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.

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM_2.5, avoiding 130,000 (90,000–160,000) premature deaths associated with PM_2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m² in 1992 to 0.031 ± 0.008 W/m² in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m³ to population-weighted PM_2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM_2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent.

Significance: Impacts of a newly launched rural residential solid fuel substitution campaign in China’s Beijing–Tianjin–Hebei area on energy, emission, air quality, and exposure reveal that abating solid fuels will significantly reduce ambient and indoor air pollution, resulting in major health benefits. The campaign will help accelerate China’s energy transition and reduce PM_2.5emission and exposure. The expected exposure reduction is largely due to improved indoor air quality, resulting in greater benefits to women.

Direct residential and transportation energy consumption (RTC) contributes significantly to ambient fine particulate matter with a diameter smaller than 2.5 μm (PM_2.5) in China. During massive rural-urban migration, population and pollutant emissions from RTC have evolved in terms of magnitude and geographic distribution, which was thought to worsen PM_2.5 levels in cities but has not been quantitatively addressed. We quantify the temporal trends and spatial patterns of migration to cities and evaluate their associated pollutant emissions from RTC and subsequent health impact from 1980 to 2030. We show that, despite increased urban RTC emissions due to migration, the net effect of migration in China has been a reduction of PM_2.5 exposure, primarily because of an unequal distribution of RTC energy mixes between urban and rural areas. After migration, people have switched to cleaner fuel types, which considerably lessened regional emissions. Consequently, the national average PM_2.5 exposure concentration in 2010 was reduced by 3.9 μg/m³ (90% confidence interval, 3.0 to 5.4 μg/m³) due to migration, corresponding to an annual reduction of 36,000 (19,000 to 47,000) premature deaths. This reduction was the result of an increase in deaths by 142,000 (78,000 to 181,000) due to migrants swarming into cities and decreases in deaths by 148,000 (76,000 to 194,000) and 29,000 (15,000 to 39,000) due to transitions to a cleaner energy mix and lower urban population densities, respectively. Locally, however, megacities such as Beijing and Shanghai experienced increases in PM_2.5 exposure associated with migration because these cities received massive immigration, which has driven a large increase in local emissions.