Xiaoying Li

Large-scale residential energy transitions from solid fuel to clean energy are promising strategies to mitigate climate change and improve population health, but rigorous evaluation of their impacts is rare. China’s Clean Heating Policy (CHP) aimed to transition tens of millions of households from coal to electric and gas-based space heating. Following evidence of policy-driven improvements in indoor air pollution and indoor temperature, we evaluated the CHP’s impact on blood pressure (BP). In winter 2018–2019, we enrolled 1,003 adults aged >40 years from 50 Beijing villages not yet treated by the CHP; 20 villages were treated during follow-up (winters 2019–2020 and 2021–2022). Brachial and central BP and covariates were measured during household visits by trained staff. Policy impacts were estimated using an extended two-way fixed-effects difference-in-differences approach with village-clustered standard errors and adjustment for key BP predictors to improve precision. We found evidence of reductions (in mmHg) in brachial systolic BP (−1.4, 95% confidence interval [CI]: −3.3, 0.5), central systolic BP (−1.5, 95% CI: −3.3, 0.4), brachial diastolic BP (−1.6, 95% CI: −2.9, −0.3), and central diastolic BP (−1.6, 95% CI: −2.9, −0.3) among villages treated by the CHP compared with those untreated. Treatment effects varied by the year villages were treated by the CHP (p for homogeneity = 0.00 to 0.14) with greater BP reductions among participants in earlier-treated villages. Household energy policies like the CHP may serve as effective population-level interventions to reduce BP in China and complement high-risk cardiovascular prevention strategies.

Municipal solid waste landfills can emit complex mixtures of volatile organic compounds (VOCs), but community exposures are difficult to characterize because concentrations vary across space and time and may be influenced by episodic odor events, meteorology, and nonlandfill sources. Community-engaged research approaches can help address these challenges while incorporating residents’ local knowledge and concerns into monitoring study design. We conducted a community-engaged citizen-science study using a modified Ultrasonic Personal Air Sampler operated in accordance with U.S. EPA Method TO-17 to assess outdoor VOCs near the Bristol Virginia Solid Waste landfill. Concentrations of benzene, toluene, ethylbenzene, and xylenes (BTEX) remained below U.S. EPA Reference Concentrations during sampling, but were significantly higher on “Stinky” nights, suggesting elevated levels of selected VOCs during odor-relevant periods. However, measured VOCs did not fully explain odor perception, likely because odor-active sulfur-containing compounds were not captured and odor events were spatially and temporally variable. Source apportionment indicated that, in addition to landfill-related emissions, traffic-related sources contributed substantially to outdoor BTEX. Estimated noncarcinogenic and carcinogenic risks were within levels of low health concern. These results demonstrate the feasibility of conducting more scalable, cost-effective near-reference monitoring through a community-engaged framework enabled by innovative sampling technology.

China's Clean Heating Policy (CHP), aimed at shifting households from coal to electricity for space heating, represents a major residential energy transition initiative. We evaluated its multi-year impacts on outdoor, indoor, and personal exposures to PM_2.5 and black carbon (BC) across 50 villages and 1,236 households in rural Beijing. Using a difference-in-differences (DiD) design, we observed a substantial (31 μg/m³) reduction in winter (3 month) indoor PM_2.5 (95% CI: -53, -9), but an increase in 24-h indoor BC by 2.6 (0.4, 4.7) μg/m³. CHP-driven reductions in personal exposures were limited, emphasizing the limitations of using single 24-h measurements to estimate "usual" exposure. Outdoor air quality improved in all villages, with no difference between treated versus untreated villages. Exposure-energy trade-off analysis showed that untreated households achieved similar personal PM_2.5 reductions at lower cost, with smaller coal use reductions and less electricity expenditures. The CHP significantly reduced seasonal indoor PM_2.5, but continued burning of biomass, which was accessible at no cost, limited air quality improvements and may have contributed to the observed increase in 24-h indoor BC. This illustrates how behavioral choices, economic feasibility, and selection of exposure metrics influence the measured impact of household energy transitions.

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.

Background: Outdoor and household PM_2.5 are established risk factors for chronic disease and early mortality. In China, high levels of outdoor PM_2.5 and solid fuel use for cooking and heating, especially in winter, pose large health risks to the country’s aging population. Hand grip strength is a validated biomarker of functional aging and strong predictor of disability and mortality in older adults. We investigated the effects of wintertime household and outdoor PM_2.5 on maximum grip strength in a rural cohort in Beijing. Methods: We analyzed data from 877 adults (mean age: 62 y) residing in 50 rural villages over three winter seasons (2018–2019, 2019–2020, and 2021–2022). Outdoor PM_2.5 was continuously measured in all villages, and household (indoor) PM_2.5 was monitored for at least two months in a randomly selected ~30% subsample of homes. Missing data were handled using multiple imputation. We applied multivariable mixed effects regression models to estimate within- and between-individual effects of PM_2.5 on grip strength, adjusting for demographic, behavioral, and health-related covariates. Results: Wintertime household and outdoor PM_2.5 concentrations ranged from 3 to 431 μg/m³ (mean = 80 μg/m³) and 8 to 100 μg/m³ (mean = 49 μg/m³), respectively. The effect of a 10 μg/m³ within-individual increase in household and outdoor PM_2.5 on maximum grip strength was 0.06 kg (95%CI: −0.01, 0.12 kg) and 1.51 kg (95%CI: 1.35, 1.68 kg), respectively. The household PM_2.5 effect attenuated after adjusting for outdoor PM_2.5, while outdoor PM_2.5 effects remained robust across sensitivity analyses. We found little evidence of between-individual effects. Conclusions: We did not find strong evidence of an adverse effect of household PM_2.5 on grip strength. The unexpected positive effects of outdoor PM_2.5 on grip strength may reflect transient physiological changes following short-term exposure. However, these findings should not be interpreted as evidence of protective effects of air pollution on aging. Rather, they highlight the complexity of air pollution’s health impacts and the value of longitudinal data in capturing time-sensitive effects. Further research is needed to better understand these patterns and their implications in high-exposure settings.

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.

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.

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 (PM_2.5) and black carbon (BC). The geometric mean personal exposure to PM_2.5 and BC was 72 and 2.5 μg/m³, respectively. The variability in PM_2.5 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 PM_2.5 and BC. Wealthier households tended to burn more coal for space heating, whereas less wealthy households used more biomass. PM_2.5 and BC exposures were almost uniformly distributed by socioeconomic status. Future work that combines these results with PM_2.5 chemical composition analysis will shed light on whether air pollution source contributors (e.g., industrial, traffic, and household solid fuel burning) follow similar distributions.

Through the analysis of the common types of trash can and considering the shortcomings of traditional trash can in garbage classification, this paper designs a safe and energy-saving intelligent trash can based on STC89C54 Microcontroller Unit (MCU) as microprocessor. The trash can is underpinned by six modules: solar power supply module, infrared detection module, key module, ultrasonic ranging module, temperature detection module and display module. It carries a controllable telescopic cutter which is convenient for opening the sealing film of the beverage cup, with a view to realize the automatic opening and closing of the trash can cover, equipped with the functions of real-time measurement, display and alarm of the height and temperature of garbage in the trash can. Compared with the traditional trash can, its functions are comprehensive and easy to realize, with a good application prospect.