Differentiated-Rate Clean Heating Strategy with Superior Environmental and Health Benefits in Northern China

Costs and Benefits of Household Fuel Policies and Alternative Strategies in the Jing-Jin-Ji Region

Air pollution is still one of the most severe problems in northern China, especially in the Jing-Jin-Ji region around Beijing. In recent years, China has implemented many stringent policies to address the air quality issue, including promoting energy transition toward cleaner fuels in residential sectors. But until 2020, even in the Jing-Jin-Ji region, nearly half of the rural households still use solid fuels for heating. For residents who are not covered by the clean heating campaign, we analyze five potential mitigation strategies and evaluate their environmental effects as well as the associated health benefits and costs. We estimate that substitution with electricity or gas would reduce air pollution and premature mortality more strongly, while the relatively low investment costs of implementing clean coal or biomass pellet lead to a larger benefit-cost ratio, indicating higher cost efficiency. Hence, clean coal or biomass pellet could be transitional substitution options for the less developed or remote areas which cannot afford a total transition toward electricity or natural gas in the short term.

Economic Growth Facilitates Household Fuel Use Transition to Reduce PM2.5-Related Deaths in China

Exposure to ambient and indoor particle matter (PM2.5) leads to millions of premature deaths in China. In recent years, indoor air pollution and premature deaths associated with polluting fuel cooking demonstrate an abrupt decline. However, the driving forces behind the mortality change are still unclear due to the uncertainty in household fuel use prediction. Here, we propose an integrated approach to estimate the fuel use fractions and PM2.5-related deaths from outdoor and indoor sources during 2000-2020 across China. Our model estimated 1.67 and 1.21 million premature deaths attributable to PM2.5 exposure in 2000 and 2020, respectively. We find that the residential energy transition is associated with a substantial reduction in premature deaths from indoor sources, with 100,000 (95% CI: 76,000-122,000) for urban and 265,000 (228,000-300,000) for rural populations during 2000-2020. Economic growth is the dominant driver of fuel use transition and avoids 21% related deaths (357,000, 315,000-402,000) from polluting fuel cooking since 2000, which offsets the adverse impact of ambient emissions contributed by economic growth. Our findings give an insight into the coupled impact of socioeconomic factors in reshaping health burden in exposure pathways.

Pollution characteristics and light-driven evolution of environmentally persistent free radicals in PM2.5 in two typical northern cities of China

Environmentally persistent free radicals (EPFRs) in PM_2.5 can pose significant health risks by generating reactive oxygen species (ROS). In this study, Beijing and Yuncheng were chosen as two representative northern cities of China that mainly relied on natural gas and coal respectively as the energy source for domestic heating in winter. The pollution characteristics and exposure risks of EPFRs in PM_2.5 around the heating season of 2020 were investigated and compared between the two cities. Through laboratory simulation experiments, the decay kinetics and secondary formation of EPFRs in PM_2.5 collected in both cities were also studied. EPFRs in PM_2.5 collected in Yuncheng in the heating period showed longer lifetime and lower reactivity, suggesting that EPFRs originated from coal combustion were more stable in the atmosphere. However, the generation rate of hydroxyl radical (·OH) by the newly formed EPFRs in PM_2.5 in Beijing under ambient conditions was 4.4 times of that in Yuncheng, suggesting higher oxidative potential of EPFRs from the atmospheric secondary processes. Accordingly, the control strategies of EPFRs and their health risks were raised for the two cities, which would also have direct implication for the control of EPFRs in other areas of similar atmospheric emission and reaction patterns.

Significant but Inequitable Cost-Effective Benefits of a Clean Heating Campaign in Northern China

Residential emissions significantly contribute to air pollution. To address this issue, a clean heating campaign was implemented to replace coal with electricity or natural gas among 13.9 million rural households in northern China. Despite great success, the cost-benefits and environmental equity of this campaign have never been fully investigated. Here, we modeled the environmental and health benefits, as well as the total costs of the campaign, and analyzed the inequality and inequity. We found that even though the campaign decreased only 1.1% of the total energy consumption, PM_2.5 emissions and PM_2.5 exposure experienced 20% and 36% reduction, respectively, revealing the amplification effects along the causal pathway. Furthermore, the number of premature deaths attributable to residential emissions reduced by 32%, suggesting that the campaign was highly beneficial. Governments and residents shared the cost of 2,520 RMB/household. However, the benefits and the costs were unevenly distributed, as the residents in mountainous areas were not only less benefited from the campaign but also paid more because of the higher costs, resulting in a notably lower cost-effectiveness. Moreover, villages in less developed areas tended to choose natural gas with a lower initial investment but a higher total cost (2,720 RMB/household) over electricity (2,190 RMB/household). With targeted investment and subsidies in less developed areas and the promotion of electricity and other less expensive alternatives, the multidevelopment goals of improved air quality, reduced health impacts, and reduced inequity in future clean heating interventions could be achieved.

Improving Building Envelope Efficiency Lowers Costs and Emissions from Rural Residential Heating in China

In 2017, the Chinese government launched a clean heating campaign that replaced millions of rural coal stoves with various clean heaters. The clean heating program contributed to remarkable improvements in air quality. However, the benefits of reducing heating demand by improving building envelope efficiency were not sufficiently considered. This study provides a needed quantitative assessment of potential energy-savings, costs, greenhouse gas emission reductions, and adoption strategies for improving building envelope efficiency in Chinese rural residential buildings. We find that different strategies must be employed in existing and new buildings to achieve desired outcomes. For existing buildings, to encourage easy and beneficial building retrofits (e.g., air sealing, efficient windows), current fuel subsidies should be replaced with retrofit subsidies. Building retrofits can reduce the size and hence capital costs of new clean heaters. They can also reduce operating costs, hence reducing the likelihood of backsliding to coal. For new construction, whole-home insulation and heat pumps would best avoid carbon lock-in. These efficient technologies have high upfront costs but decrease heating costs and significantly reduce carbon emissions relative to current policies. Hence, subsidies and policies that encourage improvements in building envelopes as well as the uptake of clean and efficient heaters are critical.

Heterogeneous changes of chemical compositions, sources and health risks of PM2.5 with the "Clean Heating" policy at urban/suburban/industrial sites

China has enacted the "Clean Heating" (CH) policy in north China. The domain-specific impacts on PM2.5 constituents and sources in small cities are still lacking, which obstruct the further policy optimization. Here, we performed an intensive observation covering the heating period (HP) and pre-heating period (PHP) in winter of 2017 at urban (UR), industrial (IS), and suburban (SUR) sites in one of the "2 + 26" cities. The mean PM2.5 concentrations at UR and IS decreased by 15.2 % and 4.6 %, while increased by 9.8 % at SUR in the HP compared with the PHP, indicating the heterogeneous responses. The lowest contribution percentages of coal combustion (14.6 %) and industrial emissions (17.1 %) to PM2.5 at UR in the HP implied the CH policy played more effective role. The most increase in NO3-/SO42- ratio by 26.8 % and the highest NO3- concentration at UR in the HP were linked mainly with the thermal-NOx emitted from natural gas (NG) burning in view of NOx emission reductions from other sources. The highest concentrations of OC, SO42-, K+, and Cl-, and contribution percentages of biomass burning (20.0 %) and coal combustion (24.8 %) to PM2.5 at SUR in the HP evidenced the enhanced usage of biomass/coal. Coal banning in the HP at IS and UR led to the obvious decreases in OC, SO42-, As, and Sb. Secondary nitrate became the largest PM2.5 source at IS and UR in the HP. Coal banning, emission control on large-size enterprises and ignored control on small-size enterprises efficiently modified the concentrations and health risks of heavy metals. The lowest carcinogenic risks moved from SUR in the PHP to UR in the HP. The policies on de-NOx of NG-burning related enterprises, reduction of biomass/coal usage in suburban area, and strict regulation of small-size enterprises were urgently need to further improve the air quality.

Substantial transition to clean household energy mix in rural China

The household energy mix has significant impacts on human health and climate, as it contributes greatly to many health- and climate-relevant air pollutants. Compared to the well-established urban energy statistical system, the rural household energy statistical system is incomplete and is often associated with high biases. Via a nationwide investigation, this study revealed high contributions to energy supply from coal and biomass fuels in the rural household energy sector, while electricity comprised ∼20%. Stacking (the use of multiple sources of energy) is significant, and the average number of energy types was 2.8 per household. Compared to 2012, the consumption of biomass and coals in 2017 decreased by 45% and 12%, respectively, while the gas consumption amount increased by 204%. Increased gas and decreased coal consumptions were mainly in cooking, while decreased biomass was in both cooking (41%) and heating (59%). The time-sharing fraction of electricity and gases (E&G) for daily cooking grew, reaching 69% in 2017, but for space heating, traditional solid fuels were still dominant, with the national average shared fraction of E&G being only 20%. The non-uniform spatial distribution and the non-linear increase in the fraction of E&G indicated challenges to achieving universal access to modern cooking energy by 2030, particularly in less-developed rural and mountainous areas. In some non-typical heating zones, the increased share of E&G for heating was significant and largely driven by income growth, but in typical heating zones, the time-sharing fraction was <5% and was not significantly increased, except in areas with policy intervention. The intervention policy not only led to dramatic increases in the clean energy fraction for heating but also accelerated the clean cooking transition. Higher income, higher education, younger age, less energy/stove stacking and smaller family size positively impacted the clean energy transition.

Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020

Anthropogenic emissions and ambient fine particulate matter (PM2.5) concentrations have declined in recent years across China. However, PM2.5 exposure remains high, ozone (O3) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010-2020. We show that PM2.5 exposure peaked in 2012 at 52.8 μg m-3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM2.5 exposure declined by 36% to 33.5 μg m-3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM2.5 exposure below the World Health Organization Interim Target 2 (25 μg m-3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.

Source contributions and drivers of physiological and psychophysical cobenefits from major air pollution control actions in North China

North China is among the most polluted regions in the country, and human exposure to PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) in this region has led to severe health consequences. The region has also benefited the most from emission reductions in recent years. It is of interest to understand to what extent and through which paths emissions from different sectors cause adverse health impacts. Here, we present the results of a full evaluation of the health benefits of emission control actions implemented in recent years based on segregated emission inventories with an emphasis on residential emissions. Two major causal paths, one from residential emissions to indoor air pollution, exposure, and premature deaths, and the other from nonresidential emissions to ambient air pollution and psychophysical impacts, were identified and quantified. From 2014 to 2019, both ambient (33%) and indoor (39%) PM_2.5 decreased significantly, leading to decreasing trends in exposure (36%), premature deaths (10%), and psychophysical impacts (21%). The Air Pollution Prevention and Control Action Plan, the Clean Heating Campaign, and spontaneous residential shifts to clean energy contributed significantly to these reductions when the effects of other drivers, such as population and economic growth, were excluded.

Toward Clean Residential Energy: Challenges and Priorities in Research

Solid fuels used for cooking, heating, and lighting are major emission sources of many air pollutants, specifically PM_2.5 and black carbon, resulting in adverse environmental and health impacts. At the same time, the transition from using residential solid fuels toward using cleaner energy sources can result in significant health benefits. Here, we briefly review recent research progress on the emissions of air pollutants from the residential sector and the impacts of emissions on ambient and indoor air quality, population exposure, and health consequences. The major challenges and future research priorities are identified and discussed.

Updated Global Black Carbon Emissions from 1960 to 2017: Improvements, Trends, and Drivers

Accurate estimation of black carbon (BC) emissions is essential for assessing the health and climate impact of this pollutant. Past emission inventories were associated with high uncertainty due to data limitations, and recent information has provided a unique updating opportunity. Moreover, understanding the drivers that cause temporal emission changes is of research value. Here, we update the global BC emission estimates using new data on the activities and emission factors (EFs). The new inventory covers 73 detailed sources at 0.1° × 0.1° spatial resolution and monthly temporal resolution from 1960 to 2017. The estimated annual emissions were 32% higher than the average of several previous inventories, which was primarily due to field-measured EFs for residential stoves and differentiated EFs for motor vehicles. In addition, the updated emissions show an inverse U-shaped temporal trend, which was mainly driven by the interaction between the positive effects of population growth, per capita energy consumption, and vehicle fleet and the negative effects of residential energy switching, stove upgrading, phasing out of beehive coke ovens, and reduced EFs for vehicles and industrial processes. Urbanization caused a significant increase in urban emissions accompanied by a more significant decline in rural emissions.

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM_2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM_2.5 concentrations for a given input configuration of emission changes. PM_2.5 concentrations are primarily sensitive to residential (51%-94% of first-order sensitivity index), industrial (7%-31%), and agricultural emissions (0%-24%). Sensitivities of PM_2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM_2.5 exposure for changes in the five emission sectors is by 68%-81%, down to 15.3-25.9 μg m^-3, remaining above the World Health Organization annual guideline of 10 μg m^-3. The greatest reductions in PM_2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 μg m^-3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors.

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51%-94% of first-order sensitivity index), industrial (7%-31%), and agricultural emissions (0%-24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68%-81%, down to 15.3-25.9 μg m-3, remaining above the World Health Organization annual guideline of 10 μg m-3. The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 μg m-3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors.