4.7 Article

Eco-efficiency optimization for municipal solid waste management

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 104, Issue -, Pages 242-249

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2014.09.091

Keywords

Climate change; Municipal solid waste; Cost benefit analysis; Eco-efficiency; Beijing

Funding

  1. Fund for Innovative Research Group of the National Natural Science Foundation of China [51121003]
  2. National Natural Science Foundation of China [41271105]

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Carbon emission from municipal solid waste (MSW) treatment is one of the anthropogenic sources to cause climate change, which accounts for 3-5% of global greenhouse gas emissions according to the report of the United Nations Environment Programme (UNEP). At the same time, the gases and liquid discharged from MSW treatment can also cause other environmental impacts, such as climate change, photochemical ozone synthesis, and acidification, especially in huge city with huge population as Beijing, China. This paper proposed an eco-efficiency analysis method, which aimed to yield maximum overall environmental improvement per unit investment cost during its life cycle processing. This method took the overall reduction in the environmental impact of MSW treatment using cost-effective techniques as the objective to optimize waste disposal systems. The separation ratio during MSW collection and the proportion of techniques used for treatment were the major indicators for optimization measures. For Beijing, an increase in the waste separation ratio during collection proved to be the most effective measure, with an eco-efficiency score of 0.144. Adjustment of the proportion of treatment techniques used was less eco-efficient, with an increase in the proportion of composting being the most effective approach. Based on real needs, the objective should be to reduce the proportion of landfills used and increase the amount of composting and incineration. This optimization measure had the lowest cost and an eco-efficiency score of 0.0461, which is 60% higher than that for the measure with the lowest eco-efficiency. (C) 2014 Elsevier Ltd. All rights reserved.

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