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网络方法揭示了 COVID-19 下交通对空气污染的时空影响。

Network approach reveals the spatiotemporal influence of traffic on air pollution under COVID-19.

机构信息

School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China.

School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.

出版信息

Chaos. 2022 Apr;32(4):041106. doi: 10.1063/5.0087844.

Abstract

Air pollution causes widespread environmental and health problems and severely hinders the quality of life of urban residents. Traffic is critical for human life, but its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between traffic emissions and air pollution in cities and regions has not yet been revealed. In particular, the spread of COVID-19 has led various cities and regions to implement different traffic restriction policies according to the local epidemic situation, which provides the possibility to explore the relationship between urban traffic and air pollution. Here, we explore the influence of traffic on air pollution by reconstructing a multi-layer complex network base on the traffic index and air quality index. We uncover that air quality in the Beijing-Tianjin-Hebei (BTH), Chengdu-Chongqing Economic Circle (CCS), and Central China (CC) regions is significantly influenced by the surrounding traffic conditions after the outbreak. Under different stages of the fight against the epidemic, the influence of traffic in some regions on air pollution reaches the maximum in stage 2 (also called Initial Progress in Containing the Virus). For the BTH and CC regions, the impact of traffic on air quality becomes bigger in the first two stages and then decreases, while for CC, a significant impact occurs in phase 3 among the other regions. For other regions in the country, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment and may be helpful in guiding the government to formulate air pollution mitigation and traffic restriction policies.

摘要

空气污染造成了广泛的环境和健康问题,并严重影响了城市居民的生活质量。交通对人类生活至关重要,但它的排放是污染的主要来源,加剧了城市空气污染。然而,城市和地区交通排放与空气污染之间的复杂相互作用尚未被揭示。特别是,COVID-19 的传播导致各个城市和地区根据当地疫情实施了不同的交通限制政策,这为探索城市交通与空气污染之间的关系提供了可能性。在这里,我们通过基于交通指数和空气质量指数重建多层复杂网络,来探索交通对空气污染的影响。我们发现,在疫情爆发后,京津冀(BTH)、成渝经济圈(CCS)和华中地区(CC)的空气质量受到周边交通状况的显著影响。在不同的抗疫阶段,一些地区的交通对空气污染的影响在第二阶段(也称为病毒初步控制阶段)达到最大。对于 BTH 和 CC 地区,交通对空气质量的影响在前两个阶段变大,然后减小,而对于 CC,在其他地区的第三阶段会出现显著影响。然而,对于中国其他地区,这种变化并不明显。我们提出的基于网络的框架为交通和环境领域提供了一个新视角,可能有助于指导政府制定空气污染减排和交通限制政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a7e/9058978/e18367f13895/CHAOEH-000032-041106_1-g001.jpg

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