Suppr超能文献

中国京津冀地区 COVID-19 封锁期间,不利气象条件导致 PM 污染持续偏高。

Persistent high PM pollution driven by unfavorable meteorological conditions during the COVID-19 lockdown period in the Beijing-Tianjin-Hebei region, China.

机构信息

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen, 361021, China.

出版信息

Environ Res. 2021 Jul;198:111186. doi: 10.1016/j.envres.2021.111186. Epub 2021 Apr 27.

Abstract

Lockdown measures to curtail the COVID-19 pandemic in China halted most non-essential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. Employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM concentrations change in this region. The model using the scenario (C3) with greater traffic reductions performed better compared to the observed PM. Compared with the no reductions base-case (scenario C1), PM reductions with scenario C3 were 2.70, 2.53, 2.90, 2.98, 3.30, 2.81, 2.82, 2.98, 2.68, and 2.83 μg/m in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai, respectively. During high-pollution days in scenario C3, the percentage reductions in PM concentrations in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai were 3.76, 3.54, 3.28, 3.22, 3.57, 3.56, 3.47, 6.10, 3.61, and 3.67%, respectively. However, significant increases caused by unfavorable meteorological conditions counteracted the emissions reduction effects resulting in high air pollution in BTH region during the lockdown period. This study shows that effective air pollution control strategies incorporating these results are urgently required in BTH to avoid severe pollution.

摘要

为遏制 2020 年 1 月 23 日在中国爆发的 COVID-19 疫情,中国采取了封锁措施,停止了大部分非必要活动。尽管人为排放显著减少,但北京-天津-河北(BTH)地区仍经历了高浓度的空气污染。采用两种减排情景,使用社区多尺度空气质量模型(CMAQ)来研究该地区的 PM 浓度变化。与观察到的 PM 相比,使用交通减排情景(C3)的模型表现更好。与没有减排的基准情景(C1)相比,情景 C3 下的 PM 减排量分别为北京、天津、石家庄、保定、沧州、承德、邯郸、衡水、唐山和邢台的 2.70、2.53、2.90、2.98、3.30、2.81、2.82、2.98、2.68 和 2.83μg/m。在情景 C3 的高污染日,北京、天津、石家庄、保定、沧州、承德、邯郸、衡水、唐山和邢台的 PM 浓度降幅分别为 3.76%、3.54%、3.28%、3.22%、3.57%、3.56%、3.47%、6.10%、3.61%和 3.67%。然而,不利的气象条件造成的显著增加抵消了减排效果,导致封锁期间 BTH 地区的空气污染仍然很高。本研究表明,BTH 地区急需采取有效的空气污染控制策略,以避免严重污染。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f49/9750169/f89ccbcc6d4e/gr2_lrg.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验