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Quantifying marginal societal health benefits of transportation emission reductions in the United States and Canada

Principal Investigator: 
,

Carleton University, Canada

The investigators will develop and apply a source‐ and location-specific database of mortality benefits per ton emissions reduction of NOx and other pollutants. 

Funded under
Status: 
Ongoing
Abstract

Poster abstract for HEI Annual Conference 2022

Quantifying Societal Health Benefits of Transportation Emission Reductions in the United States and Canada

Amir Hakami1, Shunliu Zhao1, Petros Vasilakos2, Armistead Russell2, Alan Krupnick3, Howard Chang4, Neal Fann5

1Carleton University, Ottawa, ON, Canada; 2Georgia Institute of Technology, Atlanta, GA, USA; 3Resources for the Future, Washington, DC, USA; 4Emory University, Atlanta, GA, USA; 5USEPA, RTP, NC, USA

Background. We aim to quantify the monetized societal health benefits, or Benefits-Per-Tonne (BPT), associated with emission reductions from major source sectors (i.e., transportation and energy generation) in Canada and the US. The objectives of the study are to a) create a database of location-specific BPTs for transportation and other sectors in Canada and the US, b) quantify the uncertainty in estimated BPTs, c) examine the sensitivity to various assumptions made in estimation of BPTs, and d) develop an associated database of air quality co-benefits of combustion-based CO2 reductions.

Methods. The adjoint version of the USEPA’s CMAQ model is used at 12 km resolution over Canada and the contiguous U.S. Due to the computational cost of adjoint simulations, the study design relies on reconstruction of annual exposure estimates from episodic simulations in all seasons. The simulated episodes are chosen based on an anomaly analysis of annual adjoint simulations at a coarse resolution. The study examines the robustness of various assumptions used in BPT estimations, such as a) the choice of episodes, b) the spatial resolution of the air quality model, c) decadal changes in emission levels, and d) the shape of concentration-response functions. We combine estimated BPTs with sector-specific CO2 emission profiles to develop a related database of co-benefits of combustion-based CO2 reductions.

Results. We find a wide range for BPTs across different locations. As expected BPT estimates are generally largest in proximity to population centers, while regional transport patterns appear more prominently for precursors of secondary PM2.5 and tall stack emissions. BPT values are greatest for primary PM2.5 and ammonia emissions. All BPTs exhibit seasonal variability; in particular, ammonia BPTs have distinct seasonal patterns. In our sensitivity analysis we find consistent spatial patterns in both coarse and fine spatial resolutions; however, fine resolution BPTs show wider range and larger extremes. We also find that the choice of the concentration-response function can affect the results significantly. Finally, we see significant co-benefits for the transportation sector that exceed suggested values for the social cost of carbon for some vehicle types and locations.

Conclusions. Spatial variability in BPT estimates suggests that they can be an invaluable resource in informing pollution control policies. The choice of concentration-response function is likely to be the largest source of uncertainty in BPT estimates. 12-km simulations appear to be adequate in delineating spatial patterns of BPTs at a level of detail commensurate with continental-scale modeling. Transportation sector co-benefits are sizeable, particularly for diesel heavy duty vehicles, providing supporting evidence for electrification of these vehicles in urban settings (e.g., transit, service vehicles, etc) in addition to passenger cars.