缩小尺度
气候变化
环境科学
空气质量指数
温室气体
环境资源管理
环境经济学
碳中和
中国
环境规划
空气污染
情景分析
环境质量
污染物
能源系统
气候模式
减缓气候变化
基线(sea)
地球系统科学
气候政策
代表性浓度途径
环境工程
能源政策
环境保护
排放交易
空气污染物
化石燃料
降级
能源消耗
优势(遗传学)
全球变暖
分布(数学)
煤
自然资源经济学
空气污染物标准
政策分析
高效能源利用
能源供应
质量(理念)
能量(信号处理)
作者
Xiaosong Hou,Xiaoqi Wang,Shuiyuan Cheng,Chuanda Wang,Ning Wang
标识
DOI:10.1021/acs.est.5c12973
摘要
To address the dual challenges of climate change and air pollution, an urban-scale decision-making framework is required in China to quantify energy-environment-health co-benefits, thereby addressing the limitations of existing macro-level research. This study proposes a novel analytical framework integrating scenario prediction, dynamic downscaling, pathway optimization, and benefit evaluation. The framework combines the provincial-level Global Change Analysis Model (GCAM-China) with a municipal-level dynamic downscaling model, a high-resolution emission inventory (Gridemis), the Scenario Model Intercomparison Project (ScenarioMIP), and an air quality and health assessment model. This approach effectively translates national climate goals into heterogeneous, sector-specific, municipal-scale emission pathways. It quantifies energy structure transitions, pollutant mitigation, and health co-benefits under various policy mixes while also considering future climate-related risks. Applied to the Beijing-Tianjin-Hebei region, the results show that synergistic efforts for carbon neutrality and stringent air quality policies will drive the regional energy system from coal dominance to a diversified, cleaner structure. By 2060, this optimized pathway could reduce major air pollutant emissions by 30-88%, promote a more equitable distribution of environmental and health benefits, and significantly lower premature mortality risks. This study provides a practical tool for energy and environmental policy, offering broad applicability for other regions.
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