Abstract. To tackle the problem of severe air pollution, China has implemented active clean air policies in recent years. As a consequence, the emissions of major air pollutants have decreased and the air quality has substantially improved. Here, we quantified China's anthropogenic emission trends from 2010 to 2017 and identified the major driving forces of these trends by using a combination of bottom-up emission inventory and index decomposition analysis (IDA) approaches. The relative change rates of China's anthropogenic emissions during 2010–2017 are estimated as follows: −62 % for SO2, −17 % for NOx, +11 % for nonmethane volatile organic compounds (NMVOCs), +1 % for NH3, −27 % for CO, −38 % for PM10, −35 % for PM2.5, −27 % for BC, −35 % for OC, and +16 % for CO2. The IDA results suggest that emission control measures are the main drivers of this reduction, in which the pollution controls on power plants and industries are the most effective mitigation measures. The emission reduction rates markedly accelerated after the year 2013, confirming the effectiveness of China's Clean Air Action that was implemented since 2013. We estimated that during 2013–2017, China's anthropogenic emissions decreased by 59 % for SO2, 21 % for NOx, 23 % for CO, 36 % for PM10, 33 % for PM2.5, 28 % for BC, and 32 % for OC. NMVOC emissions increased and NH3 emissions remained stable during 2010–2017, representing the absence of effective mitigation measures for NMVOCs and NH3 in current policies. The relative contributions of different sectors to emissions have significantly changed after several years' implementation of clean air policies, indicating that it is paramount to introduce new policies to enable further emission reductions in the future.

From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population–weighted annual mean PM2.5 concentrations decreased from 61.8 (95%CI: 53.3–70.0) to 42.0 µg/m3 (95% CI: 35.7–48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9–7.1), 4.4- (95% CI: 3.8–4.9), 2.8- (95% CI: 2.5–3.0), and 2.2- (95% CI: 2.0–2.5) µg/m3 declines in the national PM2.5 concentration in 2017, respectively, and further reduced PM2.5-attributable excess deaths by 0.37 million (95% CI: 0.35–0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China’s recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in East China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show the haze during the COVID lockdown were driven by enhancements of secondary pollution. In particular, large decreases in NOx emissions from transportation increased ozone and nighttime NO3 radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.