede in Osun West.
Table 1: Public Estates under the Portfolio of Osun State Property Development
S/N Senatorial Districts Name of Estate Estates Sampled Ajaka Estate Owa-Ooye Estate 1 Osun East Owamiran Estate Moremi Estate Ipetumodu Estate Moremi Estate Agunbe Estate Oroki Extension 2 Osun Central Okuku Estate Oroki Estate Okinni Estate Oroki Estate Olufi Estate Oluwo Estate 3 Osun West Ile-Ogbo Estate Akoda Estate Aiyegunle Estate Akoda Estate Source: Field Survey, 2019 The third stage is the selection of residential buildings in the selected public estates where questionnaire was administered on the residents. Preliminary survey revealed that Moremi estate has four hundred and sixteen (416) occupied residential buildings, Oroki estate has eight hundred and sixteen (816) occupied residential buildings while Akoda estate has forty-six (46) occupied residential buildings, making a total of one thousand two hundred and seventy-eight (1,278) occupied residential buildings as shown in table 2. Systematic random sampling was adopted in selecting every 5th building in the three housing estates after the first building have been randomly selected, which represented 20% of the buildings which is 83 residential buildings in Moremi estate, 163 residential buildings in Oroki estate and 9 residential buildings in Akoda Estate. This gives a total of 255 copies of questionnaire that was administered on the residents as shown in Table 2. The last stage is the administration of questionnaire on the respondent each from the 255 residential buildings. Table 2: Number of Residential Buildings Surveyed in Moremi, Oroki and Akoda Public Estates
Number of Residential Estate Location Percentage Sample Size Buildings Moremi Estate Ile-Ife 416 20 83 Oroki Estate Osogbo 816 20 163 Akoda Estate Ede 46 20 9 Total 1278 255 Source: Field Survey, 2019
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The data collected were analysed using the Mean, Residents’ Importance Index (RII) and the Residents’ Satisfaction Index (RSI). The mean was used in the estimation of respondents rating of the relevant variables. These respondents rating was extracted from responses collected using Likert scale. Mean analyses were employed to arrive at different indices in the study such as Residents’ Importance Index (RII) and Residents’ Satisfaction Index (RSI). To determine these indices, for the Residents’ Importance Index (RII) for example, residents were requested to rate the variables using 5-point Likert Scale of “Very Important” (VI-5), “Important” (I- 4), “Just Important” (JI-3 “Not Important” (NI-2) and “Not at All Important” (NA-1) for each of the identified variables. To arrive at Mean Weight Value (MWV), the Afon (2005) and Taiwo (2014) steps were adopted: Weight values of 5,4,3,2 and 1 were respectively attached to each rating of VI, I, JI, NI and NA. Summation of Weight Value (SWV) was calculated. The SWV is the addition of the product of the value attached to a rating and respective number of respondents to the rating. SWV was divided by the number of respondents. This is expressed mathematically as:
5 SWV = (1) X iYi I =1 where: SWV = Summation of Weight Value,
Xi = number of respondents to rating i;
Yi = the weight assigned a value (i = 1, 2, 3, 4, 5).
The SWV divided by the number of respondents gives the Mean Weight Value (MWV) SWV MWV = 5 (2) i = X i=1 i
The average level of importance attached to the variables in the study area is arrived at by the ratio of the sum of the MWV to all variables and total number of variables rated. Hence, MWV is given by:
MWV = ∑ MWVi-j / n (3) where: MWV = Mean Weight Value for the study area, n = number of variables.
4.0. Results and Discussion 4.1. Importance and satisfaction derived from the available infrastructure Satisfaction is usually measured through different indicators (Salleh 2008; Lee & Park 2010; Amole, 2012). Such indicators do have social, economic, and environmental attributes. The importance attached to each of these indicators is a measure of how it influences satisfaction. To this end, residents were instructed to determine the importance of some indicators (infrastructure) in measuring their satisfaction. Each indicator was rated using five-point Likert scale: 'Not at all important (Likert Scale=1), ' Not important' (Likert Scale=2), 'Fairly important', '(Likert Scale=3) Important' (Likert Scale=4) and 'Very important'(Likert Scale=5). The analysis of the data obtained resulted in the generation of an index tagged Relative Importance Index (RII). While RII showed the importance attached to each indicator by the residents' in the determination of their satisfaction; the actual satisfaction could be determined by the satisfaction residents enjoyed on each indicator. Therefore, respondents also rated their level of satisfaction on each indicator using the five-point Likert of 'Not at
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Nigerian Journal of Environmental Sciences and Technology (NIJEST) Vol 3, No. 2 October 2019, pp 398 - 409 all satisfied,’ 'Not satisfied', ' Fairly satisfied', 'Satisfied’ and ‘Very satisfied’. The level of satisfaction is measured by an index called Residents' Satisfaction Index (RSI). With the above explanation, the mean RII for the whole study area was computed to be 4.49 (Table 3). An index that was close to 4 (that is, important). However, the level of satisfaction derived on these indicators for the study area was 2.49 (Table 3). An index close to 2 (that is, not satisfied). The three most important infrastructure to residents and their corresponding satisfaction derived from the infrastructure were electricity supply during the night (RII = 4.82; RSI = 3.10), security during the night (RII = 4.81; RSI = 3.02) and communication (RII = 4.80; RSI = 2.69), as presented in Table 3. This could have a far-reaching implication for policy formulations on the importance of having more electricity supply, enhanced security and good communication networks particularly during the night. In addition to the RII determined for each infrastructure in each of the public housing estate, the mean RII for each estate was also obtained. These were 4.42, 4.55 and 4.57 for Oroki, Moremi and Akoda public housing estates respectively (Table 4), indices that were close to 4, meaning they are important. Similarly, the average RSI for each estate was determined. These were 2.54, 2.43 and 2.62 for Oroki, Moremi and Akoda public housing estates respectively. Of importance to this study were the infrastructures with indices greater than the average index of the study area and those below it. Indicators that were of more importance (that is, above the study area average index) included: electricity supply during the night (RII = 4.82), security during the night (RII = 4.81), road network (RII = 4.75), among others. However, those below it included civic centre (RII =4.13), paved walkway (RII =4.02) and religious centre (RII=3.95).
Table 3: Importance Attached to Available Infrastructure and Residents’ Level of Satisfaction with Available Infrastructure in the Study Area
Importance attached to available infrastructure in the study Residents’ level of satisfaction with available area infrastructure in the study area Infrastructure RII Ranking Infrastructure RSI Ranking Electricity supply during the night 4.82 1 Electricity supply during the day 3.11 1 security during the night 4.81 2 Electricity supply during the night 3.10 2 Communication 4.80 3 security during the night 3.02 3 Security during the day 4.77 4 Security during the day 2.94 4 Road network 4.75 5 Borehole 2.89 5 Drainage 4.73 6 Communication 2.69 6 Borehole 4.71 7 Road network 2.54 7 Refuse disposal 4.70 8 hand dug well 2.51 8 Electricity supply during the day 4.69 9 Religious centre 2.50 9 Hospital 4.60 10 Internet 2.47 10 Street light 4.59 11 School 2.46 11 Internet 4.53 12 Refuse disposal 2.38 12 School 4.53 12 Pipe borne water 2.33 13 Pipe borne water 4.48 14 Perimeter fencing 2.33 13 Parking space 4.33 15 Drainage 2.29 15 Well 4.23 16 water tanker 2.25 16 Perimeter fencing 4.20 17 Paved walkway 2.25 16 water tanker 4.18 18 Parking space 2.22 18 Recreation centre 4.13 19 recreation centre 2.19 19 Civic centre 4.13 19 Street light 2.16 20 Paved walkway 4.02 21 Civic centre 2.10 21 Religious centre 3.95 22 Hospital 2.08 22 Mean RII 4.49 Mean RSI 2.49
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Presented in Tables 4 and 5 are the summary of the importance residents attached to the satisfaction derived from infrastructure and Residents expressed satisfaction derived from infrastructure in each of the estates respectively. In Oroki estate, the mean RII and RSI indices were 4.42 and 2.54 respectively. This implies that while the infrastructures are important to the residents in the estate, residents were not satisfied with them. Infrastructures that were very important to the residents in Oroki estate included road network, communication, electricity supply during the day and night, security during the night, drainage and security during the day. Others were refuse disposal, street light, borehole, hospital, school, pipe borne water and internet. On the other hand, facilities that were low in importance to them included civic centre, water tanker, fire fighter, recreation centre, waste water treatment and disposal, perimeter fencing and religious centre. Findings showed that residents of Oroki estate (Table 5) were satisfied with infrastructures such as electricity supply during the day (3.23), electricity supply during the night (3.17), security during the night (3.11), security during the day (3.05), borehole (2.88). Others were road network (2.69), communication (2.65), bank (2.64) hand dug well (2.57) and religious centre (2.55). In the same vein, the findings revealed that residents were not satisfied with the drainage (2.29), which they perceived as being very important to them. The least three indicators that residents were not satisfied with in Oroki estate were hospital, civic centre and pipe borne water. Summary of the importance attached to infrastructure and satisfaction index computed for the residents of Moremi estate are also presented in Tables 4 and 5 respectively. The mean RII for the estate was 4.55 while the average RSI was 2.43. This implies that generally within the estate, residents perceived the rated infrastructure as important. However, the average satisfaction level on the infrastructure was not satisfactory. Also in Moremi Estate, the study showed that the following indicators (Table 4) have the respective indices such as electricity supply during the night (4.92), security during the day (4.89), security during the night (4.89), borehole (4.88), communication (4.83), refuse disposal (4.79), road network (4.77), drainage (4.77), internet (4.67), hospital (4.67), electricity supply during the day(4.61), street light(4.60), school (4.55) and pipe borne water (4.49).. Findings showed that what residents perceived to be of importance among the indicators were not very satisfactory. These indicators were refuse disposal, drainage, street light and hospital. The highest level of satisfaction was expressed on indicators such as electricity supply during the day (3.11) electricity supply during the night (3.10), security during the night (3.02), security during the day (2.94), borehole (2.89), communication (2.69), road network (2.54) and hand dug well (2.51). Other facilities include religious centre (2.50), internet (2.47) and schools (2.46). The mean RII for Akoda estate was 4.57 while its mean RSI was 2.62. This indicated that the perception held of the importance of indicators was far higher than the satisfaction enjoyed on related infrastructure within the estate, similar to findings from Oroki and Moremi estates. The study concluded that residents' level of satisfaction was very low with the indicators rated to be of high importance. These were security during the night, borehole, refuse disposal, security during the day, hospital and parking space. A common observation was the fact that most of the indicators rated important were with the least satisfaction. The five indicators on which residents had a high level of satisfaction in Akoda public housing estate were communication (3.33), electricity supply during the night (3.11), electricity supply during the day (3.00), pipe borne water (3.00) and internet (3.00) (Table 5). It can generally be concluded that residents of the estates were less satisfied with most of the indicators that were of greater importance to them.
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Table 4: Importance attached to available infrastructure in Oroki, Moremi and Akoda (Source: Author’s Field Survey (2019)) Oroki Moremi Akoda Infrastructure RII Ranking Infrastructure RII Ranking Infrastructure RII Ranking Road network 4.81 1 Electricity supply during the night 4.92 1 Pipe borne water 4.89 1 Communication 4.78 2 Security during the day 4.89 2 security during the night 4.89 1 Electricity supply during the day 4.76 3 security during the night 4.89 2 Electricity supply during the day 4.78 3 Electricity supply during the night 4.73 4 Borehole 4.88 4 Electricity supply during the night 4.78 3 security during the night 4.73 5 Communication 4.83 5 borehole 4.78 3 Drainage 4.69 6 Refuse disposal 4.79 6 Communication 4.78 3 Security during the day 4.66 7 Road network 4.77 7 Drainage 4.78 3 Refuse disposal 4.61 8 Drainage 4.77 7 Refuse disposal 4.78 3 Street light 4.61 8 Internet 4.67 9 Security during the day 4.78 3 Borehole 4.54 10 Hospital 4.67 9 Hospital 4.54 10 Electricity supply during the day 4.61 11 Hospital 4.67 10 School 4.51 12 Street light 4.60 12 Parking space 4.67 10 Pipe borne water 4.42 13 School 4.55 13 Internet 4.56 12 Internet 4.41 14 Pipe borne water 4.49 14 school 4.56 12 Parking space 4.25 15 Perimeter fencing 4.45 15 Perimeter fencing 4.44 14 Well 4.19 16 Parking space 4.37 16 Street light 4.33 15 Civic center 4.14 17 Well 4.23 17 Water tanker 4.13 18 Recreation center 4.23 18 Civic center 4.22 16 Recreational center 4.04 19 Water tanker 4.21 19 Road network 4.11 17 Perimeter fencing 3.95 19 Paved walkway 4.17 20 Religious centre 4.11 17 Religious centre 3.89 21 Civic center 4.11 20 Paved walkway 4.00 19 Paved walkway 3.89 22 Religious center 4.00 22 Mean RII 4.42 Mean RII 4.55 Mean RII 4.57
Table 5: Residents expressed satisfaction on available infrastructure in Oroki, Moremi and Akoda (Source: Author’s Field Survey (2019)) Oroki Moremi Akoda Infrastructure RSI Ranking Infrastructure RSI Ranking Infrastructure RSI Ranking Electricity supply during the day 3.23 1 Electricity supply during the night 3.01 1 Communication 3.33 1 Electricity supply during the night 3.17 2 security during the night 3.00 2 Electricity supply during the night 3.11 2 security during the night 3.11 3 Electricity supply during the day 2.99 3 Electricity supply during the day 3.00 3 Security during the day 3.05 4 Borehole 2.95 4 Pipe borne water 3.00 3 Borehole 2.88 5 Security during the day 2.89 5 Internet 3.00 3 Road network 2.69 6 Communication 2.65 6 Drainage 2.67 6 Communication 2.65 7 Pipe borne water 2.51 7 school 2.67 7 Hand dug well 2.57 8 Hand dug well 2.48 8 Paved walkway 2.67 7 Religious center 2.55 9 School 2.47 9 Borehole 2.56 9 Refuse disposal 2.48 10 Internet 2.45 10 Civic center 2.56 10 School 2.43 11 Religious centre 2.43 11 Religious center 2.56 11 Internet 2.42 12 Road network 2.39 12 Road network 2.44 12 Parking space 2.41 13 water tanker 2.31 13 Security during the night 2.44 12 Paved walkway 2.39 14 Perimeter fencing 2.29 14 Hospital 2.44 12 Perimeter fencing 2.37 15 Refuse disposal 2.27 15 Parking space 2.44 12 Drainage 2.34 16 Drainage 2.19 16 Refuse disposal 2.33 16 Streetlight 2.25 17 recreation centre 2.16 17 Security during the day 2.33 16 Water tanker 2.19 18 Streetlight 2.08 18 Perimeter fencing 2.22 18 Recreational center 2.18 19 Paved walkway 2.04 19 Street light 2.00 19 Hospital 2.17 20 Parking space 1.97 20 Civic center 2.16 21 Civic center 1.97 21 Pipe borne water 2.16 22 Hospital 1.93 22 Mean RSI 2.54 Mean RSI 2.43 Mean RSI 2.62
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5.0. Conclusions The study revealed that the level of satisfaction residents derived from available infrastructure in the study area was relatively low. This study has provided information on what should be considered and/or put in place by government in framing development policies aimed at addressing the problem of residents of public housing estates, such as policies involving government intervention programs and integrating residents' preferred infrastructure into urban development policies. For instance, government could capitalise on residents’ preferred period particularly the night period to supply more electricity, enhance security and good communication networks. Findings from this study revealed that public housing estates have a lot of potentials to enhance the satisfaction level of dwellers and also with great multiplier effects that can go a long way in alleviating poverty and save enough resources for development. Finally, findings from this study can provide information that could enhance policy formulation towards proffering solutions to the problems associated with low level of residents’ satisfaction with available infrastructure, particularly in the identified public housing estates in Osun State. In order to achieve this, the following recommendations are made as policy guidelines for decision makers toward a sustainable development of housing estates, particularly public estates. This study hereby recommends that there is need to integrate residents’ preferred infrastructure into development policies: The residents’ preferred infrastructure identified in this study should be linked and integrated into the development policy design for the estates. The identified specific needs of the residents are extremely important in order to achieve rapid development in the area, with the resultant improvement on the quality of life of the residents. These development policies could dovetail into development programmes championed by government. The recommendations can also be employed by other developing nations of the world in urban settings that have similar residential characteristics with the study area, in a bid to minimize the problems inhibiting residents’ satisfaction with available infrastructure.
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Oyedele J.B. and Oyesode M.F., 2019. Residents’ Perception of Importance and Satisfaction with Infrastructure in Selected Public Housing Estates in Osun State, Nigeria. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 398-409. https://doi.org/10.36263/nijest.2019.02.0152
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Nigerian Journal of Environmental Sciences and Technology (NIJEST)
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ISSN (Print): 2616-051X | ISSN (electronic): 2616-0501 Vol 3, No. 2 October 2019, pp 410 - 415
Engineering Feasibility of Building Blocks Produced from Recycled Rice Husks
1,* 1 1 1 1 Atikpo E. , Ukala D. C. , Agori J. E. , Agbi G. G. , Iwemah E. R. , Umukoro L. O.1 and Michael A.2 1Department of Civil and Environmental Engineering, Faculty of Engineering, Delta State University, Oleh Campus, PMB 1, Abraka, Delta State, Nigeria 2Department of Environmental Technology, Faculty of Environmental Sciences, Federal University of Technology, Owerri, PMB 1526, Imo State, Nigeria *Corresponding Author: [email protected], [email protected]
https://doi.org/10.36263/nijest.2019.02.0066 ABSTRACT
Rice husks abundance in Nigeria requires the consideration of their alternate economic uses to prevent environmental pollution from the waste heaps, litter and combustion. This study focused on the determination of the feasibility of blocks made from recycled rice husks for building construction. Twenty-four absolute cubes were moulded from a mixture of fine aggregate (sand), binder (cement) and water. These were used for control experiments. Also, 144 cubes of partially replaced sand with rice husks in the steps of 10, 20, 30, 40, 50 and 60% were produced and cured for 7, 12, 21 and 28 days like the absolute cubes. They were weighed and experimented for some engineering properties including compressive strength in triplicate. The average values of triplicate readings were recorded and documented. Laboratory strengths result at the 28th day were compared with the reference strength of sandcrete block provided in the Federal Building Code to ascertain the performances of the partial sandcrete cubes. The low maximum compressive strength of 0.54N/mm2 obtained at 30% replacement and 28th day curing showed that rice husks were not feasible for replacing fine aggregate in sandcrete blocks at the percentages tested. This strength value is far less than the minimum allowable compressive strength of 1.75N/mm2 of individual blocks provided in Federal Building Code.
Keywords: Recycling, rice husks, housing blocks and construction industry
1.0. Introduction
Waste heaps from rice husks generates serious environmental disturbance in areas where rice is produced, processed and the wastes are disposed. Stake holders are usually bordered about the disposal of these husks from the environment and ignore the economic benefits accruable from the wastes. Owners of rice-mills do not see economic gain in rice husks, therefore; they offer them out to free their environments from these wastes. However, Chukwudebelu et al. (2015); Opara (2006); Opeyemi and Makinde (2012); and Nicholas and Folorunsho (2012) have proven the economic and housing benefits of rice husks in the building industry through their research on recycling of rice husk in some forms, especially in the form of rice husk ash (RHA) for economic benefits in the building industry. Carter et al. (1982) worked on the incorporation of ungrounded rice husks into handmade, kiln–fired bricks. They measured properties like density, compressive strength, modules of rupture, water absorption and initial state of absorption; and then concluded that it was possible to substitute up to 50% rice husks (by volume of clay) into bricks without dropping the properties of brick outside the acceptable limits in developing countries.
Rice husks, also known as rice hulls are the hard protecting coverings of rice grains. They are by- products of threshing paddy and constitute close to 20% of the dry mass of harvested paddy. It is made up of about 50% cellulose, 23-35% lignin and 15-20% silica. These husks are economically, readily available in Nigeria.
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Research on wastes recycling for building materials production needs urgent attention because large demand has been placed on the building materials industries owning to the increase in population and rising prices resulting in shortage of building materials.
Sandcrete block commonly used in Nigeria is defined in the Federal Building Code (2006) as a homogeneous mixture of composite material made up of cement, sharp sand and water (Anosike and Oyebade, 2012) with 2.00 N/mm2 (300 psi) average standard strength for blocks, and 1.75 N/mm2 (250 psi) lowest strength of respective block. This strength, if achieved through research on recycling of wastes for the production of building blocks for the construction industry, will go far in saving cost and speeding up national development requiring availability of good shelters for optimal productivities of citizens.
Therefore, this work studied the suitability of rice husks for producing low cost and lightweight construction blocks for the building industry instead of the more expensive sandcrete blocks in current use. This is also in pursuit of the use of environmental friendly, low cost and lightweight materials of required standard in the building industries.
2.0. Methodology
2.1. Materials The materials include rice husks from a rice-mill in Auchi, Edo State of Nigeria; sharp sand (fine aggregate) of 3.35 mm, 0.85%, 2.64, and 2.91 sieve size, moisture content, specific gravity and coefficient of uniformity respectively; and free from loam, organic matter, clay, dirt and any chemical matter; binder - ordinary Portland cement and potable water.
2.1.1. Production of samples Following the provision of the Federal Building Code (2006), cement and sand were properly mixed to ratio 1:8 to achieve an even coloured, consistency mixture. Adequate volume of water was added to ensure a mixture of adequate workability. In the same way, rice husk was introduced in different percentages (10, 20, 30, 40, 50 and 60%) to produce some blocks. For this, cement and rice husks were properly mixed to achieve a uniform colour. Water was added in an adequate proportion to ensure mixture workability before moulding with a mould of 100 mm x 100 mm x 100 mm dimension.
2.2. Methods Twenty-four absolute cubes were moulded from a mixture of fine aggregate (sand), binder (cement) and water. These were used for control experiments. Also, 144 cubes of partially replaced sand with rice husks in the steps of 10, 20, 30, 40, 50 and 60% were produced and cured for 7, 12, 21 and 28 days like the absolute cubes. They were weighed and experimented for some engineering properties including compressive strength in triplicate. The average values of triplicate readings were recorded and documented. Laboratory data of experimented cubes were analyzed and the compressive strengths at the 28th day were compared with the reference strength of sandcrete block provided in the Federal Building Code (2006) to ascertain the performances of the partial sandcrete cubes.
3.0. Results and Discussion
The compressive strengths results are displayed in Figures 1 and 2. Figure 1 centred on control cubes’ strengths variation with curing ages. Figure 2 centred on the comparison of the compressive strengths of cubes with partial rice husks and that of the control cube at curing age 7 days. This comparison was significant to determine the relationship between strengths of partial sandcrete cubes with the 7 days’ strength of control cubes. This showed a great increase in strength of the control cubes over the partial sandcrete cubes.
There was an increase in compressive strength with age, but a decrease in strength with increase in percentage of rice husks from 10 to 20%, and a rise from this point to a peak strength at the replacement of 30%, before a final decrease in strength with replacement of sand in the cubes. Cubes from rice husks attained a maximum strength of 0.54N/mm2 at a percentage replacement of 30 on the
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28th curing day. This strength was found to be far less than the minimum strength of 1.75 N/mm2 specified for sancrete blocks in (Federal Building Code, 2006).
4.5
)
2 4 3.5 3 2.5
2 Compressive Strength 1.5 of Control Cube 1
Compressive Compressive Strength (N/mm 0.5 0 0 7 14 21 28 35 Age (Days)
Figure 1: Compressive strength of control cube and cube age
3
) 2 2.5 7 Days Compressive Strength 2 14 Days Compressive Strength 1.5 21 Days Compressive 1 Strength 28 Days Compressive
0.5 Strength Compressive Compressive Strength (N/mm 7 Days Compressive 0 Strength of Control Cube 10 20 30 40 50 60 Percentage of Substitution (%)
Figure 2: Compressive strengths in comparison
As shown in Figure 3, absolute sandcrete absorbed less water in comparison with partial sandcrete of replaced sand with rice husks. The water absorption rate increased with percentage replacement with rice husks. As discovered in previous work by Subramani and Ravi (2015), the more water absorption capacity of a sancrete block, the weaker the block and vice versa. The bond between blocks and mortar is highly dependent on their water absorption capacities. Thus, if the water absorption rate of a block is high; it absorbs water from fresh laid mortar and this ultimately results to weak strength (Subramani and Ravi, 2015).
A good number of the cubes produced from partially replaced sand with rice husks had higher water absorption capacities above the minimum 12% specified in Federal Building Code (2006).
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80 70
60 50 40 28 Days Cured Cube 30 Control Cube
WaterAbsorption (%) 20 10 0 10 20 30 40 50 60 70 Percentage Substitution (%)
Figure 3: Water absorption capacities
Bulk densities of cubes are displayed in Figures 4 and 5. Figure 5 shows control cubes bulk densities variations with curing age, while Figure 4 centred on bulk densities comparison. This comparison centred on the bulk densities of cubes from partial rice husks at various substitution percentages with bulk density of the control cube at the 7th day curing age. It was necessary because of the very high strength values of control cubes relative to the cubes with percentage rice husks.
The bulk densities of control sandcrete cubes were far greater than those of cubes produced from partial replacement of sand, and decreased with curing age. The bulk densities of absolute sandcrete cube at day 7 was 1992 kg/m³ while that of cube from partial replacement at 10% and 14 days curing age was 1512 kg/m³ as the highest values for partial sandcrete. Bulk densities were found to decrease with increase in percentage replacement of sand with rice husks. The control sample went above the minimum of 1500 kg/m³ in (British Standard Institute - BSI, 2002), and also, cubes from 10% of rice husks replacement at curing ages 7 and 14 days were above the minimum requirement bulk density values of 1500 kg/m³.
2500
2000 Cube Cured for 7 Days
) 3
1500 Cube Cured for 14 Days
1000 Cube Cured for 21 Days
Bulk Density (g/m Cube Cured for 28 500 Days Control Cube Cured for 0 7 Days 0 10 20 30 40 50 60 70 Percentage Substitution (%)
Figure 4: Bulk densities of partial sandcrete cubes and 7 days control cube
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2500
2000
) 3
1500
1000 Bulk Density (g/m 500
0 0 7 14 21 28 35 Age (Days)
Figure 5: Bulk density of control sample with age
4.0. Conclusions
This work showed that rice husks were not feasible for replacing sand in sandcrete blocks at the percentages of substitution studied. This became obvious from the very low maximum compressive strength value of 0.54N/mm2 for blocks with rice husks. This value is far below the minimum acceptable compressive strength of 1.75N/mm2 for individual blocks provided in Federal Building Code (2006); and occurred at 30% replacement and 28th day curing age.
More litres of water were required for mixing partial sandcrete than required for mixing control sandcrete. Partial sandcrete required more binder (cement) than the control sandcrete.
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British Standard Institute (BSI), (2002). Specification for Clay Bricks and Blocks, BS1200, London.
Carter, G.W., Cannor, A. M. and Mansell, D, S., (1982). Properties of Bricks in Incorporating Unground Rice Husks. Buildi. Envi., 17(4), pp. 285-291.
Chukwudebelu, J.A., Igwe, C.C. and Madukasi, E.I., (2015). prospect of using Whole Rice Husk for the Production of Dense and Hollow Bricks. Afri. J. Envi. Sci. Tech., 9(5), pp. 493-501.
Federal Building Code (2006) in Parameters for Good Site Concrete Production Management Practice in Nigeria, PhD Thesis by Anosike, M.N., (2011) and Submitted to the Department of Civil Engineering, Covenant |University, Ota, Nigeria.
Nicholas, A.M. and Folorunsho, O.A., (2012). Ultilizing Rice Husk Briquettes in Fringe Crucible Furnance for Low Temperature Melting Metals in Nigeria. ETASR. Engin. Technol. Appli. Sci., 2(4), pp. 26-268.
Opara, P.N., (2006). Usability of Rice Husk in the Production of Roofing Sheets. J. Agric. Soc. Res.,6(1), pp. 76 – 79.
Opeyemi, D.A. and Makinde, O.O., (2012). The Suitability of Partial Replacement of Cement with Rice Husk Ash and Bone Powder in Concrete Structures. Inter. J. Emerging Technol. Adv. Eng., 2(9), pp. 261- 265.
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Subramani, T. and Ravi, G. (2015), Experimental Investigation of Coarse Aggregate with Steel Slag in Concrete, 5(5), pp. 64-67.
Cite this article as: Atikpo E., Ukala D. C., Agori J. E., Agbi, G. G., Iwemah E. R., Umukoro L. O. and Michael A., 2019. Engineering Feasibility of Building Blocks Produced from Recycled Rice Husks. Nigerian Journal of Environmental Sciences and Technology, 3(2), pp. 410-415. https://doi.org/10.36263/nijest.2019.02.0066
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