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精准治污助力缓解城市重污染

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

机构信息

Research Center for Air Pollution and Health; Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, P.R. China.

Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.

出版信息

Sci Rep. 2018 May 25;8(1):8151. doi: 10.1038/s41598-018-26344-1.

Abstract

Severe and persistent haze pollution involving fine particulate matter (PM) 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 PM 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 PM peak concentrations by more than 60% from above 300 μg m to below 100 μg m, 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.

摘要

严重且持续的雾霾污染,细颗粒物(PM)浓度达到前所未有的高水平,在中国许多城市构成了严重威胁人类健康。虽然强制性暂停大多数城市和周边排放源是一种有效但代价高昂的短期措施,可以减轻空气污染,但开发长期危机应对措施仍然是一个挑战,特别是要定期遏制严重的城市雾霾事件。在这里,我们介绍并评估了一种新颖的精确空气污染控制方法(PAPCA),以减轻严重的城市雾霾事件。该方法涉及将高 PM 浓度预测与混合轨迹受体模型和全面的三维大气模型相结合,以确定导致此类事件的排放源的起源,并优化排放控制。PAPCA 在我国主要城市的五次严重雾霾事件中的应用结果表明,该策略通过将 PM 峰值浓度从 300μg/m 以上降低到 100μg/m 以下,从而有潜力显著减轻严重的城市雾霾,而与完全减排相比,所需的减排量减少了 30%至 70%。PAPCA 策略具有以经济效率有效应对严重城市雾霾污染事件的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ce4/5970218/fd493f0c19a6/41598_2018_26344_Fig1_HTML.jpg

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