Resident risk attitude analysis in the decision-making management of waste incineration construction.

Environmental pollutants generated by waste incineration plants, such as heavy metals and dioxin, make surrounding residents very sensitive to the construction of such facilities. This sensitivity and anxiety of residents may induce group events, which further leads to the emergence of social risks. Based on risk perception theory, a total of 320 questionnaires was designed and handed out to residents neighboring to Jiangqiao Waste Incineration Plant in Shanghai, China to detect the factors affecting risk attitude toward such plants. Using ordered logit model, it is found that there are four decisive factors including impact on health, information cognitive, objective characteristics, and the attitude of the neighbors. These factors have different influence on resident risk attitudes, in which the attitude of the neighbors is of most significance, followed by the economic-geography characteristics of residents, the information cognitive has minimal impact.

Is the finer the better for municipal solid waste (MSW) classification in view of recyclable constituents? A comprehensive social, economic and environmental analysis.

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.