Improving the roadside environment through integrating air quality and traffic-related data.

Details

• Creators:
  Kendrick, Christine M.
• Contributors:
  George, Linda A. ; Atkinson, Dean ; Butenhoff, Christopher ; Clifton, Kelly J.
• Corporate Contributors:
  Portland State University ; National Institute for Transportation and Communities (NITC) ; United States. Environmental Protection Agency ; United States. National Science Foundation
• Subject/TRT Terms:
  • Urban transit
  • Air pollution
  • Air quality management
  • Exhaust gases
  • Environmental impacts
  • Data analysis
• Publication/ Report Number:
  NITC-D-958
• DOI:
  http://dx.doi.org/10.15760/etd.3081
• Resource Type:
  Dissertation
• Geographical Coverage:
  United States;Oregon;Portland (Oregon)
• Corporate Publisher:
  Portland State University
• Abstract:
  Urban arterial corridors are landscapes that give rise to short and long-term ; exposures to transportation-related pollution. With high traffic volumes, congestion, and ; a wide mix of road users and land uses at the road edge, urban arterial environments are ; important targets for improved exposure assessment to traffic-related pollution. Applying ; transportation management strategies to reduce emissions along arterial corridors could ; be enhanced if the ability to quantify and evaluate such actions was improved. However, ; arterial roadsides are under-sampled in terms of air pollution measurements in the United ; States and using observational data to assess such effects has many challenges such as ; lack of control sites for comparisons and temporal autocorrelation. The availability of ; traffic-related data is also typically limited in air monitoring and health studies. The work ; presented here uses unique long-term roadside air quality monitoring collected at the ; intersection of an urban arterial in Portland, OR to characterize the roadside atmospheric ; environment. This air quality dataset is then integrated with traffic-related data to assess ; various methods for improving exposure assessment and the roadside environment. ; Roadside nitric oxide (NO), nitrogen dioxide (NO2), and particle number ; concentration (PNC) measurements all demonstrated a relationship with local traffic ; volumes. Seasonal and diurnal characterizations show that roadside PM2.5 (mass) ; measurements do not have a relationship with local traffic volumes, providing evidence ; that PM2.5 mass is more tied to regional sources and meteorological conditions. The ; relationship of roadside NO and NO2 with traffic volumes was assessed over short and ; long-term aggregations to assess the reliability of a commonly employed method of using traffic volumes as a proxy for traffic-related exposure. This method was shown to be ; insufficient for shorter-time scales. Comparisons with annual aggregations validate the ; use of traffic volumes to estimate annual exposure concentrations, demonstrating this ; method can capture chronic but not acute exposure. As epidemiology and exposure ; assessment aims to target health impacts and pollutant levels encountered by pedestrians, ; cyclists, and those waiting for transit, these results show when traffic volumes alone can ; be a reliable proxy for exposure and when this approach is not warranted. Next, it is demonstrated that a change in traffic flow and change in emissions can ; be measured through roadside pollutant concentrations suggesting roadside pollution can ; be affected by traffic signal timing. The effect of a reduced maximum traffic signal cycle ; length on measurements of degree of saturation (DS), NO, and NO2 were evaluated for ; the peak traffic periods in two case studies at the study intersection. In order to reduce ; bias from covariates and assess the effect due to the change in cycle length only, a ; matched sampling method based on propensity scores was used to compare treatment ; periods (reduced cycle length) with control periods (no change in cycle length). ; Significant increases in DS values of 2-8% were found along with significant increases of ; 5-8ppb NO and 4-5ppb NO2 across three peak periods in both case studies. Without ; matched sampling to address the challenges of observational data, the small DS and NOx ; changes for the study intersection would have been masked and matched sampling is ; shown to be a helpful tool for future urban air quality empirical investigations. ; Dispersion modeling evaluations showed the California Line Source Dispersion ; Model with Queuing and Hotspot Calculations (CAL3QHCR), an approved regulatory model to assess the impacts of transportation projects on PM2.5, performed both poor and ; well when predictions were compared with PM2.5 observations depending on season. ; Varying levels of detail in emissions, traffic signal, and traffic volume data for model ; inputs, assessed using three model scenarios, did not affect model performance for the ; study intersection. Model performance is heavily dependent on background ; concentrations and meteorology. It was also demonstrated that CAL3QHC can be used in ; combination with roadside PNC measurements to back calculate PNC emission factors ; for a mixed fleet and major arterial roadway in the U.S. The integration of roadside air quality and traffic-related data made it possible to ; perform unique empirical evaluations of exposure assessment methods and dispersion ; modeling methods for roadside environments. This data integration was used for the ; assessment of the relationship between roadside pollutants and a change in a traffic signal ; setting, a commonly employed method for transportation management and emissions ; mitigation, but rarely evaluated outside of simulation and emissions modeling. Results ; and methods derived from this work are being used to implement a second roadside air ; quality station, to design a city-wide integrated network of air quality, meteorological, ; and traffic data including additional spatially resolved measurements with feedback loops ; for improved data quality and data usefulness. Results and methods are also being used to ; design future evaluations of transportation projects such as freight priority signaling, ; improved transit signal priority, and to understand the air quality impacts of changes in ; fleet composition such as an increase in electric vehicles.
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• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32146/dot_32146_DS1.pdf
• File Type:
  [PDF - 2.39 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:fed8918d4d2e22a58413145e17e6bff82420077ab9ef1fcdd8237fe6ea0a29d7fe77b9503770dad8705e0b26a97264aaea722b469f802aaab4ff97e7ae8bfacc