This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: How will global access to food, water and energy evolve in coming decades? A new study coauthored by MIT researchers suggests the answers could be very different depending on region, resource and income.
Based on extensive modeling of many different resource scenarios, the study finds that in some regions, lower-income people could be spending roughly 50% of their income on food by 2050, in contrast to higher-income groups that could spend about 5% of their income on food in the same areas. "For a lot of these outcomes, the lower-income groups see much worse potential insecurity," says Jennifer Morris, a principal research scientist at the MIT Center for Sustainability Science and Strategy and the MIT Energy Initiative and co-author of a new paper detailing the findings. The results, she notes, can be evaluated by policymakers in different global regions to understand what the long-term, large-scale resource security risks may become for different parts of their populations.
"Anything that's taking up half of your income is potentially destabilizing for your entire life because it leaves so few resources for the other critical needs and basic life necessities," Morris says. The study focuses on projecting future access to food, water and energy, based on long-term variation across a dozen major factors influencing their availability, from economic conditions and agricultural production to trade conditions, climate, land use and more. "This study shows that there is no single driver of future food, energy and water insecurity," says Gi Joo Kim, a research scientist at Tulane University and co-author of the paper.
"Income is important, but regional conditions, land use, energy systems, water availability and consumer behavior all shape the risks people face." For policymakers, he adds, "This means they need to consider specific combinations of factors that create vulnerability in each region." The paper, "Identifying Key Uncertainties and Drivers of Future Resource Security Outcomes Through a Multisector Scenario Ensemble," appears in the journal Earth's Future. In addition to Morris and Kim, the authors include Brian O'Neill, an earth scientist at the Pacific Northwest National Laboratory; Marshall Wise, a systems engineer at the Pacific Northwest National Laboratory; John Weyant, a professor of management science and engineering at Stanford University; and Jonathan Lamontagne, an associate professor of civil and environmental engineering at Tufts University. The current study fills a gap in modeling among scientists studying issues such as long-term resource security.
Given the complications of long-term analyses, many studies have used what scientists term "shared socioeconomic pathway" circumstances, a small set of scenarios spanning broad global narratives about the future, rather than exploring specific outcomes such as how long-term resource access may shift in linked fashion across income groups in different regions of the world. Two years ago, the same group of authors wrote a paper calling for more socioeconomically specific scenario analysis focused on outcomes for human well-being; the current study is their effort to develop that kind of modeling. "For this type of study, where we're focused on human well-being outcomes, the income piece is really important," Morris says.
To conduct the study, the researchers adopted an existing framework in the field, the Global Change Analysis Model (GCAM) version 7.1, which represents interactions between energy, economies, water, land and climate while dividing the world into 32 regions, 235 water basins and 384 land-use regions and making adjustments for things like estimated commodity prices over time. Discover the latest in science, tech, and space with over 100,000 subscribers who rely on Phys.org for daily insights. d research that matter—daily or weekly. The research group used 12 main variables connected to resource availability, including population, GDP, income distribution, carbon intensity, land use, agricultural trade, multiple energy consumption scenarios, multiple water-use projections and more.
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