The expansion of solar photovoltaic farms could have unexpected consequences on farmlands, pastures, and woodlands in the United States
Abstract
Growing energy demands and the drive towards low- and medium-carbon sources of energy have accelerated the development of solar energy technologies. The simplified deployment ("plug-and-play technology") of utility-scale solar photovoltaic (PV) energy (USSPVE, i.e., ≥1 megawatt (MW)) system results in a rapid expansion of USSPVE farms across the world. The United States has rapidly risen to rank as the 2th largest solar hot spot country in the world by the end of 2017. The expansion of USSPVE farms represents a significant land cover/land use change (LCLUC) affecting the hosting ecosystems; however, the distribution of the USSPVE farms and the effect of their development on LCLUC in the United States (U.S.) are poorly understood. Based on remote sensing techniques using satellite imagery of Sentinel 1, Sentinel 2, Landsat 5, 6, and 8, we proposed a systematic approach to plot USSPVE footprints of >400 USSPV operating sites (capacity ≥5 MW) and their installation time within the continental U.S.. By 2017, the solar PV panels of these sites have a total operating area of 410.40 km2, an increase of approximately 100 folds over 2007 (3.96 km2), and most built since 2011. According to the National Land Cover Database, we reported an estimate of 53% of USSPVE installations are located in farmlands and pastures, comprising 132.55 and 87.04 km2 of change. The expansion of solar PV panels incurred not only 141.98 km2 of shrubland loss, mostly in the southwest, but also 11.89 km2 of forest declined in the east. Less than 10% of USSE installations are sited in urban and barren areas. Assessing the scale of PV development and its impact on LCLUC and the surrounding environment is key to identifying mitigation strategies, not only in semi-arid areas, but more importantly in humid landscapes, which is crucial for the healthy and sustainable development of USSPVE facilities.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.B31I2594W
- Keywords:
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- 1632 Land cover change;
- GLOBAL CHANGEDE: 1640 Remote sensing;
- GLOBAL CHANGEDE: 1855 Remote sensing;
- HYDROLOGYDE: 1942 Machine learning;
- INFORMATICS