Identification and risk prediction of potentially contaminated sites in the Yangtze River Delta.

Identification and risk prediction of potentially contaminated sites (PCS) are crucial for the management of contaminated sites. However, the identification and risk prediction methods of PCS are lacking at a regional scale. Here, we established the fuzzy matching algorithm based on the site's name for identifying PCS in the Yangtze River Delta (YRD) from 2000 to 2020. The results showed that PCS in the YRD increased by over ten times, from 336 in 2000 to 4191 in 2020. Socio-economic and physical geography drive the growth of PCS and its spatiotemporal distribution, while the former has a more significant impact than the latter. We also presented a risk probability zoning strategy based on the source-pathway-receptor model, and proposed the patch-generating land-use simulation model to predict the risk probability of PCS in 2030. The results of risk probability zoning from 2000 to 2020 indicated that the local government of the YRD has started to pay attention to PCS management and risk control while developing social and economic. The results of risk prediction demonstrated that the proportion of low-risk probability pixels is 96.1% in 2030. Therefore, the planned indicator in the Action Plan on contaminated sites established by the State Council of China can be achieved in the YRD. Our experience in identifying and predicting PCS can inform how the local government worldwide manages PCS and tackles future challenges of achieving the ambition of site pollution control.

How the Air Clean Plan and carbon mitigation measures co-benefited China in PM2.5 reduction and health from 2014 to 2020.

China implemented a stringent Air Clean Plan (ACP) since 2013 to address environmental and health risks caused by ambient fine particulate matter (PM2.5). However, the policy effectiveness of ACP and co-benefits of carbon mitigation measures to environment and health are still largely unknown. Using satellite-based PM2.5 products produced in our previous study, concentration-response functions, and the logarithmic mean Divisia index (LMDI) method, we analyzed the spatiotemporal dynamics of premature deaths attributable to PM2.5 exposure, and quantitatively estimated the policy benefits of ACP and carbon mitigation measures. We found the annual PM2.5 concentrations in China decreased by 33.65 % (13.41 µg m-3) from 2014 to 2020, accompanied by a decrease in PM2.5-attributable premature deaths of 0.23 million (95 % confidence interval (CI): 0.22-0.27), indicating the huge benefits of China ACP for human health and environment. However, there were still 1.12 million (95 % CI: 0.79-1.56) premature deaths caused by the exposure of PM2.5 in mainland China in 2020. Among all ACP measures, clean production (contributed 55.98 % and 51.14 % to decrease in PM2.5 and premature deaths attributable to PM2.5) and energy consumption control (contributed 32.58 % and 29.54 % to decrease in PM2.5 and premature deaths attributable to PM2.5) made the largest contribution during the past seven years. Nevertheless, the environmental and health benefits of ACP are not fully synergistic in different regions, and the effectiveness of ACP measures reduced from 2018 to 2020. The co-effects of CO2 and PM2.5 has become one of the major drivers for PM2.5 and premature deaths reduction since 2018, confirming the clear environment and health co-benefits of carbon mitigation measures. Our study suggests, with the saturation of clean production and source control, more targeted region-specific strategies and synergistic air pollution-carbon mitigation measures are critical to achieving the WHO's Air Quality Guideline target and the UN's Sustainable Development Goal Target in China.