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Chemometric tool to study the mechanism of arsenic contamination in groundwater of Puducherry region, South East coast of India
Accepted Manuscript Chemometric Tool to Study the Mechanism of Arsenic Contamination in Groundwater of Puducherry Region, South East Coast of India
M. Sridharan, D. Senthil Nathan PII:
S0045-6535(18)30932-9
DOI:
10.1016/j.chemosphere.2018.05.083
Reference:
CHEM 21415
To appear in:
Chemosphere
Received Date:
07 March 2018
Accepted Date:
14 May 2018
Please cite this article as: M. Sridharan, D. Senthil Nathan, Chemometric Tool to Study the Mechanism of Arsenic Contamination in Groundwater of Puducherry Region, South East Coast of India, Chemosphere (2018), doi: 10.1016/j.chemosphere.2018.05.083
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ACCEPTED MANUSCRIPT 1
Chemometric Tool to Study the Mechanism of Arsenic Contamination in Groundwater of Puducherry Region,
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South East Coast of India
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M. Sridharan1*, D. Senthil Nathan2
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1*Research
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Scholar, Department of Earth Sciences, Pondicherry University, Puducherry-605014
2Professor,
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Department of Earth Sciences, Pondicherry University, Puducherry-605014
*Corresponding
Author. Mail ID: [email protected] Ph.No:9790003360
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Abstract
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aquifers of the Puducherry region were collected and analyzed for major ions and trace metals. The concentration of As
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in groundwater of study area ranges from not detectable — 28.88 µg/L during the post-monsoon and not detectable —
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36.88 µg/L in the pre-monsoon. The desirable limit for As in groundwater is 10µg/L as per World Health Organization
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and Bureau of Indian standard. About 13.64 and 11.50% of groundwater samples shows arsenic concentration higher
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than recommended limit. Hydrochemical facies which dominate during pre and post monsoon are Na-K-Cl-SO4, Ca-Cl
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and Ca-Mg-Cl-SO4type and Na-K-Cl-SO4, mixedCa-Na-HCO3, Ca-HCO3 and mixed Ca-Mg-Cl type respectively. The
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Gibbs diagram suggested that rock-water interaction is major process controlling hydrochemistry of groundwater. From
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the Pourbaix diagram, it is inferred that H3AsO3 is the principal As species in groundwater. The PHREEQC modelling
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indicates supersaturation of ferric oxides and hydroxide mineral phases in aquifer system which on reductive dissolution
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releases arsenic into groundwater. Statistical analysis (Spearman Correlation and Principal Component Analysis) showed
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that reductive dissolution of As-bearing minerals and Fe-oxyhydroxides in the presence of organic matter is the major
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process contributing arsenic into groundwater. The relationship between As, K+ and HCO-3 indicates agricultural and
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competitive exchange process which is an additional contributor of arsenic in groundwater. The sources which act as a
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sink and responsible for the release of As into the groundwater are marine sediments enriched in As and Fe-bearing
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minerals and organic matter.
To understand occurrence, distribution and source of arsenic, 175 groundwater samples from coastal
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Key Words: Groundwater, Arsenic, Hydrochemical, Puducherry, India, PHREEQC, Reductive Dissolution
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1.
Introduction
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Arsenic is a subtle and pervasive metalloid which can form both organic and inorganic compounds. It usually
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exists in -3, 0, +3 and +5 valence states, of which As (III) and As (V) are inorganic forms and, As (0) and As (-3) do not
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exist in nature. Arsenic is found to be widely distributed in the environment such as air, water, soil, rocks, plants and
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animals. Natural geogenic sources are found to be a major sponsor of arsenic in groundwater system (Gómez et al,
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2006). It is released into our environment by the natural process like volcanic activities (Aiuppa et al, 2003), weathering
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of rock materials, forest fires, geothermal processes, etc. (Sracek et al, 2004). In addition, As is also released into our
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natural system by anthropogenic activities like farming (insecticides and herbicides), mining, use of fossil fuels, pulp and
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paper production, cement manufacturing, paint industry, wood preservatives, glass manufacture, electronics, catalysts,
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alloys, feed additives and veterinary chemicals (Pfeifer et al, 2004). The behaviour of arsenic in a natural system is found
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to be most enigmatic due to its chemical characteristics like reactivity, toxicity (Mukherjee et al, 2008); its switching
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property (readily switching over to different valence states) etc.
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The factors responsible for release of arsenic into the groundwater are pH; presence of organic matter in
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sediments (like peat, lignite and plant debris)( Hinkle & Polette et al, 1999); water table fluctuation (Rodrı́guez et al,
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2004); water saturation of sediments, limited supply of sulphur and microbial activities (Matisoff et al 1982; Chapelle,
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2000; Lovely, 1997); groundwater flow direction, age of groundwater and topography (Fendorf et al, 2010) and Marine
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transgression (Berg et al, 2001; Trafford et al, 1996). There are three major mechanisms which causes release of arsenic
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into groundwater. They are 1. Oxidation and dissolution of As and Fe bearing minerals (Smedley et al, 2002; McArthur
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et al, 2001; Welch et al, 2000) 2. Weathering and reductive dissolution of As bearing primary and secondary minerals in
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the presence of natural organic matter (NOM) (Berg et al, 2001). 3. Combination of both oxidative and reductive
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dissolution of arsenic-bearing iron oxides and oxyhydroxides (Nickson et al, 1998; Kinniburgh et al, 2001; McArthur et
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al, 2001). 4. Competitive exchange of As by other compatible ions such as nitrate, phosphate (Acharyya et al, 1999) and
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bicarbonate (Nickson et al, 2000; McArthur et al, 2001).
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Higher concentration of arsenic in groundwater is proved to be a serious threat to human health, plants and
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animals. Its toxicity and mobility vary with respect to its valence state and chemical form. The treatment process of
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arsenic contaminated groundwater is also very complex. Considering the above factors, World Health Organization
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(WHO, 2011) recommended the permissible limit for arsenic as 0.01mg/L. Whereas in India, Bureau of Indian Standards
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(BIS, 2012) sets a desirable limit for As in drinking water as 0.01mg/L and when there is no any other source for
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drinking water its concentration is recommended up to 0.05mg/L.
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Throughout the world, consumption of arsenic contaminated groundwater have caused serious health issues like
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skin, lung, kidney and bladder cancer; coronary heart disease; bronchiectasis; hyperkeratosis; arsenicosis;
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hyperpigmentation of the palm and sole; hypertension; myocardial damage; liver damage; Bowens disease; diabetes, etc.
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(Moore, 1991; Lalwani et al, 2004; Hopenhayn et al, 2006). Agricultural activities carried out in As contaminated soil
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and water may cause severe poisonous effects on plants and trees (Wagner et al, 2005). The analogous behaviour of As
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and PO2-4 (an essential nutrient for plants) in a plant-soil system cannot be endured by plants as it is phototoxic. It also
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leads to reduced plant growth, root damage and less yield (Bhumbla et al, 1994). Since rice cultivation needs stagnated
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water for its growth, agricultural land is under reducing condition for a prolonged time. It leads to accumulation of
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virulent arsenic into the soil and later to groundwater (Wagner et al, 2005; Bhumbla et al, 1994).
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Arsenic contamination in groundwater from natural sources and associated health issues have been reported in
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many countries viz. Bangladesh, India, Argentina, Chile, China, Hungary, Mexico, Vietnam, Taiwan, Romania, USA,
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Canada (Ontario), New Zealand, Poland, Alaska, Spain and Japan (Sracek et al, 2004; Mukherjee et al, 2006; FPTC,
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2004). Countries in which groundwater is contaminated by arsenic from anthropogenic sources are Thailand, India
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(Madhya Pradesh), Australia, Greece, Ghana, Rhodesia, Scotland, Sweden, England, Germany (Mandal et al, 2002 and
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Subrahmanyam et al, 2001).
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In India arsenic contamination in groundwater is first reported in Chandigarh (Datta et al, 1976) followed by
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states like West Bengal, Bihar, Uttar Pradesh, Jharkhand, Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram,
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Nagaland, Sikkim, Tripura, Punjab, Himachal Pradesh, Chhattisgarh and Andhra Pradesh (Mukherjee et al, 2006). Large
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numbers of people belonging to the above states i.e. Ganga-Brahmaputra basin are affected by diseases like skin itching,
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burning and watering of eyes, weight loss, loss of appetite, weakness, lethargy and fatigue, chronic respiratory and
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gastro-intestinal problems, anemia, conjuctival congestion, etc. (Ghosh et al, 2009). There are several natural sources
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responsible for arsenic release into groundwater along Ganga-Brahmaputra basin such as Holocene sediments,
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Gondwana coal seams, mica belt, pyrite bearing shale, Son valley gold belt (Bhattacharya et al. 2006). Industries
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manufacturing veterinary drugs, pesticides and other chemicals are found to be the major anthropogenic sources of
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arsenic contamination in groundwater in India (Mandal et al. 2002 and Subrahmanyam et al. 2001). Oxidation of pyrite
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and arsenopyrite; reductive dissolution of arsenic from soils and competitive exchange of ions are the major cause for
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mobilization of arsenic into groundwater of Ganga-Brahmaputra basin (Bose et al, 2002).
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The Puducherry region is a sedimentary terrain composed of marine sediments, alluvium, laterites, thin seams of
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peat and lignite whose age ranges from Cretaceous to Recent. Over-pumping of groundwater, the rapid growth of
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industries, urbanizations, increase in population and lack of baseline information for arsenic in the Puducherry region
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have prompted this study. Switching property and toxic nature of arsenic; it's occurrence in wide pH range; intricate
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treatment process; lack of its own isotope and technique to find exact source urged us for the current investigation. The
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main objective of this research paper is to discern the spatial and temporal distribution of arsenic, its occurrence, source
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and mechanism of release into groundwater of the Puducherry region with the aid of Chemometric tool.
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2.
Study Area
2.1 Location Puducherry is located along the Coromandel coast of India, whose latitude and longitude are 11º45'; 12º03' N
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and 79º37'; 79º37' E respectively. The study area exists as enclaves within the state of Tamil Nadu in India (Fig. 1).
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2.2 Climate
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Puducherry receives its maximum rainfall during North-East monsoon i.e. during the months of October,
99
November and December. It experiences relatively hot and humid tropical climate conditions. During the month of
100
April, May and earlier part of June, study area experiences hot climate (CGWB, 2013). The average annual rainfall of the
101
study area is 1272mm.
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2.3 Drainage
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There are two major ephemeral rivers that run across the study area namely River Gingee (also known as
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Sankarabarani and Varahanadi) and River Ponnaiyar (Fig. 1). River Gingee flows diagonally in the study area in NW-SE
105
direction. River Ponnaiyar drains along the southern boundary of the study area. Apart from these, there are several
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major and minor tanks that serve as the surface water sources for basic needs of the study area. Among all those, the
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Lake Ousteri (which lies along the bank of River Gingee) and the Lake Bahoore are the major tanks (CGWB, 2013).
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2.4 Geology and Geomorphology
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The study area is composed of sedimentary rocks whose age ranges from Cretaceous to Recent with Archaean
110
basement and the sedimentary sequences encountered here are of marine and fluvial origin. The Archaean rocks are
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charnockite and biotite-hornblende gneiss. The Cretaceous group of rocks exposed along the northern part of study area
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is composed of shelly limestone, sandstone, silt and clay which are named as Ramanathapuram, Vanur sandstone, Ottai
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clay and Turuvai limestone Formations. The Turuvai limestone, the uppermost Cretaceous Formation, is unconformably
114
overlain by the Tertiary group of rocks which include formations such as Kadaperikuppam and Manaveli of Paleocene
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Table 1 Stratigraphic Succession of the Study Area. (CGWB, 2013) Era Quaternary
Period Recent
Formations Alluvium, laterite
Lithology Sand, clay, silts, kankar, gravels and laterite Mio-Pliocene Cuddalore Formation Pebbly& gravely& coarse grained sandstones with minor clays & siltstones with thin seams of lignite ---------------------------------------Unconformity-------------------------------------------------------------Tertiary Paleocene Manaveli Formation Yellow & yellowish brown, grey calcareous siltstone and claystones & shale with thin bands of limestone Kadaperikuppam Yellowish white to dirty white sand. Formation Hard fossiliferous limestone, calcareous sandstone and clays ---------------------------------------Unconformity-------------------------------------------------------------Turuvai Formation Highly fossiliferous limestone, Mesozoic Upper Cretaceous conglomerate at places, calcareous sandstone and clays Ottai Claystone Grey to greyish green claystones, silts with thin band of sandy limestone and fine grained calcareous sandstone Lower Cretaceous Vanur Sandstone Quartzite sandstone, hard coarse grained, occasionally feldspathic or calcareous with minor clays Ramanathapuram Black carbonaceous silty clays and Formation fine to medium grained sands with bands of lignite and medium to coarse grained sandstone ---------------------------------------Unconformity-------------------------------------------------------------Archean Eastern Ghat Complex Charnockite and Biotite hornblende gneisses
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period; Cuddalore formation of Mio-Pliocene age. Palaeocene formations are characterized by clay, shale, claystone,
117
siltstone and calcareous sandstone whereas Mio-Pliocene formation is composed of ferruginous sandstone. The recent
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formation of the Quaternary period is composed of laterites, alluvium, coastal sands and clay. Bands of lignite and peat
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are found in Cuddalore and Alluvium formations of study area respectively (CGWB, 2013; Fig. 2; Table. 1).
120
Geomorphologically, the study area is classified as uplands, alluvium and coastal plains. Uplands are found
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along the north-western part of the study area with an average elevation of 15m with gullies and ravines. Alluvium
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occurs in the southern part of the study area. Coastal plains are found along the eastern part of the study area with land
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features like spits, cusp, bars, lagoons, wave-cut platform, sand dunes, etc. (CGWB, 2013).
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2.5 Hydrogeology
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The two major groups of rocks occurring in the study area are 1) Fissured and Fractured Crystalline Formations
127
and 2) Porous Sedimentary Formations (CGWB, 2013). The weathered portion and fissured-fractured zone occur under
128
phreatic and semi-confined conditions. The porous formations cover the almost entire region of the study area. They are
129
characterized by the semi-consolidated formations of Cretaceous and Tertiary and unconsolidated Quaternary formations
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of Recent age. Amidst of all the porous sedimentary aquifers, the Vanur and Ramanathapuram Sandstone (Cretaceous)
131
and the Cuddalore sandstone (Tertiary) aquifers and the shallow alluvial (Quaternary) aquifers are the three major
132
potential aquifer systems in this region. Groundwater occurs in these formations in both unconfined and confined
133
conditions.
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Fig.1 Study Area and Sample Location Map
136 137
Fig.2 Geological Map of the Study Area
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3. Materials and Methods
139
3.1 Groundwater Sampling
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About 175 groundwater samples from bore wells have been collected covering all the litho-units of the study
141
area, during the pre (PRM) i.e. August, 2014 and post monsoon (POM) i.e. January, 2015 as per the standard procedures
142
of APHA, 2005 (Fig. 1). Prior to sampling, bore wells were pumped for 15-20 minutes so as to avoid the sampling of
143
stagnant water in the pipe, which may lead to misinterpretation. Teflon containers were used for sampling to avoid
144
leaching from walls of the container. Before sampling, containers were washed using nitric acid followed by deionized
145
water and finally by the groundwater that has to be sampled. A set of each sample was collected, out of which one
146
sample is acidified and filtered for trace metal analysis and the other is used for major ion analysis. Acidification of
147
water samples was done by adding HNO3 by lowering the pH to 2, in order to withhold the metals in its ionic state by
148
inhibiting the formation of compounds and complexes.
149
3.2 Groundwater Sample Analysis
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In-situ parameters such as pH, Eh, Total Dissolved Solids (TDS) and Conductivity (EC) were analyzed in the
151
field itself. Collected water samples were then analyzed for major ions such as Na+ (Sodium), K+ (Potassium), Ca2+
152
(Calcium), Mg2+ (Magnesium), SO42- (Sulphate), HCO3- (Bicarbonate), NO3- (Nitrate) and Cl- (Chloride). Acidified water
153
samples were analyzed for metals and metalloids such as As, Fe, Sc, Ti, V, Ni, Cu, Pb, Zn, Mo, Sn, W, Pb and U.
154
pH, Eh, EC and TDS were analyzed using Hanna portable water analyzer. Major ions such as Na+, K+, Ca2+,
155
Mg2+, SO42-, NO3-, Cl- and total iron using Ion Chromatography (ICS DIONEX 1100); bicarbonate using Volumetric
156
Titration method (sulphuric acid method). As, Fe, Sc, Ti, V, Ni, Cu, Pb, Zn, Mo, Sn, W, Pb and U in groundwater
157
samples were determined by using Thermo Scientific XSERIES 2 Quadrupole Inductively Coupled Plasma Mass
158
Spectrometer (Total Arsenic concentration were measured by Collision Cell Technology method).
159 160
Spatial distribution maps were prepared using ArcGIS10.3. Mineral saturation indices were calculated using the software PHREEQC Interactive 2.8. Statistical analysis was done by using IBM SPSS statistical V20 tool.
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Table 2a Analytical and Statistical results of Water Samples Collected in Post Monsoon
165
Parameters
Minimum
Maximum
Mean
SD
166
pH
6.09
7.45
5.88
7.48
Eh
-58.00
16.00
-32.65
16.83
167
EC
110.00
3980
1143.48
557.58
168
TDS
26.24
2320.00
641.94
313.79
169
Na+
120.55
5201.24
529.88
590.43
K+
ND
417.67
64.12
73.1
171
Ca2+
63.02
1683.65
234.47
181.97
Mg2+
7.85
524.18
78.21
59.66
172
Cl-
35.46
23511.90
1027.53
2513.67
173
SO2-4
ND
4144.55
390.68
522.81
HCO-
ND
317.20
49.49
35.93
NO-3
2.45
87.87
15.60
15.04
175
Sc
1.76
12.48
7.02
2.24
176
Ti
1.96
21.02
6.15
3.10
V
.41
94.74
14.04
15.19
Ni
ND
8.93
2.04
1.57
178
Cu
ND
24.17
4.13
4.29
179
Zn
ND
3254.00
91.54
398.63
180
As
ND
28.88
4.21
4.69
Mo
ND
7.26
.93
1.29
Sn
ND
259.00
11.11
42.82
Cd
ND
.83
.13
.11
Ba
ND
948.40
180.40
169.84
W
ND
.1
.01
.02
Pb
ND
44.86
1.69
5.25
U
ND
17.57
3.40
3.87
Fe
ND
9175
998.67
1197.80
170
174
177
3
181
Concentration of Na, K, Ca, Mg, Cl, So4, HCO3 in mg/L; Sc, Ti, V, Ni, Cu, Zn, As, Mo,
182
Sn, Cd, Ba, W, Pb, U, Fe in µg/L; TDS-mg/L; EC- (µS/cm)
183
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Table 2b Analytical and Statistical results of Water Samples Collected in Pre Monsoon Pre Monsoon Parameters
Minimum
Maximum
Mean
SD
pH
5.99
8.56
7.03
.34
Eh
-115.00
-1.00
-35.59
15.90
EC
341.00
3080.00
1187.26
501.18
TDS
173.00
6380.00
646.95
668.34
Na+
26.20
3588.04
347.90
398.71
K+
ND
353.71
49.18
46.79
Ca2+
ND
881.54
159.84
110.22
Mg2+
7.77
719.19
76.01
95.38
Cl-
8.72
4707.13
360.52
579.67
SO2-4
ND
948.63
214.65
302.69
HCO-3
ND
902.80
343.14
254.18
NO-3
ND
70.00
14.85
16.04
Sc
1.88
26.52
7.6
3.23
Ti
1.57
97.36
7.47
10.63
V
.74
48.69
14.13
12.50
Ni
ND
27.94
3.17
3.90
Cu
ND
100.90
4.89
12.41
Zn
ND
4392.00
142.68
547.55
As
ND
36.88
4.63
5.33
Mo
ND
6.71
1.28
1.33
Sn
ND
30.52
.30
3.32
Cd
ND
142.70
1.89
15.37
Ba
ND
530.40
170.51
144.01
W
ND
2.32
.06
.23
Pb
ND
23.36
1.06
2.87
U
ND
13.90
3.41
3.37
Fe
ND
2378.00
545.10
577.88
185
Concentration of Na, K, Ca, Mg, Cl, So4, HCO3 in mg/L; Sc, Ti, V, Ni, Cu, Zn, As, Mo,
186
Sn, Cd, Ba, W, Pb, U, Fe in µg/L; TDS-mg/L; EC- (µS/cm)
187
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4.
Results and Discussion
4.1 Physico-Chemical Parameters of Groundwater
190
The analytical and statistical results of groundwater samples collected from the study area during Post (POM)
191
and Pre-monsoon (PRM) are shown in table 2a and 2b respectively. The concentration of the major anions during post
192
and pre-monsoon are, Anion: Cl- >SO42- > HCO3- >NO3- and Cl- > HCO3- >SO42- >NO3- respectively. The concentration
193
of the major cations in both the seasons is same as follows: Na+ >Ca2+> Mg2+> K+. The pH of the samples in the study
194
area ranges from 6.09-7.45 and 5.99-8.56 during post and pre-monsoon respectively of which majority of samples
195
exhibits near neutral pH condition. However, the locations with lower pH signify intense mineral dissolution process.
196
Electrical Conductivity ranges from 110-3980(µS/Cm) in post monsoon and 341-3080 (µS/Cm) in the pre-monsoon.
197
TDS varies from 26.24-2320 mg/L in POM and 173-6380 mg/L in PRM. Very high pH, conductivity and total
198
dissolved solids are attributed to seawater intrusion, improper sewage disposal and agricultural activities (Sarath
199
Prasanth et al. 2012; Ramesh et al. 2012; Sridharan et al, 2017a). The mean concentration of major ions viz. Na+, K+,
200
Ca2+, Mg2+, SO42-, NO3-, Cl- were higher during POM when compared to PRM due to infiltration; dissolution of
201
minerals and soluble salts and leaching. In summer the water table decreases, during which oxidation of aquifer
202
materials takes place. Due to oxidation, the precipitation of soluble salts occurs. These soluble salts are then dissolved
203
and flushed into aqueous media during the monsoon. This process causes the enrichment of ions and other dissolved
204
solids in groundwater. But with respect to time-lapse and continuous supply or infiltration of rainwater, dilution occurs
205
thereby reducing the concentration of ions (Rodrı́guez et al, 2004; Giménez –Forcada, 2010).
206
The
abundance
of
Trace
metals
during
POM
displays
the
following
order
following
order
207
Fe>Zn>Ba>Sn>V>Pb>As>Cu>U>Ti>Sc>Ni>Mo>Cd>W,
208
Fe>Ba>Zn>V>Sc>Ti>Cu>As>U>Mo>Pb>Sn>W. Iron is the most abundant trace metal occurring in the study area
209
whose concentration varies from ND-9175µg/L and ND-2378µg/L during POM and PRM respectively. Higher
210
concentration of dissolved iron in groundwater indicates the reducing environment; the presence of iron-bearing
211
minerals and sediments of marine origin (Hunt et al, 1994). In the study area, the minimum and maximum
212
concentration of arsenic during POM is ND and 28.88µg/L respectively. While in PRM concentration of arsenic varies
213
from ND-36.88µg/L. About 13.64% of samples in PRM and 11.50% samples in POM show concentration of arsenic
214
higher than World Health Organization (WHO, 2011) and Bureau of Indian standard (BIS, 2012) limit i.e. 10 µg/L in
11
whereas
PRM
shows
the
ACCEPTED MANUSCRIPT 215
groundwater of the study area. The spatial distribution map of arsenic is shown in the figure.3a and 3b.
216 217 218
Fig3a & b Spatial Distribution Map of Arsenic in Study Area 4.2 Piper Diagram
219
The Piper diagram is a pictorial representation of ions which integrates major cations and anion in groundwater on a
220
trilinear plot to discern different hydrochemical facies (Bahar et al, 2010; Fig.4). In the present study, it is recognized
221
that the most influencing hydrochemical facies of groundwater during the pre-monsoon is Na-Cl type followed by Ca-Cl
222
type and Ca-Mg-Cl type (Fig. 4). Whereas in post-monsoon the major controlling hydrochemical facies is Na- Cl type
223
followed by mixed Ca-Na-HCO3 type, Ca-HCO3 type and mixed Ca-Cl type (Fig. 4).
224
The facies enriched in Na+, HCO-3 and Cl- expresses that seawater and tidal channel plays a considerable performance
225
along the coastal tract. The freshwater-seawater interaction along the coastal aquifers causes replacement of Ca2+ in
226
groundwater by Na+ from seawater, by the action of an ion-exchange process (Bahar et al, 2010; Sridharan et al, 2017b).
227
Ca-Cl-HCO3 group of water signifies that there was not effective recharge process which led to increasing the
228
concentration of Cl- and Na+ by evaporation process (Lakshmanan, et al, 2003). Recharge of groundwater by rainfall and
229
corresponding low EC values led to the formation of Ca-HCO3 facies (Lakshmanan, et al, 2003). Rainwater along with
230
dissolved CO2 in the atmosphere becomes acidic. When such acidic rainwater oozes into the subsurface it dissolves
231
carbonate minerals leading to enrichment of Ca- HCO3 type of water (Adams et al, 2001). Mixed Ca-Na-HCO3 type of
12
ACCEPTED MANUSCRIPT 232
facies depicts rock-water interaction process, which involves the dissolution of carbonates and feldspars by the
233
recharging groundwater (Adams et al, 2001). Facies enriched in SO2-4 are due to dissolution of minerals like gypsum.
234 235 236
Fig. 4 Piper Diagram 4.3 Gibb’s Diagram to Understand Mechanism of Groundwater Quality:
237
Based on the ratio of major cations and anions with respect to TDS in groundwater samples, Gibbs designed a
238
plot which includes 3 major domains. They are 1. Rock-Water Dominance, 2.Evaporation and 3.Precipitation dominance
239
(Gibbs et al, 1970; Marghade et al, 2015). In the study area, a majority of water samples falls under the Rock-Water
240
domain which signifies that geochemical process such as precipitation-dissolution; oxidation-reduction and ion exchange
241
are the dominant governing factor of groundwater chemistry in both the seasons (Fig. 5a, b). A few numbers of samples
242
fall under the evaporation domain signifying climatic control over groundwater chemistry. It also emphasizes that by the
243
mechanism of evaporation, the water and moisture components of groundwater are precipitated and deposit as
13
ACCEPTED MANUSCRIPT 244
evaporites. Further, these evaporites percolate into the groundwater saturated zone and eventually increase the salinity
245
and total dissolved solids of groundwater (Chebbah et al, 2015; Dehnavi et al, 2011).
246 247
Fig.5a & b Gibbs plot to understand hydrochemical process of study area.
248 249 14
ACCEPTED MANUSCRIPT 250
4.4 Mineral Saturation Indices
251
From Gibbs Diagram it is concluded that rock-water interaction is the major process governing the groundwater
252
chemistry of study area (fig.5a and b). During such interaction, rocks comprising the minerals rich in trace/heavy metals
253
may be desorbed and transported, leading to contamination of groundwater (Deutsch et al, 1997). Hence using chemical
254
composition of groundwater samples analyzed, mineral phases saturated can be visualized by using a geochemical
255
modelling technique called PHREEQC. A saturation index of the mineral phases is the logarithmic ratio of ionic activity
256
product and solubility product. It can be calculated by following the expression.
257 258
SI = Log (IAP/Ksp) Where, SI is Saturation Indices; IAP is Ionic Activity Product, and Ksp is Solubility Product
259
Mineral phases, in equilibrium with the solution, if SI is equal to 0; undersaturated, if SI <0 and supersaturated,
260
if SI >0. Using this approach it is possible to predict the reactive mineral phases present in the aquifer from the
261
groundwater data without collection of any solid samples. It can be validated by analyzing the aquifer solid samples
262
(Deutsch et al, 1997; Merkel et al, 2005).
263
Table.3a Saturation Indices of different mineral phases in PRM Pre-Monsoon
264
Mineral Phases
Mean SI
Max SI
Min SI
Anglesite
-1.86
2.24
-3
Anhydrite
2.08
7
-0.39
Barite
2.07
3.87
-8.96
Cd(OH)2
-8.15
-5.07
-11.36
CdSO4
-8.95
10.88
-12.1
Fe(OH)3a
2.97
8.79
-3.14
Goethite
7.79
9.64
-3.82
Gypsum
0.45
2.09
-4.26
Halite
-1.32
19.59
-4.8
Hematite
41.58
20.98
-5.13
Jarosite-K
3.96
8.09
-6.31
Melanterite
-3.96
5.1
-6.34
Pb(OH)2
-1.85
0.39
-3.68
Zn(OH)2 e
-2.92
-0.83
-5.41
*SI – Saturation Indices; PRM- Pre-monsoon
15
ACCEPTED MANUSCRIPT 265
Table.3b Saturation Indices of different mineral phases in POM Pre-Monsoon Mineral Phases
266
Mean SI
Max SI
Min SI
Anglesite
-1.80
-0.19
-3.42
Anhydrite
2.19
9.6
0.33
Barite
2.90
4.2
-1.01
Cd(OH)2
-8.74
-7.11
-11.28
CdSO4
-10.77
-9.82
-12.37
Fe(OH)3a
2.81
3.99
-0.74
Goethite
19.27
19.35
-2.66
Gypsum
1.19
3.58
-2.73
Halite
-2.56
0.94
-3.88
Hematite
19.48
21.81
12.35
Jarosite-K
6.10
10.55
-4.2
Melanterite
-3.90
-1.72
-7.19
Pb(OH)2
-1.96
0.75
-4.52
Zn(OH)2 e
-3.32
4.07
-5.16
*SI – Saturation Indices; POM- Post-monsoon
267
PHREEQC hydrochemical modelling technique done over the samples collected during PRM and POM
268
indicates that the mineral phases viz. Anglesite, halite, melanterite, Pb and Zn hydroxides were undersaturated in
269
solution with regards to solid phases (Table.3a and b). It implies that these minerals were absent in the aquifer materials
270
or unreactive or less residence time of groundwater in the aquifer. However, mineral phases like anhydrite, barite,
271
ferrihydrite, goethite, gypsum, hematite and jarosite-K are found to be supersaturated. From supersaturation and
272
subsequent precipitation of those mineral phases, it is inferred that these group of minerals acts as a sink for dissolved
273
iron in groundwater (Agrawal et al, 2011). In addition, presence and supersaturation of ferric oxides and hydroxides
274
propose that they offer the potential site for As adsorption (Sappa et al, 2014; Fuller et al, 1993). Precipitation of the
275
above minerals may lead to desorption of As from Fe bearing minerals (Mukherjee et al, 2008). Under reducing
276
condition prevailing in the case of study area, arsenic sorbed over those mineral phases get desorbed and enter into the
277
aquifer system (Dzombak et al, 1990), as in the case of the study area.
278 279
16
ACCEPTED MANUSCRIPT 280
4.5 Statistical Analysis
281
4.5.1 Correlation of Arsenic with other Major Ions and Trace Metals
282
Bivariate Spearman correlation, a statistical tool was used to understand the relationship between arsenic and
283
other variables. Based on Spearman analysis, it is inferred that there exists strong positive correlation between As and Fe
284
(rPRM = 0.778; rPOM = 0.513); moderate correlation between As and HCO3 (rPOM = 0.363), Mo(rPOM = 0.349),
285
Ti(rPOM = 0.223), V(rPOM = 0.309); weak correlation between As and K+(rPRM = 0.225) (Fig. 7c), Sc(rPOM = 0.242),
286
Pb(rPRM = -0.247), U(rPRM = -0.243) (Table. 4a, b and 5a, b).
287
The strong to moderate correlation of TDS and EC with other major ion of groundwater such as Na+, K+, Ca2+,
288
Mg2+, SO42-, NO3-, Cl- both in pre and and the implies that the major processes governing groundwater chemistry of study
289
area are seawater intrusion (TDS, EC, Na+, K+, Ca2+, Mg2+, Cl-), ion exchange (Na+, K+ and Ca2+, Mg2+)(Sridharan et al,
290
2017b) and other anthropogenic activities like application of fertilizers (K+, SO42-, NO3-), sewage disposal (NO3-) and
291
industrial effluents (Narany et al, 2014; Table. 4a, b and 5a, b). The strong correlation between Ca2+ and Mg2+ indicates
292
dissolution of Calcite and Dolomite or silicate weathering (Narany et al, 2014). Weak correlation of K+ with other major
293
ions like Na+ and Ca2+, Mg2+ suggest that it is released into the aquifer by potassium used in agricultural land and
294
weathering of K -feldspar or K-bearing minerals (Jalali et al, 2006; Table. 4a, 4b, 5a and 5b). Higher concentration of Cl-
295
when compared to SO2-4 implies the sulfate reduction (Lakshmanan et al, 2003) (Table. 4a, 4b, 5a and 5b).
296
The negative correlation between arsenic and Eh (redox potential) and higher concentration of Fe in
297
groundwater samples of the study area indicates the redox condition of the aquifer (Shrestha et al, 2016; Table. 4a and
298
4b).
299
The excess concentration of Fe and As indicates, the presence of Fe and As bearing minerals in the study area.
300
The authors viz. Reddy et al, 2007 and Nathan et al, 2012 have reported the presence of iron and arsenic bearing
301
minerals (like arsenolite, claudetite, kamacite, pyrite, realgar, marcasite, etc.) in the study area. Reductive dissolution of
302
those minerals are attributed to the release of As and Fe into groundwater simultaneously (Pfeifer et al, 2004; Oinam et
303
al, 2011). It can also be inferred from the strong relationship between Fe and As in groundwater samples collected during
304
pre-monsoon (rPRM=0.778) and post (rPOM =0.513) monsoon of the study area.
305
During the pre-monsoon, there is more extraction of groundwater which leads to a reduction in groundwater
306
level. Lowering of water table causes oxidation of organic deposits (peat, lignite, agricultural wastes and marine
17
ACCEPTED MANUSCRIPT 307
sediments) in the subsurface. These organic deposits which were formerly saturated with water are currently exposed to
308
oxygen which leads to oxidation and downward movement of leachates creating anoxic condition within the aquifers. It
309
enhances reductive dissolution of As-bearing minerals and As sorbed Fe-oxyhydroxides. As a consequence of above
310
process Fe and As is released.
311
During POM there exist a moderate relationship between As and bicarbonate, under neutral pH and negative
312
Eh (reducing condition) (fig. 6d; table. 4a and 4b) indicates the role of microbial activity in reductive dissolution process.
313
Besides, if there exists a positive correlation between As and HCO-3 then it is inferred that arsenic is released by
314
reduction of Fe-oxyhydroxides (Nickson et al, 2000; Mcarthur et al, 2001). If this process acts as a dominant controlling
315
factor of arsenic concentration in groundwater, then there should exist, a strong correlation between Fe and bicarbonate
316
ions (Mcarthur et al, 2001). If it is not so, then there might be some other mechanism responsible for As release viz. near
317
neutral pH and reducing condition (Choprapawon and Rodcline 1997; Chowdhury et al. 2000; Ramanathan et al. 2007),
318
calcite dissolution and weathering of biotite and feldspar (Katsoyiannis et al, 2006; Nickson et al.(1998; 2000)),
319
carbonation of arsenic sulphide minerals (Kim et al. ; 2000 and Anawar et al. ;2004). Near neutral to alkaline pH
320
condition prevailing in some part of the study area, desorbs As from Fe-hydroxides by OH- ions and it also inhibits re-
321
adsorption of As onto Fe-hydroxides (Fig. 6a). It might have caused the mobilization of arsenic into the aqueous phase to
322
some extent (Kondo et al. 1999; Bhattacharya et al. 2006; Ahn et al, 2011; Zkeri et al, 2015). Also, the concentration of
323
arsenic and iron does not completely correlate with each other in all the samples which mean that there exists an
324
additional source of iron in the study area. Iron may also be released from siderite, vivianite or hydroxycarbonates or
325
other oxides (Mcarthur et al, 2001).
326
Also, there occurs positive correlation among trace metals viz. As, V, Ti, Sc, Ni, Cd, Sn during pre and post-
327
monsoon of the study area (Table. 4a and 4b). These metals are found to be enriched in argillaceous sedimentary rocks,
328
iron stones, phosphatic shales, laterites and ash deposits of peat, coal and crude oil (Schwartz et al, 1980). The presence
329
of biodegradable organic matter was accountable for reduction and mobilization of trace metals (Chitsazan et al, 2008;
330
Hem, 1985). Microbes and Dissolved Organic Carbon (DOC) are responsible for redox condition within the aquifer of
331
the study area were already reported by Kesari et al, 2015 and Thilagavathi et al, 2016. The organic matter which
332
includes peat and lignite deposits occurs in the northern and southern (alluvium formation) part of the study area
333
(CGWB, 2013). Apart from it, the study area includes marine sediments rich in organic content and agricultural wastes.
18
ACCEPTED MANUSCRIPT 334
Molybdenum is redox-sensitive oxyanion found in earth material. It is an essential element for metabolic
335
activities of nitrogen-fixing bacteria. Its presence and correlation with As in groundwater during POM explain about the
336
adsorption-desorption reaction (Dowling et al, 2002; Table. 4a and 4b). The mobility of Mo is favoured during reductive
337
dissolution mechanism of Fe and Mn oxides with respect to reducing conditions prevailing within the aquifer (Bennett et
338
al, 2003; Schliekeret al, 2001; Smedley et al, 2014). Also the correlation between As, V and Mo indicate they might be
339
mobilized from a single source.
340
Strong to moderate correlation among elements such as Ni, Cu, Cd, Pb and Zn implies that they are mobilized
341
from the different sources (Table. 4a and 4b). Usage of chemical fertilizers and pesticides enriched in above said metals
342
and chemical industries located in study area might be the cause of their concentration in groundwater (WHO, 2011).
343 344 345 346 347 348 349 350 351 352
19
353
Table. 4a Spearman Correlation table for Pre Monsoon pH
EC
TDS
Na
+
+
K
Ca
2+
2+
Mg
Cl
-
So
2 4
HCO3
-
NO 3
pH
1.0
Eh
-.945
1.0
EC
.089
-.067
1.0
TDS
.054
-.044
.975
1.0
.020
-.003
.401
.424
1.0
-.055
.093
.178
.196
.562
1.0
-.041
.006
.323
.339
.534
.376
1.0
-.130
.152
.276
.299
.479
.316
.796
1.0
.203
-.223
.446
.483
.224
.198
.203
.108
1.0
.214
-.227
.436
.457
.198
.150
.080
-.051
.747
1.0
.234
-.216
.376
.364
.268
.018
.186
.171
.271
.212
1.0
-.076
.100
.318
.355
.169
-.048
.285
.446
.115
.084
.088
1.0
.187
-.111
.020
.001
.075
.225
.036
-.107
-.106
-.005
.062
-.168
Na
+
+
K
Ca
2+
2+
Mg -
Cl
SO
2 4
HCO3 -
NO 3 As
354
Eh
*Values in bold indicate they have significant relationship
355 356 357 20
As
1.0
358
Table 4b Spearman Correlation table for Post Monsoon pH
EC
TDS
Na
+
+
K
Ca
2+
2+
Mg
-
Cl
So
2 4
HCO3
-
NO 3
pH
1.000
Eh
-.990
1.000
EC
.115
-.118
1.000
TDS
.188
-.177
.935
1.000
-.059
.075
.206
.222
1.000
-.100
.123
.068
.091
.436
1.000
-.170
.173
.289
.299
.252
.284
1.000
-.114
.107
.335
.319
.295
.221
.741
1.000
-.133
.158
.451
.481
.294
.317
.431
.489
1.000
-.029
.059
.488
.553
.374
.187
.237
.277
.597
1.000
.347
-.298
.165
.274
.080
.045
.117
.071
.106
.288
1.000
-.171
.164
.228
.203
-.060
.069
.211
.090
.115
.157
-.012
1.000
.186
-.153
.043
.118
.127
.115
-.018
-.118
-.113
.091
.363
.041
Na
+
+
K
Ca
2+
2+
Mg -
Cl
SO
2 4
HCO3 -
NO 3 As
359
Eh
*Values in bold indicate they have significant relationship
360 361
21
As
1.000
362
Table 5a Spearman Correlation table for Pre Monsoon (Trace elements) Sc
363
Ti
V
Ni
Cu
Zn
As
Mo
Sn
Cd
Ba
W
Pb
U
Sc
1.000
Ti
.634
1.000
V
.237
.357
1.000
Ni
.283
.278
.122
1.000
Cu
.159
.268
.175
.355
1.000
Zn
.025
-.034
.127
.146
.151
1.000
As
.001
-.081
-.006
-.020
-.139
-.004
1.000
Mo
-.125
.115
.143
.102
.044
-.008
.143
1.000
Sn
.242
.262
.024
.605
.128
.066
.064
-.038
1.000
Cd
-.023
-.165
.078
-.013
.258
.011
.010
-.101
-.085
1.000
Ba
.071
-.072
.373
.091
-.166
.185
.044
-.002
-.020
.127
1.000
W
.001
.062
-.218
.292
.172
-.005
.022
.131
.478
-.118
-.209
1.000
Pb
.103
.089
-.105
.308
.560
.310
-.247
-.129
.271
.107
-.129
.354
1.000
U
.430
.279
.647
.275
.060
.094
-.243
-.078
.108
.015
.280
-.168
.076
1.000
Fe
.002
-.119
-.134
.084
-.150
.122
.778
.129
.153
.076
.004
.134
-.101
-.284
*Values in bold indicate they have significant relationship
364 365 366 22
Fe
1.000
367
Table 5b Spearman Correlation table for Post Monsoon (Trace elements) Sc
368
Ti
V
Ni
Cu
Zn
As
Mo
Sn
Cd
Ba
W
Pb
U
Fe
Sc
1
Ti
.656
1
V
.362
.489
1
Ni
.272
.318
.397
1
Cu
.239
.231
.313
.438
1
Zn
.051
.117
.076
.357
.613
1
As
.242
.309
.309
.244
.062
.093
1
Mo
.057
.481
.455
.398
.230
.242
.349
1
Sn
-.220
-.184
-.163
-.077
.107
.013
-.303
-.169
1
Cd
.203
.292
.057
.243
.495
.390
.028
.161
.119
1
Ba
.162
.175
.369
.492
.155
.171
.179
.311
-.168
-.107
1
W
-.229
-.187
-.228
-.256
-.102
-.098
-.135
-.230
.112
-.056
-.262
1
Pb
-.143
-.106
-.208
-.234
-.124
-.090
-.234
-.203
.031
-.176
-.190
.121
1
U
.088
.067
.027
.016
.042
.006
-.069
-.242
-.087
-.002
-.038
-.093
-.052
1
Fe
.192
.102
.200
.166
.224
.025
.513
.151
-.050
.038
.207
.045
-.213
-.029
*Values in bold indicate they have significant relationship
23
1
ACCEPTED MANUSCRIPT
369 370
Fig. 6a Plot pH versus As, 6b Plot NO-3 versus As, 6c Plot K+ versus As, 6d Plot HCO-3 versus As, and 6e Plot
371
Fe versus As
24
ACCEPTED MANUSCRIPT 372
4.5.2 Principal Component Analysis
373
Principal Component or Factor Analysis was done to evaluate the compositional relationship between
374
hydrochemical parameters of water samples; factors affecting each other variables and to identify hidden
375
geochemical process, extent and source of pollution in groundwater samples. Table.6a and b depicts the PCA results
376
of both pre and post-monsoon respectively which includes loadings, Eigenvalues, the percentage of variance and
377
cumulative variance. In the present study, the data were subjected to Varimax rotation with Kaiser Normalization to
378
make complex and tedious data structure into simpler one called factor scores. And the factor scores, whose
379
Eigenvalues were greater than and equal to 1 is considered. The factor score with greater Eigenvalue is capable of
380
explaining the underlying hydrochemical process.
381
Based on the above considerations five independent factors both in pre and the post-monsoon have been
382
extracted. It explains the total variance of about 56.684 and 49.607% in pre and post-monsoon respectively (table 6a
383
and 6b).
384
In pre-monsoon, factor-1 with 13.594% variance show the highest loading of variables such as EC, TDS,
385
Na+, K+, Ca2+, Mg2+, SO42-, NO3-, Cl-, As and Fe. The strong relationship among TDS, Na+, Ca2+, Mg2+, SO42-, Cl-
386
indicate seawater ingress and ion exchange process during pre-monsoon. In addition, the negative correlation of As
387
and Fe with aforesaid variables, explains that the influence of seawater ingress in the release of As into groundwater
388
system is insignificant. Factor-2 shows a variance of 12.433% with highest loadings of parameters viz. pH, Eh, EC,
389
K+, HCO-3, V, As, Mo and Fe which clearly explains about the mechanism of As release into groundwater. Reducing
390
condition of an aquifer and presence of organic matter can be inferred from the association of Eh, Fe and V (Oinam et
391
al, 2011). Association of As and Fe indicate presence of Fe and As-bearing minerals. Moreover moderate relationship
392
of As with K+ and HCO3- indicates the role of agricultural activities and microbial reduction leading to mobility of As
393
in groundwater (Nickson et al, 2000; McArthur et al, 2001). Factor3 shows higher loadings for variables such as NO-
394
3,
395
groundwater chemistry such as lack of proper sewage system; discharge from chemical industries; usage of chemical
396
fertilizers and pesticides. Factor 4 shows a total variance of 10.337% with highest positive loadings to Ni, Sn, W and
397
Pb indicates a marshy and loamy environment; dissolution of minerals comprising those elements, alloy industries,
398
discarded batteries and diesel fuel used in farming activities and paint industries of the study area. Factor-5 with a
Sc, Ti, Cu, Cd with a total variance of 10.913%. Such association implies anthropogenic sources affecting
25
ACCEPTED MANUSCRIPT 399
total variance of 9.407% shows highest loadings to variables viz. Ba and U imply they are mostly derived from the
400
geogenic sources.
401
In post-monsoon, factor-1 accounts for 16.169% variance displays maximum loadings to major cations and
402
anions like Ca2+, Mg2+, SO42, Cl- and HCO-3. Strong correlation among major cations and anions indicates rock-water
403
interaction which acts as a dominant process governing groundwater chemistry in the study area. Correlation of Ca2+,
404
Mg2 and HCO-3 indicates dissolution of detrital calcite, detrital dolomite and ferromagnesian minerals. A high loading
405
of SO42 and Cl- implies long residence time due to sluggish groundwater flow; anthropogenic sources like sewage and
406
domestic waste (Saha et al, 2009) and secondary salinity. High Cl- concentrations are due to Cl- trapped within the
407
clay lenses thereby reducing flushing rate of the aquifer and it gradually enters the aquifer system. Factor-2 explains
408
the variance of about 9.686% and exhibits maximum loadings of variables viz. Sc, Ti, V, As, Mo and Fe. Association
409
of As, Fe, V and Mo (i.e. redox-sensitive elements) with strong to moderate loadings suggests reductive dissolution
410
of Fe hydroxides; degradation of organic matter; near neutral pH condition (Smedley et al, 2017). Factor-3 exhibits
411
variance of about 8.430% with maximum loadings of variables such as pH, EC, TDS and Ba. Higher loadings of TDS
412
and EC indicates salinization index (Liu et al, 2003) however moderate correlation of Barium implies dissolution of
413
carbonate rocks and sandstone rich in minerals like barite, witherite, barium hydroxides, etc. (Tudorache et al, 2009);
414
presence of peat, lignite and petroleum deposits in study area which might be the contributing factor (Fenelon, 1998).
415
Marine sediments of the study area are found to be the major supplier of Ba (Kontak et al, 2006; Méndez-Rodríguez
416
et al, 2013). Factor-4 exhibits total variance of about 8.112%. It shows highest negative loadings to pH, W and
417
positive loadings to Eh, K+, NO-3, Cd and U. Higher to moderate loadings of NO-3 and K+ signifies influence of
418
agricultural activities, usage of fertilizers and mineralization of groundwater with the aid of microbes. Lack of
419
sanitation and presence of a microorganism such as E. coli, Staphylococcus aureus, Proteus vulgaris, Salmonella
420
typhii, and Pseudomonas aeruginosa in the faecal matter, as reported by Saha and Kumar (2006), leads to elevated
421
concentration of nitrate in groundwater. Factor 5 accounts for total variance of 7.3% and shows maximum loadings to
422
Cu, Zn, Cd and negative loadings to Sn indicates anthropogenic sources like industrial and agricultural activities;
423
leaching from the storage tanks and/or distribution pipes (Al-Saleh et al, 1998; Brima et al, 2014).
424 425
26
ACCEPTED MANUSCRIPT 426
Table. 6a Principal Component Matrix of Pre-Monsoon after Varimax rotation with Kaiser Normalization Variables
427
Rotated Component Matrix Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
pH
-.161
.888
.026
-.138
-.003
Eh
.190
-.877
.004
.030
-.018
EC
.371
.316
.255
-.041
.279
TDS
.660
.002
.199
.047
.072
Na+
.893
.040
.031
-.013
.072
K+
.339
.327
.144
-.119
-.274
Ca2+
.917
.019
.023
-.025
.048
Mg2+
.789
-.192
.080
.016
.014
Cl-
.736
.103
.071
.032
.047
SO2- 4
.522
.266
-.091
-.032
.122
HCO-3
.279
.447
.225
.004
.267
NO-3
.016
-.164
.532
-.072
.179
Sc
.085
.037
.755
-.125
.169
Ti
.030
-.029
.930
.009
-.071
V
.226
.392
-.132
.075
.269
Ni
.098
-.015
.234
.742
-.037
Cu
-.045
.157
.859
.282
-.096
Zn
-.025
.001
.024
.098
-.126
As
-.589
.310
-.038
.068
.095
Mo
-.010
.326
-.122
.176
-.173
Sn
-.069
-.027
-.061
.954
-.031
Cd
-.022
.002
.928
.042
-.053
Ba
.094
-.028
-.223
-.103
.347
W
-.045
-.022
-.060
.934
-.060
Pb
-.118
.039
-.050
.890
-.041
U
.185
.123
-.060
-.004
.636
Fe
-.588
.364
-.051
.165
.113
Eigen Value
3.67
3.36
2.95
2.79
2.54
Variance (%)
13.59
12.43
10.91
10.35
9.41
Cumulative Variance (%)
13.59
26.02
36.93
47.28
56.68
*Values in bold indicate they have significant relationship
428 429 27
ACCEPTED MANUSCRIPT 430
Table.6b Principal Component Matrix of Post-Monsoon after Varimax rotation with Kaiser Normalization Variables
431
Rotated Component Matrix Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
pH
-.017
.089
.377
-.417
.034
Eh
-.044
-.295
-.159
.681
-.228
EC
.140
.152
.867
.043
.004
TDS
.140
.149
.904
-.083
-.013
Na+
.261
-.118
.241
.130
-.128
K+
-.009
-.300
.041
.392
.170
Ca2+
.951
.037
.049
.079
-.011
Mg2+
.923
.030
.092
.070
-.089
Cl-
.964
.027
.002
.002
-.015
SO2-4
.879
.046
.171
.020
.044
HCO-3
.848
.010
-.116
-.243
.122
NO-3
-.033
.137
.064
.691
.218
Sc
-.002
.600
-.027
.092
.232
Ti
.062
.848
-.016
.014
-.027
V
-.088
.753
.170
-.081
.167
Ni
.074
.191
.296
.281
.132
Cu
-.049
.125
.006
.026
.851
Zn
-.014
-.145
.044
-.228
.330
As
-.085
.343
-.138
-.258
.136
Mo
.169
.598
.185
-.028
-.151
Sn
-.104
-.005
-.099
-.068
-.351
Cd
-.053
.199
-.209
.397
.561
Ba
-.028
-.051
.357
-.008
.087
W
.006
-.309
.002
-.498
.105
Pb
.018
.028
-.155
-.139
-.073
U
.036
-.071
.071
.412
-.046
Fe
-.070
.603
.123
-.105
.095
Eigen Value
4.37
2.62
2.25
2.19
1.97
Variance (%)
16.17
9.67
8.34
8.11
7.30
Cumulative Variance (%)
16.17
25.86
34.20
42.31
49.61
*Values in bold indicate they have significant relationship
432 433 28
ACCEPTED MANUSCRIPT 434
4.6 Arsenic Speciation in Groundwater (Pourbaix Diagram)
435
A Pourbaix diagram is constructed to depict the relationship between pH and Eh over As species in
436
groundwater system (Hundal et al, 2007). With respect to changes in pH and Eh, the oxidation state and mobility of
437
arsenic vary. Arsenic can be mobilized under wide pH range from 6-9. However, in the case of the study area, the
438
higher concentration of arsenic (>10 µg/L) is found to occur at neutral pH range of 5.99 – 8.56 (Fig. 6a). Arsenious
439
acid is commonly found at very low pH i.e. acidic condition. Under the oxidizing condition, H2AsO-4 species is
440
known to occur at low pH whereas H2AsO4 and AsO4 occur in acidic and alkaline pH respectively. At pH less than 9,
441
neutral arsenic species H3AsO3 (As(III)) occurs both in oxidizing and reducing condition. In general, arsenate
442
(As(V)) predominates in the oxidizing environment like surface water. However, As(III) predominates under
443
reducing condition i.e. organic-rich environment (Oremland et al, 2003). When compared to As(V) the sorption
444
capacity of As(III) onto minerals like ferrihydrite and goethite is less. Thus As(III) is highly mobile and found to
445
occur in the aqueous system. In the case of the study area, dominant arsenic species is H3AsO3 indicating the
446
reducing environment (Fig. 7).
447 448
Fig.7 Eh-pH (Pourbaix) diagram for aqueous arsenic species (As-O2-H2O, 298K, 1atm)
449 29
ACCEPTED MANUSCRIPT 450
4.7 Source and Mechanism for Arsenic in Groundwater
451
Several studies carried out on arsenic contamination of groundwater on a global scale, point mainly towards
452
geogenic origin followed by anthropogenic activities. And the major geological processes responsible for such
453
contamination are 1. Water table fluctuation and consequent pyrite oxidation (and other sulfide minerals) i.e.
454
Oxidative Dissolution. 2. Competitive exchange of As with other ions like PO2-4, NO-3 and HCO3-. 3. Reductive
455
dissolution of As-bearing minerals and Fe-oxyhydroxides in the presence of organic matter.
456
If process 1 is expected to be the dominant mechanism for As release into groundwater, then there should
457
exist a positive correlation between Fe, SO42- and As. But in the case of study area there is no such relationship and
458
hence this mechanism is not considered responsible for arsenic contamination in the study area.
459
In the second concept it is stated that As in aquifer sediments are replaced by other ions like PO2-4, NO-3 via
460
application of fertilizers enriched in those ions. In addition to above activities, weathering of K+ bearing minerals
461
may also cause exchange of As in aquifer sediments. Samples collected during pre-monsoon show significantly
462
moderate correlation between K+ and As which indicates that this process plays a minor role in the study area (Fig.
463
7b). Also, exchange of As and HCO3- during the post-monsoon also play a role in the study area.
464
According to the third process, there should exist reducing condition (negative Eh); neutral pH; As-bearing
465
minerals; Fe-oxyhydroxides and organic matter. In the presence of all the above conditions in the aquifer system,
466
there occurs reductive dissolution of As-bearing minerals and Fe-oxyhydroxides. It also keeps As in mobile
467
condition. In addition to the above-said factors, the strong correlation between As and Fe depicts that reductive
468
dissolution mechanism plays a vital role in the release of As into groundwater in the study area. XRD analysis of bore
469
well sediments collected from study area shows the presence of As and Fe bearing minerals such as Pyrite, Realgar,
470
Arsenolite, Claudetite, Scorodite, Covellite, Enargite and Prosstite which was already reported by Nathan et al, 2012.
471
Borewells at northern and southern part of the study area are found to be polluted by arsenic. The higher
472
concentration of arsenic in groundwater in the northwestern part of study area might be due to the presence of marine
473
sediments rich in organic material which on dissolution released arsenic into groundwater. However, in the southern
474
part, there are alluvium, peat and lignite deposits and intense agricultural activities which act as a major contributor
475
for arsenic in groundwater. During POM the increase of water table leads to reducing condition of the aquifer which
30
ACCEPTED MANUSCRIPT 476
is responsible for the dissolution of minerals. In PRM there is a considerable decrease in concentration of arsenic due
477
to its sorption capacity over precipitated Fe-oxyhydroxides.
478
Conclusions and Recommendations
479
Studies on contamination of groundwater with respect to arsenic are done widely all over the world because
480
of its toxic effects on human health. Pre and post-monsoon groundwater samples were collected from coastal aquifers
481
of the Puducherry region and chemometric tool was used to study the status of arsenic contamination, its source and
482
mechanism controlling the release of As into groundwater. The analysis reveals that 13.64 and 11.50% of
483
groundwater samples were contaminated by arsenic during POM and PRM respectively. Northwestern and southern
484
part of the study area is highly contaminated by arsenic. The Piper diagram depicts the following major
485
hydrochemical facies in the study area: Na-K-Cl-SO4; Ca-Cl and Ca-Mg-Cl- SO4 type in pre-monsoon and Na-K-Cl-
486
SO4; mixed Ca-Na-HCO3; Ca- HCO3 and mixed Ca-Mg-Cl type in post monsoon. From the Gibbs diagram, it is
487
inferred that rock-water interaction is the major process governing the hydrochemistry of groundwater in the study
488
area.
489
Based on the relationship between pH and Eh (Pourbaix Diagram), it is established that H3AsO3 is the major
490
arsenic species occurring in groundwater under a reduced condition of the aquifer in the study area. From PHREEQC
491
modelling it is concluded that mineral phase's viz. Ferric oxides and hydroxide are the possible sorbing site for As in
492
study area. Such minerals on reductive dissolution discharge arsenic into the groundwater. The strong correlation
493
between in-situ parameters and major ions during pre and post monsoon suggest that groundwater chemistry of study
494
area is controlled primarily by geogenic processes like rock-water interaction; ion exchange; mineral dissolution and
495
seawater intrusion (as highlighted in Spearman Correlation and PCA). Chemistry of groundwater is also controlled to
496
some extent by human activities like over pumping, industrial accomplishments, use of chemical fertilizers in
497
agricultural land and lack of sewage system (as highlighted in Spearman Correlation and PCA).
498
Statistical analysis (Spearman Correlation and PCA) obviously reveals that organic-rich marine sediments
499
(peat, lignite and agricultural waste), As and Fe bearing minerals are the source and are accountable for the reductive
500
dissolution and release of arsenic into aquifer system. It is also evident from the association of Eh and pH; As, K+,
501
HCO3-, Fe and other trace metals (Sc, Ti, V, Ni, Cd and Mo).
31
ACCEPTED MANUSCRIPT 502
This study strongly recommends for regular monitoring of groundwater. Besides, health risk assessment in
503
relation to arsenic contamination needs to be done for the study area.
504
Acknowledgement: We sincerely thank University Grants Commission (UGC), New Delhi for supporting the
505
current work financially through major research project [F.No. 41-1035/2012 (SR); date: 23.07.2012]. Also, we
506
extend our heartfelt thanks to Department of Earth Sciences, Department of Ecology and Environmental Sciences and
507
Central Instrumentation Facility of Pondicherry University for providing necessary facilities for analysis. We also
508
acknowledge the editor and anonymous reviewer for their cherished suggestions for bringing this research paper to
509
the current level.
510
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Highlights: 1. 2. 3. 4. 5.
Current investigation deals with occurrence, distribution, source and mechanism of arsenic mobility in groundwater of Puducherry region. Major sources for Arsenic contamination in groundwater are As, Fe bearing minerals and organic matter present in the marine and fluvial sediments of study area. Reductive Dissolution is the dominant mechanism contributing As into groundwater. Groundwater in northern and southern part of study area is contaminated by Arsenic. Arsenic in groundwater is of geogenic origin.
M. Sridharan, D. Senthil Nathan PII:
S0045-6535(18)30932-9
DOI:
10.1016/j.chemosphere.2018.05.083
Reference:
CHEM 21415
To appear in:
Chemosphere
Received Date:
07 March 2018
Accepted Date:
14 May 2018
Please cite this article as: M. Sridharan, D. Senthil Nathan, Chemometric Tool to Study the Mechanism of Arsenic Contamination in Groundwater of Puducherry Region, South East Coast of India, Chemosphere (2018), doi: 10.1016/j.chemosphere.2018.05.083
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ACCEPTED MANUSCRIPT 1
Chemometric Tool to Study the Mechanism of Arsenic Contamination in Groundwater of Puducherry Region,
2
South East Coast of India
3
M. Sridharan1*, D. Senthil Nathan2
4
1*Research
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Scholar, Department of Earth Sciences, Pondicherry University, Puducherry-605014
2Professor,
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Department of Earth Sciences, Pondicherry University, Puducherry-605014
*Corresponding
Author. Mail ID: [email protected] Ph.No:9790003360
7
Abstract
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aquifers of the Puducherry region were collected and analyzed for major ions and trace metals. The concentration of As
9
in groundwater of study area ranges from not detectable — 28.88 µg/L during the post-monsoon and not detectable —
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36.88 µg/L in the pre-monsoon. The desirable limit for As in groundwater is 10µg/L as per World Health Organization
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and Bureau of Indian standard. About 13.64 and 11.50% of groundwater samples shows arsenic concentration higher
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than recommended limit. Hydrochemical facies which dominate during pre and post monsoon are Na-K-Cl-SO4, Ca-Cl
13
and Ca-Mg-Cl-SO4type and Na-K-Cl-SO4, mixedCa-Na-HCO3, Ca-HCO3 and mixed Ca-Mg-Cl type respectively. The
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Gibbs diagram suggested that rock-water interaction is major process controlling hydrochemistry of groundwater. From
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the Pourbaix diagram, it is inferred that H3AsO3 is the principal As species in groundwater. The PHREEQC modelling
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indicates supersaturation of ferric oxides and hydroxide mineral phases in aquifer system which on reductive dissolution
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releases arsenic into groundwater. Statistical analysis (Spearman Correlation and Principal Component Analysis) showed
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that reductive dissolution of As-bearing minerals and Fe-oxyhydroxides in the presence of organic matter is the major
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process contributing arsenic into groundwater. The relationship between As, K+ and HCO-3 indicates agricultural and
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competitive exchange process which is an additional contributor of arsenic in groundwater. The sources which act as a
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sink and responsible for the release of As into the groundwater are marine sediments enriched in As and Fe-bearing
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minerals and organic matter.
To understand occurrence, distribution and source of arsenic, 175 groundwater samples from coastal
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Key Words: Groundwater, Arsenic, Hydrochemical, Puducherry, India, PHREEQC, Reductive Dissolution
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1.
Introduction
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Arsenic is a subtle and pervasive metalloid which can form both organic and inorganic compounds. It usually
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exists in -3, 0, +3 and +5 valence states, of which As (III) and As (V) are inorganic forms and, As (0) and As (-3) do not
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exist in nature. Arsenic is found to be widely distributed in the environment such as air, water, soil, rocks, plants and
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animals. Natural geogenic sources are found to be a major sponsor of arsenic in groundwater system (Gómez et al,
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2006). It is released into our environment by the natural process like volcanic activities (Aiuppa et al, 2003), weathering
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of rock materials, forest fires, geothermal processes, etc. (Sracek et al, 2004). In addition, As is also released into our
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natural system by anthropogenic activities like farming (insecticides and herbicides), mining, use of fossil fuels, pulp and
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paper production, cement manufacturing, paint industry, wood preservatives, glass manufacture, electronics, catalysts,
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alloys, feed additives and veterinary chemicals (Pfeifer et al, 2004). The behaviour of arsenic in a natural system is found
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to be most enigmatic due to its chemical characteristics like reactivity, toxicity (Mukherjee et al, 2008); its switching
40
property (readily switching over to different valence states) etc.
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The factors responsible for release of arsenic into the groundwater are pH; presence of organic matter in
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sediments (like peat, lignite and plant debris)( Hinkle & Polette et al, 1999); water table fluctuation (Rodrı́guez et al,
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2004); water saturation of sediments, limited supply of sulphur and microbial activities (Matisoff et al 1982; Chapelle,
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2000; Lovely, 1997); groundwater flow direction, age of groundwater and topography (Fendorf et al, 2010) and Marine
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transgression (Berg et al, 2001; Trafford et al, 1996). There are three major mechanisms which causes release of arsenic
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into groundwater. They are 1. Oxidation and dissolution of As and Fe bearing minerals (Smedley et al, 2002; McArthur
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et al, 2001; Welch et al, 2000) 2. Weathering and reductive dissolution of As bearing primary and secondary minerals in
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the presence of natural organic matter (NOM) (Berg et al, 2001). 3. Combination of both oxidative and reductive
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dissolution of arsenic-bearing iron oxides and oxyhydroxides (Nickson et al, 1998; Kinniburgh et al, 2001; McArthur et
50
al, 2001). 4. Competitive exchange of As by other compatible ions such as nitrate, phosphate (Acharyya et al, 1999) and
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bicarbonate (Nickson et al, 2000; McArthur et al, 2001).
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Higher concentration of arsenic in groundwater is proved to be a serious threat to human health, plants and
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animals. Its toxicity and mobility vary with respect to its valence state and chemical form. The treatment process of
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arsenic contaminated groundwater is also very complex. Considering the above factors, World Health Organization
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(WHO, 2011) recommended the permissible limit for arsenic as 0.01mg/L. Whereas in India, Bureau of Indian Standards
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(BIS, 2012) sets a desirable limit for As in drinking water as 0.01mg/L and when there is no any other source for
57
drinking water its concentration is recommended up to 0.05mg/L.
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Throughout the world, consumption of arsenic contaminated groundwater have caused serious health issues like
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skin, lung, kidney and bladder cancer; coronary heart disease; bronchiectasis; hyperkeratosis; arsenicosis;
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hyperpigmentation of the palm and sole; hypertension; myocardial damage; liver damage; Bowens disease; diabetes, etc.
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(Moore, 1991; Lalwani et al, 2004; Hopenhayn et al, 2006). Agricultural activities carried out in As contaminated soil
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and water may cause severe poisonous effects on plants and trees (Wagner et al, 2005). The analogous behaviour of As
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and PO2-4 (an essential nutrient for plants) in a plant-soil system cannot be endured by plants as it is phototoxic. It also
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leads to reduced plant growth, root damage and less yield (Bhumbla et al, 1994). Since rice cultivation needs stagnated
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water for its growth, agricultural land is under reducing condition for a prolonged time. It leads to accumulation of
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virulent arsenic into the soil and later to groundwater (Wagner et al, 2005; Bhumbla et al, 1994).
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Arsenic contamination in groundwater from natural sources and associated health issues have been reported in
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many countries viz. Bangladesh, India, Argentina, Chile, China, Hungary, Mexico, Vietnam, Taiwan, Romania, USA,
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Canada (Ontario), New Zealand, Poland, Alaska, Spain and Japan (Sracek et al, 2004; Mukherjee et al, 2006; FPTC,
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2004). Countries in which groundwater is contaminated by arsenic from anthropogenic sources are Thailand, India
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(Madhya Pradesh), Australia, Greece, Ghana, Rhodesia, Scotland, Sweden, England, Germany (Mandal et al, 2002 and
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Subrahmanyam et al, 2001).
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In India arsenic contamination in groundwater is first reported in Chandigarh (Datta et al, 1976) followed by
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states like West Bengal, Bihar, Uttar Pradesh, Jharkhand, Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram,
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Nagaland, Sikkim, Tripura, Punjab, Himachal Pradesh, Chhattisgarh and Andhra Pradesh (Mukherjee et al, 2006). Large
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numbers of people belonging to the above states i.e. Ganga-Brahmaputra basin are affected by diseases like skin itching,
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burning and watering of eyes, weight loss, loss of appetite, weakness, lethargy and fatigue, chronic respiratory and
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gastro-intestinal problems, anemia, conjuctival congestion, etc. (Ghosh et al, 2009). There are several natural sources
79
responsible for arsenic release into groundwater along Ganga-Brahmaputra basin such as Holocene sediments,
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Gondwana coal seams, mica belt, pyrite bearing shale, Son valley gold belt (Bhattacharya et al. 2006). Industries
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manufacturing veterinary drugs, pesticides and other chemicals are found to be the major anthropogenic sources of
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arsenic contamination in groundwater in India (Mandal et al. 2002 and Subrahmanyam et al. 2001). Oxidation of pyrite
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and arsenopyrite; reductive dissolution of arsenic from soils and competitive exchange of ions are the major cause for
84
mobilization of arsenic into groundwater of Ganga-Brahmaputra basin (Bose et al, 2002).
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The Puducherry region is a sedimentary terrain composed of marine sediments, alluvium, laterites, thin seams of
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peat and lignite whose age ranges from Cretaceous to Recent. Over-pumping of groundwater, the rapid growth of
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industries, urbanizations, increase in population and lack of baseline information for arsenic in the Puducherry region
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have prompted this study. Switching property and toxic nature of arsenic; it's occurrence in wide pH range; intricate
89
treatment process; lack of its own isotope and technique to find exact source urged us for the current investigation. The
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main objective of this research paper is to discern the spatial and temporal distribution of arsenic, its occurrence, source
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and mechanism of release into groundwater of the Puducherry region with the aid of Chemometric tool.
92 93 94 95
2.
Study Area
2.1 Location Puducherry is located along the Coromandel coast of India, whose latitude and longitude are 11º45'; 12º03' N
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and 79º37'; 79º37' E respectively. The study area exists as enclaves within the state of Tamil Nadu in India (Fig. 1).
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2.2 Climate
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Puducherry receives its maximum rainfall during North-East monsoon i.e. during the months of October,
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November and December. It experiences relatively hot and humid tropical climate conditions. During the month of
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April, May and earlier part of June, study area experiences hot climate (CGWB, 2013). The average annual rainfall of the
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study area is 1272mm.
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2.3 Drainage
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There are two major ephemeral rivers that run across the study area namely River Gingee (also known as
104
Sankarabarani and Varahanadi) and River Ponnaiyar (Fig. 1). River Gingee flows diagonally in the study area in NW-SE
105
direction. River Ponnaiyar drains along the southern boundary of the study area. Apart from these, there are several
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major and minor tanks that serve as the surface water sources for basic needs of the study area. Among all those, the
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Lake Ousteri (which lies along the bank of River Gingee) and the Lake Bahoore are the major tanks (CGWB, 2013).
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2.4 Geology and Geomorphology
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The study area is composed of sedimentary rocks whose age ranges from Cretaceous to Recent with Archaean
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basement and the sedimentary sequences encountered here are of marine and fluvial origin. The Archaean rocks are
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charnockite and biotite-hornblende gneiss. The Cretaceous group of rocks exposed along the northern part of study area
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is composed of shelly limestone, sandstone, silt and clay which are named as Ramanathapuram, Vanur sandstone, Ottai
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clay and Turuvai limestone Formations. The Turuvai limestone, the uppermost Cretaceous Formation, is unconformably
114
overlain by the Tertiary group of rocks which include formations such as Kadaperikuppam and Manaveli of Paleocene
115
Table 1 Stratigraphic Succession of the Study Area. (CGWB, 2013) Era Quaternary
Period Recent
Formations Alluvium, laterite
Lithology Sand, clay, silts, kankar, gravels and laterite Mio-Pliocene Cuddalore Formation Pebbly& gravely& coarse grained sandstones with minor clays & siltstones with thin seams of lignite ---------------------------------------Unconformity-------------------------------------------------------------Tertiary Paleocene Manaveli Formation Yellow & yellowish brown, grey calcareous siltstone and claystones & shale with thin bands of limestone Kadaperikuppam Yellowish white to dirty white sand. Formation Hard fossiliferous limestone, calcareous sandstone and clays ---------------------------------------Unconformity-------------------------------------------------------------Turuvai Formation Highly fossiliferous limestone, Mesozoic Upper Cretaceous conglomerate at places, calcareous sandstone and clays Ottai Claystone Grey to greyish green claystones, silts with thin band of sandy limestone and fine grained calcareous sandstone Lower Cretaceous Vanur Sandstone Quartzite sandstone, hard coarse grained, occasionally feldspathic or calcareous with minor clays Ramanathapuram Black carbonaceous silty clays and Formation fine to medium grained sands with bands of lignite and medium to coarse grained sandstone ---------------------------------------Unconformity-------------------------------------------------------------Archean Eastern Ghat Complex Charnockite and Biotite hornblende gneisses
5
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period; Cuddalore formation of Mio-Pliocene age. Palaeocene formations are characterized by clay, shale, claystone,
117
siltstone and calcareous sandstone whereas Mio-Pliocene formation is composed of ferruginous sandstone. The recent
118
formation of the Quaternary period is composed of laterites, alluvium, coastal sands and clay. Bands of lignite and peat
119
are found in Cuddalore and Alluvium formations of study area respectively (CGWB, 2013; Fig. 2; Table. 1).
120
Geomorphologically, the study area is classified as uplands, alluvium and coastal plains. Uplands are found
121
along the north-western part of the study area with an average elevation of 15m with gullies and ravines. Alluvium
122
occurs in the southern part of the study area. Coastal plains are found along the eastern part of the study area with land
123
features like spits, cusp, bars, lagoons, wave-cut platform, sand dunes, etc. (CGWB, 2013).
124 125
2.5 Hydrogeology
126
The two major groups of rocks occurring in the study area are 1) Fissured and Fractured Crystalline Formations
127
and 2) Porous Sedimentary Formations (CGWB, 2013). The weathered portion and fissured-fractured zone occur under
128
phreatic and semi-confined conditions. The porous formations cover the almost entire region of the study area. They are
129
characterized by the semi-consolidated formations of Cretaceous and Tertiary and unconsolidated Quaternary formations
130
of Recent age. Amidst of all the porous sedimentary aquifers, the Vanur and Ramanathapuram Sandstone (Cretaceous)
131
and the Cuddalore sandstone (Tertiary) aquifers and the shallow alluvial (Quaternary) aquifers are the three major
132
potential aquifer systems in this region. Groundwater occurs in these formations in both unconfined and confined
133
conditions.
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134 135
Fig.1 Study Area and Sample Location Map
136 137
Fig.2 Geological Map of the Study Area
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3. Materials and Methods
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3.1 Groundwater Sampling
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About 175 groundwater samples from bore wells have been collected covering all the litho-units of the study
141
area, during the pre (PRM) i.e. August, 2014 and post monsoon (POM) i.e. January, 2015 as per the standard procedures
142
of APHA, 2005 (Fig. 1). Prior to sampling, bore wells were pumped for 15-20 minutes so as to avoid the sampling of
143
stagnant water in the pipe, which may lead to misinterpretation. Teflon containers were used for sampling to avoid
144
leaching from walls of the container. Before sampling, containers were washed using nitric acid followed by deionized
145
water and finally by the groundwater that has to be sampled. A set of each sample was collected, out of which one
146
sample is acidified and filtered for trace metal analysis and the other is used for major ion analysis. Acidification of
147
water samples was done by adding HNO3 by lowering the pH to 2, in order to withhold the metals in its ionic state by
148
inhibiting the formation of compounds and complexes.
149
3.2 Groundwater Sample Analysis
150
In-situ parameters such as pH, Eh, Total Dissolved Solids (TDS) and Conductivity (EC) were analyzed in the
151
field itself. Collected water samples were then analyzed for major ions such as Na+ (Sodium), K+ (Potassium), Ca2+
152
(Calcium), Mg2+ (Magnesium), SO42- (Sulphate), HCO3- (Bicarbonate), NO3- (Nitrate) and Cl- (Chloride). Acidified water
153
samples were analyzed for metals and metalloids such as As, Fe, Sc, Ti, V, Ni, Cu, Pb, Zn, Mo, Sn, W, Pb and U.
154
pH, Eh, EC and TDS were analyzed using Hanna portable water analyzer. Major ions such as Na+, K+, Ca2+,
155
Mg2+, SO42-, NO3-, Cl- and total iron using Ion Chromatography (ICS DIONEX 1100); bicarbonate using Volumetric
156
Titration method (sulphuric acid method). As, Fe, Sc, Ti, V, Ni, Cu, Pb, Zn, Mo, Sn, W, Pb and U in groundwater
157
samples were determined by using Thermo Scientific XSERIES 2 Quadrupole Inductively Coupled Plasma Mass
158
Spectrometer (Total Arsenic concentration were measured by Collision Cell Technology method).
159 160
Spatial distribution maps were prepared using ArcGIS10.3. Mineral saturation indices were calculated using the software PHREEQC Interactive 2.8. Statistical analysis was done by using IBM SPSS statistical V20 tool.
161 162 163 8
ACCEPTED MANUSCRIPT 164
Table 2a Analytical and Statistical results of Water Samples Collected in Post Monsoon
165
Parameters
Minimum
Maximum
Mean
SD
166
pH
6.09
7.45
5.88
7.48
Eh
-58.00
16.00
-32.65
16.83
167
EC
110.00
3980
1143.48
557.58
168
TDS
26.24
2320.00
641.94
313.79
169
Na+
120.55
5201.24
529.88
590.43
K+
ND
417.67
64.12
73.1
171
Ca2+
63.02
1683.65
234.47
181.97
Mg2+
7.85
524.18
78.21
59.66
172
Cl-
35.46
23511.90
1027.53
2513.67
173
SO2-4
ND
4144.55
390.68
522.81
HCO-
ND
317.20
49.49
35.93
NO-3
2.45
87.87
15.60
15.04
175
Sc
1.76
12.48
7.02
2.24
176
Ti
1.96
21.02
6.15
3.10
V
.41
94.74
14.04
15.19
Ni
ND
8.93
2.04
1.57
178
Cu
ND
24.17
4.13
4.29
179
Zn
ND
3254.00
91.54
398.63
180
As
ND
28.88
4.21
4.69
Mo
ND
7.26
.93
1.29
Sn
ND
259.00
11.11
42.82
Cd
ND
.83
.13
.11
Ba
ND
948.40
180.40
169.84
W
ND
.1
.01
.02
Pb
ND
44.86
1.69
5.25
U
ND
17.57
3.40
3.87
Fe
ND
9175
998.67
1197.80
170
174
177
3
181
Concentration of Na, K, Ca, Mg, Cl, So4, HCO3 in mg/L; Sc, Ti, V, Ni, Cu, Zn, As, Mo,
182
Sn, Cd, Ba, W, Pb, U, Fe in µg/L; TDS-mg/L; EC- (µS/cm)
183
9
ACCEPTED MANUSCRIPT 184
Table 2b Analytical and Statistical results of Water Samples Collected in Pre Monsoon Pre Monsoon Parameters
Minimum
Maximum
Mean
SD
pH
5.99
8.56
7.03
.34
Eh
-115.00
-1.00
-35.59
15.90
EC
341.00
3080.00
1187.26
501.18
TDS
173.00
6380.00
646.95
668.34
Na+
26.20
3588.04
347.90
398.71
K+
ND
353.71
49.18
46.79
Ca2+
ND
881.54
159.84
110.22
Mg2+
7.77
719.19
76.01
95.38
Cl-
8.72
4707.13
360.52
579.67
SO2-4
ND
948.63
214.65
302.69
HCO-3
ND
902.80
343.14
254.18
NO-3
ND
70.00
14.85
16.04
Sc
1.88
26.52
7.6
3.23
Ti
1.57
97.36
7.47
10.63
V
.74
48.69
14.13
12.50
Ni
ND
27.94
3.17
3.90
Cu
ND
100.90
4.89
12.41
Zn
ND
4392.00
142.68
547.55
As
ND
36.88
4.63
5.33
Mo
ND
6.71
1.28
1.33
Sn
ND
30.52
.30
3.32
Cd
ND
142.70
1.89
15.37
Ba
ND
530.40
170.51
144.01
W
ND
2.32
.06
.23
Pb
ND
23.36
1.06
2.87
U
ND
13.90
3.41
3.37
Fe
ND
2378.00
545.10
577.88
185
Concentration of Na, K, Ca, Mg, Cl, So4, HCO3 in mg/L; Sc, Ti, V, Ni, Cu, Zn, As, Mo,
186
Sn, Cd, Ba, W, Pb, U, Fe in µg/L; TDS-mg/L; EC- (µS/cm)
187
10
ACCEPTED MANUSCRIPT 188 189
4.
Results and Discussion
4.1 Physico-Chemical Parameters of Groundwater
190
The analytical and statistical results of groundwater samples collected from the study area during Post (POM)
191
and Pre-monsoon (PRM) are shown in table 2a and 2b respectively. The concentration of the major anions during post
192
and pre-monsoon are, Anion: Cl- >SO42- > HCO3- >NO3- and Cl- > HCO3- >SO42- >NO3- respectively. The concentration
193
of the major cations in both the seasons is same as follows: Na+ >Ca2+> Mg2+> K+. The pH of the samples in the study
194
area ranges from 6.09-7.45 and 5.99-8.56 during post and pre-monsoon respectively of which majority of samples
195
exhibits near neutral pH condition. However, the locations with lower pH signify intense mineral dissolution process.
196
Electrical Conductivity ranges from 110-3980(µS/Cm) in post monsoon and 341-3080 (µS/Cm) in the pre-monsoon.
197
TDS varies from 26.24-2320 mg/L in POM and 173-6380 mg/L in PRM. Very high pH, conductivity and total
198
dissolved solids are attributed to seawater intrusion, improper sewage disposal and agricultural activities (Sarath
199
Prasanth et al. 2012; Ramesh et al. 2012; Sridharan et al, 2017a). The mean concentration of major ions viz. Na+, K+,
200
Ca2+, Mg2+, SO42-, NO3-, Cl- were higher during POM when compared to PRM due to infiltration; dissolution of
201
minerals and soluble salts and leaching. In summer the water table decreases, during which oxidation of aquifer
202
materials takes place. Due to oxidation, the precipitation of soluble salts occurs. These soluble salts are then dissolved
203
and flushed into aqueous media during the monsoon. This process causes the enrichment of ions and other dissolved
204
solids in groundwater. But with respect to time-lapse and continuous supply or infiltration of rainwater, dilution occurs
205
thereby reducing the concentration of ions (Rodrı́guez et al, 2004; Giménez –Forcada, 2010).
206
The
abundance
of
Trace
metals
during
POM
displays
the
following
order
following
order
207
Fe>Zn>Ba>Sn>V>Pb>As>Cu>U>Ti>Sc>Ni>Mo>Cd>W,
208
Fe>Ba>Zn>V>Sc>Ti>Cu>As>U>Mo>Pb>Sn>W. Iron is the most abundant trace metal occurring in the study area
209
whose concentration varies from ND-9175µg/L and ND-2378µg/L during POM and PRM respectively. Higher
210
concentration of dissolved iron in groundwater indicates the reducing environment; the presence of iron-bearing
211
minerals and sediments of marine origin (Hunt et al, 1994). In the study area, the minimum and maximum
212
concentration of arsenic during POM is ND and 28.88µg/L respectively. While in PRM concentration of arsenic varies
213
from ND-36.88µg/L. About 13.64% of samples in PRM and 11.50% samples in POM show concentration of arsenic
214
higher than World Health Organization (WHO, 2011) and Bureau of Indian standard (BIS, 2012) limit i.e. 10 µg/L in
11
whereas
PRM
shows
the
ACCEPTED MANUSCRIPT 215
groundwater of the study area. The spatial distribution map of arsenic is shown in the figure.3a and 3b.
216 217 218
Fig3a & b Spatial Distribution Map of Arsenic in Study Area 4.2 Piper Diagram
219
The Piper diagram is a pictorial representation of ions which integrates major cations and anion in groundwater on a
220
trilinear plot to discern different hydrochemical facies (Bahar et al, 2010; Fig.4). In the present study, it is recognized
221
that the most influencing hydrochemical facies of groundwater during the pre-monsoon is Na-Cl type followed by Ca-Cl
222
type and Ca-Mg-Cl type (Fig. 4). Whereas in post-monsoon the major controlling hydrochemical facies is Na- Cl type
223
followed by mixed Ca-Na-HCO3 type, Ca-HCO3 type and mixed Ca-Cl type (Fig. 4).
224
The facies enriched in Na+, HCO-3 and Cl- expresses that seawater and tidal channel plays a considerable performance
225
along the coastal tract. The freshwater-seawater interaction along the coastal aquifers causes replacement of Ca2+ in
226
groundwater by Na+ from seawater, by the action of an ion-exchange process (Bahar et al, 2010; Sridharan et al, 2017b).
227
Ca-Cl-HCO3 group of water signifies that there was not effective recharge process which led to increasing the
228
concentration of Cl- and Na+ by evaporation process (Lakshmanan, et al, 2003). Recharge of groundwater by rainfall and
229
corresponding low EC values led to the formation of Ca-HCO3 facies (Lakshmanan, et al, 2003). Rainwater along with
230
dissolved CO2 in the atmosphere becomes acidic. When such acidic rainwater oozes into the subsurface it dissolves
231
carbonate minerals leading to enrichment of Ca- HCO3 type of water (Adams et al, 2001). Mixed Ca-Na-HCO3 type of
12
ACCEPTED MANUSCRIPT 232
facies depicts rock-water interaction process, which involves the dissolution of carbonates and feldspars by the
233
recharging groundwater (Adams et al, 2001). Facies enriched in SO2-4 are due to dissolution of minerals like gypsum.
234 235 236
Fig. 4 Piper Diagram 4.3 Gibb’s Diagram to Understand Mechanism of Groundwater Quality:
237
Based on the ratio of major cations and anions with respect to TDS in groundwater samples, Gibbs designed a
238
plot which includes 3 major domains. They are 1. Rock-Water Dominance, 2.Evaporation and 3.Precipitation dominance
239
(Gibbs et al, 1970; Marghade et al, 2015). In the study area, a majority of water samples falls under the Rock-Water
240
domain which signifies that geochemical process such as precipitation-dissolution; oxidation-reduction and ion exchange
241
are the dominant governing factor of groundwater chemistry in both the seasons (Fig. 5a, b). A few numbers of samples
242
fall under the evaporation domain signifying climatic control over groundwater chemistry. It also emphasizes that by the
243
mechanism of evaporation, the water and moisture components of groundwater are precipitated and deposit as
13
ACCEPTED MANUSCRIPT 244
evaporites. Further, these evaporites percolate into the groundwater saturated zone and eventually increase the salinity
245
and total dissolved solids of groundwater (Chebbah et al, 2015; Dehnavi et al, 2011).
246 247
Fig.5a & b Gibbs plot to understand hydrochemical process of study area.
248 249 14
ACCEPTED MANUSCRIPT 250
4.4 Mineral Saturation Indices
251
From Gibbs Diagram it is concluded that rock-water interaction is the major process governing the groundwater
252
chemistry of study area (fig.5a and b). During such interaction, rocks comprising the minerals rich in trace/heavy metals
253
may be desorbed and transported, leading to contamination of groundwater (Deutsch et al, 1997). Hence using chemical
254
composition of groundwater samples analyzed, mineral phases saturated can be visualized by using a geochemical
255
modelling technique called PHREEQC. A saturation index of the mineral phases is the logarithmic ratio of ionic activity
256
product and solubility product. It can be calculated by following the expression.
257 258
SI = Log (IAP/Ksp) Where, SI is Saturation Indices; IAP is Ionic Activity Product, and Ksp is Solubility Product
259
Mineral phases, in equilibrium with the solution, if SI is equal to 0; undersaturated, if SI <0 and supersaturated,
260
if SI >0. Using this approach it is possible to predict the reactive mineral phases present in the aquifer from the
261
groundwater data without collection of any solid samples. It can be validated by analyzing the aquifer solid samples
262
(Deutsch et al, 1997; Merkel et al, 2005).
263
Table.3a Saturation Indices of different mineral phases in PRM Pre-Monsoon
264
Mineral Phases
Mean SI
Max SI
Min SI
Anglesite
-1.86
2.24
-3
Anhydrite
2.08
7
-0.39
Barite
2.07
3.87
-8.96
Cd(OH)2
-8.15
-5.07
-11.36
CdSO4
-8.95
10.88
-12.1
Fe(OH)3a
2.97
8.79
-3.14
Goethite
7.79
9.64
-3.82
Gypsum
0.45
2.09
-4.26
Halite
-1.32
19.59
-4.8
Hematite
41.58
20.98
-5.13
Jarosite-K
3.96
8.09
-6.31
Melanterite
-3.96
5.1
-6.34
Pb(OH)2
-1.85
0.39
-3.68
Zn(OH)2 e
-2.92
-0.83
-5.41
*SI – Saturation Indices; PRM- Pre-monsoon
15
ACCEPTED MANUSCRIPT 265
Table.3b Saturation Indices of different mineral phases in POM Pre-Monsoon Mineral Phases
266
Mean SI
Max SI
Min SI
Anglesite
-1.80
-0.19
-3.42
Anhydrite
2.19
9.6
0.33
Barite
2.90
4.2
-1.01
Cd(OH)2
-8.74
-7.11
-11.28
CdSO4
-10.77
-9.82
-12.37
Fe(OH)3a
2.81
3.99
-0.74
Goethite
19.27
19.35
-2.66
Gypsum
1.19
3.58
-2.73
Halite
-2.56
0.94
-3.88
Hematite
19.48
21.81
12.35
Jarosite-K
6.10
10.55
-4.2
Melanterite
-3.90
-1.72
-7.19
Pb(OH)2
-1.96
0.75
-4.52
Zn(OH)2 e
-3.32
4.07
-5.16
*SI – Saturation Indices; POM- Post-monsoon
267
PHREEQC hydrochemical modelling technique done over the samples collected during PRM and POM
268
indicates that the mineral phases viz. Anglesite, halite, melanterite, Pb and Zn hydroxides were undersaturated in
269
solution with regards to solid phases (Table.3a and b). It implies that these minerals were absent in the aquifer materials
270
or unreactive or less residence time of groundwater in the aquifer. However, mineral phases like anhydrite, barite,
271
ferrihydrite, goethite, gypsum, hematite and jarosite-K are found to be supersaturated. From supersaturation and
272
subsequent precipitation of those mineral phases, it is inferred that these group of minerals acts as a sink for dissolved
273
iron in groundwater (Agrawal et al, 2011). In addition, presence and supersaturation of ferric oxides and hydroxides
274
propose that they offer the potential site for As adsorption (Sappa et al, 2014; Fuller et al, 1993). Precipitation of the
275
above minerals may lead to desorption of As from Fe bearing minerals (Mukherjee et al, 2008). Under reducing
276
condition prevailing in the case of study area, arsenic sorbed over those mineral phases get desorbed and enter into the
277
aquifer system (Dzombak et al, 1990), as in the case of the study area.
278 279
16
ACCEPTED MANUSCRIPT 280
4.5 Statistical Analysis
281
4.5.1 Correlation of Arsenic with other Major Ions and Trace Metals
282
Bivariate Spearman correlation, a statistical tool was used to understand the relationship between arsenic and
283
other variables. Based on Spearman analysis, it is inferred that there exists strong positive correlation between As and Fe
284
(rPRM = 0.778; rPOM = 0.513); moderate correlation between As and HCO3 (rPOM = 0.363), Mo(rPOM = 0.349),
285
Ti(rPOM = 0.223), V(rPOM = 0.309); weak correlation between As and K+(rPRM = 0.225) (Fig. 7c), Sc(rPOM = 0.242),
286
Pb(rPRM = -0.247), U(rPRM = -0.243) (Table. 4a, b and 5a, b).
287
The strong to moderate correlation of TDS and EC with other major ion of groundwater such as Na+, K+, Ca2+,
288
Mg2+, SO42-, NO3-, Cl- both in pre and and the implies that the major processes governing groundwater chemistry of study
289
area are seawater intrusion (TDS, EC, Na+, K+, Ca2+, Mg2+, Cl-), ion exchange (Na+, K+ and Ca2+, Mg2+)(Sridharan et al,
290
2017b) and other anthropogenic activities like application of fertilizers (K+, SO42-, NO3-), sewage disposal (NO3-) and
291
industrial effluents (Narany et al, 2014; Table. 4a, b and 5a, b). The strong correlation between Ca2+ and Mg2+ indicates
292
dissolution of Calcite and Dolomite or silicate weathering (Narany et al, 2014). Weak correlation of K+ with other major
293
ions like Na+ and Ca2+, Mg2+ suggest that it is released into the aquifer by potassium used in agricultural land and
294
weathering of K -feldspar or K-bearing minerals (Jalali et al, 2006; Table. 4a, 4b, 5a and 5b). Higher concentration of Cl-
295
when compared to SO2-4 implies the sulfate reduction (Lakshmanan et al, 2003) (Table. 4a, 4b, 5a and 5b).
296
The negative correlation between arsenic and Eh (redox potential) and higher concentration of Fe in
297
groundwater samples of the study area indicates the redox condition of the aquifer (Shrestha et al, 2016; Table. 4a and
298
4b).
299
The excess concentration of Fe and As indicates, the presence of Fe and As bearing minerals in the study area.
300
The authors viz. Reddy et al, 2007 and Nathan et al, 2012 have reported the presence of iron and arsenic bearing
301
minerals (like arsenolite, claudetite, kamacite, pyrite, realgar, marcasite, etc.) in the study area. Reductive dissolution of
302
those minerals are attributed to the release of As and Fe into groundwater simultaneously (Pfeifer et al, 2004; Oinam et
303
al, 2011). It can also be inferred from the strong relationship between Fe and As in groundwater samples collected during
304
pre-monsoon (rPRM=0.778) and post (rPOM =0.513) monsoon of the study area.
305
During the pre-monsoon, there is more extraction of groundwater which leads to a reduction in groundwater
306
level. Lowering of water table causes oxidation of organic deposits (peat, lignite, agricultural wastes and marine
17
ACCEPTED MANUSCRIPT 307
sediments) in the subsurface. These organic deposits which were formerly saturated with water are currently exposed to
308
oxygen which leads to oxidation and downward movement of leachates creating anoxic condition within the aquifers. It
309
enhances reductive dissolution of As-bearing minerals and As sorbed Fe-oxyhydroxides. As a consequence of above
310
process Fe and As is released.
311
During POM there exist a moderate relationship between As and bicarbonate, under neutral pH and negative
312
Eh (reducing condition) (fig. 6d; table. 4a and 4b) indicates the role of microbial activity in reductive dissolution process.
313
Besides, if there exists a positive correlation between As and HCO-3 then it is inferred that arsenic is released by
314
reduction of Fe-oxyhydroxides (Nickson et al, 2000; Mcarthur et al, 2001). If this process acts as a dominant controlling
315
factor of arsenic concentration in groundwater, then there should exist, a strong correlation between Fe and bicarbonate
316
ions (Mcarthur et al, 2001). If it is not so, then there might be some other mechanism responsible for As release viz. near
317
neutral pH and reducing condition (Choprapawon and Rodcline 1997; Chowdhury et al. 2000; Ramanathan et al. 2007),
318
calcite dissolution and weathering of biotite and feldspar (Katsoyiannis et al, 2006; Nickson et al.(1998; 2000)),
319
carbonation of arsenic sulphide minerals (Kim et al. ; 2000 and Anawar et al. ;2004). Near neutral to alkaline pH
320
condition prevailing in some part of the study area, desorbs As from Fe-hydroxides by OH- ions and it also inhibits re-
321
adsorption of As onto Fe-hydroxides (Fig. 6a). It might have caused the mobilization of arsenic into the aqueous phase to
322
some extent (Kondo et al. 1999; Bhattacharya et al. 2006; Ahn et al, 2011; Zkeri et al, 2015). Also, the concentration of
323
arsenic and iron does not completely correlate with each other in all the samples which mean that there exists an
324
additional source of iron in the study area. Iron may also be released from siderite, vivianite or hydroxycarbonates or
325
other oxides (Mcarthur et al, 2001).
326
Also, there occurs positive correlation among trace metals viz. As, V, Ti, Sc, Ni, Cd, Sn during pre and post-
327
monsoon of the study area (Table. 4a and 4b). These metals are found to be enriched in argillaceous sedimentary rocks,
328
iron stones, phosphatic shales, laterites and ash deposits of peat, coal and crude oil (Schwartz et al, 1980). The presence
329
of biodegradable organic matter was accountable for reduction and mobilization of trace metals (Chitsazan et al, 2008;
330
Hem, 1985). Microbes and Dissolved Organic Carbon (DOC) are responsible for redox condition within the aquifer of
331
the study area were already reported by Kesari et al, 2015 and Thilagavathi et al, 2016. The organic matter which
332
includes peat and lignite deposits occurs in the northern and southern (alluvium formation) part of the study area
333
(CGWB, 2013). Apart from it, the study area includes marine sediments rich in organic content and agricultural wastes.
18
ACCEPTED MANUSCRIPT 334
Molybdenum is redox-sensitive oxyanion found in earth material. It is an essential element for metabolic
335
activities of nitrogen-fixing bacteria. Its presence and correlation with As in groundwater during POM explain about the
336
adsorption-desorption reaction (Dowling et al, 2002; Table. 4a and 4b). The mobility of Mo is favoured during reductive
337
dissolution mechanism of Fe and Mn oxides with respect to reducing conditions prevailing within the aquifer (Bennett et
338
al, 2003; Schliekeret al, 2001; Smedley et al, 2014). Also the correlation between As, V and Mo indicate they might be
339
mobilized from a single source.
340
Strong to moderate correlation among elements such as Ni, Cu, Cd, Pb and Zn implies that they are mobilized
341
from the different sources (Table. 4a and 4b). Usage of chemical fertilizers and pesticides enriched in above said metals
342
and chemical industries located in study area might be the cause of their concentration in groundwater (WHO, 2011).
343 344 345 346 347 348 349 350 351 352
19
353
Table. 4a Spearman Correlation table for Pre Monsoon pH
EC
TDS
Na
+
+
K
Ca
2+
2+
Mg
Cl
-
So
2 4
HCO3
-
NO 3
pH
1.0
Eh
-.945
1.0
EC
.089
-.067
1.0
TDS
.054
-.044
.975
1.0
.020
-.003
.401
.424
1.0
-.055
.093
.178
.196
.562
1.0
-.041
.006
.323
.339
.534
.376
1.0
-.130
.152
.276
.299
.479
.316
.796
1.0
.203
-.223
.446
.483
.224
.198
.203
.108
1.0
.214
-.227
.436
.457
.198
.150
.080
-.051
.747
1.0
.234
-.216
.376
.364
.268
.018
.186
.171
.271
.212
1.0
-.076
.100
.318
.355
.169
-.048
.285
.446
.115
.084
.088
1.0
.187
-.111
.020
.001
.075
.225
.036
-.107
-.106
-.005
.062
-.168
Na
+
+
K
Ca
2+
2+
Mg -
Cl
SO
2 4
HCO3 -
NO 3 As
354
Eh
*Values in bold indicate they have significant relationship
355 356 357 20
As
1.0
358
Table 4b Spearman Correlation table for Post Monsoon pH
EC
TDS
Na
+
+
K
Ca
2+
2+
Mg
-
Cl
So
2 4
HCO3
-
NO 3
pH
1.000
Eh
-.990
1.000
EC
.115
-.118
1.000
TDS
.188
-.177
.935
1.000
-.059
.075
.206
.222
1.000
-.100
.123
.068
.091
.436
1.000
-.170
.173
.289
.299
.252
.284
1.000
-.114
.107
.335
.319
.295
.221
.741
1.000
-.133
.158
.451
.481
.294
.317
.431
.489
1.000
-.029
.059
.488
.553
.374
.187
.237
.277
.597
1.000
.347
-.298
.165
.274
.080
.045
.117
.071
.106
.288
1.000
-.171
.164
.228
.203
-.060
.069
.211
.090
.115
.157
-.012
1.000
.186
-.153
.043
.118
.127
.115
-.018
-.118
-.113
.091
.363
.041
Na
+
+
K
Ca
2+
2+
Mg -
Cl
SO
2 4
HCO3 -
NO 3 As
359
Eh
*Values in bold indicate they have significant relationship
360 361
21
As
1.000
362
Table 5a Spearman Correlation table for Pre Monsoon (Trace elements) Sc
363
Ti
V
Ni
Cu
Zn
As
Mo
Sn
Cd
Ba
W
Pb
U
Sc
1.000
Ti
.634
1.000
V
.237
.357
1.000
Ni
.283
.278
.122
1.000
Cu
.159
.268
.175
.355
1.000
Zn
.025
-.034
.127
.146
.151
1.000
As
.001
-.081
-.006
-.020
-.139
-.004
1.000
Mo
-.125
.115
.143
.102
.044
-.008
.143
1.000
Sn
.242
.262
.024
.605
.128
.066
.064
-.038
1.000
Cd
-.023
-.165
.078
-.013
.258
.011
.010
-.101
-.085
1.000
Ba
.071
-.072
.373
.091
-.166
.185
.044
-.002
-.020
.127
1.000
W
.001
.062
-.218
.292
.172
-.005
.022
.131
.478
-.118
-.209
1.000
Pb
.103
.089
-.105
.308
.560
.310
-.247
-.129
.271
.107
-.129
.354
1.000
U
.430
.279
.647
.275
.060
.094
-.243
-.078
.108
.015
.280
-.168
.076
1.000
Fe
.002
-.119
-.134
.084
-.150
.122
.778
.129
.153
.076
.004
.134
-.101
-.284
*Values in bold indicate they have significant relationship
364 365 366 22
Fe
1.000
367
Table 5b Spearman Correlation table for Post Monsoon (Trace elements) Sc
368
Ti
V
Ni
Cu
Zn
As
Mo
Sn
Cd
Ba
W
Pb
U
Fe
Sc
1
Ti
.656
1
V
.362
.489
1
Ni
.272
.318
.397
1
Cu
.239
.231
.313
.438
1
Zn
.051
.117
.076
.357
.613
1
As
.242
.309
.309
.244
.062
.093
1
Mo
.057
.481
.455
.398
.230
.242
.349
1
Sn
-.220
-.184
-.163
-.077
.107
.013
-.303
-.169
1
Cd
.203
.292
.057
.243
.495
.390
.028
.161
.119
1
Ba
.162
.175
.369
.492
.155
.171
.179
.311
-.168
-.107
1
W
-.229
-.187
-.228
-.256
-.102
-.098
-.135
-.230
.112
-.056
-.262
1
Pb
-.143
-.106
-.208
-.234
-.124
-.090
-.234
-.203
.031
-.176
-.190
.121
1
U
.088
.067
.027
.016
.042
.006
-.069
-.242
-.087
-.002
-.038
-.093
-.052
1
Fe
.192
.102
.200
.166
.224
.025
.513
.151
-.050
.038
.207
.045
-.213
-.029
*Values in bold indicate they have significant relationship
23
1
ACCEPTED MANUSCRIPT
369 370
Fig. 6a Plot pH versus As, 6b Plot NO-3 versus As, 6c Plot K+ versus As, 6d Plot HCO-3 versus As, and 6e Plot
371
Fe versus As
24
ACCEPTED MANUSCRIPT 372
4.5.2 Principal Component Analysis
373
Principal Component or Factor Analysis was done to evaluate the compositional relationship between
374
hydrochemical parameters of water samples; factors affecting each other variables and to identify hidden
375
geochemical process, extent and source of pollution in groundwater samples. Table.6a and b depicts the PCA results
376
of both pre and post-monsoon respectively which includes loadings, Eigenvalues, the percentage of variance and
377
cumulative variance. In the present study, the data were subjected to Varimax rotation with Kaiser Normalization to
378
make complex and tedious data structure into simpler one called factor scores. And the factor scores, whose
379
Eigenvalues were greater than and equal to 1 is considered. The factor score with greater Eigenvalue is capable of
380
explaining the underlying hydrochemical process.
381
Based on the above considerations five independent factors both in pre and the post-monsoon have been
382
extracted. It explains the total variance of about 56.684 and 49.607% in pre and post-monsoon respectively (table 6a
383
and 6b).
384
In pre-monsoon, factor-1 with 13.594% variance show the highest loading of variables such as EC, TDS,
385
Na+, K+, Ca2+, Mg2+, SO42-, NO3-, Cl-, As and Fe. The strong relationship among TDS, Na+, Ca2+, Mg2+, SO42-, Cl-
386
indicate seawater ingress and ion exchange process during pre-monsoon. In addition, the negative correlation of As
387
and Fe with aforesaid variables, explains that the influence of seawater ingress in the release of As into groundwater
388
system is insignificant. Factor-2 shows a variance of 12.433% with highest loadings of parameters viz. pH, Eh, EC,
389
K+, HCO-3, V, As, Mo and Fe which clearly explains about the mechanism of As release into groundwater. Reducing
390
condition of an aquifer and presence of organic matter can be inferred from the association of Eh, Fe and V (Oinam et
391
al, 2011). Association of As and Fe indicate presence of Fe and As-bearing minerals. Moreover moderate relationship
392
of As with K+ and HCO3- indicates the role of agricultural activities and microbial reduction leading to mobility of As
393
in groundwater (Nickson et al, 2000; McArthur et al, 2001). Factor3 shows higher loadings for variables such as NO-
394
3,
395
groundwater chemistry such as lack of proper sewage system; discharge from chemical industries; usage of chemical
396
fertilizers and pesticides. Factor 4 shows a total variance of 10.337% with highest positive loadings to Ni, Sn, W and
397
Pb indicates a marshy and loamy environment; dissolution of minerals comprising those elements, alloy industries,
398
discarded batteries and diesel fuel used in farming activities and paint industries of the study area. Factor-5 with a
Sc, Ti, Cu, Cd with a total variance of 10.913%. Such association implies anthropogenic sources affecting
25
ACCEPTED MANUSCRIPT 399
total variance of 9.407% shows highest loadings to variables viz. Ba and U imply they are mostly derived from the
400
geogenic sources.
401
In post-monsoon, factor-1 accounts for 16.169% variance displays maximum loadings to major cations and
402
anions like Ca2+, Mg2+, SO42, Cl- and HCO-3. Strong correlation among major cations and anions indicates rock-water
403
interaction which acts as a dominant process governing groundwater chemistry in the study area. Correlation of Ca2+,
404
Mg2 and HCO-3 indicates dissolution of detrital calcite, detrital dolomite and ferromagnesian minerals. A high loading
405
of SO42 and Cl- implies long residence time due to sluggish groundwater flow; anthropogenic sources like sewage and
406
domestic waste (Saha et al, 2009) and secondary salinity. High Cl- concentrations are due to Cl- trapped within the
407
clay lenses thereby reducing flushing rate of the aquifer and it gradually enters the aquifer system. Factor-2 explains
408
the variance of about 9.686% and exhibits maximum loadings of variables viz. Sc, Ti, V, As, Mo and Fe. Association
409
of As, Fe, V and Mo (i.e. redox-sensitive elements) with strong to moderate loadings suggests reductive dissolution
410
of Fe hydroxides; degradation of organic matter; near neutral pH condition (Smedley et al, 2017). Factor-3 exhibits
411
variance of about 8.430% with maximum loadings of variables such as pH, EC, TDS and Ba. Higher loadings of TDS
412
and EC indicates salinization index (Liu et al, 2003) however moderate correlation of Barium implies dissolution of
413
carbonate rocks and sandstone rich in minerals like barite, witherite, barium hydroxides, etc. (Tudorache et al, 2009);
414
presence of peat, lignite and petroleum deposits in study area which might be the contributing factor (Fenelon, 1998).
415
Marine sediments of the study area are found to be the major supplier of Ba (Kontak et al, 2006; Méndez-Rodríguez
416
et al, 2013). Factor-4 exhibits total variance of about 8.112%. It shows highest negative loadings to pH, W and
417
positive loadings to Eh, K+, NO-3, Cd and U. Higher to moderate loadings of NO-3 and K+ signifies influence of
418
agricultural activities, usage of fertilizers and mineralization of groundwater with the aid of microbes. Lack of
419
sanitation and presence of a microorganism such as E. coli, Staphylococcus aureus, Proteus vulgaris, Salmonella
420
typhii, and Pseudomonas aeruginosa in the faecal matter, as reported by Saha and Kumar (2006), leads to elevated
421
concentration of nitrate in groundwater. Factor 5 accounts for total variance of 7.3% and shows maximum loadings to
422
Cu, Zn, Cd and negative loadings to Sn indicates anthropogenic sources like industrial and agricultural activities;
423
leaching from the storage tanks and/or distribution pipes (Al-Saleh et al, 1998; Brima et al, 2014).
424 425
26
ACCEPTED MANUSCRIPT 426
Table. 6a Principal Component Matrix of Pre-Monsoon after Varimax rotation with Kaiser Normalization Variables
427
Rotated Component Matrix Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
pH
-.161
.888
.026
-.138
-.003
Eh
.190
-.877
.004
.030
-.018
EC
.371
.316
.255
-.041
.279
TDS
.660
.002
.199
.047
.072
Na+
.893
.040
.031
-.013
.072
K+
.339
.327
.144
-.119
-.274
Ca2+
.917
.019
.023
-.025
.048
Mg2+
.789
-.192
.080
.016
.014
Cl-
.736
.103
.071
.032
.047
SO2- 4
.522
.266
-.091
-.032
.122
HCO-3
.279
.447
.225
.004
.267
NO-3
.016
-.164
.532
-.072
.179
Sc
.085
.037
.755
-.125
.169
Ti
.030
-.029
.930
.009
-.071
V
.226
.392
-.132
.075
.269
Ni
.098
-.015
.234
.742
-.037
Cu
-.045
.157
.859
.282
-.096
Zn
-.025
.001
.024
.098
-.126
As
-.589
.310
-.038
.068
.095
Mo
-.010
.326
-.122
.176
-.173
Sn
-.069
-.027
-.061
.954
-.031
Cd
-.022
.002
.928
.042
-.053
Ba
.094
-.028
-.223
-.103
.347
W
-.045
-.022
-.060
.934
-.060
Pb
-.118
.039
-.050
.890
-.041
U
.185
.123
-.060
-.004
.636
Fe
-.588
.364
-.051
.165
.113
Eigen Value
3.67
3.36
2.95
2.79
2.54
Variance (%)
13.59
12.43
10.91
10.35
9.41
Cumulative Variance (%)
13.59
26.02
36.93
47.28
56.68
*Values in bold indicate they have significant relationship
428 429 27
ACCEPTED MANUSCRIPT 430
Table.6b Principal Component Matrix of Post-Monsoon after Varimax rotation with Kaiser Normalization Variables
431
Rotated Component Matrix Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
pH
-.017
.089
.377
-.417
.034
Eh
-.044
-.295
-.159
.681
-.228
EC
.140
.152
.867
.043
.004
TDS
.140
.149
.904
-.083
-.013
Na+
.261
-.118
.241
.130
-.128
K+
-.009
-.300
.041
.392
.170
Ca2+
.951
.037
.049
.079
-.011
Mg2+
.923
.030
.092
.070
-.089
Cl-
.964
.027
.002
.002
-.015
SO2-4
.879
.046
.171
.020
.044
HCO-3
.848
.010
-.116
-.243
.122
NO-3
-.033
.137
.064
.691
.218
Sc
-.002
.600
-.027
.092
.232
Ti
.062
.848
-.016
.014
-.027
V
-.088
.753
.170
-.081
.167
Ni
.074
.191
.296
.281
.132
Cu
-.049
.125
.006
.026
.851
Zn
-.014
-.145
.044
-.228
.330
As
-.085
.343
-.138
-.258
.136
Mo
.169
.598
.185
-.028
-.151
Sn
-.104
-.005
-.099
-.068
-.351
Cd
-.053
.199
-.209
.397
.561
Ba
-.028
-.051
.357
-.008
.087
W
.006
-.309
.002
-.498
.105
Pb
.018
.028
-.155
-.139
-.073
U
.036
-.071
.071
.412
-.046
Fe
-.070
.603
.123
-.105
.095
Eigen Value
4.37
2.62
2.25
2.19
1.97
Variance (%)
16.17
9.67
8.34
8.11
7.30
Cumulative Variance (%)
16.17
25.86
34.20
42.31
49.61
*Values in bold indicate they have significant relationship
432 433 28
ACCEPTED MANUSCRIPT 434
4.6 Arsenic Speciation in Groundwater (Pourbaix Diagram)
435
A Pourbaix diagram is constructed to depict the relationship between pH and Eh over As species in
436
groundwater system (Hundal et al, 2007). With respect to changes in pH and Eh, the oxidation state and mobility of
437
arsenic vary. Arsenic can be mobilized under wide pH range from 6-9. However, in the case of the study area, the
438
higher concentration of arsenic (>10 µg/L) is found to occur at neutral pH range of 5.99 – 8.56 (Fig. 6a). Arsenious
439
acid is commonly found at very low pH i.e. acidic condition. Under the oxidizing condition, H2AsO-4 species is
440
known to occur at low pH whereas H2AsO4 and AsO4 occur in acidic and alkaline pH respectively. At pH less than 9,
441
neutral arsenic species H3AsO3 (As(III)) occurs both in oxidizing and reducing condition. In general, arsenate
442
(As(V)) predominates in the oxidizing environment like surface water. However, As(III) predominates under
443
reducing condition i.e. organic-rich environment (Oremland et al, 2003). When compared to As(V) the sorption
444
capacity of As(III) onto minerals like ferrihydrite and goethite is less. Thus As(III) is highly mobile and found to
445
occur in the aqueous system. In the case of the study area, dominant arsenic species is H3AsO3 indicating the
446
reducing environment (Fig. 7).
447 448
Fig.7 Eh-pH (Pourbaix) diagram for aqueous arsenic species (As-O2-H2O, 298K, 1atm)
449 29
ACCEPTED MANUSCRIPT 450
4.7 Source and Mechanism for Arsenic in Groundwater
451
Several studies carried out on arsenic contamination of groundwater on a global scale, point mainly towards
452
geogenic origin followed by anthropogenic activities. And the major geological processes responsible for such
453
contamination are 1. Water table fluctuation and consequent pyrite oxidation (and other sulfide minerals) i.e.
454
Oxidative Dissolution. 2. Competitive exchange of As with other ions like PO2-4, NO-3 and HCO3-. 3. Reductive
455
dissolution of As-bearing minerals and Fe-oxyhydroxides in the presence of organic matter.
456
If process 1 is expected to be the dominant mechanism for As release into groundwater, then there should
457
exist a positive correlation between Fe, SO42- and As. But in the case of study area there is no such relationship and
458
hence this mechanism is not considered responsible for arsenic contamination in the study area.
459
In the second concept it is stated that As in aquifer sediments are replaced by other ions like PO2-4, NO-3 via
460
application of fertilizers enriched in those ions. In addition to above activities, weathering of K+ bearing minerals
461
may also cause exchange of As in aquifer sediments. Samples collected during pre-monsoon show significantly
462
moderate correlation between K+ and As which indicates that this process plays a minor role in the study area (Fig.
463
7b). Also, exchange of As and HCO3- during the post-monsoon also play a role in the study area.
464
According to the third process, there should exist reducing condition (negative Eh); neutral pH; As-bearing
465
minerals; Fe-oxyhydroxides and organic matter. In the presence of all the above conditions in the aquifer system,
466
there occurs reductive dissolution of As-bearing minerals and Fe-oxyhydroxides. It also keeps As in mobile
467
condition. In addition to the above-said factors, the strong correlation between As and Fe depicts that reductive
468
dissolution mechanism plays a vital role in the release of As into groundwater in the study area. XRD analysis of bore
469
well sediments collected from study area shows the presence of As and Fe bearing minerals such as Pyrite, Realgar,
470
Arsenolite, Claudetite, Scorodite, Covellite, Enargite and Prosstite which was already reported by Nathan et al, 2012.
471
Borewells at northern and southern part of the study area are found to be polluted by arsenic. The higher
472
concentration of arsenic in groundwater in the northwestern part of study area might be due to the presence of marine
473
sediments rich in organic material which on dissolution released arsenic into groundwater. However, in the southern
474
part, there are alluvium, peat and lignite deposits and intense agricultural activities which act as a major contributor
475
for arsenic in groundwater. During POM the increase of water table leads to reducing condition of the aquifer which
30
ACCEPTED MANUSCRIPT 476
is responsible for the dissolution of minerals. In PRM there is a considerable decrease in concentration of arsenic due
477
to its sorption capacity over precipitated Fe-oxyhydroxides.
478
Conclusions and Recommendations
479
Studies on contamination of groundwater with respect to arsenic are done widely all over the world because
480
of its toxic effects on human health. Pre and post-monsoon groundwater samples were collected from coastal aquifers
481
of the Puducherry region and chemometric tool was used to study the status of arsenic contamination, its source and
482
mechanism controlling the release of As into groundwater. The analysis reveals that 13.64 and 11.50% of
483
groundwater samples were contaminated by arsenic during POM and PRM respectively. Northwestern and southern
484
part of the study area is highly contaminated by arsenic. The Piper diagram depicts the following major
485
hydrochemical facies in the study area: Na-K-Cl-SO4; Ca-Cl and Ca-Mg-Cl- SO4 type in pre-monsoon and Na-K-Cl-
486
SO4; mixed Ca-Na-HCO3; Ca- HCO3 and mixed Ca-Mg-Cl type in post monsoon. From the Gibbs diagram, it is
487
inferred that rock-water interaction is the major process governing the hydrochemistry of groundwater in the study
488
area.
489
Based on the relationship between pH and Eh (Pourbaix Diagram), it is established that H3AsO3 is the major
490
arsenic species occurring in groundwater under a reduced condition of the aquifer in the study area. From PHREEQC
491
modelling it is concluded that mineral phase's viz. Ferric oxides and hydroxide are the possible sorbing site for As in
492
study area. Such minerals on reductive dissolution discharge arsenic into the groundwater. The strong correlation
493
between in-situ parameters and major ions during pre and post monsoon suggest that groundwater chemistry of study
494
area is controlled primarily by geogenic processes like rock-water interaction; ion exchange; mineral dissolution and
495
seawater intrusion (as highlighted in Spearman Correlation and PCA). Chemistry of groundwater is also controlled to
496
some extent by human activities like over pumping, industrial accomplishments, use of chemical fertilizers in
497
agricultural land and lack of sewage system (as highlighted in Spearman Correlation and PCA).
498
Statistical analysis (Spearman Correlation and PCA) obviously reveals that organic-rich marine sediments
499
(peat, lignite and agricultural waste), As and Fe bearing minerals are the source and are accountable for the reductive
500
dissolution and release of arsenic into aquifer system. It is also evident from the association of Eh and pH; As, K+,
501
HCO3-, Fe and other trace metals (Sc, Ti, V, Ni, Cd and Mo).
31
ACCEPTED MANUSCRIPT 502
This study strongly recommends for regular monitoring of groundwater. Besides, health risk assessment in
503
relation to arsenic contamination needs to be done for the study area.
504
Acknowledgement: We sincerely thank University Grants Commission (UGC), New Delhi for supporting the
505
current work financially through major research project [F.No. 41-1035/2012 (SR); date: 23.07.2012]. Also, we
506
extend our heartfelt thanks to Department of Earth Sciences, Department of Ecology and Environmental Sciences and
507
Central Instrumentation Facility of Pondicherry University for providing necessary facilities for analysis. We also
508
acknowledge the editor and anonymous reviewer for their cherished suggestions for bringing this research paper to
509
the current level.
510
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Highlights: 1. 2. 3. 4. 5.
Current investigation deals with occurrence, distribution, source and mechanism of arsenic mobility in groundwater of Puducherry region. Major sources for Arsenic contamination in groundwater are As, Fe bearing minerals and organic matter present in the marine and fluvial sediments of study area. Reductive Dissolution is the dominant mechanism contributing As into groundwater. Groundwater in northern and southern part of study area is contaminated by Arsenic. Arsenic in groundwater is of geogenic origin.