Chao Huang’s research while affiliated with China University of Geosciences and other places

China is an extremely sensitive nation severely impacted by global climate change, with frequent floods in the Yangtze River Economic Zone causing severe socioeconomic losses and ecological and environmental issues. To investigate the potential industry-related economic losses and comprehensive hazards of flooding in the Yangtze River Economic Zone, as well as to investigate the comprehensive improvement of disaster resilience, this paper first uses an input–output model to account for the indirect economic losses caused by floods to various industries in different years. On this basis, a comprehensive flood risk assessment system was constructed from five aspects, including meteorological and geographical conditions, exposure, vulnerability, emergency response and recovery capacity, and disaster losses; the entropy weight method and TOPSIS method were used to rank the flood risks, while ArcGIS was used for visualization and analysis. The results indicate that the most severe economic losses affected by floods in 2020, 2017 and 2012 are in Anhui, Hunan and Sichuan, respectively; manufacturing, agriculture, forestry, animal husbandry and fishery, transportation and storage, and electricity, heat and production and supply are all highly sensitive sectors that are severely impacted by flooding. The risk assessment indicates that the integrated flood risk in the upstream areas of Yunnan and Chongqing has been low and belongs to the low or medium–low risk area, whereas the integrated flood risk in the downstream areas is high, with Shanghai belonging to the high risk area in each of the three years. Lastly, effective regional flood risk management countermeasures are proposed.

Analyzing the driving factors of PM2.5 pollution in different industries is of great significance for developing energy conservation and emission reduction policies in China's industries. In this study, the consumption-based PM2.5 emissions of China's industries are estimated by using an input–output model; on this basis, the generalized Divisia index method (GDIM) is used to measure the contributions of driving factors to the changes in PM2.5 emissions from China's six major industries. The results show that China's consumption-based PM2.5 emissions presented a downward trend from 2007 to 2015, the changes in industrial PM2.5 emissions had a much higher impact on China's total PM2.5 emissions changes than other industries and occupied a dominant position. The generalized Divisia index decomposition analysis results show that investment, output and energy consumption scale were the primary contributors to the increase of PM2.5 emissions in six sectors, with investment scale contributing the most. The investment PM2.5 emission intensity, output PM2.5 emission intensity and energy consumption PM2.5 intensity play a major role in suppressing PM2.5 emissions, while investment efficiency and energy intensity have a smaller inhibitory effect. Therefore, the government should guide investments to more high-end, low-emission industries and encourage companies to increase green investments and use renewable energy and clean energy. Avoiding excessive investments and improving investment efficiency in related industries can also effectively alleviate PM2.5 emissions.

Currently, interprovincial trade and the industrial division of labor in China are rapidly developing. The end users of products are not responsible for their wastewater discharge but indirectly transfer their own wastewater discharge to production locations through trade flows. This undoubtedly exacerbates the burden of environmental governance at production locations and results in the unreasonable sharing of discharge reduction responsibility between production and consumption areas of products. Studies that focus on the embodied wastewater transfer caused by interprovincial trade and its drivers are important for the formulation of equitable emission reduction targets and environmental policies. Therefore, based on the multiregional input-output (MRIO) model and structural decomposition analysis (SDA), this paper analyzes the transfer and driving factors of industrial embodied wastewater in interprovincial trade in China at the interprovincial and industrial sector levels. The results demonstrate that the transfer volume of industrial embodied wastewater increased from 5,423,884,700 tons in 2012 to 6,343,801,700 tons in 2015 in Chinese interprovincial trade, at a growth rate of 16.96%. The regions with industrial embodied wastewater net outflows were mainly located in eastern regions with a more well-developed manufacturing industry such as Shandong and Jiangsu, the net inflow areas were mainly concentrated in central and western regions such as Chongqing, Sichuan and Yunnan. From the perspective of the industrial sector, the chemical industry, papermaking and printing and manufacturing industry of cultural items, education resources and sports goods, and food manufacturing and tobacco processing industry were the three key sectors regarding the inflow and outflow of embodied wastewater in trade. Through SDA, it was found that the growth of the economic scale was the main reason for the outflow of industrial embodied wastewater in the various provinces. The technology effect imposed a negative influence on the transfer of industrial embodied wastewater in most provinces, especially in Henan and Guangxi. In the short term, technology improvements can be employed to reduce the transfer volume of industrial embodied wastewater, but in the long term, industrial structure optimization and upgrading are required to reduce the discharge and transfer of industrial embodied wastewater. Therefore, to reduce water pollution and control industrial wastewater discharge, it is necessary to consider the transfer and main driving factors of embodied wastewater caused by interprovincial trade when assigning environmental governance responsibilities to each province.

Currently, preventing and controlling air pollution and inhibiting the excessively rapid growth of medical expenditures to reduce the living burden of residents have become a focus of general concern of society as a whole. It is of great significance to conduct an in-depth study of the relationship between air pollution and public health expenditure and clarify to what extent air pollution affects health expenditure. Thus, this paper adopted spatial econometric methods to measure the impact of air pollution on residents’ health expenditure via panel data from 16 core cities in the Yangtze River Delta in China from 2005 to 2017. The results indicate that (1) at present, the air pollution in the Yangtze River Delta core urban agglomeration is still relatively prominent and has obvious spatial aggregation phenomena, and the particulate matter 2.5 (PM2.5) concentration shows the characteristic of decreasing gradually from northwest to southeast; (2) air pollution is the main factor that promotes the increase in residents’ health expenditure; (3) the spatial spillover effect of air pollution is obvious, accounting for half of the total effect; and (4) the impact of government public services on residents’ health expenditure varies. Finally, this paper proposes corresponding policy implications based on the findings.