Tangible human health co-benefits can motivate stronger support for climate policy. For example, decarbonizing the energy system can produce sizable health co-benefits by reducing co-emitted air pollutants. However, assessing near-term decarbonization strategies with health considerations faces two key analytical challenges: (i) unintended health co-harms from some carbon mitigation strategies; for instance, large-scale bioenergy production can drive up food prices, which leads to nutrition-related health co-harms, and (ii) deep uncertainties about the future, such as socioeconomic patterns, technology costs, and market factors. The objectives of this project are: (i) to improve the quantitative understanding of key factors and processes that determine the magnitude and distribution of health outcomes from decarbonization, and (ii) to identify features of decarbonization strategies that are most likely to yield robust net health benefits given deep future uncertainties.
The investigators hypothesize that while health co-benefits and co-harms are both affected by local technology choices (e.g., electricity generation technologies and vehicle types) and socioeconomic factors (e.g., income growth and population aging), the health co-harms are further determined by complex interactions across regions and sectors, such as inter-regional trade of electricity, biofuel, and food. With a focus on the United States, the investigators will test the hypothesis by: (i) developing an integrated energy-food-health modeling framework, by improving the representation of health drivers in a state-level integrated assessment model (GCAM-USA) and connecting it with a fine- resolution health impact assessment module, (ii) constructing a large-scale ensemble of decarbonization scenarios to represent a wide range of future uncertainties in socioeconomic patterns, energy technology costs, and food/energy market setups, and (iii) identifying the key factors and processes that determine health outcomes at the county, state, and national levels. By combining knowledge from energy system modeling, health impact assessment, and decision analysis, this convergent research targets improving understanding of the non-linear interactions between low-carbon energy strategies and human health, as well as the role of the market and natural systems on which these interactions depend. Thus, this project seeks to advance quantitative understanding of the complex systems governing interconnected societal challenges on energy, health, and climate. Through a convergence of various disciplines, it seeks to provide new insights on key interacting dynamics that determine health outcomes from decarbonization. Further, by leveraging modern computational capabilities to analyze a large scenario ensemble, a data-driven approach is intended to enable quantification of the relative importance of various socioeconomic, technological, and market uncertainties in determining the health co-benefits or co-harms. The project will produce open-source model code and teaching materials for research and educational purposes. It will also train undergraduate and doctoral students in a highly interdisciplinary environment. Findings are intended to guide practitioners to improve their decisions to better navigate the climate-health nexus.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|Effective start/end date||9/1/21 → 8/31/24|
- National Science Foundation: $167,581.00