Journal
WASTE MANAGEMENT
Volume 113, Issue -, Pages 508-520Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.wasman.2020.05.033
Keywords
Municipal solid waste; Greenhouse gas; Waste sector; Recycling; Environmental sustainability; Machine Learning
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Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990-2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach. Empirical findings underline a bidirectional causal relationship between municipal solid waste generation and GDP, indicating that the Environmental Kuznets Curve hypothesis holds for Switzerland. Moreover, we found that waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. In fact, in the Tree Model, the probability that a change in the waste recovery variable could lead to a reduction in the greenhouse gas emissions registered a value of 87%. (C) 2020 Elsevier Ltd. All rights reserved.
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