A Framework for Assessing Uncertainty Associated with Human Health Risks from MSW Landfill Leachate Contamination. Issue 7 (24th September 2016)

• Record Type: Journal Article
• Authors: Mishra, Harshit; Karmakar, Subhankar; Kumar, Rakesh; Singh, Jitendra
• Is Part Of: Risk analysis. Volume 37:Issue 7(2017)
• Page Start: 1237
• Page End: 1255
• Publication Date: 2016-09-24
• Subjects: Cubic spline -- human health risk assessment -- LandSim -- leachate -- Monte Carlo analysis -- Mumbai -- Turbhe landfill -- uncertainty modeling; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12713
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract : Landfilling is a cost‐effective method, which makes it a widely used practice around the world, especially in developing countries. However, because of the improper management of landfills, high leachate leakage can have adverse impacts on soils, plants, groundwater, aquatic organisms, and, subsequently, human health. A comprehensive survey of the literature finds that the probabilistic quantification of uncertainty based on estimations of the human health risks due to landfill leachate contamination has rarely been reported. Hence, in the present study, the uncertainty about the human health risks from municipal solid waste landfill leachate contamination to children and adults was quantified to investigate its long‐term risks by using a Monte Carlo simulation framework for selected heavy metals. The Turbhe sanitary landfill of Navi Mumbai, India, which was commissioned in the recent past, was selected to understand the fate and transport of heavy metals in leachate. A large residential area is located near the site, which makes the risk assessment problem both crucial and challenging. In this article, an integral approach in the form of a framework has been proposed to quantify the uncertainty that is intrinsic to human health risk estimation. A set of nonparametric cubic splines was fitted to identify the nonlinear seasonal trend in leachate quality parameters. LandSim 2.5, a landfill simulator, was used to simulate the landfill activities for various time slices, and further uncertainty in noncarcinogenic human health risk was estimated using a Monte Carlo simulation followed by univariate and multivariate sensitivity analyses.