low carbon agriculture systems and food supply chains; mathematical systems modeling and policy analyses for food security and carbon policy.
Nearly one in every eight residents of the Northeast US is food insecure. In addition, the global food system, from fertilizer manufacture to food storage and packaging, is responsible for up to one third of all human-caused greenhouse-gas (GHG) emissions. Regional Food Systems (RFS) offer significant potential for improving food access for vulnerable communities while strengthening local economies. However, comprehensive evaluations of these food systems and education about lessons learned are needed to realize this potential. To address these inherently complex systems, our USDA-sponsored project (Enhancing Food Security of Underserved Populations in the Northeast through Sustainable Regional Food Systems) supports an interdisciplinary team of scientists and expert practitioners to evaluate multiple consumption, distribution and production components of RFS in the Northeast along with their associated feedbacks and interdependencies, across multiple scales and nested supply chains for a “healthy food basket”. For example, in spite of the increased interest in, and support for, programs and policies aimed at localizing food supply chains; there is limited empirical evidence of how localization influences environmental and economic outcomes, particularly from a broader systems perspective. Our study contributes to the literature on localization using a systems approach to examine multidimensional impacts of state- and regional-level initiatives to localize food production, processing and consumption. Specifically, we develop an optimization model to assess the impacts of two alternative scenarios for localizing fluid milk supply chains on multiple outcomes of potential interest to policy makers and businesses: 1) distances traveled by fluid milk and other dairy products, 2) transportation costs, 3) emissions of CO2 equivalent, particulate matter (PM) and nitrogen oxides (NOx), 4) regional employment, and 5) economic activity. This more comprehensive, systemic approach provides insights to public and private organizations to support better decisions when considering programs and policies to foster localization of food supply chains.
A considerable amount of the total food intake by mass (30%) is represented by fruits and vegetables, which constitute the largest food group consumed worldwide. Fruit Supply Chains (FSCs) are an important component of this system, and they play an important role in todays’ economy, as consumer demand for healthier diets and fresh products is increasing. The recent debate at the Convention of the Parties of the United Nations Framework on Climate Change (COP21) attests to this concern and to the range of viewpoints on how to reduce CO2 emissions. In the context of food systems in particular, the COP21 calls for strategies that include agricultural intensification, food waste reduction in production and distribution, development of CO2-efficient postharvest technologies, and policies to influence behavior of private decision makers (e.g. consumers, businesses), among others. Another study in my group offers a systems approach to evaluate alternative CO2 reduction strategies in FSCs taking into consideration socioeconomic and environmental dimensions simultaneously. We apply our model to the case of the U.S apple supply chain. We find that an R&D strategy yielding improved storage technologies with lower CO2 emission rates, in combination with an appropriate carbon-tax policy, reduces CO2 emissions and improves economic welfare simultaneously. Land sparing is a reasonable option to offset CO2 emissions when ignoring economic impacts. Interventions that combine investment in R&D, appropriate tax levels and land sparing to reduce CO2 emissions can further contribute to mitigate emissions to enhance economic welfare. We also consider for the first time in the literature a Perishable products Inventory vehicle Routing Problem in the context of Cold supply chain (PIRPC). We explicitly model GHG emissions due to transportation activities depending on the vehicle load during delivery.