Yes, Eating Meat Affects the Environment, But Cows Are Not Killing the Climate
By Frank M. Mitloehner
As the scale and impacts of climate change become increasingly alarming, meat is a popular target for action. Advocates urge the public to eat less meat to save the environment. Some activists have called for taxing meat to reduce consumption of it.
A key claim underlying these arguments holds that globally, meat production generates more greenhouse gases than the entire transportation sector. However, this claim is demonstrably wrong, as I will show. And its persistence has led to false assumptions about the linkage between meat and climate change.
My research focuses on ways in which animal agriculture affects air quality and climate change. In my view, there are many reasons for either choosing animal protein or opting for a vegetarian selection. However, foregoing meat and meat products is not the environmental panacea many would have us believe. And if taken to an extreme, it also could have harmful nutritional consequences.
Global livestock production by region (milk and eggs expressed in protein terms). FAO, CC BY-ND
Setting the Record Straight on Meat and Greenhouse Gases
A healthy portion of meat's bad rap centers on the assertion that livestock is the largest source of greenhouse gases worldwide. For example, a 2009 analysis published by the Washington, DC-based Worldwatch Institute asserted that 51 percent of global GHG emissions come from rearing and processing livestock.
According to the U.S. Environmental Protection Agency, the largest sources of U.S. GHG emissions in 2016 were electricity production (28 percent of total emissions), transportation (28 percent) and industry (22 percent). All of agriculture accounted for a total of 9 percent. All of animal agriculture contributes less than half of this amount, representing 3.9 percent of total U.S. greenhouse gas emissions. That's very different from claiming livestock represents as much or more than transportation.
Why the misconception? In 2006 the United Nations Food and Agriculture Organization published a study titled "Livestock's Long Shadow," which received widespread international attention. It stated that livestock produced a staggering 18 percent of the world's greenhouse gas emissions. The agency drew a startling conclusion: Livestock was doing more to harm the climate than all modes of transportation combined.
This latter claim was wrong, and has since been corrected by Henning Steinfeld, the report's senior author. The problem was that FAO analysts used a comprehensive life-cycle assessment to study the climate impact of livestock, but a different method when they analyzed transportation.
For livestock, they considered every factor associated with producing meat. This included emissions from fertilizer production, converting land from forests to pastures, growing feed, and direct emissions from animals (belching and manure) from birth to death.
However, when they looked at transportation's carbon footprint, they ignored impacts on the climate from manufacturing vehicle materials and parts, assembling vehicles and maintaining roads, bridges and airports. Instead, they only considered the exhaust emitted by finished cars, trucks, trains and planes. As a result, the FAO's comparison of greenhouse gas emissions from livestock to those from transportation was greatly distorted.
Researchers have identified multiple options for reducing greenhouse gas emissions from the livestock sector. Red bars represent the potential range for each practice. Herrero et al, 2016, via Penn State University
I pointed out this flaw during a speech to fellow scientists in San Francisco on March 22, 2010, which led to a flood of media coverage. To its credit, the FAO immediately owned up to its error. Unfortunately, the agency's initial claim that livestock was responsible for the lion's share of world greenhouse gas emissions had already received wide coverage. To this day, we struggle to "unring" the bell.
In its most recent assessment report, the FAO estimated that livestock produces 14.5 percent of global greenhouse gas emissions from human activities. There is no comparable full life-cycle assessment for transportation. However, as Steinfeld has pointed out, direct emissions from transportation versus livestock can be compared and amount to 14 versus 5 percent, respectively.
Giving Up Meat Won't Save the Climate
Many people continue to think avoiding meat as infrequently as once a week will make a significant difference to the climate. But according to one recent study, even if Americans eliminated all animal protein from their diets, they would reduce U.S. greenhouse gas emissions by only 2.6 percent. According to our research at the University of California, Davis, if the practice of Meatless Monday were to be adopted by all Americans, we'd see a reduction of only 0.5 percent.
Moreover, technological, genetic and management changes that have taken place in U.S. agriculture over the past 70 years have made livestock production more efficient and less greenhouse gas-intensive. According to the FAO's statistical database, total direct greenhouse gas emissions from U.S. livestock have declined 11.3 percent since 1961, while production of livestock meat has more than doubled.
Demand for meat is rising in developing and emerging economies, with the Middle East, North Africa and Southeast Asia leading the way. But per capita meat consumption in these regions still lags that of developed countries. In 2015, average annual per capita meat consumption in developed countries was 92 kilograms (approximately 203 pounds), compared to 24 kilograms in the Middle East and North Africa and 18 kilograms in Southeast Asia.
Still, given projected population growth in the developing world, there will certainly be an opportunity for countries such as the U.S. to bring their sustainable livestock rearing practices to the table.
In developing countries, raising livestock such as these goats in Kenya is an important source of food and income for many small-scale farmers and herders. Loisa Kitakaya
The Value of Animal Agriculture
Removing animals from U.S. agriculture would lower national greenhouse gas emissions to a small degree, but it would also make it harder to meet nutritional requirements. Many critics of animal agriculture are quick to point out that if farmers raised only plants, they could produce more pounds of food and more calories per person. But humans also need many essential micro- and macronutrients for good health.
It's hard to make a compelling argument that the U.S. has a calorie deficit, given its high national rates of adult and child obesity. Moreover, not all plant parts are edible or desirable. Raising livestock is a way to add nutritional and economic value to plant agriculture.
As one example, the energy in plants that livestock consume is most often contained in cellulose, which is indigestible for humans and many other mammals. But cows, sheep and other ruminant animals can break cellulose down and release the solar energy contained in this vast resource. According to the FAO, as much as 70 percent of all agricultural land globally is range land that can only be utilized as grazing land for ruminant livestock.
The world population is currently projected to reach 9.8 billion people by 2050. Feeding this many people will raise immense challenges. Meat is more nutrient-dense per serving than vegetarian options, and ruminant animals largely thrive on feed that is not suitable for humans. Raising livestock also offers much-needed income for small-scale farmers in developing nations. Worldwide, livestock provides a livelihood for 1 billion people.
Climate change demands urgent attention, and the livestock industry has a large overall environmental footprint that affects air, water and land. These, combined with a rapidly rising world population, give us plenty of compelling reasons to continue to work for greater efficiencies in animal agriculture. I believe the place to start is with science-based facts.
Changing the Main Course of #ClimateChange @nongmoproject @foodmatters #FoodMatters https://t.co/BLIMsj28Wm— EcoWatch (@EcoWatch)1540134132.0
Frank M. Mitloehner is a professor of animal science and an air quality extension specialist at the University of California, Davis.
Disclosure statement: Frank M. Mitloehner receives funding from the California Air Resources Board (CARB) and the California Department of Food and Agriculture (CDFA).
Reposted with permission from our media associate The Conversation.
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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.