Temporally-resolved sectoral and regional contributions to air pollution in Beijing: Informing short-term emission controls
Temporally-resolved sectoral and regional contributions to air pollution in Beijing: Informing short-term emission controls
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DOI：
10.5194/acp-2020-814
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
T. Ansari;O. Wild;E. Ryan;Ying Chen;Jie Li;Zifa Wang
中科院分区：
文献类型：
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作者：
T. Ansari;O. Wild;E. Ryan;Ying Chen;Jie Li;Zifa Wang
我们调查了本地和区域排放源对北京空气污染的贡献，为缓解主要污染事件的短期排放控制策略的设计提供信息。我们使用一个经过良好评估的WRF-Chem模式版本，在3 km水平分辨率下，确定2014年10月在一系列气象条件下北京地区本地和区域污染源的日累积量。考虑到住宅、交通、电力和工业部门的可行减排，我们发现，对当地排放的1 d控制对当天的PM2.5（直径小于2.5 μm的颗粒物）浓度有即时影响，但在停滞条件下，可能会在5 d后产生持续影响。周边省份的一天控制措施对北京的影响最大，但在当地排放占主导地位的西北风下，影响可能微不足道。为了探索不同排放部门和地区的贡献，我们依次进行模拟，去除每个源。我们发现，在主要污染事件期间，来自邻近省份的住宅和工业部门主导了北京的PM2.5水平，但在某些事件期间，本地住宅排放和来自较远省份的工业或住宅排放也可能产生显着影响。然后，我们进行了一组结构化的扰动排放模拟，使我们能够建立统计模拟器，代表排放源和空气污染之间的关系，在北京的时间。我们使用这些计算速度快的仿真器来确定PM2.5浓度对不同排放源的敏感性以及它们之间的相互作用，包括二次PM，并创建北京每日平均PM2.5浓度的污染物响应面。我们使用这些表面来确定短期排放控制，以满足不同强度污染事件的日平均PM2.5小于75 μg m−3的国家空气质量目标。我们发现，对于PM2.5日均值高于225 μg m−3的重污染日，即使北京及周边省份所有部门减排90%，也可能不足以满足国家空气质量标准。这些结果突出了PM污染的区域性，以及在重大污染事件中应对PM污染的挑战。
We investigate the contributions of local and regional emission sources to air pollution in Beijing to inform the design of short-term emission control strategies for mitigating major pollution episodes. We use a well-evaluated version of the WRF-Chem model at 3 km horizontal resolution to determine the daily accumulation of pollution over Beijing from local and regional sources in October 2014 under a range of meteorological conditions. Considering feasible emission reductions across residential, transport, power, and industrial sectors, we find that 1 d controls on local emissions have an immediate effect on PM2.5 (particulate matter with diameter less than 2.5 μm) concentrations on the same day but can have lingering effects as much as 5 d later under stagnant conditions. One-day controls in surrounding provinces have the greatest effect in Beijing on the day following the controls but may have negligible effects under northwesterly winds when local emissions dominate. To explore the contribution of different emission sectors and regions, we perform simulations with each source removed in turn. We find that residential and industrial sectors from neighbouring provinces dominate PM2.5 levels in Beijing during major pollution episodes but that local residential emissions and industrial or residential emissions from more distant provinces can also contribute significantly during some episodes. We then perform a structured set of perturbed emission simulations to allow us to build statistical emulators that represent the relationships between emission sources and air pollution in Beijing over the period. We use these computationally fast emulators to determine the sensitivity of PM2.5 concentrations to different emission sources and the interactions between them, including for secondary PM, and to create pollutant response surfaces for daily average PM2.5 concentrations in Beijing. We use these surfaces to identify the short-term emission controls needed to meet the national air quality target of daily average PM2.5 less than 75 μg m−3 for pollution episodes of different intensities. We find that for heavily polluted days with daily mean PM2.5 higher than 225 μg m−3, even emission reductions of 90 % across all sectors over Beijing and surrounding provinces may be insufficient to meet the national air quality standards. These results highlight the regional nature of PM pollution and the challenges of tackling it during major pollution episodes.