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Reducing carbon emissions of food supply chains has increasingly received attention from businesses and policymakers. In order to propose sound policies aimed at lowering such emissions, policy makers favor tools that are informative in the economic and environmental dimensions simultaneously. In this study we offer a systems-based approach which is intended to do just that by developing a spatially and temporally disaggregated price equilibrium mathematical model for a food production and distribution system and applying it to the U.S. apple supply chain. We considered three emission reduction interventions: a carbon tax, a land-sparing incentive, and new emission-reduction technologies. We find that R&D which leads to storage technologies with lower carbon emission rates has the greatest potential for emission reduction. Carbon taxes also has the potential to reduce emissions, but at the cost of decreasing apple production and increasing consumer price. These results are unexpected and important, particularly since several countries are implementing carbon taxes and/or land sparing/sharing strategies.
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OBJECTIVE: Electronic health record (EHR) data linked with address-based metrics using geographic information systems (GIS) are emerging data sources in population health studies. This study examined this approach through a case study on the associations between changes in ejection fraction (EF) and the built environment among heart failure (HF) patients. MATERIALS AND METHODS: We identified 1287 HF patients with at least 2 left ventricular EF measurements that are minimally 1 year apart. EHR data were obtained at an academic medical center in New York for patients who visited between 2012 and 2017. Longitudinal clinical information was linked with address-based built environment metrics related to transportation, air quality, land use, and accessibility by GIS. The primary outcome is the increase in the severity of EF categories. Statistical analyses were performed using mixed-effects models, including a subgroup analysis of patients who initially had normal EF measurements. RESULTS: Previously reported effects from the built environment among HF patients were identified. Increased daily nitrogen dioxide concentration was associated with the outcome while controlling for known HF risk factors including sex, comorbidities, and medication usage. In the subgroup analysis, the outcome was significantly associated with decreased distance to subway stops and increased distance to parks. CONCLUSIONS: Population health studies using EHR data may drive efficient hypothesis generation and enable novel information technology-based interventions. The availability of more precise outcome measurements and home locations, and frequent collection of individual-level social determinants of health may further drive the use of EHR data in population health studies.
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UNLABELLED: Based on the current status of research on tradable emission rights futures, this paper introduces basic market-related assumptions for China's interprovincial air pollution control problem. The authors construct an interprovincial air pollution control model based on futures prices: the model calculated the spot price of emission rights using a classic futures pricing formula, and determined the identities of buyers and sellers for various provinces according to a partitioning criterion, thereby revealing five trading markets. To ensure interprovincial cooperation, a rational allocation result for the benefits from this model was achieved using the Shapley value method to construct an optimal reduction program and to determine the optimal annual decisions for each province. Finally, the Beijing-Tianjin-Hebei region was used as a case study, as this region has recently experienced serious pollution. It was found that the model reduced the overall cost of reducing SO2 pollution. Moreover, each province can lower its cost for air pollution reduction, resulting in a win-win solution. Adopting the model would therefore enhance regional cooperation and promote the control of China's air pollution. IMPLICATIONS: The authors construct an interprovincial air pollution control model based on futures prices. The Shapley value method is used to rationally allocate the cooperation benefit. Interprovincial pollution control reduces the overall reduction cost of SO2. Each province can lower its cost for air pollution reduction by cooperation.
