Research Article Effects of Bahir Dar Textile Factory Effluents...

Research ArticleEffects of Bahir Dar Textile Factory Effluents on the WaterQuality of the Head Waters of Blue Nile River Ethiopia

Abrehet Kahsay Mehari1 Shewit Gebremedhin1 and Belayneh Ayele2

1Fisheries Wetlands and Wildlife Management Department Bahir Dar University PO Box 5501 Bahir Dar Ethiopia2Natural Resource Management Department Bahir Dar University PO Box 5501 Bahir Dar Ethiopia

Correspondence should be addressed to Abrehet Kahsay Mehari abrehetkahsay66gmailcom

Received 16 July 2015 Accepted 5 November 2015

Academic Editor Adil Denizli

Copyright copy 2015 Abrehet Kahsay Mehari et alThis is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

The study was conducted in 201314 with the objective of determining the effects of Bahir Dar textile factory effluents on the head ofBlue Nile River water quality Dissolve oxygen was higher at the upstream site of the river whereas BOD5 TDS and total alkalinityvalues were higher at wastewater outlet of the factory site The mean values of dissolved oxygen BOD5 and total alkalinity wereabove maximum permissible limits set by WHO for drinking water at head of Blue Nile River The mean value of BOD5 wasabove permissible limit of IFC for textile effluents to be discharged to surface water A total of 836 aquatic macroinvertebrateindividuals belonging to 21 families were collected The Shannon-Wiener Diversity Index the Hilsenhoff family-level biotic indexfamily richness and percent dipterans were calculated Hilsenhoff family-level biotic index and percent dipterans metrics differedsignificantly among sampling sites (119875 lt 005) Hilsenhoff family-level biotic index was higher at the most downstream site butpercent dipterans were higher at site of discharge of effluent to the head of Blue Nile River Therefore there is indication thateffluent demands frequent control and proper treatment before being discharged to the environment

1 Introduction

Pollution of natural waters with waste water arising fromvarious industries has become a serious problem globallyTextile industries are large industrial consumers of waters aswell as producers of wastewaters with the increased demandfor textile products leading to increase in the generation oftextile wastewater whichmakes the textile industry one of themain sources of severe pollution problems worldwide [1ndash3]

Effluents from the textile factory commonly contain highconcentrations of organic and inorganic chemicals and arecharacterized by high Chemical Oxygen Demand (COD)Biological Oxygen Demand (BOD) Total Dissolved Solids(TDS) pH Total Suspended Solids (TSS) values and lowdissolved oxygen (DO) value as well as strong color Themajor concern with color is its aesthetic character at the pointof discharge with respect to the visibility of the receivingwaters [4ndash6]

The textile factory in Ethiopia dates back to 1939 inrelation with Italian colonialism era when the first industrial

textile factory was established in Dire-Dawa in the name ofDire-Dawa textilemill Since 2010 the Ethiopian governmenthas put effort to improve support and expand the textileindustry serving the domestic market but mainly with theaim to export and be competitive at the global market [7]Ethiopia has potential of building a textile factory withgovernmental support offering low-cost production and rawmaterial and with a growing young population eager forjobs [8] The factory is one of the largest employers inEthiopia with 35000 direct employees (cotton farming (10)and textilegarment manufacturing (90)) excluding the500000 engaged in the informal hand-loom weaving sector[9]

Bahir Dar textile factory is one of Ethiopia textile facto-ries manufacturing 100 cotton products including yarnsand fabrics It was established in 1961 from the fund of Italianwar reparation in the town of Bahir Dar 570 km northwest ofAddis Ababa Ethiopia The factory has production capacityof 17 tons per day of yarns and 5000metersrsquo wool fabrics [10]The major factories in Bahir Dar town including Bahir Dar

Hindawi Publishing CorporationInternational Journal of Analytical ChemistryVolume 2015 Article ID 905247 7 pageshttpdxdoiorg1011552015905247

2 International Journal of Analytical Chemistry

11∘3599840042998400998400N

11∘369984009998400998400N

11∘3599840042998400998400N

11∘369984009998400998400N

37∘24

99840020

998400998400E 37∘24

99840040

998400998400E

37∘24

99840020

998400998400E 37∘24

99840040

998400998400E

0 155 310 620

(m)

T2

T2

U

U

Blue Nile River

Blue Nile

River

D

D

A

A

T1

T1

N

Figure 1 Location map of study area

textile factory Bahir Dar tanneries and Bahir Dar Abattoirare built at the edge of head of Blue Nile River wheremost of them dispose their solid and liquid wastes directlyinto this river Despite the extensive work that has beenconducted on Bahir Dar tanneries effluents with regard tophysicochemical parameter and aquatic macroinvertebrates[11] little information is documented about the effect of BahirDar textile factory effluents on head of Blue Nile River

Therefore the objective of this studywas to investigate theeffect of Bahir Dar textile factory effluents on the head of BlueNile River using aquatic macroinvertebrate as bioindicatorsthrough addressing the following research questions (1)What is the pollution level of textile factory effluents (2)Do the observed water quality parameters in the study areaexceed the maximum permissible limits of national andinternational standards (3) To what extent are the waterquality parameters higher than the standard (4) To whatextent is the headwater of the Blue Nile River affected by theeffluents from the factory

2 Materials and Methods

21 Study Areas Bahir Dar the capital of Amhara NationalRegional State is situated on the southern shore of LakeTana the source of Blue Nile River approximately 565 kmsnorthwest of Addis Ababa at an altitude of 1801masl having

latitude of 1103810158401015840N and longitude of 3701010158401015840E The averageelevation in the town is about 1795masl with ldquoWoina Degardquotype of agroecological zone The town covers an area ofabout 16000 hectares The study area experiences averageannual rainfall that ranges from 1200 to 1600mm and ithas mean annual temperature of 26∘C [15] It is a rapidlyexpanding town with commercial centers small industriesand residences in all sectors of the town The textile factorylocated at the edge of head of Blue Nile River dischargesits effluents directly into head of Blue Nile River Howeverthe water from this river is used for different purposes likedrinking livestock watering hygiene and irrigation by thedownstream communities

22 Sampling Five sampling sites were established on studyarea according to the method stated in [16] The mostupstream site from the head of Blue Nile River (U) thewastewater outlet of the factory (T1) neutralization pond(T2) where effluent is discharged and joins the head ofBlue Nile River (A) and 200 m downstream site of wastejoining the river (D) were chosen (Figure 1) Samples for bothwater quality parameters and aquatic macroinvertebrateswere collected in August and December 2013 and Aprilof 2014 Samples for aquatic macroinvertebrates were notrecorded from sampling sites T1 and T2 because these siteswere concrete made ponds

International Journal of Analytical Chemistry 3

23 Data Collection

231 Water Quality Parameters Samples of water qualityparameters water temperature dissolved oxygen (DO) pHTotal Dissolved Solids (TDS) and conductivity from all siteswere measured in situ using YSI 556 MPS multiprobe fieldmeter Water sample for BOD5 total alkalinity and totalhardiness were collected and stored in clean polythene bottlesthat had been prewashed with 10 nitric acid and thoroughlyrinsed with deionized water using standard methods statedin [17] Water samples for BOD5 were analyzed according tothe standard methods of [18] at the laboratory of the Instituteof Technology of Bahir Dar University while samples fortotal hardiness and total alkalinity were analyzed at AmharaDesign and Supervision Work Enterprise Laboratory usingPaqualab photometer instrument with their respective palin-test tablets

232 Aquatic Macroinvertebrate Samples of aquatic macro-invertebrates were taken using 119863-frame dip net with meshsize of 500 120583m from U A and D sampling sites In the fieldthose visible organisms were removed with forceps and putinto the specimen bottles All samples were preserved with70 ethanol until laboratory analysis and counting All theorganisms in the sample were enumerated and identified tothe family level using a dissecting microscope and standardkeys [19ndash22]

233 Data Analysis Descriptive statistics were used to analyzethe mean value and standard error of the water quality dataFour indices of the aquatic macroinvertebrate communitieswere calculated for each sampling site The Shannon-WienerDiversity Index (1198671015840) is a diversity index that incorporatesrichness and evenness A high 1198671015840 indicates a good waterquality1198671015840 was calculated as follows

1198671015840= minussum(119875

119894ln [119875119894]) (1)

where 119875119894is the relative abundance (119899

119894119873) of family 119894 119899

119894is

the number of individuals in family 119894 and 119873 is the totalnumber of individuals in all families1198671015840 is ranging from 0 fora community with a single family to over 7 for a very diversecommunity

The Hilsenhoff family-level biotic index (HFBI) is abiotic index that is calculated by multiplying the number ofindividuals of each family by an assigned tolerance value forthat family Assigned tolerance values range from 0 to 10 forfamilies and increase as water quality decreases [23 24] Thisindex was calculated as follows

HFBI =Σ [(TV

119894) (119899119894)]

119873 (2)

where TV119894is tolerance value for family 119894 119899

119894is the number

of individuals in family 119894 and 119873 is the total number ofindividuals in the sample collection High HFBI communityvalues are an indication of organic pollution while low valuesindicate good water quality

Research has indicated that the percentage of dipteranstends to increase with a decrease in water quality they

become increasingly dominant in terms of percent taxonomiccomposition and relative abundance along a gradient ofincreasing enrichment for heavy metals concentration [2526] This index was calculated as follows

Dipterans = 100

lowast ( Individual Dipterans

Total Individuals in sample)

(3)

Family richness reflects the health of the community asa measurement of the variety of families present Richnessgenerally increases with increasing water quality habitatdiversity and habitat suitability This index was calculated asfollows

FR

= the number of different family of animals in the sample(4)

Excel spreadsheets and Statistical Package for Social Sci-ences Software (SPSS version 20) were used for the statisticalanalysis One-way ANOVA was used to evaluate differencesin water quality data and aquatic macroinvertebrate metricsamong the sampling sites Differences among means weretested using Tukey HSD

3 Results and Discussions

31 Water Quality Parameters The mean values of dissolvedoxygen ranged from 37mgL at sampling site T1 to 78mgLat U and showed significant variation among sampling sites(119865 = 15259 119875 = 0000) The value at site U was significantlyhigher than that at the other sites (Table 1) Many studiesalso showed that dissolved oxygen level of textile effluents islow and varied from 042 to 460mgL with average value of236mgL [27] 48mgLndash8mgL [12] about 04mgL [28]and 028mgLndash512mgL [29] The mean values of dissolvedoxygen at sampling sites from head of Blue Nile River (U andD) were not acceptable for drinking purpose [30]

The mean values of BOD5 which varied from 53mgLat sampling site U to 403mgL at site T1 showed significantvariation among sampling sites (119865 = 95767 119875 = 0000) Thevalue at sampling site T1 was higher than that at the othersites (Table 1) The high value of BOD5 at T1 could be due tohigher content of organic load and the high levels of BOD5 arethe indicators of the pollution strength of the waters [13 14]The mean value of BOD5 of the study at sampling sites fromhead of Blue Nile River (U and D) was found to be above thepermissible limit set for drinking water [30] The mean valueof effluent joining the head of Blue Nile River (A) was withinthe range of acceptable levels of [31] for textile effluents tobe discharged into inland surface water bodies but was abovestandard limits of [32]

The pH mean values ranged from 7 at A to 87 at T1The mean values did not differ significantly among samplingsites (119865 = 2367 119875 = 0123) The temperature mean valuesranged from 204∘C at A to 252∘C at T1 and values did notvary among sampling sites (119865 = 0718 119875 = 0599) (Table 1)The mean values of temperature and pH of the study werewithin [31] as well as [30] guideline values Similar to present


Table 1 Mean values of water quality parameters of study sites compared to guideline values ofWHO [12] EEPA [13] and IFC [14] Differentletters within the same row show significant variation among sampling sites according to Tukey HSD (119875 lt 0000)

Parameters Sampling sites StandardsT1 T2 A D U 119875 value IFC EEPA WHO

DO (mgL) 37b 77a 67a 72a 78a 0000 NA NA gt10BOD5 (mgL) 403a 363ab 33bc 82d 53df 0000 30 50 lt4pH (pH Units) 84a 78a 71a 77a 73a 0123 6ndash9 6ndash9 65ndash85Temperature (∘C) 252a 208a 204a 243a 236a 0599 NA 40 lt25TDS (ppm) 6123a 391b 4478bc 129d 1017df 0000 NA NA lt500Conductivity (120583Scm) 1050a 8358b 9437ab 168c 141cd 0000 NA NA 400ndash800Total hardness (mgL) 88a 102a 117a 11033a 84a 0590 NA NA NATotal alkalinity (mgL) 247a 225a 107b 9467bc 91bcd 0000 NA NA lt75NA not available IFC International Finance Corporation EEPA Ethiopian Environmental Protection Authority and WHO World Heath Organization

study [33 34] reported the mean pH value of textile effluentsin the range of 6ndash9 The temperature of textile effluents wasalso reported in the range of 27ndash34∘C [12 35]

The mean values of TDS varied from 1017 ppm atsampling site U to 6123 ppm at T1 and showed significantvariation (119865 = 60039 119875 = 0000) with the value at T1 beingsignificantly higher than that at other sampling sites (Table 1)Studies of these authors [27 36] reportedTDS values of textileeffluents as 860mgL and 1260mgL respectively which aremuch higher than the TDS values recorded in the presentstudyThemean values of TDS at sampling sites U andDwerewithin standards of [30] since water with a TDS lt 1200mgLgenerally had an acceptable taste for drinking purposes

Themean value for conductivity varied from 141 120583Scm atsampling site U to 1050 120583Scm at sampling site T1 There wassignificant variation among sampling sites (119865 = 110142 119875 =0000) with the value at T1 being significantly higher thanthat at other sampling sites (Table 1) The conductivity fortextile effluent was recorded in the range of 3804ndash1704 120583Scm[37]Themean value of conductivity at sampling sites (U andD) was within the range of the standard limit of [30] which isin the range of 400ndash800 120583Scm for drinking purposes

The mean values of total hardiness varied from 84mLgat sampling site U to 117mgL at A with mean value of100mLg Total hardiness did not show significance amongsampling sites (119865 = 0733 119875 = 0590) (Table 1) Based onthe classification Khopkar [38] hardness of natural water wasclassified into five categories on the basis of total ion contentsoft (0ndash40mgL)moderately hard (40ndash100mgL) hard (100ndash300mgL) very hard (300ndash500mgL) and extremely hard(500ndash1000mgL) Based on this classification the head ofBlueNile River water can be put in the category ofmoderatelyhard at upstream site (U) and hard at the most downstreamsite (D)Thewater containing excess hardness is not desirablefor drinking [39] As compared to present study some studies[40 41] reported higher mean values for textile effluents(in the range of 470ndash1010mgL CaCO

3) and one study [29]

reported slightly lower mean values (in the range of 63ndash88mgL CaCO

3) for textile effluents

Total alkalinity mean values ranged from 91mgL at U to247mgL at T1 The mean values differ significantly amongsampling sites (119865 = 168 119875 = 000) (Table 1) The meanvalues at sampling sites U and D are found to be above the

DAU

0102030405060708090

100

()

Ephe

mer

opte

ra

Tric

hopt

era

Col

eopt

era

Hem

ipte

ra

Acar

ina

Odo

nata

Dip

tera

Snai

ls

Figure 2 Relative abundance of main taxonomic group at eachsampling site

permissible limit set for drinking water lt75mgL [30] andthis could be due to the use of soaps by local people forbathing and washing clothes which was apparent activitiesat these sampling sites Studies of [27 35] reported similarfindings about the high alkalinity mean value of textileeffluents

32 Bioindicators

321 Aquatic Macroinvertebrate Taxa A total of 836 indi-viduals composed of 21 families were collected from thethree sites (U A and D) The total number of familiespresent at each site ranged from 9 (D) to 11 (A) The mostdominant families were Veliidae (103) Belostomatidae (102)Planorbidae (96) Gerridae (79) and Corixidae (64) Thefamilies least encountered were Tetragnathidae (4) Lestidae(4) and Aeshnidae (5) Furthermore it is found out thatmore than 823 of the individuals collected belong to insectorders while less than 177 belong to the noninsect orderlike Acarina and Snail orders Among the insect ordersHemiptera and Coleopteran were the most dominant with474 and 8 respectively (Figure 2 Table 2)


Table 2 Number of aquatic macroinvertebrates collected fromstudy sites

Familyorder TV Sampling sitesT1 T2 U A D Total

AcarinaTetragnathidae 4 NA NA 4 0 0 4

DipteransCeratopogonidae 6 NA NA 0 10 0 10Chironomidae 8 NA NA 9 0 0 9Culicidae 8 NA NA 0 30 0 30

EphemeropteraBaetidae 5 NA NA 48 0 3 51

HemipteraBelostomatidae 9 NA NA 37 43 22 102Corixidae 8 NA NA 0 35 29 64Gerridae 9 NA NA 0 68 11 79Naucoridae 6 NA NA 21 0 0 21Notonectidae 9 NA NA 0 22 5 27Veliidae 7 NA NA 94 8 1 103

SnailsHydrobiidae 8 NA NA 0 25 8 33Lymnaeidae 6 NA NA 0 7 0 7Physidae 7 NA NA 0 8 0 8Planorbidae 7 NA NA 14 65 17 96

Odonata (Damsel and Dragon)Aeshnidae 3 NA NA 5 0 0 5Coenagrionidae 9 NA NA 9 15 20 44Cordulidae 3 NA NA 15 0 0 15Lestidae 9 NA NA 0 4 0 4Libellulidae 9 NA NA 0 3 14 17

TrichopteraHydropsychidae 4 NA NA 40 0 0 40Total individuals 328 373 134 835Total families 11 14 9 21

TV = tolerance values NA = not available

Stated as in [26] sites that are with greater than 26families are considered as nonimpacted 19ndash26 as slightlyimpacted 11ndash18 as moderately impacted and 0-1 as severelyimpacted Based on this finding sampling sites U and D fallunder moderately impacted while sampling site A fall underseverely impacted site

322 Aquatic Macroinvertebrate Metrics The mean valueof Shannon-Wiener Diversity Index (1198671015840) ranged from 2 atsampling site U to 18 at A indicating this site has less diversitythan upstream and the most downstream sites (Table 3) The1198671015840 value did not show significant variation among sampling

sites (119865 = 100 119875 = 0422) 1198671015840 is ranging from 0 for acommunity with a single family to over 7 for a very diversecommunity1198671015840 value of less than 1 indicates highly polluted1ndash3 moderately polluted and greater than 4 unpolluted waterbodies [42] In present study all the three sites are undermoderate polluted conditions

Table 3 Mean values plusmn std error of 1198671015840 HFBI and dipterans ateach sampling site

Sampling sites 1198671015840 HFBI Dipterans

U 2 plusmn 00a 6 plusmn 14bc 27 plusmn 13bA 18 plusmn 33a 75 plusmn 91ab 107 plusmn 35aD 2 plusmn 11a 79 plusmn 26a 0 plusmn 00bclowastDifferent letters within the same column show significant differences (119875 lt005) 1198671015840 Shannon-Wiener Diversity Index HFBI Hilsenhoff family-levelbiotic index and Std error standard error

The mean values for Hilsenhoff family-level biotic index(HFBI) ranged from 6 at sampling site U to 79 at D Meanvalues showed significant variation among sampling sites(119865 = 7678 119875 = 0022) with value being higher at the mostdownstream site (Table 3)This indexwas developed to detectorganic pollution In this study all sites showed higher HFBIvalues suggesting fair water quality conditions at samplingsite U and poor at A and D

Themean values for percent dipterans ranged from 0 atsampling site D to 107 at A and values showed significantvariation among sampling sites (119865 = 9494 119875 = 0014)with mean value being high at site A (Table 3) Since mostdipterans larvae contain hemoglobin they are able to survivelow oxygen conditions [43] and their higher abundance isindication of poor water quality [44]

4 Conclusion

We conclude that the textile factory poses serious pollutionload to the aquatic habitat of the head of BlueNile Riverwhichin turn makes the water highly polluted The values of mostmetrics follow pollution gradient and showed deterioratedwater quality conditions of the head of Blue Nile RiverTherefore hence there are many immediate downstreamusers of the water river for drinking fishing bathing andirrigation the effluent demands frequent control and propertreatment before being discharged to the environment

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was conducted with the help of a grant fromBahir Dar University for which the authors are grateful Theauthors are thankful for the practical and mental support ofcolleagues and friends during the course of the research

References

[1] S Sen and G N Demirer ldquoAnaerobic treatment of real textilewastewater with a fluidized bed reactorrdquo Water Research vol37 no 8 pp 1868ndash1878 2003

[2] A Dos Santos Reductive decolourisation of dyes by thermophilicanaerobic granular sludge [PhD thesis] Wageningen Univer-sity Wageningen The Netherlands 2005


[3] A B dos Santos F J Cervantes and J B van Lier ldquoReviewpaperon current technologies for decolourisation of textile wastew-aters perspectives for anaerobic biotechnologyrdquo BioresourceTechnology vol 98 no 12 pp 2369ndash2385 2007

[4] S K A Solmaz A Birgul G E Ustun and T Yonar ldquoColourand COD removal from textile effluent by coagulation andadvanced oxidation processesrdquo Coloration Technology vol 122no 2 pp 102ndash109 2006

[5] World Bank ldquoA detailed analysis on industrial pollution inBangladeshrdquo Workshop Discussion Paper Transfer EPA-6253-74-004 World Bank Dhaka Office Dhaka Bangladesh 2010

[6] H Ben Mansour I Houas F Montassar et al ldquoAlteration of invitro and acute in vivo toxicity of textile dyeing wastewater afterchemical and biological remediationrdquo Environmental Scienceand Pollution Research vol 19 no 7 pp 2634ndash2643 2012

[7] TIDI Textile Industry Development Institute httpwwwtidigovetBackgroundhtml

[8] C Alderin Made in Ethiopia (Challenges and Opportunities inEmerging Textile Industry in Ethiopia) ArbetsrapportserieDepartment of Social and Economic Geography Uppsala Uni-versitet Uppsala Sweden 2014

[9] Federal Ministry of Science and Technology Report on Techno-logical Capabilities of Ethiopian Textile and Garment IndustriesFederal Ministry of Science and Technology 2011

[10] Bahir Dar textile share company 2015 httpwwwbdtscgovethome20amhtml

[11] A Wosnie and A Wondie ldquoAssessment of downstream impactof Bahir Dar tannery effluent on the head of Blue Nile Riverusing macroinvertebrates as bioindicatorsrdquo International Jour-nal of Biodiversity and Conservation vol 6 no 4 pp 342ndash3502014

[12] M Sultana M Islam R Sahaa and M Al-Mansur ldquoImpact ofthe effluents of textile dyeing industries on the surface waterquality inside DND (DhakaNarayanganj-Demra) Embank-ment Narayanganjrdquo Bangladesh Journal of Scientific and Indus-trial Research vol 44 pp 65ndash80 2009

[13] R Yusuff and J Sonibare ldquoCharacterization of textile industriesEffluents in Kaduna Nigeria and pollution implicationsrdquoGlobalNEST Journal vol 6 no 3 Article ID 212221 2004

[14] A Geetha P Palanisamy P Sivakumar P Ganesh and MSujatha ldquoAssessment of underground water contamination andeffect of textile effluents on Noyyal River basin in and aroundTiruppur town Tamilnadurdquo E-Journal of Chemistry vol 5 no4 pp 696ndash705 2008

[15] CSA Statistical Abstract 2010 Central Statistical Agency AddisAbaba Ethiopia 2010

[16] D Klemm P Lewis F Fulk and J M Lazorchak ldquoMacroinver-tebrate field and laboratory methods for evaluating the biolog-ical integrity of surface watersrdquo Tech Rep EPA6004-90030US Environmental Protection Agency Office of Research andDevelopment Washngton DC USA 1990

[17] C Jain and K Bhatia Physicochemical Analysis of Water andWasteWater Mannual UM-26 National Institute of HydrologyRoorkee India 1987

[18] American Public Health Association Standard Methods for theExamination ofWater andWastewater American Public HealthAssociation Washington DC USA 20th edition 1998

[19] W Edmondson Fresh Water Biology John Wiley amp Sons NewYork NY USA 2nd edition 1959

[20] K Jessup A Markowitz and J Stribling ldquoFamily-level key tothe stream invertebrates of Maryland and surrounding areasrdquo

Tech Rep CBWP-MANTA-EA-99-2 Maryland Departmentof Natural Resources Chesapeake Bay and Watershed Pro-gram ResourceAssessment ServiceMonitoring andNon-TidalAssessment Division 1999

[21] J Gooderham and E Tysrlin The Water Bug Book A Guide tothe Freshwater Macroinvertebrates of Temperate Australi CsiroPublishing 2002

[22] R Bouchard Guide to Aquatic Macro Invertebrates of the UpperMid West Water Resources Center St Paul Minn USA 2004

[23] W L Hilsenhoff ldquoRapid field assessment of organic pollutionwith a family level biotic indexrdquo Journal of the North AmericanBenthological Society vol 7 no 1 pp 65ndash68 1988

[24] R Bode M Novak and L Abele Quality Assurance Work Planfor Biological Stream Monitoring in New York State New YorkState Department of Environmental Conservation Albany NYUSA 1996

[25] L Ferrington ldquoCollection and identification of floating exuviaeofChironomidae for use in studies of surface water qualityrdquo SOPFW 130A US Environmental Protection Agency Region VIIKansas City Mo USA 1987

[26] J Plafkin M Barbour K Porter S Gross and R HughesldquoRapid bioassessment protocols for use in streams and riversBenthic macroinvertebrates and fishrdquo Tech Rep EPA 440-4-89-00 US Environmental Protection Agency Office of WaterRegulations and Standards Washington DC USA 1989

[27] N Mohabansi P Tekade and S Bawankar ldquoPhysico-chemicalparameters of textile mill effluent Hinganghat DistrictWardhardquo Current World Environment vol 6 pp 165ndash168 2011

[28] R Knat ldquoTextile dyeing industry an environmental hazardrdquoNatural Science vol 4 no 1 pp 22ndash26 2012

[29] K Abraha A Gebrekidan Y Weldegebriel and A HaderaldquoPhysico-chemical analysis of almeda textile industry effluentsin tigrayrdquo International Journal of Environmental AnalyticalChemistry vol 1 no 1 2014

[30] WorldHealthOrganization International Standard forDrinkingWater Quality World Health Organization Geneva Switzer-land 2008

[31] Ethiopian Environmental Protection Authority ldquoProvisionalstandards for industrial pollution control in Ethiopia Pre-pared under the ecologically sustainable industrial develop-ment (ESID) projectrdquo Tech Rep USETH99068 EthiopianEnvironmental Protection Authority Addis Ababa Ehiopia2003

[32] International Finance Corporation and World Bank GroupEnvironmental Health and Safety Guidelines for Textile Man-ufacturing World Bank Group Washington DC USA 2007

[33] K K Sivakumar C Balamurugan D Ramakrishnan and LH Bhai ldquoAssessment studies on wastewater pollution by textiledyeing and bleaching industries at Karur Tamil NadurdquoRasayanJournal of Chemistry vol 4 no 2 pp 264ndash269 2011

[34] L Varma and J Sharma ldquoAnalysis of physical and chemicalparameters of textile wastewaterrdquo Journal of InternationalAcademy of Physical Sciences vol 15 no 2 pp 269ndash276 2011

[35] J Awomeso A Taiwo A Gbadebo and J Adenowo ldquoStudieson the pollution of water body by textile industry effluents inLagosrdquo Nigeria Journal of Applied Sciences in EnvironmentalSciences vol 5 no 4 pp 353ndash359 2010

[36] R Roy A Fakhruddin R Khatun M Islam M Ahsan andA Neger ldquoCharacterization of textile industrial effluents and itseffects on aquaticmacrophytes and algaerdquoBangladesh Journal ofScientific and Industrial Research vol 45 no 1 pp 79ndash84 2010


[37] I Hussain L Raschid M Hanjra F Marikar and W HoekldquoWastewater use in agriculture review of impacts and method-ological issues in valuing impactsrdquo Working Paper 37 Interna-tional Water Management Institute Colombo Sri Lanka 2002

[38] S Khopkar Environmental Pollution Analysis Wiley EasternNew Delhi India 1993

[39] D Neeraj J Sharma and N Patel ldquoEvaluation of groundwaterquality index of the urban segmen of Surat city Indiardquo Interna-tional Journal of Geology vol 1 no 4 pp 220ndash245 2010

[40] A I Ohioma N O Luke and O Amraibure ldquoStudies on thepollution potential of wastewater from textile processing facto-ries in Kaduna Nigeriardquo Journal of Toxicology and Environmen-tal Health Sciences vol 1 no 2 pp 34ndash37 2009

[41] S A Paul S K Chavan and S D Khambe ldquoStudies on charac-terization of textile industrial waste water in Solapur cityrdquo Inter-national Journal of Chemical Sciences vol 10 no 2 pp 635ndash6422012

[42] J Wilhm and T Dorris ldquoBiological parameters of water qualitycriteriardquo Bioscience vol 18 no 6 pp 477ndash481 1968

[43] P S Lake ldquoEcological effects of perturbation by drought inflowing watersrdquo Freshwater Biology vol 48 no 7 pp 1161ndash11722003

[44] F OMaseseMMuchiri and P O Raburu ldquoMacroinvertebrateassemblages as biological indicators of water quality in theMoiben River Kenyardquo African Journal of Aquatic Science vol34 no 1 pp 15ndash26 2009

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11∘3599840042998400998400N

11∘369984009998400998400N

11∘3599840042998400998400N

11∘369984009998400998400N

37∘24

99840020

998400998400E 37∘24

99840040

998400998400E

37∘24

99840020

998400998400E 37∘24

99840040

998400998400E

0 155 310 620

(m)

T2

T2

U

U

Blue Nile River

Blue Nile

River

D

D

A

A

T1

T1

N

Figure 1 Location map of study area

textile factory Bahir Dar tanneries and Bahir Dar Abattoirare built at the edge of head of Blue Nile River wheremost of them dispose their solid and liquid wastes directlyinto this river Despite the extensive work that has beenconducted on Bahir Dar tanneries effluents with regard tophysicochemical parameter and aquatic macroinvertebrates[11] little information is documented about the effect of BahirDar textile factory effluents on head of Blue Nile River

Therefore the objective of this studywas to investigate theeffect of Bahir Dar textile factory effluents on the head of BlueNile River using aquatic macroinvertebrate as bioindicatorsthrough addressing the following research questions (1)What is the pollution level of textile factory effluents (2)Do the observed water quality parameters in the study areaexceed the maximum permissible limits of national andinternational standards (3) To what extent are the waterquality parameters higher than the standard (4) To whatextent is the headwater of the Blue Nile River affected by theeffluents from the factory

2 Materials and Methods

21 Study Areas Bahir Dar the capital of Amhara NationalRegional State is situated on the southern shore of LakeTana the source of Blue Nile River approximately 565 kmsnorthwest of Addis Ababa at an altitude of 1801masl having

latitude of 1103810158401015840N and longitude of 3701010158401015840E The averageelevation in the town is about 1795masl with ldquoWoina Degardquotype of agroecological zone The town covers an area ofabout 16000 hectares The study area experiences averageannual rainfall that ranges from 1200 to 1600mm and ithas mean annual temperature of 26∘C [15] It is a rapidlyexpanding town with commercial centers small industriesand residences in all sectors of the town The textile factorylocated at the edge of head of Blue Nile River dischargesits effluents directly into head of Blue Nile River Howeverthe water from this river is used for different purposes likedrinking livestock watering hygiene and irrigation by thedownstream communities

22 Sampling Five sampling sites were established on studyarea according to the method stated in [16] The mostupstream site from the head of Blue Nile River (U) thewastewater outlet of the factory (T1) neutralization pond(T2) where effluent is discharged and joins the head ofBlue Nile River (A) and 200 m downstream site of wastejoining the river (D) were chosen (Figure 1) Samples for bothwater quality parameters and aquatic macroinvertebrateswere collected in August and December 2013 and Aprilof 2014 Samples for aquatic macroinvertebrates were notrecorded from sampling sites T1 and T2 because these siteswere concrete made ponds


23 Data Collection




1198671015840= minussum(119875

119894ln [119875119894]) (1)


119894119873) of family 119894 119899

119894is



HFBI =Σ [(TV

119894) (119899119894)]

119873 (2)


119894is the number




Dipterans = 100



(3)


FR



















DAU

0102030405060708090

100

()

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32 Bioindicators





















4 Conclusion




Acknowledgments


References

























































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


23 Data Collection




1198671015840= minussum(119875

119894ln [119875119894]) (1)


119894119873) of family 119894 119899

119894is



HFBI =Σ [(TV

119894) (119899119894)]

119873 (2)


119894is the number




Dipterans = 100



(3)


FR



















DAU

0102030405060708090

100

()

Ephe

mer

opte

ra

Tric

hopt

era

Col

eopt

era

Hem

ipte

ra

Acar

ina

Odo

nata

Dip

tera

Snai

ls



32 Bioindicators





















4 Conclusion




Acknowledgments


References

























































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of













DAU

0102030405060708090

100

()

Ephe

mer

opte

ra

Tric

hopt

era

Col

eopt

era

Hem

ipte

ra

Acar

ina

Odo

nata

Dip

tera

Snai

ls



32 Bioindicators





















4 Conclusion




Acknowledgments


References

























































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




















4 Conclusion




Acknowledgments


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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