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Mitigation of severe urban haze pollution by a precision air pollution control approach

机译:通过精确的空气污染控制方法缓解严重的城市霾

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Severe and persistent haze pollution involving fine particulate matter (PM2.5) concentrations reaching unprecedentedly high levels across many cities in China poses a serious threat to human health. Although mandatory temporary cessation of most urban and surrounding emission sources is an effective, but costly, short-term measure to abate air pollution, development of long-term crisis response measures remains a challenge, especially for curbing severe urban haze events on a regular basis. Here we introduce and evaluate a novel precision air pollution control approach (PAPCA) to mitigate severe urban haze events. The approach involves combining predictions of high PM2.5 concentrations, with a hybrid trajectory-receptor model and a comprehensive 3-D atmospheric model, to pinpoint the origins of emissions leading to such events and to optimize emission controls. Results of the PAPCA application to five severe haze episodes in major urban areas in China suggest that this strategy has the potential to significantly mitigate severe urban haze by decreasing PM2.5 peak concentrations by more than 60% from above 300?μg m?3 to below 100?μg m?3, while requiring ~30% to 70% less emission controls as compared to complete emission reductions. The PAPCA strategy has the potential to tackle effectively severe urban haze pollution events with economic efficiency.
机译:在中国许多城市中,涉及细颗粒物(PM2.5)浓度的前所未有的严重雾霾污染严重威胁着人类健康。尽管强制性暂时停止大多数城市及周边排放源是减轻空气污染的有效但成本高昂的短期措施,但制定长期危机应对措施仍然是一项挑战,特别是对于定期遏制严重的城市烟雾事件。在这里,我们介绍并评估一种新颖的精密空气污染控制方法(PAPCA),以减轻严重的城市霾事件。该方法涉及将高PM2.5浓度的预测与混合轨迹接收器模型和全面的3-D大气模型相结合,以查明导致此类事件的排放源并优化排放控制。 PAPCA在中国主要城市地区发生的五次严重雾霾事件中的应用结果表明,该策略有可能通过将PM2.5峰值浓度从300?μgm?3以上降低至60%来显着缓解严重的城市雾霾低于100微克m?3,同时与完全减少排放量相比,排放控制量减少了约30%至70%。 PAPCA战略具有以经济效率有效解决严重的城市霾污染事件的潜力。

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