Journal of Research in Biology Biology Journal Journal of Biology Biology research journal biomedical journal
Calculating Integrated Pollution Indices for Heavy Metals in Ecological Geochemistry Assessment Near Sugar Mill
PDF
HTML

Keywords

Atomic Absorption Spectrophotometer
integrated indices
pollution index
heavy metals
ecological risk index
Nemerow pollution index

How to Cite

D, S. T., & MA, S. (2012). Calculating Integrated Pollution Indices for Heavy Metals in Ecological Geochemistry Assessment Near Sugar Mill. Journal of Research in Biology, 2(5), 489-498. Retrieved from https://ojs.jresearchbiology.com/index.php/jrb/article/view/241

Abstract

The sugar mill is a good example of a site where human pressures and ecological values collide with each other. One of the aims of this work was to select different types of index to aggregate and assess heavy metal contamination near sugar mill in an accessible manner. Concentrations of heavy metals (Iron, Manganese, Zinc and Copper) are studied in the soil near sugar mill to asses metal contamination due to industrialization. The soil samples were collected from three different depths A (0 cm), B (5 cm) and C (10 cm) for a period between October 2010 and March 2011 (winter and summer) and the heavy metal contents were analyzed by Atomic Absorption Spectrophotometer. Pollution index is a powerful tool for ecological geochemistry assessment. Nine integrated indices were divided into two groups. One group is suitable for the normal distribution single indices including the average, vector modulus, and Nemerow pollution indices, and the other for log-normal distribution including the product, root of the product, and weighted power product pollution indices. Using background levels as reference values, five contamination classes were divided, and the terminologies are suggested for the integrated indices to unify the assessment results. The pollution load index (Ecological risk index) indicates that soil near sugar mill was highly polluted due to heavy metals (PLIFe = 0.30, PLIMn = 0.58, PLIZn = 0.24 and PLICu = 0.34). The results of contamination index, index for chemistry and metal pollution were in agreement with pollution load index. Average and vector modulus of pollution index and Nemerow pollution index indicated slightly polluted domain. Since the aim of work on contamination evaluation is to assess the overall contamination of a study area, the indices are highly appropriate.

PDF
HTML

References

Aikpokpodion PE, Ipinmoroti RR and Omotoso SM. 2010. Evaluation of Camellia sinensis (tea) biomass in nickel contaminated waste water treatment, J. Soil Nature 4(1): 7-16.

Alloway JB. 1995. ―Soil Pollution and Land Contamination‖, in Pollution: Causes, Effects and Control, ed. R. M. Harrison. Cambridge: The Royal Society of Chemistry, 318.

Arora PN, Sumeet Arora, Arora S. 2007. Comprehensive Statistical Methods, S.Chand and Company Ltd, New Delhi.

Bakkialakshmi S and Vinodhini R. 2008. Spectro-chemical study of Ambika sugar factory waste affected soil and water in Pennadam, Cuddalore District,

Tamil Nadu, Indian journal of Environmental Protection, 28(5): 405-414.

Bhattacharya A, Routh J, Jacks G. 2006. Environmental Assessment of Abandoned Mine Tailings in Adak, Västerbotten District (Northern Sweden). Applied Geochemistry, 21:1760-1780.

Bhupander Kumar, Sanjay Kumar, Dev Prakash, Singh, SK, Meenu Mishra Jain PK, Lal, RB, Sharma CS. and Mukherjee, DP. 2011. A study on sugar mill pressmud compost for some heavy metal content and their bio-availability, Asian Journal of Plant Science and Research, 1 (3): 115-122.

Burges TM and Webster R. 1980. Optimal interpolation and arithmic mapping of soil properties, Journal of Soil Sciences, 31: 315-331.

Burges TM, Webster R and Mc Bratney AB. 1981. Optimal sampling and isarithmic mapping of soil properties, IV-Sampling strategy. Journal of Soil Sciences, 32:1028-1032.

Caeiro S, Costa MH, Ramos TB. 2005. Assessing Heavy Metal Contamination in Sado Estuary Sediment: An Index Analysis Approach. Ecological Indicators, 5:151-169.

Cheng JL, Shi Z, Zhu YW. 2007. Assessment and Mapping of Environmental Quality in Agricultural Soils of Zhejiang Province, China. Journal of Environmental Sciences, 19:50-54.

Committee of Soil Standard Methods for Analyses and Measurements. 1986. Soil Standard Methods for Analyses and Measurements. Hakuyusha, Tokyo, Japan.

DelValls TA, Forja JM, Go ´mez-Parra A. 1998. Integrated assessment of sediment quality in two littoral ecosystems from the Gulf of Ca ´diz, Spain. Environ. Toxicol. Chem., 17:1073-1084.

Forstner U. 1981. Metal pollution assessment from different analysis, In: Forstner, U. and Wittmann, G.T.W., (eds) metal pollution in the aquatic environment Springer, Berlin Heidelberg, New York, p 486.

Gong Qingjie, Deng Jun, Xiang Yunchuan, Wang Qingfei, Yang Liqiang. 2008. Calculating Pollution Indices by Heavy Metals in Ecological Geochemistry Assessment and a case study in Parks of Beijing, Journal of China University of Geosciences, 19(3): 230-241.

Hooda PS and Naidu R. 2004. Speciation, bioavailability and toxicity relationships of contaminants in the terrestrial environment, in: Proceedings of International Contaminated Site Remediation Conference, Adelaide, South Australia, 15–18, September.

Jaquet JM, Davaud E, Rapin F and Vernet JP. 1982. Basic concepts and associated statistical methodology in geochemical study of lake sediments, Hydrobiologia,, 91(1): 139-146.

Johansson SAE, Johansson TB. 1976. Analytical application of particle induced X-ray emission. Nuclear Instruments and Methods 137(3):473-516.

Nriagu J, Wong HKT, Lawson G and Daniel P. 1998. Saturation of ecosystems with toxic metals in Sudbury basin, Ontario, Canada, The Science of the Total Environment, 223, 99-117.

Ott WR. 1978. Environmental Indices—Theory and Practice. Ann Arbor Science, Michigan, USA, 371.

Riba I, DelValls TA, Forja JM, Go ´mez-Parra, A. 2002a. Evaluating the heavy metal contamination in sediments from the Guadalquivir estuary after the Aznalco ´ llar mining spill (SW Spain): a multivariate analysis approach. Environ. Monit. Assess. 77:191-207.

Sarala Thambavani D and Sabitha MA. 2012a. Multivariate statistical analysis between COD and BOD of sugar mill effluent, Scholarly Journal of Mathematics and Computer Science Vol. 1(1):6-12.

Sarala Thambavani D and Sabitha MA. 2011. Variation in air pollution tolerance index and anticipated performance index of plants near a sugar factory: implications for landscape-plant species selection for industrial areas, Journal of Research in Biology, 7:494-502.

Sarala Thambavani D and Sabitha, MA. 2012b. Soil physico-chemical characteristics affected by sugar industry effluent at Alanganallur, Tamil Nadu, J. Ecotoxicol. Environ. Monit., 22(3):245-252.

Sarala Thambavani D, Sabitha MA and Rajeswari G. 2009a. Tolerance of plants to air pollution near leather tanneries, J. Ecotoxicol. Environ. Monit., 19(6):609-612.

Sarala Thambavani D, Sabitha MA and Selvasundari R. 2009b. Air Pollution Tolerance Index of tree species growing in traffic area of Madurai, Tamil Nadu, The Asian Journal of Experimental Chemistry, 4(1 & 2):126-132.

Sayadi MH, Sayyed MRG and Shabani N. 2009. Quantification of heavy metal pollutants in the surface soils of Chitgar industrial area Tehran, Iran with spatial references to their spatial pattern, Pollution Research, 28: 345-351.

Senesi GS, Baldassarre G, Senesi N, Radina B. 1999. Trace element inputs by anthropogenic activities and implications for human health. Chemosphere 39:343- 377.

U.S.E.P.A. 2003. Drinking water contaminants, National primary drinking water regulations, EPA 816-F-03-016.

Usero J, Gonza ´lez-Regalado E, Gracia I. 1996. Trace metals in the bivalve mollusc Chamelea gallina from the Atlantic Coast of Southern Spain. Mar. Pollut. Bull. 32(3):305-310.

W.H.O. 2004. Guidelines for Drinking Water Quality, 3rd ed., ISBN 9241546387, Retrieved from http://www.who.int/water sanitation health/dwq/guidelines/ en/.

Wheater CP, Cook PA. 2002. Using Statistics to Understand the Environment. Routledge, London, 254.

Wilson JG, Jeffrey DW. 1987. Europe-wide indices for monitoring estuarine quality. In: Kramer, K.J.M. (Ed.), Biological Indicators of Pollution. Royal Irish Academy, Dublin, Ireland, 225-242.

Copyright license for the research articles published in Journal of Research in Biology are as per the license given below

Creative Commons License
Journal of Research in Ecology is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0). (www.creativecommons.org)
Based on a work at www.jresearchbiology.com
What this License explains us?

You are free to:

Share — copy and redistribute the material in any medium or format

Adapt — remix, transform, and build upon the material

for any purpose, even commercially.

This license is acceptable for Free Cultural Works. The licensor cannot revoke these freedoms as long as you follow the license terms.

[As given in the www.creativecommons.org website]

Under the following terms:

Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.