摘要
本文选取了2021年1月1日到2021年12月18日北京、天津、河北、山东、山西、辽宁两个直辖市、四个省份中的52个城市的实时PM2.5浓度数据,通过计算转移熵,分别构建中国东北部城市群之间的年度和月份PM2.5互相关网络,寻找城市之间是否存在雾霾相互影响,以及该影响随月份的演化规律。发现:1) 聊城、晋中、济南、淄博、锦州、阜新6个城市在PM2.5污染传播的过程中和周边城市的关联性较强,山东地区和辽宁地区属于PM2.5传播的重要省份;2) 2021年1~3月和11~12月PM2.5浓度和传播程度处于全年较高水平,6~9月处于全年较低水平,PM2.5浓度在全年中呈现“U”型变化特征;3) 辽阳、朔州、邯郸为波动较小结构中的重要节点,泰安、承德、衡水、滨州为波动较大结构中的重要节点。
In this paper, we selected some real-time PM2.5 concentration data. These data contain data of 52 cities in Beijing, Tianjin, Hebei, Shandong, Shanxi, and Liaoning from January 1, 2021 to December 18, 2021. By calculating the transfer entropy, this paper constructs annual and monthly PM2.5 cross-correlation networks among urban clusters in northeastern China, respectively. Thus, it is possible to obtain whether there is a haze mutual influence between cities and the evolution pat-tern of this influence with month. It is found that 1) there are six cities with strong correlation with neighboring cities in the process of PM2.5 pollution propagation. These six cities are Liaocheng, Jin-zhong, Jinan, Zibo, Jinzhou, and Fuxin. Shandong region and Liaoning region belong to the important provinces for PM2.5 propagation. 2) In 2021, PM2.5 concentration and transmission are at a high level from January to March and from November to December, and at a low level from June to Sep-tember, showing a “U”-shaped change in PM2.5 concentration throughout the year. 3) Liaoyang, Shuozhou and Handan are important nodes in the less volatile structure, while Tai’an, Chengde, Hengshui and Binzhou are important nodes in the more volatile structure.
出处
《应用数学进展》
2022年第6期3624-3634,共11页
Advances in Applied Mathematics
