Modeling Environmental Susceptibility of Municipal Solid Waste Disposal Sites: A Case Study in São Paulo State, Brazil

Abstract

The large excess of solid waste generated in cities is a result of population growth and economic development. Properly managing this municipal solid waste (MSW) is a challenge, mainly in underdeveloped and developing countries where financial concerns are an added problem. From the environmental point of view, a major issue is properly disposing MSW taking into consideration a wide range of factors, and working with different spatial data. In this study, we used geographic information system (GIS) to perform multi-criteria decision analysis (MCDA) conducted by analytical hierarchy process (AHP). The development of the environmental impact susceptibility model (EISM) for municipal solid waste disposal sites (MSWDS) applied to the state of São Paulo, Brazil considered factors such as geology, pedology, geomorphology, water resources, and climate represented by fifteen associated sub-factors. The results indicated that more than 82% of São Paulo's territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 18% of the state land area, 85 landfills are located in areas with high and very high environmental impact susceptibility categories. These results are alarming because these 85 landfills receive approximately 17,886 tons of MSW on a daily basis, which corresponds to 46% of all municipal solid waste disposed in São Paulo state. Therefore, decision makers, urban planners and policymakers could use the findings of the EISM towards mitigating the environmental impacts caused by MSWDS.

Integrating GIS and multi-criteria decision analysis for landfill site selection, case study: Javanrood County in Iran

“…The first fundamental step in site selection was the determination of criteria to assess the suitability of land to gain the objectives. In this study, criteria were selected based on literature review (Marin et al 2012;Karimzadeh Motlagh and Sayadi 2015;Rahmat et al 2017; Bahrani et al Kahraman et al 2017;Victor et al 2017;Khan et al 2018), national regulations and standards (Department of the Environment 2011), data availability, regional characteristics and expert opinion. Eight criteria were selected and classified into the main group (Fig.…”

“…Moreover, this combination can be used for a vast range of spatial tasks and provide solutions for the problems in environmental sensitivity analysis. An integrating approach of the GIS and MCDA has widely been used in landfill site selection studies (Moeinaddini et al 2010;Eskandari et al 2012;Gorsevski et al 2012;Nazari et al 2012;Alavi et al 2013;Gbanie et al 2013;Feo and Gisi 2014;Ashraf et al 2015;Karimzadeh Motlagh and Sayadi 2015;Rahmat et al 2017;Bahrani et al 2016;Aksoy and San 2017;Barakat et al 2016;Kahraman et al 2017;Victor et al 2017;Al-Anbari et al 2018;Khan et al 2018;Santhosh and Sivakumar 2018;Yildirim et al 2018;Demesouka et al 2019).…”

A New Strategy for Consortium Sanitary Landfill Allocation Based on Multicriteria Analysis

“…Selecting a suitable landfill area using MCDA in a GIS-based environment is the traditional approach and was applied in different countries, such as USA (Chang et al, 2008), China (Wang et al, 2009), Sierra Leone (Gbanie et al, 2012), Italy (De Feo and De Gisi, 2014), Ghana (Bosompem et al, 2016), India (Kumar and Hassan, 2013;Kolekar et al, 2017), Canada (Khan et al, 2018, Turkey (Yesilnacarar et al, 2012;Yildirim and Guler, 2016;Yildirim et al, 2018), Iran (Eskandari et al, 2012;Alanbari et al, 2014;Motlagh and Sayadi, 2015;Rahmat et al, 2016;Torabi-Kaveh et al, 2016;Khodaparast et al, 2018;Khoshand et al, 2018;Karimi et al, 2018) and Brazil (Nascimento and Silva, 2014;Nascimento et al, 2017;Colvero et al, 2018;Pavani et al, 2019). To construct the inference models, the aforementioned studies adopted criteria divided into three basic contexts: environment, social, and economic.…”

Regional Distance Routes Estimation for Municipal Solid Waste Disposal, Case Study São Paulo State, Brazil

“…According to [25,26], in all activities involving the MSW collection and transport operation, it is essential to consider vehicle itineraries and efficient routes to minimize the distance covered, as well as the cost and time. Hence, GIS can be regarded as an effective method for analyzing spatial data in MSW studies [27][28][29][30][31]. This technology and its different processes associated with MSW management applications are widely accepted [9].…”