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 PM_2.5 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 PM_2.5 during the COVID‐19 lockdown. Indoor‐generated PM_2.5 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.

Reliable assessment of personal exposure to air pollution remains a challenge due to the limitations of monitoring technology. Recent technology developments, such as reductions in the size and cost of samplers as well as incorporation of continuous sensors for location, activity, and exposure (i.e., global positioning systems [GPS], accelerometers, and low-cost pollutant sensors), have advanced our ability to assess personal exposure to air pollution. This study evaluated the upgraded Ultrasonic Personal Aerosol Sampler (UPAS v2.1 PLUS) as a tool for quantifying time-integrated indoor and personal exposure to particulate matter (PM) and black carbon (BC) among a panel of participants in California's Central Valley and exploring personal exposures in different microenvironments using time/location-resolved PM data. Three field campaigns demonstrated that filter-derived PM₁₀, PM_2.5, PM₁₀ BC, and PM_2.5 BC concentrations measured using the UPAS were linear, unbiased, and precise compared to those measured using conventional personal sampling equipment. Time-resolved PM, GPS, and light intensity data from the UPAS allowed for personal PM_2.5 exposure assessment across microenvironments. The majority of daily PM_2.5 exposure occurred inside the home. Participants with higher out-of-home PM_2.5 exposures received those exposures primarily in agricultural and in-transit environments, in accordance with their self-reported occupational exposures. This study demonstrated the UPAS v2.1 PLUS is a reliable and valid tool for characterizing indoor air pollution and personal exposures in both temporal and spatial dimensions. Its enhanced capabilities should reduce the burden of personal activity logging in the field and enable accurate and precise estimation of exposures for epidemiological and community-based research.

California’s San Joaquin Valley experiences some of the worst particulate matter (PM) air pollution in the U.S., but PM_2.5 and PM₁₀ exposures in agricultural communities are understudied. We collaborated with rural residents living adjacent to large-scale agricultural production and processing activities to assess 24-h-average personal and indoor PM_2.5 and PM₁₀ concentrations during different seasons. We visited 35 participants from 18 households during December 2023, May 2024, and the September 2024 harvest season to collect PM samples and survey data. Mixed effects linear regression models (with random effects for participant or household) assessed associations between natural log-transformed PM concentrations and regional ambient PM, harvest season, as well as participant/household characteristics. Participants were mostly female (69%) and Hispanic/Latino(a) (100%). Median household distance to processing facility silos was 633 m. Median personal exposures to PM_2.5 and PM₁₀ were 11.1 and 45.5 µg m⁻³. Median indoor PM_2.5 and PM₁₀ levels were 12.9 and 24.3 µg m⁻³. Overall, 29% of personal and indoor PM_2.5 samples and 33% of personal and indoor PM₁₀ samples exceeded WHO 24-h air quality guidelines (15 µg m⁻³ PM_2.5, 45 µg m⁻³ PM₁₀). The factors most strongly associated with personal and indoor PM were household members working in agriculture and regional ambient PM measures.