A new approach for evaluating regional exposure to particulate matter emissions from motor vehicles

Exposure to fine particulate matter from vehicle exhaust is associated with increased health risk. This study develops a new approach for creating spatially detailed regional maps of fine particulate matter concentration from vehicle exhaust using a dispersion model to better evaluate these risks. The spatial extent, diurnal, and seasonal patterns of concentration fields across Los Angeles County, California are evaluated and population exposure and exposure equity by race and income are investigated. The results demonstrate how this modeling approach can create new knowledge about vehicle emissions exposure. This approach also provides a method for proactively screening out regional plans, or specific projects within these plans, that are likely to cause air quality concerns. A proactive and regional air quality assessment can identify potential problems earlier in the planning process and a wider range of solutions, saving time, money and protecting public health. The detailed concentration maps can also be used to improve the siting of regulatory air quality monitors and provide more accurate exposure data for epidemiology studies.     

Electric vehicle park-charge-ride programs: A planning framework and case study in Chicago

In suburban areas, combining the use of electric vehicles (EV) and transit systems in an EV Park-Charge-Ride (PCR) approach can potentially help improve transit accessibility, facilitate EV charging and adoption, and reduce the need for long-distance driving and ensuing impacts. Despite the anticipated growth of EV adoption and charging demand, PCR programs are limited. With a focus on multi-modal trips, this study proposes a generic planning process that integrates EV infrastructure development with transit systems, develops a systematic assessment approach to fostering the PCR adoption, and illustrates a case implementation in Chicago. Specifically, this study develops a Suitability Index (SI) for EV charging locations at parking spots that are suitable for both EV charging and transit connections. SI can be customized for short-term and long-term planning scenarios. SI values are derived in Chicago as an example for (1) commuter rail stations (for work trips), and (2) shopping centers near transit stops as potential opportunities for additional weekday parking and EV charging (for multi-purpose trips/MPT). Furthermore, carbon emissions and vehicle miles travelled (VMT) across various travel modes and trip scenarios (i.e., work trips and MPT) are calculated. Compared to the baseline of driving a conventional vehicle, this study found that an EV PCR commuter can reduce up to 87% of personal VMT and 52% of carbon emissions. A more active role of the public sector in the PCR program development is recommended.     

Analysis of light rail rider travel behavior: Impacts of individual,built environment,and crime characteristics on transit access

This paper analyzes factors that influence the mode choice for trips between home and light rail stations, an often neglected part of a person’s trip making behavior. This is important for transit planning, demand modeling, and transit oriented development. Using transit survey data describing St. Louis MetroLink riders in the United States, this study found that some of the factors associated with increased shares of walking relative to other modes were full-time student status, higher income transit riders, and trips made during the evening. It was also found that crime at stations had an impact. In particular, crime made female transit riders more likely to be picked-up/dropped-off at the station. Females are more likely to be picked-up or dropped-off at night. Bus availability and convenience showed that transit riders that have a direct bus connection to a light rail station were more likely to use the bus. Private vehicle availability was strongly associated with increased probability of drive and park, when connecting to light rail.     

The influence of individuals’ environmental attitudes and urban design features on their travel patterns in sustainable neighborhoods in the UK

This paper explores the influence of individuals’ environmental attitudes and urban design features on travel behavior, including mode choice. It uses data from residents of 13 new neighborhood UK developments designed to support sustainable travel. It is found that almost all respondents were concerned about environmental issues, but their views did not necessarily ‘match’ their travel behavior. Individuals’ environmental concerns only had a strong relationship with walking within and near their neighborhood, but not with cycling or public transport use. Residents’ car availability reduced public transport trips, walking and cycling. The influence of urban design features on travel behaviors was mixed, higher incidences of walking in denser, mixed and more permeable developments were not found and nor did residents own fewer cars than the population as a whole. Residents did, however, make more sustainable commuting trips than the population in general. Sustainable modes of travel were related to urban design features including secured bike storage, high connectivity of the neighborhoods to the nearby area, natural surveillance, high quality public realm and traffic calming. Likewise the provision of facilities within and nearby the development encouraged high levels of walking.     

Traffic generated by mixed-use developments—A follow-up 31-region study

This study aims to improve a previously-developed methodology for predicting the traffic impacts of mixed-use developments (MXDs). In 31 diverse metropolitan regions across the United States, we collected consistent regional household travel survey data and computed built environment characteristics—D variables—of MXDs. Multilevel modeling (MLM) was employed to predict the probability of trips captured internally within MXDs, walking on internal trips, and travel mode choice on external trips, by trip purpose. Larger, denser, mixed-use, and more walkable MXDs show a larger share of trips internally, compared with conventional suburban developments. Those MXDs with good access to transit, employment, and destinations also show higher levels of walking, biking, and transit shares on external trips, thus helping to reduce traffic impacts on the external road network. Perhaps the most impressive finding is that well-designed MXDs have walk shares of more than 50 percent on internal trips. A k-fold cross-validation supports the robustness of our analyses.     

Metropolitan sprawl measurement and its impacts on commuting trips and road emissions

This study measures urban form as indicators of metropolitan sprawl and explores its impact on commuting trips and NO_x and CO₂ emissions from road traffic in all metropolitan statistical areas (MSAs) and four groups’ MSAs separated by population in the continental United States. Encompassing all MSAs, the study adds the accessibility factor to four existing factors: density, land use mix, centeredness, and street connectivity. The study establishes multivariate regression models between urban form, commuting trips, and emissions from road traffic while controlling for socioeconomic conditions. The study shows that urban form index and five urban form factors have a statistically significant association with commuting trips, NO_x and CO₂ emissions from road traffic. In four MSA groups as determined by MSA population size, higher values of urban form factors (i.e., lower sprawl) are statistically associated with more walking commuters. On the other hand, higher values of urban form factors are associated with fewer commuting vehicles per household in large MSAs with the moderate effect, a lower average commuting drive time in medium and small MSAs, and more commuters using public transportation in medium and large MSAs. This study provides an urban form index covering all metropolitan areas in the continental United States by adding another urban form factor, and the findings show that urban form factors have different effects on mode choices, drive time, and emission from road traffic depending on the MSA population size.     

Traffic and emissions impact of congestion charging in the central Beijing urban area: A simulation analysis

Congestion charging is being considered as a potential measure to address the issue of substantially increased traffic congestion and vehicle emissions in Beijing. This study assessed the impact of congestion charging on traffic and emissions in Beijing using macroscopic traffic simulation and vehicle emissions calculation. Multiple testing scenarios were developed with assumptions in different charging zone sizes, public transit service levels and charging methods. Our analysis results showed that congestion charging in Beijing may increase public transit use by approximately 13%, potentially reduce CO and HC emissions by 60–70%, and reduce NOx emissions by 35–45% within the charging zone. However, congestion charging may also result in increased travel activities and emissions outside of the charging zone and a slight increase in emissions for the entire urban area. The size of charging zone, charging method, and charging rate are key factors that directly influence the impact of congestion charging; improved public transit service needs to be considered as a complementary approach with congestion charging. This study is used by Beijing Transportation Environment and Energy Center (BTEC) as reference to support the development of Beijing’s congestion charging policy and regulation.     

Traditional neighborhoods and commuting in the San Francisco Bay area

Neo-traditional designs, proponents argue, reduce dependency on the automobile and provide attractive environments for walking, bicycling, and transit riding. This paper explores the extent to which this proposition holds for seven traditional neighborhoods in the San Francisco Bay Area that evolved around early streetcar services. Matched-pair comparisons of modal shares and trip generation rates for work trips are made between these neighborhoods and newer auto-oriented suburbs, controlling for the effects of income and, to a lesser extent, existing bus service levels. Pedestrian/bicycle modal shares and trip rates tended to be considerably higher, in some cases five time as high, in transit-oriented than in the paired auto-oriented neighborhood. Transit neighborhoods also averaged around 70 more daily transit work trips per 1,000 households than auto-oriented neighborhoods, though trip rates varied considerably among neighborhood pairs. Higher residential densities were also found to have a proportionately greater impact on transit commuting in transit-oriented than in auto-oriented neighborhoods. The paper concludes that in order to yield significant transportation benefits, neo-traditional development must be coordinated with larger regional planning efforts and public policy initiatives to reduce automobile dependency.     

Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior

This paper describes the characteristics of transportation demand management. The origin of transportation demand management (TDM) as it has evolved in the US is related to federal policy initiatives that first focused on improving the efficiency of the urban transportation system through operational improvements, and then incorporated concerns such as air quality and energy conservation into the transportation planning process. The paper then examines the effectiveness of TDM actions, and concludes that those actions most likely to increase the “price” of travel for single occupant vehicle use will be most effective. The paper identifies several strategies for improving the effectiveness of TDM actions in the context of regional transportation planning, including: incorporating TDM as part of the solutions for regional transportation planning, linking TDM to land use decisions, making the costs of travel more apparent to the user, and making TDM implementation more palatable to the general public.     

Total cost minimizing transit route structures considering trips towards CBD and periphery

The total cost minimizing approach to design transit systems is extended here beyond the usual dimensions of fleet (frequency) and vehicle size in order to examine the most appropriate spatial setting of transit lines as well. Motivated by the case of large cities in Latin America, characterized by high volumes of relatively long urban trips, we analyze the best ways to provide public transport services in a simplified urban setting represented by an extended cross-shaped network, where short trips (periphery–center) and long trips (periphery–periphery) coexist, generating economies of density. Three families of strategic lines structures are compared: mostly direct, feeder–trunk and hub and spoke. For each structure fleet and vehicle sizes are optimized, considering total (users’ and operators’) costs. The best structure is found parametrically in total passenger volume, the proportion of long trips and the value of the transfer penalty. The advantages of each dominating structure are explained in terms of factors like idle capacity, waiting or in-vehicle times and number of transfers.     

Conformity: How VMT-speed distributions can affect mobile emission inventories

Transportation conformity is a US regulatory process that requires that transportation modeling be integrated with air quality modeling. Consequently, every change to either modeling process is undertaken with great scrutiny by the regional governments, who have to use the models for demonstrating conformity. This paper explores the "trip versus link debate," which stems from the fact that the standard travel demand models used by most metropolitan planning organizations are primarily link oriented, while the air quality models have been primarily trip oriented. Using the Sacramento region we examine the effects on mobile source emissions inventories when speed-VMT distributions are constructed using the trip and link-based philosophies. The results of our study indicate that trip-based VMT-speed distributions produce consistently lower emissions estimates than the link-based distributions. We use the results to assert that deciding between a trip-based or link-based conformity modeling process involves more than the technical difficulty of changesto the models or the potential political ramifications, it involves assessing which method will provide the most accurate estimates of regional motor vehicle emissions. We also examine ways to think about constructing mobile source emission inventories.     

Preparing highway emissions inventories for urban scale modeling: A case study in Philadelphia

Highway emissions represent a major source of many pollutants. Use of local data to model these emissions can have a large impact on the magnitude and distribution of emissions predicted and can significantly improve the accuracy of local scale air quality modeling assessments. This paper provides a comparison of top–down and bottom–up approaches for developing emission inventories for modeling in one urban area, Philadelphia, in calendar year 1999. A bottom–up approach relies on combining motor vehicle emission factors and vehicle activity data from a travel demand model estimated at the road link level to generate hourly emissions data. This approach can result in better estimates of levels and spatial distribution of on-road motor vehicle emissions than a top–down approach that relies on more aggregated information and default modeling inputs.     

Built environment and pedestrian behavior at rail rapid transit stations in Bangkok

Urbanization and demands for mobility have spurred the development of mass rapid transit infrastructure in industrializing Asia. Differences between the character of pre-existing urban structure in these localities and worldwide precedents suggest a need for studies examining how new rapid transit systems function locally. This study of Bangkok’s elevated and underground rail systems identifies relationships between the built environment and pedestrian behavior surrounding stations. Based on details of 1,520 pedestrian egress trips from three elevated and three underground stations in 2006, multiple regression and analysis of variance (ANOVA) revealed that types of pedestrian destinations, reflecting land uses, were related to length of walking egress trips. Trips to shopping centers and office buildings were longer, while trips to eating places were shorter. The most common type of pedestrian trip recorded was to another vehicle, and trips to automobile taxis and motorcycle taxis figured prominently. Policy implications of the findings are considered.     

Estimating mortality impacts from vehicle emission reduction efforts: The Tune In and Tune Up program in the San Joaquin Valley

As a response to profoundly poor air quality and associated environmental justice concerns in the San Joaquin Valley region in California, the Tune In & Tune Up (TI&TU) program provides residents with free vehicle emissions testing and vouchers for smog repair. We used data on approximately 19,000 repaired TI&TU vehicles from 2012 to 2018, and several estimation techniques, to quantify a range of nitrogen oxides (NO_X) emissions prevented as a result of the program. We then calculated resulting mortality impacts from reduced exposure to fine particulate matter (PM_2.5) in the form of secondary nitrates. After applying a novel smog repair emissions abatement depreciation function, we find that six years of operation of the TI&TU program has reduced NO_X emissions by approximately 53–302 tons by the end of 2018. Using a concentration response function for ambient PM_2.5, we found that between 0.055 and 0.31 premature deaths have also been avoided. We present multiple methods for assessing public health impacts, which can be used as guidance for evaluating similar transportation-based emission reduction programs.     

Extent and correlates of walking in the USA

This paper examines data about walking trips in the US Department of Transportation’s 2001 National Household Travel Survey. The paper describes and critiques the methods used in the survey to collect data on walking. Using these data, we summarize the extent of walking, the duration and distance of walk trips, and variations in walking behavior according to geographic and socio-demographic factors. The results show that most Americans do not walk at all, but those who do average close to thirty minutes of walking a day. Walk trips averaged about a half-mile, but the median trip distance was a quarter of a mile. A significant percentage of the time Americans’ walk was spent traveling to and from transit trips. Binary logit models are used for examining utility and recreational walk trips and show a positive relationship between walking and population density for both. For recreational trips, this effect shows up at the extreme low and high ends of density. For utility trips, the odds of reporting a walk trip increase with each density category, but the effect is most pronounced at the highest density categories. At the highest densities, a large portion of the effect of density occurs via the intermediary of car ownership. Educational attainment has a strong effect on propensity to take walk trips, for both for utility and recreation. Higher income was associated with fewer utility walk trips but more recreational trips. Asians, Latinos, and blacks were less likely to take utility walk trips than whites, after controlling for income, education, density, and car ownership. The ethnic differences in walking are even larger for recreational trips.     

Impacts of built environment and emerging green technologies on daily transportation greenhouse gas emissions in Quebec cities: a disaggregate modeling approach

This paper aims to investigate the impact of the built environment (BE) and emerging transit and car technologies on household transport-related greenhouse gas emissions (GHGs) across three urban regions. Trip-level GHG emissions are first estimated by combining different data sources such as origin–destination (OD) surveys, vehicle fleet fuel consumption rates, and transit ridership data. BE indicators for the different urban regions are generated for each household and the impact of neighborhood typologies is derived based on these indicators. A traditional ordinary least square (OLS) regression approach is then used to investigate the direct association between the BE indicators, socio-demographics, and household GHGs. The effect of neighborhood typologies on GHGs is explored using both OLS and a simultaneous equation modeling approach. Once the best models are determined for each urban region, the potential impact of BE is determined through elasticities and compared with the impact of technological improvements. For this, various fuel efficiency scenarios are formulated and the reductions on household GHGs are determined. Once the potential impact of green transit and car technologies is determined, the results are compared to those related to BE initiatives. Among other results, it is found that BE attributes have a statistically significant effect on GHGs. However, the elasticities are very small, as reported in several previous studies. For instance, a 10 % increase in population density will result in 3.5, 1.5 and 1.4 % reduction in Montreal, Quebec and Sherbrooke, respectively. It is also important to highlight the significant variation of household GHGs among neighborhoods in the same city, variation which is much greater than among cities. In the short term, improvements on the private passenger vehicle fleet are expected to be much more significant than BE and green transit technologies. However, the combined effect of BE strategies and private-motor vehicle technological improvement would result in more significant GHGs reductions in the long term.     

Mitigating air pollution impacts of passenger ferries

Increasing regional mobility demand amid rising roadway congestion has motivated plans for passenger ferry expansion and modernization in many parts of the US. While this trend applies to ferry systems in Alaska, New York, Boston, and Washington state, efforts to expand ferry service in the San Francisco Bay Area are unique in scale and vision. Integrating ferry service into the regional, door-to-door transit system can significantly increase water-crossing capacity for commuters. However, to realize this potential, the ferry industry must meet several challenges associated with growth, including environmental impacts. In particular, concern over air pollution emissions from marine engines is motivating new comparisons between ferries and other transportation modes in terms of both mobility and air pollution. This paper describes the current debate about ferry system operation and expansion, and presents a parametric analysis comparing existing, uncontrolled ferry emissions to automobiles. Under all reasonable assumptions, we show that diesel-powered ferries without emissions controls will produce more NO_x and PM, but less CO per passenger-trip than if those people commuted by car under current conditions. This paper also projects the emissions from the expanded ferry system proposed for the San Francisco Bay Area, showing that a larger ferry fleet equipped with new engines meeting future EPA emissions standards could become one of the major non-road NO_x sources in the region. We conclude by outlining the alternatives and challenges to reduce ferry emissions so that they are more comparable to automobile emissions. Policy implications of these alternatives are also discussed.     

Time-based life-cycle assessment for environmental policymaking: Greenhouse gas reduction goals and public transit

As decision-makers increasingly embrace life-cycle assessment (LCA) and target transportation services for regional environmental goals, it becomes imperative that outcomes from changes to transportation infrastructure systems are accurately estimated. Greenhouse gas (GHG) reduction policies have created interest in better understanding how public transit systems reduce emissions. Yet the use of average emission factors (e.g., grams CO₂e per distance traveled) persists as the state-of-the-art masking the variations in emissions across time, and confounding the ability to accurately estimate the environmental effects from changes to transit infrastructure and travel behavior. An LCA is developed of the Expo light rail line and a competing car trip (in Los Angeles, California) that includes vehicle, infrastructure, and energy production processes, in addition to propulsion. When results are normalized per passenger kilometer traveled (PKT), life-cycle processes increase energy use and GHG emissions up to 83%, and up to 690% for smog and respiratory impact potentials. However, the use of a time-independent PKT normalization obfuscates a decision-maker’s ability to understand whether the deployment of a transit system reduces emissions below a future year policy target (e.g., 80% of 1990 emissions by 2050). The year-by-year marginal effects of the decision to deploy the Expo line are developed including reductions in automobile travel. The time-based marginal results provide clearer explanations for how environmental effects in a region change and the critical life-cycle processes that should be targeted to achieve policy targets. It shows when environmental impacts payback and how much reduction is achieved by a policy-specified future year.     

The net effects of the built environment on household vehicle emissions: A case study of Austin,TX

Growing concerns over climate change have led to an increasing interest in the role of the built environment to reduce transportation greenhouse gas (GHG) emissions. Many studies have reported that compact, mixed-use, and well-connected developments reduce vehicle miles traveled (VMT). Others, however, argue that densification and mixture of land uses can slow down vehicle movements, and consequently generate more driving emissions. Methodologically, VMT is only a proxy, not an exact measure of emissions. This study quantifies the net effects of the built environment on household vehicle emissions through a case study of Austin, TX. The study employed structural equation modeling (SEM) techniques and estimated path models to improve understanding of the relationship between the built environment and vehicle emissions. The results show a rather complex picture of the relationship. Densification can reduce regional vehicle emissions despite its secondary effect of reduced vehicle travel speed. A 1% increase in density was found to reduce household vehicle emissions by 0.1%. However, intensification of the design feature of the built environment in developed areas may work in the opposite direction; the modeling results showed a 1% increase in grid-like network being associated with 0.8% increase in household vehicle emissions. Based on the results, the study addressed the potential of and the challenges to reducing vehicle emissions through modifying the built environment in local areas.     

Subjective value of time in bus transit travel

A psychological scaling technique, magnitude estimation, is used to rate time spent on various elements of bus transit trips. Relative values of time are found for in-vehicle portions of trips, walking, waiting and transferring. Because magnitude estimation produces a ratio scale, results can be directly incorporated into modal choice analyses, route planning and evaluation procedures where monetary values of time are not necessarily required.