{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T11:21:42Z","timestamp":1791285702908,"version":"4.1.0"},"reference-count":57,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T00:00:00Z","timestamp":1661731200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Second Tibetan Plateau Scientific Expedition","award":["2019QZKK0304"],"award-info":[{"award-number":["2019QZKK0304"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Economic development is responsible for excessive sulfur dioxide (SO2) emissions, environmental pressure increases, and human and environmental risks. This study used spatial autocorrelation, the Environmental Kuznets Curve (EKC), and the Logarithmic Mean Divisia Index model to study the spatiotemporal variation characteristics and influencing factors of SO2 emissions in the Yangtze River Economic Belt (YREB) from 1997 to 2017. Our results show that the total SO2 emissions in the YREB rose from 513.14 \u00d7 104 t to 974.00 \u00d7 104 t before dropping to 321.97 \u00d7 104 t. The SO2 emissions from 11 provinces first increased and then decreased, each with different turning points. For example, the emission trends changed in Yunnan in 2011 and in Anhui in 2015, while the other nine provinces saw their emission trends change during 2005\u20132006. Furthermore, the SO2 emissions in the YREB showed a significant agglomeration phenomenon, with a Moran index of approximately 0.233\u20130.987. Moreover, the EKC of SO2 emissions and per capita GDP in the YREB was N-shaped. The EKCs of eight of the 11 provinces were N-shaped (Shanghai, Zhejiang, Anhui, Jiangxi, Sichuan, Guizhou, Hunan, and Chongqing) and those of the other three were inverted U-shaped (Jiangsu, Yunnan, and Hubei). Thus, economic development can both promote and inhibit the emission of SO2. Finally, during the study period, the technical effect (approximately \u22121387.97 \u00d7 104\u2013130.24 \u00d7 104 t) contributed the most, followed by the economic (approximately 27.81 \u00d7 104\u20131255.59 \u00d7 104 t), structural (approximately \u221256.45 \u00d7 104\u2013343.90 \u00d7 104 t), and population effects (approximately 4.25 \u00d7 104\u201339.70 \u00d7 104 t). Technology was the dominant factor in SO2 emissions reduction, while economic growth played a major role in promoting SO2 emissions. Therefore, to promote SO2 emission reduction, technological innovations and advances should be the primary point of focus.<\/jats:p>","DOI":"10.3390\/ijerph191710770","type":"journal-article","created":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T21:01:31Z","timestamp":1661806891000},"page":"10770","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China"],"prefix":"10.3390","volume":"19","author":[{"given":"Hui","family":"Guo","sequence":"first","affiliation":[{"name":"Shihezi University, Shihezi 832000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Southwest China Wildlife Resources Conservation, Ministry of Education, China West Normal University, Nanchong 637009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yawen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Southwest China Wildlife Resources Conservation, Ministry of Education, China West Normal University, Nanchong 637009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen\u2019an","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Science, Shihezi University, Shihezi 832000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"105709","DOI":"10.1016\/j.atmosres.2021.105709","article-title":"Contributions of biomass burning to global and regional SO2 emissions","volume":"260","author":"Ren","year":"2021","journal-title":"Atmos. 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