Interaction of interregional O 3 pollution using complex network analysis

PeerJ

article

Qiang Zhang¹  Yunan Zhu¹  Dianxiang Xu¹  Jiaqiong Yuan¹  Zhihe Wang¹  Yong Li¹  Xueyan Liu² 

[1] Computer Science and Engineering, The Northwest Normal University;Mathematics and Statistics, The Northwest Normal University

关键词: Air quality;    Complex network;    Time series;    Node importance;    Transfer entropy;    Precise governance;   

DOI  :  10.7717/peerj.12095

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

In order to improve the accuracy of air pollution management and promote the efficiency of coordinated inter-regional prevention and control, this study analyzes the interaction of O3 in Qilihe District, Lanzhou City, China. Data used for analysis was obtained from 63 air quality monitoring stations between November 2017 and October 2018. This paper uses complex network theory to describe the network structure characteristics of O3 pollution spatial correlation. On this basis, the node importance method is used to mine the sub-network with the highest spatial correlation in the O3 network, and use transfer entropy theory to analyse the interaction of pollutants between regions. The results show that the O3 area of Qilihe District, Lanzhou City can be divided into three parts: the urban street community type areas in urban areas, the township and village type areas in mountain areas and the scattered areas represented by isolated nodes. An analysis of the mutual influence of O3 between each area revealed that the impact of O3 on each monitoring station in adjacent areas will vary considerably. Therefore these areas cannot be governed as a whole, and the traditional extensive management measures based on administrative divisions cannot be used to replace all other regional governance measures. There is the need to develop a joint prevention and control mechanism tailored to local conditions in order to improve the accuracy and efficiency of O3 governance.

【 授权许可】

CC BY