Health-Based Intelligent Transportation Systems

Traditionally, Intelligent Transportation Systems (ITS) applications have been developed to address pollutant emissions on a large regional basis, but have not focused on the local health impacts. California is home to many densely populated communities that are adjacent to roadways with heavy traffic. In Los Angeles, more than 30% of the population is living within 50-100 meters of major roads, where pollutant concentrations are often 2-4 times higher than those 100 meters away. The Transportation Systems Research Group is developing novel approaches to reducing the exposure of local communities to high levels of atmospheric particulate matter (PM) through the use of technologies such as pedestrian routing applications.
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  • Particulate Matter from Vehicle Emissions

    Bridging Model Estimates of Vehicular Emissions with Near-Roadway Ambient Measurements 

    Particulate Matter (PM) formation from gasoline vehicle emissions were measured with a temperature controlled dilution sampler to account for additional PM formation during the dilution and cooling process, on the timescale of near-roadway emissions. The dilution sampler simulates the rapid dilution and cooling that occurs as the vehicle exhaust mixes with the ambient atmosphere. The emission factor of a gasoline vehicle was measured as a function of dilution to assess the sensitivity of the emission factors to near-roadway meteorology. A new module within MOVES will be developed using ratios of measured (after dilution) emission factor to chassis and PEMS emission factors to identify the sensitivity of the near-roadway PM estimation from tailpipe to dilution processes.

    Lead Researchers: Ayla Moretti, Dr. David Cocker, Dr. Matthew Barth, Dr. Ji Luo 


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    Enery Electric/Plug-in Hybrid Electric Trucks and Connected Vehicle Technologies for Drayage Application

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    Advances in connected vehicle (CV) technologies have the potential for reducing GHG emissions, fuel consumption, and emissions of other pollutants. The UCR research team has developed a variety of CV applications. One such application is Eco-Approach and Departure (EAD), which uses signal phase and timing information from the traffic signal to determine an optimal speed profile for approaching and departing the intersection in the most eco-friendly manner. With the projected increasing market shares of plug-in hybrid electric trucks in the freight sector in the next several years, this project will evaluate the energy and emission benefits of employing plug-in hybrid electric trucks in place of conventional diesel trucks. Read more...

    Lead Faculty: Dr. Peng Hao, Dr. Kanok Boriboonsomsin, Dr. Ji Luo, Dr. Alexander Vu, Daniel Sandez, Chao Wang

    Quantifying Traffic Congestion Induced Change of Near-road Air Pollutant Concentration
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    Traffic congestion exacerbates the ambient air pollution by contributing a large amount of additional fuel consumption and tailpipe emissions. However, the relationship between the prevailing traffic condition and local air pollutant concentration is not well quantified in previous literature. The primary goal of this study is to quantify the contributions to the ambient air quality degradation due to traffic congestion. The study will use real-time traffic characteristics and ambient air quality data from monitoring sites to develop and validate a statistical model that can be used to understand the air quality impacts of traffic congestion. Read more..

    Lead Faculty: Dr. Ji Luo, Dr. Guoyuan Wu

    Secondary Particulate Matter Exceed Primary Emissions from Current Gasoline Vehicles: Air Quality and Public Health Implications
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    Gasoline Direct Injection (GDI) technology is becoming increasingly popular among vehicles in the market today. While there is relatively little-established knowledge on GDI vehicle emissions, studies have raised concerns relating to PM emissions, as well as the generation of polycyclic aromatic hydrocarbons (PAHs) and nitrated-PAHs. Another aspect that has not been investigated in detail is the secondary organic aerosol (SOA) formation, which is also a contributor to airborne PM. This study will characterize the primary emissions and the secondary organic aerosol (SOA) formation from current technology gasoline direct injection (GDI) and port fuel injection (PFI) vehicles when operated under different driving cycles, through in-use emissions testing and the use of a mobile atmospheric chamber and oxidation flow reactor to assess secondary aerosol formation. Read more...

    Lead Faculty: Dr. Georgios Karavalakis, Dr. David Cocker, Dr. Thomas Durbin 

    Onboard Sensing, Analysis, and Reporting (OSAR): Expanded Field Demonstrations and Development of Associated Visual Aids
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    Heavy-duty vehicles represent one of the most important contributions to the emission inventory for both nitrogen oxides (NOx) and particulate matter (PM) emissions. Heavy-duty engines have been subject to increasingly more stringent standards over the years. The latest round of standards essentially requiring the use of diesel particulate filters (DPFs) and selective catalytic reduction (SCR) to meeting the PM and NOx emsiions, it is important to verify that these systems are operating optimally under the full range of in-use conditions to ensure that air quality standards can be met. Read more...

    Lead faculty: Dr. Kent Johnson, Dr. George Scora, Dr. Thomas Durbin, Dr. Georgios Karavalakis 


  • CalTrans

    Emission-based Routing 


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