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Evaluating municipal solid waste dumps using geographic information system

100%

Mahmood K. , Batool S. A. , Chaudhry M. N. , Daud A.

Polish Journal of Environmental Studies

2015

tom 24

nr 2

This study evaluates two existing dumpsites, namely Saggian and Mahmood Booti, regarding their inappropriate locations and related hazards. Four parameters were considered for the assessment: 1) threat to residential areas, 2) surface water bodies, 3) road network and related data, and 4) fluvial sediment sequence to groundwater depth. Geographic information system (GIS) has been used to conduct the study. Both dumping sites are unsafe for the neighboring community as 6,731 and 9,490 houses were found to lie within the hazardous region (1000 m) around Saggian and Mahmood Booti sites, respectively. Among them, 6.4% houses around Saggian dump are within 210 m of the site, while around Mahmood Booti dump the residential area starts after 210 m. It was calculated that 249.5 m³/day and 519 m³/day leachate is being produced by Saggian and Mahmood Booti, respectively. Saggian dumpsite is found to be more dangerous with higher co-efficient of permeability (11.37×10⁻⁵m/s), high water table (18.2 m below surface), and its location along the bank of the Ravi River. However, a higher number of accidents is found near Mahmood Booti, which may be an effect of the obnoxious smell from the dumped waste.

Ranking criteria for assessment of municipal solid waste dumping sites

100%

Mahmood K. , Batool S. A. , Chaudhary M. N. , Ul-Haq Z.

tom Vol. 43, no. 1

95--105

Priority wise channelization of resources is the key to successful environmental management, especially when funds are limited. The study in hand has successfully developed an algorithmic criterion to compare hazardous effects of Municipal Solid Waste (MSW) dumping sites quantitatively. It is a Multi Criteria Analysis (MCA) that has made use of the scaling function to normalize the data values, Analytical Hierarchy Process (AHP) for assigning weights to input parameters showing their relevant importance, and Weighted Linear Combination (WLC) for aggregating the normalized scores. Input parameters have been divided into three classes namely Resident’s Concerns, Groundwater Vulnerability and Surface Facilities. Remote Sensing data and GIS analysis were used to prepare most of the input data. To elaborate the idea, four dumpsites have been chosen as case study, namely Old-FSD, New-FSD, Saggian and Mahmood Booti. The comparison has been made first at class levels and then class scores have been aggregated into environmental normalized index for environmental impact ranking. The hierarchy of goodness found for the selected sites is New-FSD > Old-FSD > Mahmood Booti > Saggian with comparative scores of goodness to environment as 36.67, 28.43, 21.26 and 13.63 respectively. Flexibility of proposed model to adjust any number of classes and parameters in one class will be very helpful for developing world where availability of data is the biggest hurdle in research based environmental sustainability planning. The model can be run even without purchasing satellite data and GIS software, with little inaccuracy, using imagery and measurement tools provided by Google Earth.