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    Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition by Zhang, Da, Wang, Qingyi, Song, Shaojie, Chen, Simiao, Li, Mingwei, Shen, Lu, Zheng, Siqi, Cai, Bofeng, Wang, Shenhao, Zheng, Haotian

    Published 2024
    “…In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. …”
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