Study on Summer Microclimate Analysis and Optimization Strategies for Urban Parks in Xinjiang—A Case Study of Mingzhu Park
To investigate the impact of landscape characteristics on microclimate and thermal comfort in summer urban parks in Xinjiang, we focused on Mingzhu Park in Shihezi City. We collected microclimatic data through field measurements and analyzed the correlations among these factors, the physiological eq...
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description | To investigate the impact of landscape characteristics on microclimate and thermal comfort in summer urban parks in Xinjiang, we focused on Mingzhu Park in Shihezi City. We collected microclimatic data through field measurements and analyzed the correlations among these factors, the physiological equivalent temperature (PET), and the landscape features. ENVI-met was utilized for microclimate simulations to assess the optimization effects. The results revealed that different landscape features significantly influenced the microclimate and thermal comfort. Trees and grass effectively lowered the temperature, increased humidity, reduced wind speeds, blocked solar radiation, and decreased the PET. Water bodies exposed to sunlight and without shade have a low reflectivity, leading to significant temperature increases. While evaporation can lower the surrounding temperatures, the water surface temperature remains higher than in shaded areas, raising temperatures there. The temperature, humidity, wind speed, and mean radiant temperature show significant correlations. The correlation ranking is as follows: mean radiant temperature (Tmrt) > air temperature (Ta) > relative humidity (RH) > wind speed (Va). After increasing the tree cover and designing dispersed water bodies, the average PET decreased by up to 0.67 °C, with the park experiencing the largest reduction of 1.86 °C. The PET in the eastern built-up area was reduced by 0.35 °C, and in the western built-up area, by only 0.13 °C. |
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We collected microclimatic data through field measurements and analyzed the correlations among these factors, the physiological equivalent temperature (PET), and the landscape features. ENVI-met was utilized for microclimate simulations to assess the optimization effects. The results revealed that different landscape features significantly influenced the microclimate and thermal comfort. Trees and grass effectively lowered the temperature, increased humidity, reduced wind speeds, blocked solar radiation, and decreased the PET. Water bodies exposed to sunlight and without shade have a low reflectivity, leading to significant temperature increases. While evaporation can lower the surrounding temperatures, the water surface temperature remains higher than in shaded areas, raising temperatures there. The temperature, humidity, wind speed, and mean radiant temperature show significant correlations. The correlation ranking is as follows: mean radiant temperature (Tmrt) > air temperature (Ta) > relative humidity (RH) > wind speed (Va). After increasing the tree cover and designing dispersed water bodies, the average PET decreased by up to 0.67 °C, with the park experiencing the largest reduction of 1.86 °C. The PET in the eastern built-up area was reduced by 0.35 °C, and in the western built-up area, by only 0.13 °C.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su16177687</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Cities ; Cooling ; Energy consumption ; Global warming ; Humidity ; Microclimate ; Outdoor activities ; Parks & recreation areas ; Research methodology ; Simulation ; Summer ; Sustainable development ; Temperature ; Topography ; Trees ; Urban heat islands ; Vegetation</subject><ispartof>Sustainability, 2024-09, Vol.16 (17), p.7687</ispartof><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/). 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We collected microclimatic data through field measurements and analyzed the correlations among these factors, the physiological equivalent temperature (PET), and the landscape features. ENVI-met was utilized for microclimate simulations to assess the optimization effects. The results revealed that different landscape features significantly influenced the microclimate and thermal comfort. Trees and grass effectively lowered the temperature, increased humidity, reduced wind speeds, blocked solar radiation, and decreased the PET. Water bodies exposed to sunlight and without shade have a low reflectivity, leading to significant temperature increases. While evaporation can lower the surrounding temperatures, the water surface temperature remains higher than in shaded areas, raising temperatures there. The temperature, humidity, wind speed, and mean radiant temperature show significant correlations. The correlation ranking is as follows: mean radiant temperature (Tmrt) > air temperature (Ta) > relative humidity (RH) > wind speed (Va). After increasing the tree cover and designing dispersed water bodies, the average PET decreased by up to 0.67 °C, with the park experiencing the largest reduction of 1.86 °C. The PET in the eastern built-up area was reduced by 0.35 °C, and in the western built-up area, by only 0.13 °C.</description><subject>Cities</subject><subject>Cooling</subject><subject>Energy consumption</subject><subject>Global warming</subject><subject>Humidity</subject><subject>Microclimate</subject><subject>Outdoor activities</subject><subject>Parks & recreation areas</subject><subject>Research methodology</subject><subject>Simulation</subject><subject>Summer</subject><subject>Sustainable development</subject><subject>Temperature</subject><subject>Topography</subject><subject>Trees</subject><subject>Urban heat islands</subject><subject>Vegetation</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNkM9Kw0AQhxdRsNRefIIFb0J0Jptkk2Mp_oNKhVrwFjbJbt3abOpuckjx4EP4hD6JW1vQufzm8PEb5iPkHOGKsQyuXYcJcp6k_IgMQuAYIMRw_G8_JSPnVuCHMcwwGZCPedtVPW0MnXd1LS191KVtyrWuRSvp2Ih177SjwlR0tml1rbei1Tu6tR5Yaumoaixd2EIY-iTsm6Pa0BdtVlqY5ffn15hOhJP0cEb5frPcvna_7Bk5UWLt5OiQQ7K4vXme3AfT2d3DZDwNSkyjNhAcCwZRXHKIU-mzUlkGScEqVBCHWVUAljws_OtKyZBLXu4gkEkaZVBxNiQX-96Nbd476dp81XTW_-ZyhhBhhBBGnrrcU16Ac1aqfGO9BtvnCPlOcP4nmP0Aevtu1Q</recordid><startdate>20240904</startdate><enddate>20240904</enddate><creator>Zhao, Zhao</creator><creator>Li, Jie</creator><creator>Fu, Zongchi</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>20240904</creationdate><title>Study on Summer Microclimate Analysis and Optimization Strategies for Urban Parks in Xinjiang—A Case Study of Mingzhu Park</title><author>Zhao, Zhao ; Li, Jie ; Fu, Zongchi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c184t-a71b3045c7058e45cdf9906b3d1f0529db01c72b776ffe27e7c45cd0e68490d73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Cities</topic><topic>Cooling</topic><topic>Energy consumption</topic><topic>Global warming</topic><topic>Humidity</topic><topic>Microclimate</topic><topic>Outdoor activities</topic><topic>Parks & recreation areas</topic><topic>Research methodology</topic><topic>Simulation</topic><topic>Summer</topic><topic>Sustainable development</topic><topic>Temperature</topic><topic>Topography</topic><topic>Trees</topic><topic>Urban heat islands</topic><topic>Vegetation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Zhao</creatorcontrib><creatorcontrib>Li, Jie</creatorcontrib><creatorcontrib>Fu, Zongchi</creatorcontrib><collection>CrossRef</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Zhao</au><au>Li, Jie</au><au>Fu, Zongchi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Study on Summer Microclimate Analysis and Optimization Strategies for Urban Parks in Xinjiang—A Case Study of Mingzhu Park</atitle><jtitle>Sustainability</jtitle><date>2024-09-04</date><risdate>2024</risdate><volume>16</volume><issue>17</issue><spage>7687</spage><pages>7687-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><abstract>To investigate the impact of landscape characteristics on microclimate and thermal comfort in summer urban parks in Xinjiang, we focused on Mingzhu Park in Shihezi City. We collected microclimatic data through field measurements and analyzed the correlations among these factors, the physiological equivalent temperature (PET), and the landscape features. ENVI-met was utilized for microclimate simulations to assess the optimization effects. The results revealed that different landscape features significantly influenced the microclimate and thermal comfort. Trees and grass effectively lowered the temperature, increased humidity, reduced wind speeds, blocked solar radiation, and decreased the PET. Water bodies exposed to sunlight and without shade have a low reflectivity, leading to significant temperature increases. While evaporation can lower the surrounding temperatures, the water surface temperature remains higher than in shaded areas, raising temperatures there. The temperature, humidity, wind speed, and mean radiant temperature show significant correlations. The correlation ranking is as follows: mean radiant temperature (Tmrt) > air temperature (Ta) > relative humidity (RH) > wind speed (Va). After increasing the tree cover and designing dispersed water bodies, the average PET decreased by up to 0.67 °C, with the park experiencing the largest reduction of 1.86 °C. The PET in the eastern built-up area was reduced by 0.35 °C, and in the western built-up area, by only 0.13 °C.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su16177687</doi><oa>free_for_read</oa></addata></record> |
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subjects | Cities Cooling Energy consumption Global warming Humidity Microclimate Outdoor activities Parks & recreation areas Research methodology Simulation Summer Sustainable development Temperature Topography Trees Urban heat islands Vegetation |
title | Study on Summer Microclimate Analysis and Optimization Strategies for Urban Parks in Xinjiang—A Case Study of Mingzhu Park |
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