学位论文详细信息
Modeled Health Impacts of Changes in Transportation-Related Fine Particulate Matter Emissions Resulting From Proposed Climate Policy in Oregon
Sustainability;health;climate policy;fine particulate;greenhouse gas;transportation;PM 2.5;Oregon
Elbel, Elizabeth M.
University:Havard University
Department:Sustainability
关键词: Sustainability;    health;    climate policy;    fine particulate;    greenhouse gas;    transportation;    PM 2.5;    Oregon;   
Others  :  https://dash.harvard.edu/bitstream/handle/1/37365401/ELBEL-DOCUMENT-2020.pdf?sequence=1&isAllowed=y
美国|英语
来源: Digital Access to Scholarship at Harvard
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【 摘 要 】

The focus of this research was to compare how different climate mitigation policies influence air pollutant emissions in the transportation sector. As these policies also often reduce other air pollutants harmful to humans, policies that mitigate greenhouse gases can lead to improved air quality and better health. (West et al., 2013). One such pollutant is fine particulate matter (PM 2.5), which, when inhaled deep into the lungs, can agitate asthma, as well as respiratory and heart conditions (Oregon Health Authority [OHA], 2017). Understanding the relationships and potential co-benefits of reducing air pollution through climate mitigation policies allows decision makers to assess the broader benefits of a specific policy. My research examined climate policy scenarios based on proposed or current policy in Oregon. As a case study, emissions from passenger vehicles and light duty trucks were modeled for six different policy scenarios and one reference scenario for Jackson County, Oregon. The policy scenarios include several economy-wide carbon pricing policies, a transportation-specific zero-emission vehicle (ZEV) adoption scenario and a vehicle mile travel (VMT) tax policy.Two separate models were utilized to develop the emissions estimates. The first was the Regional Strategic Planning Model (RSPM), used to model the impacts of different policies on the transportation sector. Select outputs from RSPM were used as inputs into EPA’s Motor Vehicle Emissions Simulator (MOVES). MOVES produced estimates of greenhouse gas and particulate matter emissions for each scenario.These results were compared to the reference scenario to determine the change in emissions.Based on this information, an economic analysis was constructed for comparison. The analysis included the monetized health benefits of emission reductions, social cost of carbon savings and, if applicable, revenue generation from pricing carbon.The results demonstrated that, while high carbon-pricing scenarios have a greater impact on emissions, an increased adoption of zero-emission vehicles has similar impacts to a low to mid-range carbon price in regards. The zero-emission vehicle adoption policy resulted in 90% of the cumulative greenhouse gas emission reductions achieved by the high carbon-pricing scenario. The medium pricing scenario achieved only 52%. The reductions in PM 2.5 achieved by the zero-emission vehicle adoption scenario were less robust. The zero-emission vehicle policy resulted in 23% of the PM 2.5 emission reductions achieved by the high pricing scenario, slightly below the 26% achieved by the low pricing scenario. The less robust reductions of PM 2.5 from the zero-emission vehicle scenario are a result of the shift in the source of PM 2.5 emissions. Engine exhaust is the primary source of PM 2.5 emissions in the initial years, while tire wear and brake use are greater contributors in future years. For example, 84% of PM 2.5 emissions were attributed to exhaust in 2010 while only 24% of PM 2.5 emissions were attributable to exhaust in 2050, the other portion being emissions from tire and break wear. With this in mind, policies that reduce exhaust emissions have greater co-benefits in the near term than in future years, when engine technology advances reduce emissions exhaust. Alternatively, in future years, reductions in VMT have a greater impact on PM 2.5 emissions since emissions are primarily resulting from tire wear and break use.

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