China is confronting the challenge of opposite health benefits (OHBs) during ambient ozone (O3) mitigation because the same reduction scheme might yield opposite impacts on O3 levels and associated public health across different regions. Here, we used a combination of chemical transport modeling, health benefit assessments, and machine learning to capture such OHBs and optimize O3 mitigation pathways based on 121 control scenarios. We revealed that, for the China mainland, Beijing–Tianjin–Hebei and its surroundings (“2 + 26” cities), Yangtze River Delta, and Pearl River Delta, there could be at most 2897, 920, 1247, and 896 additional O3-related deaths in urban areas, respectively, accompanying 21,512, 3442, 5614, and 642 avoided O3-related deaths in rural areas, respectively, at the same control stage. Additionally, potential disbenefits during O3 mitigation were “pro-wealthy”, that is, residents in developed regions are more likely to afford additional health risks. In order to avoid OHBs during O3 abatement, we proposed a two-phase control strategy, whereby the reduction ratio of NO X (nitrogen oxide) to VOCs (volatile organic compounds) was adjusted according to health benefit distribution patterns. Our study provided novel insights into China’s O3 attainment and references for other countries facing the dual challenges of environmental pollution and associated inequality issues.

The emissions from various pollution sources were not proportional to their contributions to ambient PM2.5 concentrations and associated health burdens. That means even with the same total abatement targets, different abatement allocation strategies across emission sources can have distinct health benefits. Insufficient knowledge of various sources’ contributions to health burdens in China, the country suffering substantial PM2.5-related deaths, hindered the government from seeking optimized abatement allocation strategies. In this context, we separated the contributions of 155 emission sources (31 provinces × 5 sectors) to PM2.5-related mortality across China in 2017 by coupling the Comprehensive Air Quality Model with Extensions (CAMx), Weather Research and Forecasting model (WRF), and health impact assessment model. We further identified the priority-control emission sources and quantified interprovincial ecological compensation volumes to alleviate inequality induced by emission allocation strategies. Results showed that PM2.5 pollution caused 899,443 excess deaths and around 127 billion USD costs in 2017. Approximately half of the deaths and costs were attributable to emissions from sources outside the boundary of the regions where the deaths occurred. Twenty-five out of 155 emission sources that contributed to the top 60% mortality burdens and had high marginal abatement efficiencies in China shall be the priority-control emission sources. A 1 μg/m3 decrease of PM2.5 concentration in regions where these key emission sources occur shall be compensated by 76–153 million USD in their receptor regions. Our study sheds light on the sources’ contributions to mortality burdens and costs and provides scientific evidence for optimizing the emission allocation and compensation strategies in China. It also has wide implications for other countries suffering similar problems.

China will attempt to achieve its simultaneous goals in 2060, whereby carbon neutrality will be accomplished and the PM2.5 (fine particulate matter) level is expected to remain below 10 μg/m3. Identifying interaction patterns between air cleaning and climate action represents an important step to obtain cobenefits. Here, we used a random sampling strategy through the combination of chemical transport modeling and machine learning approach to capture the interaction effects from two perspectives in which the driving forces of both climate action and air cleaning measures were compared. We revealed that climate action where carbon emissions were decreased to 1.9 Bt (billion tons) could lead to a PM2.5 level of 12.4 μg/m3 (95% CI (confidence interval): 10.2–14.6 μg/m3) in 2060, while air cleaning could force carbon emissions to reach 1.93 Bt (95% CI: 0.79–3.19 Bt) to achieve net carbon neutrality based on the potential carbon sinks in 2060. Additional controls targeting primary PM2.5, ammonia, and volatile organic compounds were required as supplements to overcome the partial lack of climate action. Our study provides novel insights into the cobenefits of air-quality improvement and climate change mitigation, indicating that the effect of air cleaning on the simultaneous goals might have been underestimated before.