“Our results from a large sample of wind farms revealed significant local warming effects at night, insignificant impacts during the daytime, and the mostly negative impacts on vegetation.” (Yingzuo Qin et al., Environmental Research Letters, 2022)
Deep Ecology is a philosophy that puts nature on an equal footing with humankind. It speaks in religious tones to its broad congregation of partial and total believers. “The froth and frenzy of industrial civilization mask our deep loneliness for that communion with the world that can lift our spirits and fill our senses with the richness and immediacy of life itself,” Al Gore stated in Earth in the Balance (1992), calling for “bold and unequivocal” global action where “the rescue of the environment” is “the central organizing principle for civilization.”
Applied to the Church of Climate, the often unstated assumptions are:
To members of this philosophy-religion, the planet “has been delivered in perfect working condition and cannot be exchanged for a new one.” (Natural Capitalism, by Amory Lovins et al., 2013.) An issue of World Watch magazine, “Playing God with Climate” (Volume 10, no. 6; Nov-Dec 1997), scolded man for interfering with the Earth’s default condition.
Hard Being Green
It is hard being green! Imagine all the look-the-other-way insults to the living space that come with the shotgun wedding to industrial wind turbines, in particular. I was reminded of this upon encountering an article called “Impacts of 319 Wind Farms on Surface Temperature and Vegetation in the United States,” (Yingzuo Qin et al., Environmental Research Letters, February 11, 2022)
The abstract follows, with the politically correct first sentence (maybe a reviewer recommended this) to demote the bad news. We report–you decide.
The development of wind energy is essential for decarbonizing energy production. 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 moderate resolution imaging spectroradiometer satellite data to quantify the impacts on local climate and vegetation of 319 wind farms in the United States.
Our results indicated insignificant impacts on LST during the daytime but significant warming of 0.10 °C of annual mean nighttime LST averaged over all wind farms, and 0.36 °C for those 61% wind farms 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 normalized difference vegetation index (NDVI) for 59% of wind farms due to infrastructure construction, with an average reduction 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 NDVI were only evident within the wind farm locations. Wind farms built in grassland and cropland showed larger warming effects but weaker vegetation impact than those built on forests.
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 evidence for wind farm impacts with improved representativeness compared to previous studies.
This knowledge is important to fully understand the climatic and environmental implications of energy system decarbonization.
Based on satellite remote sensing data, our assessment of 319 wind farms in the United States provides new observational evidence for the impacts of wind farms on local climate and vegetation. Our study reconciles the inconsistent impacts reported in previous studies, which focused only on a few individual wind farms lacking representativeness.
Our results from a large sample of wind farms revealed significant local warming effects at night, insignificant impacts during the daytime, and the mostly negative impacts on vegetation. The large heterogeneity in wind farm impacts highlights the role of wind farm characteristics, environmental factors, and undocumented local factors.
The quantification method can be applied to other countries or regions with available wind farm information. Further studies using satellite data at finer resolution than MODIS data could reveal the impact with more spatial detail. These observations can be combined with numerical simulations to advance the mechanistic understanding of wind farm impacts on the local climate.
The improved knowledge of wind farm impacts helps inform the environmental consequences of wind energy development and guide clean energy planning for sustainable development.