{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T11:36:29Z","timestamp":1763552189602,"version":"build-2065373602"},"reference-count":79,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,4,17]],"date-time":"2022-04-17T00:00:00Z","timestamp":1650153600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science and Technology Project of Nantong","award":["MS12020075","MS12021082"],"award-info":[{"award-number":["MS12020075","MS12021082"]}]},{"DOI":"10.13039\/501100012456","name":"National Social Science Foundation of China","doi-asserted-by":"publisher","award":["19ZDA189"],"award-info":[{"award-number":["19ZDA189"]}],"id":[{"id":"10.13039\/501100012456","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Industry-University Cooperation Collaborative Education Projects","award":["202102245013"],"award-info":[{"award-number":["202102245013"]}]},{"DOI":"10.13039\/501100013254","name":"National College Students Innovation and Entrepreneurship Training Program","doi-asserted-by":"publisher","award":["202110304042Z","202110304041Z"],"award-info":[{"award-number":["202110304042Z","202110304041Z"]}],"id":[{"id":"10.13039\/501100013254","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The cross-impact of environmental pollution among cities has been reported in more research works recently. To implement the coordinated control of environmental pollution, it is necessary to explore the structural characteristics and influencing factors of the PM2.5 spatial correlation network from the perspective of the metropolitan area. This paper utilized the gravity model to construct the PM2.5 spatial correlation network of ten metropolitan areas in China from 2019 to 2020. After analyzing the overall characteristics and node characteristics of each spatial correlation network based on the social network analysis (SNA) method, the quadratic assignment procedure (QAP) regression analysis method was used to explore the influence mechanism of each driving factor. Patent granted differences, as a new indicator, were also considered during the above. The results showed that: (1) In the overall network characteristics, the network density of Chengdu and the other three metropolitan areas displayed a downward trend in two years, and the network density of Wuhan and Chengdu was the lowest. The network density and network grade of Hangzhou and the other four metropolitan areas were high and stable, and the network structure of each metropolitan area was unstable. (2) From the perspective of the node characteristics, the PM2.5 spatial correlation network all performed trends of centralization and marginalization. Beijing-Tianjin-Hebei and South Central Liaoning were \u201cmulti-core\u201d metropolitan areas, and the other eight were \u201csingle-core\u201d metropolitan areas. (3) The analysis results of QAP regression illustrated that the top three influencing factors of the six metropolitan areas were geographical locational relationship, the secondary industrial proportion differences, respectively, and patent granted differences, and the other metropolitan areas had no dominant influencing factors.<\/jats:p>","DOI":"10.3390\/ijgi11040267","type":"journal-article","created":{"date-parts":[[2022,4,18]],"date-time":"2022-04-18T04:21:28Z","timestamp":1650255688000},"page":"267","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Structural Differences of PM2.5 Spatial Correlation Networks in Ten Metropolitan Areas of China"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6224-1991","authenticated-orcid":false,"given":"Shuaiqian","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Geographical Sciences, Nantong University, Nantong 226007, China"}]},{"given":"Fei","family":"Tao","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nantong University, Nantong 226007, China"},{"name":"Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China"}]},{"given":"Qi","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nantong University, Nantong 226007, China"}]},{"given":"Qile","family":"Han","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nantong University, Nantong 226007, China"}]},{"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nantong University, Nantong 226007, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3041-6264","authenticated-orcid":false,"given":"Tong","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nantong University, Nantong 226007, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kumar, P., Sajjad, H., Chaudhary, B.S., Rawat, J.S., and Rani, M. 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