Research Article Assessment of Groundwater Quality along...

Hindawi Publishing CorporationJournal of ChemistryVolume 2013 Article ID 672372 10 pageshttpdxdoiorg1011552013672372

Research ArticleAssessment of Groundwater Quality along the Cooum RiverChennai Tamil Nadu India

N S Elangovan1 and M Dharmendirakumar2

1 Department of Civil Engineering Jerusalem College of Engineering Chennai Tamil Nadu 600 100 India2Department of Applied Science and Technology Alagappa College of Technology Anna University ChennaiTamil Nadu 600 025 India

Correspondence should be addressed to M Dharmendirakumar mdkumarannaunivedu

Received 26 November 2012 Accepted 28 January 2013

Academic Editor Stefan Tsakovski

Copyright copy 2013 N S Elangovan and M Dharmendirakumar This is an open access article distributed under the CreativeCommons Attribution License which permits unrestricted use distribution and reproduction in any medium provided theoriginal work is properly cited

Groundwater quality in Chennai city along the Cooum river during the premonsoon (JunendashJuly) and postmonsoon (DecndashJan) forthree years from 2009 to 2011 was analyzed Groundwater samples were collected from 20 bore wells on either side of the riverTheanalysis focused on the determination of seven specific water quality parameters namely pH EC TDS BOD COD Na and Pbusing standard procedures The statistical analysis like the mean and standard deviation coefficient of variance and correlationandmultilinear regression analysis of the obtained data were carried outThe analysis of the collected samples reveals that the statedwater quality parameters have not complied with theWHO standards and the water is not fit for drinking and domestic purposesThe correlation and multilinear regression analyses suggest that the conductivity has a significant correlation with the other sixconsidered water quality parameters

1 Introduction

Groundwater is a natural precious resource that sustainsthe basic needs of all living creatures It cannot be createdor supplemented electronically or hydrologically or by anyother means [1 2] People living on earth suffer withoutpotable water though the earth is covered by 75 of waterGroundwater serves as a vital source for domestic agricul-tural and industrial uses [3 4] In Chennai city the growingurbanization and rapid industrialization lead to the gener-ation of huge quantities of waste water The uncontrolleddischarge of sewage garbage and industrial effluents intothe downstream of the Cooum river percolates through thesoil and contaminates the Groundwater sources As per theWHO [5] about 80 of all the diseases in human beingsare caused by impure water The Cooum river originatesin Tiruvallur district traversing about 70 km and ends inChennai city draining into the Bay of Bengal Of this 16 kmthe study area falls within Chennai city In Chennai districtthe river flows through three corporation zones namelyKilpauk Nungambakkam and Triplicane

The Cooum river is 80 more polluted than the treatedsewage [6] Hence a periodic assessment of the Ground-water becomes necessary to ensure the suitability of waterfor drinking Considering these aspects the present studyfocuses on analyzing the specific water quality parameters ofsome groundwater samples on either side of the Cooum riverwithin the city limits as shown in Figure 1

2 Experimental

21 Study Area The study area along the Cooum river inChennai district of Tamil Nadu India lies between latitude13∘4101584051810158401015840 north and longitude 80∘17101584090610158401015840 east The Cooumriver is the starting point where the municipalities and townPanchayats that lie on either side of the river dischargeboth treated and untreated industrial effluents and domesticsewage in addition to the bathing of animals human activi-ties washing of vehicles directly or by feeder drains into the16 km length of the Cooum river [7] People living near thisarea depend on bore wells for their daily requirement Theliterature survey reveals that no Groundwater studies on bore

2 Journal of Chemistry

Table 1 Detail of sample sites along the left side (SL) of the Cooum river

Site no Area Latitudelongitude Depth of bore well (m) Apparent water qualitySL1 Arumbakkam 13∘4101584030810158401015840N 80∘121015840294310158401015840E 33 Odorless colorlessSL2 Nungambakkam 13∘31015840572710158401015840N80∘131015840563710158401015840E 34 Odorless colorlessSL3 Chintadripet 13∘80∘14101584055N 421015840101584031015840596010158401015840E 34 Odorless colorlessSL4 Chintadripet 13∘41015840206410158401015840N80∘161015840112710158401015840E 35 Odorless colorlessSL5 Nungambakkam 13∘31015840327210158401015840N80∘141015840158210158401015840E 33 Odorless colorlessSL6 MMDA Colony 13∘31015840594210158401015840N80∘121015840495410158401015840E 35 Odorless colorlessSL7 Choolaimedu 13∘31015840346710158401015840N80∘131015840326210158401015840E 33 Odorless colorlessSL8 Chinmaya Nagar 13∘31015840428910158401015840N80∘111015840441510158401015840E 34 Odorless colorlessSL9 Vadapalani 13∘31015840234210158401015840N80∘121015840200910158401015840E 33 Odorless colorlessSL10 Gopalapuram 13∘3101584021110158401015840N80∘151015840227610158401015840E 32 Turns yellowish

Table 2 Detail of sample sites along the right side (SR) of the Cooum river

Site no Area Latitudelongitude Depth of bore well (m) Apparent water qualitySR1 Aayiram Vilakku 13∘31015840597210158401015840N80∘151015840283810158401015840E 34 Odorless colorlessSR2 Anna Salai 13∘41015840271310158401015840N80∘161015840514810158401015840E 33 Odorless colorlessSR3 Anna Nagar 13∘41015840491510158401015840N80∘121015840161210158401015840E 33 Odorless colorlessSR4 Anna Nagar East 13∘5101584097010158401015840N80∘131015840131710158401015840E 33 Odorless colorlessSR5 Periamet 13∘41015840559510158401015840N80∘16101584085210158401015840E 34 Odorless colorlessSR6 Anna Nagar 13∘51015840131310158401015840N80∘121015840126310158401015840E 33 Odorless colorlessSR7 Kilpauk 13∘41015840532410158401015840N80∘14101584031710158401015840E 33 Odorless colorlessSR8 Egmore 13∘41015840305910158401015840N80∘15101584016210158401015840E 32 Odorless colorlessSR9 Periamet 13∘41015840524910158401015840N80∘151015840334710158401015840E 33 Odorless colorlessSR10 Purasavakkam 13∘51015840151210158401015840N80∘141015840507110158401015840E 32 Odorless colorless

India

Tamil Nadu

Figure 1 A map showing sampling locations along the Cooum river

wells close to the river were done so far Hence the study hasbeen carried out on 20 different sites that cover the area of16 times 2 km which includes 10 sites on the left side of the riverand 10 sites on the right side of the river to assess the impactof the percolation of the river water flow on the GroundwaterThe location of the sample sites was given in Tables 1 and 2

22 Collection of Samples Water samples were collected fromthe bore wells at a depth of 32ndash35m below the ground levelat 20 locations along the Cooum river Two water sampleswere collected per year per sampling station covering bothpre- and postmonsoon seasons A total of 120 samples weretested and analyzed for a period of three years (2009ndash2011)

The collected samples were stored in cleaned and well-dried brown polythene glass bottles (25 L) with necessaryprecautions (APHA 1995) [8] These bottles were labeledwith respect to the collecting points date and time in orderto avoid any error between collection and analysis All thesample collections were immediately preserved in an iceboxand brought to the laboratory for determining the specificwater quality parameters

23 Sample Analysis The collected samples were analyzedfor specific water quality parameters such as pH electricalconductivity (EC) total dissolved solids (TDS) biochemicaloxygen demand (BOD) chemical oxygen demand (COD)

Journal of Chemistry 3

Table 3 Methods used for analysis of quality parameters for thewater samples

Quality parameters studied Methods usedpH pH meterElectrical conductivity Conductivity meterTotal dissolved solids Evaporation methodBiochemical oxygen demand Modified Winklerrsquos methodChemical oxygen demand Titrated with an excess of K2Cr2O7

Sodium Flame photometryLead Atomic absorption spectrometry

sodium (Na) and lead (Pb) using standard methods astabulated in Table 3TheWorld Health Organisation (WHO)permissible limit of drinking water quality parameters werespecified in Table 4 The observed values of the above speci-fied water quality parameters along the left and right sides ofthe river were shown in Figures 2(a)ndash8(a) and 2(b)ndash8(b) forthe pre- and postmonsoon seasons Tables 5 and 6 summarizethe maximum minimum mean and standard deviationsand coefficient of variance (CV) found in the differentGroundwater samples for the pre- and postmonsoon seasonsrespectively The correlation and multi linear regressionanalyses have also been carried out to find the correlationbetween the water quality parameters and are listed in Tables7 and 8

3 Results and Discussion

31 pH pH is a measure of the concentration of hydrogenions (H+) in waterWater with a pH value below 7 is said to beacidic and water with a pH value above 7 is basic or alkalinein nature [9 10] For fish and aquatic life the protectionlimit of the pH ranges from 60 to 90 The experimentalvalues of the water samples were found to be between 671and 831 during the premonsoon and between 66 and 77during postmonsoonwhich are within the prescribed limit assuggested by WHO (Figures 2(a) and 2(b)) This shows thatthe pHof thewater sampleswould not affect the domestic andaquatic system The high pH value during the premonsoonindicates the surface water contamination resulting from thepenetration into the Groundwater The mean value of pH upto 7548 plusmn 036026 and 72545 plusmn 0284225 during the pre-and postmonsoon seasons indicates slight alkalinity naturepresumably due to the seepage of waste water from domesticuse and industries The maximum variance value during thepremonsoon CV = 5948777 was found to be higher thanthat of the postmonsoon season that is CV = 4050786

32 EC Electrical conductivity is ameasure of concentrationof ionized substances that convey electric current in water[11]The higher EC indicates how strong is current flow basedon the amount of total dissolved salts In the present studyEC values were found within the range of 498ndash2371120583Scm

Table 4 Water quality parameters with respect to the WHOstandards

S no Parameter WHO1 pH 70ndash852 Electrical conductivity (EC) (120583Scm) 14003 Total dissolved solids (mgL) 1000

4 Bio chemical oxygen demand (BOD)(mgL) 5

5 Chemical oxygen demand (COD)(mgL) 10

6 Sodium (mgL) 2007 Lead 001

and 508ndash2207120583Scm during pre- and postmonsoon seasons(Figures 3(a) and 3(b)) The mean SR1ndashSR10 for the pre-and postmonsoon of 2009ndash2011 value of EC upto 152375 plusmn55989 120583Scm and 149005 plusmn 46566 120583Scm during pre- andpostmonsoon shows that the higher concentration of EC wasdue to the higher amount of TDS The analysis of the studyperiod from 2009 to 2011 shows the increasing level of EC thatenhances the level of the ionized substances of the water Themaximum variance value during premonsoon CV = 4211was found to be higher than that of the postmonsoon seasonthat is CV = 333672

33 TDS TDS is a measure of the combined concentrationof cations and anions [12] The major components of TDSinclude bicarbonate (HCO

3

minus) sulphate (SO4

2minus) hydrogen(H+) silica (SiO

4) chlorine (Clminus) calcium (Ca+2) mag-

nesium (Mg+2) sodium (Na+) potassium (K+) nitrates(NO3

minus) and phosphate (PO4

3minus) The TDS of the Ground-water is mainly due to the vegetable decay and the disposalof effluents from industries The TDS values of the samplingsites varied from 987 to 2892mgL and 905 to 2716mgLduring the pre- and postmonsoon seasons The presentinvestigation shows that all the samples exceeded the limitprescribed by WHO except the sample of the site SR10(Figures 4(a) and 4(b)) The mean values of the TDS werefound to be 20735 plusmn 58585mgL and 20073 plusmn 58192mgLduring the pre- and postmonsoon seasons This reveals thehigh concentration of the TDS value during the premonsoondue to the evaporation of waterTheMaximumvariance valueduring the premonsoon CV = 3038904 was found to behigher than that of the postmonsoon season that is CV =3064991

34 BOD The BOD values indicate the amount of organicwaste present in the water [13] The analyzed BOD valuesvaried from 424 to 856mgL and from 43 to 897mgLduring the pre- and postmonsoons indicating that thevalue of BOD is higher during the postmonsoon seasonpresumably due to the percolation of industrial effluents anddomestic wastes into the Groundwater The sampling sitesSL1 SL3 SL4 SR1ndashSR3 SR8 showed higher BOD values thanthose permitted by WHO (Figures 5(a) and 5(b)) The mean


02468

10

SL1 SL2 SL3 SL4 SL5 SL6 SL7 SL8 SL9 SL10

pH

Samples

2011 postmonsoon 2011 premonsoon2010 postmonsoon 2010 premonsoon2009 postmonsoon 2009 premonsoon

Variation of pH pre- and postmonsoon (2009ndash2011)

(a)

02468

10

SR1 SR2 SR3 SR4 SR5 SR6 SR7 SR8 SR9 SR10

pH

Samples

pH 2011 postmonsoon pH 2011 premonsoonpH 2010 postmonsoon pH 2010 premonsoonpH 2009 postmonsoon pH 2009 premonsoon


(b)

Figure 2 (a) Observations of pH in water from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011 (b) Observations of pH inwater from the sites SR1ndashSR10 for the pre- and postmonsoon of 2009ndash2011

0500

1000150020002500


EC

Samples

Variation of EC pre- and postmonsoon (2009ndash2011)


(a)

0500

100015002000


EC

Samples



(b)

Figure 3 (a) Observations of EC in water from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011 (b) Observations of EC inwater from the sites SR1ndashSR10 for the pre- and postmonsoon of 2009ndash2011

value of BOD was 68995 plusmn 134mgL and 6755 plusmn 127mgLduring the pre- and postmonsoons which shows the presenceof soluble salts in the sampling sites The maximum variancevalue during the premonsoon of CV = 2038 was found tobe higher than the postmonsoon seasons CV = 1932

35 COD The COD level indicates the amount of toxicityin water [14] The observed values of the COD in both theseasons from all the sampling sites were found to exceed thepermissible limit (Figures 6(a) and 6(b)) The analyzed CODvalues of the sampling sites varied from 111 to 248mgL andfrom 103 to 246mgL for the pre- and postmonsoon seasonsThe observed COD value was higher during premonsoonthe season presumably due to the decreased flow of waterduring this period The mean value of 1972 plusmn 39mgL and18645plusmn399mgL indicates that the COD values were abovethe desirable limit during the pre- and postmonsoon seasonsThe maximum variance value during the premonsoon CV= 203865 was found to be higher than the postmonsoonseasons CV = 1932 The analyzed COD values were foundto be higher than the BOD values This indicates the ample

presence of chemically oxidizable substances of which themajority are nonbiodegradable [15]

36 Na The higher concentration of sodium in the Ground-water causes cardiovascular diseases and toxemia in pregnantwomen [16] The sodium of the water samples collected liesin the range of 130ndash313mgL and 120ndash313mgL during thepre- and postmonsoon seasons The mean values of 230 plusmn5754mgL and 2163 plusmn 5822mgL during the pre- andpostmonsoon seasons show that domestic discharge maycontribute to increase the sodium content through leaching[17]The present analysis shows that the sampling points SL1ndashSL4 SR1ndashSR5 SR8 SR9 (Figures 7(a) and 7(b)) exceed thepermissible value The maximum variance value during thepremonsoon of CV = 2501 was found lower than that ofthe postmonsoon season that is CV = 2814

37 Pb Lead (Pb) is a heavy metal gets into the environ-ment through waste water or solid waste disposal Highconcentration of lead causes kidney damage bone damageand nervous disorder [18] The lead concentrations in


0500

100015002000250030003500


TDS

Samples

Variation of TDS pre- and postmonsoon (2009ndash2011)


(a)

0500

10001500200025003000


TDS

Samples



(b)

Figure 4 (a) Observations of TDS in water from the sites SL1ndashSL10 for the pre- and postmonsoons of 2009ndash2011 (b) Observations of TDSin water from the sites SR1ndashSR10 for the pre- and postmonsoon of 2009ndash2011

02468

10


BOD

Samples

Variation of BOD pre- and postmonsoon (2009ndash2011)


(a)

02468

10


BOD

Samples



(b)

Figure 5 (a) Observations of BOD in water from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011 (b) Observations of BODin water from the sites SR1ndashSR10 for the pre- and postmonsoon of 2009ndash2011

05

1015202530


COD

Samples

Variation of COD pre- and postmonsoon (2009ndash2011)


(a)

05

1015202530


COD

Samples



(b)

Figure 6 (a) Observations of COD in water from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011 (b) Observations of CODin water from the sites SR1ndashSR10 for the pre- and postmonsoon of 2009ndash2011

the samples were found to be between 0025 and 0087mgLand between 003 and 0083mgL for the pre- and post-monsoon seasons respectively (Figures 8(a) and 8(b)) Thepresent study shows that all the samples obtained fromthe adjoining bore wells were above the permissible limit

the mean value of Pb is above the limit due to the seepageof the Cooum water into the Groundwater and indicatsits toxicity during the pre- and postmonsoon of seasons(00642plusmn0014mgL and 00578plusmn0014mgL)Themaximumvariance found during the postmonsoon of CV = 2680


Table 5 Statistics of three years (2009ndash2011) groundwater quality datamdashpremonsoon

PremonsoonParameter Year pH EC (120583Scm) TDS (mgL) BOD (mgL) COD (mgL) Na (mgL) Pb (mgL)

2009 831 2173 2677 834 242 287 0081Max 2010 826 2296 2713 835 246 303 0083

2011 83 2371 2892 856 248 313 00872009 685 498 987 439 133 130 0025

Min 2010 671 631 1048 424 111 137 0032011 704 583 1010 464 118 150 00362009 751 1355 189415 68135 1873 21975 00585

Mean 2010 74185 151595 2029 674 18755 22655 00552011 7548 152375 20735 68995 1972 230 006422009 041391 570724 575614 127868 34278 5318 001494

Std 2010 044131 53677 577915 137405 40111 55006 00145672011 036026 559887 585852 134849 39107 57544 00144682009 551145 4211985 3038904 1876686 1830112 2420023 2553846

CV 2010 59487 3540816 2848275 203865 2138683 2540013 26485452011 47729 3674402 2825426 1954475 1983114 2501913 2253583

050

100150200250300350


Na

Samples

Variation of Na pre- and postmonsoon (2009ndash2011)


(a)

050

100150200250300350


Na

Samples



(b)

Figure 7 (a) Observations of Na in water from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011 (b) Observations of Na inwater from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011

0002004006008

01


Pb

Samples

Variation of Pb pre- and postmonsoon (2009ndash2011)


(a)

0002004006008

01


Pb

Samples



(b)

Figure 8 (a) Observations of Pb in water from the sites SL1ndashSL10 for the pre- and postmonsoon of 2009ndash2011 (b) Observations of Pb inwater from the sites SR1ndashSR10 for the pre- and postmonsoon of 2009ndash2011


Table 6 Statistics of three years (2009ndash2011) groundwater quality datamdashpostmonsoon

PostmonsoonParameter Year pH EC (120583Scm) TDS (mgL) BOD (mgL) COD (mgL) Na (mgL) Pb (mgL)

2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599

Table 7 Correlation coefficient (119903) for different water quality parametersmdashpremonsoon

Parameter pH EC TDS BOD COD Na Pb2009 premonsoon

pH 1EC 0251 1TDS 0331 096 1BOD 0217 0831 0785 1COD 0226 0867 0884 0668 1Na 0449 0926 0895 0878 0768 1Pb 0103 0761 0819 0829 0709 0821 1

2010 premonsoonpH 1EC 0437 1TDS 0447 0896 1BOD 0192 0782 0900 1COD 0442 0911 0863 0762 1Na 0238 0811 0941 0932 0731 1Pb 0420 0846 0816 0758 0835 0750 1



Table 8 Correlation coefficient (119903) for different water quality parametersmdashpostmonsoon

Parameter pH EC TDS BOD COD Na Pb2009 postmonsoon


2010 postmonsoonpH 1EC 0363 1TDS 0445 0972 1BOD 0405 0884 0921 1COD 0244 0933 0893 0829 1Na 0333 0846 0886 0809 0762 1Pb 0186 0849 0808 0747 0857 0781 1


was higher than that of the premonsoon season that isCV = 2648

38 Statistical Analysis The statistical relationship betweenthe water quality parameters was examined through theanalysis of the linear correlation method [19 20] Thecorrelation coefficient 119903 between two parameters 119909 and 119910 isdetermined using the following equation

119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)

where 119909 = values of the 119909-variable 119910 = values of the119910-variable 119899 = number of data points

A positive correlation exists when an increase in thevalue of one parameter is associated with a correspondingincrease in the value of another parameter The correlationmatrices for all the samples of three years during pre- andpostmonsoon seasons are listed in Tables 7 and 8 Accordingto the guidelines the correlation is good if 119903 gt 06 andmarginal if 047 lt 119903 lt 06 The conductivity shows asignificant correlation with the other parameters like TDSBOD COD Na Pb with (119903 gt 07610) and (119903 gt 0821)during the pre- and postmonsoon seasons except the pHThecorrelation between the pH and Na (119903 gt 0278) and (119903 gt0333) during the pre- and postmonsoons indicates the levelof bicarbonate and carbonate of sodium in the Groundwater

samples and hence the presence of alkanity of the water [21]TheBODandCODshows a good correlationwith (119903 gt 0668)and (119903 gt 0676) during pre- and postmonsoons The highdegree of association between the TDS and Na (119903 gt 0926amp 119903 gt 0843) during the pre- and postmonsoon seasonsindicates the anthropogenic activities such as dischargeof sewage which percolates and mixes with Groundwater[22]

Multivariate methods like cluster analysis factor analysisprincipal component analysis discriminate analysis neuronnet classification and multiple regression analysis have beensuccessfully used in water quality analysis without much lossof information to a reasonably manageable data set [23ndash25]In the present study the statistical multiple regressionmodelshave been used for predicting the correlation between theindependent variables and the dependent variable Howevermultiple regression is very sensitive to outliers and modelsdeveloped for one area may not be suitable for differentarea [26] Despite its limitations the multiple regression isused to evaluate Groundwater samples since it generatesminimum data set of indicators and is also easy to implementand interpret [27] The six selected independent variablespH TDS BOD COD Na and Pb and a dependent vari-able EC were used as input data in the following multiplelinear regression equation [28 29] Electrical conductivityis selected as a dependent variable based on the correlationanalysis studies The following equation predicts whether


Table 9 Regression equations based on analyzed parameters

Year Regression equation 1198772 value 119865 value

Premonsoon

2009 EC = 36358 lowast pH + 0807 lowast TDS + 107888 lowast BOD + 24851 lowast COD minus 3528 lowast Na + 6124594 lowast Pbminus 1231212

0958 49555

2010 EC = 2818 lowast pH + 0211 lowast TDS minus 94336 lowast BOD + 71715 lowast COD + 2966 lowast Na + 6154062 lowast Pb minus671780

0892 17981

2011 EC = minus184985 lowast pH + 0571 lowast TDS + 66079 lowast BOD + 31193 lowast COD + 0332 lowastNa + 1575589 lowast Pb+ 487066

0945 3707

Postmonsoon

2009 EC = minus86422 lowast pH + 0594 lowast TDS + 4994 lowast BOD + 25715 lowast COD minus 0229 lowast Na + 2456061 lowast Pb+ 306783

0977 91861

2010 EC = minus45855 lowast pH + 0683 lowast TDS minus 30021 lowast BOD + 25132 lowast COD minus 0619 lowastNa + 3254098 lowast Pb+ 119508

0969 676

2011 EC = minus17058 lowast pH + 0495 lowast TDS minus 10607 lowast BOD + 36501 lowast COD minus 0134 lowast Na + 1181900 lowast Pbminus 476028

0969 68523

the dependent variable EC is related to more than oneindependent variable Consider the following

119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883

119899denotes the independent variable 119884

stands for the dependent variable 1205730represents the intercept

1205731 and 120573

119899represents the regression coefficients of the

variablesThe multilinear regression analysis was carried out by

using the IBM Statistical Package for Social Science (SPSS)software The estimated 1198772 value and 119865 values of this modelare represented in Table 9 The high 1198772 (1198772 gt 0892 amp 1198772 gt0969) during the pre- and postmonsoon seasons indicatesthat the conductivity has a very good correlation with theother chosen parametersThe variance ratio of the 119865 values ishigh indicating a significant correlation of EC with the otherparameters

4 Conclusion

The results of the study indicate that the bore wells in theadjoining areas of the Cooum river are highly polluted andhence the groundwater of the study area is unfit for domesticuse The analysis in respect of seven parameters namelypH EC TDS BOD COD Na and Pb reveals that morethan 90 of the water samples have exceeded the drinkingwater permissible limit prescribed by the WHO except thepH The result of the correlation and multilinear regressionanalysis shows that the conductivity has high significantcorrelation with the other parameters The concentrationsof EC TDS COD Na and Pb increased every consecutiveyear compared to the first year of the study period Thisindicates the increase in the pollution load due to theintrusion of domestic sewage and industrial effluents intothe Groundwater Hence consistent monitoring measuresare essential to assess the impact of the percolation ofthe wastewater causing contamination of the groundwater

in the study area and a preventive mechanism coupledwith remedial measures is necessary for the benefit ofmankind

Conflict of Interests

The authors declare no conflict of interests or financialdisclosures relevant to this paper

References

[1] K Brindha and L Elango ldquoHydrochemical characteristics ofgroundwater for domestic and irrigation purposes in Madhu-ranthakam TamilNadu Indiardquo Earth Sciences Research Journalvol 15 no 2 pp 101ndash108 2011

[2] L S Sathiyamurthy ldquoWater managementmdashour ancestors knewit wellrdquoThe Hindu October 2012

[3] A A Jameel and J Sirajudeen ldquoRisk assessment of physico-chemical contaminants in groundwater of pettavaithalai areaTiruchirappalli TamilnadumdashIndiardquo Environmental Monitoringand Assessment vol 123 no 1ndash3 pp 299ndash312 2006

[4] S Rengaraj T Elampooranan L Elango and V RamalingamldquoGroundwater quality in suburban regions of Madras cityIndiardquo Journal of Pollution Research vol 15 no 4 pp 325ndash3281996

[5] WHO Guidelines for Drinking Water vol 1 WHO GenevaSwitzerland 1984

[6] httparticlestimesofindiaindiatimescom[7] P Arockia Sahayaraj and K Ayyadurai ldquoBioaccumulation of

lead in milk of buffaloes from Cooum river belt in ChennairdquoJournal of Environmental Biology vol 30 no 5 pp 651ndash6542009

[8] APHA Standard Methods for Examination of Water andWastewater American Public Health Association WashingtonDC USA 19th edition 1995

[9] R K Trivedy and P K Goel Chemical and Biological Methodsfor Water Pollution Studies Environmental Publication KaradIndia 1986


[10] C C Harilal A Hashim P R Arun and S Baji ldquoHydro-geochemistry of two rivers of Kerala with special reference todrinking water qualityrdquo Ecology Environment and Conserva-tion vol 10 no 2 pp 187ndash192 2004

[11] N Kumar and D K Sinha ldquoDrinking water quality man-agement through correlation studies among various physico-chemical parameters A case studyrdquo International Journal ofEnvironmental Sciences vol 1 no 2 pp 253ndash259 2010

[12] S G Daraigan A S Wahdain A S BaMosa and M H ObidldquoLinear correlation analysis study of drinking water quality datafor AlMukalla City Hadhramout Yemenrdquo International Journalof Environmental Sciences vol 1 no 7 pp 1692ndash1701 2011

[13] K Usharani K Umarani P M Ayyasamy K Shanthi and PLakshmanaperumalsamy ldquoPhysico-chemical and bacteriologi-cal characteristics of Noyyal River and Ground Water Qualityof Perur Indiardquo Journal of Applied Sciences amp EnvironmentalManagement vol 14 no 2 pp 29ndash35 2010

[14] V T Patil and P R Patil ldquoGroundwater quality of openwells and tube wells around amalner town of jalgaon DistrictMaharashtra Indiardquo E-Journal of Chemistry vol 8 no 1 pp 53ndash58 2011

[15] P Raja M A Amarnath R Elangovan and M PalanivelldquoEvaluation of physical and chemical parameters of riverKaveriTiruchirappalli Tamil Nadu Indiardquo Journal of EnvironmentalBiology vol 29 no 5 pp 765ndash768 2008

[16] M C Shah P G Shilpkar and P B Acharya ldquoGround waterquality of Gandhinagar Taluka Gujarat Indiardquo E-Journal ofChemistry vol 5 no 3 pp 435ndash446 2008

[17] C Prabakar K Saleshrani D Dhanasekaran KTharmaraj andK B Askaran ldquoSeasonal variation in phsio-chemical param-eters of Walajapet Vellore district Tamil Nadurdquo InternationalJournal of Current Life Sciences vol 1 no 6 pp 039ndash043 2011

[18] G R Bhagure and S R Mirgane ldquoHeavy metal concentrationsin groundwaters and soils of Thane Region of MaharashtraIndiardquo Environmental Monitoring and Assessment vol 173 no1ndash4 pp 643ndash652 2011

[19] S M Yahya and H N A Aziz-ur-Rahman ldquoAssessment ofseasonal and polluting effects on the quality of River Water byusing regression analysis a case study of River Indus in Provinceof Sindh Pakistanrdquo International Journal of EnvironmentalProtection vol 2 pp 10ndash16 2012

[20] S A Antony M Balakrishnan S Gunasekaran and R KNatarajan ldquoA correlation study of the ground water quality inthe Manali Petroleum Industrial Region in Tamil Nadu IndiardquoIndian Journal of Science and Technology vol 1 no 6 pp 1ndash112008

[21] J K Pathak M Alam and S Sharma ldquoInterpretation ofgroundwater quality using multivariate statistical technique inMoradabad City Western Uttar Pradesh State Indiardquo E-Journalof Chemistry vol 5 no 3 pp 607ndash619 2008

[22] G Raja and P Venkatesan ldquoAssessment of groundwater pol-lution and its impact in and around Punnam area of KarurDistrict Tamilnadu Indiardquo E-Journal of Chemistry vol 7 no2 pp 473ndash478 2010

[23] P Praus ldquoWater quality assessment using SVD-based principalcomponent analysis of hydrological datardquoWater SA vol 31 no4 pp 417ndash422 2005

[24] A F M Alkarkhi ldquoAssessment of surface water throughmultivariate analysisrdquo Journal of Sustainable Development vol1 no 3 pp 27ndash33 2008

[25] MDas AKumarMMohapatra and SDMuduli ldquoEvaluationof drinking quality of groundwater through multivariate tech-niques in urban areardquo Environmental Monitoring and Assess-ment vol 166 no 1ndash4 pp 149ndash157 2010

[26] A Keshavarzi and F Sarmadian ldquoComparison of artificial neu-ral network and multivariate regression methods in predictionof soil cation exchange capacityrdquo World Academy of ScienceEngineering amp Technology vol 72 pp 495ndash500 2010

[27] I Chenini and S Khemiri ldquoEvaluation of ground water qual-ity using multiple linear regression and structural equationmodelingrdquo International Journal of Environmental Science andTechnology vol 6 no 3 pp 509ndash519 2009

[28] ldquoMultiple Regressionrdquo httpordinationokstateeduMULTI-PLEhtm

[29] Abdul Saleem M N Dandigi and K Vijay KumarldquoCorrelation-regression model for physico-chemical qualityof groundwater in the South Indian city of Gulbargardquo AfricanJournal of Environmental Science and Technology vol 6 no 9pp 353ndash364 2012

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Inorganic ChemistryInternational Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal ofPhotoenergy


Carbohydrate Chemistry

International Journal of


Journal of

Chemistry


Advances in

Physical Chemistry

Hindawi Publishing Corporationhttpwwwhindawicom

Analytical Methods in Chemistry

Journal of

Volume 2014

Bioinorganic Chemistry and ApplicationsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

SpectroscopyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Medicinal ChemistryInternational Journal of


Chromatography Research International


Applied ChemistryJournal of



Theoretical ChemistryJournal of


Journal of

Spectroscopy

Analytical ChemistryInternational Journal of


Journal of


Quantum Chemistry


Organic Chemistry International

ElectrochemistryInternational Journal of



CatalystsJournal of


Table 1 Detail of sample sites along the left side (SL) of the Cooum river

Site no Area Latitudelongitude Depth of bore well (m) Apparent water qualitySL1 Arumbakkam 13∘4101584030810158401015840N 80∘121015840294310158401015840E 33 Odorless colorlessSL2 Nungambakkam 13∘31015840572710158401015840N80∘131015840563710158401015840E 34 Odorless colorlessSL3 Chintadripet 13∘80∘14101584055N 421015840101584031015840596010158401015840E 34 Odorless colorlessSL4 Chintadripet 13∘41015840206410158401015840N80∘161015840112710158401015840E 35 Odorless colorlessSL5 Nungambakkam 13∘31015840327210158401015840N80∘141015840158210158401015840E 33 Odorless colorlessSL6 MMDA Colony 13∘31015840594210158401015840N80∘121015840495410158401015840E 35 Odorless colorlessSL7 Choolaimedu 13∘31015840346710158401015840N80∘131015840326210158401015840E 33 Odorless colorlessSL8 Chinmaya Nagar 13∘31015840428910158401015840N80∘111015840441510158401015840E 34 Odorless colorlessSL9 Vadapalani 13∘31015840234210158401015840N80∘121015840200910158401015840E 33 Odorless colorlessSL10 Gopalapuram 13∘3101584021110158401015840N80∘151015840227610158401015840E 32 Turns yellowish

Table 2 Detail of sample sites along the right side (SR) of the Cooum river

Site no Area Latitudelongitude Depth of bore well (m) Apparent water qualitySR1 Aayiram Vilakku 13∘31015840597210158401015840N80∘151015840283810158401015840E 34 Odorless colorlessSR2 Anna Salai 13∘41015840271310158401015840N80∘161015840514810158401015840E 33 Odorless colorlessSR3 Anna Nagar 13∘41015840491510158401015840N80∘121015840161210158401015840E 33 Odorless colorlessSR4 Anna Nagar East 13∘5101584097010158401015840N80∘131015840131710158401015840E 33 Odorless colorlessSR5 Periamet 13∘41015840559510158401015840N80∘16101584085210158401015840E 34 Odorless colorlessSR6 Anna Nagar 13∘51015840131310158401015840N80∘121015840126310158401015840E 33 Odorless colorlessSR7 Kilpauk 13∘41015840532410158401015840N80∘14101584031710158401015840E 33 Odorless colorlessSR8 Egmore 13∘41015840305910158401015840N80∘15101584016210158401015840E 32 Odorless colorlessSR9 Periamet 13∘41015840524910158401015840N80∘151015840334710158401015840E 33 Odorless colorlessSR10 Purasavakkam 13∘51015840151210158401015840N80∘141015840507110158401015840E 32 Odorless colorless

India

Tamil Nadu

Figure 1 A map showing sampling locations along the Cooum river

wells close to the river were done so far Hence the study hasbeen carried out on 20 different sites that cover the area of16 times 2 km which includes 10 sites on the left side of the riverand 10 sites on the right side of the river to assess the impactof the percolation of the river water flow on the GroundwaterThe location of the sample sites was given in Tables 1 and 2

22 Collection of Samples Water samples were collected fromthe bore wells at a depth of 32ndash35m below the ground levelat 20 locations along the Cooum river Two water sampleswere collected per year per sampling station covering bothpre- and postmonsoon seasons A total of 120 samples weretested and analyzed for a period of three years (2009ndash2011)

The collected samples were stored in cleaned and well-dried brown polythene glass bottles (25 L) with necessaryprecautions (APHA 1995) [8] These bottles were labeledwith respect to the collecting points date and time in orderto avoid any error between collection and analysis All thesample collections were immediately preserved in an iceboxand brought to the laboratory for determining the specificwater quality parameters

23 Sample Analysis The collected samples were analyzedfor specific water quality parameters such as pH electricalconductivity (EC) total dissolved solids (TDS) biochemicaloxygen demand (BOD) chemical oxygen demand (COD)
















3









02468

10


pH

Samples



(a)

02468

10


pH

Samples



(b)


0500

1000150020002500


EC

Samples



(a)

0500

100015002000


EC

Samples



(b)








0500

100015002000250030003500


TDS

Samples



(a)

0500

10001500200025003000


TDS

Samples



(b)


02468

10


BOD

Samples



(a)

02468

10


BOD

Samples



(b)


05

1015202530


COD

Samples



(a)

05

1015202530


COD

Samples



(b)







2009 831 2173 2677 834 242 287 0081Max 2010 826 2296 2713 835 246 303 0083

2011 83 2371 2892 856 248 313 00872009 685 498 987 439 133 130 0025

Min 2010 671 631 1048 424 111 137 0032011 704 583 1010 464 118 150 00362009 751 1355 189415 68135 1873 21975 00585

Mean 2010 74185 151595 2029 674 18755 22655 00552011 7548 152375 20735 68995 1972 230 006422009 041391 570724 575614 127868 34278 5318 001494

Std 2010 044131 53677 577915 137405 40111 55006 00145672011 036026 559887 585852 134849 39107 57544 00144682009 551145 4211985 3038904 1876686 1830112 2420023 2553846

CV 2010 59487 3540816 2848275 203865 2138683 2540013 26485452011 47729 3674402 2825426 1954475 1983114 2501913 2253583

050

100150200250300350


Na

Samples



(a)

050

100150200250300350


Na

Samples



(b)


0002004006008

01


Pb

Samples



(a)

0002004006008

01


Pb

Samples



(b)





2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599














119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of
















3









02468

10


pH

Samples



(a)

02468

10


pH

Samples



(b)


0500

1000150020002500


EC

Samples



(a)

0500

100015002000


EC

Samples



(b)








0500

100015002000250030003500


TDS

Samples



(a)

0500

10001500200025003000


TDS

Samples



(b)


02468

10


BOD

Samples



(a)

02468

10


BOD

Samples



(b)


05

1015202530


COD

Samples



(a)

05

1015202530


COD

Samples



(b)







2009 831 2173 2677 834 242 287 0081Max 2010 826 2296 2713 835 246 303 0083

2011 83 2371 2892 856 248 313 00872009 685 498 987 439 133 130 0025

Min 2010 671 631 1048 424 111 137 0032011 704 583 1010 464 118 150 00362009 751 1355 189415 68135 1873 21975 00585

Mean 2010 74185 151595 2029 674 18755 22655 00552011 7548 152375 20735 68995 1972 230 006422009 041391 570724 575614 127868 34278 5318 001494

Std 2010 044131 53677 577915 137405 40111 55006 00145672011 036026 559887 585852 134849 39107 57544 00144682009 551145 4211985 3038904 1876686 1830112 2420023 2553846

CV 2010 59487 3540816 2848275 203865 2138683 2540013 26485452011 47729 3674402 2825426 1954475 1983114 2501913 2253583

050

100150200250300350


Na

Samples



(a)

050

100150200250300350


Na

Samples



(b)


0002004006008

01


Pb

Samples



(a)

0002004006008

01


Pb

Samples



(b)





2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599














119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


02468

10


pH

Samples



(a)

02468

10


pH

Samples



(b)


0500

1000150020002500


EC

Samples



(a)

0500

100015002000


EC

Samples



(b)








0500

100015002000250030003500


TDS

Samples



(a)

0500

10001500200025003000


TDS

Samples



(b)


02468

10


BOD

Samples



(a)

02468

10


BOD

Samples



(b)


05

1015202530


COD

Samples



(a)

05

1015202530


COD

Samples



(b)







2009 831 2173 2677 834 242 287 0081Max 2010 826 2296 2713 835 246 303 0083

2011 83 2371 2892 856 248 313 00872009 685 498 987 439 133 130 0025

Min 2010 671 631 1048 424 111 137 0032011 704 583 1010 464 118 150 00362009 751 1355 189415 68135 1873 21975 00585

Mean 2010 74185 151595 2029 674 18755 22655 00552011 7548 152375 20735 68995 1972 230 006422009 041391 570724 575614 127868 34278 5318 001494

Std 2010 044131 53677 577915 137405 40111 55006 00145672011 036026 559887 585852 134849 39107 57544 00144682009 551145 4211985 3038904 1876686 1830112 2420023 2553846

CV 2010 59487 3540816 2848275 203865 2138683 2540013 26485452011 47729 3674402 2825426 1954475 1983114 2501913 2253583

050

100150200250300350


Na

Samples



(a)

050

100150200250300350


Na

Samples



(b)


0002004006008

01


Pb

Samples



(a)

0002004006008

01


Pb

Samples



(b)





2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599














119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


0500

100015002000250030003500


TDS

Samples



(a)

0500

10001500200025003000


TDS

Samples



(b)


02468

10


BOD

Samples



(a)

02468

10


BOD

Samples



(b)


05

1015202530


COD

Samples



(a)

05

1015202530


COD

Samples



(b)







2009 831 2173 2677 834 242 287 0081Max 2010 826 2296 2713 835 246 303 0083

2011 83 2371 2892 856 248 313 00872009 685 498 987 439 133 130 0025

Min 2010 671 631 1048 424 111 137 0032011 704 583 1010 464 118 150 00362009 751 1355 189415 68135 1873 21975 00585

Mean 2010 74185 151595 2029 674 18755 22655 00552011 7548 152375 20735 68995 1972 230 006422009 041391 570724 575614 127868 34278 5318 001494

Std 2010 044131 53677 577915 137405 40111 55006 00145672011 036026 559887 585852 134849 39107 57544 00144682009 551145 4211985 3038904 1876686 1830112 2420023 2553846

CV 2010 59487 3540816 2848275 203865 2138683 2540013 26485452011 47729 3674402 2825426 1954475 1983114 2501913 2253583

050

100150200250300350


Na

Samples



(a)

050

100150200250300350


Na

Samples



(b)


0002004006008

01


Pb

Samples



(a)

0002004006008

01


Pb

Samples



(b)





2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599














119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




2009 831 2173 2677 834 242 287 0081Max 2010 826 2296 2713 835 246 303 0083

2011 83 2371 2892 856 248 313 00872009 685 498 987 439 133 130 0025

Min 2010 671 631 1048 424 111 137 0032011 704 583 1010 464 118 150 00362009 751 1355 189415 68135 1873 21975 00585

Mean 2010 74185 151595 2029 674 18755 22655 00552011 7548 152375 20735 68995 1972 230 006422009 041391 570724 575614 127868 34278 5318 001494

Std 2010 044131 53677 577915 137405 40111 55006 00145672011 036026 559887 585852 134849 39107 57544 00144682009 551145 4211985 3038904 1876686 1830112 2420023 2553846

CV 2010 59487 3540816 2848275 203865 2138683 2540013 26485452011 47729 3674402 2825426 1954475 1983114 2501913 2253583

050

100150200250300350


Na

Samples



(a)

050

100150200250300350


Na

Samples



(b)


0002004006008

01


Pb

Samples



(a)

0002004006008

01


Pb

Samples



(b)





2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599














119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




2009 77 2004 2605 897 237 313 0081Max 2010 77 2073 2673 839 243 300 008

2011 775 2207 2716 825 246 310 00832009 67 508 905 43 103 120 003

Min 2010 66 557 981 437 109 127 0032011 67 567 993 446 113 133 0032009 7222 13581 187335 66555 17365 20745 00528

Mean 2010 7187 142235 194408 6644 18072 2077 00552011 72545 149005 20073 6755 18645 2163 005782009 02658 45316 57418 125741 39141 56049 0014152

Std 2010 029113 455259 570488 128389 3987 58448 0014072011 0284225 4656663 5819234 1268574 3997562 5822199 00144132009 3680421 333672 3064991 188928 2254017 2701808 2680303

CV 2010 4050786 3200752 2934488 1932405 2206175 2814059 25581822011 3917913 3125172 2899036 1877978 214404 2691724 2493599














119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of









119903 =119899sum119909119910 minus sum119909sum119910

radic[119899sum1199092

minus (sum119909)2

] [119899sum1199102

minus (sum119910)2

]

(1)








Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




Premonsoon


0958 49555


0892 17981


0945 3707

Postmonsoon


0977 91861


0969 676


0969 68523


119884 = 1205730+ 12057311198831+ 12057321198832+ sdot sdot sdot 120573

119899119883119899 (2)

where 1198831 1198832 and 119883



1205731 and 120573




4 Conclusion





References








































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of

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