Coal-fired power plants (CPPs) dominate China's energy supply systems. Over the past two decades, the explosive growth of CPPs has led to negative air quality and health impacts in China, and a series of control policies have been implemented to alleviate those impacts. In this work, by combining a CPPs emission database over China (CPED), a regional chemical transport model (WRF-CMAQ), and the integrated exposure-response model, we summarized historical and ongoing emission control policies on CPPs over China, investigated the air quality and health impacts of China's CPPs during 2005-2020, and quantified the benefits of each policy. We found that despite the 97.4% growth of coal-fired power generation during 2005-2015, PM 2.5 exposures caused by emissions from China's CPPs decreased from 9.0 μg m −3 in 2005 to 3.6 μg m −3 in 2015. The active emission control policies have decreased CPPs-induced PM 2.5 exposures by 10.0 μg m −3 during 2005-2015. We estimated that upgrading end-of-pipe control facilities and early retirement of small and low-efficiency units could respectively reduce PM 2.5 exposures by 7.9 and 2.1 μg m −3 during 2005-2015 and avoid 111 900 and 31 400 annual premature deaths. Since 2015, China's government has further required all CPPs to comply with the so-called 'ultra-low emission standards' before 2020 as a major component of China's clean air actions. If the policy is fully deployed, CPPs-induced PM 2.5 exposures could further decrease by 2.5 μg m −3 and avoid 43 500 premature deaths annually. Our study confirms the effectiveness of tailored control policies for China's CPPs and reveals that those policies have played important roles in air quality improvement in China.

As the largest energy infrastructure in China, the power sector consumed approximately half of China's coal over the past decade and threatened air quality and greenhouse gas (GHG) abatement targets. In this work, we assessed the evolution of coal-fired power plants and associated emissions in China during 2010−2030 by using a unit-based emission projection model, which integrated the historical power plant information, turnover of the future power plant fleet, and evolution of end-of-pipe control technologies. We found that, driven by stringent environmental legislation, SO 2 , NO x , and PM 2.5 (particulate matter less than 2.5 μm in diameter) emissions from coalfired power plants decreased by 49%, 45%, and 24%, respectively, during 2010−2015, compared to 15% increase in CO 2 emissions. In contrast to everincreasing CO 2 emissions until 2030 under current energy development planning, we found that aggressive energy development planning could curb CO 2 emissions from the peak before 2030. Owing to the implementation of a "near zero" emission control policy, we projected emissions of air pollutants will significantly decrease during 2016−2030. Early retirement of small and low-efficiency power plants would further reduce air pollutants and CO 2 emissions. Our study explored various mitigation pathways for China's coal-fired power plants, which could reduce coal consumption, air pollutants, and CO 2 emissions and improve energy efficiency.

Abstract. Direct measurements of NOx, CO and aromatic volatile organic compound (VOC) (benzene, toluene, C2-benzenes and C3-benzenes) flux were made for a central area of Beijing using the eddy-covariance technique. Measurements were made during two intensive field campaigns in central Beijing as part of the Air Pollution and Human Health (APHH) project, the first in November–December 2016 and the second during May–June 2017, to contrast wintertime and summertime emission rates. There was little difference in the magnitude of NOx flux between the two seasons (mean NOx flux was 4.41 mg m−2 h−1 in the winter compared to 3.55 mg m−2 h−1 in the summer). CO showed greater seasonal variation, with mean CO flux in the winter campaign (34.7 mg m−2 h−1) being over twice that of the summer campaign (15.2 mg m−2 h−1). Larger emissions of aromatic VOCs in summer were attributed to increased evaporation due to higher temperatures. The largest fluxes in NOx and CO generally occurred during the morning and evening rush hour periods, indicating a major traffic source with high midday emissions of CO, indicating an additional influence from cooking fuel. Measured NOx and CO fluxes were then compared to the MEIC 2013 emissions inventory, which was found to significantly overestimate emissions for this region, providing evidence that proxy-based emissions inventories have positive biases in urban centres. This first set of pollutant fluxes measured in Beijing provides an important benchmark of emissions from the city which can help to inform and evaluate current emissions inventories.

Abstract. Air quality in China has changed dramatically in response to rapid development of the economy and to policies. In this work, we investigate the changes in anthropogenic source contribution to ambient fine particulate matter (PM2.5) air pollution and related health impacts in China during 1990–2015 and elucidate the drivers behind the decadal transition. We estimate the contribution of five anthropogenic emitting sectors to ambient PM2.5 exposure and related premature mortality over China during 1990–2015 with 5-year intervals, by using an integrated model framework of a bottom-up emission inventory, a chemical transport model, and the Global Exposure Mortality Model (GEMM). The national anthropogenic PM2.5-related premature mortality estimated with the GEMM for nonaccidental deaths due to noncommunicable diseases and lower respiratory infections rose from 1.26 million (95 % confidence interval (CI) [1.05, 1.46]) in 1990 to 2.18 million (95 % CI [1.84, 2.50]) in 2005; then, it decreased to 2.10 million (95 % CI [1.76, 2.42]) in 2015. In 1990, the residential sector was the leading source of the PM2.5-related premature mortality (559 000, 95 % CI [467 000, 645 900], 44 % of total) in China, followed by industry (29 %), power (13 %), agriculture (9 %), and transportation (5 %). In 2015, the industrial sector became the largest contributor of PM2.5-related premature mortality (734 000, 95 % CI [615 500, 844 900], 35 % of total), followed by the residential sector (25 %), agriculture (23 %), transportation (10 %), and power (6 %). The decadal changes in source contribution to PM2.5-related premature mortality in China represent a combined impact of socioeconomic development and clean-air policy. For example, active control measures have successfully reduced pollution from the power sector, while contributions from the industrial and transportation sectors have continuously increased due to more prominent growth in activity rates. A transition in fuel consumption has dominated the decrease in the contribution from residential sector. Meanwhile, the contribution from the agriculture sector has continuously increased due to persistent NH3 emissions and enhanced formation of secondary inorganic aerosols under an NH3-rich environment.

Abstract. We examine the street-scale variation of NOx, NO2, O3 and PM2.5 concentrations in Beijing during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) winter measurement campaign in November–December 2016. Simulations are performed using the urban air pollution dispersion and chemistry model ADMS-Urban and an explicit network of road source emissions. Two versions of the gridded Multi-resolution Emission Inventory for China (MEIC v1.3) are used: the standard MEIC v1.3 emissions and an optimised version, both at 3 km resolution. We construct a new traffic emissions inventory by apportioning the transport sector onto a detailed spatial road map. Agreement between mean simulated and measured pollutant concentrations from Beijing's air quality monitoring network and the Institute of Atmospheric Physics (IAP) field site is improved when using the optimised emissions inventory. The inclusion of fast NOx–O3 chemistry and explicit traffic emissions enables the sharp concentration gradients adjacent to major roads to be resolved with the model. However, NO2 concentrations are overestimated close to roads, likely due to the assumption of uniform traffic activity across the study domain. Differences between measured and simulated diurnal NO2 cycles suggest that an additional evening NOx emission source, likely related to heavy-duty diesel trucks, is not fully accounted for in the emissions inventory. Overestimates in simulated early evening NO2 are reduced by delaying the formation of stable boundary layer conditions in the model to replicate Beijing's urban heat island. The simulated campaign period mean PM2.5 concentration range across the monitoring network (∼15 µg m−3) is much lower than the measured range (∼40 µg m−3). This is likely a consequence of insufficient PM2.5 emissions and spatial variability, neglect of explicit point sources, and assumption of a homogeneous background PM2.5 level. Sensitivity studies highlight that the use of explicit road source emissions, modified diurnal emission profiles, and inclusion of urban heat island effects permit closer agreement between simulated and measured NO2 concentrations. This work lays the foundations for future studies of human exposure to ambient air pollution across complex urban areas, with the APHH-China campaign measurements providing a valuable means of evaluating the impact of key processes on street-scale air quality.