Grantee Research Project Results
2019 Progress Report: Evaluating the Timeline of Particulate Matter Exposure from UrbanTransportation and Land-Use Greenhouse Gas Mitigation Strategies Using aNovel Modeling Framework
EPA Grant Number: R835885Title: Evaluating the Timeline of Particulate Matter Exposure from UrbanTransportation and Land-Use Greenhouse Gas Mitigation Strategies Using aNovel Modeling Framework
Investigators: Rowangould, Gregory
Institution: University of Vermont
Current Institution: University of Vermont
EPA Project Officer: Keating, Terry
Project Period: January 1, 2016 through December 31, 2018 (Extended to December 31, 2021)
Project Period Covered by this Report: January 1, 2019 through December 31,2019
Project Amount: $335,605
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text | Recipients Lists
Research Category: Air , Climate Change , Early Career Awards
Objective:
The aim of the proposed research is creating a clearer picture of how changes in land-use patterns and transportation systems affect population exposure to particulate matter (PM) pollution from vehicle traffic. The research also aims to understand how the timing of land-use and transportation system changes, particularly those strategies intended to mitigate climate change, affect greenhouse gas (GHG) emissions and cumulative exposure to PM emissions. Finally the research will consider how well changes in PM emission inventories, which are widely used to assess improvements in air quality, correspond to changes in PM exposure.
Progress Summary:
During year 4 the principle investigator (PI) began a new position as an Associate Professor at the University of Vermont. Work on the project was paused while the EPA award was transferred to the University of Vermont from the University of New Mexico and the PI relocated. A one year no cost-extension to the project was granted to accommodate the delays caused by the move.
Prior to the pause in the project during year 4, we detected and fixed an error in our modeling of how autonomous vehicles (AVs) could affect travel demand, land-use, GHG emissions and exposure to PM2.5. The corrected analysis did not change the main finding of our previous modeling. During year 4 we also completed our analysis of the GHG emissions and air quality impacts expected from AVs, finding that AVs would likely result in a short term decrease in GHG emission before contributing to a longer-term increase in emissions. We also found that AVs would likely reduce PM2.5 emissions and exposure to PM2.5, although some parts of our study area would likely see an increase in PM2.5 emissions exposure while others would see a decrease. We plan to evaluate the equity implications of these changes in exposure due to AVs and for the other modeling scenarios we have developed as part of this project.
Finally, analysis completed in years 1-3 for the Albuquerque region considered several bundles of transportation projects and policies that aimed at reducing travel demand and air pollutant emissions. We evaluated each scenario at annual time steps with the integrated travel demand, land-use and emission modeling framework developed in the first years of the project. We found that modeling the change in traffic, land-use and emissions on an annual basis results in a significant change in traffic volumes and patterns, development patterns, and air pollutant emissions when compared to the widely adopted approach of only modeling the first and last year in a multiyear (often decades long) planning horizon. While these results were not entirely unexpected, the magnitude of the change in traffic volumes on individual roadway links and the significant change in development patterns were. We therefore, constructed two additional modeling scenarios designed to challenge the performance of our modeling system and help us gain a better understanding of the impact that a single project or policy change can have a region’s future traffic patterns, vehicle emissions and PM2.5 exposure. During year 4 we obtained initial results from modeling a scenario that added capacity to a congested highway corridor and a scenario that restricted suburban housing development and removed restrictions from urban housing development. In both scenarios, our models behaved as expected, confirming their sensitivity to these scenarios which are difficult to model using traditional modeling methods. The results also show that individual highway projects and changes to local zoning regulations can have region wide impacts. In particular, our analysis of the highway expansion scenario showed impacts on development trends across the entire region. Next steps are to evaluate how the change in development trends and traffic affect regional emissions and emissions exposure.
Future Activities:
We have now developed, tested, and used all the modeling methods required to complete the project’s 7 main tasks and answer the 5 research questions we posed in our research proposal. Our plans for year 5 remain the same as those for year 4 given the pause in research during the novation, although additional delays are expected due to COVID-19 on staff availability. We plan to complete as many remaining project tasks during the 5th year as possible while reviewing options with EPA to address further delays related to COVID-19.
Over the remaining period of this project we plan to use our dynamic modeling approach to evaluate year 2020 and 2040 planning scenarios in the Atlanta region. We also plan to complete a more in-depth analysis of the results we have already obtained, as well as future modeling results, focusing on disparities in exposure by land-use, activity, and socioeconomic characteristics. We aim to identify population subgroups that have unique exposure patterns and disproportionately high exposures. We also aim to identify how changes over time affect exposure components (activities and places contributing to average daily exposure) and the exposures of different population subgroups. This will help us understand how long-range transportation plans may change exposure patterns and possibly identify more effective mitigation strategies.
We also plan to model a wide range of alterative land-use and transportation plans for the Albuquerque region as outlined in our research proposal. We will also be completing more in-depth analysis of our current and future modeling results to understand exposure disparities by land-use and socioeconomic characteristics.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 16 publications | 6 publications in selected types | All 6 journal articles |
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Type | Citation | ||
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Tayarani M and Rowangould G. Estimating exposure to fine particulate matter emissions from vehicle traffic:Exposure misclassification and daily activity patterns in a large, sprawling region. Environ Res 2020; 182:108999. |
R835885 (2019) R835885 (Final) |
Exit Exit |
Supplemental Keywords:
Dispersion Modeling, Mobile Sources, Travel DemandProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- Final Report
- 2020 Progress Report
- 2018 Progress Report
- 2017 Progress Report
- 2016 Progress Report
- Original Abstract
6 journal articles for this project