Two Studies Offer New Insights into Low-to-Moderate Income Solar Adoption Webinar (Text Version)
This is the text version of the "Two Studies Offer New Insights into Low-To-Moderate Income Solar Adoption" webinar presented on June 11, 2020.
The webinar was hosted by the Solar Energy Evolution and Diffusion Studies program.
Harrison Dreves speaking: All right. We'll go ahead and get started. Again, thanks for joining us for this
webinar hosted by the National Renewable Energy Laboratory that presents some results
from Solar Energy Evolution and Diffusion Studies.
Today, we're going to be looking at two studies that offer new insights into lower to moderate income solar adoption. I'm going to turn it over to Ben Sigrin at NREL who's going to moderate the webinar shortly so he can introduce the topic and our speakers, but, first, a few quick housekeeping items.
The slides from this webinar will be made available a few days after the webinar. We're going to post them to the NREL SEEDS website. You can see a link there, but don't worry, you don't have to jot it down. We're also going to be sending out an email from GoToWebinar, so it'll be from the same address you got the link to join this webinar at. We'll be sending out an email from GoToWebinar probably in about a week, once those slides have posted. So just keep an eye out for that, and you'll get a link to the website so you can see the slides when they're available.
If you're having any audio issues, we recommend switching from computer to phone audio. That often solves people's problems. If problems persist, you can contact GoToWebinar technical support at the number there.
Finally, we're going to be taking questions at the end of this webinar, and we encourage anybody who wants to submit one. If at any point during the webinar you have a question or a discussion topic, feel free to submit it using the questions panel. You can see what that should look like on your screen there on the right side. Submit that at any point, and we will do our best to answer as many questions as possible at the end of the webinar.
So, with that, I'm going to hand it over to Ben Sigrin, who can give you an overview of the SEEDS II project and the work at NREL and our partnering institutions.
Solar Energy Evolution and Diffusion Studies II Overview
Ben Sigrin speaking: Thank you, Harrison, and good morning to everyone on the call. We appreciate you taking the time out of your day to listen to our presentation. So today, we'll be presenting, as Harrison mentioned, two recent studies that we've conducted to better understand drivers of historic adoption of solar by low and moderate income households.
So, this is one phase of three phases of our project. This phase is about developing models to understand historic adoption of solar for LMI households both at the individual level and at the neighborhood level, but other phases of the project—our first phase, determining the technical potential of the LMI market, that phase has completed and is available on our project website, if you haven't read the paper or listened to the webinar yet. And then our third phase of the project is all about understanding the role and sources of referrals in LMI communities. We think that referrals are pivotal for encouraging solar among LMI and non-LMI populations.
So stay tuned for that. We'll be hosting a webinar later this summer to present our results there. It'll be another dual webinar where we'll present results of our ground-breaking market experiment to test new ways of getting referrals and also developing predictive models to predict who provides referrals and why.
Why Does Low-to-Moderate Solar Matter?
So before I proceed, let me also just define what we mean by LMI. LMI is an acronym for low and moderate income, and in this study, it's defined as households that make between 0% and 80% of area median income. So that's the definition that we use. Other people may have slightly different definitions.
I also want to call out two other of our project partners that are on the call or that are presenting work today. The first is Grid Alternatives, a nonprofit that is our industry partner on this project that helped us procure most of the data that you'll see analyzed, and then also Lawrence Berkeley National Lab.
So, I think before we proceed with the presentation itself, I think it's important to ask why does LMI solar matter in the first place. Why should we separately care about adoption of solar by LMI versus non-LMI households?
So, the first thing I would say is that LMI households represent 43% of the U.S. population, and in the first phase of the project, they also represented a similar fraction of the overall US potential for rooftop solar energy. So, it's a large population, and they spend disproportionately more of their income on energy, so any bill savings from solar, any reductions in retail expenditures, would be more impactful for LMI households than non-LMI.
The second point is that it's not an exaggeration to say that solar has been disproportionately adopted by higher-income households. And so, I think that from an equity point of view, there's growing backlash against rooftop solar policies that may favor the more affluent, that may lead to higher adoption rates by the affluent as opposed to less affluent. And particularly, we want to make sure that we don't encourage rate payer cross-subsidization. So we think it's important that all households have access to rooftop solar, not just the most affluent.
And then third is our country already has several policies that are meant to address energy poverty and reduce household expenditures on energy, so the role of solar in that policy mixture is still being considered, but there certainly is increasing interest in policy interventions to encourage LMI adoption and to more broadly create equitable access. So if we don't understand the drivers of LMI solar adoption, the technical possibility, the factors that lead to it being adopted more effectively than not, then those policy measures could fall on their face. So we do need research to guide policy and to understand how to make policy more effective. Next slide, please.
All right. So, we're about to proceed into our presentations. So, we have two really excellent academics on the call today. They're at the forefront of their files. So first, Dr. Kim Wolske. She's a research associate and assistant professor at the Harris School of Public Policy at the University of Chicago, and also a research fellow with EPIC, which is the Energy Policy Institute at Chicago.
Dr. Wolske's research draws on the fields of environmental, social, and cognitive psychology to examine the behavioral dimensions of energy production and use. And she's particularly interested in understanding the motivations and barriers associated with home energy investments, and has spent the last seven years partnering with NREL and myself to investigate strategies for accelerating consumer demand for rooftop residential solar.
Our second presenter, Dr. Tony Reames, is an assistant professor at the University
of Michigan School for Environment and Sustainability, and he also directs the Urban
Energy Justice Lab. His research focuses on the emerging fields of energy justice,
investigating fair and equitable access to affordable, reliable, efficient, and clean
energy, and also seeks to understand the production and persistence of spatial, racial,
socioeconomic residential energy disparities. He has a PhD in public administration, a master's in energy management, and a BS in civil engineering. And Dr. Reames is also a licensed professional engineer and a U.S. Army veteran.
So, thank you for joining us. Our first presenter is Dr. Wolske. Dr. Wolske, the floor is yours.
Kim Wolske speaking: Thank you. Let me just get my slides up and going. Okay. Does that look good? I'm going to assume so.
Ben Sigrin speaking: Yep, you're good.
Profiles of High-Income and Low-Income U.S. Solar Adopters
Kim Wolske speaking: Great. Thanks. And thanks, Ben, and thanks to all of you for taking time to join us this afternoon.
So, I'm going to share a comparative analysis of high income and low income solar adopters, and the goal of this work was really to understand whether the underlying psychology of the decision to go solar is the same for these two different groups.
Rapid Growth in U.S. Residential Photovoltaics
And Ben already gave away a lot of what I was going to say in terms of the motivation for this. As he noted, most solar adoption is concentrated in higher income households, and there's really a missed opportunity here. He pointed out it's 42 percent of all LMI – or 42 percent of solar potential on any type of housing is LMI, and it's 31 percent of owner occupied rooftop potential is on LMI households.
And in response to these growing sort of equity concerns, whether there's equitable access to solar, there's of course renewed interest in how we expand solar to this population, and that really raises the question, can we be sure that we can apply the same theory of change of what we know about getting higher income households to adopt, can we apply that to lower income households as well?
Why Do People Go Solar?
There have been – I'm sorry. I'm just trying to get my slides to advance. Here we go. So much of what we know about solar adoption has come from studying the people who got it first, who tend to be higher income households who may be less risk averse. And if we look at the literature, what we know is that some of the earliest adopters, they got solar because they have strong environmental values, and they felt it was the right thing to do. We're of course seeing growing interest in solar as a way for people to save money and lower the cost of energy, and there's also growing research trying to understand sort of social contagion. What's the effect of being around others who have solar panels, seeing solar as this new, innovative technology that people are interested in adopting.
So, we have these different theories of why people consider solar, and I as part of a prior SEEDS project with some colleagues kind of came up with an integrative framework for explaining what makes someone interested in solar. And I will spare you all of the academic theory language, but the main idea here is that our research suggests that what is most determinant of whether someone is interested in or considers solar is their specific beliefs about the technology, what do they see as the benefits, what do they see as potential risks or what are concerns they have? Do they perceive that others around them would support their decision to get solar? And then this last idea, perceived behavioral control, is this notion of do you feel capable of making this investment, either in terms of your own financial resources, or having to go investigate who an appropriate installer is?
And if you're wondering what all these little letters are, these refer to those theories that were on the prior slide. So, if you're interested and these slides are posted, you can go back to this.
So, we suspect that these beliefs have the strongest effect or influence on the decision to go solar, and these beliefs can also be influenced by what we call someone's personal disposition. So, these are sort of traits of a person. One of these in the literature is called pro-environmental norm, but it's basically this idea that you feel a sense of moral obligation to act for the benefit of the environment. And there is research showing that the more you have this pro-environmental norm, the more beneficial you think solar is, not only to the environment, but to you personally. There can also be people, though, who are interested in solar because it is an innovative, cool technology, and likewise, the more innovative someone is, the more likely they are to have positive perceptions of the technology.
And then finally, there can be these external influences, whether there's actually an incentive program, or how easy is it for you to observe what others around you are doing. Do you see that other people have solar? Or are you exposed to different market? So there's sort of these different buckets of factors that can influence the decision to consider or get solar, your dispositions, these external factors, and your very specific beliefs.
And the question I'm interested in understanding is if we look at high income households who have adopted solar, and low-income households who have adopted solar, do they have similar profiles on these constructs?
Theory Would Suggest No Difference Between Low- and High-Income Household Influences
The theory would actually suggest that they shouldn't. If you're familiar with the idea of diffusion of innovation, this idea that when there is a new innovation or technology, the first people who adopt are innovators and early adopters, they're more willing to take on risk, they're more independent in their decision-making, and if a technology is still pretty new and there aren't subsidies, we can expect that only this small segment of the population is going to be attracted to it.
But as soon as we introduce a subsidy, and in the case of low income solar, a subsidy that may entirely cover the cost of the system, we should perhaps expect this to be different, because now it's changing sort of the internal calculus of how you view solar, and that it may seem more beneficial, and the risks may seem lower because you're not having to pay the cost.
So, this is really what I'm going to share with you today, is a comparison of what do these two groups of adopters look like. We should – our expectations going into this is that they would look quite different, and I think this is a common assumption among a lot of program managers and policy makers. Well, if we're giving something away at no cost, this should be attractive to a really wide swathe of the population.
Sample: Two Survey Data Sets
So that's the question we're seeking to answer, and in terms of how we did this, Ben and I had actually worked on a prior project where we surveyed California solar adopters in early 2015. So, from that data set, I'm focusing on about 700 people who all got their solar systems from the same installer, and over 80 percent of them have either a lease or a power purchase agreement. And to understand then how low-income solar adopters might compare, this is where we worked with Grid Alternatives, who Ben mentioned. If you're not familiar, they are a nonprofit headquartered in California, where they provide solar at no cost to qualifying low to moderate income homes.
So, this survey went out in late 2017. You can see we also offered this in Spanish, so it's a little bit of a different demographic. And let me say here that when – so both groups got surveys, and what I'm going to show you are a comparison of means on different measures. Any time you're comparing two wildly different populations, you have to make sure that people interpret the survey questions in the same way. So, for example, it could be that maybe for some reason people in the higher income sample are less likely on a ten point scale to use the extreme points of one and ten, whereas maybe the other population isn't. I won't go into this, but let me just say I did a bunch of analyses to make sure we could be confident in comparing the means of these two groups.
Sample: Survey Demographic Profile
So, to give you a little sense of the demographic profile, not surprisingly, the average income for the higher income group is quite a bit higher than the low-income group. The higher income adopters have slightly smaller households, about three people versus four, and they have fewer children at home. The respondents tended to be male, and they were also slightly older than the low-income survey respondents, who were predominantly female. And we also see that the high-income group had more education than the low income group.
And what I want to point out here is I think there's often a mistake, I'll call it, where we tend to focus on these differences when we're thinking about different income populations. And what I hope you will take from the end of this is that this is only a small part of the story, and that there are other aspects of these populations that are actually much more similar than we might expect.
So, I've just given the – let the cat out of the bag. Contrary to what we expected going in and what theory would predict, both sets of these adopters are actually much more alike on these psychological variables than they aren't.
Survey Respondent Motivations
So, the first thing that I looked at were their reported motivations for going solar. So, each of the things you see here on the bottom, these are actually composite measures from different Likert scales. So, people are rating how important it was for them to try to save money, how that factored into their decision to go solar.
And what we see here is that the two adopter groups have a similar pattern of endorsement across these measures. So, both groups were most likely to endorse that they wanted to get solar in order to save money, and they really sort of tapped out at the end of the scale. There's no difference between them.
The second highest rated motivation was this desire to use renewable energy technology and to demonstrate it to their community. And then there was less endorsement for wanting to enhance their home or improve their home value in some way.
So, in looking at this chart, the first thing that should strike you is that like the overall pattern is very similar in terms of which is the – has the highest mean within each adopter group, but then it's also interesting that for enhancing their home and using green technology, the low-income group actually has a higher mean. And we will see this pattern reemerge.
Survey Respondent Concerns
The survey also asked them about their concerns about getting solar, so long-term risks included concerns about the overall cost and maintenance. This idea of PV could detract from the home was concerns about how it would look from curbside or whether it would damage the roof in some way. These are measures where I'm less confident that the two groups were interpreting the questions in the same way. That's why I don't have confidence intervals here. And it could just be that for the low-income population, they have less resources available if something goes wrong with their system, and they may be thinking about risk differently. So, we again still seem that same overall pattern, but we can't be as confident in comparing the means of these groups.
Survey Respondent Personal Dispositions
And then I looked at those personal dispositions, which, again, this idea of pro-environmental norms, how much do you feel a sense of moral obligation to act on the benefit of the environment, we see here it's moderately to highly endorsed by both groups, but even more so for the low-income population. And then we also have two measures of innovativeness. And the first is this idea of consumer novelty-seeking, which is basically are you someone who goes out and seeks new technology? And do you look for information on new technology? And this has been shown to be correlated with stronger intentions to pursue solar. It's also highly correlated with being an early adopter of alternative fuel vehicles. And it's pretty interesting. We actually see that the low income adopter group scores higher on this.
There's another form of innovativeness that measures how much are you an independent thinker. Are you someone that decides all on your own to go get solar? Or are you someone who really talks to all of your friends and family and seeks the opinions of others? Typically, innovative people are more independent in their judgment thinking. And this is where we finally see the pattern break, that the high-income adopters actually score higher on this than the low-income adopters. And this may speak to – this – the lower income group perceiving more risk in this decision.
Survey Respondent Observability
And we had some other measures on the survey that also tried to tap into the role of social influence in their decision, and we asked all of the respondents, how many solar adopters did you know prior to getting solar to yourself – getting solar for yourself. We find no difference between the groups. But when we asked them how frequently had you heard people talk about solar, the low-income group reported hearing about solar more frequently. Likewise, they saw solar more often than the lower income group. And there was sort of a list of things of what sort of triggered you to consider solar, and we found that about 40 percent of the low-income group said that talking to someone prompted them, compared to about 31 percent in the high-income group. So there seems to be a slightly greater reliance on looking to others for their opinions on solar in the low to moderate income group.
Survey Findings Summary
So just to sort of summarize across all these different findings I've shared, we find that saving money is the primary motivation for LMI and higher income households, and there's maybe some evidence that the LMI group is slightly more risk averse, but that's really something where we need more research. I think the most important takeaway from this is that even though people may be motivated to save money, even in the case of LMI adopters who were getting their systems at no cost, PV may still be most attractive to the people who are more innovative and who care about the environment. So that slide I showed you at the beginning that showed the people separated into different groups, we don't find evidence in support of that. We're basically finding that the profiles of low to moderate income adopters are very similar to the profiles of early higher income adopters.
And there's also then evidence that we should especially pay attention to the role of social networks in encouraging LMI solar adoption, and it may be that these groups are really important to sort of alleviating their concerns and perceived risks.
How Do We Explain Higher Ratings?
I will also address sort of this interesting finding that the low to moderate income adopters tended to have higher means on a lot of measures. And I told you up front that there were more male respondents in the high-income group and more female respondents in the low-income group, and there's a slight difference in average age. So, I re-ran analyses to – controlling for all of this, and the higher means still persisted. But I did find one interesting association in explaining some of the more environmental attitudes, and that is when you divide out the income groups by gender, there is a difference in how environmental they are.
So, if you look – these are two different measures measuring their pro-environmental norm and their desire to use green technology. And if you look just within the low to moderate income group, it doesn't matter what your gender is, you're still ranking high on these measures of what I'll call greenness. But it's different in the high-income group. You can see that high-income males are less green than their female counterparts, but also less green than either low to moderate income men or women. So, it could be that what we're picking up on really has to do with a difference in males. And we note in the low to moderate income survey that a majority of these respondents were Latino. We don't have a race or ethnicity measure from the high-income survey, but we know from other research that solar adoption in California tends to be correlated with being white. And Yale has done a lot of interesting research showing that Latino populations are more pro-environmental. So, this could be another factor that drives these subtle differences between these two groups.
So, let me just close by saying I am not making any claims here about what causes someone to go solar. This is really just a correlational analysis and a first cut at trying to understand how if we're going to try to reach the LMI population, what do we need to know about them to market programs effectively. Of course, these people already had solar, so in both populations, the survey may be capturing how they feel as a result of getting it. So, we really need more work to sort of tease these things apart and to try to understand really what are the causal mechanisms for getting solar. And I also want to recognize, when we did this study, because we were pairing with an existing survey, we were limited in the questions we could answer or ask, rather, and it may be that there are other motivations and barriers that are really unique to LMI households that we need to account for.
So, I just want to give a shout out to the other partners, including some who are from the team who are not here. And I also see that my former research assistant Andrew Bray is on the line. He has gone on to do bigger and better things, but Andrew has – was instrumental in handling all of the survey data, so I want to shout out to him. And I'll hand it over to you, Tony. Ben Sigrin speaking: Thank you, Kim. Let's – we'll now transition to our second talk by Dr. Reames. Dr. Reames, the floor is yours.
Distributional Disparities in Solar Potential and Penetration in Four U.S. Cities
Tony Reames speaking: Thank you. I hope everybody can hear me. I just switched to a different Wi-Fi. Okay. All right.
So today, what I want to talk about is kind of another part of this study that we chose to look at four cities to understand distributional disparities in solar potential and penetration, taking advantage of several national websites that now provide us data on potential and penetration.
So, this paper just came out last week, and so we will provide the link to the paper after this talk, but it was published in Energy Research & Social Science, where Kim also published her paper.
What Is Energy Justice?
Really quickly, I want to talk about this idea of energy justice. We can relate it to the UN Sustainable Development Goals, goal number seven, to ensure access to affordable, reliable, sustainable, and modern energy for all, and also to a paper by a colleague of mine at Columbia University, Diana Hernandez, that issued this call for energy justice and this idea or notion that energy is a basic right. What are those four rights? And so it's the right to a healthy, sustainable energy production, the right to the best available infrastructure, the right to energy that is affordable, and the right to energy that is uninterrupted. And so again, use this idea to frame the rest of this conversation.
The State of U.S. Energy Security
And this is important in the US, because the most recent residential energy consumption survey from the Energy Information Administration highlighted that one in three US households faced some challenging meeting basic energy needs. And so the energy insecurity measures the survey looked at was receiving a disconnect notice, keeping your home at an unhealthy temperature, or reducing or forgoing basic necessities because you're trying to pay your energy bill. And so you can see across those three factors you have anywhere from 15 to 20 percent of households reporting that they've experienced that energy insecurity either almost every month, some months, or one to two months throughout the year.
So again, we have an affordability problem. We have an understanding of where LMI households are when it comes to adoption. But we want to see this idea of energy equity and justice.
Solar Adoption Disparities
And so although the cost of solar continues to decline, we know that adoption rate by LMI households and households of color are growing at a much slower rate. In some studies, households earning greater than $45,000.00 a year represent 90 percent of solar installations, but roughly 65 percent of the population. Those earning less than $45K are about 13 percent of PV installations, or about half of their representation in these two different studies.
And then a study from 2019 showed that majority black and Hispanic communities had 69 percent and 30 percent respectively less solar installed when compared to white majority communities, which had 21 percent more solar when you compare those to census tracts that had no racial or ethnic majority.
And so in response to the solar disparity, we see states and local governments creating programs and policies that are focused on solar adoption parity and focusing primarily on LMI households. But some policies also include environmental justice communities. I'm thinking about those that are overburdened by pollution, majority minority, and high poverty.
One of the studies in the SEEDS project that Ben mentioned is the Replica study, which was also used here, that found that a majority of potential for rooftop residential solar is on single family rooftop, so about 68 percent of all solar suitable rooftops are single family, and of that, 37 percent are occupied by LMI households, either owner occupied or renter occupied.
Solar Equity Policies
And so we chose to identify policies, states, and cities that were along the spectrum of solar equity investment. And so we started with California, which is one of the early states that included some type of solar equity program. So, in 2006, California's Solar Initiative created the SASH program, Solar – Single-Family Affordable Solar Home program, which launched in 2009, and this is for the state's customers who are in investor-owned utilities.
In Washington, DC, they passed a renewable portfolio expansion in 2016, which established another Solar For All program, and the goal of that program is to provide solar to 100,000 low income households and to reduce their energy bills by 50 percent by That program officially launched in 2017.
And in Illinois, although they had a Solar For All program since 2007, it was fully funded at about $750 million in 2016 in the Future Energy Jobs Act. And for that program, one of the goals, when I talked about including environmental justice communities, is that 25 percent of the incentives in the Solar For All program go to environmental justice communities. And so this is the newest Solar For All program, and so the analysis of Chicago is trying to set a baseline for solar potential and penetration.
So, the study has three research questions. First, how are spatial distributions of rooftop potential and penetration similar and different across cities? How is rooftop penetration distributed across non-LMI communities and LMI communities in different cities? And how do the relationships between penetration and local socioeconomic and demographic characteristics vary, characteristics that are identified sometimes as barriers to adoption.
Case Study Cities
And so just to give you kind of an overview of the four case study cities, we chose Riverside and San Bernardino because they're located in the same metro in California, but they don't both – or citizens don't both have access to the SASH low income program. And so Riverside operates its own utility, while San Bernardino residents are in one of the investor-owned utilities and can participate in the SASH program. And again, DC and Chicago are at different stages of their low-income solar programs, and we wanted to have a diversity of cities in size, in non-white population, English proficiency, and things of that nature.
So, the data. Again, this study allows us to pull together different data sets that kind of look at national potential estimated by NREL and the Technical Potential Report, a new study by Stanford called Deep Solar, and then using census data for socioeconomic and demographic characteristics.
So, the first data set if the Replica data set, again, from NREL, that allows us to understand rooftop potential across the country, with a special emphasis on LMI potential, and it's based off rooftops that are considered solar suitable, determined by shading, azimuth, tilt, and the square area.
So, Stanford's Deep Solar is a machine learning framework that was recently released based on data from 2015. And then we also use the census for the demographic data. Now the Deep Solar data allows us to look at solar penetration.
And so the study calculates four variables. Total rooftop potential: this is the proportion of single-family rooftops that are estimated as solar suitable by the NREL study. LMI rooftop potential: this is isolating LMI rooftops and trying to identify what proportion of just LMI rooftops are solar suitable. LMI market share is to understand within a census tract what percentage of the solar suitable roofs are occupied by LMI households. And then total rooftop penetration is looking at the total number of suitable solar rooftops and what proportion of those are estimated to have solar from the Deep Solar study.
And so you can see how those four variables vary across the cities. The total rooftop potential and LMI rooftop potential are almost similar across the cities. Where you see some difference is when you think about the market share, what proportion of solar-suitable roofs are LMI, and you can see the total penetration across the four cities, ranging from 12 percent in DC to .3 percent in Chicago, and pretty similar in Riverside and San Bernardino.
Study Spatial Distributions
So, the next three slides, we'll kind of look at the spatial distribution of some of these characteristics across the four cities. Again, San Bernardino and Riverside are very close to each other, in the same metropolitan area, and so you can see Riverside on the bottom and San Bernardino on the top. And so this first panel looks at an estimate of total rooftop potential. So, the darker shaded areas are where you have a greater proportion of households that are estimated as being solar suitable. The middle panel looks at the LMI market share, and so what proportion of the solar suitable households are occupied by LMI households. And then the final panel looks at penetration, and so where do we see the greatest penetration of rooftop solar?
And these maps allow you to see that necessarily where you have greater LMI market share, so more of the homes are occupied by LMI households, does not correlate with where you see the penetration, and sometimes does not correlate with where you see the potential.
Very similar in Washington, DC. You can see where potential and market share might actually overlap, as well as where the penetration is occurring. And then finally in Chicago, you can see a concentration of areas of really high penetration or really high LMI market share, which are totally different from where you see high concentrations of solar penetration.
Relationship Between Market Share and Rooftop Penetration
So next, we wanted to understand the relationship between LMI market share, so where you have a great proportion of households that are solar suitable, but occupied by LMI households, and this rooftop penetration, so this penetration occurring differently across LMI and non-LMI communities.
And so what the graph on the right shows us is that in Riverside and San Bernardino, average penetrations reach near 15 percent in some census tracts, and then the lowest market share quintiles in DC, you can see almost 20 percent in some areas.
The mean rooftop penetration in Chicago is relatively low when you compare that to all the other three cities. So, some census tracts reached about an average of 3.2 percent, and that was statistically higher than the really high LMI market share census tracts.
One thing we wanted to point out when it came to Riverside and San Bernardino is that although Riverside households did participate in SASH and Riverside households are not able to, you would expect to see a greater share of LMI adoption in San Bernardino. And while it's not overwhelming, we can see that if you look at the last four quintiles, so quintiles two, three, four, and five in San Bernardino, penetration rates are actually higher in those census tracts, not statistically higher, but they are higher when you compare that to Riverside. And so there could be some indication that being a part of the SASH program does allow for more low-income households to participate in solar.
So, because we know that income is just one barrier, we thought it would be interesting to look at how do relationships with different socioeconomic and demographic characteristics vary across the four cities, and how do they show up and manifest differently in those cities? And so the table at the right allows us to look at the relationship between penetration rates and various socioeconomic and demographic characteristics.
What we see in Riverside is that the significant variables, there were three of them, so it's percentage of households without internet increases in Riverside, we saw lower penetration rates in those census tracts. Areas with older housing, we saw lower rates of penetration. And there was a statistically significant relationship between home value and penetration, a positive relationship, and so maybe those census tracts are the ones being targeted by solar installers.
In San Bernardino, where you had higher LMI market share, there was a lower level of penetration in those census tracts, as well as where more residents spoke English or did not have high English proficiency.
_____ where you had a greater number of the population without a high school diploma, older population, and non-white population, we saw increased penetration. Again, I think Kim mentioned this, is that there was a higher Hispanic population in the Inland Empire area where San Bernardino is located, and so that could be the reason for that.
There were three variables in DC that all had negative relationships with penetration. And so in areas where you even had more homes that were solar suitable, you saw less penetration in those areas, as well as where there were more homes that were LMI. And when areas where the population was older, you saw less penetration.
In Chicago, there were two variables. _____ potential went up, again, penetration was down, and homes that were newer were more likely to be in areas with higher solar penetration.
And so just to kind of bring these thoughts together, solar potential not only differs across cities, but also within communities in a city. In some areas where LMI households represented a larger share of the potential, we know that there should be greater penetration in those areas, but there are other issues, like roof quality, that must be considered.
As expected, penetration rates varied greatly across cities, and still remains relatively low, when we think about the estimated potential by NREL.
This study also highlights that in some cities there's this mismatch between potential penetration, and so higher rooftop potential did not necessarily translate into higher penetration, like in DC and Chicago, especially when that higher potential was located in majority LMI communities.
And so what we really want to highlight is that beyond just income as a barrier, that there are some other socioeconomic and demographic characteristics, such as race and ethnicity, limited English proficiency, the age of the housing stock, and even internet access that could be associated with increased or reduced rooftop penetration.
And so only a fraction of the LMI market has been tapped, so there remains some great potential for expanding rooftop solar to LMI households and communities, and the growth of policies that support that type of expansion. So, we must recognize that there are distribution disparities in both potential and penetration, and we take into account the unique socioeconomic and demographic characteristics, this will allow us to more holistically understand the LMI solar market that we want to reach. This knowledge can help with better policy design and better program implementation.
So, thank you. That's all I have for you. And I look forward to the Q&A.
Questions and Answers
Ben Sigrin speaking: Thank you, Tony, so much. So, it's a fascinating talk. And thank you also to Kim for her fascinating talk as well. To our audience, if you have any questions for our presenters about their talks or about LMI solar more generally, please do enter them either in the chat box, or there's a specific question box.
And while we're waiting for some of these questions to roll in, I'll just pose one of my own first to Tony, and then the same question to Kim. Tony, was there anything about this research that surprised you? Or what do you consider perhaps the most surprising result of your paper?
Tony Reames speaking: Yeah, I think a couple of things did jump out at me. I was really shocked at the higher rate of adoption or penetration in DC compared to the other cities, and after doing some additional digging, noticed that DC had some previous examples of solar programs, and some that were actually focused on increasing low income solar.
I think another thing that jumped out at me was that a lot of people say you don't see low income solar because there's not a lot of potential, and I think the Replica study demonstrated that there is potential, rooftop potential in low income communities, and how potential and penetration were not always positively or positively correlated. And so just because an area has high potential, whether LMI or not LMI, does not mean you'll see greater rooftop penetration in that area.
Kim Wolske speaking: And then for my study, I would say, I mean, this was kind of the theme of the presentation, but in general, it was just surprising to see that low to moderate income adopters were so similar to higher income adopters, and then notably, that they had these stronger pro-environmental trends, and then also at least were more innovative in terms of wanting to seek out new technology. I don't think that's something we would have expected at all, and again, I think this really speaks to the takeaway message, that we shouldn't make assumptions about what people's underlying motivations are just based on different demographic profiles that we have of them.
Ben Sigrin speaking: Yes. All right. We've had several questions rolling in. I'm not sure we'll be able to address all of them, but I do promise that we will follow up, let you know, for those questions we don't get to on this call.
Okay, so I think the first question is for Tony. Tony, do we have any empirical data that shows how LMI programs – LMI solar programs have actually reduced or relieved utility bills? So, do we have any best case examples of the degree to which previous programs \ have alleviated energy poverty?
Tony Reames speaking: That's a really great question, and I don't have any right off the top of my head, but I'm sure that there are studies out there. And I know we've had conversations with _____ as we've been working on this project about being able to understand how access to solar through the SASH program has benefited households. I know DC is also tracking that in their Solar For All program, because one of their goals is to reduce household energy burdens by 50 percent. And so they're wrapping up their first year, I think, of the program rollout, and so there should be data coming out from that as well.
Ben Sigrin speaking: Great. Great. Kim, your study was primarily focused on solar in single family homes, but do you have any intuition on how your results may translate to adoption of community solar by LMI populations?
Kim Wolske speaking: I don't want to be too speculative. I also see there's a question, too, about thinking about other countries, like Nepal, what are lessons that transfer. I guess my intuition is that to the extent that LMI households have any say in what's happening – well, to the extent that LMI households are offered an opportunity to participate in community solar, I would expect that there would be some perhaps similar trends, that it will be most appealing to people who already have some interest in that technology in addition to the prospect of it saving them money.
And then to this question I see about how do we think about solar adoption in other contexts, especially a developing country, I think that's where we have to think about how solar fits in with their existing practices. One of the ideas from the theory of diffusion of innovations is that a new innovation or technology really has to be compatible with how you already do things, and so if it seems like too far of a stretch from the current routines and habits that people have, or if it imposes some sort of constraint, it may be – people may be less open to it than they might otherwise.
Ben Sigrin speaking: Great. Yeah. Tony, feel free to jump in if there's questions you particularly want to answer. So, another question came in from Connor Willis. Dr. Reames, your data focuses on single family homes, so would your hunch be similar for apartments as well, particularly with the Cities of Chicago and Washington, DC, where those are obviously cities that have a high apartment percentage, right?
Tony Reames speaking: Yeah. Thank you for that question, Connor, and Ben, you might jump in here, also, but thinking about the offset of the number of units in an apartment building, I know some property owners have thought about adding solar as a way to offset energy for common spaces, and using that as a way to reduce costs for – particularly in Chicago, where you have some affordable housing, and trying to use that as a way to reduce the overall cost for tenants.
I can't remember off the top of my head, Ben, what our – what the estimates were for rental apartments for multi-family housing, but there is some significant potential on multi-family rooftops, but just thinking about what you could actually offset with the limited roof space is probably the biggest issue.
Ben Sigrin speaking: Yeah, just to comment on that, because we did look into that in the Rooftop Technical Potential Study. So, I don't remember the statistics exactly, but I want to say it's about a third of residential rooftop space is on multi-family buildings, and certainly willing to be corrected if I'm quoting that incorrectly.
But I think the other thing that's interesting about multi-family is that per capita, energy consumption tends to be lower in multi-family buildings. So, it's not only a significant segment in terms of technical potential, but also you can offset a higher rate – a higher fraction of energy consumption on multi-family buildings by virtue of lower per capita consumption levels.
Okay, seeing a lot of questions here. Want to make sure that everyone's voice is heard. I'm going to jump in and ask one of my own editorial questions to both researchers. So, in your opinion, are there any aspects of LMI solar where you see that there is good research, there is some type of literature there, but that it's perhaps misunderstood by the public, or the public may consider a topic to be more uncertain than the research indicates? This is a very open-ended question, but do you – to both researchers, do you see any common misconceptions in the general public about LMI solar or energy justice more broadly?
Tony Reames speaking: I'll take a first stab at – I think one of the misconceptions is that one, it's too expensive to solarize low income households. There's also this misconception of connecting energy efficiency and renewable energy and how that could actually improve the lives of low-income households, this idea that there is no potential in low income communities.
And again, I think what this study kind of made me think about is how we can be more comprehensive in improving quality of life and housing stock in low income communities, where you combine energy efficiency, combine solar, which could also lead to improved or brand new roofs. And so again, you fix a house and prepare that for the next 20 years, and so how can we be strategic in states that have these types of programs, as well as their low-income energy efficiency programs, and what the role of utilities and solar installers – just, again, being more comprehensive in the rollout of any of these programs or policies.
And so I think that's what really stuck out to me as I kind of look at this across four different cities.
Kim Wolske speaking: I don't know that I have much to add. Tony is much more the expert in the energy justice space than I am. But I think a general lesson I have both from this research and solar research and energy behavior research in general is just for us to not think of income as this single variable that we often in academic studies just control for, and we kind of treat it a little too unidimensionally, that really, there are different segments of the population, and we really need to understand those different segments, even within the LMI population, rather than assuming that they're all the same.
Ben Sigrin speaking: Yeah. Thank you. Thank you. Good point. Well, we're now at the end of our hour, and both of our presenters have conflicts, so we will need to end. So thank you all for attending. I'd just like to make a couple of reminds, that one, we will be shortly sending out recordings and the PowerPoints of these presentations. Some people have asked for questions – for the links to the papers themselves, and we will provide those as well.
And I also wanted to say that there was an anonymous request for any individuals on the call today that are interested in collaborating more on LMI solar topics and developing case studies around the most successful efforts to bring solar to LMI customers. So, if you are interested in collaborating either with the researchers on this call or the general population on this call, please email us afterwards, and we'll try to connect people so that there can be collaboration going on.
Thank you all and have a great day. Take care.