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1.
Sci Data ; 10(1): 760, 2023 11 08.
Article in English | MEDLINE | ID: mdl-37938593

ABSTRACT

Over 4,400 large-scale solar photovoltaic (LSPV) facilities operate in the United States as of December 2021, representing more than 60 gigawatts of electric energy capacity. Of these, over 3,900 are ground-mounted LSPV facilities with capacities of 1 megawatt direct current (MWdc) or more. Ground-mounted LSPV installations continue increasing, with more than 400 projects appearing online in 2021 alone; however, a comprehensive, publicly available georectified dataset including spatial footprints of these facilities is lacking. The United States Large-Scale Solar Photovoltaic Database (USPVDB) was developed to fill this gap. Using US Energy Information Administration (EIA) data, locations of 3,699 LSPV facilities were verified using high-resolution aerial imagery, polygons were digitized around panel arrays, and attributes were appended. Quality assurance and control were achieved via team peer review and comparison to other US PV datasets. Data are publicly available via an interactive web application and multiple downloadable formats, including: comma-separated value (CSV), application programming interface (API), and GIS shapefile and GeoJSON.

2.
Sci Data ; 7(1): 15, 2020 01 13.
Article in English | MEDLINE | ID: mdl-31932591

ABSTRACT

Over 60,000 utility-scale wind turbines are installed in the United States as of October, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.

3.
J Acoust Soc Am ; 146(2): 1124, 2019 08.
Article in English | MEDLINE | ID: mdl-31472564

ABSTRACT

With results from a nationwide survey sponsored by the U.S. Department of Energy, factors that affect outdoor audibility and noise annoyance of wind turbines were evaluated. Wind turbine and summer daytime median background sound levels were estimated for 1043 respondents. Wind turbine sound level was the most robust predictor of audibility yet only a weak, albeit significant, predictor of noise annoyance. For each 1 dB increase in wind turbine sound level (L1h-max), the odds of hearing a wind turbine on one's property increased by 31% [odds ratio (OR): 1.31; 95% CI (confidence interval): 1.25-1.38] and the odds of moving to the next level of annoyance increased by 9% (OR: 1.09; 95% CI: 1.02-1.16). While audibility was overwhelmingly dependent on turbine sound level, noise annoyance was best explained by visual disapproval (OR: 11.0; 95% CI: 4.8-25.4). The final models correctly predict audibility and annoyance level for 80% and 62% of individuals, respectively. The results demonstrate that among community members not receiving personal benefits from wind projects, the Community Tolerance Level of wind turbine noise for the U.S. aligns with the international average, further supporting observations that communities are less tolerant of wind turbine noise than other common environmental noise sources at equivalent A-weighted sound levels.

4.
Environ Int ; 132: 105090, 2019 11.
Article in English | MEDLINE | ID: mdl-31437643

ABSTRACT

As wind turbines and the number of wind projects scale throughout the world, a growing number of individuals might be affected by these structures. For some people, wind turbine sounds and their effects on the landscape can be annoying and could even prompt stress reactions. This comparative study analyzed a combined sample of survey respondents from the U.S., Germany and Switzerland. It utilized a newly developed assessment scale (AS-Scale) to reliably characterize these stress-impacted individuals living within populations near turbines. Findings indicate low prevalence of annoyance, stress symptoms and coping strategies. Noise annoyance stress (NAS-Scale) was negatively correlated with the perceptions of a lack of fairness of the wind project's planning and development process, among other subjective variables. Objective indicators, such as the distance from the nearest turbine and sound pressure level modeled for each respondent, were not found to be correlated to noise annoyance. Similar result patterns were found across the European and U.S. samples.


Subject(s)
Noise/adverse effects , Power Plants , Stress, Physiological , Adaptation, Psychological , Female , Germany , Humans , Male , Middle Aged , Surveys and Questionnaires , Switzerland , Wind
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