A stepwise emission clustering analysis method for analyzing the effects of heavy metal emissions from multiple income groups
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Emissions of various heavy metals (i.e. Hg, As, Cd, Cr and Pb) have emerged as one of the most tremendous pressures on the socio-economic and environmental systems. The pressures caused by such heavy metals would be getting intensified if no adequate and timely solution is implemented, especially because their emissions are associated with economic activities (i.e. regional trade and household consumption). In this study, emissions of various heavy metals derived from regional trade as well as rural and urban household consumption are quantified to identify the critical regions and significant household consumption. In order to detail the impacts of household consumption on such emissions, rural and urban household are divided respectively into five and seven groups with hierarchic income from poorest to richest. The Hg, As, Cd, Cr and Pb emissions caused by intermediate commodity consumption are 1172.86, 2607.57, 23.28, 57.49 and 85.16 tons, respectively. Among them, such emissions induced by self-consumption are 662.95, 1539.34, 12.28, 33.10 and 43.49 tons. Shandong, Guangdong and Jiangsu are identified for high self-emissions due to their advanced economy and rare resources. On the contrast, Hebei and Shanxi with abundant resources are the critical regions for the high transfer-out emissions. Moreover, emissions of multiple heavy metals are inequal due to the variations of rural and urban income groups. Emissions caused by R5 are identified through stepwise cluster analysis for its significant difference in compare with other income groups. It is verified that the main difference of emissions in economically developed regions are caused by rural income groups, while urban income groups are the critical reason for the disaggregation of emissions in less developed regions. Policies should be further implemented based on the regional similarity and income-group inequality.