Background: The impact of environmental pollution (such as air pollution) on health costs has received a great deal of global attention in the last 20 years. Methods: This review aims to summarize the theoretical analysis model of air pollution affecting health costs, and further explore the actual characteristics of the impact of air pollution on health costs. The following main databases were taken into account: Web of Science Core Collection, Medline, SCOPUS, PubMed, and CNKI (China). As of 30 March 2021, we retrieved a total of 445 papers and ended up with 52 articles. Results: This review mainly expounds clarification of the concept of air pollution and health costs, the theoretical model and the actual characteristics of air pollution affecting health costs. In addition, it also discusses other related factors affecting health costs. Conclusion: Our conclusion is that, while academic research on the relationship between air pollution and health costs has made some progress, there are still some shortcomings, such as insufficient consideration of individual avoidance behavior and rural–urban and international mobility. Therefore, the simple use of the original data obtained in the statistical yearbook of the health cost caused by air pollution is also the reason for the errors in the empirical results. In addition, the choice of proxy variables of environmental pollution by scholars is relatively simple, mainly focusing on air pollutants, while the impact of water quality or soil pollution safety on health costs is becoming increasingly prominent, and will become the focus of future research.

Background: The aging population has led to a growing health expenditure burden. According to the National Bureau of Statistics of China, the old-age dependency ratio rose from 10.7% in 2003 to 17.8% in 2019, and health expenditure increased from 658.410 billion yuan in 2003 to 5812.191 billion yuan in 2019 in China.Methods: This paper utilizes the quantile regression method to discuss the influencing factors of health expenditure in urban China based on the China Household Finance Survey (CHFS), especially dependency burden. Moreover, its regional heterogeneity is also compared.Results: The old-age dependency ratio, age, family size, self-rated health status, and income significantly impact the health expenditure of urban families in the quantile regression of the national sample. Dependency burden and other variables on urban household health expenditure have great regional heterogeneity. The relationship between urban health expenditure and residential areas in western China is more stable than that in eastern and central China.Discussion: Government should improve the healthcare system suitable for the older adult population as soon as possible. The government of western China should pay more attention to the introduction of professional medical talents and the configuration of precision medical equipment to improve the health system in western China.

A large amount of heavy metal (HM) inputs exists in the farming areas of the Hebei plain of northern China. However, the potential ecological risk, source, and input flux of HMs in these areas have not been well-investigated. In this study, atmospheric deposition, fertilizer, irrigation water, and agricultural soil samples were collected from farming areas (~74,111 km²) in Hebei Province, China. The HM index of geoaccumulation (I_geo) and potential ecological risk index (RI) of soil was calculated for eight HMs. The source and input flux of each element were predicted using the input flux and principal component score–multiple linear regression (PCS–MLR) methods. The results showed that Cd and Hg increased I_geo values, and the maximum levels of As (29.5 mg/kg), Cu (228.9 mg/kg), Cd (4.52 mg/kg), and Zn (879.0 mg/kg) were greater than the health risk screening values in the soil quality standard of China. The potential ecological risk factor (Er) of Cd demonstrated a moderately potential ecological risk, accounting for 67.72%. The distribution map showed that Cd was mainly concentrated in eastern area of Baoding (BD) in the study area. The result of the atmospheric dry and wet deposition contributed more to soil pollution than the usage of fertilizer or irrigation water by calculating the input flux. The order was Zn (94%) > Cu (92%) > Pb (89%) > Cr (86%) > Cd (72%) > Hg = Ni (71%) > As (59%). Principal component analysis (PCA) results showed that there were four sources of HMs in soil. Geological sources contribute to the accumulation of As, Cr, and Ni in soil. Cu and Pb in the soil were attributable to the input from vehicular emissions and irrigation water. Cd and Zn in the soil were attributable to the farming activity, whereas Hg originates from the combustion of coal. The results of PCS–MLR demonstrated that the contribution rate of As, Ni, and Cr in the study area was 30.06%, 71.86%, 57.71% for the first group (natural source); Cu, Pb and Zn were 71.78%, 63.59%, and 30.72% for the second group (vehicle emissions); Zn was 60.93% for the third group (fertilizer application and irrigation water); and Hg was 85.16%, for the fourth group (coal combustion). These factors provide a valuable reference for remediating HM pollution.

Against the global backdrop of the manufacturing industry (MFI)’s transition toward sustainability, we investigated the impact mechanisms and spatial effects of digital elements on the green upgrading of manufacturing industries. Based on an innovation ecosystem perspective, we utilize panel data from 13 prefecture-level cities in the Beijing–Tianjin–Hebei (BTH) region of China spanning 2003 to 2023, employing a spatial Durbin model (SDM) for empirical analysis. The findings reveal the following: (1) Both digital element inputs and manufacturing green upgrading in the BTH region exhibit significant positive spatial correlation, with the latter demonstrating notable path dependence. (2) While digital elements significantly drive local manufacturing green upgrading, they also generate a spatial siphon effect at the regional level, exerting a certain inhibitory impact on the green upgrading of neighboring areas. (3) Mechanism analysis indicates that local digital elements facilitate manufacturing green upgrading by enhancing firms’ digital innovation capabilities, stimulating consumer digital demand, and optimizing corporate resource allocation efficiency. This research provides theoretical support and empirical evidence for governments to formulate targeted digital economy policies and promote low-carbon, green development in the manufacturing industry (MFI).