Literature DB >> 28681321

Assessment of air quality in Haora River basin using fuzzy multiple-attribute decision making techniques.

Ajit Pratap Singh1, Sumanta Chakrabarti2, Sumit Kumar3, Anjaney Singh4.   

Abstract

This paper deals with assessment of air quality in Haora River basin using two techniques. Initially, air quality indices were evaluated using a modified EPA method. The indices were also evaluated using a fuzzy comprehensive assessment (FCA) method. The results obtained from the fuzzy comprehensive assessment method were compared to that obtained from the modified EPA method. To illustrate the applicability of the methodology proposed herein, a case study has been presented. Air samples have been collected at 10 sampling sites located along Haora River. Six important air pollutants, namely, carbon monoxide, sulfur dioxide, nitrogen dioxide, suspended particulate matter (SPM), PM10, and lead, were monitored continuously, and air quality maps were generated on the GIS platform. Comparison of the methodologies has clearly highlighted superiority and robustness of the fuzzy comprehensive assessment method in determining air quality indices under study. It has effectively addressed the inherent uncertainties involved in the evaluation, modeling, and interpretation of sampling data, which was beyond the scope of the traditional weighted approaches employed otherwise. The FCA method is robust and prepares a credible platform of air quality evaluation and identification, in face of the uncertainties that remain eclipsed in the traditional approaches like the modified EPA method. The insights gained through the present study are believed to be of pivotal significance in guiding the development and implementation of effective environmental remedial action plans in the study area.

Entities:  

Keywords:  Air quality; Fuzzy comprehensive assessment; Pollution; Suspended particulate matter

Mesh:

Substances:

Year:  2017        PMID: 28681321     DOI: 10.1007/s10661-017-6075-3

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  8 in total

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  8 in total
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Journal:  Environ Monit Assess       Date:  2018-11-14       Impact factor: 2.513

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  4 in total

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