How Do Household Energy Transitions Work?

Abstract

Introduction: Since 2015, thousands of rural and peri-urban villages across Beijing and northern China have been treated by a household Clean Heating Policy (CHP) that banned household coal burning and subsidized the costs of electric heaters and electricity. Whether this large-scale policy was successful in improving air quality and health remains an important and unresolved question. We estimated the effects of the CHP policy on air quality and cardiopulmonary health in Beijing villages and quantified how much of the policy's effects on health were mediated by changes in air pollution and indoor temperature.

Methods: In winter 2018-2019, we enrolled 1,003 participants in 50 Beijing villages that were eligible for, but not currently treated by, the CHP and followed them over four consecutive winter data collection waves. In waves 1, 2, and 4, we administered questionnaires and measured participants' anthropometrics, blood pressure (BP), airway inflammation (fractional concentration of exhaled nitric oxide [FeNO]), and 24-hour personal exposure to fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter [PM_2.5]). Fasting whole blood samples were obtained at clinic visits in waves 1 and 2 for analysis of glucose, lipid profile, and markers of inflammation and oxidative stress. We attempted to contact all prior participants in each follow-up wave. If a previously enrolled participant was not at home or refused subsequent participation, staff first tried to randomly recruit an eligible participant from the same household. If this was not possible, village guides helped field staff to enroll a new participant from a new household using the same sampling procedures as the baseline. Wintertime outdoor PM_2.5 was measured in all four waves, and wintertime indoor PM_2.5 was measured in waves 2, 3, and 4. Indoor temperature was measured in all waves. The PM_2.5 filters were analyzed for their mass, black carbon (BC), and chemical composition, which were used for source apportionment. To estimate the impacts of the policy, we used a difference-in-differences design that accommodated the staggered rollout of the CHP. We used "extended" two-way fixed effects models and marginal effects to quantify the effect of the policy on air pollution and health outcomes. We further evaluated whether villages treated by the policy in different years responded differently to the policy and whether the observed health impacts of the policy were mediated through changes in air pollution or home (indoor) temperature.

Results: We enrolled a total of 1,438 participants from 1,236 households during our four study waves. At baseline (wave 1), the mean participant age was 60 years old (standard deviation [SD] = 9.2), 60% of participants were female, and most participants (63%) worked in agriculture. Geometric mean personal exposures to PM_2.5 were twice as high as outdoor PM_2.5 (72 vs. 36 µg/m³), and the main source contributors were local and transported dust, regional and domestic coal and biomass burning, and secondary pollutants. By waves 2, 3, and 4, there were cumulative totals of 10, 17, and 20 villages (of 50 total) exposed to the CHP. Uptake and adherence to the policy were high: among villages treated in wave 2, the proportion of households using heat pumps and coal heaters, respectively, changed from 3% and 97% in wave 1 to 94% and 3% in wave 4, with similar clean energy transitions in villages exposed to the policy in later waves. Marginal effects derived from multivariable extended two-way fixed effects models showed that exposure to the policy increased wintertime indoor temperature by 1° to 2°C and reduced indoor seasonal PM_2.5 by approximately 20 µg/m³. Treatment by the policy also reduced contributions to PM_2.5 from solid fuel sources, including household coal burning, and improved BP (~1.5 mm Hg lower systolic BP [SBP] and diastolic BP [DBP]) and self-reported respiratory symptoms (~8 percentage point reduction in any symptoms). There was notable heterogeneity in effects across treatment cohorts, with larger benefits to indoor PM_2.5 and health in villages treated in earlier years relative to later years. In the mediation analysis, indoor PM_2.5 and indoor temperature explained most of the total effect of the policy on SBP and roughly half of the total effect on DBP, but this did not explain improvements in self-reported respiratory symptoms. We did not find evidence of meaningful effects of the policy on outdoor or personal exposure to PM_2.5 or on biomarkers of inflammation and oxidative stress.

Conclusions: In this comprehensive field-based assessment of a large-scale household energy policy in Beijing, we observed high fidelity and compliance with the CHP. Exposure to the policy reduced BP and self-reported chronic respiratory symptoms, and the effects for BP were mediated by reductions in indoor PM_2.5 and improvements in home temperature, providing empirical evidence that clean household energy policies can provide population health benefits.