JAGBE Aspatial Distribution of Copper, Ammonia and Phosphate

Journal of Applied Geoscience and Built Environment, Vol. 1 No. 2 (2019) p. 1-5

JAGBE Journal of Applied Geoscience and Built Environment

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A Spatial Distribution of Copper, Ammonia and Phosphate from Road Runoff

Mohd Hairul Khamidun1,*, Muhammad Shakir Naim Che Man 1,, Umi Fazara Md Ali2, Shakila Abdullah3 Mohammad Ashraf Abdul Rahman4

1Faculty of Civil and Environmental Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, MALAYSIA 2School of Environmental Engineering, University Malaysia Perlis, Kompleks Pusat Pengajian Jejawi 3, 02600 Arau, Perlis, MALAYSIA 3Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia, Pagoh Educational Hub, 84600 Pagoh, Johor, MALAYSIA. 4Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, Pagoh Educational Hub, 84600 Pagoh, Johor, MALAYSIA.

*[email protected]; [email protected]

Received 15 August 2019; Abstract: Copper, ammonia and phosphate are among the constituents in road runoff which might Accepted 28 September 2019; contribute effectively in the degradation of the water quality. The current study aimed to illustrate Available online 30 October the spatial distribution of copper, ammonia and phosphate concentrations in Universiti Tun Hussein 2019 Onn Malaysia (UTHM) road runoff. Furthermore, the relationship between traffic volumes and copper, ammonia and phosphate concentrations was also investigated. Mapping analyses showed different levels of these pollutants assessed at the five collecting points namely Persiaran Tun Ghazali Shafie, Persiaran Tun Dr Ismail, Persiaran Tun Ghafar Baba, Jalan Delta 1 and Persiaran Tun Tan Siew Sin. The results revealed that the highest concentration of copper was 0.11 mg/L at Persiaran Tun Dr Ismail and while the lowest concentration was 0.02 mg/L was recorded at Jalan Delta 1.. The highest concentrations of phosphate was 4.87 mg/L observed at Persiaran Tun Ghazali Shafie, while the lowest concentratiuons were 3.13 mg/L at Persiaran Tun Dr Ismail. These concentrations exceeded the permissible limits of class II of National Quality Water Standard. The distribution of copper and ammonia concentration was not significant to average daily traffic except for phosphate. The pathway of these pollutants important to understand due to increase urbanization and roadway usage.

Keywords: ammonia, copper, phosphate, road runoff, spatial distribution

1. Introduction organic materials, whether natural or synthetic can enter water

Modernization in human life and wildly advancement in solution or suspended in runoff [2]. exercises have influenced the normalKeywords: type of water Keyword itself. Water 1, keyword 2, numberAt the of pointkeywords when is theusually rain 3 falls-7, but out more and is about, allowed the if which could recuperate us from ailmentsdeemed additionallynecessary could overflow will stream to the water bodies, for example, lakes hurt us when its creation is not any safer for human utilization. and lakes adjacent. Overwhelming metals, oils, other harmful Expanding quantities of vehicles due to increases of population substances and flotsam and jetsam from development activity particularly in urban territories have great contribution to the and spillage can be conveyed with spill over water to lakes, environmental pollution. Eventually, the pollutants yield from streams and coves. There are many components that add to the the paved parking lots, gasoline and friction of tires wash off water contamination that impact nature. In the long-term, by the rain storm directly to the water bodies [1]. Thus, these serious environmental impacts may occur responsibly by road events lead to the rising index of water pollution as a result of runoff water. Expressway overflow checking considers having accumulation of pollutants in water bodies. Nutrients affirmed starting at now the sorts of pollutions present and enrichments of water bodies such as lakes can result in algae showed how much toxic substances weights and obsessions growth causing excessive oxygen demand through plant depend upon road properties and precipitation patterns. Storm decomposition, reduction of light penetrations and release of water overflow from urban impermeable surfaces amid rain is toxins on the death of blue-green algae. Besides, biodegradable a key polluter of urban conduits, contributing contaminations, for example, silt furthermore, overwhelming metals [3]. In

numerous urban ranges, untreated runoff is released Vis Spectrophotometer were used for the measurements of specifically into the closest conduit, causing different these parameter. The measurements of pH and dissolved antagonistic effects on the aquatic biological system [4]. Road oxygen (DO) were made using a portable meter. The + 2+ 3+ runoff including tunnel wash water spill overs have been concentrations of NH4 , Cu and PO4 obtained in this study distinguished as a noteworthy wellspring of diffuse pollution. were used for spatial distribution mapping using Surfer 8. There are several factors that contribute to the pollution in road runoff. One of it is the arrangement of auto parking spots keeps on growing as the number of autos increments together with their related use for work and recreation activities. Current worldwide assessments are that there are 600,000,000 passenger cars and this number keeps on developing every day [5]. It is widely acknowledged that streets have major natural effects on aquatic ecosystems. For instance, sediment loading can alter the habitat quality [6] and contaminations discharged from transportation [7]. Overflow from streets contains a plenty of pollutants and is considered a major source of diffuse contamination [8] causing negative effects on the getting water bodies [9]. Also, it has been accounted for that over 90 % of spill over is released specifically into waterways in regions that have executed rain and sewage redirection. This implies the expanding number of non-point source pollutants are all the more widely circulated and are hard to control with centralized measures [10]. In addition to contamination, streets and the development of them may irritate or even wreck aquatic natural surroundings physically. Disturbance of connectivity by streets may likewise contrarily influence the movement of animals [11]. In contrast, with earthbound environments, freshwater Fig.1- Sampling Locations living spaces endure more noteworthy biodiversity decay due to different stressors overwhelmed by anthropogenic factors, 2.2 Traffic Volume Count for example, habitat loss and degradation, and contamination Counts of the number of vehicles passing at a point are [12]. This study is carried out to investigate the copper, required to determine the average daily traffic (ADT). On road ammonia and phosphate concentration and their relationship sections, the number of vehicles travelling in each direction was with traffic volumes. Besides, it is crucial to study the points of counted (Norhasnida, 2010). The method used to get the data copper, ammonia and phosphate distribution around UTHM of traffic volume in this study were by automatic method (video that could be visualized through spatial distribution that is recording) for one week. developed using Surfer 8 software. Thus, this data could be used as preliminary data for the future researcher to propose 3. Results and Discussions treatments that could fix the issue. 3.1 Characteristics of road runoff Characterisation of road runoff at five separate locations in 2. Materials and Methods UTHM were examined to determine the concentrations of TSS, + 3- NH4 , PO4 , pH, DO, COD and Cu in the road runoff. 2.1 Sampling Locations and Methods Samplings were performed during rainy seasons on April Table.1 - Comparison of Road Runoff based on NWQS 2018 for two times. Sampling were carried out at five collecting standard points namely Persiaran Tun Ghazali Shafie, Persiaran Tun Dr Ismail, Persiaran Tun Ghafar Baba, Jalan Delta 1 and Persiaran Sampling point (Coordinate) NWQS

Tun Tan Siew Sin as shown in Fig.1. The coordinates of these Standard PTGS PTDI PTGB JD1 PTTSS sampling points were determined using global positioning system. pH 6.5 – 9 6.30 6.09 6.47 6.44 6.37 TSS Sampling method was used to obtain the road runoff < 50 5.20 4.40 6.00 4.00 7.00 sample and was done for three times. The bottles were (mg/L) DO prewashed with distilled water to ensure the purity of road 5 – 7 7.66 5.91 7.21 7.00 6.88 runoff were not being disturbed. The samples were taken using (mg/L) COD < 25 9.00 3.00 7.00 5.00 11.00 grab sampling method using 1L container. The samples (mg/L) collected were the first wash of rainfall before the runoff NH 4 < 0.3 0.32 1.05 0.41 1.14 0.72 discharge into the drainage to make sure the pollutants of road (mg/L) 3- runoff were not washed away. This is important to maintain the PO4 < 0.2 4.87 3.13 3.61 4.27 4.14 integrity of the sample. (mg/L) Cu 0.02 0.02 0.07 0.03 0.02 0.05 2.1 Analytical Methods (mg/L) ADT(v Spatial distribution was mapping from measurements - 9030 6375 3500 4890 6900 + eh/d) concentration of ammonium (NH4 ) using the Nessler method, Note: PTGS-Persiaran Tun Ghazali Shafie; PTDI-Persiaran Tun Dr copper (Cu) using Method 8506 (CuVer1) and phosphate Ismail; PTGB-Persiaran Tun Ghafar Baba; JD1-Jalan Delta 1; PTTSS- 3+ (PO4 ) using the amino acid method. HACH DR 5000 UV– Persiaran Tun Tan Siew Sin. 2 Published by FAZ Publishing http://www.fazpublishing.com/jagbe

Journal of Applied Geoscience and Built Environment, Vol. 1 No. 2 (2019) p. 1-5

+ The pattern of spatial distribution of NH4 concentration shows Table 1 shows the concentration of pollutants at selected the higher density color at PTSS, JD 1 and PTGB as shown in sampling points. Based on the results, all the sampling locations Fig. 2 (a). After the second rainfall event as depicted in + have pH level in range of NWQS level. High concentration of Fig.2(b), the pattern of NH4 concentration is decreasing for suspended solids is 7.00 mg/L located at PTTSS while lowest entire sampling location due to first-flush runoff on 22/4/2018 + suspended solid was at JD1 with 4.00 mg/L. Concentration of was carries concentration of NH4 into water bodies. Road + DO on the road runoff, all the samples have higher than 5 mg/L runoff at PTGS had an increment of NH4 concentration from of dissolved oxygen which means the runoff has good dissolve 0.32 mg/L to 0.41 mg/L. On the other way around, ammonia oxygen. Meanwhile, from the COD results, all the samples of concentration in road runoff at PTDI, PTGB, JD1 and PTTSS road runoff comply with NWQS standard which less than 25 decreases with highest decrement of about 68% at JD1. + 3+ mg/L. However, concentrations of NH4 , PO4 and Cu for all 3- In this study, concentration of PO4 in all road runoff sampling location exceeded NWQS standard. samples are exceeded the NWQS limit. Excessive amount of 3- 3.2 Spatial Distribution Mapping of Ammonia and PO4 accelerates the growth of algae through eutrophication Phosphorus process. Consequences of accelerated eutrophication can cause degradation of aquatic life populations. From Fig.3 (a) shows Ammonia and phosphorus are common nutrients that can be overall contour map shows red indicator which means found in road runoff. The presence of these nutrients concentrations of phosphate in the road runoff are higher than permissible level (0.2 mg/L). Conversely, the concentration of excessively in water bodies frequently due to runoff can 3- degrade the quality of water bodies through eutrophication PO4 decreases when the runoff samples taken at second 3- rainfall event as shown in Fig. 3(b) with lower density of colour process. The water quality criteria state that PO4 should not exceed 0.2 mg/L if streams discharge into lakes or reservoirs, indicator. These can happen when most of contaminants on the to control algae growth (NQWS, 2006). The NQWS pavement surface were flush away during the first rainfall event + (when the samples are collected) and the next rainfall would recommends a limit of 0.3 mg/L as NH4 in freshwater or 3- marine environments. In this study, the road runoff samples flush lower concentration of PO4 from the road surfaces. were collected twice with different time interval of rainfall + 3- events. The contour maps for NH4 and PO4 were plotted as (a) 5 4.8 shown in Fig.2 and Fig.3, respectively. 103.088 4.6 PTTSS 4.4 4.2 103.087 4 (a) 2.7 3.8 2.6 3.6 103.088 2.5 3.4 PTTSS 2.4 103.086 3.2 2.3 PTGS 3 2.2 JD1 2.8 103.087 2.1 2.6 2 103.085 2.4 1.9 2.2 1.8 2 103.086 1.7 PTGS 1.8 1.6 103.084 1.6 JD1 1.5 1.4 1.4 1.2 103.085 1.3 1.2 1 1.1 103.083 0.8 1 0.6 103.084 0.9 0.4 0.8 0.2 103.082 0.7 PTDI 0 0.6 PTGB 103.083 0.5 0.4 1.855 1.856 1.857 1.858 1.859 1.86 1.861 0.3 0.2 0.1 103.082 PTDI 0 PTGB 1.855 1.856 1.857 1.858 1.859 1.86 1.861 (b) 5 103.088 4.8 4.6 PTTSS 4.4 4.2 103.087 4 (b) 2.7 3.8 2.6 3.6 103.088 2.5 3.4 PTTSS 2.4 103.086 3.2 2.3 PTGS 3 2.2 JD1 2.8 103.087 2.1 2.6 2 103.085 1.9 2.4 1.8 2.2 103.086 PTGS 1.7 2 1.6 1.8 JD1 1.5 103.084 1.6 1.4 1.4 103.085 1.3 1.2 1.2 1.1 1 1 103.083 0.8 103.084 0.9 0.6 0.8 0.4 0.7 0.2 0.6 103.082 PTDI 0 103.083 0.5 0.4 PTGB 0.3 0.2 1.855 1.856 1.857 1.858 1.859 1.86 1.861 0.1 103.082 PTDI 0 Fig. 3 –Spatial distribution of phosphate on (a) 22/4/2018 and PTGB 1.855 1.856 1.857 1.858 1.859 1.86 1.861 (b) 24/4/2018.

3.3 Spatial Distribution Mapping of Copper Fig. 2 –Spatial distribution of ammonia on (a) 22/4/2018 and (b) 24/4/2018. The high concentrations of heavy metals such as copper in any water body because it will lead to gigantic environmental issues affecting aquatic and human lives that depend on the 3 Published by FAZ Publishing http://www.fazpublishing.com/jagbe Khamidun. MH et al., Journal of Applied Geoscience and Built Environment, Vol. 1 No. 2 (2019) p. 1-5

waterway. High levels of copper in water can be deadly for 3.4 Correlation of Copper, Ammonia and Phosphate many different aquatic organisms, thus altering the natural Concentrations with Traffic Volume ecosystems living in streams, rivers and lakes. Spatial The number of vehicles on the road contribute to the distribution mapping was developed to explain further the release of different amount of pollutants. Road runoff was dispersal of Cu in UTHM road runoff. Figure 4 depicted for tested to indicate whether this was a contributing factor to the pattern of Cu concentrations at these five points in different concentration of the runoff leaving the pavement. Fig. 5 shows rainfall events. the correlation of traffic volumes with copper, ammonia and

phosphate. (a ) 0.05 103.088 0.048 0.05 6 103.088 0.048 PTTSS 0.046 PTTSS 0.044 0.046 R² = 0.3137 0.044 0.042 5 103.087 0.04 0.042 103.087 0.038 0.04 0.036 0.038 PTGS 0.034 0.036 4 103.086 0.032 0.034 103.086 PTGS JD1 0.03 0.032 PO43+ JD1 0.028 0.03 0.026 0.028 3 103.085 0.024 0.026 Cu 103.085 0.022 0.024 0.02 0.022 2 NH4+ 0.018 0.02 103.084 0.016 R² = 0.065 103.084 0.018 0.014 0.016 0.012 0.014 1 0.01 0.012 (mg/L) Concentration 103.083 0.008 103.083 0.01 R² = 0.0021 0.006 0.008 0 0.004 0.006 0.002 0.004 103.082 0 2000 4000 6000 8000 10000 103.082 PTDI 0.002 PTDI 0 PTGPTGBB 1.855 1.856 1.857 1.858 1.859 1.86 1.861 1.855 1.856 1.857 1.858 1.859 1.86 1.861 ADT (Veh/day)

( b) Fig.5 – Correlation of Copper, Ammonia and Phosphate 0.05 Concentrations Concentration to Traffic Volume 103.088 0.048 PTTSS 0.046 0.044 0.042 The Fig.5 indicate that traffic volume explains approximately 103.087 0.04 0.038 30% of the variation in concentrations at selected sampling 0.036 + 0.034 location. Traffic volume has no correlations with Cu and NH4 PTGS 103.086 0.032 2 0.03 concentrations with R are 0.0021 and 0.065, respectively. JD1 0.028 3- 0.026 Traffic volume has correlations around 31% with PO4 103.085 0.024 0.022 concentrations. Approximately 69% of the variation of 0.02 3- 0.018 concentrations remains unexplained for PO4 . The main factor 103.084 0.016 0.014 influence of concentration in road runoff is fine particle. The 0.012 0.01 fine particles size in range of 0.45–50 μm contributed up to 103.083 0.008 94% of total particle content high P concentrations in 0.006 0.004 combination with these particles in the road runoff [11]. 0.002 103.082 PTDI 0 The rainfall intensity and preceding dry days PTGB significantly influence the concentration of ammonia and 1.855 1.856 1.857 1.858 1.859 1.86 1.861 phosphate in road runoff. Road design such as junction or exit Fig.4 –Spatial distribution of copper on (a) 22/4/2018 and (b) lanes and surrounding land use may contribute significantly to 24/4/2018. the concentrations of copper in runoff from road surfaces [12].

The comparison of these two rainfall events can be seen 4. Conclusion clearly where there are changes in the densities of Cu at every sampling points except for Persiaran Tun Ghazali Shafie A weak correlations between pollutant concentrations in road (PTGS) and Jalan Delta 1 (JD1) where the Cu2+ concentration runoff and traffic volume was recorded and not statistically was 0.2 mg/L respectively. Contrary to PTGS and JD1, strong enough to suggest traffic volume is the best selection Persiaran Tun Dr Ismail (PTDI) and Persiaran Tun Ghafar Baba indicator for roads requiring runoff treatment. The 3- (PTGB) shows increments in the Cu concentration within two concentration of PO4 in road runoff shows high significant to rainfall events. The concentration of copper at PTGB increases the traffic volumes as pollutant. However, their concentration from 0.07 mg/L to 0.11 mg/L while at PTDI increases from varies based on the frequency and intensity of rainfall events. 0.03 mg/L to 0.04 mg/L. Inversely, only road runoff at More often rain fall would be lesser pollutants deposit. The Persiaran Tun Tan Siew Sin (PTTSS) had decreased from 0.05 great temporal and spatial variability observed in the obtained mg/L to 0.03 mg/L of Cu2+ concentration. data is clearly due to site characteristics and to rainfall pattern. The difference level of Cu concentration between these A substantial agreement with concentration ranges and ratios two events may be due falling rain has the potential to entrain measured in the road runoff were occasionally over acceptance airborne pollutants. The high level of Cu detection could also limits be attributable to promotion in the traffic volumes and possibly the diverse nature of road runoffs within this period of References assessment. Furthermore, the effect of Cu concentration to the road runoff should be investigated for urban stormwater [1] Lagadec, L.-R., Patrice, P., Braud, I., Chazelle, B., quality. Moulin, L., Dehotin, J., Breil, P. (2016). Description and

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Journal of Applied Geoscience and Built Environment, Vol. 1 No. 2 (2019) p. 1-5

evaluation of a surface runoff susceptibility mapping method. Journal of Hydrology, 541, 495–509. [2] Charters, F. J., Cochrane, T. A., & O’Sullivan, A. D. (2016). Untreated runoff quality from roof and road surfaces in a low intensity rainfall climate. Science of the Total Environment, 550, 265–272. [3] Barbosa, A. E., Fernandes, J. N., & David, L. M. (2012). Key issues for sustainable urban stormwater management. Water Research, 46(20), 6787–6798. [4] Jakle, J. A. (2012). Rethinking a Lot: The Design and Culture of Parking. Eran Ben-Joseph. Urban Geography, 33(6), 915–915. [5] Angermeier, P. L., Wheeler, A. P., & Rosenberger, A. E. (2004). A Conceptual Framework for Assessing Impacts of Roads on Aquatic Biota. Fisheries, 29(12), 19–29. [6] Le Viol, I., Mocq, J., Julliard, R., & Kerbiriou, C. (2009). The contribution of motorway stormwater retention ponds to the biodiversity of aquatic macroinvertebrates. Biological Conservation, 142(12), 3163–3171. [7] Van Bohemen, H. D., & Van De Laak, W. H. J. (2003). The influence of road infrastructure and traffic on soil, water, and air quality. Environmental Management, 31(1), 50–68. [8] Jensen, T. C., Meland, S., Schartau, A. K., & Walseng, B. (2014). Does road salting confound the recovery of the microcrustacean community in an acidified lake? Science of the Total Environment, 478, 36–47. [9] Loperfido, J. V., Noe, G. B., Jarnagin, S. T., & Hogan,D. M. (2014). Effects of distributed and centralized stormwater best management practices and land cover on urban stream hydrology at the catchment scale. Journal of Hydrology, 519(PC), 2584–2595. [10] Forman, R., Sperling, D., Bissonette, J., Clevenger, A., Cutshall, C., Dale, V., Winter, T. (2003). Road ecology: science and solutions. Review Literature And Arts Of The Americas, 481. [11] Wu, J., Ren,Y., Wang, X., Wang X., Chen, L., Liu, G., (2015) Nitrogen and phosphorus associating with different size suspended solids in roof and road runoff in Beijing, China Environ. Sci. Pollut. Res. Int., 22 (20), pp. 15788-15795. [12] D. Drapper, R. Tomlinson, P. Williams (200) Pollutant concentrations in road runoff: Southeast Queensland case study Journal of Environmental Engineering April, pp. 313-320

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