By Daniel Ross
All that glitters ain't gold, or so the old adage goes. And when it comes to the glitter used in everyday cosmetics, specialty make-up, hair products and party paraphernalia, the negative effects on human health and the environment are indeed far from golden.
"They really do get into everything, and despite their tiny size, they can have a devastating impact on humans and non-human animals," wrote Trisia Farrelly, a social anthropologist at Massey University in New Zealand and an expert in waste plastics, in an email to AlterNet.
Glitter is one member of a large family of microplastics—tiny little bits of plastic less than five millimeters in size. Think microbeads, microfibers and fingernail-sized fragments of much larger plastic wastes that have broken down over time. When washed or flushed away, microplastics make their way into our oceans and great lakes, slowly accumulating over time, creating all sorts of health and environmental hazards, the full breadth of which is still being grasped.
For one, there's the issue of how microplastics like cosmetic glitter—made by bonding aluminum with polyethylene terephthalate (PET)—impact sensitive ecosystems. That's because PETs leach out endocrine-disrupting chemicals, which, when eaten by marine life, can cause adverse developmental, reproductive, neurological and immune effects, said Farrelly. In this recent study, microplastics are shown to significantly impact the reproduction rates of oysters.
Then there's the domino-like effect of microplastics through the food-chain, for the sheer volume of microplastics consumed by seafood-loving humans is staggering. This study from the University of Ghent found that Europeans who eat shellfish can consume as much as 11,000 microplastics per year. But what are some of the long-term implications from glitter passing through the food-chain?
PETs attract and absorb persistent organic pollutants and pathogens, adding an extra layer of contamination. When those at the bottom of the ladder—like molluscs, sea snails, marine worms, and plankton—eat pathogen or pollutant-carrying particles of glitter, these minuscule poison pills can concentrate in toxicity as they move up the food chain, all the way to our dinner plates, said Farrelly.
"When we eat Kai moana [Maori term for seafood], we are taking on these toxins," she wrote. "When they enter the gut, the toxins and pathogens are very easily taken up."
A growing body of research is shining a light on the resulting effects of these toxins and pathogens on humans. Studies connect endocrine disrupting chemicals with marine and freshwater fish population collapses, as well as declines in sex ratios in human populations that live adjacent to plastic factories.
All of which is prompting many marine experts and environmentalists to advocate for the same ban on glitter as there has been on microbeads—the tiny little balls of plastic used in things like exfoliating beauty products.
"At the rate we are going, there could be one pound of plastic for every three pounds of finfish in the ocean in the next ten years," wrote Nick Mallos, director of Ocean Conservancy's Trash Free Seas Program, in an email. "And unless action is taken, the problem is only going to get bigger."
At the end of 2015 after a sustained campaign at the state level, the Obama administration signed the Microbead-Free Waters Act, banning plastic microbeads in cosmetics and personal care products. Other countries have subsequently followed suit. The U.K. and New Zealand announced their own prohibitions on microbeads earlier this year.
Importantly, these bans aren't necessarily a reflection of the singular impact from microbeads. Rather, they're a nod to a much wider understanding of the pervasiveness in the environment of microplastics in general, for the amount of microplastics entering the ocean alone is staggering. According to estimates made in 2014, there are between 15 and 51 trillion microplastic particles, weighing between 93 and 236 thousand metric tons, sitting in the world's seas.
What's more, their impacts are myriad
.A number of studies have shown that tiny plastic particles have been detected in sea salts sold commercially. In an interview with the Guardian, Sherri Mason, a professor at the State University of New York at Fredonia who led one of these studies, described plastics as being "ubiquitous in the air, water, the seafood we eat, the beer we drink, the salt we use—plastics are just everywhere." Microfibers have even been found in honey.
Microplastic had also made their way into 83 percent of tap water samples from more than a dozen countries around the world including India, Lebanon, France and Germany, according to an investigation by Orb Media. The U.S. languished at the bottom of the pile, with plastic fibers appearing in 94 percent of samples.
But microplastics comprise only a fraction of the global plastic pollution problem. The world's oceans are pockmarked, for example, with massive clusters of marine debris and plastics—the Great Pacific Garbage Patch found in the North Pacific Ocean proving to be the largest such gyre. According to the U.N., more than 8 million tons of plastic makes its way into the ocean each year—equal to a garbage truck of plastic dumped every minute.
Data shows that rapidly developing economies, where population growth and consumption are outpacing waste collection and recycling capacity, are responsible for the largest amounts of plastic wastes entering the oceans, said Nick Mallos. And he warned that, without intervention, growing economies would likely exacerbate these "unintended consequences of development spread." Still, he remains optimistic.
"By raising awareness of the issue of ocean plastic," Mallos wrote, "we can curb the flow through reduced consumption, improved waste management and innovative product and material solutions."
Reposted with permission from our media associate AlterNet.
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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.