论文标题
部分可观测时空混沌系统的无模型预测
Network approach reveals the spatiotemporal influence of traffic to air pollution under the COVID-19
论文作者
论文摘要
空气污染会导致广泛的环境和健康问题,并严重阻碍了城市居民的生活质量。交通对人类的生活至关重要,其排放是污染的主要来源,加剧了城市空气污染。但是,尚未揭示交通排放与城市空气污染之间的复杂相互作用。特别是,根据当地流行病的情况,COVID-19的传播使各个城市实施了不同的交通限制政策,这提供了探索城市交通与空气污染之间关系的可能性。在这里,我们通过重建多层复杂网络基础对交通指数和空气质量指数的重建,探讨了流量对空气污染的影响。我们发现,北京-Tianjin-Hebei(BTH),Chengdu-ChongQing经济环(CCS)和中国中部地区(CC)地区的空气质量受到爆发后周围交通状况的显着影响。在与流行病阶段的不同斗争下,其他城市对空气污染的影响达到了第2阶段的最大值(在含有病毒中也称为初步进展)。对于BTH和CC区域,交通对空气质量的影响在前两个阶段变得更大,然后减少,而对于CC,在第3阶段中发生了重大影响。但是,对于其他地区,变化并不明显。我们提出的基于网络的框架为运输和环境领域提供了新的视角,也许有助于指导政府制定缓解空气污染和交通限制政策。
Air pollution causes widespread environmental and health problems and severely hinders the life quality of urban residents. Traffic is a critical for human life and its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between the traffic emissions and the air pollution in the cities has not yet been revealed. In particular, the spread of the COVID-19 has caused various cities 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 to air pollution by reconstructing a multi-layer complex network base on traffic index and air quality index. We uncover that air quality in Beijing-Tianjin-Hebei (BTH), Chengdu-Chongqing Economic Circle (CCS) and Central China (CC) regions are significantly influenced by the surrounding traffic conditions after the outbreak. Under different fights against the epidemic stages, the influence of traffic in other cities on the air pollution reached the maximum in stage 2 (also called Initial Progress in Containing the Virus). For BTH and CC regions, the impact of traffic on air quality becomes larger in the first two stages and then decreases, while for CC, the significant impact occurs in Phase 3 among regions. For other regions, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment, and maybe helpful to guide the government to formulate air pollution mitigation and traffic restriction policies.