An Euler atmospheric transport model (Canadian Model for Environmental Transport of Organochlorine Pesticides, CanMETOP) was applied and validated to estimate polycyclic aromatic hydrocarbon (PAH) ambient air concentrations at ground level in China based on a high-resolution emission inventory. The results were used to evaluate lung cancer risk for the Chinese population caused by inhalation exposure to PAHs. The uncertainties of the transport model, exposure, and risk analysis were assessed by using Monte Carlo simulation, taking into consideration the variation in PAH emission, aerosol and OH radical concentrations, dry deposition, respiration rate, and genetic susceptibility. The average benzo[ a ]pyrene equivalent concentration (B[ a ]P _eq ) was 2.43 [≈1.29–4.50 as interquartile range (IR)] ng/m ³ . The population-weighted B[ a ]P _eq was 7.64 (IR, ≈4.05–14.1) ng/m ³ because of the spatial overlap of the emissions and population density. It was estimated that 5.8% (IR, ≈2.0–11%) of China's land area, where 30% (IR, ≈17–43%) of the population lives, exceeded the national ambient B[ a ]P _eq standard of 10 ng/m ³ . Taking into consideration the variation in exposure concentration, respiration rate, and susceptibility, the overall population attributable fraction (PAF) for lung cancer caused by inhalation exposure to PAHs was 1.6% (IR, ≈0.91–2.6%), corresponding to an excess annual lung cancer incidence rate of 0.65 × 10 ⁻⁵ . Although the spatial variability was high, the lung cancer risk in eastern China was higher than in western China, and populations in major cities had a higher risk of lung cancer than rural areas. An extremely high PAF of >44% was estimated in isolated locations near small-scale coke oven operations.

Residential contribution to air pollution–associated health impacts is critical, but inadequately addressed because of data gaps. Here, we fully model the effects of residential energy use on emissions, outdoor and indoor PM_2.5 concentrations, exposure, and premature deaths using updated energy data. We show that the residential sector contributed only 7.5% of total energy consumption but contributed 27% of primary PM_2.5 emissions; 23 and 71% of the outdoor and indoor PM_2.5 concentrations, respectively; 68% of PM_2.5 exposure; and 67% of PM_2.5-induced premature deaths in 2014 in China, with a progressive order of magnitude increase from sources to receptors. Biomass fuels and coal provided similar contributions to health impacts. These findings are particularly true for rural populations, which contribute more to emissions and face higher premature death risks than urban populations. The impacts of both residential and nonresidential emissions are interconnected, and efforts are necessary to simultaneously mitigate both emission types.

Increased human water use combined with climate change have aggravated water scarcity from the regional to global scales. However, the lack of spatially detailed datasets limits our understanding of the historical water use trend and its key drivers. Here, we present a survey-based reconstruction of China’s sectoral water use in 341 prefectures during 1965 to 2013. The data indicate that water use has doubled during the entire study period, yet with a widespread slowdown of the growth rates from 10.66 km ³ ⋅y ⁻² before 1975 to 6.23 km ³ ⋅y ⁻² in 1975 to 1992, and further down to 3.59 km ³ ⋅y ⁻² afterward. These decelerations were attributed to reduced water use intensities of irrigation and industry, which partly offset the increase driven by pronounced socioeconomic development (i.e., economic growth, population growth, and structural transitions) by 55% in 1975 to 1992 and 83% after 1992. Adoptions for highly efficient irrigation and industrial water recycling technologies explained most of the observed reduction of water use intensities across China. These findings challenge conventional views about an acceleration in water use in China and highlight the opposing roles of different drivers for water use projections.