ECO-CHRONICLE 55

ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 55 - 58

PETROGRAPHY OF ULTRAMAFIC ROCKS ALONG SIRUMUGAI AREA, COIMBATORE (DIST), TAMILNADU.

Santhosh Kumar, E., Kumar, R.S., Prabhakaran, R. and Permcharles, A.

Department of Earth sciences, Annamalai University, Annamalai Nagar, Tamil Nadu. Corresponding Author: [email protected]

ABSTRACT

The sirumugai Area is characterized by occurrence of ultramafic rocks aligned parallel to the Bhavani shear zone, intruding the Gabbroic -Anorthosite –Gabbroic-Pyroxenite suite. The ultramafic rocks occur as small lenses, pockets, veins, and thindykes and are intimately associated with mafic (Gabbros) rock. A few samples from the country rock were selected for the modal analysis. The characters represent that they might have been product of Archaean-Granodiorite-Tonalitic Gneisses and basic, ultra basic rocks are of which are predominant components of continental crust at the time of its formation. Key words: Petrology, Ultramafic, Sirumugai, Anorthosite.

INTRODUCTION Analytical Techniques

Ultramafic roués have received Chemical – mineralogical classification was considerable affection within the geological carried out using a CIPW norms thin community in recent years because they sections of gabbroic – anorthosite gabbroic provide excellent opportunities to gain – pyroxenite were studied using laborious insight into the in accessible realm of poles microscope and photo graphed on mantle rocks. Mostly they are formed by the leica micro system camera. partial melting of upper mantle and facilitate in the understating of the details of Geology of the Area fractionation origin, tectonic history and other petrological process (Raymond 2002) The study area lies between the east ultramafic roués act as hosts for Cr, Ni, Cu longitude 77 00 to 77 70 and the north and PGE mineralization. latitude of 11 24’ and 11 19’ of the SOI topo sheets (Fig 1). The area fails in the trichy The ultramafic rocks of sirumugai area Madurai plate. The suture zone are the gabbroic – anorthortes, gabbroic – mettupalayam-perambalur suture zone pyroxenites suite form the focus of (Gopalakrishana ,1990) the gabbroic interest. anorthosite – gabbroic – pyroxinite suite 56 ECO-CHRONICLE covers about 1/10 of the mapped area. The gabbroic, gabbroic – anorthosite Important out crops of this rock are found in are indicated to be tectonic slices with places near about thenkal malai and odhi in gneisses as their contacts are malai (Fig 2). invariably sheared (Jayananda et al, 1995). Fig.1. Location map of the study Area. The sathyamangalam supracrustal of the area include hornblende – biotite gneisses magnetite quartzite. The foliation trends which are variable from WNE–ESE. Ramakrishna (1991) proposes that the pandyan mobile belt, by analogy with the lim popo belt of South Africa.

RESULTS AND DISCUSSION

Petrography:

Fig.2.Geology map of the study area. The ultramafic rocks of the study area are gabbro- anorthorite, gabbroic – pyroxinite studied under crossed nicols.The detailed petro graphic studies were carried our followed by model analysis for the selected this section of the representative samples. In thin section these rocks often show and equigranalar inter locking granolithic texture with medium grained. They are of labordorite composition. Wavy extinction, Fig-3. Shows AFM Diagram wedging and distortion of twin lamellae are common which indicate stress effects. It’s also common as islands with in garnet pyroxenes show higher degree of alteration.

In some sections the rocks shows a highly cataclastic fabric. The petrochemical characters of these rocks reveal ECO-CHRONICLE 57 Fig. 4. Petrographic thin sections. 58 ECO-CHRONICLE that they are disintegration (or) early almandine-pyrope type which according to Archean grano-dioritic-tonalitic gneisses ramberg indicates formation under (Winkler, 1976). pressure environment.

Geochemistry: REFERENCES

The Chemical data Presented here and the Allegre Cj, Poirier Jp, Hhumier E, Hofmann discussions are follow (hollocher one if the Aw (1995). The chemical composition of the sampler form the country rock was selected earth planet. sci. lett. 134: 515-528. for modal ananlysis. The hornblende biotite gneisses shows higher silica in the range Ballhaus, C.G. & Glikson, A.Y., 1995, of 44.14, AL2O3-10.51, Fe2O3-11.28, Feo- Petrology of layered mafic-ultramafic

16.79, Mgo-12.89, Cao-16.34 and K2O-1.79 intrusions of the Giles Complex, western by the modal analysis.the character Musgrave Block, central Australia. AGSO represent that they might have been product Journal, 16/1&2: 69-90. of Archean grano-dioriteic-tonalitic gneisses. Which are predominant Blatt, Harvey; Tracy, Robert J.; Owens, Brent component of continental crust at the time (2005), Petrology: igneous, sedimentary, of the formation On AFM Diagram the and metamorphic (New York: W. H. samples plot in the field of metamorphic Freeman). ISBN 978-0716737438 peridotites and ultramafic rocks (Coleman, 1977). Radhakrishna, T.; Divakara Rao, V. and . Krishna Rao, J.S.R.(1982). Occurrence and CONCLUSION significance of awaruite in the Dras ultramafics, Kashmir Himalaya, . In the sirumugai area small outcrops of Mineralogical Magazine, 46: 405-484. ultramafic rocks in association with gabbro- anorthosite-gabbro-pyroxinite. The suite of Sinharoy, S. & Radhakrishna, T. (1982). rocks include a dominant gabbroic facies Geochemistry of the ultramafic and mafic and relatively subordinate anorthositic rocks complex of Agali, and its and pyroxinites. It shows a distinct implications for Archaean greenstones of stratiform layering. The garnet form South India. Neues. Jah. Miner Abh., 143 : anorthosite rock is almandine grosular and 309-330. ECO-CHRONICLE 59

ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 59 - 66

A MULTIVARIATE STATISTICALANALYSIS OF GROUNDWATER CHEMISTRY DATAIN CUMBUM VALLEY WATERSHED MADURAI DISTRICT TAMIL NADU, INDIA.

Venkateswaran, S. and M. Vijay Prabhu

Hydrogeological Laboratory, Dept. of Geology, Periyar University, Salem, Tamil Nadu.

Corresponding author: [email protected]

ABSTRACT

The Cumbam valley watershed, located in Uttamapalyam and a small part of Periyakulam taluk, the western corner of Madurai District covers an area of about 890.97 Km 2, Tamilnadu, has been selected for this study. A multivariate statistical assessment has been adapted to the classification of a large, irregular dataset of 55 subsurface water samples in pre-monsoon 2009 and analyzed +2 +2 + + - - -2 for various water quality parameters such as pH, EC, TDS, Ca , Mg , Na , K , HCO3 , CO­3 , SO4 and Cl-. Hydrogeochemical data for 55 groundwater samples were subjected to Q- and R- mode factor and cluster analysis. R-mode analysis reveals the inter-relations among the variables studied and the Q-mode analysis reveals the inter-relations among the samples studied. The R-mode factor analysis shows that Mg and CI with CO3 account for most of the electrical conductivity, total dissolved solids and total hardness of the groundwater. Both Q-mode factor and Q-mode cluster analyses shows that there is an exchange between the river water and adjacent groundwater. Cluster classification map reveals that 97.79% of the study area comes under cluster I classification.

Key words: Groundwater – Multivariate statistical analysis – Factor analysis, Cluster analysis

INTRODUCTION types, topography of the area, human activities on the ground, etc. Apart from these The earth without water is difficult to factors, Charnockite, Calc-Gnieses, imagine. There is evidence that the life on granulites and contact between them play the earth originated in water. Today, water is an important role in determining the quality continuously polluted from different of the groundwater. sources. In the current world economic paradigms, sustainable socioeconomic In this study, such a situation has been development of every community depends deduced by using multivariate statistical much on the sustainability of the available techniques such as factor and cluster water resources. Water of adequate quantity analyses. Here, a qualitative study has been and quality is required to meet growing attempted to major cations and anions household, industrial and agricultural interaction in the groundwater. Multivariate needs. Sub-surface water quality is a very statistical analysis has been successfully sensitive issue, which transcends national applied in a number of hydrogeochemical boundaries. The quality of groundwater is studies. Steinhorst and Williams (1985) controlled by several factors, including used multivariate statistical analysis of climate, soil characteristics, manner of water chemistry data in two different field circulation of groundwater through the rock studies to identify groundwater sources. In 60 ECO-CHRONICLE their application of multivariate analysis to The area around Cumbum is diversified by chemical data, Usunoff and Guzma´n- several ranges of hills, falls and rapids which Guzma´n (1989) demonstrated the impart to the region a picturesque usefulness of the approach in appearance. The prominent mountain of the hydrogeochemical investigations when study area is the High Wavy Mountain and it considering the geological and is flanked on either side by hills. In the hydrogeological knowledge of the aquifer. eastern portion, there is an intermountane Multivariate statistical analyses, such as valley called the Varshanad valley. cluster and factor, aim to interpret the governing processes through data MATERIALS AND METHODS reduction and classification and are widely applied mainly to spatial data in GEOCHEMISTRY geochemistry (Papatheodorou et al., 1999; hydrochemistry (Voudouris et al., 2000); 55 groundwater samples (Open wells) were mineralogy (Seymour et al., 2004) and even collected during the pre-monsoon period in marine geophysics (Papatheodorou et (May) of the year 2009. Fig. 1 shows the al., 2002). The use of these methods to locations of the groundwater samples. The water quality monitoring and assessment samples were analysed using standard has increased in the last decade, mainly water analysis methods (Trivedy et al., 1986; due to the need to obtain appreciable data APHA, 1995). The ionic constituents Ca2+, 2+ + + - 2- - 2- reduction for analysis and decision (Vega Mg , Na , K , Cl , CO3 , HCO3 , and SO4 and et al., 1998; Helena et al., 2000; Lambrakis the non-ionic constituents pH, Electrical et al., 2004). Multivariate treatment of conductivity (EC), Total dissolved solids environmental data is widely used to (TDS) and Total hardness (TH) were characterize and evaluate surface waters determined for these groundwater. These (Reisenhofer et al., 1995; Miller et al., 1997; data were subjected to multivariate De Ceballos et al., 1998; Momen et al., 1999; analytical techniques such as factor and Perona et al., 1999; Lau and Lane, 2002; cluster analysis. Multivariate techniques can Simeonov et al., 2003; Yu et al., 2003) and help to simplify and organize large data sets groundwater quality (Vengosh and Keren, and to make useful generalizations that can 1996; Suk and Lee, 1999; Panagopoulos lead to meaningful insight (Laaksoharju et et al., 2004, Vincent Cloutier et al 2008, ) al., 1999). Cluster and factor analyses are and it is useful for evidencing temporal and efficient ways of displaying complex spatial variations caused by natural and relationships among many objects (Davis human factors linked to seasonality. et al., 1973). The STATISTICA software has been used to carry out the analysis. The STUDY AREA data have been standardized by using standard statistical procedures. The Cumbam valley watershed, location of whole Taluk of Uttamapalyam and a small RESULTS AND DISCUSSION part of Periyakulam Taluk, located in the western corner of Madurai district of Tamil R – MODE FACTOR ANALYSIS Nadu. It lies between 9°34' N to 10°10' N latitudes, and 77°10' E to 77°31' E R-mode factor analysis for the cations, longitudes covering an area of 1485.62 Sq anions, TDS, EC, pH and TH have been km out of which plain area covers 890.97 considered for the present study. The Sq km and Hilly & Forest area covers 594.65 analysis generated 3 factors which Sq km (Fig.1). This is a linear valley located together account for 71.05% of variance. at the catchment zone of the river Sureli Ar of The varimax raw loadings, eigen values, Vaigai basin. Cumbum is a village located percentage of variance and cumulative in the valley situated amidst the hills that percentage of variance of all 3 factors are comprise the eastern arm of . given in Table 1. ECO-CHRONICLE 61 Fig.1. Study area of Cumbum Valley Watershed and CO3 and TH and also with sample locations moderate loading of TDS, pH and Ca. This factor accounts for the permanent hardness of the water. Factors 3 are characterized by the dominance of only four variables such as K and Ca is very high loading and Mg and Cl is also moderate loading. This factor accounts for the polluted of the groundwater.

Q – MODE FACTOR ANALYSIS

The rotated loadings, eigen values, percentage of variance and cumulative percentage of variance of the two factors are given in Table 2. Q- mode factor analysis of the 55 groundwater samples was carried out. The analysis has generated two factors which together account for 99.13% of the variance.

The first factor which accounted for 94.82% of the variance consist of high loadings of samples The first eigen value is 5.23 which accounts 5, 7-8, 11-14, 16-18, 20-26, 29-30, 32-34, for 43.54% of the total variance and this 36-45, 47-49, 52-55. The second factor constitutes the first and main factor. The which accounted for 4.31% of the variance second and third eigen values are 2.03 and consists of high loadings of samples 1-3, 1.27 and these account for 16.93% and 6, 10, 19, 27-30, 35, 39, 44-46, 51 and 54. 10.59%. The first factor (which accounts for However, the majority of the samples within 43.54% of the total variance) is factor 1 fall on either side of the main course characterized by very high loadings of Mg, of the river system. This strongly suggests Cl and EC and moderate to high loadings that there is an exchange between the river of Ca and TH. This factor reveals that the water and adjacent groundwater. It is also EC and TH in the study area are mainly due discussed by Reghunath et al., 2002. to Mg, Ca and CI. The second factor (which However, the majority of the samples within accounts for 16.93% of the total variance) is factor 1 fall on rock interaction of the mainly associated with very high loading of groundwater. 62 ECO-CHRONICLE Table 1. R – Mode factor analysis with Varimax normalized HIERARCHICAL CLUSTER rotation ANALYSIS (HCA) Factor - 1 Factor - 2 Factor -3 Variable Cluster analysis Ca 0.760 0.246 0.346 comprises of a series of Mg 0.835 -0.037 0.148 multivariate statistical Na 0.681 -0.293 -0.461 methods which are used to find true groups of data K 0.449 -0.341 0.544 or stations. In clustering, HCO3 0.433 -0.530 -0.562 the objects are grouped CO3 0.256 0.721 -0.352 such that similar objects fall into the same class SO4 0.606 -0.400 -0.186 (Danielsson et al., 1999). Cl 0.881 0.080 0.152 The HCA is a data pH 0.496 0.471 -0.203 classification technique. EC 0.975 -0.048 -0.080 There are different TDS -0.368 0.516 -0.250 clustering techniques, but the hierarchical clustering TH 0.747 0.556 0.109 is the one most widely Eigen value 5.225 2.031 1.270 applied in Earth sciences Percentage of (Davis, 1986), and often 43.542 16.925 10.585 variance used in the classification Cumulative of hydrogeochemical data 43.542 60.466 71.051 Percentage (Steinhorst and Williams, Fig.3. Cluster Classification of Spatial Distribution Map 1985; Schot and van der Wal, 1992; Ribeiro and Macedo, 1995; Gu¨ler et al., 2002). The result of the hierarchical cluster analysis was given as a dendrogram (Fig. 2). For this work, the Euclidean distance was chosen as the distance measure, or similarity measurement, between sampling sites. The sampling sites with the larger similarity are first grouped. Next, groups of samples are joined with a linkage rule, and the steps are repeated until all observations have been classified. With this geochemical dataset, Ward’s method was more successful to form clusters that are more or less homogenous and geochemically distinct from other clusters, compared to other ECO-CHRONICLE 63 Table 2. Q – Mode factor analysis with Varimax methods such as the normalized rotation weighted pair-group average. Ward’s method is Sample Factor Factor sample. Factor Factor distinct from other linkage No. - 1 - 2 No. - 1 – 2 rules because it uses an 1 -0.745 0.641 29 -0.997 0.055 analysis of variance approach to evaluate the 2 -0.990 0.055 30 -0.997 0.236 distances between clusters 3 -0.985 0.103 31 -0.949 -0.043 (StatSoft Inc., 2004). Other 4 -0.985 -0.163 32 -0.999 -0.005 studies used Ward’s 5 -0.997 -0.057 33 -0.996 -0.042 method as linkage rule in 6 -0.978 0.190 34 -0.998 -0.031 their cluster analysis (Adar et al., 1992; Schot and van 7 -0.999 -0.025 35 -0.976 0.189 der Wal, 1992). Gu¨ler et al. 8 -0.990 -0.056 36 -0.998 -0.064 (2002) also found that using 9 -0.982 -0.028 37 -0.998 -0.054 the Euclidean distance as 10 -0.987 0.152 38 -0.996 -0.084 a distance measure and 11 -0.997 -0.072 39 -0.999 0.604 Ward’s method as a linkage 12 -0.998 -0.032 40 -0.998 -0.055 rule produced the most distinctive group. 13 -0.991 -0.128 41 -0.995 -0.068 14 -0.992 -0.137 42 -0.995 -0.053 Q-mode cluster analysis 15 -0.990 -0.114 43 -0.997 -0.072 16 -0.995 -0.249 44 -0.995 0.158 The output of the Q-mode 17 -1.000 -0.020 45 -0.999 0.010 cluster analysis there are 18 -0.995 -0.076 46 -0.967 0.210 two major clusters is given as a dendrogram (Fig. 2). 19 -0.965 0.163 47 -0.993 -0.093 Clusters 1 and 2 20 -0.993 -0.116 48 -0.997 -0.079 correspond to the factors 21 -0.995 -0.090 49 -0.995 -0.165 1and 2, respectively. The 22 -0.993 -0.092 50 -0.965 -0.251 similarly of the Q-mode 23 -0.995 -0.063 51 -0.356 0.877 cluster analysis to the Q- 24 -0.995 -0.066 52 -0.994 -0.169 mode factor analysis confirms the interpretations 25 -0.993 -0.061 53 -0.990 -0.136 made using the Q-mode 26 -0.991 -0.123 54 -0.999 0.028 factor analysis. To 27 -0.986 0.151 understand the spatial 55 -0.995 -0.066 28 -0.921 0.366 distribution of various Eigen value 52.149 2.371 clusters class in the study Percentage of variance 94.817 4.311 area, the results were taken into GIS plat form wherein Cumulative Percentage 94.817 99.128 spatial distribution map is prepared (Fig 3). The result Table 3. Results of Spatial Distribution Map of Cluster of spatial distribution map Classification is given in the Table 3. Cluster classification Cluster 2 Area in Km Area in % spatial distribution map classification clearly reveals that 80.80% Cluster - I 719.95 80.80 of the study area comes under cluster I Cluster - II 171.06 19.20 classification. Cluster II classification fall as a 64 ECO-CHRONICLE

Tree Diagram for 55 Variables that exchange between the Single Linkage river water and the Euclidean distances groundwater plays a 1 39 dominant role in the 2 18 hydrogeochemical 21 evolution of groundwater. 49 26 Cluster classification 34 47 spatial distribution map 37 52 clearly reveals that 80.80% 23 54 of the study area comes 3 under cluster I 16 44 classification. Cluster II 53 30 classification fall as a 7 9 packets in the southern and 6 central part of the 10 24 watershed. 5 38 48 20 REFERENCES 17 32 11 A.P.H.A. (1995). Standard 43 13 methods of analysis of 14 36 water, waste water, 41 55 American Public Health 4 th 12 Association, USA, 14 40 ed., Washington DC, 22 42 1457 pp. 45 8 29 25 Adar, E.M., Rosenthal, E., 33 Issar, A.S., Batelaan, O., 51 28 1992. Quantitative 46 35 assessment of the flow 31 15 pattern in the southern 27 19 Arava Valley (Israel) by 50 environmental tracers and 0 20 40 60 80 100 120 a mixing cell model. (Dlink/Dmax)*100 Journal of Hydrology 136, 333–352. packets in the southern and central part of Danielsson, A., Cato, I., Carman, R., Rahm, the watershed. L., 1999. Spatial clustering of metals in the sediments of the Skagerrak/Kattegat. CONCLUSION Applied Geochemistry 14, 689 - 706.

The non-mixing or partial mixing of different Davis JC. 1973. Statistics, data analysis in types of groundwater as deduced by the R- geology. New York:Wiley, 550pp. mode factor analysis indicates slow movement of groundwater or the absence Davis, J.C., 1986. Statistics and Data of interconnected underground fractures. Analysis in Geology. John Wiley & Sons Inc., The R-mode factor analysis shows that Mg New York. and CI with CO3 account for most of the electrical conductivity, total dissolved solids De Ceballos, B.S.O., Koning, A., De Olivera, and total hardness of the groundwater. The J.F., 1998. Dam reservoir eutrophication: a Q-mode factor and cluster analyses indicate simplified technique for a fast diagnosis of ECO-CHRONICLE 65 an environmental degradation. Water Res. Papatheodorou, G., Hotos, G., Geraga, M., 32 (11), 3477–3483. Avramidou, D., Vorinakis, T., 2002a. Heavy metal concentrations in sediments of Guler, C., Thyne, G.D., McCray, J.E., Turner, Klisova lagoon (S.E. 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ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 67 - 74

DESIGN, DEVELOPMENT AND EVALUATION OF A SULLAGE TREATMENT SYSTEM

Asha Joseph, Soumya Rani, T., Arjun Gopakumar and Shajeer, A.K.P

Kelappaji College of Agricultural Engineering and Technology, Kerala agricultural University, Tavanur.P.O. Malappuram - 679573, Kerala.

ABSTRACT

The demand of fresh water is increasing with the growing population and industrial development. Hence the reuse of treated waste water is gaining much importance nowadays. Sullage is the waste water from kitchen and bathrooms. A treatment system consisting of a holding tank for sullage and two separate containers for activated carbon and sand particles was designed and developed for treating the sullage water. The performance of sullage treatment system for removal of TDS, total hardness, chlorides, sulphates, COD and BOD5 were analyzed by the chemical analysis of the influent and effluent of the system. An excellent removal of 70 % or more was observed in case of sulphates, COD and TDS. The results obtained by the quality analysis were compared with the acceptable limits of treated water and were found highly satisfactory. This ecological and environment friendly treatment system can reduce many objectionable pollutants from waste water to a great extent and make this water available to secondary users without any health risks.

Key words: Sullage water, Activated carbon, TDS,BOD5, COD

INTRODUCTION by 60 % (Samir et al ,1993). The system is compact, easy to install, operate and Water is the most precious and prime maintain, and is very cost effective. Highly element in the socio economic skilled personals are not required for development of the nation and can be designing a sullage treatment system and described as “eco currency”. Polluted water also no energy is required for running the and fecal matter are the main factors system. responsible for the spread and transmission of infectious diseases. Hence The treatment technologies that are being treatment of waste water is very essential. in use for recycling sullage water nowadays Sullage water is the domestic waste water are essentially the same that are used for from kitchens, bathrooms, sinks, laundry, sewage treatment. Recycling and reuse of swimming pool, wash basin etc, except sullage alone for housing societies is the water from toilets (Veronica Thorp et al. latest approach in India where water supply 2002). Due to extreme water scarcity, reuse is scarce and the residents has to purchase of waste water for secondary water use is tanker water for purposes other than becoming essential in many parts of world drinking (Ahmed. K, 1975). In this packaged (Friedel, J.K, 2000). But there are certain system, the sullage is treated by multi-grade limitations in direct use of this ravaged filter where alum is added for coagulation water. This sullage water can be treated and purpose followed by sand (Rangwala, recycled for toilet flushing, gardening etc. 2007) and activated carbon filtration (Laak, thus reducing the requirement of fresh water R, 1974). The carbon filters were most 68 ECO-CHRONICLE effective at removing chlorine, sediment and wastewater is very important (Hypes, volatile compounds from water (Patil, 2005). W.D.1974). Therefore an investigation was After that chlorination is done for disinfecting conducted to determine pH, total hardness, purpose and the treated water is reused. chlorides, total dissolved solids (TDS), Hence the present study aimed to design Biological Oxygen Demand (BOD ), develope and evaluate a sullage treatment Chemical Oxygen demand (COD), and5 system. presence of detergents of the sullage water. The presence of detergents was estimated MATERIALS AND METHODS by sulphates. The general characteristic of the sullage water is shown in the table 1. The experimental site was selected near the kitchen, men’s hostel, Kelappaji Design and development of a sullage College of Agricultural Engineering and treatment system Technology, Tavanur, Malappuram. The waste water coming from the sources The technology consists of one multi grade contains food wastes, waste water, soap sand filter, followed by activated carbon filter. particles etc (Veronica Thorp et al.2002). At In addition to this, the system requires one first the sullage water was filtered by a cloth underground sullage storage tank, and only the liquid content was taken. The pumping machinery, separate overhead treatment and analysis were done during tank to store the treated sullage water and the month of November and December separate piping system for large-scale purification. 2009 and the minimum and0 maximum0 temperature prevailed were 19 C and 31 C respectively. The samples were analyzed Generally it is advisable to use locally and by availing the facilities of chemistry and cheaply available material as sand filter bioenergy laboratories of this college. media. The media properties such as grain size, hydraulic conductivity, porosity and Sullage water characterisation reaction constant should be considered for scientific design. For the present study, fine To design any wastewater treatment sand and pebbles were used as filter system, a detailed characterisation of media. The size of the sand particles selected ranges from 0.3 to 0.6 mm. The particle size of the activated carbon granules Table 1. General characteristics of affects the removal rates. The sullage water recommended size is 0.5 – 50 microns. It reduces volatile organic compounds, Parameter Unit Range of pesticides, herbicides etc.The activated values carbon filters used for the home water pH 10-11.5 treatment typically contain either granular activated carbon or powdered block carbon. Total hardness Ppm 140-160 This carbon is generally activated with a Chlorides Ppm 140-160 positive charge and is designed to attract negatively charged water contaminants. Total dissolved solids Ppm 450-550 The raw sullage was collected in a holding tank. It was allowed to stay for half an hour BOD in the holding tank for settling. Then this 5 Ppm 60-80 water was passed through the sand filter COD Ppm 240-280 (Boyle, W.C., 1982). The sand filtered Sulphates Ppm 100-200 sullage was then passed to the tank containing activated carbon granules where Source: Indian Plumbing Today, June 2005 it was again filtered. The flow diagram ECO-CHRONICLE 69 illustrates the procedure (Fig.1). After that C = a coefficient =140 (for PVC pipes with the treated water was collected in a very smooth inside surface) separate tank. The quality of water was evaluated before and after treatment and RESULTS AND DISCUSSION compared with the acceptable limits (Patil, S.M. 2005) of treated water (Table 2). To design a sullage treatment system, the characteristics of sullage water were Table 2. Acceptable limits for treated water monitored. All the characteristic parameters were estimated using standard procedure. Parameter Acceptable limit It is seen that sullage water from the same for sullage water source may exhibit wide variability on a daily Colour Colourless basis and therefore long term monitoring pH 6.5-8.8 can only give a reasonable approximation Total solids <500 of average value. In our present experiment Chlorine content <100 we were monitored eight samples at weekly COD <100 intervals and sullage characteristics were BOD <50 assessed and the same is tabulated (Table.3). Source: Indian Plumbing Today, June 2005 Hydraulic design Specific waste water characteristics, construction aspects, system hydraulic Hydraulic design is based on Darcy’s law, parameters and economy were considered which describes the flow regime in a porous in planning and design of the sullage media. Hence flow rate is determined from treatment system. Based on all the above Darcy’s law which states that the velocity of aspects the sullage treatment system was flow through a porous medium is directly precisely developed and installed. Figure proportional to the hydraulic gradient (2) shows the field set up of the designed (Rangwala, 2007). sullage treatment system. i.e., Q = KiA After the installation of the system and

3 consequent treatment of the sullage water, Where, Q = flow per unit time, m /day; K = the pollutant removal capability was hydraulic conductivity of a unit area of the monitored by analyzing both influent and medium perpendicular to flow direction; A = effluent water characteristics at weekly total cross-sectional2 area perpendicular to interval. Each time, three set of samples the flow, m ; i = hydraulic gradient of the were analyzed for influent sullage water water surface in the flow system. before and after settling and also the effluent water sample from the treatment To determine the pipe size carrying the system. sullage from the holding tank to the containers containing sand and activated The performance of this system for the carbon, Hazen Williams’s formula was removal of pollutants was discussed used (Rangwala, 2007). The formula is considering the following parameters. given by: pH of sullage water V=0.85 C m 0.63 i 0.54 Where, In the present experiment effective pH V = velocity of flow in meter/sec removal was observed with a mean m = hydraulic mean depth in meters = d/4 percentage removal of nearly 35%. The bar d = diameter of pipe. diagram (Fig.3) given below represents the i = slope or hydraulic gradient=vertical/ pH removal from the treatment system. In horizontal all the treated samples pH was found below 70 ECO-CHRONICLE

Table.3 Characteristics of influent sullage water

Samples taken Parameters mean 1 2 3 4 5 6 7 8

pH 10.2 10.0 11.2 10.2 11.4 10.8 10.2 10.8 10.6

TDS (ppm) 545 520 440 518 489 545 544 535 517 Total hardness 170 162 182 162 180 170 162 170 169.7 (ppm) Chlorides 102 91 103 91 133 88 100 88 99.5 (ppm) Sulphates 191 120 188 120 188 120 195 116 154.7 (ppm) COD (ppm) – 256. 234. 251 303 251 313 256 234 262.5 titration 8 8 BOD (ppm) 140 132 202 132 222 132 144 132 154.5

Table.4 Characteristics of treated sullage water

Samples taken mean Parameter 1 2 3 4 5 6 7 8

pH 7.1 6.9 7.2 6.9 7.2 7.1 7.1 7 7.06 13 TDS (ppm) 190 163 155 122 190 194 175 165.1 2 Total hardness 62 62 61 62 61 62 62 62 61.75 (ppm) Chlorides 66 51 51 44 58 44 66 44 53 (ppm) Sulphates 76 44 49 44 49 30 66 30 48.5 (ppm) COD (ppm) 66 61 76 61 78 63 66 63 66.75

BOD (ppm) 50 44 47 44 55 48 50 43 47.63

7.2 which indicated that the treated water is removal of nearly 70%. The high removal safe for secondary use. rate of TDS may be due to the effective filtration through the slow sand filter media. TDS of sullage water For all the samples the final effluent TDS was found below 190 ppm. (Fig.4) The TDS removal occurs mainly in the inlet section due to the adsorption of solids Total hardness within the porous spaces of sand, pebbles and activated carbon. The effective TDS The total hardness removal was observed removal was observed with a percentage with a percentage removal of nearly 65%. ECO-CHRONICLE 71 Fig.1. Flow diagram for the proposed Raw Sullage sullage treatment system

Alum

Sullage Holding Tank

Sand Size=0.35mm Depth=25cm Sand Size=0.6mm Depth=25cm Pebbles Depth=10cm

Activated carbon Chlorine Granules Depth=40cm

Pebbles Depth=10cm

Treated Water

Fig. 2. Field set up of the sullage treatment system 72 ECO-CHRONICLE

12 600

10 500

8 400 Before settling Before settling 6 After settling 300 After Settling Treated sullage Treated sullage 4 200 pH pH concentration TDS Concentration 2 100

0 0 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 Set of samples Set of samples

Fig. 3. pH removal from sullage Fig. 4. TDS removal from sullage

200 250 180 160 200 140 120 Before settling 150 Before settling 100 After settling After settling 80 Treated sullage 100 Treated sullage 60

Total hardness (ppm) Total hardness 40 50 20 Sulphates Sulphates concentration(ppm) 0 0 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 Set of samples Set of samples

Fig. 5. Total Hardness removal from sullage Fig. 6. Sulphate removal from sullage

140 350

120 300

100 250 Before settling Before settling 80 200 After settling After settling 60 150 Treated sullage Treated sullage 40 100

20 concentration(ppm) COD 50 Chloride concentration(ppm) 0 0 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 Set of samples Set of samples

Fig. 7. Chloride removal from sullage Fig. 8. C.O.D. removal from sullage

250

200

150 Before settling After settlimg 100 Treated sullage

50 BOD5 concentration(ppm) BOD5

0 1 2 3 4 5 6 7 8 Set of samples Plate 1. Sullage water and the treated Fig. 9. B.O.D. removal from sullage sullage water ECO-CHRONICLE 73 So it is concluded that total hardness environment. It reduces the pollution of the removal is very effective in the system. In all water bodies, and soil, and also it reduces the treated samples the total hardness was the demand of fresh water. Hence the found below 63 ppm (Fig.5). sullage water recycling is one of the best methods to save the water for domestic Sulphates uses such as gardening and toilet flushing. The sulphates concentration removal was observed with a percentage removal of SUMMRY AND CONCLUSION nearly 70% (Fig.6). Hence sulphates removal was found to be very effective in the Sullage treatment system by the use of multi- system. The sulphates may be present in filter unit is the best option for on-site waste the waste water from sources like washing water treatment, as it is a chemical, physical soap and detergents. Superfluous and biological waste water treatment. It has presence of sulphates in water is not safe. been observed that sullage treatment In the influent water, the sulphates system forms a cost effective, low energy concentration was observed in the range of and robust alternative to more conventional 88-133 ppm. In all the cases sulphates engineered systems to treat potential concentration was reduced by more than polluting substances. 60 %. In all the treated samples the sulphates concentration was in the range The following conclusions were evolved of 30-76 ppm. from the study.

Chlorides 1. The sullage water sample was The figure (Fig.7) showed an effective characterized and the average chloride concentration removal with a concentration of TDS, total hardness, percentage removal of nearly 50 %. This chlorides, sulphates, COD and BOD5 were may be due to the effectiveness of the filter found to be 466.66 ppm, 175.33 ppm, 99.0 media as sand and activated carbon. In all ppm, 165.33 ppm, 285.66ppm and 178.66 the treated samples the chloride ppm respectively. concentration was found below 65 ppm. 2. The sullage treatment system was Chemical oxygen demand (COD) designed and constructed in the light of The effective COD removal was observed results obtained from the characterization with a percentage removal of nearly 75 %. of sullage water samples. In all the treated samples the COD was in the range of 60 – 80 ppm. (Fig.8). 3. The characteristics of treated sullage water were found to be in the

Biochemical oxygen demand (BOD5) acceptable limits. The average

An effective BOD5 removal was observed concentration of TDS, total hardness, with a percentage removal of nearly 70%. chlorides, sulphates, COD and BOD5 of The physical removal of BOD is believed to treated water were 165.1 ppm, 61.75 ppm, occur rapidly through settling5 and 53ppm, 48.5 ppm, 66.75 ppm and 47.63 entrapment of particulate matter in the void ppm respectively. The removal percentage spaces in the sand and activated carbon. was found to be 70%, 65%, 50%, 70%, 75%

The BOD5 of treated sullage was found and 70% respectively. below 60 ppm in all the samples (Fig.9). The results of quality analysis were Hence it is concluded that the sullage compared with the acceptable limits of the treatment system with two filter media is a treated water and were found highly good on-site sullage water treatment satisfactory. It is very clear from the method for rural communities which can photograph shown (plate1). Sullage reduce fresh water demand and make recycling has two major positive effects on waste water available for secondary water 74 ECO-CHRONICLE uses like gardening, toilet flushing etc. Also T., ed., Manual of Greywater Treatment sullage treatment systems have great Practices, Michigan, Ann Arbor Science, pp: potential to reduce the health risks by the 79-88. avoidance of mosquito and other undesirable insects. Thus this is an efficient Laak, R. 1974., Relative pollution strength means of reusing the precious resource of of undiluted waste materials discharged in nature. households and the dilution waters used for each. In: Winneberger, Manual of REFERENCES greywater treatment practices, Michigan, Ann Arbor Science, pp. 68-78. Ahmed, k., 1975. Rural water consumption survey. Report No. 026-12-74, Institute of Patil, S.M., 2005. Waste water treatment for Public Health Engineering and Research, secondary use. Indian Plumbing Today, Lahore. official publication of Indian plumbing association, New Delhi. Boyle, W.C., 1982.Treatment of residential grey water with intermittent sand filtration, Rangwala, S.C., 2007. Water Supply and In: Eikum, A.S. & Sea bloom, R.W., ed., Sanitary Engineering (Environmental Alternative wastewater treatment. Dordrecht. engineering), Charotar Publishing House, Reidel. pp. 277-300. Anand, India.

Friedel, J.K., 2000. Effects of long term Samir, M et al., 1993. Impact of reuse of waste water irrigation on soil organicmatter, domestic waste water for irrigation on Soil microbial biomass and its activities on ground water quality. Central Mexico, Text book of biology and Veronica Thorp et.al., 2002. Living at Nine fertility of soils. Mile Beach, Coast care Publications, Natural Heritage Trust. Hypes, W. D., 1974. Characteristics of typical household greywater. In: Winneberger, J. H. ECO-CHRONICLE 75

ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 75 - 84

EXACUM BICOLOR – A BEAUTIFUL ENDEMIC GENTIAN VANISHING IN KERALA

Sreelatha, U.* and Baburaj, T.S**

*Agricultural Research Station, Mannuthy, Kerala. **Regional Agricultural Research Station, Ambalavayal, Kerala Agricultural University, Mannuthy, Kerala

ABSTRACT

Having great potential as ornamental plant, Exacum bicolor struggle for its existence in Kerala due to severe habitat destruction. The habitats were severely destructed for laterite mining, quarrying, and setting up plantations of rubber, cashew and coconut. Grasslands in the plains were also converted as sites for industry and educational institutions. Hillocks disappear all at once by mechanized soil excavation mainly done for construction or widening of highways. Dry grasslands are the major habitats of Exacum bicolor (70.73%). Among this 68.29% habitats are in private possession that may get destroyed at any time. Resurvey conducted in 12 sampling units spread over , Malappuram and Palakkd districts revealed complete disappearance of Exacum bicolor in three units which were previously recorded for occurrence of the plant. This itself indicates the plant as a dying one Kerala.

INTRODUCTION time there will be 10 – 20 buds in bloom. Flowering period lasts for 30 – 45 days. A Exacum bicolor Roxb. is a gentian, single flower lasts for 8- 10 days in field. endemic to Peninsular India. Its common name is Country kreat and the plant belongs Its ornamental value has been reported by to family Gentianaceae. Other popular John, et .al (2001), Rao (1986) Sreelatha names of the plant are Kannamthali in (2001), Sreelatha, et. al (2006) and , Akshipushpi in Sanskrit, Woodrow(1910). Apart from its ornamental Bharachirata in Hindi, , Dodda chirayuta in value, the plant is reported to possess some Kannada and ceti in Tamil. medicinal properties also. Exacum bicolor is reported to have febrifuge properties. Exacum bicolor (Figure 1) is a herbaceous Dried stalks of the plant were sold in South perennial. Habitats of the plant are both Indian markets during early 20 th shola grasslands in high ranges and dry century(Rao,1914).The tonic and stomachic grasslands in hillocks of 50-200 m altitude properties of the plant was reported in in plains of Kerala. The plant grows during Wealth Of India(1952) and it is mentioned the South West monsoon season i.e. from as a substitute for Gentiana and Swertia. July to November in plains and from July to Chopra, et.al.(1956) and Srivastava(1989) January in high ranges. It is non- lodging have also quoted the plant for its medicinal even in severe rains. In plains, flowering properties As a herbal remedy against period of the plant is from September to diabetes, the aerial parts of E. bicolor has November while in high ranges flowering been recommended by Reddy, et. al (2005). lasts up to January. Number of flowers per This wild plant was very popular in Kerala plant usually ranges from 40 to 80. At any about 5-8 decades back. Exacum was one 76 ECO-CHRONICLE of the choice flowers to adorn eastern parts of Ernakulam district. Trikkakkarayappan, the earthen deity Floristic studies in Kerala were referred to worshipped during Onam, an important get a preliminary idea about grasslands regional festival. The unique feature of the which are the habitats of the plant. Most of plant is that even in a vast stretch of these studies represent shola grasslands grassland, it is seen limited to small in wild life sanctuaries, national parks and pockets only. There have been places with bio reserves occurring at high altitudes. In only a single plant in an area of 5-10 acres the plains of Kerala, survey was conducted of grassland. The population is severely concentrating the hillocks where dry affected due to habitat destruction. No grasslands occur. Each location visited studies were undertaken regarding any was taken as a sampling unit. Each aspect of this potential ornamental as well sampling unit was initially observed as medicinal plant which has been reported thoroughly for the occurrence of the plant as an endemic plant. Hence a research and there after purposive sampling was project was undertaken with the financial done in places of plant occurrence in a assistance from the Department of sampling unit. This was necessitated by Biotechnology, Government of India, from the unique feature of the plant by its 2004-2008 with objectives of habitat survey concentrated occurrence in a few pockets & characterisation, habitat mapping and even within a sampling unit. evaluation of ornamental value of the plant. Population was assessed using quadratic MATERIALS AND METHODS sampling method by counting the number of plants in a quadrate of 1m x 1m. Based Survey was conducted from June 2005 to on the area of the sampling unit, 20-40 December 2006 in all the districts of Kerala quadrates were sampled. Geographical except Ernakulam and Alappuzha which parameters like latitude, longitude and were exempted due to its coastal habitats altitude of each sampling unit were and already established plantations in the recorded using a Global Positioning System. Political status (forest/revenue/ private/others) of the sampling unit was also recorded. Phyto sociological parameters calculated were frequency of distribution of the plant in a district, density and abundance of the plant in each sampling unit.

In some locations, quadrate sampling could not be done due to very steep terrain and occurrence of tall grasses (even upto 2m high). In such cases, number of plants sighted was recorded. Quadrate sampling was also avoided in sampling units with less than 20 plants altogether.

Name of many of the sampling units especially in the plains are followed by “Kunnu” which means “hillock” in colloquial language. The abbreviations P and NP provided in tables stand for ‘Present’ and ‘Not present’ respectively for the presence of Exacum bicolor. ECO-CHRONICLE 77 Table.1 Habitat characterization of sampling units in Thiruvananthapuram and Kollam districts District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of (%) E. bicolor Thiruvananthapuarm 0 Oliprathukunnu 152 8.54443 77.11922 Forest NP - - Bonacaud 702 8.68572 77.15647 Forest NP - - Kurisumudi 825 8.68305 77.15087 Forest NP - - Ponmudi 1008 8.76489 77.11313 Forest NP - - Vellanad 215 8.56460 77.06405 Private NP - - Kollam 0 Karadippara 288 8.88571 77.16253 Forest NP - - 13,Kannara bridge 354 8.96822 77.08790 Forest NP - - Manjatheri 884 8.92687 77.19166 Forest NP - - Vilakkumaram 572 8.93316 77.17044 Forest NP - - Darbhakulam 616 9.00668 77.15370 Forest NP - - State boundry 692 9.00712 77.15630 Forest NP - - Darbhakulam Rosmala 369 8.91863 77.17776 Forest NP - - Shendurney WLS 730 8.93032 77.19260 Forest NP - - Table 2. Habitat characterization of sampling units in district District / Altitude Latitude Longitude Politica Presence F D A Sampling unit (m) l status of ( %) E. bicolor Pathanamthitta 37.5 Upper Moozhiyar 1051 9.31543 77.12837 Forest NP - - Kakki dam site 1088 9.31991 77.14072 Forest NP - - Kakki hills 1096 9.38426 77.14365 Forest NP - - 10th mile Gavi 1139 9.44264 77.14367 Forest P 1.10 3.0 Ponnambalamedu 1077 9.39797 77.13774 Forest P Single plant Varadiyan kokka 1146 9.37426 77.15253 Forest P 1.20 2.4 Konni- V.Kottayam 115 9.20368 76.81278 Forest NP Pachakkanam 1077 9.38740 77.14648 Forest NP Table 3. Habitat characterization of sampling units in Kottayam ane Idukki districts

District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Kottayam 25.0 Elaveezhapoonchira 977 9.80831 76.77887 Revenue P 8 plants site I Elaveezhapoonchira 882 9.80766 76.78188 Revenue NP site II Illikkalmala 926 9.75586 76.82062 Revenue NP Vazhikkadavu 953 9.68374 76.89767 Forest NP Idukki 12.5 Uppupara 1194 9.47026 77.08987 Forest P 1.4 3.0 Rajamala 2046 10.14726 77.03686 Forest NP - - Ramakkalmedu 1090 9.90826 77.21837 Forest NP - - Mannavanshola 2247 10.17567 77.19085 Forest NP - - Wagamon 1123 9.64420 76.92519 Forest NP - - Nadukani 879 9.79492 76.87185 Forest NP - - 930 9.52904 76.97351 Revenue NP - - Kuttikkanam 1077 9.57143 76.97683 Revenue NP - - 78 ECO-CHRONICLE Table 4. Habitat characterization of sampling units in

District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Thrissur 58.3 0 Kadangode 78 10.69732 76.13335 Private P 7.50 7.50 Peruvanmala 104 10.62262 76.13521 Private P 3.50 4.30 Chernthala 64 10.64844 76.16342 Private P 2.30 3.30 Kallazhikunnu 62 10.67337 76.08717 Private P 0.17 0.10 Kidangur 58 10.57007 76.10456 Private NP - - Vilangankuunu 115 10.33439 76.10080 Revenu P 2.80 5.40 e Ottuparakunnu 59 10.63939 76.20242 Private P 3.80 5.00 Thachakunnu 60 10.74637 76.19365 Private NP - - Pindalikunnu 126 10.73586 76.18225 Private NP - - Thiruvilwamala 122 10.73696 76.44813 Forest NP - - Karukaputhur 93 10.73343 76.16616 Private NP - - Pilakkad 121 10.73699 76.44807 Private P 50 plants Table 5. Habitat characterization of sampling units in Palakkad district District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Palakkad 18.8 Nemmara NSS 90 10.59194 76.58278 Private NP - - College Jellippara 750 11.06667 76.59616 Forest NP - - Athanad hill 138 10.58785 76.60824 Private NP - - Varadimala 1398 11.04295 76.71158 Forest NP - - Parakkulamkunnu 101 10.80200 76.06951 Private P Single plant Moolakkamal 1287 11.03625 76.74617 Forest NP Narimadankunnu 64 10.80058 76.05733 Private P 3.10 5.10 Nelliyampathy top 1332 10.49729 76.65536 Forest NP - - station Thonikunnu 65 10.81855 76.03974 Private NP - - Veezhumala 127 10.61683 76.53964 Private NP - - Rayiranellurmala 220 1087175 76.16068 Private NP - - Silent valley dam 1061 11.09255 76.44563 Forest NP - - site Cherukunnu 160 10.85984 76.58242 Private NP - - Sirendri – Silent 1062 11.08792 76.44650 Forest P 1.60 3.90 Valley Koombanpara, S.V 1115 11.10502 76.39225 Forest NP Ommala 740 11.05362 76.58406 Forest NP RESULTS AND DISCUSSION In Pathanamthitta district, sampling was done in eight units which were all forest Results of survey done in twelve districts lands. Exacum bicolor was observed only are elaborated here with. Survey conducted in three locations viz. 10 th mile Gavi, in Thiruvananthapuram and Kollam Varadiyankokka and Ponnambalamedu. districts revealed no occurrence of Exacum Details are given in table 2. Only a single bicolor (Table 1).Though many locations plant was sighted in Ponnambalamedu in these districts are suitable habitats, the which is vast stretch of grassland. plant has not been recorded in earlier floristic studies also. Altogether 12 sampling units were surveyed ECO-CHRONICLE 79 Table 6. Habitat characterization of sampling units in Malappuram district

District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Malappuram 58.8 0 Paloorkotta 166 10.96745 76.15063 private P 3.1 4.70 Thaniyappankunnu 189 10.91409 76.05699 Private NP - - Chetharakunnu 121 10.92636 76.06264 Private P 10 plants Parambakulamkunnu 128 10.92887 76.07721 Private P 0.8 1.60 Nayyurkunnu 160 10.82111 76.06233 Private NP - - Thalapolipalakunnu 108 10.82043 76.07391 Private P 2 plants Olipramkadavu 105 11.14338 75.89242 Private P 0.6 2.40 Koombanpara site I 844 11.11183 76.38105 Forest P 50 plants Koombanpara site II 1114 11.11021 76.38465 Forest NP - - Malaparamba 170 10.95901 76.15291 private NP - - Malamakkavu temple 112 10.82008 76.0736 Private P 2 plants Noorukadukunnu 78 10.8254 76.04405 private P 1.1 2.80 Perumbalam temple 42 10.82545 76.03965 Private NP - - Chelakottakunnu 63 11.18484 75.90233 Private NP - - Chenathalakunnu 114 11.18800 75.90123 Private P 0.8 2.50 Nadukunnu 215 11.19362 75.92421 Private P 1.1 0.40 Thrikkaliyur temple 59 11.26302 76.00993 Private NP - -

Table 7. Habitat characterization of sampling units in Kozhikode district

District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Kozhikode 40.0 Palakurumbakunnu 75 11.22472 75.83893 Private P 0.35 2.30 Thaneeriyilmala 110 11.45429 75.74223 Private NP - - Ithlamkunnu 53 11.16905 75.87293 private P 2 plants Pallikunnu 174 NP - - Chngathadammala 87 11.32785 75.95581 private NP - -

Table 8. Habitat characterization of sampling units in Wayanad district

District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Wayanad 62.5 Chembra hill site I 1487 11.5441 76.08227 Forest P 1.30 3.10 Chembra hill site II 1560 11.5525 76.08413 Forest P 0.51 1.70 Brahmagiri 1366 11.93281 75.97968 Forest P 15 plants Watch tower, 1210 11.92333 75.98686 Forest NP - - Thirunelli State Border, 1450 11.93834 75.96525 Forest NP - - Thirunelli Pakshipathalam 1472 11.93871 75.96182 Forest NP - - Kurichiarmala site 1265 11.59798 75.97307 Forest P 0.80 2.50 I Kurichiarmala site 1376 11.60022 75.97001 Forest P 0.70 3.00 II 80 ECO-CHRONICLE Table 9. Habitat characterization of sampling units in Kannur district

District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of ( %) E. bicolor Kannur 30.34 Madayipara 35 12.02964 75.25402 Private NP - - Payyannur NSS 25 12.10374 75.23471 Private P 1.10 2.40 College Campus Mathil 75 12.16991 75.23961 Private NP - - Pilathara 33 12.07681 75.25864 Private P 0.20 0.15 Aruvanchal 103 12.215 75.28182 Private NP - - Govt. Brennan 55 11.77863 75.47055 Private NP - - College Ramanthali 105 12.04661 75.20642 Private NP - - Madakkampoyil 180 12.20452 75.33103 Private NP - - Ezhimala 110 12.01328 75.24364 Private NP - - Olembadi 158 12.19740 75.33094 Private NP - - Naduvil 150 12.11951 75.48389 Private NP - - Meenkulam 109 12.17368 75.30918 private NP - - Nadukani 168 12.10674 75.41006 Private NP - - Kanhirad 95 12.06003 75.37761 private NP - - Manna, 72 12.04683 75.37113 Private NP - - Thaliparamba Pariyaram Ayurveda College 54 12.07883 75.2882 private P 1.95 5.60 Campus Pariyaram Medical 54 12.07128 75.29973 private P 1.50 4.20 College Campus Munderi 165 11.90234 75.44266 Govt. NP - - PoovathumtharaKu 65 11.88116 75.45518 Private P 0.80 3.40 nnu Chalakunnu 48 11.85886 75.42341 Private NP - - Sadhu park, Chala 45 11.85826 75.42838 Private P 5 plants Chepparambu 90 12.02533 75.51614 private NP - - Sreekantapuram Bhaskara College of Fine arts, 90 12.11867 75.28952 Private P 2.80 4.00 Mathamangalam Table 10. Habitat characterization of sampling units in Kasargode district District / Altitude Latitude Longitude Political Presence F D A Sampling unit (m) status of (%) E. bicolor Kasargode 18.2 Cheruvathur 35 12.20885 75.15457 private NP - - Kuttamath HS 35 12.22065 75.16152 Private NP - - Neeleswaram 65 12.26122 75.15174 private NP - - Manjampothikunnu 120 12.33235 75.11469 private NP - - Cherkala 85 12.50634 75.05369 private NP - - Darmasala snake 65 11.99021 75.38911 private NP - - park area Cheemeni 100 12.23607 75.23415 private NP - - Kumbala School 24 12.59391 74.94530 private NP - - Narayana- 65 12.59455 74.96805 private NP - - mangalam Seenthankoli 95 12.59207 75.01146 Private P 2.3 5.10 Kumaramangalam 65 12.59321 74.01235 Private P 20 plants ECO-CHRONICLE 81 Table 11. Political status of Habitats of Exacum bicolor in Kerala

Number of habitats Total District Revenue – Forest – shola Revenue –Dry Private –Dry habitats Shola grassland grassland grassland grassland Thiruvananthapuram 0 0 0 0 0 Kollam 0 0 0 0 0 Pathanamthitta 3 0 0 0 3 Idukki 1 0 0 0 1 Kottayam 0 1 0 0 1 Thrissur 0 0 1 6 7 Palakkad 1 0 0 2 3 Malappuram 1 0 0 9 10 Kozhikode 0 0 0 2 2 Wayanad 5 0 0 0 5 Kannur 0 0 0 7 7 Kasargode 0 0 0 2 2 Total 11 1 1 28 41 in Kottayam and Idukki districts. Of the four In the State itself, the highest density and units sampled in Kottayam district and eight abundance (7.50) of the plant was reported in Idukki district, the plant could be sighted from Kadangode. The unit which is in private only in single unit each in both the districts possession was a plot recently planted with (Table 3). coconut and mango with tapioca and banana as intercrops. Exacum bicolor was Numerical status of the plant could not be seen only at the top of the hillock in a small assessed at Eleveezhapoonchira site I, due pocket. After 5-6 years, population of the to the steep terrain and presence of tall plant may be affected due to growing grasses. The unit is a notified tourist spot coconut and mango trees. Pilakkad is in Kerala. The inflow of visitors is increasing another private plot planted with cashew, every year and there is the risk of loss of Kallazhikunnu and Ottuparakunnu were plant by uprooting. Exacum bicolor was not being exploited for laterite mining. sighted in the vast grasslands of Eravikulam, Cherntthala with a density of 2.30 was Ramakkalmedu and Wagamon in Idukki entirely changed during a revisit in 2006. district. Uppupara which was adjacent to More than 90 % of the area was prepared Pathanamthitta district boundary, was the for planting with rubber. All these results only site where the plants were growing. reveal that a natural habitat of Exacum bicolor belonging to private possession is Most of the hillocks in southern districts likely to disappear at any moment. were already accommodated with Vilangankunnu, a revenue property with a established rubber plantations or public or density of 2.80 for the plant, is being planted private educational institutions. with tree seedlings every year as part of greening programme. The open Of the 12 sampling units in Thrissur district, grasslands may shrink considerably posing occurrence of Exacum bicolor was noted in threat to Exacum bicolor which can not seven units. Six of the sites were in private survive under full grown trees. Perhaps the possession and one is revenue land (Table most undisturbed unit in Thrissur is 4). Peruvanmala. A hillock of 104 m altitude is a temple property. The most interesting Thrissur with frequency of 58.30 is a district feature of the hillock is that Exacum bicolor accommodating more natural habitats of is occurring only in one side of the hillock. Exacum bicolor in the central part of Kerala. The location is gaining popularity and in 82 ECO-CHRONICLE future, the plant population may suffer Thalapolipalakunnu and Mamlamakkavu because of mass uprooting of the plant by temple premises with only 2 plants during visitors. 2005 was getting converted to residential area and rubber plantation. Nadukunnu with Results in table 5 shows that in Palakkad only a density of 1.10 was a location already district, of the 16 sampling units visited, being exploited for quarrying. occurrence of Exacum bicolor was noted Noorukadukunnu with a density of 1.10 only in three viz. Parakkulamkunnu, during 2005 was entirely changed to rubber Narimadankunnu and Sirendri(Silent plantation during revisit in 2006. At the time Valley). Two units are private properties and of revisit two JCBs were working in the place the other is forest land. to make contour bunds across the hill slope. Chenathalakunnu with a low density of 0.80 In Parakkulamkunnu, only a single plant was infested with many bushy plants and was sighted during survey in 2005. During the entire area was getting partitioned to the revisit in next year not a single plant was smaller plots by the owners. Olipramkadavu observed revealing complete within Calicut University Campus, disappearance of Exacum bicolor from the Parambakkulakunnu and Koombanpara location. Narimadankunnu was a better site were the most undisturbed habitats in in terms occurrence of Exacum bicolor with Malappuram district. a density of 3.10. But the location is destroyed at least by 50 % due to laterite In Kozhikode district, of the five units mining. Sirendri in Silent Valley is the most surveyed, Exacum bicolor occurred in two undisturbed habitat of the plant with a private units viz. Palakurumbakunnu and density of 1.60. Ithlamkunnu (Table 7).

Results of habitat characterization in Palakurumbakunnu was a degraded Malappuram district (Table 6) reveled that grassland with some portion of the hillock of the 16 sampling units studied, Exacum already disturbed for laterite mining. Only bicolor occurred in 10 locations and of two plants were sighted in Ithlamkunnu which nine are in private possession. during 2005. Local inhabitants opined that Exacum bicolor was very common in the With regard to the occurrence of Exacum place a few years back. Perhaps human bicolor, Malappuram is ranked second with interference is the factor for the the frequency of occurrence of 58.80%. Of disappearance of the plant in the location. the nine privately possessed habitats only a few plants occurred in three units viz. Wayanad district recorded the highest Chetharakunnu, Thalapolipalakunnu and frequency of 62.50% with regard to the Malamakkaveu temple. Paloorkotta which occurrence of Exacum bicolor in Kerala is in possession by many owners was a (Table 8). Perhaps the most undisturbed place with highest density of the plant in locations are in Wayanad. Malappuram district, during 2005. During revisit to the place in 2006, it was observed Density was considerably low in all the units that the plant population was very meager surveyed in Wayanad. In spite of large area in the place. Discussion with the locals of open grasslands very few plants could revealed that many plots were sold for be sighted in entire Thirunelli area. construction purposes and the others were utilized as foot ball ground by locals and Maximum area was surveyed in Kannur neighbours. Plants were also uprooted by district which is famous for many hillocks. many who visited the place for enjoying the Among the 23 units studied, Exacum beauty of the vast stretch of open grassland. bicolor occurred in 7 units and all of them Chetharakunnu with only 10 plants was were in private possession. Details of survey already a site exploited for laterite mining. results are given in table 9. ECO-CHRONICLE 83 The highest density of 2.80 for Exacum Exacum bicolor in isolated pockets even bicolor in Kannur district was observed in within a sampling unit was a unique feature the campus of Bhaskara College of Fine observed. The restricted occurrence might arts, Mathamangalam. The campus is a be attributed to its association with soil vast stretch of grassland with isolated trees. mycorrhizae (Strewe, et.al., 2002). Even Exacum bicolor plants were seen in an within a district, some locations are widely isolated pocket in the area. The area was separated and in some districts the plant being disturbed for construction of buildings itself does not occur. This could be as well as for cultivation purposes as part attributed to the discontinuous genus status of various activities of the College. The same of Exacum (Good, 1953). was the case with campuses like Payyanur NSS College , Pariyaram Ayurveda and Exacum bicolor is such a beautiful plant that Medical Colleges. As apart of greening the those who spot the plant will take it away to campuses many tree seedlings were also their home hoping to grow the same. But being planted in the grasslands. Both being a gentian, uprooting of the plant Pilathara and Poovathutharakunnu with poses great risk to its survival. The risk from negligible density of the plant were planted uprooting exists in many locations where with coconut and cashew respectively. there is large inflow of visitors. Sadhu Park, Chala with only 5 plants of Exacum bicolor was almost completely SUMMARY AND CONCLUSION disturbed for the construction of an amusement park. Habitat survey conducted in Kerala during 2005-2006 has revealed that there is Among the 11 sampling units surveyed in serious threat to the existence of Exacum Kasargode district, Exacum bicolor could bicolor in Kerala. Two southern most be sighted only in two privately possessed districts viz. Thiruvananthapuram and plots (Table 10). Kollam were devoid of the plant. Like wise, Exacum bicolor could not be sighted in In both the units studied in Kasargode major portion of Idukki grasslands. This district, Exacum bicolor plants were seen factor was assessed during survey in 2005 underneath small cashew plants. and again ensured in 2006 with the help of forest officials who updated for the Political status of the sampling units of occurrence of the plant during their regular occurrence of Exacum bicolor is an field visits. Among the 125 sampling units important determining factor for the studied in Kerala, occurrence of the plant existence of this plant in Kerala especially could be noted only in 41 units with a in the plains. The political status of habitats frequency of 32.80% for whole the State. of the plant in 12 districts of Kerala is Among the 41 units, 28 (68.29%) are in summarised in table 11. private possession, 11 are forest lands and 2 as revenue properties. Again, among the The results of the survey in entire Kerala 41 units of occurrence of Exacum bicolor, revealed that major habitats (70.73%) were 20 or less than 20 plants were recorded in dry grasslands in the plains of Kerala. 10 units during 2005. Within the 10 units These habitats were severely destructed for with less than 20 plants, six of them had laterite mining, quarrying, setting up only 5 or less than 5 plants in the entire plantations of rubber, coconut and cashew, area. Among the 28 private units, except one Grasslands in the plains were also in Thrissur (Peruvanmala), all other habitats converted as sites for industry and were seriously disturbed with laterite educational institutions. Enormous quantity mining, construction and plantations. Hence of soil is dumped for widening the high ways it could be easily summerised that all these and hillocks disappear all at once by habitats will be lost within a period of 5- 6 mechanized soil excavation. Occurrence of years. 84 ECO-CHRONICLE Hillocks in southern districts were planted Good, R. 1953. Geographical distribution with rubber decades back. Rubber and of flowering plants. Longman, Britain, p452 cashew plantations are spreading in the hillocks of northern Kerala. Resurvey was John, J. K, Nizar, A.M and Velayudhan, conducted in 2006 in 12 sampling units K.C.2001. Exacum bicolor: a beautiful wild spread over in Thrissur , Malappuarm and flowering herb. Indian Horticulture ,46(3) : Palakkad districts where Exacum bicolor 25. plants were reported during the previous year. Among the 12units, Plants could not Rao, M.R.1914. Flowering plants of be sighted in two units in Malappuram and Travancore, pp. 268-271. Bishen Singh one in Palakkad indicating a habitat loss of Mahendra Pal Singh, Dehra dun. 25 per cent within a period of one year. Plant population was severely affected due to loss Rao, R.S. 1986. Flora of Goa, Diue ,Daman, of more than 90 % of area in one unit Dadra and Nagarhaveli . Vol . 2 p.272 Thrissur and three units in Malappuram Botanical Survey of India, Calcutta. district owing to rubber planting, house construction and laterite mining. Reddi, S.T.V, Naidu, B.V.A.R and Prasanthi, S.2005. Herbal remedies for diabetes( in) Habitat survey of Exacum bicolor in Kerala Herbal remedies for diseases. I.Alikhan has revealed the distressing situation of the and A. Khanum(Eds.). Ukay publications, plant for its survival especially in the plains Hyderabad, pp 67-134. of Kerala. Plants in a few pockets of high altitude shola grasslands have to compete Sreelatha, U 2001. “Kanninantham with tall growing grasses to render its beauty Pakarum Kannamthali”. Mathrubhumi Daily, and hence grow very lanky with few flowers. July 7th Calicut Edition. Plants growing in hillocks in plains are more attractive with compact habit and more Sreelatha, U, Baburaj, T.S, Narajanan kutty, number of flowers. But the unscrupulous C, Mini Raj, N and. Nazeem P.A. 2006. exploitation of its habitats renders Exacum Exacum bicolor – An exquisite, endemic bicolor as a vanishing plant in Kerala. flowering herb from the wild. Abstracts, National Symposium on Under Utilized ACKNOWLEDGEMENTS Horticultural Crops held during 8-9th, June at IIHR, Bangalore, p 137. The Authors acknowledge the Department of Biotechnology, Government of India for Srivastava, R.C,1989, Drug plant resources funding the project entitled of Central India (an inventory) , p.57 Today “Characterisation, evaluation and & Tomorrow’s Printers and Publishers, New conservation of Exacum bicolor in Kerala Delhi. with emphasis on ornamental, medicinal and dye value” implemented by Kerala Struwe, L, Kadereit, J.W , Klackenberg, J, Agricultural University from 2004-2008. Nilsson, S, Thiv, M, Von Hagen, K.B and Albert V.A. 2002. Systematics, character evolution REFERENCES and biogeography of Gentianaceae, including a new tribal and sub tribal Anon,1952. Wealth of India: Raw Materials, classification (in) Gentinaceae Systematics Vol.III : p.234. Publication and Information and Natural History. L Struwe and V.A. Directorate, CSIR, New Delhi. Albert.(Eds.). Cambridge University Press, UK, pp 21-310. Chopra, R.N, Nayar S.L and Chopra, I.C. 1956. Glossary of Indian Medicinal Plants, Woodrow, G.M. 1910. Gardening in the P116. National Institute of Science Tropics. pp 395-396. Paisley: Alexander Communication, New Delhi. Gardner, London. ECO-CHRONICLE 85

ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 85 - 92

BIO ACCUMULATION OF SOME HEAVY METALS IN FISHES IN TUTICORIN COASTAL AREA, GULF OF MANNAR, INDIA

Obadiah, A.1, Sathish, V.2, Vasanth Kumar, S.1* and T. Bala Subramanian3

1Department of Chemistry, Karunya University, Coimbatore, Tamil Nadu. 2School of Chemistry, Madurai Kamaraj University, Madurai, Tamil Nadu. 3Department of Chemistry, V.O.C. College, Tuticorin, Tamil Nadu.

* Corresponding author: email: [email protected]

ABSTRACT

Bio-accumulation of some heavy metals in fishes in the Tuticorin coastal area of Gulf of Mannar, India has been studied. The bio accumulation of As, Pb, Cd, Cu, and Cr in fishes muscles, obtained from different coastal area and also from preserved canned fishes have been determined using Atomic Absorption Spectroscopy. The findings indicate that the presence of heavy metals in the fishes from Tuticorin coastal belt may lead to enormous environmental and health hazards. The effluents and wastes from Industries along the coast of Tuticorin, which are dumped into the sea adds on to the heavy metal bio-accumulation in fishes drastically.

Key words: Fishes, Gulf of Mannar, Bio accumulation, Heavy metals, Atomic Absorption Spectroscopy

INTRODUCTION human activities from around Tuticorin to Tiruchendur have altered the ecosystem Coastal marine ecosystems in many parts (Jonathan et al., 2004). Aluminium fluoride, of the world are under unrelenting stress urea, ammonium chloride, and caustic caused by urban development, pollutants soda manufacturing factories are located and other ecological impacts such as in the district of Tuticorin. Except for some buildings for infrastructural development, of the major industries, the effluents coming land reclamation for port and industrial out of the small scale industries are development, habitat modification, tourism disposed off in the coastal area. Tuticorin and recreational activities (Venkateswara Municipality generates sewage of 14mld Rao et al., 2007). The Gulf of Mannar is a capacity. This sewage is discharged into transitional zone between the Arabian sea the sea without any treatment (Tamil Nadu and the Indian ocean and is connected to Fisheries Statistics, 2004). the Bay of Bengal by a shallow sill, the Palk Strait. The area under investigation, which Over the last few decades, there has been is off Tuticorin in the Gulf of Mannar presents growing interest in determining heavy metal great interest because it is an industrial belt levels in the marine environment and consisting of many major industries, attention was drawn to the measurement involved in the production of chemicals, of contamination levels in public food petrochemicals and plastics. [Map 2 supplies, particularly in fish. Toxicological Industrial Area] In addition, a major harbour, and environmental studies have prompted thermal power plant, heavy water plant and interest in the determination of toxic 86 ECO-CHRONICLE elements in food (Ashraf, 2006). In general, aquatic organisms in the food chain, may studies on heavy metals can be important often accumulate large amounts of certain from the public health point of view, where metals. Essentially, fishes assimilate these attention has been centered on measuring heavy metals through ingestion of the accumulation of heavy metals; suspended particulates, food materials particularly those metals which pose and by constant ion exchange process of serious health hazards to human beings. dissolved metals across lipophilic (Table 1), (Khaled, 2004 ; The Hindu Survey membranes (Reddy et al., 2007). of Indian Industry, 2007). Gulf of mannar was the first Marine Biosphere Reserve of The inter-governmental oceanographic Southern Asia.[Map.1 Our Study area] This commission, an international agency within gene pool is presently under threat due to UNESCO for ocean research and related varied sources of pollution (Raghavan, matters, defines: marine pollutions as the (2006). To obtain a preliminary view of its introduction by man, directly or indirectly, of environmental conditions, geochemical substances or energy into the marine distribution of major elements Si, Al, Fe, Ca, environment(including estuaries), resulting Mg, Na, K, P and other trace elements like in such serious effects such as: harm to Mn, Cr, Cu, Ni, Co, Pb, Zn, Cd were analyzed living resources; hazards to human health; (Jonathan et al., 2004). The discharge of hindrance to marine activities including metals in aquatic systems normally takes fishing; impairing the quality of usage of sea its origin from weathering of soil and rocks, water and reduction of amenities (Varkey, volcanic eruption and a variety of human 1999). activities such as mining and processing industries that involve heavy metal Fishes have been used for many years to contaminants. In many countries, significant determine the pollution status of water, and alterations in industrial development lead are thus regarded as excellent biological to an increased discharge of chemical markers of metals in aquatic ecosystems. effluents into the ecosystem, leading to Bioaccumulation of heavy metals by damage of marine habitats. Heavy metal absorption occurs across the entire body discharged into the marine environment can surface of the fish (Benson et al., 2007). damage both marine species diversity and ecosystems, due to their toxicity and MATERIALS AND METHODS accumulative behaviour. Industrial wastes and mining can create a potential source of Sample collection heavy metal pollution in the aquatic environment. Under certain environmental Samples were stored in poly ethylene bags conditions, heavy metals might accumulate and brought to the laboratory, packed with up to toxic concentrations and cause ice (at 4°C) and proper labeling was done ecological damage. Thus, heavy metals on the same day of fish capture acquired through the food chain as a result (Venkateswara Rao et al., 2007). In the of pollution are potential chemical hazards Laboratory, the fish samples were weighed threatening consumers. Metals, such as and dissected for analysis. Composite copper, manganese, are essential metals samples of muscle tissues of each species since they play important roles in biological were taken using stainless steel system. Whereas, lead and cadmium are instruments, using the methods toxic, even in trace amounts. The recommended by UNEP/FAO/IAEA/IOC consequence of heavy metal pollution can (1984). be hazardous to man and it often becomes mandatory to check chemical contaminants Each muscle tissue was weighed in foods from the aquatic environment to separately in a clean labeled Petri-dish and understand their hazard levels (Perumal et dried over night for 1-2 days at 70°C to get a al., 2007). Fishes being one of the main constant weight. Pulverization was achieved ECO-CHRONICLE 87 Map 1. Graphical image of the study area by grinding the tissue samples in a Teflon mortar (Benson et al., 2007). All glassware and plastic devices used in manipulation of samples were completely acid washed and reagents of the analytical grade were utilized for the blanks and calibration curves. The performance of the method was evaluated by analyzing a reference material muscle homogenate provided by the International Atomic Energy Agency (IAEA) (Khaled, 2004).

Reagents

Map 2: Graphical image of the Industrialarea of All reagents used were of Tuticorin Coast Analytical grade (Analar-AR Grade). Working standards of Lead, Arsenic, Copper, Cadmium and Chromium, (Merck, Germany) of 1000mg/l were prepared in double distilled Deionized water.

Sample preparation

The dried samples (about 1 gm) were digested using 12ml of perchloric acid (AR) and nitric acid (AR) in the ratio 2:1 until the formation of a white residue at 100 0 C in a hot plate. The completely digested samples were allowed to cool to room temperature. The Table 1. Sources and the health effects of Heavy Metals

Element Sources Health effect

Coal Mining, Automobile, Paper, Learning disabilities, Mental LEAD Dyeing Leaded gasoline, Paints retardation Leather - tannery, Thermal Power plants, CHROMIUM Bronchial asthma, allergies Textile, Fertilizer, Photography Coal, Nuclear Power plants, Batteries, CADMIUM Itai Itai disease (fragile boner) Ceramics Coal burning, Processing of Sulphite ores, gastrointestinal disorder, ARSENIC Impurity in phosphates carcinogenic. COPPER Copper Smelting Industrial Wastes Hypertension, anemia. 88 ECO-CHRONICLE Table 2

SAMPLES Cu (ppm) Cd (ppm) Pb (ppm) As (ppm) Cr (ppm) Permeable limit 1.0 0.25 0.25 0.1 0.05 INDUSTRIAL AREA FISHES 0.2662 0.4500 0.3437 - 0.4120 1. S1 (Thres puram) 2. S2 (Fishing Harbour) 6.2562 0.1037 0.1900 - 0.3510

3. S3 (TTPS Channel) 1.4537 0.1575 0.4563 0.1540 0.4512

4. S4( Fishing Harbour) 2.0300 0.1988 0.1988 0.212 0.3852

NON INDUSTRIAL AREA 5. S5 Chippikullam 0.6300 0.1775 0.0838 - BDL

6. S6 Tharuvaikulam 0.3613 0.1688 0.0713 - BDL

7. S7 Manappadu 0.4788 0.2200 0.0675 0.0450 BDL

PRESERVED SEA FOODS (CANNED FISHES) 8. P.S – 1 0.8700 0.1238 0.1133 - 0.2156

9. P.S – 2 1.5762 0.1975 0.975 - 0.1802

10. P.S – 3 0.1528 0.0913 0.1628 - 0.1460 BDL – Below Detectable Limit cooled residue was dissolved completely spiked with standards. The concentrations by adding 1N HCl and made upto 25 ml of Cu, Cd, Cr, Pb & As detected in the edible with distilled water (Yoshinga 1999, Varkey portions of the fishes are given in the table 2. 1999). The solution was filtered through cotton and wool and the filtrate was The results indicate that concentration of subjected to trace metal analyses in an the Pb varies from 0.07 to 0.45ppm. The Atomic Absorption Spectroscopy (GBC industrial area fishes had high Pb avanta model). Some samples were concentration compared to fishes from non- analyzed in duplicate using Atomic Industrial sites and canned sea foods (Fig.1 Absorption Spectroscopy (GBC Avanta Industrial area). Lead was present in all the Model) available in the Offshore Platform samples. The highest concentrations were and Marine Electro Chemistry Centre – found in sample 3. Sample 3 was collected Centre for Electro Chemical Research near the Thermal Power Station, where fly Institute (OPMEC – CECRI) in Tuticorin unit ash is spread all over the site. Fly ash at Tuticorin Harbour. contains 1520μg/g-1 of Lead. (Block 1975) The contaminant from this thermal industry RESULTS AND DISCUSSION is the major reason for the high content of toxic metals like lead. Ten samples of fishes from industrial area, non-industrial area and canned fishes were The maximum concentration of Lead which analyzed for Cu, Cd, Cr, Pb & As. The results is permitted in prepared foods specifically of analysis showed good recovery when intended for babies or young children is ECO-CHRONICLE 89 Figure 1. Industrial area Fishes in Tuticorin Coastal area. 200µg/kg. (FAO/ WHO) The quantity Industrial Area Fishes of lead to be tolerated in human 7 food is 0.3 mg per week. Lead causes 6 renal failure, Cu 5 learning disability, Cd 4 mental retardation ppm m Pb and liver damage in 3 As humans (Perumal 2 Cr et al., 2007). 1 Therefore the bio- accumulation of Pb 0 in the fishes around S1 S2 S3 S4 this area poses Different Area Fishes great concern.

Figure 1. Non-industrial area Fishes in Tuticorin Coastal area. The concentration of the Cd varied from Non Industrial Area 0.09 to 0.45 ppm. Low Cd 0.7 concentration is 0.6 found in non- Cu 0.5 industrial site when Cd 0.4 compared with Pb ppm 0.3 m industrial site.(Fig.2 As Non industrial area) 0.2 Cr The joint Food and 0.1 Agricultural 0 Organization/World S5 S6 S7 Health Organization Different Area Fishes (FAO/WHO) expert committee on food Figure 3. Preserved fishes in Different Food companies in additives has Tuticorin. suggested a provisional toler- Preserved Sea Foods able intake of 400- 500µg of Cd per 1.8 week for man. The 1.6 threshold for acute 1.4 Cu cadmium toxicity 1.2 would appear to be Cd 1 a total ingestion of 3-

ppm m Pb 0.8 15mg. Severe toxic 0.6 As symptoms are 0.4 Cr reported to occur 0.2 with ingestions of 0 10-320mg of Cd. Fatal ingestions of 1 2 3 cadmium produces Different area Sea Foods shock. Acute renal 90 ECO-CHRONICLE Acute renal failure occurs from ingestions Chromium, arsenic and nickel are a group exceeding 350mg (Perumal et al., 2007). of hazardous metals notified by the USFDA The bio-accumulation of Cd is below even though not covered by EC Regulations permissible level except in sample 1 for fish and other aquatic products. because sample 1 fishes were collected Chromium was detected almost in all from the waters near the thermal power samples and a high concentration in station and Southern Petrochemical sample three (0.4512 ppm). Again this Industrial Corporation.. indicates the mixing of industrial effluents into the water in the Tuticorin Thermal Power The Arsenic content was not found in most Station Channel. Chromium is an essential samples. Only three samples contained trace element and the biologically usable Arsenic and two out of three (namely S3 and form of chromium plays an essential role in S4 from TTPS Channel and Fishing glucose metabolism. It has been estimated Harbour) had Arsenic above the permitted that the average human requirement is 1µg/ level. This result is due to the mixing of day. Deficiency of chromium results in industrial effluents from the nearby site. impaired growth and disturbances in Chronic arsenic poisoning symptoms glucose lipid and protein metabolism. include pigmented skin lesions, gangrene Excess of chromium results in asthma and of the lower extremities, with neuritis and allergic diseases. paralysis, anemia and disturbance of the liver and circulatory system (Perumal et al., Preserved (Canned) fishes from different 2007). From this it is very evident that food companies in Tuticorin were taken for industrial effluents mixing with the sea water our study. Copper was detected in almost in the Tuticorin Thermal Power Station all the samples and a high concentration in channel and fish harbor area increase the sample 2 (P.S.2). In the other two samples Arsenic content. it is within permissible limit. Another heavy metal Cd was present in all the samples Contaminated food probably represents studied, and is present within permissible a more important source of copper than limits. Arsenic in all the samples was below water. Despite the existence of a number the detecting level. Lead is detected in all of detoxifying and storage systems for Cu, the preserved fish samples, but in only one it is the most toxic metal after mercury and sample (i.e P.S.2) it is above the permissible silver, to a wide spectrum of marine life limit. Chromium is detected in all samples (Khaled, 2004). It is highly toxic to and a high concentration of it is present in invertebrates but moderately toxic to preserved sea food (P.S.1) sample mammals. Copper deficiencies in infants results in anemia and hypoproteinemia From the above study, it is evident that (Perumal et al., 2007). The concentration bioaccumulation of As, Pb, Cd, and Cu in of copper in the samples analyzed ranged the fishes found in the Tuticorin coastal belt from 0.3 to 2.03ppm. But the concentration is true. This can definitely pose are below the toxic limit. Copper is environmental and health problems. moderately high in sample 4, which may be due to the agricultural or industrial CONCLUSION wastes mixing with the sea water in this site. Copper is an essential element that Fishes are potential biomarkers of metals serves as a cofactor in a number of in the aquatic ecosystem. Marginally higher enzyme systems for most living concentrations of Cd, Pb and Cu, in fish organisms. But at high concentration, samples could be related to industrialization copper becomes a toxic pollutant. It is and related activities in the Tuticorin coastal used as a chemotherapeutic agent in areas. Results of this study supply valuable aqua cultures (Santos Carvalho et al., information about metal content in fishes private communication). found in the coastal area of Tuticorin. It also ECO-CHRONICLE 91 directly indicates the environmental hazards exposed to sublethal doses of the element, along the Tuticorin coastal area. Moreover, Asian science, 6, pp: 183-191. these results are valuable to understand the quality of fish available in the Tuticorin Khaled, A., 2004. Seasonal determination coastal belt and it enables one to evaluate of some heavy metals in muscle tissues of the possible risks and toxicity associated siganus rivulatus and sargus sargus fish with their consumption. form el-max bay and eastern harbour, Egypt, J. Aquat. Biol, Fish, pp: 2-9. ACKNOWLEDGEMENT Lima, E.C., Krug, F.J., Ferreira, A.T. and The authors acknowledge the financial Barbosa, F., 1994. Tungsten-rhodium support of TNSCST, and the AAS instrument permanent chemical modifier for cadmium facility extended by OPMEC-CECRI, determination in fish slurries by electro Tuticorin. The authors also thank the thermal atomic absorption spectrometry. Management of Karunya University and Journal of analytical atomic spectrometry, V.O.C. College for their encouragement and 14, pp: 269-274. support. Special thanks are due to Mr.R Kannan(Research Scholar) for his Perumal, P.S., Sankar, T.V. and Viswanath invaluable help. nair, P.G., 2007. Heavy metal concentrations in fish products form internal markets of REFERENCES India vis-à-vis international standards, J. Food chemistry, 102, pp: 612-620. Ashraf, W., 2006. Levels of selected heavy metals in tuna fish, The Arabian journal for Raghavan, R., 2006. Bio accumulation of science and engineering, 31, pp: 89 - 92. certain heavy metals in edible oyster crassartrea madafensis off Tuticorin coast, Block, C. and Dams, R., 1975. Lead Gulf of mannar India. Fisheries College and contents of coal ash and fly ash, water, air Research Institute. and soil pollution, 5, pp: 207-211. Reddy, M.S., Mehta, B., Joshi, M. and Benson, N.U., Essien, J.P., Williams, A.B., Bhasha, S., 2007. Bio accumulation of heavy and Bassey, D.E., 2007. Mercury metals in some commercial fishes and accumulation in fishes form tropical aquatic crabs of the gulf of cambay, India. Current ecosystems in the niger delta, Nigeria. science, 92 (11), pp: 1489-1491. Current Science, 92 (6), pp: 781-785. Santos Carvalho, C.D., Selistre de araujo, Jonathan, M.P., Ram-Mohan, V. and H.S. and Fernandes, M.N., Copper toxicity Srinivasalu, S., 2004. Geochemical and metallothionein induction in fish: effect variations of major and trace elements in of water temperature and pH. Private recent sediments, off the gulf of mannar, communication, pp: 215-220. the southeast coast of India, Environmental geology,45, pp: 466-480. Takatsu, A., and Uchiumi, A., 1998. Abnormal arsenic accumulation by fish living in a James, R., Sampath, K. and Edward, D.S., naturally acidified lake. The Analyst, 123, pp: 2003. Copper toxicity on growth and 73-75. reproductive potential in an ornamental fish, xiphophorus helleri, Asian fisheries Tamil Nadu Fisheries Statistics, 2004, science, 16, pp: 317-326. Coastal and marine environmental, pp: 40- 50. James, R., Sampath, K. and Devakiamma, G., 1993. Accumulation and depuration of The Hindu Survey of Indian Industry. 2007. mercury in a catfish heteropneustes fossilis: Pp: 329-333. 92 ECO-CHRONICLE Vetharoy, D., 2001. Geo chemistry of Varkey, M.J., 1999. Pollution of coastal seas, Tamiraparani estuary sediment. Ph.D., Journal of Science education. Resonance, thesis submitted to Manonmanian January, pp: 36-44. Sundaranar University. Yoshinaga, J., Morita, M., and Edmonds, Venkateswara Rao, J., Kavitha, P., Srikanth, J.S., 1999. Determination of copper, K., Usman, P.K. and Gnanashwar Rao, T., zinc cadmium and lead in a fish otolith 2007. Environmental contamination using certified reference material by isotope accumulation of metals in marine sponge, dilution inductively coupled plasma Sigmadocia fibulata inhabiting the coastal mass spectrometry using off-line waters of Gulf of Mannar India, Journal solvent extraction, Journal of analytical Toxicological and Environmental chemistry, atomic spectrometry, 14, pp: 1589- 89 (3), pp: 487-498. 1592. ECO-CHRONICLE 93

ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 93 - 98

PRIMARY PRODUCTIVITY STUDIES OF KUTTANAD AGRO ECOSYSTEM

Harilal, C.C.* and Ciju, M.

Division of Environmental Science, Department of Chemistry, St. Berchmans’ College, Changanacherry, Kerala. *Division of Plant Diversity and Ecology, Department of Botany, University of Calicut, Malappuram District, Kerala.

ABSTRACT

Kuttanad agro ecosystem refers to a water logged ecosystem, with a network of streams, channels, rivers, lakes and other impoundments. In the present study, Primary Productivity characteristics of Kuttanad agroecosystem has been assessed with respect to their efficiency for utilization for various aquaculture activities. Attempts were also carried out to assess the physic-chemical characteristics of these aquatic ecosystems and their impact on primary productivity.

Upon assessment of water quality parameters like Temperature, pH, Total Acidity, Total Alkalinity, Free Carbondioxide, Dissolved Oxygen and BOD along with Primary Productivity characteristics like Gross Primary Productivity, Net Primary Productivity and Respiration, it has been noticed that almost all sites under study can be effectively brought under aquaculture activities, after adopting adequate management measures. Key words: Kuttanad agro ecosystem, Primary Productivity Studies, Aquaculture

INTRODUCTION Various methods are employed for the measurement of primary productivities of Primary productivity of an ecological system, varying ecosystems. Each procedure is community or any part thereof is defined as having certain advantages and the rate at which radiant energy is converted disadvantages (Ryther, 1954). Some of the by photosynthetic activity of producer methods which are being followed in this organisms into organic substances. It is direction include: being represented as Gross Primary Direct count or numerical estimation Productivity (GPP), which is a measure of method the total organic matter synthesized, Harvest method including the organic matter used up in Oxygen method respiration during the period of Carbondioxide method measurement. On the other hand Net Chlorophyll method Primary Productivity (NPP) refers to the rate Radioactive tracer method or C14 method of storage of organic matter, excluding the pH method etc. organic matter being used up in respiration. Different ecosystems have different primary Assessment of the primary productivity of productivities depending upon their physical, any aquatic system gives us information chemical and biological characteristics. relating to the amount of energy available to Typical ecosystem productivities vary from 0.5 support its biological activity (Volenweider, grams of dry organic matter per square meter 1969). Estimation of primary productivities per day to nearly 20 grams per square meter of aquatic ecosystems, which are adversely per day. Most terrestrial ecosystems produce affected by anthropogenic activities serve 4 to 10 grams per square meter per day during as an important tool in studying the effect of ideal growth conditions. those activities on such ecosystems. In the 94 ECO-CHRONICLE present study, primary productivity studies CO2, DO and BOD using standard methods of Kuttanad Agro ecosystem has been as prescribed in APHA (1995). Information carried out to assess the efficiency of such pertaining to the sampling sites is given in a system to support various aquaculture Figure and data pertaining to water quality activities. characteristics together with those of GPP, NPP and Respiration are given in the Table MATERIALS AND METHODS 1 (a-b).

Kuttanad, the rice bowl of kerala, lying RESULTS AND DISCUSSION between latitude 908’ and 90 52’ N and longitude 760 19’ and 7604’ E, is a complex Accurate estimates of primary productivity ecosystem, unique in its ecological features. are essential considerations for the proper It encompasses an area of 1150 sq. km., conservation and management of all natural lying 0.6 to 2.2 m below mean sea level. habitats. It provides us with a means of Out of the total area, 110 sq. km. remains assessing whether an ecosystem is being water logged throughout the year, 55 sq. km. under exploited or over exploited or the yield is reclaimed land and 136 sq. km. covers is as great as it could be (Clarke, 1954). the lakes, rivers and canals. It is a deltaic This is perhaps the only way of assessing formation of four major rivers, Meenachil, the productive potential, particularly in case Pamba, Manimala and Achancoil, together of aquatic habitats (Hynes, 1960). with the low lying areas in and around Vembanad lake. This region is water logged It is well established that the primary almost round the year and is subjected to productivity is controlled by several physico flood submergence during monsoon and chemical and biotic interactions. It is difficult salt water ingression during summer. to point out the most critical factor that determines the rate of productivity. Most This region experiences a humid tropical important among numerous physico climate with average temperature ranging chemical parameters of the fluvial system from 21-340C. The mean relative humidity is 79%. A prolonged rainy season from May which have a bearing on their productivity to November and a lean period from are pH, alkalinity, acidity, temperature, free CO , DO, BOD and availability of nutrients. December to April are characteristic feature 2 of this region. The south west monsoon Many of these factors are interrelated contributes over 60% of the rainfall of the (Hynes, 1960) and changes in any of these region. The existence of warm weather and factors affect aquatic life. humid environmental conditions are convenient and congenial for agriculture – pH measurements in water gives a straight aquaculture integrated activities. picture of its acidic / alkaline nature and is considered to be a significant index in water In the present study, an attempt has been pollution studies. pH determines the carried out to assess the primary productivity growth, existence and distribution of many status of the aquatic systems of lower aquatic organisms. Majority of aquatic Kuttanad, with a view to bring them under organisms are best suited for a pH of various aquculture activities. Primary approx. 7; but some grow rapidly in water productivity status of water from 56 having other pH values. In the present study, environments, representing rivers, lakes, pH of aquatic systems studied ranged channels and other impoundments of the between 4.50 (site 36) and 8.01 (site 38) study area has been assessed using light with a mean value of 7.028. and dark bottle method (Gaarder and Gran, 1927). Attempts were also carried out to Temperature can be a real factor in assess various water quality parameters estimating primary production. Higher like pH, Temperature, Alkalinity, Acidity, Free temperature can be a real cause of rich ECO-CHRONICLE 95 productivity in some areas, whereas it is of Of various gaseous constituents in water, little importance in some others. oxygen is a factor which provides more Temperature influences DO and in turn information about the overall health of the affects aquatic productivity. DO decreases aquatic system than any other chemical in water with a constant increase in parameter. It is also important since the temperature beyond a limit. In the present existence of aquatic life is intimately linked study, temperature of water bodies showed with the availability of oxygen for their survival. a minimum value of 240C (site 43 and 44) The amount of DO in natural waters and a maximum value of 350C (site 48, 51 depends on various factors such as and 54) with a mean value of 29.070C). temperature, partial pressure and salinity. DO may be helpful to explain the various Total alkalinity is the measure of the capacity physical, chemical and biological of the water to neutralize a strong acid. processes taking place in water (De’souza Alkalinity in water is generally imparted by and Sen Gupta, 1981). Lower oxygen the salts of carbonates, bicarbonates, concentration also enhances the toxicity of phosphates, nitrates, borates, silicates etc. most poisonous substances (Kupchella together with hydroxyl ions in the free state. and Hyland, 1989). In the study, DO ranged Saha et al (2001) found that the total from 0.527 mg/l (site 18) to 3.691mg/l (site alkalinity exerts a direct significant role on 33) with a mean value of 1.482 mg/l. gross primary productivity. Highly productive waters have alkalinity values over 100 mg/l. BOD is a semi quantitative measure of Shivananda Murthy (1998) reported that biodegradable organic waste contained in alkalinity above 50ppm have been found any water and its measurement is crucial suitable for aquaculture. In the present in the assessment of organic pollution. In study, alkalinity ranged from 6.0 mg/l (site the present study, BOD ranged from 25) to 210 mg/l (site 45) with a mean value 0.276mg/l (site 6) to 1.687 mg/l (site 3) with of 58.21 mg/l. a mean value of 0.189mg/l.

Acidity of water is its capacity to neutralize a In the present study, GPP ranged from 0.002 strong base to a fixed pH. It is caused by the mg C/l/hr (site 2) to 0.068 mg C/l/hr (site 40) presence of strong mineral acids, weak with a mean value of 0.031 mg C/l/hr, acids and hydrolyzing salts of strong acids. whereas NPP ranged from 0.002 mg C/l/hr However in natural unpolluted fresh waters, (site 2) to 0.060 mg C/l/hr (site 1) with a the acidity is mostly due to the presence Location Map of free CO2 in the form of carbonic acid. In the present study, acidity of water samples showed a maximum of 2.5 mg/ l (site 27) and a maximum of 115mg/ l (site 8) with a mean value of 17.517 mg/l and the conce ntrations of free CO2 varied from 1.76 mg/ l (site 33) to 79.2mg/ l (site 24) with a mean value of 12.468 mg/l. 96 ECO-CHRONICLE Table 1 (a) Table Agro ecosystem Results of water quality and primary productivity of water samples collected from various water resources of Kuttanad ECO-CHRONICLE 97 Table 1 (b) Table Results of water quality and primary productivity of water samples collected from various water resources of Kuttanad Agro ecosystem 98 ECO-CHRONICLE mean value of 0.0182 mg C/l/hr and values agro ecosystem, almost all aquatic systems relating to respiration from 0mg/l (site 1) to can be effectively brought under fish farming, 0.933 mg/l (site 16) with a mean value of after adopting certain management 0.164 mg/l. measures.

Assessment and management of water REFERENCES quality is one of the most important aspects in aqua farming. As per the tolerance Ryther John, H. 1954. The ecology of guidelines for aquaculture, a pH ranging phytoplankton blooms in Moriches Bay and from 6.5 – 9 is desirable for fish farming. In Great South Bay, Long Island, New York. the present study, most of the sites exhibited Biol. Bull., 106: 198 – 209. optimum alkaline pH, capable of sustaining aquaculture activities. This was also Vollenweider, R. A., 1969. A manual on supported by high alkalinity, less acidity and methods for measuring primary production less free carbon dioxide content of water in aquatic environments. Backwell, Oxford, samples. Temperature of water bodies 225. were also found to be in optimum levels to sustain fishery. Gaarder, T. and Gran, H.H., 1927. Investigations on the production of plankton Desirable range of DO for fish growth is in Osla, Fjord. Rapp. Et. Proc. Verb. Cons. 5mg/l. In DO ranging from 1-4mg/l, fishes Int. Explor. Mer., 42: 1 – 48. will survive, but will be of slow growth. In the present study, all sites reported DO APHA, 1995. Standard methods for the less than 4.0 mg/l, indicating a stressful examination of water and waste water, condition in the growth of fishes. These American Public Health Association, points out the need for artificially aerating Washington, D.C. (19th Edition). the systems, throughout the course of aquaculture. BOD less than 2.0 mg/l can Clarke, G. L.,1954. Elements of Ecology. sustain fishery and in the present study, John Wiley & Sons, New York, 560. all sites recorded low BOD, less than 2.0 mg/l, indicating less of organic pollution. It Hynes, H.N.B., 1960. The biology of polluted has also been noticed that gross primary water. Liverpool University Press, productivities and net primary productivities Cambridge, 202. are more or less optimum to sustain aquaculture. Net productivities are usually Shivananda Murthy, H., 1998. Fresh water 30 – 50% of gross primary productivities prawn culture in India. Info fish International, and in the present study also, similar 5198: 30 – 36. pattern has been noticed. De’souza, S.N. and Sen Gupta, R.S., 1981. Thus on an overall assessment of the water Studies on the nutrients of Mandove and quality and primary productivity of Kuttanad Zuari river systems. Ibid, 10: 314 – 321. ECO-CHRONICLE 99

ECO-CHRONICLE, Vol. 5., No. 2. June 2010, pp: 99 - 106 ISSN: 0973-4155

HYDROGEOCHEMISTRY IN THE PART OF ARIYALUR REGION, PERAMBALUR DISTRICT, TAMIL NADU, INDIA.

Vijayakumar, V., Vasudevan, S., Venkatramanan, S. and Ramkumar, T.

Department of Earth Sciences, Annamalai University, Annamalainagar, Tamil Nadu. Corresponding author: [email protected]

ABSRACT

Hydrogeochemistry of a region is a reflection of the hydrodynamic process, lithological composition and physical constraints. Case study has been carried out in a varied lithological terrain with Archeaen, Gondwana, and Cretaceous rocks to unravel the hydrogeochemical process. The groundwater nature is explained by the Johnson plot, which indicates high Ca + Mg, SO4+Cl and

HCO3+CO3 facies in both the seasons. Geochemical processes of the study area is explained by Gibbs plot and identified evaporation process, which is the major process controlling the groundwater chemistry of the study area. The quality of the water for irrigation was estimated by USSL classification indicating high salinity and low sodium hazard, satisfactory for plants having moderate salt tolerance on soils. Doneen plot reveals that groundwater samples in both the seasons fall in class I indicating water is good for irrigation purpose. Silicate minerals are less saturated, and are comparatively undersaturated with respect to carbonate minerals. Dilution of water chemistry during the post-monsoon season in the Archaean formation and mixing in the Cretaceous formation are noted.

Keywords: Hydrogeochemistry, Perambalur, Tamilnadu.

INTRODUCTION process and reactions, that has acted on the water from the moment it has Ground water hydrology and condensed in the time its discharged by a hydrogeochemistry is a broad field with well (or) spring. The hydro geochemical many ramifications. Hydrogeochemistry of composition of ground water can also be groundwater is determined by its chemical indicative of its origin and history, of the and biogeochemical constituents, its underground materials that the water has sediments, lithologic content and its been in contact with, in shallow and deep- temperature is of a great importance is seated conditions. Natural sources and determined the suitability of a particular anthropogenic sources and significance of ground water for certain utilities i.e. public chemical and biogeochemical constituents water supply, irrigation, industrial have been considerably altering the ground application, cooling, heating, power water quality in the recent time and in the generation etc. The quality of ground water past. The study area has three distinct is the resultant of all biogeochemical geological formations viz. Archeaen, 100 ECO-CHRONICLE Fig 1. Location and Geology map of the quality perspectives of the study area region by developing base line data.

STUDY AREA

The study area falls in a part of Ariyalur region, Perambalur district, located in the central part of the Tamilnadu. It lies between North latitudes 11°08å00åå -11°31å00åå and East longitude 78° Fig. 2. Hill Piper Diagram 35å00åå – 78°59å50åå Fig 1. Location and Geology map of the study area (Fig.1). The area falls in the survey of India toposheets 58 1/11, 12, 14, 15&16. The study area bounded by Trichirapalli district in the south western side, Salem district in northern side, Cuddalore district in north and north east. On the south eastern

Premonsoon side, it is bounded by Alattur and Veppur taluk of Perambalur district.

STRATIGRAPHY

The study area has three distinct geologic formation viz. Archean, Gondwana and Cretaceous. Cretaceous formation are underlying by hard igneous rock in some places. Few areas of upper Post monsoon Gondwana beds are found near Uttathur village,

Gondwana,Fig 2. Hill Piper andDiagram Cretaceous. Analyses of consisting of micaceous hydrogeochemistry of groundwater in and shales, grey, sandstone and part of Ariyalur region Perambalur area has grits. Upper Gondwana rests been attempted to obtain ground water on Archean gneisses and ECO-CHRONICLE 101 Fig 3. Gibbs plot overlain by the Cretaceous formations. Uttatur group of rocks rest over the platform

Premonsoon of Charnockite in the central part of the study area, and at certain places it rests over upper Gondwana formations comprising conglomerates, greyshale/ limestone/ marl/ calcareousclay/ limestone, marl/calcareous clay/lime silt clays, argillaceous sandstone, with bands of marl stone, calcareous siltstone, Limestone etc in stratigraphical order. METHODOLOGY

Post monsoon Groundwater samples were collected during pre-monsoon (August 2007) and post monsoon periods (Dec, 2007). 18 samples were collected, from different litho units Archean (8), Gondwana (3) and Cretaceous (7). The depth of water table at the time of sample collection was 42.4 –

Fig 4. USSL diagramFig 3. Gibbs plot Fig 5. Doneen plot

Premonsoon

Premonsoon

Post monsoon

Post monsoon

Fig 4. USSL diagram Fig 5. Doneen plot 102 ECO-CHRONICLE Table 1a. Chemical composition of groundwaters during premonsoon (All values in mg/l except EC in µs/cm and pH)

S. pH EC Ca Mg Na K Cl HCO3 SO4 H4SiO4 TDS No A1 9 1850 216 33.6 68 22 319 335 60 38.8 1192

A2 8.5 1560 144 24.7 67 28 71 587 30 0.4 986

A3 7.3 1590 132 40.8 70 31 337 203 65 1 883

A4 7.3 1840 192 4.8 77 35 284 231 70 20.4 936

A5 8.1 1400 160 35 69 43 195 490 65 0.1 1068 Archaean A6 7.9 1500 168 36.6 81 35 337 272 66 29.7 1052

A7 8.1 1523 100 43.7 77 39 177 375 40 27.6 892

A8 8.7 1303 45 48 37 40 71 322 59 24.8 650

G1 7.1 2070 204 98.4 40 28 355 572 65 5.9 1370

G2 8.1 1435 50 50.4 37 34 89 351 40 4.8 667 ondwana

G G3 7.3 1562 140 38.4 40 22 89 442 67 1.5 850

C1 7.1 3200 272 101 79 51 449 846 75 5.7 1890

C2 7.2 1732 68 120.4 45 53 266 367 71 8 1005

C3 7.9 2040 180 38.4 40 56 266 516 70 2.7 1186

C4 7.3 3256 352 153.6 56 55 950 358 76 3.4 2025

Cretaceous C5 7.1 3842 584 81.6 79 55 1186 323 76 3.1 2398

C6 7.1 2875 424 43.2 65 30 845 299 75 1.2 1790

C7 7.2 2610 196 147.2 49 27 580 474 71 1.7 1560

90.9m BGL. The samples collected were Water in the study area is generally alkaline analysed for major cations like, Ca and Mg in nature, with pH ranging from 7.1 – 8.98. by Titrimetry, Na and K by Flame photometer In pre-monsoon season it is relatively more

(CL 378); anions, Cl and HCO3 by Tirimetry, alkaline than in the post-monsoon season.

SO4, PO4, and H4SiO4 by Spectrophotometry Electrical conductivity (EC) shows seasonal (SL 171 minispec). EC and pH were variation with values of 1303 - 3842 ?scm-1 determined in the field using electrode. The and 820 - 2800 ?scm-1 for pre-monsoon analyses were done by adopting standard and post monsoon seasons respectively, procedures (APHA, 1998). indicating increase in concentration of major ions in non-monsoon period and dilution RESULT AND DISCUSSION during monsoon. EC shows dilution in Archaean formations during post-monsoon Chemical constituents present in water in season but enhancement of EC is noted in different seasons are presented in Table.2. a few samples in Cretaceous formation. ECO-CHRONICLE 103 Table 1b. Chemical composition of groundwaters during postmonsoon (All values in mg/l except EC in µs/cm and pH)

S. pH EC Ca Mg Na K Cl HCO3 SO4 H4SiO4 TDS No

A1 8 2100 176 108 59 24 390 744 37 2.1 1340

A2 7.1 1560 152 53.2 51 24 153 617 25 22 996

A3 7.6 1570 164 48 39 20 336 362 36 0.2 1005

A4 7.5 1378 164 32 51 18 256 344 25 22.5 879

A5 7.1 1046 136 4.8 56 19 188 225 30 30 656 Archaean

A6 7.5 1545 204 34 56 25 208 485 45 11.7 986

A7 7.1 1147 112 24 39 20 124 314 20 32.8 670

A8 7.9 1220 188 12 40 27 212 355 33 1.1 813

G1 8.1 1700 184 86.4 37 18 408 391 23 36.8 1087

G2 7.3 820 64 12 47 19 106 247 20 35.6 512

Gondwana G3 7.5 950 128 32 42 23 287 262 24 0.7 598

C1 7.2 2290 278 84 69 20 195 869 48 1.6 1464

C2 7.8 970 100 21 40 22 180 229 45 3.8 620

C3 8 1200 128 29 41 20 188 288 44 37.2 748

C4 7.3 2500 410 12 60 19 385 658 46 1.2 1560

Cretaceous C5 8.3 2800 512 16.8 56 19 678 466 47 1.4 1768

C6 8.1 2450 372 36 48 22 594 492 47 2.2 1542

C7 8.7 1300 184 4.8 63 18 201 284 45 2.8 798

Output of WATCLAST (Chidambaram, 2004) in all rock types in post-monsoon season for two seasons (Table.3) shows Na%, in and during pre-monsoon season Ca-Na safe category. In USGS hardness facies is dominant in Archaean and classification, the samples fall in very hard Gondwana formations. Seasonal influence category irrespective of lithology. In the plot was not noticed in Na%, EC and in Cation for EC, samples in Archaean formations fall facies. within permissible limit irrespective of season. But in Gondwana and Cretaceous The modified Hill Piper by Johnson (Fig 2) formations the samples fall in both was used for the geochemical studies. The permissible and doubtful ranges. Plot for diamond shaped field is converted into a cation facies shows dominance of Ca-Mg square. The diagram shows that samples 104 ECO-CHRONICLE are equally distributed in category 1 and 2 indicates high Ca+Mg,

SO4+Cl and HCO3+CO3 facies in both the seasons (Piper. 1994).

The hydro chemical studies are not only to explain the origin and distribution of the dissolved constituents but also to elucidate the factors controlling the groundwater chemistry. As per the classification of Gibbs (1970), the major natural mechanisms controlling world surface - ground water chemistry are (i) atmospheric precipitation (ii) Rock weathering and (iii) evaporation and fractional crystallization. A boomerang shaped diagram resulted when Gibbs plotted the ratio of three major cations as (Na+K)/ (Na+Ca+K), versus TDS.

Table 2. Output of WATCLAST PROGRAMME (A*) Pre monsoon (B*) Postmonsoon (B*) monsoon Pre (A*) PROGRAMME WATCLAST of Output 2. Table In the study area, the ratios of (Na+K) / (Na+Ca+K) of the groundwater samples have been plotted against TDS. Similarly the ratios of Cl / (Cl +

HCO3) have been plotted ECO-CHRONICLE 105 against TDS and is shown in Fig , both the automatically leads to the conservation of figures show the similar nature of water. water and water resources. In regions of Most of the samples in both the seasons scanty rainfall, every drop of water has to be fall in evaporation zone (Fig 3). This stored. The meteorological study point out indicates evaporation process is also an the higher amount of rainfall is during the important mechanism controlling the water north east monsoon. The temperature of chemistry. the region is higher in the summer. The study draws out the following conclusions Salinity of groundwater and sodium Groundwater in the study area is generally absorption ratio (SAR) also determines its alkaline in nature. Electrical conductivity utility for agricultural purposes. Salinity (EC) shows seasonal variation with values originates in groundwater due to weathering of 1303 - 3842 ?scm-1 and 820 - 2800 ?scm- of rocks and leaching of ions from top soil, 1 for pre-monsoon and post monsoon anthropogenic sources along with minor seasons. The dominance of Ca-Mg facies influence on climate. The level of Na and is shown in all rock types in post-monsoon

HCO3 in irrigation groundwater affects seasons and during premonsoon season permeability of soil and drainage of the area. Ca-Na facies is dominant in the Archaean When SAR (alkali hazard) and specific and Gondwana formations .In USGS conductance (Salinity hazard) is plotted in hardness classification, the samples fall in USSL diagram, classification of water for very hard category irrespective of lithology. irrigation purpose can be determined The groundwater nature is explained by the (USSL. 1954). In both the seasons, all the Johnson plot, which indicates high Ca+Mg, groundwater samples fall in C3S1 zone SO4+Cl and HCO3+CO3 facies in both the indicating high salinity and low sodium seasons. Geochemical processes of the hazard, satisfactory for plants having study area is explained by Gibbs plot and moderate salt tolerance on soils (Fig 4). identified evaporation process, which is the major process controlling the groundwater Permeability index is an important factor chemistry of the study area. The quality of which influences quality of irrigation water, the water for irrigation was estimated by in relation to soil for development in USSL classification indicating high salinity agriculture. Based on permeability index, and low sodium hazard, satisfactory for classified the groundwater as class I, class plants having moderate salt tolerance on II and class III to find out suitability of soils. Doneen plot reveals that groundwater groundwater for irrigation purpose (Fig 5). samples in both the seasons fall in class I All the groundwater samples in both the indicating water is good for irrigation seasons fall in class I indicating water is purpose. good for irrigation purpose (Wilcox. 1955). REFERENCES CONCLUSION APHA., 1998. Standard methods for the The increasing need for water, puts a high examination of water and wastewater, 19th strain on the available water resource, edition. APHA, Washington DC, USASS. 106 ECO-CHRONICLE Gibbs. R.J., 1970. Mechanisms controlling USSL., 1954. Diagnosis and improvement world’s water chemistry, Science, 170, of Saline and Alkali soils, USDA Handbook pp:1088 – 1090. 60, p:147.

Piper A.M., 1994. A graphic procedure in the Wilcox L.V., 1955. Classification and use of geochemical interpretation of water Irrigation water, U.S Geological Department analysis. Trans Geophysics union 25, Agri Arc 969, p:19. pp:914 – 923. ECO-CHRONICLE 107

ECO-CHRONICLE, Vol. 5., No. 2. ISSN: 0973-4155 June, 2010, pp: 107 - 110

DO FEMALE STUDENTS HAVEAN EDGE IN TECHNICAL EDUCATION?

Prince Arulraj, G1., Brema, J.2 and C. Joseph Kenndedy3

1. Department of Civil Engineering, SNS College of Technology, Coimbatore, Tamil Nadu. 2. School of Civil Engineering, Karunya University, Coimbatore, Tamil Nadu. 3. Controller of Examinations, Karunya University, Coimbatore.

ABSTRACT

Few decades back, the female students of our country were deprived off the education. Only very few female students were allowed to go for higher education. At present, the scenario has drastically changed and female candidates study all courses and they takeup challenging responsibilities. The performance of female students is better in schools and colleges. Most of the top ranks are snatched by girl students. An attempt has been made to find out whether the performance of girl students is better than that of the male students in technical education. The data of the students of Karunya University has been considered for the study. The study indicates that the performance of girl students is better than that of the male students. The reasons for this are also presented.

Keywords: Female students, Performance, Technical education

INTRODUCTION been made to compare the performance of the girl students in technical education with Women in India were seen as a burden to that of their male counterparts. society and not as an asset few decades back. This idea still prevails in rural areas Karunya University is one of the best of this country. The main reason for this universities in India offering Engineering, concept is that parents of a female child Technological, Management and Arts and usually will have to pay dowry to the other Sciences Courses in various disciplines. family so that the girl will be allowed to marry The university is located at the foot hills of one of the members of the other family. Siruvani hills, 28 km from the city of Dowry is demanded because the bride Coimbatore in Tamil Nadu. The strength of cannot work and earn money like the the students in Karunya University was husband, due to lack of educational 4801 during the academic year 2008-09. qualification. About 44.85 % of them were female students. The results of the November/ The education for women in India was a December 2008 examinations of the major problem. After turning 10, half of university have been used to evaluate the India’s girl children discontinue school. Due performance of female students. to the steps taken by the leaders of the country and social awareness, the literacy Performance of U.G. students rate among women has increased in the recent past. The number of girl students Out of 4364 U.G. students who appeared undergoing technical education has also for the exam, 406 girl students had one or increased in recent years. An attempt has more arrears. This percentage comes to 108 ECO-CHRONICLE 9.33. The number of male students with Performance of P.G. Students: one or more arrears is 1040. The Out of 431 P.G. students appeared for the percentage of male students having exam, 23 girl students had one or more arrears comes to 23.83. It is clear from this arrears. This percentage comes to 8.90. The data that only very few female students have number of male students having one or arrears whereas many male students have more arrears is 51. The % of male students arrears. having arrears comes to 29.12. It is clear from this data that only very few female The number of female students who students have arrears whereas many male bagged the top three ranks for all the students have arrears in P.G. courses also. courses comes to 169 whereas the number of male students who are in the The number of female students who top three places is only 83. This clearly bagged the top three ranks for all the shows that female students have an edge courses comes to 35 where as the number over the male students as far as the ranks of male students who are in the top three are considered. The average CGPA of the places is only 13. This clearly shows that male students comes to 6.98 whereas the female students have an edge over the male average CGPA of the female students students as far as the ranks are considered. comes to 7.44 out of ten. The salient The average CGPA of the male students features of the comparative performance comes to 7.09 whereas the average CGPA of the male students and female students of the female students comes to 7.59 out of are given in Table 1. ten. The salient features of the comparative

Table 1. Salient Features of the Performance of Male students and Female students of the U.G. Programme

Sl. Nomenclature No. of No. of No. of No. of % % No Male Female Male Female Success Success . students students students students of Male of appeared appeared Passed Passed students Female for for Exam students Exam. 1. B.E. (Civil) 182 67 66 48 36.26 71.64 2. B.E. (EEE) 159 103 105 74 66.03 71.84 3. B.E. (ECE) 591 325 400 283 67.68 87.07 4. B.E. (EIE) 161 100 79 77 49.06 77.00 5. B.E. (CSE) 532 386 342 341 64.28 88.34 6. B.E. (IT) 304 221 166 185 54.60 83.71 B.Tech. 7. 176 88 63 58 35.79 65.90 (Media)

B.Tech. 8. 161 346 92 252 57.14 72.83 (Biotechnology)

B.Tech. (Bio- 9. 111 153 51 111 45.94 72.54 informatics) 10 B.Tech. (Food 92 106 35 56 38.04 52.83 . Processing) Total 2469 1895 1399 1485 ECO-CHRONICLE 109 performance of the P.G. male students and female students are given in Table 2. From Table 3, it can be seen that nearly 76% of first ranks, 59% of second ranks and 64% Ranks Obtained: of third ranks (are bagged by the female Analysis of the results indicates that the girl students) in U.G. Programmes. In case of students secure more ranks compared to P.G.Programmes, nearly 69.1% of female the male students. Table 3. and Table 4. students bagged the first rank while 56% gives the details about the ranks secured and 94% of female students bagged the by the students of U.G and P.G. students. second and third ranks respectively.

Table 2. Salient Features of the Performance of Male students and Female students of the P.G. Programme

Sl. Nomenclature No. of No. of No. of No. of % % No. Male Female Male Female Success Success students students students students for Male for appeared appeared Passed Passed students Female for for students Exam. Exam. 1. M.Tech (Civil) 18 11 11 7 38.89 100 2. M.Tech (EEE) 8 12 10 4 50 83.33

3. M.Tech (ECE) 49 56 39 54 79.59 96.42

4. M.Tech (EIE) 22 14 15 11 68.18 78.57

5. M.Tech (CSE) 50 100 47 96 94.00 96.00

M.Tech 6. 19 52 11 44 57.89 84.61 (BioTechnology) M.Tech 7. 9 6 4 4 44.44 66.66 (BioInformatics)

M.Tech (Food 8. 6 5 3 5 50 100 Processing) Total 181 256 140 225

Table 3. Rank Table for U.G. Programmes Table 3. Rank Table for P.G. Programmes

Rank No. of No. of % of % of Rank No. of No.of % of % of Male Female Male Female Male Female Male Female studen student studen student studen student studen student ts ts ts ts ts ts ts ts I 16 50 24.24 75.76 I 5 11 31.25 68.75

II 27 39 40.91 59.09 II 7 9 43.75 56.25

III 24 42 36.36 63.64 III 1 15 6.25 93.75

Total 67 131 33.84 66.16 Total 13 35 27.08 72.92 110 ECO-CHRONICLE Table 5. Grade Distribution for U.G. The leave rules for the female students are Programmes rigid considering the security and safety of female students. Female students are Grade No. of No. of % of % of expected to be back in their hostels before Male Female Male Female 6.30 p.m whereas the male students are student student student student free upto 8.30 p.m on week days and 9.30 ts ts ts ts p.m on Saturdays and Sundays. Male >=9.0 3 16 0.15 0.84 students have more distractions such as get-together functions, going to theatres, >=8.5 88 150 4.63 7.89 having pleasure trips, visiting their friends etc. The male students are also not as >=8.0 225 336 11.83 17.67 serious as female students as far as studies are concerned; hence the >=7.0 799 846 42.03 44.50 performance of female students is much better compared to that of male students. >=6.0 1088 501 57.23 26.35 CONCLUSION >=5.0 266 46 13.99 2.41 A study has been conducted to find out the Table 6. Grade Distribution for P.G. comparative performance of female Programmes students in a technical institution. The study revealed that the performance of female Rank No. of No. of % of % of students in examinations is much better Male Female Male Female than that of the male students. The main studen student student student reasons for the poor performance of the ts ts ts ts male students are attributed to lack of >=9.0 0 0 0 0 interest, carelessness, distractions and higher degree of freedom. However, >=8.5 3 9 1.7 3.5 performance of students in examination is only one of the indicators of their knowledge >=8.0 13 60 7.2 23.0 level. Male students excel in co-curricular, extracurricular competitions, competitive >=7.0 65 128 36.0 50.0 examinations and take up innovative projects. Educational institutions and faculty >=6.0 77 53 43.0 21.0 members must take initiatives to develop >=5.0 23 6 13.0 2.3 this potential of students.

Reasons for Better Performance of ACKNOWLEDGEMENT Female Students: Many reasons can be attributed for the better The authors express their gratitude to the performance of the female students. Male Chancellor Dr.Paul Dhinakaran, Vice- students have more freedom in Indian System compared to that of female Chancellor Dr.Paul P.Appasamy and students. In line with the tradition, even in Registrar Dr.Anne Mary Fernandez for Karunya Campus, male students have granting permission to use the data relatively more freedom than their pertaining to Karunya University for the study. counterparts.