Analysis and Selection of Appropriate Aggregation Function for Calculating of Leachate Pollution Index of Landfill Lysimeter

A technique to quantify the leachate pollution potential of solid waste landfills on a comparative scale using an index known as the leachate pollution index (LPI) developed. The LPI is a quantitative tool by which the leachate pollution data of the landfill sites can be reported uniformly. It is an...

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Bibliographic Details
Published inIranica journal of energy & environment Vol. 3; no. 4; pp. 370 - 379
Main Author Rafizul, Islam M.
Format Journal Article
LanguageEnglish
Published Babol Noshirvani University of Technology 2012
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Summary:A technique to quantify the leachate pollution potential of solid waste landfills on a comparative scale using an index known as the leachate pollution index (LPI) developed. The LPI is a quantitative tool by which the leachate pollution data of the landfill sites can be reported uniformly. It is an increasing scale index and has been formulated based on Delphi technique. The formulation process involved selecting variables, deriving weights for the selected pollutant variables, formulating their sub-indices curves and finally representing the pollutant variables to arrive at LPI. The aggregation function is one of the most important steps in calculating any environmental index. If aggregation function is ambiguous, the result will raise an unnecessary alarm, indicating a comparatively less polluted environmental situation as mere contaminated. Similarly, if the aggregation function is eclipsed a false sense of security may be created, indicating a highly polluted environmental situation as less polluted. In this paper, the concept of LPI is briefly described. In order to select the most appropriate aggregation function, various possible aggregation functions are described and used to calculate LPI values for pilot scale landfill lysimeter at KUET campus, Khulna, Bangladesh. Based on obtained results, it is concluded that the weighted linear sum aggregation function is the best possible aggregation function for calculating LPI. Sensitivity analysis of the six short-listed aggregation functions is performed to substantiate this conclusion.
ISSN:2079-2115
2079-2123
DOI:10.5829/idosi.ijee.2012.03.04.11