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Environ Sci Technol


Title:Interaction Patterns between Climate Action and Air Cleaning in China: A Two-Way Evaluation Based on an Ensemble Learning Approach
Author(s):Liu Z; Dong M; Xue W; Ni X; Qi Z; Shao J; Guo Y; Ma M; Zhang Q; Wang J;
Address:"College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China. Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing 100012, China"
Journal Title:Environ Sci Technol
Year:2022
Volume:20220617
Issue:13
Page Number:9291 - 9301
DOI: 10.1021/acs.est.2c01966
ISSN/ISBN:1520-5851 (Electronic) 0013-936X (Linking)
Abstract:"China will attempt to achieve its simultaneous goals in 2060, whereby carbon neutrality will be accomplished and the PM(2.5) (fine particulate matter) level is expected to remain below 10 mug/m(3). 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 PM(2.5) level of 12.4 mug/m(3) (95% CI (confidence interval): 10.2-14.6 mug/m(3)) 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 PM(2.5), 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"
Keywords:*Air Pollutants/analysis *Air Pollution/analysis/prevention & control Carbon China Environmental Monitoring Machine Learning Particulate Matter/analysis Co2 Pm2.5 air pollution climate change mitigation integrated assessment;
Notes:"MedlineLiu, Zeyuan Dong, Mengting Xue, Wenbo Ni, Xiufeng Qi, Zhulin Shao, Jiacheng Guo, Yingzhuang Ma, Mengying Zhang, Qingyu Wang, Jinnan eng Research Support, Non-U.S. Gov't 2022/06/18 Environ Sci Technol. 2022 Jul 5; 56(13):9291-9301. doi: 10.1021/acs.est.2c01966. Epub 2022 Jun 17"

 
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