Impacts of 319 wind farms on surface temperature and vegetation in the United States

Qin, Yingzuo and Li, Yan and Xu, Ru and Hou, Chengcheng and Armstrong, Alona and Bach, Eviatar and Wang, Yang and Fu, Bojie (2022) Impacts of 319 wind farms on surface temperature and vegetation in the United States. Environmental Research Letters, 17 (2): 024026. ISSN 1748-9326

Abstract

The development of wind energy is essential for decarbonizing energy supplies. However, the construction of wind farms changes land surface temperature (LST) and vegetation by modifying land surface properties and disturbing land-atmosphere interactions. In this study, we used MODIS satellite data to quantify the impacts of 319 wind farms on local climate and vegetation in the United States. Our results indicated insignificant impacts on LST during the daytime but significant warming of 0.10°C on annual mean nighttime LST averaged for all wind farms, and 0.36°C for those 61% wind farm samples with warming. The nighttime LST impacts exhibited seasonal variations, with stronger warming in winter and autumn up to 0.18°C but weaker effects in summer and spring. We observed a decrease in peak NDVI for 59% of wind farms due to infrastructure construction, with an average decrease of 0.0067 compared to non-wind-farm areas. The impacts of wind farms depended on wind farm size, with winter LST impacts for large and small wind farms ranging from 0.21°C to 0.14°C, and peak NDVI impacts ranging from -0.009 to -0.006. The LST impacts declined with the increasing distance from the wind farm, with detectable impacts up to 10 km. In contrast, the vegetation impacts on NVDI were only evident within the wind farm locations. Wind farms built in grassland and cropland showed larger warming effects but weaker vegetation impact compared to those built on forest land. Furthermore, spatial correlation analyses with environmental factors suggest limited geographical controls on the heterogeneous wind farm impacts and highlight the important role of local factors. Our analyses based on a large sample offer new observational evidence for the wind farm impacts with improved representativeness. This knowledge is important to fully understand the climatic and environmental implications of energy system decarbonization.