China's rapid economic growth and urbanization have made it the world's largest energy consumer, leading to severe air pollution and increased CO₂ emissions. To address air quality, the Chinese government implemented the Air Pollution Prevention and Control Action Plan (2013) and the Three-Year Action Plan for Winning the Blue Sky Defense Battle (2018). These plans aimed to significantly reduce PM2.5 concentrations. While the primary focus was air quality, these clean air measures also impacted the energy system, potentially leading to CO₂ emission reductions. Previous studies have shown regional CO₂ emission reduction co-benefits from clean air actions, but a comprehensive quantification of the national impact of China's two-phase clean air actions on CO₂ emissions remains unclear. This study addresses this gap by quantifying the CO₂ emission reduction co-benefits of China's clean air actions from 2013 to 2020 using a modeling framework.

Existing research primarily focuses on the air pollution-induced climate forcing effects of clean air policies, with limited understanding of their CO₂ reduction impact. Regional studies have demonstrated CO₂ reduction co-benefits from specific clean air measures, but a comprehensive national-level assessment of China's multi-faceted clean air actions was lacking. This study builds upon these previous findings by providing a comprehensive analysis of the impact of China's clean air actions on CO2 emissions at a national scale, considering the interplay between various policy measures and their combined effect on energy use patterns.

The study employed a bottom-up approach using the Multi-resolution Emission Inventory of China (MEIC) model to estimate China's anthropogenic emissions of major air pollutants and CO₂ from 2013 to 2020. Six major clean air measures were identified and analyzed: upgrades on industrial boilers, phasing out small and polluting factories, phasing out outdated industrial capacity, promoting clean fuels in the residential sector, retiring yellow-label and old vehicles, and strengthening industrial emission standards (end-of-pipe measures). An ex-post assessment was conducted to quantify the impact of energy-related measures on energy end-use flows and CO₂ emissions using real implementation rates collected from government data. The CO₂ emission reduction co-benefits of each measure were estimated using the MEIC model. The study also considered the CO₂ emission increase from end-of-pipe devices. Regional patterns of CO₂ emission reduction co-benefits were analyzed for four key regions (Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, and Fenwei Plain) and at the provincial level. Finally, an economic analysis assessed the cost-effectiveness of the co-beneficial measures compared to traditional CO₂ mitigation measures.

Emissions of SO₂, NOx, and primary PM2.5 decreased significantly (69%, 28%, and 44%, respectively) between 2013 and 2020, leading to improved air quality. Despite overall upward trends in energy consumption and CO₂ emissions, China's clean air actions resulted in a cumulative CO₂ emission reduction of 2.66 Gt from 2013 to 2020. The five co-beneficial measures (excluding end-of-pipe measures) avoided 0.57 Gt of CO₂ emissions in 2020 (5.5% of total emissions). Phasing out outdated industrial capacities and upgrading industrial boilers were the most effective CO₂ reduction measures. The net cumulative CO₂ emission reduction (2.43 Gt) surpassed the accumulated increase from end-of-pipe devices (0.23 Gt). Regional analysis revealed that Beijing-Tianjin-Hebei, Yangtze River Delta, and Fenwei Plain regions were the largest contributors to the CO₂ emission reduction co-benefits. Provincial-level analysis showed a correlation between stricter pollution control policies, improved air quality, and higher CO₂ emission reductions. The average unit cost of CO₂ emission reduction from the co-beneficial measures was estimated to be 95.6 $/ton, higher than traditional mitigation measures, but offset by health and economic benefits of improved air quality. The study also estimated that China's accumulated CO₂ emissions could have been 3.78 Gt higher without the increased renewable energy generation.

The findings demonstrate that China's stringent air quality targets acted as a powerful driver for energy system transformation and CO₂ emission mitigation, even though climate change wasn't the initial policy objective. The rapid phase-out of carbon-intensive infrastructure and promotion of cleaner technologies led to improved energy efficiency. This study's results have significant implications for the global carbon budget, considering China's substantial contribution to global CO₂ emissions. While clean air measures achieved remarkable CO₂ emission reductions, continued efforts are needed to optimize the energy system and economic structure to ensure a green recovery from the COVID-19 pandemic and promote long-term green growth. The higher abatement cost of co-beneficial measures compared to traditional methods is balanced by the substantial health and economic benefits from improved air quality. The success of China's approach offers valuable lessons for other developing countries facing similar challenges of air pollution and climate change.

China's experience demonstrates that stringent clean air policies can yield substantial CO₂ emission reduction co-benefits. The phase-out of outdated, inefficient, and polluting facilities, coupled with the adoption of cleaner energy sources, played a crucial role. Future policy designs should prioritize measures that simultaneously address air pollution and climate change, balancing the cost-effectiveness with the associated health and economic advantages of cleaner air. Continued investment in renewable energy is essential for achieving China's carbon neutrality goal. This approach provides a potentially effective strategy for other developing countries striving to balance economic development with environmental sustainability.

The study relied on government-collected data on the implementation rate of clean air measures, which might contain some uncertainties. The model used for CO₂ emission estimation includes inherent uncertainties associated with emission factors and activity data. The economic analysis focused on the direct costs of CO₂ emission reduction from the co-beneficial measures, without fully accounting for the broader societal benefits associated with improved public health and reduced healthcare costs. Further research could explore a more in-depth cost-benefit analysis incorporating broader economic and health impacts.