RESUMEN

This study examined the potential health risks posed by the operation of 96 waste-to-energy (WtE) plants in 30 cities in the Bohai Rim of China. Utilizing a sophisticated simulation approach, the Weather Research and Forecasting (WRF) model coupled with the California Puff (CALPUFF) model, we obtained the spatial distribution of pollutants emitted by WtE plants in the atmosphere. Hazard indices (HI) and cancer risks (CR) were calculated for each plant using the United States Environmental Protection Agency's recommended methodologies. The results indicated that both HIs and CRs were generally low, with values below the accepted threshold of 1.0 and 1.0 × 10-6, respectively. Specifically, the average HI and CR values for the entire study area were 2.95 × 10-3 and 3.43 × 10-7, respectively. However, some variability in these values was observed depending on the location and type of WtE plant. A thorough analysis of various parameters, such as waste composition, moisture content, and operating conditions, was conducted to identify the factors that influence the health risks associated with incineration. The findings suggest that proper waste sorting and categorization, increased cost of construction, and elevated height of chimneys are effective strategies for reducing the health risks associated with incineration. Overall, this study provides valuable insights into the potential health risks associated with WtE plants in the Bohai Rim region of China. The findings can serve as useful guidelines for law enforcement wings and industry professionals seeking to minimize the risks associated with municipal solid waste (MSW) management and promote sustainable development.

RESUMEN

Waste treatment is a problem faced by cities all over the world. In recent years, China, as a developing country, regards the municipal solid waste (MSW) classification as one of the important strategies to deal with the MSW problem. The previous MSW classification policies in China were all only advocacy in nature. It was not until January 2019 that the "Regulations on the Management of MSW in Shanghai" was officially promulgated as China's first compulsory MSW classification policy, marking the beginning of an era of compulsory MSW classification in China. How effective is the implementation of Shanghai's compulsory MSW classification policy 18 months after its implementation and can developing countries continuously and effectively implement compulsory MSW classification policies? These are important issues of concern to the government, academia, and the public. This paper establishes a three-stage DEA model to evaluate the implementation effect of the compulsory MSW classification policies in Shanghai during the period of February 2019 and July 2020. The study found that the average efficiency of the compulsory MSW classification policy in Shanghai reached 0.906 during the study period, indicating that the policy was executed reasonably well. However, there are only 5 months in 18 months that the policy was fully effective (reaching efficiency level 1), suggesting that there is still room for improvement. The main reason for not being able to achieve full effectiveness in some months is attributed to scale efficiency. At the same time, the general public budget revenue and expenditure of environmental variables have positive and negative impacts on the policy implementation effect in Shanghai. The research results can provide experience for China to comprehensively implement the compulsory MSW classification policy in the future and can also provide valuable case study information for cities in other developing countries to implement the compulsory MSW classification policy.

RESUMEN

To promote sustainable development, the Chinese government launched a new municipal solid waste (MSW) classification strategy in 2017. Shanghai was selected as one of the first pilot cities for MSW classification. The Shanghai municipal government first established the new MSW classification policy in 2017. The Shanghai Municipal Solid Waste Management Regulation was published in 2019 and came into effect on 1 July 2019. This short communication reports on Shanghai's new MSW classification policy and its implementation. The main content and measures adopted by Shanghai's government to ensure the effective implementation of the new MSW classification policy are introduced. Besides, a SWOT (i.e., strengths, weaknesses, opportunities, and threats) analysis on the present policy and measures is conducted, and based on the results, some discussions and suggestions regarding the implementation of MSW classification in Shanghai and the whole of China are presented.

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RESUMEN

With the accelerating pace of urbanization, the continuous increase of municipal solid waste (MSW) has become a major obstacle to China's economic development. Therefore, China recently regards MSW classification scenario as an important strategy for national ecological civilization. However, published references have not focused on MSW classification in view of environmental, economic and social acceptation simultaneously. This research proposes a new Decision Support System (DSS) model considering all three aspects to analyze the comprehensive benefit of the four MSW classification scenarios in Pudong (Shanghai, China) using cost benefit analysis (CBA), life cycle assessment (LCA) and analytical hierarchy process (AHP). Among them, there is an important boundary factor in the life cycle assessment. This work mainly focuses on the net energy consumption, namely the air and water emission of different substances. The results show that the classification scenario II, dividing MSW into toxic and hazardous waste, recyclable, kitchen waste and combustible waste, is the best option. Although scenario III (MSW is divided into toxic and hazardous waste, recyclable waste (paper, plastic, scrap metal, waste glass and other small class), kitchen waste and combustible wastes) and IV (recyclable waste in Scenario II is further classified, for example, paper is subdivided into newspapers, books, cardboard, etc.) further refine the MSW classification, the DSS model analysis results indicate that neither of these are the most feasible scenario. Therefore, finer classification is not always the better if we consider all three pillars of sustainability.

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