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Determining air quality and greenhouse gas impacts of hydrogen infrastructure and fuel cell vehicles.
Abstract
Adoption of hydrogen infrastructure and hydrogen fuel cell vehicles (HFCVs) to replace gasoline internal combustion engine (ICE) vehicles has been proposed as a strategy to reduce criteria pollutant and greenhouse gas (GHG) emissions from the transportation sector and transition to fuel independence. However, it is uncertain (1) to what degree the reduction in criteria pollutants will impact urban air quality, and (2) how the reductions in pollutant emissions and concomitant urban air quality impacts compare to ultralow emission gasoline-powered vehicles projected for a future year (e.g., 2060). To address these questions, the present study introduces a "spatially and temporally resolved energy and environment tool" (STREET) to characterize the pollutant and GHG emissions associated with a comprehensive hydrogen supply infrastructure and HFCVs at a high level of geographic and temporal resolution. To demonstrate the utility of STREET, two spatially and temporally resolved scenarios for hydrogen infrastructure are evaluated in a prototypical urban airshed (the South Coast Air Basin of California) using geographic information systems (GIS) data. The well-to-wheels (WTW) GHG emissions are quantified and the air quality is established using a detailed atmospheric chemistry and transport model followed by a comparison to a future gasoline scenario comprised of advanced ICE vehicles. One hydrogen scenario includes more renewable primary energy sources for hydrogen generation and the other includes more fossil fuel sources. The two scenarios encompass a variety of hydrogen generation, distribution, and fueling strategies. GHG emissions reductions range from 61 to 68% for both hydrogen scenarios in parallel with substantial improvements in urban air quality (e.g., reductions of 10 ppb in peak 8-h-averaged ozone and 6 mug/m(3) in 24-h-averaged particulate matter concentrations, particularly in regions of the airshed where concentrations are highest for the gasoline scenario).
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