Public and Local Policymaker Preferences for Large-Scale Energy Project Characteristics

doi:10.21203/rs.3.rs-3962742/v1

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Public and Local Policymaker Preferences for Large-Scale Energy Project Characteristics

https://doi.org/10.21203/rs.3.rs-3962742/v1

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published 01 Aug, 2024

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Rapidly building utility-scale energy infrastructure requires not only public support, but also political will across levels of government. This research explores determinants of opposition and support for large-scale energy projects among residents and local elected officials in Pennsylvania—a key transition state due its high solar potential, and where siting authority rests at the local level. This work extends prior research by using a conjoint to compare many project characteristics simultaneously, expanding the set of characteristics typically considered, sampling both the public and elected officials in a key transition state, and assessing the accuracy of public officials’ perceptions of their constituents. Using a conjoint experiment, we assess support for different characteristics of energy projects among a demographically representative sample of residents (n = 894) and a sample of local elected officials (n = 206). Key findings include that creation of permanent, union-wage jobs and cooperative community ownership increases support for energy projects and that solar projects are preferred over wind, nuclear, and natural gas power plants with carbon capture and storage. Support among both the public and local elected officials is lower when projects are owned by foreign companies. Strikingly, we find limited partisan differences in preferences for large scale renewable energy project characteristics, suggesting a promising path towards building bipartisan support for such projects. We also find, however, that local elected officials misperceive the preferences of their constituents, underestimating support for renewable energy and the importance of job creation. Given the role of local elected officials as key decision-makers regarding energy infrastructure development, their preferences and how they perceive their constituents’ preferences may dictate what types of energy projects are approved and what benefits they deliver to local communities.

Social science/Environmental studies

Earth and environmental sciences/Environmental social sciences/Energy and society

Earth and environmental sciences/Environmental social sciences/Climate-change mitigation

While there are multiple pathways for the United States to reach net-zero emissions by 2050, there is broad agreement that all rely on rapid, large-scale deployment of renewable energy technology to meet increased demand for electricity generation while quickly reducing emissions (Jenkins et al., 2021; Larson et al., 2021). This transition will require radical technological, industrial, economic, and social shifts: most net-zero pathways call for the US energy and industrial system to phase out coal use by around 2030 and significantly reduce oil and natural gas use by 2050. In addition to large-scale wind and solar energy development, transitioning to renewable energy at scale requires major expansion and extension of transmission grids. The viability of building out the extraordinary levels of infrastructure development required for deep decarbonization depend critically on social and community acceptance (Wüstenhagen et al., 2007) and unprecedented political will (Anderson et al., 2021).

Despite the fact that emissions reduction targets and renewable energy production goals are often set at the national or state level, the planning, siting, and deployment of large-scale energy infrastructure projects often happens locally, at the county or municipal level. Siting authority varies widely state by state in the US, but in the vast majority of states, on-shore wind and solar siting authority rests either solely at the local level, or authority varies based on project size, where at least some siting happens locally rather than at the state level (Essa et al., 2021; Kahn & Shields, 2020). Thus, local elected officials have a key role to play in the siting of large-scale energy projects, including developing zoning ordinances, voting on project approvals, and negotiating community benefits. While some research has explored the policy preferences of local elected officials relating to energy (Tumlison et al., 2018), there is a notable gap in work that examines their preferences and perceptions of their constituents’ preferences for large-scale energy projects.

This study thus seeks to understand cross-partisan public and local elected official preferences for characteristics of large-scale local energy projects, including distance from residential areas, employment opportunities, local benefits, ownership structures, site type, and fuel type. We focus on Pennsylvania—a critical energy transition state in the US (Larson et al., 2021) and historical home of extractive energy industries—where in March 2021 Governor Tom Wolf announced the largest state government solar initiative in the US to date (Commonwealth of Pennsylvania, 2021). Pennsylvania grants local governments authority for both onshore wind and solar siting (Essa et al., 2021; Kahn & Shields, 2020). Further, a recent analysis found that across more than 2500 municipalities in the Commonwealth, 87% of zoning codes provide no guidance on siting utility-scale solar (Badissy, 2021).

In this study, we thus ask: 1) what attributes of large-scale energy projects impact public and political support for their development among Pennsylvania residents? And 2) how do local elected officials perceive public support for projects? While several studies have examined how aspects of project characteristics shape public preferences for specific renewable energy projects, few have examined preferences across many project features at once or compared preferences for different types of energy projects. Additionally, no study to our knowledge has examined the preferences of publics and local elected officials using a similar survey, which allows us to compare responses among the two groups. Finally, we also ask public officials about their perceptions of the public’s preferences. Understanding whether policymakers have accurate perceptions of public preferences is important as their decisions likely reflect, at least in part, what they believe their constituents want.

We find that direct benefits to communities, including the creation of permanent, union-wage jobs and cooperative community ownership increases support for energy projects. Pennsylvanians prefer solar projects over wind, nuclear, and natural gas power plants with carbon capture and storage. Local elected officials, however, misperceive the preferences of their constituents, underestimating support for renewable energy and the importance of job loss and creation. The public and local elected officials have similar opinions of foreign-owned products, which is associated with the greatest reductions in support. Importantly, we find limited partisan differences in preferences for large scale renewable energy project characteristics, suggesting a promising path towards building bipartisan support for such projects. Given the role of local elected officials as key decision-makers regarding energy infrastructure development, their preferences and how they perceive their constituents’ preferences may be important predictors of which projects come to fruition and what benefits they provide to local communities, offering opportunities to realize just energy transitions.

1.1 Characteristics of Large-Scale Energy Projects

While various studies have examined siting preferences for specific types of large-scale energy projects, little research has compared preferences among different types of large-scale low-carbon energy projects across various dimensions. Polls consistently show that Americans overwhelmingly support the development of renewables, including wind and solar (Tyson et al., 2022), and are more likely to support wind or solar than nuclear energy (Leppert, 2022). People who already live near wind turbines tend to prefer additional wind to other types of centralized power plants (Sharpton et al., 2020). Sharpton et al. (2020) also found positive perceptions of natural gas as an energy supply, as respondents associated it with positive economic impact and local employment. In this study, in addition to measuring support for large-scale onshore wind and solar projects, we also examine support for nuclear energy and natural gas to enable comparisons across technologies.

Beyond support or opposition based on type of technology or energy infrastructure, there are a wide variety of project characteristics that may influence public preferences. In public discourse, large-scale energy projects are routinely framed in ways that emphasize specific risks or benefits to local communities, and support or opposition to projects is often tied to narratives about these risks and benefits (Bjärstig et al., 2022; Bollman, 2022). At the individual level, narratives help individuals make sense of uncertainty, influence cognition, and support or challenge existing power relations and policy outcomes (Constantino & Weber, 2021). Narratives, in this sense, also help to draw attention to and evaluate justice and equity implications surrounding project development (Carley & Konisky, 2020). Thus, we can consider a package of characteristics as one narrative - and bundling different combinations of characteristics may help us understand which narratives influence support or opposition across which groups. In this work, we consider characteristics across six dimensions: energy source, distance from residential areas, type of development site, job opportunities, local benefits, and project ownership. We selected these dimensions based on an extensive review of existing literature, conversations with experts in the field, and informed by narratives prevalent in recent news stories about energy project development. Here, we briefly review literature related to these dimensions, partisan differences in support for energy infrastructure, and Pennsylvania’s unique energy history.

A rich body of literature examines preferences for siting energy infrastructure, with a focus on renewable energy. Early research focused largely on visual aesthetics and distance from residential areas in response to NIMBY (not in my back yard) concerns from local residents (Devine-Wright, 2013; van der Horst, 2007; Wolsink, 2000). NIMBY looked to be a promising explanation for the ‘social gap’ in renewable energy siting decisions—why, when there is consistent broad public support for renewable energy, are specific projects heavily opposed (Bell et al., 2005)? However, across geographical, cultural, and project-specific contexts, there is mixed evidence for the importance of proximity to residential areas as a predictor of opposition to large-scale energy projects. Early research suggests that while proximity can have strong effects on public support for proposed projects, the ‘selfish’ components of NIMBY opposition are more nuanced, depending less on physical proximity to infrastructure and more on other characteristics of the project, like concern that projects will decrease economic and aesthetic value of the land (Devine-Wright, 2005; van der Horst, 2007). In contrast, recent survey research finds that closer proximity to residential areas or respondents’ homes is associated with reduced support for large-scale projects, including wind turbines in Germany (Langer et al., 2017) and renewable energy projects generally in the US (Sharpton et al., 2020). Further, concerns about visual impacts are associated with reduced support for large-scale solar in California (Carlisle et al., 2016), and minimum distance requirements from residential areas increase support for carbon capture and storage (CCS) projects in the US (Pianta et al., 2021).

In addition to proximity to residential areas, the siting of projects on specific types of land, like wildlife habitats and farmland, has implications for public support. Various studies point to local concerns about the ecological impact of large-scale energy projects. Ecological impact was the strongest predictor of opposition for wind energy projects in Switzerland, Estonia, and Ukraine (Vuichard et al., 2022) and respondents in Ireland favor wind projects located away from protected habitat areas (Hallan & González, 2020). This concern aligns with recurring narratives in the US about wind turbines as harmful to threatened bird species—recently, a wind energy company in the US pleaded guilty to violating the Migratory Bird Treaty Act after their turbines killed at least 150 bald eagles (The Associated Press, 2022). This concern also holds for solar, with respondents in the US preferring that solar farms have large buffers around wildlife habitat (Carlisle et al., 2016). In addition to wildlife habitat, farmland often takes a center role in discussions about renewable energy siting. Recent studies have explored the tensions between farmers and developers, seeking to better understand the intersection of farmland preservation and renewable energy siting (Moore et al., 2022; Pascaris et al., 2021). Other studies have examined the potential for development of renewables on brownfield sites or decommissioned mining sites, citing the co-benefit of fewer land constraints and greater public support (Adelaja et al., 2010; Spiess & De Sousa, 2016).

Economic risks and opportunities associated with renewable and low-carbon energy sources, specifically about employment, are particularly salient in political arguments about energy transition dynamics. Studies have found that previous federal legislation in the US, including the 2009 American Recovery and Reinvestment Act, have proven successful in creating energy sector jobs (Lim et al., 2020). Tackling climate change while creating jobs is key to US President Biden’s agenda, aiming to dispel narratives that a renewable energy transition will result in widespread job loss, particularly in states that are economically tied to the production of coal and gas (Davenport et al., 2021). However, while net employment is expected to increase as renewable energy production ramps up, this is true at a regional or national scale. At the local level, coal communities will likely see job losses at the individual and household level, resulting in loss of retail and commercial employment, and decreases of local tax revenue bases (Carley & Konisky, 2020). Furthermore, workers justifiably fear lower wages and precarious job security in renewables work compared to traditional energy industry jobs which are often unionized (Jolley et al., 2019; Scheiber, 2021).

There is potential for other local benefits, in addition to job creation, to increase local support, including direct financial benefits, reduced local air pollution, and environmental justice considerations. In Germany, both individual and collective financial benefits including discounted electricity rates, payments to communities, and payments to municipalities, were found to improve acceptance of local wind projects (Knauf, 2022). In the case of both wind turbines and electricity transmission pylons, perceptions of health risks were also found to be crucial for public support—hypothetical projects that cited a high frequency of health complaints were strongly rejected and projects that cited no occurrence of health complaints were accepted, and health related attributes were more important than location and compensation payments (Zaunbrecher et al., 2017). Beyond just predicting support or opposition to projects, understanding preferences for local benefits also has implications for equitable distribution of energy transition costs and benefits - it is critical that marginalized groups already subject to historical environmental inequities do not bear the additional brunt of potential negative transition impacts, including rising energy prices (Carley & Konisky, 2020).

Project ownership is another facet of energy infrastructure development that may impact public support. More than 80% of US energy infrastructure is owned by the private sector, including national and international companies (US Department of Homeland Security & US Department of Energy, 2015). Studies have found preferences for local ownership, though this is not the norm in practice (Goedkoop & Devine-Wright, 2016; Vuichard et al., 2022). Other studies find opposition to foreign ownership (Venus et al., 2020), which is supported in the US by the ‘America First’ rhetoric and the prioritization of national industry over foreign competitors (Lynch, 2019). While it may currently seem unlikely for large-scale energy projects to be community owned, recent work has explored possibilities for scaling up or mainstreaming community-owned energy (Roby & Dibb, 2019; Warlenius & Nettelbladt, 2023).

Partisan differences in support for renewable energy

While the trends discussed above are supported by various samples and studies, there is also heterogeneity by individual characteristics, including partisanship (Mayer, 2019). While members of both parties in the US largely support renewable energy, Republican support has dropped in recent years (Kennedy & Spencer, 2021). Reasons for renewable support also differ by party: while Republicans express support when they anticipate economic opportunities associated with renewable energy development, Democrats tend to focus on renewables as a climate change solution (Gustafson et al., 2020). At the national level, Republicans typically have a more favorable opinion of natural gas than Democrats (Hazboun & Boudet, 2021) and are also more likely to support nuclear energy (Leppert, 2022). We draw attention to partisanship, here, as climate and energy are often viewed as highly polarized issues and political identities have been found to exert powerful influences preferences (Mayer, 2019). Finding opportunities for bipartisan cooperation is one avenue toward advancing climate action, and these may be more likely to occur at the state and local levels than in national agenda-setting (Marshall & Burgess, 2022).

Studying energy infrastructure in Pennsylvania

In addition to its predilection for local, decentralized decision-making, Pennsylvania is an ideal study site as the state has a rich and diverse energy history (Levri, 2019). Princeton’s Net-Zero America modeling identified Pennsylvania (PA) as a top five state for solar capacity in the decade leading up to 2050, with one model calling for 95 gigawatts of new installed capacity (Larson et al., 2021). In addition to being a key state for renewables development in the coming decades, for almost two centuries Pennsylvania has been central to US energy resources (Black & Ladson, 2012). The state has historically been a site of extractive energy practices, including coal mining and hydraulic fracturing (fracking) of shale gas, which has been linked to adverse public health impacts (McDermott-Levy et al., 2013). Nuclear energy is another component of PA’s energy production portfolio, and indeed PA is home to Three Mile Island, the site of a partial reactor meltdown and worst nuclear incident in US history (Zaretsky, 2018). While the accident has not been linked to adverse physical health impacts, scholars have documented long-term mental health consequences for locals (Bromet et al., 1990). In the face of this history, the documented health co-benefits of renewable energy deployment in PA may be particularly salient (Dimanchev et al., 2019).

To examine preferences for low carbon energy infrastructure projects in Pennsylvania, we conducted two conjoint experiments to test the effects of various characteristics of energy projects on support for project development. These attributes are displayed in Table 1 and were selected based on the above literature of previous energy siting studies along with considerations about current discourse around energy projects in the US and Pennsylvania. We examine the effects of these project features on project approval in our samples of residents and policy makers and broken down by party affiliation.

Experimental Design

Conjoint experiments allow researchers to compare tradeoffs across multiple dimensions by randomly generating bundles of attributes and asking respondents to pick between two such choice bundles. This design more closely captures decision making in realistic contexts than asking respondents to independently evaluate options. Use of conjoint experiments to measure public preferences has increased in recent years across the social sciences (Bergquist et al., 2020; Bernauer & Gampfer, 2015; Gampfer et al., 2014). Conjoint experiments have high external validity and lower social desirability bias compared to other methods of eliciting preferences (Bansak et al., 2016; Hainmueller et al., 2014; Horiuchi et al., 2020). In experiment 1, we examine twenty-four project dimensions in a demographically representative sample of Pennsylvania residents. In experiment 2, we examine a reduced set of nineteen dimensions in a smaller sample of local elected officials. We use a limited number of attributes, and increase the number of choice pairs that respondents evaluate, to ensure that we are powered to detect 0.07 and 0.05 effect sizes despite the smaller sample size. We selected attributes to drop based on the results of experiment 1 (e.g., eliminating attribute levels that did not have significant variation, like in project benefits, and adding an additional attribute level in response to feedback from researchers experienced with elite samples). We asked respondents to choose between two energy-infrastructure projects in their area that varied on five dimensions. The full list of attributes is displayed in Table 1. In experiment 2, we additionally asked local elected officials to report their perceptions of constituent support for each proposed pair of projects.

Table 1

Conjoint Attributes Across Experiments
	Experiment 1 (public, n = 895)	Experiment 2 (local elected officials, n = 206)
Distance from residential areas	*50 miles (not likely to be visible from your home, school, or workplace) 10 miles (potentially visible during drives or commutes in and out of the area) 5 miles (potentially visible from your home, school, or workplace) 2 miles (likely visible from your home, school, or workplace)	*50 miles 2 miles
Job opportunities	*No changes to number of local energy jobs 50 jobs lost due to retirement of an old plant Creation of 50 permanent jobs with union-scale wages Creation of 50 hourly-wage jobs during construction	*No net increase of permanent jobs Net decrease of 50 permanent jobs Net increase of 50 permanent jobs
Local project benefits	* Reduced energy costs for all local residents Increased access to affordable clean energy in marginalized communities Increased overall economic activity in the community Reduced local air pollution	*Reduced residential energy costs Increased economic activity
Ownership structure	*Owned by an American private company Owned by a foreign private company Owned by a state government Owned cooperatively by a community	*Owned by an American private company Owned by a foreign private company Owned by state government Owned cooperatively by a community
Site type	*Low visual impact on scenic resources Agricultural land Decommissioned mining or industrial site Low impact on wildlife habitats	*Minimal impact on scenic views Minimal impact on agriculture Minimal impact on wildlife habitats
Energy source	*Natural gas power plant with carbon capture and storage (CCS) Large-scale onshore wind turbines Large-scale solar energy farm Nuclear power plant	*Natural gas power plant with carbon capture and storage (CCS) Natural gas power plant Large-scale onshore wind turbines Large-scale solar energy farm Nuclear power plant

*Indicates baseline attribute used in analyses (reference category set at zero)

Sampling

For experiment 1, we collected a sample of 894 Pennsylvanians that was demographically representative on age, gender, ethnicity, and household income (based on 2019 ACS 1-year estimates) and balanced on rural (25%), urban (25%), and suburban residence (50%). Our public sample was recruited by the survey firm Lucid. All respondents from our public sample completed the survey between February 7th and February 24th, 2022. 57 respondents who failed an attention check were removed from the sample and subsequent analyses. Each respondent was asked to choose between five distinct pairs of randomly generated projects, testing support across a total of 8,940 projects. For both experiments, the attribute levels were fully randomized within and across project pairs, ensuring the non-parametric identification of causal effects of the attributes (Bechtel & Scheve, 2013; Pianta et al., 2021). For this sample, probability weights were created with a post-stratification raking procedure using Census variables (from 2019 ACS 1-year estimates). This procedure follows the methodology outlined in DeBell & Krosnick (2009) for the American National Elections Study (ANES). Robustness tests including comparison across attention check failure and profile order are included in the supplementary material.

Table 2

Unweighted demographics for PA resident sample (Experiment 1)
	Variable	%	N
	Total Sample	100	894
Demographic area	Urban	25%	227
	Suburban	49%	434
	Rural	26%	233
Gender	Male	47%	416
	Female	53%	473
	Non-binary/Other	1%	5
Political party	Republican	37%	316
	Democrat	38%	319
	Independent	25%	213
Household income	Less than $25k	19%	169
	$25k-49,999	21%	190
	$50k-74,999	19%	169
	$75k-99,999	12%	111
	$100k-200k	25%	220
	More than $200k	6%	35
Age	18–34 35–54	27% 33%	238 294
	55–74	34%	306
	75+	6%	56
Level of education	Less than high school	2%	19
	High school diploma or equivalent	23%	208
	Some college	21%	186
	2-year college	13%	116
	4-year college	26%	235
	Advanced degree	15%	130
Race	White	84%	749
	Black	11%	99
	American Indian & Alaskan	0%	4
	Asian	3%	23
	Native Hawaiian	0%	1
	Other	2%	28

For Experiment 2, a sample of 219 local elected officials was recruited by the survey firm CivicPulse. 13 respondents did not complete the conjoint experiment portion of the survey, bringing the analysis sample to 206. The survey was fielded from September 20, 2022, to November 9, 2022. The sample of respondents consisted of elected policymakers in Pennsylvania from local governments (i.e., township, municipality, and county governments) with a population over 1,000 residents. Elected policy makers include top elected officials and governing board members. Each respondent was asked to choose between four distinct pairs of randomly generated projects, testing support across a total of 824 projects. For this sample, probability weights were created with a post-stratification raking procedure using the Census and presidential vote share variables. Weights are calculated using local governments in Pennsylvania with populations over 1,000 residents. This procedure follows the methodology outlined in DeBell and Krosnick (2009) for the American National Elections Study (ANES). Both surveys were approved by Princeton University’s Institutional Review Board (IRB#14367: “Origins, Functions, and Mechanisms of Coalitions for Change: Linking Individual Cognition and Collective Action, PI Elke Weber).

Table 3

Unweighted demographics for local elected official sample (Experiment 2)
	Variable	%	N
	Total Sample	100%	206
Level of education	Less than high school	0%	1
	High school graduate	7%	15
	Some college	17%	34
	College graduate	29%	60
	Some graduate school	6%	13
	Graduate degree	35%	71
	Technical/trade school	5%	11
Political party	Democrat	44%	89
	Republican	39%	79
	Independent	10%	21
	Other party	6%	13
Level of government	County	6%	12
	Municipality	54%	112
	Township	40%	82

Statistical Analysis

Stefanelli and Lukac (2020) provide a framework for conducting power analyses for conjoint experiments using simulation techniques. Using their online power-analysis tool (https://mblukac.shinyapps.io/conjoints-power-shiny/), we find that experiment 1 is well powered. With 894 participants, 5 tasks, and 4 variable levels (attribute with the largest number of options), the experiment has 94% power to detect an effect 0.05 and 81% power to detect an effect of 0.04. Experiment 2 is not as well powered given the smaller available sample size of local elected officials—with 206 participants, 4 tasks, and 4 variable levels, the experiment has 42% power to detect an effect of 0.05 and 78% power to detect an effect of 0.07.

We calculate Average Marginal Component Effects (AMCEs) for each option across attributes (Hainmueller et al., 2014), which measure the average causal effect of each attribute level on support for the project relative to a baseline. Thus, we can estimate how much each attribute level increases or decreases support for a project, holding all other elements constant. The dependent variable is a binary indicator for whether a given energy project was preferred (Y = 1) or not preferred (Y = 0). We use Ordinary Least Squares (OLS) regression to calculate the ACME for each attribute level, clustering standard errors at the respondent level to account for within-respondent correlations in responses. We use the model:

Yp = 𝛂 + 𝛃D_p + 𝛄J_p + 𝛈B_p + 𝛇_Op + 𝛉L_p + 𝛌F_p + 𝛜_p

Y represents the binary variable for whether the project p was selected. D, J, B, O, L, and F are indicators for the distance from residential areas; job impacts; local benefits; ownership model; site of land; and energy fuel-type for p, respectively, followed by an error term.

While AMCEs have a clear causal interpretation, they can be misleading for subgroup analyses when one wishes to descriptively interpret differences in preferences between two or more groups. Following the advice of Leeper et al. (2020), we report marginal means instead of differences in AMCEs as indicators of favorability toward a given feature when conducting subgroup analyses. Because levels of each attribute were randomly assigned, pairwise differences between two marginal means for a given attribute have a direct causal interpretation. Marginal means have the advantage of directly presenting differences between subgroup preferences without relying on reference categories for comparison, while AMCEs are interpreted relatively.

Experiment 1

Figure 1 shows the ACMEs from experiment 1, with 95% confidence intervals. When reporting ACMEs, one level per attribute is displayed as a baseline category and is set at zero.

Distance from residential areas

PA residents are less likely to support projects close to home, compared to projects located far from residential areas (50 miles). Support decreases by 7 percentage points (pp) 95% CI [-11.2, -3.4] when projects are located 2 miles away from residential areas, compared to when they are 50 miles away.

Job opportunities

Changes to local employment opportunities are also salient to respondents. Using no changes to jobs as a reference category, job loss reduces overall support for projects by 12pp 95% CI [-15.9, -8.4] and the creation of permanent jobs increases support by 12pp 95% CI [8.2, 16.4]. Creating temporary jobs increases support by 4pp compared to no job changes 95% CI [0.5, 8.5].

Local project benefits

Respondents find personal monetary benefits (e.g., reduced costs) preferable to community or health benefits. They prefer the reference category, reduced energy costs for all local residents, to increased overall economic activity in the community, which is associated with a reduction of 6pp in support 95% CI [-9.4, -2.0] and reduced local air pollution, which is associated with a reduction of 5pp in support 95% CI [-8.7, -1.0].

Ownership structure

Variation in ownership explains the greatest variation in support compared to other attributes. Respondents prefer cooperative community ownership, associated with a 5pp increase in support 95% CI [0.5, 10.0], relative to American private company ownership. There is no significant difference in support between the reference category and state government ownership. The most pronounced result concerns ownership by a foreign private company, which decreases support by 17pp 95% CI [-22.3, -12.4].

Site type

PA residents appear to be indifferent about the type of land on which energy projects are sited. We find no statistically significant differences in support detected between the reference category, low visual impact on scenic resources, and other attributes including agricultural land, decommissioned mining or industrial sites, and areas that would have low impact on wildlife habitats.

Energy type

PA residents appear to support solar projects over other types of energy projects, with an associated 7pp increase in support 95% CI [2.7, 11.7] relative to the reference category of natural gas power plants with CCS. Nuclear projects are associated with a 6pp reduction in support compared to natural gas with CCS 95% CI [-10.6, -1.5].

Figure 2 displays the results of a subgroup analysis by political party, comparing preferences of Democrats, Republicans, and Independents. Here, we report marginal means for each party on each attribute.

We find statistically significant differences in preferences as a function of political party affiliation between Republics and Democrats, Republicans and Independents, and Independents and Democrats. Considering distance from residential areas and site types, there is no significant difference in marginal means across respondents from any political party. Considering jobs, there is not a statistically significant difference in marginal means between Republicans and Democrats, suggesting similar preferences. There are small differences between Independents and each other party that indicate Independents do not prioritize jobs as heavily (6pp difference between Independents and Democrats’ for “no changes to number of jobs”, 7pp difference between Independents and Republicans for “50 jobs lost due to retirement of an old plant”). In both cases, Independents lean further towards the middle.

Considering the ownership and fuel type attributes, there are statistically significant differences between Republicans’ and Democrats’ marginal means in some levels. There is a 12pp difference between the parties’ marginal means in the “owned by an American private company level”, indicating that Republicans more strongly prefer projects that are owned by American private companies, and an 8.4pp difference indicating that Democrats more strongly prefer projects owned by state governments. Regarding project type, Democrats have a stronger preference for onshore wind turbines (10.6pp difference) and Democrats are less favorable toward nuclear energy than Republicans (8.6pp difference). Similarly to Republicans, Independents favor American private companies more than Democrats (11pp difference) and also have a less favorable opinion of onshore wind (12pp difference). A full table of differences in marginal means across attributes and levels between the three parties are reported in the Supplementary Information.

Experiment 2

In Experiment 2, we conducted a reduced version of the conjoint experiment with a sample of local elected officials. For this study, we ask local elected officials not only about their own support of renewable projects, but also about their perceptions of constituent support for these projects.

Distance from residential areas, job opportunities, and site type do not have a statistically significant causal effect on personal support for energy projects in the overall sample of PA local elected officials. Like the PA resident sample in experiment 1, ownership models are the strongest predictors of local elected officials’ support compared to other attributes. Compared to a baseline of ownership by an American private company, ownership by a foreign private company reduces support by 29pp 95% CI [-38.3, -18.8]. Unlike the public sample in experiment 1, local elected officials in PA do not prefer solar energy to natural gas with CCS, where we see no statistically significant difference between levels. In fact, local elected officials prefer this baseline to other options—notably, onshore wind turbines are associated with a 26pp reduction in support 95% CI [-39.2, -12.8]. Natural gas without CSS is associated with a 19pp decrease in support compared to natural gas with CCS 95% CI [-33.5, -4.6]. Nuclear power plants are associated with an 18pp reduction in support compared to natural gas with CCS 95% CI [-33.8, -2.1].

Splitting the sample of public officials into Republicans and Democrats (considering there were few Independents in this sample) and looking at the marginal means, we find limited differences. In Fig. 4, the rightmost panel displays differences in marginal means between parties, with positive values indicating that Republicans prefer a level more than Democrats, and negative values indicating that Democrats prefer a level more than Republicans. For public officials, there are very few statistically significant differences in marginal means between parties. This may be due to the very small sample size and lack of power for these comparisons. The only attribute level that differs significantly across parties is support for projects that have minimal impact on wildlife habitats, where a 17pp difference indicates that Democrats are more concerned about protecting wildlife habitats when siting energy projects.

In addition to asking local elected officials which project they preferred, we also asked them to pick which project they think their constituents would prefer. Figure 5 displays ACMEs for Experiment 1 on the left panel, compared to what elected officials predicted constituents would prefer on the right panel. These are presented as AMCEs as they are not subgroups, but samples from two different populations in different surveys (with different, though largely corresponding, attribute levels). Thus, we can not make direct comparisons across samples, but can observe general patterns. It appears that elected officials largely project their own preferences when judging those of their constituents. Considering constituent support for jobs, local elected official predictions do not show statistically significant differences between levels or a baseline of no changes to number of jobs, while there are relatively large casual impacts across levels of this attribute in PA residents. The most notable difference is officials’ perceptions of energy type, where officials believe that their constituents do not prefer other types of energy projects to the baseline category of natural gas with CCS. In the PA resident sample, respondents preferred solar energy to the same baseline, suggesting that elected officials underestimate support for solar renewable energy among their constituents.

The results of our conjoint experiments, and unique samples of matched public and elected officials in a key transition state, have implications for both planning and policy development around energy projects and how dimensions of proposed projects are both decided on and communicated to local communities. Considering the results of two experiments, we raise four key implications for discussion: (1) evidence of shared priorities across political parties, (2) the importance of and opportunity for labor-energy coalitions, (3) the role of alternative ownership models in just transitions, and (4) the importance of local elected officials to energy transition research.

Considering increasing polarization in the US and that federal climate change policy is framed as a highly partisan issue, our results are promising - we largely see similarity, rather than heterogeneity, in preferences for energy infrastructure projects across Democrats and Republicans in our PA resident sample. We only saw significant differences between the parties’ preferences across two attributes - ownership and energy type. Considering classic partisan ideological differences, it is not surprising that Republicans favor project ownership by American private companies more than Democrats and Democrats prefer government-owned projects more than Republicans. Across energy types, Democrats have a stronger preference for onshore wind turbines and are also less likely to prefer nuclear energy projects. Considering the wide range of project characteristics our experiment covered, it is encouraging that parties broadly share values around other dimensions like employment opportunities and project benefits. Agreement on the importance of jobs suggests that just transitions may be a bipartisan value.

The importance of net job creation to respondents across parties echoes narratives that argue for a just energy transition that supports labor in the face of fossil fuel job losses (Wang & Lo, 2021). A link between “green jobs” and “good jobs” has been central to climate policy under the Biden Administration (Davenport et al., 2021). It is also likely that this narrative is particularly salient in Pennsylvania, which has seen recent declines in nuclear, coal, and natural gas fuel jobs (BW Research, 2021). Echoing other calls, our results suggest an opportunity for labor-energy coalitions and worker-led transitions (Mijin Cha et al., 2022). Partnerships between renewable energy developers and labor organizations may be one pathway towards developing projects with broad public support, as well as other investments aimed at supporting job creation and minimizing structural unemployment, such as job training programs.

In addition to employment, project ownership appears to exert influence on public support for energy projects. Projects owned cooperatively by communities were preferred to other forms of ownership, specifically the baseline of projects owned by American private companies. This result is supported by a literature on community energy and energy sovereignty that examines a wide range of community ownership and management structures (Creamer et al., 2018; Schelly et al., 2020). Currently, most large-scale energy projects require private capital for financing, but there have been various recent calls among climate activists for public ownership of renewable energy infrastructure (Bozuwa et al., 2021; Dawson, 2021). Our findings suggest that these calls may not just be from a vocal activist minority, but could broadly increase support for project development. It is also interesting to note the lack of support for foreign owned projects. This may have been particularly salient for Americans in 2021, given increases in populist, anti-globalization sentiment, particularly among the far right (Skonieczny, 2018).

Employment opportunities and ownership structures stand in contrast to attributes that did not have strong effects on support among resident respondents, like local project benefits, site types, and distance from residential areas. It is possible that responses to projects sited close to residential areas may be different in practice - other studies point out that people may not understand distances accurately in the abstract in which they are represented in survey questions (Carlisle et al., 2016). Considering local project benefits, respondents narrowly preferred receiving low-cost energy to other benefits, including increased overall economic activity in the community and reduced local air pollution. Residential energy costs in Pennsylvania have continued to rise from 2021 through 2022, so it is reasonable to believe that costs are top of mind for ratepayers in the state (US EIA, 2022). This finding is interesting because state governments and project developers often use narratives about local community benefits when promoting projects and seeking to gain community acceptance. For example, Cottontail Solar, a large project developed by LightsourceBP currently in progress in Pennsylvania as a part of their state-wide solar initiative, touts the local economic benefits of the project, including $40 million in tax revenue over the project lifespan. The website also points to the number of temporary local jobs created and metric tons of carbon dioxide reduced each year (Lightsource BP, 2020). Our findings suggest that other possible aspects of this and other projects, including permanent jobs created, electricity rate reductions, and local ownership models, may shift support more significantly.

While respondents in the PA resident sample broadly preferred solar to other types of energy projects, we find a different pattern in our sample of local elected officials, who appear to favor natural gas with CSS to other types of projects. Considering that many US states defer siting authority to local jurisdictions, the preferences and perceptions of local elected officials are an incredibly important and understudied piece of the transition puzzle. A recent survey of utility-scale wind and solar developers found that they consider local zoning ordinances and community opposition to be two of the biggest reasons for project delays and cancellations (Nilson et al., 2024). Thus, it matters that local elected officials have accurate perceptions of public preferences when they hold decision-making power about these projects. Local elected officials also report perceptions of their constituents’ preferences in line with their own, underestimating support for solar projects. This suggests a disconnect between local elected officials and their constituents who appear more tolerant and interested in renewable energy projects like solar, and echoes other studies that find that local elected officials misperceive public preferences regarding climate policy (Mildenberger & Tingley, 2019)

These implications point to several avenues for future research. Future experimental survey research might examine additional renewable energy sources and legacy fossil fuel sources, including coal-fired power plants. We also suggest similar studies be carried out in nationally representative samples, both in the US and internationally, to examine geographic heterogeneity in preferences. Further, the importance of employment and project ownership suggest that respondent choices were influenced by attributes that correspond with community-buy in. The dimensions we measured do not represent every concern that could be raised about a project, and these experiments do not consider issues of process. For example, additional research could measure preferences for type and duration of community engagement for project development. Some existing research closely examines the siting process and argues for the role of perceived distributional and procedural justice in building community support (Vuichard et al., 2022). These dimensions might be better untangled in qualitative case study research that pays close attention to processes and power dynamics across multiple projects and communities (Caggiano & Weber, 2023).

Limitations

While our study points to important implications for energy transitions research, we also acknowledge limitations. First, the hypothetical nature of the experiment could differ from actual siting decisions in practice. Some combinations of attribute levels are more plausible than others. For example, we are not aware of any existing community-owned large-scale energy projects in Pennsylvania. That said, we believe all combinations of attributes represent possibilities that grant insight into preferences. Next, there are limitations to our sample of local elected officials in experiment 2. Local elected officials are a difficult group to survey, and our sample of 206 officials is likely underpowered to detect statistically significant differences across subgroups - this may suggest a lack of differences where differences exist. Despite this, our results do provide some insight into preferences for energy projects for which local elected officials in Pennsylvania often are key decision makers.

In this study, we assess the marginal impact of various characteristics of energy projects on support for project development among both the public and local elected officials in a key transition state. We find that the public is more likely to support solar projects, projects that create permanent jobs and community-owned projects. Foreign ownership reduces support for projects, as does job loss. On a positive note, we find substantial overlap in project characteristics preferences between Republican and Democrat respondents. We also find, however, that local elected officials misperceive the preferences of their constituents, underestimating support for renewable energy and the importance of job creation. Given the role of local elected officials as key decision-makers regarding energy infrastructure development, their preferences and perceptions of their constituents’ preferences may play an important role when considering which energy projects are approved and what benefits they deliver to local communities.

Acknowledgements:

This research was presented at the Association of Collegiate Schools of Planning Conference in October 2023, and we thank discussant Dr. Makena Coffman for her generous feedback on the manuscript. It was also presented at the 2024 American Political Science Association Virtual Research Meeting, and we thank participants of the “Greener Futures in Tense Times” panel for their comments. We also acknowledge the assistance of various research assistants and lab managers in Princeton’s Behavioral Science for Policy Lab and UBC’s School of Community and Regional Planning in making this work possible, especially Kris Nichols and Madison Lore. Finally, we acknowledge the time and expertise of the multiple stakeholders that reviewed early drafts of the conjoint experiment.

Funding acknowledgement:

We acknowledge internal funding from the Andlinger Center for Energy and the Environment that made this research possible.

Data availability statement:

All data and analyses for replication are available at https://osf.io/wkgt9/?view_only=6c8cde7c7ed34c099895ff700148c92b.

Adelaja, S., Shaw, J., Beyea, W., & Charles McKeown, J. D. (2010). Renewable energy potential on brownfield sites: A case study of Michigan. Energy Policy, 38(11), 7021–7030. https://doi.org/10.1016/j.enpol.2010.07.021
Anderson, C., Greig, C., & Ebert, P. (2021). From ambition to reality: Weaving the threads of net-zero delivery. Worley & Princeton E-Filliates Partnership. https://www.worley.com/~/media/Files/W/Worley-V3/documents/our-thinking/from-ambition-to-reality/from-ambition-to-reality-report.pdf
Badissy, M. R. (2021). Comments for Joint Hearing of the Agriculture and Rural Affairs & Local Government Committees on “Utility Scale Solar Development & Local Government Ordinances.” Penn State Dickinson Law.
Bansak, K., Hainmueller, J., & Hangartner, D. (2016). How economic, humanitarian, and religious concerns shape European attitudes toward asylum seekers. Science, 354(6309), 217–222. https://doi.org/10.1126/science.aag2147
Bechtel, M. M., & Scheve, K. F. (2013). Mass support for global climate agreements depends on institutional design. Proceedings of the National Academy of Sciences, 110(34), 13763–13768. https://doi.org/10.1073/pnas.1306374110
Bell, D., Gray, T., & Haggett, C. (2005). The ‘Social Gap’ in Wind Farm Siting Decisions: Explanations and Policy Responses. Environmental Politics, 14(4), 460–477. https://doi.org/10.1080/09644010500175833
Bergquist, P., Mildenberger, M., & Stokes, L. C. (2020). Combining climate, economic, and social policy builds public support for climate action in the US. Environmental Research Letters, 15(5), 054019. https://doi.org/10.1088/1748-9326/ab81c1
Bernauer, T., & Gampfer, R. (2015). How robust is public support for unilateral climate policy? Environmental Science & Policy, 54, 316–330. https://doi.org/10.1016/j.envsci.2015.07.010
Bjärstig, T., Mancheva, I., Zachrisson, A., Neumann, W., & Svensson, J. (2022). Is large-scale wind power a problem, solution, or victim? A frame analysis of the debate in Swedish media. Energy Research & Social Science, 83, 102337. https://doi.org/10.1016/j.erss.2021.102337
Black, B., & Ladson, M. (2012). The Legacy of ExtractionReading Patterns and Ethics in Pennsylvania’s Landscape of Energy. Pennsylvania History: A Journal of Mid-Atlantic Studies, 79(4), 377–394. https://doi.org/10.5325/pennhistory.79.4.0377
Bollman, M. (2022). Frames, fantasies, and culture: Applying and comparing different methodologies for identifying energy imaginaries in American policy discourse. Energy Research & Social Science, 84, 102380. https://doi.org/10.1016/j.erss.2021.102380
Bozuwa, J., Riofrancos, T., Knuth, S., Robbins, P., Baker, S., McCullough, A. L., McDonald, K., Mackin, C., Aldana Cohen, D., Fleming, B., Graetz, N., & Shah, N. (2021). A New Era of Public Power: A Vision for New York Power Authority in Pursuit of Climate Justice. climate + community project. https://www.climateandcommunity. org/a-new-era-of-public-power.
Bromet, E. J., Parkinson, D. K., & Dunn, L. O. (1990). Long-term Mental Health Consequences of the Accident at Three Mile Island. International Journal of Mental Health, 19(2), 48–60. https://doi.org/10.1080/00207411.1990.11449162
BW Research. (2021). 2021 Pennsylvania Energy Employment Report. Pennsylvania Department of Environmental Protection. https://www.dep.pa.gov/Business/Energy/OfficeofPollutionPrevention/EnergyEfficiency_Environment_
and_EconomicsInitiative/Pages/Workforce-Development.aspx
Caggiano, H., & Weber, E. U. (2023). Advances in Qualitative Methods in Environmental Research. Annual Review of Environment and Resources, 48(1), null. https://doi.org/10.1146/annurev-environ-112321-080106
Carley, S., & Konisky, D. M. (2020). The justice and equity implications of the clean energy transition. Nature Energy, 5(8), 569–577. https://doi.org/10.1038/s41560-020-0641-6
Carlisle, J. E., Solan, D., Kane, S. L., & Joe, J. (2016). Utility-scale solar and public attitudes toward siting: A critical examination of proximity. Land Use Policy, 58, 491–501. https://doi.org/10.1016/j.landusepol.2016.08.006
Commonwealth of Pennsylvania. (2021, March 22). Gov. Wolf Announces Largest Government Solar Energy Commitment in the U.S. Governor Tom Wolf. https://prdpwpgovernor.pwpca.pa.gov/gov-wolf-announces-largest-government-solar-energy-commitment-in-the-u-s/
Constantino, S. M., & Weber, E. U. (2021). Decision-making under the deep uncertainty of climate change: The psychological and political agency of narratives. Current Opinion in Psychology, 42, 151–159. https://doi.org/10.1016/j.copsyc.2021.11.001
Creamer, E., Eadson, W., van Veelen, B., Pinker, A., Tingey, M., Braunholtz-Speight, T., Markantoni, M., Foden, M., & Lacey-Barnacle, M. (2018). Community energy: Entanglements of community, state, and private sector. Geography Compass, 12(7), e12378. https://doi.org/10.1111/gec3.12378
Davenport, C., Scheiber, N., & Friedman, L. (2021, March 31). Biden’s Big Bet: Tackling Climate Change Will Create Jobs, Not Kill Them. The New York Times. https://www.nytimes.com/2021/03/31/climate/biden-climate-jobs.html
Dawson, A. (2021, September 15). Lessons from the Public Power Campaign. Dissent Magazine. https://www.dissentmagazine.org/online_articles/lessons-from-the-public-power-campaign
DeBell, M., & Krosnick, J. A. (2009). Computing weights for American national election study survey data. Nes012427. Ann Arbor, MI, Palo Alto, CA: ANES Technical Report Series.
Devine-Wright, P. (2005). Beyond NIMBYism: Towards an integrated framework for understanding public perceptions of wind energy. Wind Energy, 8(2), 125–139. https://doi.org/10.1002/we.124
Devine-Wright, P. (2013). Explaining “NIMBY” Objections to a Power Line: The Role of Personal, Place Attachment and Project-Related Factors. Environment and Behavior, 45(6), 761–781. https://doi.org/10.1177/0013916512440435
Dimanchev, E. G., Paltsev, S., Yuan, M., Rothenberg, D., Tessum, C. W., Marshall, J. D., & Selin, N. E. (2019). Health co-benefits of sub-national renewable energy policy in the US. Environmental Research Letters, 14(8), 085012. https://doi.org/10.1088/1748-9326/ab31d9
Essa, E., Curtiss, K., & Dodinval, C. (2021, February). Solar Siting Authority Across the United States. University of Michigan Center for Local, State, and Urban Policy. https://closupstage.fordschool.umich.edu/research/working-papers/solar-siting-authority-across-united-states
Gampfer, R., Bernauer, T., & Kachi, A. (2014). Obtaining public support for North-South climate funding: Evidence from conjoint experiments in donor countries. Global Environmental Change, 29, 118–126. https://doi.org/10.1016/j.gloenvcha.2014.08.006
Goedkoop, F., & Devine-Wright, P. (2016). Partnership or placation? The role of trust and justice in the shared ownership of renewable energy projects. Energy Research & Social Science, 17, 135–146. https://doi.org/10.1016/j.erss.2016.04.021
Gustafson, A., Goldberg, M. H., Kotcher, J. E., Rosenthal, S. A., Maibach, E. W., Ballew, M. T., & Leiserowitz, A. (2020). Republicans and Democrats differ in why they support renewable energy. Energy Policy, 141, 111448. https://doi.org/10.1016/j.enpol.2020.111448
Hainmueller, J., Hopkins, D. J., & Yamamoto, T. (2014). Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments. Political Analysis, 22(1), 1–30. https://doi.org/10.1093/pan/mpt024
Hallan, C., & González, A. (2020). Adaptive responses to landscape changes from onshore wind energy development in the Republic of Ireland. Land Use Policy, 97, 104751. https://doi.org/10.1016/j.landusepol.2020.104751
Hazboun, S. O., & Boudet, H. S. (2021). Natural gas – friend or foe of the environment? Evaluating the framing contest over natural gas through a public opinion survey in the Pacific Northwest. Environmental Sociology, 7(4), 368–381. https://doi.org/10.1080/23251042.2021.1904535
Horiuchi, Y., Markovich, Z. D., & Yamamoto, T. (2020). Does Conjoint Analysis Mitigate Social Desirability Bias? (SSRN Scholarly Paper ID 3219323). Social Science Research Network. https://doi.org/10.2139/ssrn.3219323
Jenkins, J. D., Mayfield, E. N., Larson, E. D., Pacala, S. W., & Greig, C. (2021). Mission net-zero America: The nation-building path to a prosperous, net-zero emissions economy. Joule, 5(11), 2755–2761. https://doi.org/10.1016/j.joule.2021.10.016
Kahn, J., & Shields, L. (2020, September 2). State Approaches to Wind Facility Siting. National Conference of State Legislatures. https://www.ncsl.org/energy/state-approaches-to-wind-facility-siting
Kennedy, B., & Spencer, A. (2021, June 8). Most Americans support expanding solar and wind energy, but Republican support has dropped. Pew Research Center. https://www.pewresearch.org/fact-tank/2021/06/08/most-americans-support-expanding-solar-and-wind-energy-but-republican-support-has-dropped/
Knauf, J. (2022). Can’t buy me acceptance? Financial benefits for wind energy projects in Germany. Energy Policy, 165, 112924. https://doi.org/10.1016/j.enpol.2022.112924
Langer, K., Decker, T., & Menrad, K. (2017). Public participation in wind energy projects located in Germany: Which form of participation is the key to acceptance? Renewable Energy, 112, 63–73. https://doi.org/10.1016/j.renene.2017.05.021
Larson, E., Greig, C., Jenkins, J., Mayfield, E., Pascale, A., Zhang, C., Drossman, J., Williams, R., Pacala, S., Socolow, R., Baik, E., Birdsey, R., Duke, R., Haley, B., Leslie, E., Paustian, K., & Swan, A. (2021). Net-Zero America: Potential Pathways, Infrastructure, and Impacts [Final Report]. Princeton University.
Leppert, R. (2022). Americans continue to express mixed views about nuclear power. Pew Research Center. https://www.pewresearch.org/fact-tank/2022/03/23/americans-continue-to-express-mixed-views-about-nuclear-power/
Levri, E. P. (2019). Alternative energy in Pennsylvania in the twenty-first century. Journal of the Pennsylvania Academy of Science, 93(2), 162–166. https://doi.org/10.5325/jpennacadscie.93.2.0162
Lightsource BP. (2020). Pennsylvania Cottontail Solar Farm Project | Lightsource bp. Lightsource Bp USA. https://www.lightsourcebp.com/us/projects/cottontail-solar-farm-project/
Lim, T., Guzman, T. S., & Bowen, W. M. (2020). Rhetoric and Reality: Jobs and the Energy Provisions of the American Recovery and Reinvestment Act. Energy Policy, 137, 111182. https://doi.org/10.1016/j.enpol.2019.111182
Lynch, D. (2019, August 19). With ‘America First,’ some foreign companies in the U.S. fear Trump is putting them last. Washington Post. https://www.washingtonpost.com/business/economy/with-america-first-some-foreign-companies-in-the-us-fear-trump-is-putting-them-last/2019/08/16/cbc5b94e-b14c-11e9-951e-de024209545d_story.html
Marshall, R., & Burgess, M. G. (2022). Advancing bipartisan decarbonization policies: Lessons from state-level successes and failures. Climatic Change, 171(1), 17. https://doi.org/10.1007/s10584-022-03335-w
Mayer, A. (2019). National energy transition, local partisanship? Elite cues, community identity, and support for clean power in the United States. Energy Research & Social Science, 50, 143–150. https://doi.org/10.1016/j.erss.2018.11.020
McDermott-Levy, R., Kaktins, N., & Sattler, B. (2013). Fracking, the Environment, and Health. AJN The American Journal of Nursing, 113(6), 45–51. https://doi.org/10.1097/01.NAJ.0000431272.83277.f4
Mijin Cha, J., Stevis, D., Vachon, T. E., Price, V., & Brescia-Weiler, M. (2022). A Green New Deal for all: The centrality of a worker and community-led just transition in the US. Political Geography, 95, 102594. https://doi.org/10.1016/j.polgeo.2022.102594
Mildenberger, M., & Tingley, D. (2019). Beliefs about Climate Beliefs: The Importance of Second-Order Opinions for Climate Politics. British Journal of Political Science, 49(4), 1279–1307. https://doi.org/10.1017/S0007123417000321
Moore, S., Graff, H., Ouellet, C., Leslie, S., & Olweean, D. (2022). Can we have clean energy and grow our crops too? Solar siting on agricultural land in the United States. Energy Research & Social Science, 91, 102731. https://doi.org/10.1016/j.erss.2022.102731
Nilson, R., Hoen, B., & Rand, J. (2024). Survey of Utility-Scale Wind and Solar Developers Report. Lawrence Berkeley National Laboratory. https://emp.lbl.gov/publications/survey-utility-scale-wind-and-solar
Pascaris, A. S., Schelly, C., Burnham, L., & Pearce, J. M. (2021). Integrating solar energy with agriculture: Industry perspectives on the market, community, and socio-political dimensions of agrivoltaics. Energy Research & Social Science, 75, 102023. https://doi.org/10.1016/j.erss.2021.102023
Pianta, S., Rinscheid, A., & Weber, E. U. (2021). Carbon Capture and Storage in the United States: Perceptions, preferences, and lessons for policy. Energy Policy, 151, 112149. https://doi.org/10.1016/j.enpol.2021.112149
Roby, H., & Dibb, S. (2019). Future pathways to mainstreaming community energy. Energy Policy, 135, 111020. https://doi.org/10.1016/j.enpol.2019.111020
Schelly, C., Bessette, D., Brosemer, K., Gagnon, V., Arola, K. L., Fiss, A., Pearce, J. M., & Halvorsen, K. E. (2020). Energy policy for energy sovereignty: Can policy tools enhance energy sovereignty? Solar Energy, 205, 109–112. https://doi.org/10.1016/j.solener.2020.05.056
Sharpton, T., Lawrence, T., & Hall, M. (2020). Drivers and barriers to public acceptance of future energy sources and grid expansion in the United States. Renewable and Sustainable Energy Reviews, 126, 109826. https://doi.org/10.1016/j.rser.2020.109826
Skonieczny, A. (2018). Emotions and Political Narratives: Populism, Trump and Trade. Politics and Governance, 6(4), 62–72. https://doi.org/10.17645/pag.v6i4.1574
Spiess, T., & De Sousa, C. (2016). Barriers to Renewable Energy Development on Brownfields. Journal of Environmental Policy & Planning, 18(4), 507–534. https://doi.org/10.1080/1523908X.2016.1146986
The Associated Press. (2022, April 6). A wind energy company has pleaded guilty after killing at least 150 eagles. NPR. https://www.npr.org/2022/04/06/1091250692/esi-energy-bald-eagles
Tumlison, C., Button, E. D., Song, G., & Kester, J. (2018). What explains local policy elites’ preferences toward renewable energy/energy efficiency policy? Energy Policy, 117, 377–386. https://doi.org/10.1016/j.enpol.2018.03.016
Tyson, A., Funk, C., & Kennedy, B. (2022, March 1). Americans Largely Favor U.S. Taking Steps To Become Carbon Neutral by 2050. Pew Research Center Science & Society. https://www.pewresearch.org/science/2022/03/01/americans-largely-favor-u-s-taking-steps-to-become-carbon-neutral-by-2050/
US Department of Homeland Security & US Department of Energy. (2015). National Infrastructure Protection Plan (NIPP) Energy Sector-Specific Plan (NIPP) (p. 39). https://www.cisa.gov/sites/default/files/publications/nipp-ssp-energy-2015-508.pdf
US EIA. (2022). Electric Power Monthly. U.S. Energy Information Administration (EIA). https://www.eia.gov/electricity/monthly/epm_table_grapher.php
van der Horst, D. (2007). NIMBY or not? Exploring the relevance of location and the politics of voiced opinions in renewable energy siting controversies. Energy Policy, 35(5), 2705–2714. https://doi.org/10.1016/j.enpol.2006.12.012
Venus, T. E., Hinzmann, M., Bakken, T. H., Gerdes, H., Godinho, F. N., Hansen, B., Pinheiro, A., & Sauer, J. (2020). The public’s perception of run-of-the-river hydropower across Europe. Energy Policy, 140, 111422. https://doi.org/10.1016/j.enpol.2020.111422
Vuichard, P., Broughel, A., Wüstenhagen, R., Tabi, A., & Knauf, J. (2022). Keep it local and bird-friendly: Exploring the social acceptance of wind energy in Switzerland, Estonia, and Ukraine. Energy Research & Social Science, 88, 102508. https://doi.org/10.1016/j.erss.2022.102508
Wang, X., & Lo, K. (2021). Just transition: A conceptual review. Energy Research & Social Science, 82, 102291. https://doi.org/10.1016/j.erss.2021.102291
Warlenius, R. H., & Nettelbladt, S. (2023). Scaling up community wind energy: The relevance of autonomy and community. Energy, Sustainability and Society, 13(1), 33. https://doi.org/10.1186/s13705-023-00411-6
Wolsink, M. (2000). Wind power and the NIMBY-myth: Institutional capacity and the limited significance of public support. Renewable Energy, 21(1), 49–64. https://doi.org/10.1016/S0960-1481(99)00130-5
Wüstenhagen, R., Wolsink, M., & Bürer, M. J. (2007). Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy, 35(5), 2683–2691. https://doi.org/10.1016/j.enpol.2006.12.001
Zaretsky, N. (2018). Radiation Nation: Three Mile Island and the Political Transformation of the 1970s. Columbia University Press.
Zaunbrecher, B. S., Linzenich, A., & Ziefle, M. (2017). A mast is a mast is a mast…? Comparison of preferences for location-scenarios of electricity pylons and wind power plants using conjoint analysis. Energy Policy, 105, 429–439. https://doi.org/10.1016/j.enpol.2017.02.043

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Public and Local Policymaker Preferences for Large-Scale Energy Project Characteristics

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1.1 Characteristics of Large-Scale Energy Projects

Partisan differences in support for renewable energy

Studying energy infrastructure in Pennsylvania

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