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A human health risk assessment (HHRA) will not remain simple and straightforward when it involves multiple uncertain input variables. Uncertainties in HHRA result from the unavailability and subjectivity of input variables. Though several studies have performed HHRA, the quantification of uncertainty in HHRA under a situation of data scarcity and the simultaneous application of random and non-random input variables have rarely been reported. The present study proposes an integrated hybrid health risk modeling framework involving the concurrent treatment of random and non-random input variables and estimating the uncertainties linked to the input variables in HHRA. The proposed framework presents the flexibility to classify the input variables into fuzzy and probabilistic categories, based on their data availability and provenience nature. The framework is demonstrated over the Turbhe sanitary landfill in Navi Mumbai, India, where the fate and transport of heavy metals in leachate are investigated through LandSim modeling. The present study considers the LandSim-simulated heavy metal concentration and body weight as a random variable and water intake, exposure duration, frequency, bioavailability, and average time as fuzzy variables. Further, the uncertainties in the non-carcinogenic human health risk have been quantified using Monte Carlo simulations, followed by a comprehensive multivariate sensitivity analysis of the proposed framework. High health risk at Turbhe is estimated for the male and female population. This study presents the first effort to quantify the non-carcinogenic human health risks from leachate-contaminated groundwater considering the health risk input variables as non-deterministic. The proposed framework is generic and applicable to any landfill site and will remain unaltered when integrated health risk assessment and uncertainty assessment are performed for the landfill., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The handling and management of municipal solid waste (MSW) are major challenges for solid waste management in developing countries. Open dumping is still the most common waste disposal method in India. However, landfilling also causes various environmental, social, and human health impacts. The generation of heavily polluted leachate is a major concern to public health. Engineered barrier systems (EBSs) are commonly used to restrict potentially harmful wastes by preventing the leachate percolation to groundwater and overflow to surface water bodies. The EBSs are made of natural (e.g., soil, clay) and/or synthetic materials such as polymeric materials (e.g., geomembranes, geosynthetic clay liners) by arranging them in layers. Various studies have estimated the human health risk from leachate-contaminated groundwater. However, no studies have been reported to compare the human health risks, particularly due to the leachate contamination with different liner systems. The present study endeavors to quantify the human health risk to contamination from MSW landfill leachate using multiple simulations for various EBSs. To quantify the variation in health risks to groundwater consumption to the child and adult populations, the Turbhe landfill of Navi Mumbai in India has been selected. The leachate and groundwater samples were collected continuously throughout January-September in 2015 from the landfill site, and heavy metal concentrations were analyzed using an inductively coupled plasma system. The LandSim 2.5 Model, a landfill simulator, was used to simulate the landfill activities for various time slices, and non-carcinogenic human health risk was determined for selected heavy metals. Further, the uncertainties associated with multiple input parameters in the health risk model were quantified under a Monte Carlo simulation framework.

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., (© 2016 Society for Risk Analysis.)

Rapid industrialisation, growing population and changing lifestyles are the root causes for the generation of huge amounts of solid waste in developing countries. In India, disposal of municipal solid waste (MSW) through open dumping is the most common waste disposal method. Unfortunately, leachate generation from landfill is high due to the prolonged and prominent monsoon season in India. As leachate generation rate is high in most of the tropical countries, long-term and extensive monitoring efforts are expected to evaluate actual environmental pollution potential due to leachate contamination. However, the leachate characterisation involves a comprehensive process, which has numerous shortcomings and uncertainties possibly due to the complex nature of landfilling process, heterogeneous waste characteristics, widely varying hydrologic conditions and selection of analytes. In order to develop a sustainable MSW management strategy for protecting the surface and ground water resources, particularly from MSW landfill leachate contamination, assessment and characterisation of leachate are necessary. Numerous studies have been conducted in the past to characterise leachate quality from various municipal landfills; unfortunately, none of these propose a framework or protocol. The present study proposes a generic framework for municipal landfill leachate assessment and characterisation. The proposed framework can be applied to design any type of landfill leachate quality monitoring programme and also to facilitate improved leachate treatment activities. A landfill site located at Turbhe, Navi Mumbai, India, which had not been investigated earlier, has been selected as a case study. The proposed framework has been demonstrated on the Turbhe landfill site which is a comparatively new and the only sanitary landfill in Navi Mumbai.