
In the past, I have compared big, polluting fossil fuel companies to zombies. Now I feel bad. Upon reflection, I believe I may have been a little unfair—to zombies.
You might not like zombies, but you can't really blame them for being that way. It's not like they chose to join the walking dead. In a way, zombies are victims. You can't say the same for fossil fuel corporations and big utilities, though. In the face of urgency to act on climate and despite exciting clean energy options, too often they are choosing the dark side—or at least obsolescence—of their own volition.
The latest round of fossil fuel zombie attacks is coming from big utilities that want to stop the spread of rooftop solar. Just like a zombie horde, they use tactics that are clumsy, somewhat brainless and yet potentially effective.
Here's how it works: Utilities (and the fossil fuel corporations from which they buy dirty fuels like coal and gas) convince a "friendly" legislator to introduce a bill to hit solar customers with an extra tax or fee to make solar more expensive. These bills are usually based on a template written by the Koch brothers-backed American Legislative Council (ALEC). An alternate tactic is to go to the state utility commission and try to convince the regulators there to add the extra fees. The usual claim is that customers who have solar panels are "freeloading" by taking advantage of the grid infrastructure—even though they might not be buying much electricity. If they get their way, the zombies—who don't know they're already dead—win a temporary victory.
In the real world, studies like this one commissioned by the Nevada Public Utilities Commission have found zero basis for the argument that solar customers are hurting non-solar customers. No, what's actually got the utilities spooked is the prospect of an ever-increasing number of their customers generating their own solar power and reducing their power bills. One way they're doing that is through "net metering," which utilities really hate. I wrote a whole post about this a few years ago when it came under attack in California, but basically it means solar customers get credit for all of the energy they generate and contribute to the grid.
There's one big problem with this campaign against rooftop solar. Across the U.S., people love solar power. A poll released early this year found that 80 percent of voters want the country to rely more on solar energy in the next five years. Solar may be one of the few things that almost everyone in America agrees on. What's not to like about free energy that creates no pollution? The benefits are so obvious that rooftop solar actually goes viral. One studyfound that as soon as solar establishes a foothold in an area, it starts spreading in a "wave-like centrifugal pattern."
So when politicians introduce ALEC-authored bills to kill rooftop solar, they suddenly find themselves facing a crowd of angry constituents who want to know whether baseball, mom, or apple pie will be the next target.
As I said, these attacks on solar customers are both clumsy and poorly thought-out. Even so, we cannot afford to ignore them. Rooftop solar can't be completely stopped—it's just too good an idea. But if enough of these bills were somehow to get passed, or if enough utility commissions were to adopt regressive fees, it could slow down the viral spread of solar. And that would mean fewer clean energy jobs (solar energy is a job-creating machine that employs 174,000 Americans), more air-pollution deaths, higher utility bills, and of course, a harder time meeting our goals for cutting carbon emissions and stopping climate disruption.
The irony is that utilities do have reason to be concerned. Over the long term, rooftop solar will have some effect on their business. The smart response, though, isn't to double down on an archaic system. Instead, utilities need to adapt and adopt a business model that incorporates the inevitable rise of distributed energy sources.
Instead of wasting time and resources on helping the Koch brothers sow fear, uncertainty, and doubt about renewables, why aren't utilities working on a strategy for modernizing the outdated U.S. grid, which costs our economy $25 billion or more every year because of outages? And you can bet that extreme weather will only make that problem worse. Clean, free distributed solar energy from millions of rooftops is actually going to be a big part of the solution. Eventually, utilities will see that or they will fail.
In the meantime, though, we have some zombies to fight off. Clean energy champions did exactly that in Indiana earlier this month, but solar is still under attack in states like Florida and Georgia. The next undead outbreak could happen anywhere. Count on this, though: The Sierra Club's unparalleled nationwide network of grassroots activists will be at the forefront of helping to turn back these attacks wherever they happen. Let the sun shine (and the zombies beware)!
YOU MIGHT ALSO LIKE
Battle Continues in Fight to Save States’ Renewable Energy Policies
Clever Interactive Video Encourages Americans to Join Renewable Energy Revolution
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 ... ›
Trending
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> [2003]. 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>Wisconsin will end its controversial wolf hunt early after hunters and trappers killed almost 70 percent of the state's quota in the hunt's first 48 hours.
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.