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035 a| (OCoLC)1397376855;

043 a| n-us---;

090 a| HD9681.U62;

049 a| EREE;

100 1 a| Quainoo, Ruth,e| author.?| UNAUTHORIZED;

245 10 a| Preference for and impacts of different utility-scale energy siting decisions for electricity generators in coastal regions /c| by Ruth Quainoo.;

264 1 a| [Greenville, N.C.] :b| [East Carolina University],c| 2023.;

300 a| 1 online resource (141 pages) :b| illustrations (some color);

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

347 a| text fileb| PDFc| 1.973 MB2| rda;

538 a| System requirements: Adobe Reader.;

538 a| Mode of access: World Wide Web.;

502 b| Ph.D.c| East Carolina Universityd| 2023.;

500 a| Presented to the Faculty of the Department of Coastal Studies;

500 a| Advisor: Gregory Howard;

500 a| Title from PDF t.p. (viewed September 24, 2024).;

520 3 a| Both site selection and fuel choice decisions for utility-scale generators have important ramifications for the surrounding community. This is especially true in coastal regions, where land is often scarce due to high population densities. This study explores different aspects of site selection and fuel choice for large utility-scale energy generators in three different papers. Chapter 1 explores the public's preference for utility-scale solar energy siting in Rhode Island based on four current land types: agricultural, brownfield, commercial, and forest land. This chapter uses a discrete choice experiment survey to help evaluate how program attributes affect respondent preferences for large utility-scale solar energy siting in Rhode Island. Public's willingness to pay for a large set of solar siting decision attributes such as the size of a solar installation, visibility of solar panels, setback or a minimum distance of the solar panels from property lines, and the probability of residential development was estimated. Chapter 2 uses the hedonic pricing method and spatial difference-in-differences estimators to examine how multiple energy sources (that is, clean or dirty fuel types) impact property values in four East Coastal US states (GA, NC, RI, and SC) using Zillow ZTRAX housing transaction data and Energy Information Administration powerplant data. Geographic Information Systems (GIS) is used to measure the distance from each property to the closest energy generators within the region. The final chapter of this study uses data from Energy Information Administration (EIA) and spatially explicit data on flood risk with a variety of measures from First Street Foundation's Flood Lab to assess the resilience of coastal community energy infrastructure and the flood risk faced by renewable energy infrastructure.;

504 a| Includes bibliographical references.;

650 0 a| Solar energy industriesx| Environmental aspectsz| Rhode Island.=| ^A134738;

650 0 a| Solar energy industriesx| Environmental aspectsz| Atlantic Coast (Middle Atlantic States)=| ^A134738;

650 0 a| Electric generatorsz| Rhode Island.=| ^A79544;

650 0 a| Electric generatorsz| Atlantic Coast (Middle Atlantic States)=| ^A79544;

650 0 a| Floodsx| Risk assessment.=| ^A21216;

650 0 a| Hedonic pricing.=| ^A1474366;

653 a| Discrete Choice Experiment;

653 a| Conditional Logit Model;

653 a| Mixed Logit Model;

653 a| Spatial difference-in-difference;

653 a| Spatial Merge;

653 a| Energy Infrastructure;

653 a| Housing Transactions;

700 1 a| Howard, Gregory,e| degree supervisor.?| UNAUTHORIZED;

710 2 a| East Carolina University.b| Department of Coastal Studies.?| UNAUTHORIZED;

856 40 z| Access via ScholarShipu| http://hdl.handle.net/10342/13119;

994 a| C0b| ERE;

596 a| 1 4;

998 a| 6234508;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6234508-1001l| JNETm| JOYNERr| Ys| Yt| JNE3ETDu| 9/15/2023x| ETDz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6234508-2001l| HSLELECm| HSLr| Ys| Yt| HEETDu| 9/15/2023x| ETDz| HERESOURCE;

Preference for and impacts of different utility-scale energy siting decisions for electricity generators in coastal regions / by Ruth Quainoo.

Author/creator	Quainoo, Ruth author.
Other author	Howard, Gregory, degree supervisor.
Other author	East Carolina University. Department of Coastal Studies.
Format	Theses and dissertations
Publication	[Greenville, N.C.] : [East Carolina University], 2023.
Description	1 online resource (141 pages) : illustrations (some color)
Supplemental Content	Access via ScholarShip
Subjects	Solar energy industries--Environmental aspects. --Rhode Island. Solar energy industries--Environmental aspects. --Atlantic Coast (Middle Atlantic States). Electric generators--Rhode Island. Electric generators--Atlantic Coast (Middle Atlantic States). Floods--Risk assessment. Hedonic pricing.

Summary	Both site selection and fuel choice decisions for utility-scale generators have important ramifications for the surrounding community. This is especially true in coastal regions, where land is often scarce due to high population densities. This study explores different aspects of site selection and fuel choice for large utility-scale energy generators in three different papers. Chapter 1 explores the public's preference for utility-scale solar energy siting in Rhode Island based on four current land types: agricultural, brownfield, commercial, and forest land. This chapter uses a discrete choice experiment survey to help evaluate how program attributes affect respondent preferences for large utility-scale solar energy siting in Rhode Island. Public's willingness to pay for a large set of solar siting decision attributes such as the size of a solar installation, visibility of solar panels, setback or a minimum distance of the solar panels from property lines, and the probability of residential development was estimated. Chapter 2 uses the hedonic pricing method and spatial difference-in-differences estimators to examine how multiple energy sources (that is, clean or dirty fuel types) impact property values in four East Coastal US states (GA, NC, RI, and SC) using Zillow ZTRAX housing transaction data and Energy Information Administration powerplant data. Geographic Information Systems (GIS) is used to measure the distance from each property to the closest energy generators within the region. The final chapter of this study uses data from Energy Information Administration (EIA) and spatially explicit data on flood risk with a variety of measures from First Street Foundation's Flood Lab to assess the resilience of coastal community energy infrastructure and the flood risk faced by renewable energy infrastructure.
General note	Presented to the Faculty of the Department of Coastal Studies
General note	Advisor: Gregory Howard
General note	Title from PDF t.p. (viewed September 24, 2024).
Dissertation note	Ph.D. East Carolina University 2023.
Bibliography note	Includes bibliographical references.
Technical details	System requirements: Adobe Reader.
Technical details	Mode of access: World Wide Web.

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Preference for and impacts of different utility-scale energy siting decisions for electricity generators in coastal regions / by Ruth Quainoo.

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