By Joe Rand and Ben Hoen
Solar power is blazing hot in a growing number of communities across the U.S. And nowhere is it hotter than in sunny California. California is home to two out of five customer-owned solar systems in the U.S.
As solar panels become common features on homes, they are becoming part of the process of buying and selling real estate.
How does solar power affect home sales?
Research from the Berkeley Lab, Elevate Energy and the Center for Sustainable Energy shows that buyers think solar is a desirable feature, but that they, realtors and appraisers need more help to find and value solar homes.
California is by far the U.S. leader in solar on homes. The Golden State has bountiful sunshine, historically strong state incentives and some of the highest electricity rates in the country. Homeowners in the hot Central Valley can see summertime bills soaring for air conditioning and pool pumps, making solar a very attractive option.
Back in 2004, California Gov. Arnold Schwarzenegger set a goal of 1 million solar roofs by 2018, leading to the creation of the $3.3 billion Go Solar California! Campaign. Progress has been outstanding, with more than 537,000 homes, businesses, schools and farms sporting solar panels, according to data from state agencies.
That much solar means that solar homes are becoming common in some neighborhoods.
To find out how common, we worked with the Center for Sustainable Energy (CSE) to analyze solar homes by zip code and compared that with the number of single family homes in those same zips.
We found that San Diego County is an especially hot spot for solar in California, with 21 of the top 50 zip codes in the state. CSE estimates that San Diego County has 76,239 solar homes as of April of this year—that's one out of eight single family homes.
Top 10 California Zip Codes by Percent of Homes with Solar
Zip codes are limited to those with more than 5,000 single-family homes, in the service territories of Pacific Gas & Electric, Southern California Edison, San Diego Gas & Electric and Los Angeles Department of Waterand Power. Data as of April 30.CPUC, LADWP, U.S. Census
And some neighborhoods have much more. Scripps Ranch, on the north side of town, is 26 percent solar, according to CSE, making it the most solar-saturated zip code in the state. Six zip codes in San Diego county exceed 20 percent. (See an interactive database below of the top 50 solar home zip codes in California).
And as the number of solar homes increases, more solar homes are entering the real estate market.
"We've seen a pretty substantial increase in solar homes sales over the past few years," said J. Daniel Geddis of One Mission Realty in San Diego.
He expects solar home sales to increase over time, due to the time lag between when solar is installed and when the house may be sold. "When people put solar on or do a big improvement they don't sell their house right away," he points out.
High concentrations of solar homes in a neighborhood means that home buyers, realtors and appraisers are dealing with them every day.
Yet the standard tool for finding homes on the market, the Multiple Listing Service or MLS, typically doesn't include information on solar power.
"The average buyer is becoming more educated, but a lot of education still needs to happen," Geddis said. "They see solar panels and think 'that's great' but they don't think about whether it's leased or owned, how much they put out or how old they are."
"The biggest problem is getting information out to buyers as well as to real estate agents, since not all agents understand it either," he added.
Berkeley Lab is working with Elevate Energy and a team of experts from the real estate, appraisal and MLS communities to enable agents to add details about solar systems to MLS databases across the country. This will increase transparency and make it easier for shoppers, realtors and appraisers to find solar homes and properly value solar as a feature.
And solar does indeed have value. A series of reports by Berkeley Lab, including Selling Into The Sun and Appraising into The Sun, have found that solar power that is owned by the homeowner can increase the sales price of homes by an average of $4 per watt or $15,000 for a typical system. Premiums are dependent on the size and age of the solar system, the prevailing price of electricity and the "replacement" cost of similarly sized system in the neighborhood.
Many solar systems are not owned by the homeowner, but rather are owned by a third party, which installs it on the homeowner's roof and leases the system back to the homeowner. This third-party arrangement has the potential to complicate sales, but a recent qualitative survey in San Diego led by Berkeley Lab found that sales of homes with leased systems went smoothly with little to no additional effect on home values.
Geddis thinks ownership makes for an easier sale. "The new owner gets an instant benefit without paying for a loan payment or lease," he said. "With the right marketing, that tends to speed up the time on market and usually demands a higher value."
Solar adds to what he calls "the HGTV effect," after the Home and Garden TV network. "A lot of buyers these days want a move-in ready house," he said. "Solar panels are a bright shiny object—a cool new feature, something the neighbors might not have. It compares to a new remodeled kitchen."
And the savings on the utility bill also helps. "Buyers often don't factor in the cost of living in the home, but solar gives them something to think about," he pointed out.
Experience has shown that solar is a good investment, and is sought after by home buyers. Incorporating it into the standard process of home buying will help highlight and capture that value and make it easier for buyers and sellers to get together.
The U.S. Department of Energy's SunShot Initiative is putting a spotlight on issues around solar and real estate. See research, graphics and more here.
The authors are with the Electricity Markets and Policy Group at Berkeley Lab, which conducts technical, economic and policy analysis of energy topics in the U.S. electricity sector. This article was written to highlight work the Berkeley Lab has done for the Department of Energy's SunShot Initiative on solar and real estate. SunShot is a national collaborative effort to make solar energy cost-competitive with other forms of electricity by the end of the decade.
A rare yellow penguin has been photographed for what is believed to be the first time.
- World-Renowned Photographer Documents Most Remote ... ›
- This Penguin Colony Has Fallen by 77% on Antarctic Islands ... ›
EcoWatch Daily Newsletter
By Stuart Braun
We spend 90% of our time in the buildings where we live and work, shop and conduct business, in the structures that keep us warm in winter and cool in summer.
But immense energy is required to source and manufacture building materials, to power construction sites, to maintain and renew the built environment. In 2019, building operations and construction activities together accounted for 38% of global energy-related CO2 emissions, the highest level ever recorded.
- Could IKEA's New Tiny House Help Fight the Climate Crisis ... ›
- Los Angeles City-Owned Buildings to Go 100% Carbon Free ... ›
- New Jersey Will Be First State to Require Building Permits to ... ›
By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.