The Chinese government implemented a national household energy transition program that replaced residential coal heating stoves with electricity-powered heat pumps for space heating in northern China. As part of a baseline assessment of the program, this study investigated variability in personal air pollution exposures within villages and between villages and evaluated exposure patterns by sociodemographic factors. We randomly recruited 446 participants in 50 villages in four districts in rural Beijing and measured 24 h personal exposures to fine particulate matter (PM2.5) and black carbon (BC). The geometric mean personal exposure to PM2.5 and BC was 72 and 2.5 μg/m3, respectively. The variability in PM2.5 and BC exposures was greater within villages than between villages. Study participants who used traditional stoves as their dominant source of space heating were exposed to the highest levels of PM2.5 and BC. Wealthier households tended to burn more coal for space heating, whereas less wealthy households used more biomass. PM2.5 and BC exposures were almost uniformly distributed by socioeconomic status. Future work that combines these results with PM2.5 chemical composition analysis will shed light on whether air pollution source contributors (e.g., industrial, traffic, and household solid fuel burning) follow similar distributions.

The coronavirus (COVID‐19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID‐19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID‐19 lockdown in homes with different energy use patterns. Using calibrated real‐time PM2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID‐19 lockdown. Community pollution was higher during the lockdown (61 ± 47 μg/m3) compared with before (45 ± 35 μg/m3, p < 0.001) and after (47 ± 37 μg/m3, p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM2.5 during the COVID‐19 lockdown. Indoor‐generated PM2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID‐19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID‐19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.