Impacts of air pollution and its spatial spillover effect on public health based on China's big data sample

Although the existing studies have paid much attention to the issue on the impacts of air pollution on public health, they fail to consider the spatial spillover effect and externality of air pollution as a significant influencing factor of public health, causing the biased results. This paper employs a spatial Durbin model (SDM) to investigate the impacts of both air pollution and its spatial spillover effect on public health in 116 cities of China over 2006-2012. We use the survey data of lung cancer mortality and respiratory diseases mortality from 161 sites of mortality censoring spots in China to measure public health and use the statistical data of industrial emissions of sulfur dioxide and soot from the corresponding cities to measure air pollution. Compared with the existing studies, from the perspective of the scale and scope of dataset, our dataset can be regarded as a big data sample in the fields of environmental and health economics. We estimate the direct and indirect effects of air pollution to distinguish the local and neighbors' impacts of air pollution on the mortalities caused by the two diseases. The empirical results provide the evidence for the adverse impacts of air pollution and its spatial spillover effect on public health. On average, an increase of ten thousand tonnes in industrial sulfur dioxide emissions in certain city will lead to an increase of 0.035 and 0.03 per ten thousand persons in local mortalities from lung cancer and respiratory diseases, respectively, and a total increase of 0.217 and 1.543 per ten thousand persons in the mortalities of all its neighbors from lung cancer and respiratory diseases, respectively. On an annual average, due to the air pollution, more than 200 billion RMB are spent on the medical treatment for curing health damages, and approximate hundred thousand lives were taken away. (C) 2016 Elsevier Ltd. All rights reserved.