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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Examining the Link Between Food Prices and Food Insecurity: a Multi-Level Analysis of Maize Price and Birthweight in Kenya

In developing countries where many poor people rely on rainfed, locally produced food for the majority of their caloric intake, shifts in climate and weather patterns can dramatically reduce agricultural productivity. The reduction in agricultural productivity reduces overall food availability and ultimately impacts food accessibility, putting millions of people at risk for malnutrition. In this project we focus on Kenya where roughly a third of households are food insecure. We examine the relationship of the price of maize and low birth weight to help quantify the impact of local food prices on one outcome of household food insecurity. Using spatially referenced data from recent Kenyan Demographic and Health Survey datasets, price data, livelihood information, and a remotely sensed-based measure of local growing season productivity, we develop a dataset linking pregnancies occurring from 2001 to 2008 to the spatially and temporally relevant maize price data. We construct several regression models to examine the impact of local maize prices and remotely sensed based estimates of crop production on infant birth weight - specifically low birth weight. The results of the models highlight the importance of including community crop production to evaluate maize price impacts on low birth weight outcomes. Also, because of the positive correlation between pre-pregnancy maize prices and birth weight, the results suggest that some households may benefit from high prices or that high prices may impact the number of conceptions. More generally, our work demonstrates that multilevel models that account for community-level variation are important for disentangling these complex relationships and can contribute to the discussion of how to design more effective food policies.

Low birth weight↗
NASA NTRS2012

Local Staple Food Price Indices in the Age of Biofuels

In many poor, food insecure regions, agriculture is a primary source of income and farmers are reliant both on their own production and on purchasing food in the market to feed their families. Large local food price increases over a short time period can be indicative of a deteriorating food security situation and may be the consequence of weather-related food production declines, Dr can simply be the result of price transmission from the international commodity market. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets far from the places where the chronically food insecure live. A much better understanding of how local staple food prices in isolated regions such as West Africa that grow most of the food they eat to better understand the impact of global commodity market transformations on sensitive communities at the margin. This information will also enable improved strategies for these farmers who are extraordinarily sensitive to climate change impacts on agricultural growing conditions.

Brown, Molly E.↗
NASA NTRS2013

Toward Global Drought Early Warning Capability - Expanding International Cooperation for the Development of a Framework for Monitoring and Forecasting

Drought has had a significant impact on civilization throughout history in terms of reductions in agricultural productivity, potable water supply, and economic activity, and in extreme cases this has led to famine. Every continent has semiarid areas, which are especially vulnerable to drought. The Intergovernmental Panel on Climate Change has noted that average annual river runoff and water availability are projected to decrease by 10 percent-13 percent over some dry and semiarid regions in mid and low latitudes, increasing the frequency, intensity, and duration of drought, along with its associated impacts. The sheer magnitude of the problem demands efforts to reduce vulnerability to drought by moving away from the reactive, crisis management approach of the past toward a more proactive, risk management approach that is centered on reducing vulnerability to drought as much as possible while providing early warning of evolving drought conditions and possible impacts. Many countries, unfortunately, do not have adequate resources to provide early warning, but require outside support to provide the necessary early warning information for risk management. Furthermore, in an interconnected world, the need for information on a global scale is crucial for understanding the prospect of declines in agricultural productivity and associated impacts on food prices, food security, and potential for civil conflict. This paper highlights the recent progress made toward a Global Drought Early Warning Monitoring Framework (GDEWF), an underlying partnership and framework, along with its Global Drought Early Warning System (GDEWS), which is its interoperable information system, and the organizations that have begun working together to make it a reality. The GDEWF aims to improve existing regional and national drought monitoring and forecasting capabilities by adding a global component, facilitating continental monitoring and forecasting (where lacking), and improving these tools at various scales, thereby increasing the capacity of national and regional institutions that lack drought early warning systems or complementing existing ones. A further goal is to improve coordination of information delivery for drought-related activities and relief efforts across the world. This is especially relevant for regions and nations with low capacity for drought early warning. To do this requires a global partnership that leverages the resources necessary and develops capabilities at the global level, such as global drought forecasting combined with early warning tools, global real-time monitoring, and harmonized methods to identify critical areas vulnerable to drought. Although the path to a fully functional GDEWS is challenging, multiple partners and organizations within the drought, forecasting, agricultural, and water-cycle communities are committed to working toward its success.

GDEWS↗
DOE OSTI2016

Global economic consequences of deploying bioenergy with carbon capture and storage (BECCS)

Bioenergy with carbon capture and storage (BECCS) is considered a potential source of net negative carbon emissions and, if deployed at sufficient scale, could potentially help reduce carbon dioxide emissions and concentrations. However, the viability and economic consequences of large-scale BECCS deployment are not fully understood. We use the GCAM integrated assessment model to explore the potential global and regional economic impacts of BECCS. BECCS always needs a net subsidy to be deployed; it never produces net tax revenue. We show that by mid-century, in a world committed to limiting climate change to 2°C, carbon tax revenues have peaked and are rapidly approaching the point where climate mitigation is a net burden on general tax revenues. Assuming that the required policy instruments are available to support BECCS deployment, we consider its effects on regional fossil fuels and biomass trade patterns. We find that in a world committed to limiting climate change to 2°C, the absence of CCS harms fossil-fuel exporting regions, while the presence of CCS and BECCS allows greater continued use and export of fossil fuels. We also explore the relationship between carbon prices, food crop prices and BECCS. We show that the carbon price and food-crop prices are directly related. We also show that BECCS reduces the upward pressure on food crop prices exerted by carbon prices due to its effect on lowering carbon prices and lowering the total biomass demand in climate change mitigation scenarios. All of this notwithstanding, many challenges, both technical and institutional, remain to be addressed before BECCS could be deployed at scale.

09 BIOMASS FUELS↗
DOE OSTI2018

Pity the poor biofuels policymaker: reconsidered

The purpose of this note is to clarify three significant misrepresentations published in a Policy Update (Tyner, 2013) titled “Pity the poor biofuel policymaker.” The stated aim of the Policy Update (Tyner, 2013) was to “review some of the literature on three key biofuels issues”: land-use change (LUC), fossil fuel prices and food prices impacts. However, Tyner (2013) repeatedly cited our publication, “Global economic effects of US biofuel policy and the potential contribution from advanced biofuels” (Oladosu et al., 2012). The following compares statements made in the Policy Update (Tyner, 2013) with the substance of what was published by Oladosu et al. (2012).

09 BIOMASS FUELS↗
NASA NTRS2011

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Brown, Molly E.↗
NASA NTRS2012

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

USAID↗
NASA NTRS2012

Provisioning in Agricultural Communities: Local, Regional and Global Cereal Prices and Local Production on Three Continents

Monitoring and incorporating diverse market and staple food information into food price indices is critical for food price analyses. Satellite remote sensing data and earth science models have an important role to play in improving humanitarian aid timing, delivery and distribution. Incorporating environmental observations into econometric models will improve food security analysis and understanding of market functioning.

Brown, Molly E.↗
DOE OSTI2023

Compounding Uncertainties in Economic and Population Growth Increase Tail Risks for Relevant Outcomes Across Sectors

Understanding the long-term effects of population and GDP changes requires a multisectoral and regional understanding of the coupled human-Earth system, as the long-term evolution of this coupled system is influenced by human decisions and the Earth system. This study investigates the impact of compounding economic and population growth uncertainties on long-term multisectoral outcomes. We use the Global Change Analysis Model (GCAM) to explore the influence of compounding and feedback between future GDP and population growth on four key sectors: final energy consumption, water withdrawal, staple food prices, and CO 2 emissions. The results show that uncertainties in GDP and population compound, resulting in a magnification of tail risks for outcomes across sectors and regions. Compounding uncertainties significantly impact metrics such as CO 2 emissions and final energy consumption, particularly at the upper tail at both global and regional levels. However, the impact of staple food prices and water withdrawal depends on regional factors. Additionally, an alternative low-carbon transition scenario could compound uncertainties and increase tail risk, particularly in staple food prices, highlighting the influence of emergent constraints on land availability and food-energy competition for land use. The findings underscore the importance of considering and adequately accounting for compounding uncertainties in key drivers of multisectoral systems to enhance our comprehensive understanding of the complex nature of multisectoral systems. The paper provides valuable insights into the potential implications of compounding uncertainties.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity

Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises.

Brown, Molly E.↗
DOE OSTI2020

Stranded asset implications of the Paris Agreement in Latin America and the Caribbean

Achieving the Paris Agreement's near-term goals (Nationally Determined Contributions, NDCs) and long-term temperature targets could result in pre-mature retirement, or stranding, of carbon-intensive assets before the end of their useful lifetime. We use an integrated assessment model to quantify the implications of the Paris Agreement for stranded assets in Latin America and the Caribbean (LAC), a developing region with the least carbon-intensive power sector in the world. We find that meeting the Paris goals results in stranding of 37-90 billion and investment of 1.9-2.6 trillion worth of power sector capital (2021-2050) across a range of future scenarios. Strengthening the NDCs could reduce stranding costs by 27-40%. Additionally, while politically shielding power plants from pre-mature retirement or increasing the role of other sectors (e.g. land-use) could also reduce power sector stranding, such actions could make mitigation more expensive and negatively impact society. For example, we find that avoiding stranded assets in the power sector increases food prices 13%, suggesting implications for food security in LAC. Our analysis demonstrates that climate goals are relevant for investment decisions even in developing countries with low emissions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Agricultural Productivity Forecasts for Improved Drought Monitoring

Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop simulation system, which integrates the effects of soil, crop phenotype, weather, and management options. It has been in use for more than 15 years by researchers, growers and has become a de-facto standard in crop modeling communities spanning over 100 countries. The meteorological forcings to DSSAT are provided by NASA s National Land Data Assimilation System (NLDAS) datasets. NLDAS is a framework that incorporates atmospheric forcing and land parameter values along with land surface models to diagnose and predict the state of the land surface.

Limaye, Ashutosh↗
DOE OSTI2022

Evaluating the regional risks to food availability and access from land-based climate policies in an Integrated Assessment Model

Mitigating greenhouse gas (GHG) emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the Global Change Analysis Model (GCAM4.0). We then project consumer prices and our measure of food security along the Shared Socioeconomic Pathways (SSPs). Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions is more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples.

Cui, Ryna↗
DOE OSTI2026

Historical and Future Global Irrigation Energy Consumption by Fuel and Region

Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.

Global Change Analysis Model (GCAM)↗
DOE OSTI2016

Socioeconomic indicators for sustainable design and commercial development of algal biofuel systems

Abstract Social and economic indicators can be used to support design of sustainable energy systems. Indicators representing categories of social well‐being, energy security, external trade, profitability, resource conservation, and social acceptability have not yet been measured in published sustainability assessments for commercial algal biofuel facilities. We review socioeconomic indicators that have been modeled at the commercial scale or measured at the pilot or laboratory scale, as well as factors that affect them, and discuss additional indicators that should be measured during commercialization to form a more complete picture of socioeconomic sustainability of algal biofuels. Indicators estimated in the scientific literature include the profitability indicators, return on investment (ROI) and net present value (NPV), and the resource conservation indicator, fossil energy return on investment (EROI). These modeled indicators have clear sustainability targets and have been used to design sustainable algal biofuel systems. Factors affecting ROI, NPV, and EROI include infrastructure, process choices, and financial assumptions. The food security indicator, percent change in food price volatility , is probably zero where agricultural lands are not used for production of algae‐based biofuels; however, food‐related coproducts from algae could enhance food security. The energy security indicators energy security premium and fuel price volatility and external trade indicators terms of trade and trade volume cannot be projected into the future with accuracy prior to commercialization. Together with environmental sustainability indicators, the use of a suite of socioeconomic sustainability indicators should contribute to progress toward sustainability of algal biofuels.

09 BIOMASS FUELS↗
DOE OSTI2025

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗
NASA NTRS2013

A City and National Metric measuring Isolation from the Global Market for Food Security Assessment

The World Bank has invested in infrastructure in developing countries for decades. This investment aims to reduce the isolation of markets, reducing both seasonality and variability in food availability and food prices. Here we combine city market price data, global distance to port, and country infrastructure data to create a new Isolation Index for countries and cities around the world. Our index quantifies the isolation of a city from the global market. We demonstrate that an index built at the country level can be applied at a sub-national level to quantify city isolation. In doing so, we offer policy makers with an alternative metric to assess food insecurity. We compare our isolation index with other indices and economic data found in the literature.We show that our Index measures economic isolation regardless of economic stability using correlation and analysis

Brown, Molly E.↗