In China, ambient fine particulate matter (PM2.5) causes a large health burden and raises specific concerns for policymakers. However, assessments of the health effects associated with air pollution from industrial land layouts remain inadequate. This study established a comprehensive assessment framework to quantify the health and economic impacts of PM2.5 exposure at different industrial geographical locations. This framework aims to optimize the spatial distribution of industrial emissions to achieve the lowest public health costs in Changsha, a representative industrial city in China. Health effects were estimated by applying the integrated exposure-response model and a long-range pollution dispersion model (CALPUFF). The value of statistical life (VSL) was used to monetize health outcomes. It was found that implementing an optimal industrial land layout can yield considerable social and financial benefits. Compared with the current industrial space layout, in 2030, the averted contribution by Changsha's industrial sector to PM2.5-related mortality and corresponding economic losses will be 60.8% and 0.69 billion US dollars (USD), respectively. The results of optimization analyses highlighted that population density and emission location are significant factors affecting the health burden. This method can identify the optimal geographical allocation of industrial land with minimal expected health and economic burden. These results will also provide policymakers with a measurable assessment of health risks related to industrial spatial planning and the associated health costs to enhance the effectiveness of efforts to improve air quality.
Keywords: Economic burden; Emission locations; Health impacts; Industrial land layout; PM(2.5).
Copyright © 2020 Elsevier Ltd. All rights reserved.