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Seasonal and Diurnal Characteristics and Drivers of Urban Heat Island Based on Optimal Parameters-Based Geo-Detector Model in Xinjiang, China
In the context of sustainable urban development, elucidating urban heat island (UHI) dynamics in arid regions is crucial. By thoroughly examining the characteristics of UHI variations and potential driving factors, cities can implement effective strategies to reduce their impacts on the environment...
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Published in: | Atmosphere 2024-11, Vol.15 (11), p.1377 |
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description | In the context of sustainable urban development, elucidating urban heat island (UHI) dynamics in arid regions is crucial. By thoroughly examining the characteristics of UHI variations and potential driving factors, cities can implement effective strategies to reduce their impacts on the environment and public health. However, the driving factors of a UHI in arid regions remain unclear. This study analyzed seasonal and diurnal variations in a surface UHI (SUHI) and the potential driving factors using Pearson’s correlation analysis and an Optimal Parameters-Based Geographic Detector (OPGD) model in 22 cities in Xinjiang, northwest China. The findings reveal that the average annual surface urban heat island intensity (SUHII) values in Xinjiang’s cities were 1.37 ± 0.86 °C, with the SUHII being most pronounced in summer (2.44 °C), followed by winter (2.15 °C), spring (0.47 °C), and autumn (0.40 °C). Moreover, the annual mean SUHII was stronger at nighttime (1.90 °C) compared to during the daytime (0.84 °C), with variations observed across seasons. The seasonal disparity of SUHII in Xinjiang was more significant during the daytime (3.91 °C) compared to nighttime (0.39 °C), with daytime and nighttime SUHIIs decreasing from summer to winter. The study also highlights that the city size, elevation, vegetation cover, urban form, and socio-economic factors (GDP and population density) emerged as key drivers, with the GDP exerting the strongest influence on SUHIIs in cities across Xinjiang. To mitigate the UHI effects, measures like urban environment enhancement by improving surface conditions, blue–green space development, landscape optimization, and economic strategy adjustments are recommended. |
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By thoroughly examining the characteristics of UHI variations and potential driving factors, cities can implement effective strategies to reduce their impacts on the environment and public health. However, the driving factors of a UHI in arid regions remain unclear. This study analyzed seasonal and diurnal variations in a surface UHI (SUHI) and the potential driving factors using Pearson’s correlation analysis and an Optimal Parameters-Based Geographic Detector (OPGD) model in 22 cities in Xinjiang, northwest China. The findings reveal that the average annual surface urban heat island intensity (SUHII) values in Xinjiang’s cities were 1.37 ± 0.86 °C, with the SUHII being most pronounced in summer (2.44 °C), followed by winter (2.15 °C), spring (0.47 °C), and autumn (0.40 °C). Moreover, the annual mean SUHII was stronger at nighttime (1.90 °C) compared to during the daytime (0.84 °C), with variations observed across seasons. The seasonal disparity of SUHII in Xinjiang was more significant during the daytime (3.91 °C) compared to nighttime (0.39 °C), with daytime and nighttime SUHIIs decreasing from summer to winter. The study also highlights that the city size, elevation, vegetation cover, urban form, and socio-economic factors (GDP and population density) emerged as key drivers, with the GDP exerting the strongest influence on SUHIIs in cities across Xinjiang. To mitigate the UHI effects, measures like urban environment enhancement by improving surface conditions, blue–green space development, landscape optimization, and economic strategy adjustments are recommended.</description><identifier>ISSN: 2073-4433</identifier><identifier>EISSN: 2073-4433</identifier><identifier>DOI: 10.3390/atmos15111377</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Arid regions ; Arid zones ; Cities ; Climate ; Correlation analysis ; Daytime ; Diurnal variations ; driving factors ; Economic factors ; Economic growth ; Economics ; Energy consumption ; Environmental aspects ; Environmental impact ; GDP ; Green development ; Green infrastructure ; Gross Domestic Product ; Heat ; Impact factors ; Land use ; Night ; Night-time ; Nighttime ; optimal parameters-based geographic detector ; Parameters ; Plant cover ; Population ; Population density ; Public health ; Remote sensing ; Research methodology ; seasonal and diurnal characteristics ; Sensors ; Socioeconomic aspects ; Socioeconomic factors ; Socioeconomics ; Summer ; Sustainable development ; Urban areas ; Urban development ; Urban environments ; urban heat island ; Urban heat islands ; Urbanization ; Vegetation ; Vegetation cover ; Winter</subject><ispartof>Atmosphere, 2024-11, Vol.15 (11), p.1377</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c295t-bd1ff4e55cba616893319bbea96c61cd455e2e03492e0e22ee9bac8f69f1a9f53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3132909308/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3132909308?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25744,27915,27916,37003,44581,74887</link.rule.ids></links><search><creatorcontrib>Chen, Han</creatorcontrib><creatorcontrib>Mamitimin, Yusuyunjiang</creatorcontrib><creatorcontrib>Abulizi, Abudukeyimu</creatorcontrib><creatorcontrib>Huang, Meiling</creatorcontrib><creatorcontrib>Tao, Tongtong</creatorcontrib><creatorcontrib>Ma, Yunfei</creatorcontrib><title>Seasonal and Diurnal Characteristics and Drivers of Urban Heat Island Based on Optimal Parameters-Based Geo-Detector Model in Xinjiang, China</title><title>Atmosphere</title><description>In the context of sustainable urban development, elucidating urban heat island (UHI) dynamics in arid regions is crucial. 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The seasonal disparity of SUHII in Xinjiang was more significant during the daytime (3.91 °C) compared to nighttime (0.39 °C), with daytime and nighttime SUHIIs decreasing from summer to winter. The study also highlights that the city size, elevation, vegetation cover, urban form, and socio-economic factors (GDP and population density) emerged as key drivers, with the GDP exerting the strongest influence on SUHIIs in cities across Xinjiang. To mitigate the UHI effects, measures like urban environment enhancement by improving surface conditions, blue–green space development, landscape optimization, and economic strategy adjustments are recommended.</description><subject>Arid regions</subject><subject>Arid zones</subject><subject>Cities</subject><subject>Climate</subject><subject>Correlation analysis</subject><subject>Daytime</subject><subject>Diurnal variations</subject><subject>driving factors</subject><subject>Economic factors</subject><subject>Economic growth</subject><subject>Economics</subject><subject>Energy consumption</subject><subject>Environmental aspects</subject><subject>Environmental impact</subject><subject>GDP</subject><subject>Green development</subject><subject>Green infrastructure</subject><subject>Gross Domestic Product</subject><subject>Heat</subject><subject>Impact factors</subject><subject>Land use</subject><subject>Night</subject><subject>Night-time</subject><subject>Nighttime</subject><subject>optimal parameters-based geographic detector</subject><subject>Parameters</subject><subject>Plant cover</subject><subject>Population</subject><subject>Population density</subject><subject>Public health</subject><subject>Remote sensing</subject><subject>Research methodology</subject><subject>seasonal and diurnal characteristics</subject><subject>Sensors</subject><subject>Socioeconomic aspects</subject><subject>Socioeconomic factors</subject><subject>Socioeconomics</subject><subject>Summer</subject><subject>Sustainable development</subject><subject>Urban areas</subject><subject>Urban development</subject><subject>Urban environments</subject><subject>urban heat island</subject><subject>Urban heat islands</subject><subject>Urbanization</subject><subject>Vegetation</subject><subject>Vegetation cover</subject><subject>Winter</subject><issn>2073-4433</issn><issn>2073-4433</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpVkd9LHDEQx5dioWJ97Hugr67m1-5tHu1p9UCx0Ap9C7PJ5JpjL7kmUegf4f_cnCuiCSTDd2Y-mcw0zRdGT4VQ9AzKNmbWMcbEYvGhOeR0IVophTh4Y39qjnPe0LqkElzIw-bpJ0KOASYCwZIL_5D29vIPJDAFk8_Fmzz7kn_ElEl05D6NEMg1QiGrPO2d3yCjJTGQu13x20r4UQFbrITczr4rjO1FFUyJidxGixPxgfz2YeMhrE_qkz7A5-ajgynj8ct91Nx_v_y1vG5v7q5Wy_Ob1nDVlXa0zDmJXWdG6Fk_KCGYGkcE1ZueGSu7DjlSIVU9kXNENYIZXK8cA-U6cdSsZq6NsNG7VEtO_3QEr5-FmNYaUv35hFoyZSmAos5wSXk3VtsNhi5QWdNzqKyvM2uX4t8HzEVv4nMXsxZMcEWVoEONOp2j1lChPrhYaofrtrj1JgZ0vurnAxsYZcPQ14R2TjAp5pzQvZbJqN5PXL-buPgP1gifdw</recordid><startdate>20241101</startdate><enddate>20241101</enddate><creator>Chen, Han</creator><creator>Mamitimin, Yusuyunjiang</creator><creator>Abulizi, Abudukeyimu</creator><creator>Huang, Meiling</creator><creator>Tao, Tongtong</creator><creator>Ma, Yunfei</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>SOI</scope><scope>DOA</scope></search><sort><creationdate>20241101</creationdate><title>Seasonal and Diurnal Characteristics and Drivers of Urban Heat Island Based on Optimal Parameters-Based Geo-Detector Model in Xinjiang, China</title><author>Chen, Han ; 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By thoroughly examining the characteristics of UHI variations and potential driving factors, cities can implement effective strategies to reduce their impacts on the environment and public health. However, the driving factors of a UHI in arid regions remain unclear. This study analyzed seasonal and diurnal variations in a surface UHI (SUHI) and the potential driving factors using Pearson’s correlation analysis and an Optimal Parameters-Based Geographic Detector (OPGD) model in 22 cities in Xinjiang, northwest China. The findings reveal that the average annual surface urban heat island intensity (SUHII) values in Xinjiang’s cities were 1.37 ± 0.86 °C, with the SUHII being most pronounced in summer (2.44 °C), followed by winter (2.15 °C), spring (0.47 °C), and autumn (0.40 °C). Moreover, the annual mean SUHII was stronger at nighttime (1.90 °C) compared to during the daytime (0.84 °C), with variations observed across seasons. The seasonal disparity of SUHII in Xinjiang was more significant during the daytime (3.91 °C) compared to nighttime (0.39 °C), with daytime and nighttime SUHIIs decreasing from summer to winter. The study also highlights that the city size, elevation, vegetation cover, urban form, and socio-economic factors (GDP and population density) emerged as key drivers, with the GDP exerting the strongest influence on SUHIIs in cities across Xinjiang. To mitigate the UHI effects, measures like urban environment enhancement by improving surface conditions, blue–green space development, landscape optimization, and economic strategy adjustments are recommended.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/atmos15111377</doi><oa>free_for_read</oa></addata></record> |
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subjects | Arid regions Arid zones Cities Climate Correlation analysis Daytime Diurnal variations driving factors Economic factors Economic growth Economics Energy consumption Environmental aspects Environmental impact GDP Green development Green infrastructure Gross Domestic Product Heat Impact factors Land use Night Night-time Nighttime optimal parameters-based geographic detector Parameters Plant cover Population Population density Public health Remote sensing Research methodology seasonal and diurnal characteristics Sensors Socioeconomic aspects Socioeconomic factors Socioeconomics Summer Sustainable development Urban areas Urban development Urban environments urban heat island Urban heat islands Urbanization Vegetation Vegetation cover Winter |
title | Seasonal and Diurnal Characteristics and Drivers of Urban Heat Island Based on Optimal Parameters-Based Geo-Detector Model in Xinjiang, China |
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