Wind Farms Impacts on Land Surface Temperature and Its Driving Factors in an Arid Area of Xinjiang, China

Hongnan Jiang (), Mengyu Xie (), Xu Li, Maohua Tian, Wangcai Cui and Doudou Hao
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Hongnan Jiang: College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830017, China
Mengyu Xie: College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830017, China
Xu Li: College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830017, China
Maohua Tian: College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830017, China
Wangcai Cui: College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830017, China
Doudou Hao: College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830017, China

Sustainability, 2025, vol. 17, issue 21, 1-30

Abstract: Wind energy is vital for clean energy development in ecologically fragile arid regions. This study presents the first comprehensive analysis of wind farm impacts on land surface temperature (LST) in the extremely arid area of Xinjiang, China, using MODIS (2008–2022) and Landsat data. Key findings include (1) pronounced nighttime warming in winter (up to 1.548 °C/15a) in densely turbine-populated areas, contrasting with autumn cooling; (2) Random Forest regression identifying wind speed, precipitation, NDVI, and snow cover as key drivers of LST changes; (3) enhanced post-construction warming, especially in summer nights in the Southeast Wind Zone; (4) significant thermal effects confirmed against non-affected areas, showing diurnal asymmetry and downwind warming; and (5) a distance–decay pattern of LST anomalies, strongest within 2–5 km of turbines yet detectable up to 20 km. These results reveal a unique spatial–seasonal complexity in LST changes induced by wind farms in arid regions, emphasizing the critical roles of topography and turbine density. This study underscores the necessity of integrating microclimate feedbacks into sustainable wind energy planning in arid environments.

Keywords: wind farms; arid regions; land surface temperature; driving factors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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