by J. Matthew Roney
Wind power is the world’s leading source of renewable electricity, excluding hydropower, with 238,000 megawatts of capacity installed at the start of 2012. Thus far, almost all of this wind power has been tapped on land; worldwide just 4,600 megawatts of offshore wind farms were operating as of mid-2012. Offshore wind capacity is growing quickly, however, expanding nearly six-fold since 2006. Twelve countries now have wind turbines spinning offshore, and more will be joining them to take advantage of the powerful winds blowing over the oceans.
More than 90 percent of offshore wind installations are in Europe. Denmark erected the world’s first offshore wind farm in 1991—the 5-megawatt Vindeby project. Offshore wind grew sporadically through the 1990s, as Sweden and the Netherlands also added capacity. Denmark added 400 megawatts of offshore capacity from 2001 to 2003. Since then, however, despite several other countries joining in, the United Kingdom has totally dominated the market. Of the 520 megawatts of new offshore wind capacity installed in Europe in the first half of 2012, roughly 80 percent was in the Irish Sea and North Sea waters of the United Kingdom. The rest was built by Belgium, Germany, and Denmark. (See data.)
By the end of June 2012, the United Kingdom had 2,500 megawatts of offshore wind, over half of the world total. And the country hosts the world’s largest operational offshore wind farm, the Greater Gabbard project in the North Sea. All but 11 of its 504 megawatts were installed and connected to the grid by mid-2012. The United Kingdom also has the largest offshore wind farm under construction: close to one third of the London Array’s 630-megawatt first phase was installed by early May 2012. If approved, Phase Two would bring the project total to 1,000 megawatts.
Outside Europe, only China and Japan have operational offshore wind farms. Although its first offshore project was not installed until 2010, China already ranks fourth behind the United Kingdom, Denmark and Belgium, with 260 megawatts. The government’s goal is 30,000 megawatts of offshore capacity by 2020. This could generate the equivalent of roughly one fifth of China’s current residential electricity consumption.
Japan, with just 25 megawatts of offshore wind power capacity, is developing a pilot 16-megawatt floating wind farm project off the coast of Fukushima. Elsewhere in East Asia, South Korea also has big plans for offshore wind, targeting 2,500 megawatts by 2019.
While the U.S. trails only China in land-based wind generating capacity, it has yet to install a single offshore turbine. For more than a decade, the developers of Cape Wind—a proposed 470-megawatt project off the coast of Massachusetts—have been obtaining permits and fending off legal challenges from groups opposed to the project. As of August 2012, the Federal Aviation Administration (FAA) was again reviewing Cape Wind to determine whether its turbines could have an adverse effect on aircraft radar systems. (The FAA affirmed multiple times during both the Bush and Obama administrations that the project would be safe, only to have its determinations appealed by project opponents). Even so, developers still aim to begin construction in 2013.
Two other proposed projects off the U.S. East Coast slated to begin construction in 2013 are also vying to become the country’s first offshore wind farm. In July 2012, offshore developer Fishermen’s Energy received the final permit needed to begin construction of a 25-megawatt wind farm off Atlantic City, New Jersey. And in Rhode Island’s waters, the firm Deepwater Wind’s 30-megawatt wind farm would meet much of nearby Block Island’s electricity needs. Deepwater Wind has also proposed three 1,000-megawatt offshore wind complexes that would serve the New England and Mid-Atlantic regions, but these are still in the early planning stages.
Part of what has thus far stymied offshore wind in the United States is concern about the aesthetic impact of turbines visible from shore. With its Smart from the Start leasing program, the federal government’s Bureau of Ocean Energy Management hopes to avoid that controversy: the 2,400 square miles set to be auctioned off for wind development later in 2012 are located at least 10 miles from shore, on the Outer Continental Shelf off the East Coast. Smart from the Start also looks to proactively address other common concerns about wind power through careful siting to minimize effects on migratory birds, marine species and archaeological sites.
One project that would facilitate wind development far from shore is the Atlantic Wind Connection, a proposed offshore “transmission backbone” of highly efficient underwater high voltage direct current cables financed by Google, Marubeni, and other investors. Stretching some 300 miles from New York to Virginia, this venture could connect some 7,000 megawatts of offshore wind to the Mid-Atlantic’s population centers. In mid-2012 the project entered the environmental review stage of obtaining a federal right-of-way. Complete construction would take approximately 10 years.
In contrast to the Pacific Coast’s steep drop-off, the U.S. East Coast enjoys a wide, shallow expanse of continental shelf that is especially favorable for offshore wind development. The National Renewable Energy Laboratory estimates that wind turbines installed in the shallow waters of the Mid-Atlantic region could add up to nearly 300,000 megawatts of capacity—enough to power 90 million U.S. homes. For the entire Atlantic Coast, including deeper waters, the resource is estimated at 1 million megawatts.
Nine of the top 10 carbon dioxide emitting countries in 2010 have more than enough offshore wind energy potential to meet all their current electricity needs. (The one that does not is Iran). Russia’s offshore wind resources, for example, exceed its current electricity demand by a factor of 23. Canada’s current electricity needs could be met 36 times over with domestic offshore wind energy.
In addition to the twelve countries with operational offshore wind farms, some 20 others, including Australia, Brazil, and India, have offshore projects in at least the planning stage. In the near term, however, the current leaders in offshore wind are expected to remain the principal sites for deployment. The International Energy Agency projects that even with tight supplies of undersea transmission cables and construction vessels causing some delays in development, offshore wind power will grow nearly six-fold to 26,000 megawatts by 2017. China, the United Kingdom and Germany are expected to account for more than 70 percent of the new installations. As interest grows and technology advances, offshore wind appears headed for a prominent position in the world’s renewable energy mix.
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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.