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Considering future regional air quality impacts of the transportation sector

Abstract Regional air pollution is strongly impacted by transportation emissions. Policy mechanisms to reduce emissions are required to reach environmental quality goals. Projecting the drivers (e.g., technical, economic, societal, regulatory) that will impact future emissions is challenging, and assessing regional air quality (AQ) is complicated by the need for detailed modeling tools and data inputs to simulate chemistry and transport of pollutants. This work assesses the contribution of emissions from transportation sources to ground-level concentrations of ozone and fine particulate matter via two methods. First, impacts are quantified for three U.S. regions including California using output from an economic optimization model to grow a base year emissions inventory to 2055. Second, impacts are considered for California using state-level projections with an updated emissions inventory and modeling suite in 2035. For both, advanced AQ models are used, showing that the impacts of light duty vehicles are moderate, reflecting shifts to more efficient and lower emitting technologies. In contrast, heavy duty vehicles, ships, and off-road equipment are associated with important ozone and PM2.5 burdens. Emissions from petroleum fuel production and distribution activities also have notable impacts on ozone and PM2.5. These transportation sub-sectors should be the focus of future emissions reduction policies.
- University of California, Irvine United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).26 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
