Alex Karner

Near-Roadway Air Quality: Synthesizing the Findings from Real-World Data

Despite increasing regulatory attention and literature linking roadside air pollution to health outcomes, studies on near roadway air quality have not yet been well synthesized. We employ data collected from 1978 as reported in 41 roadside monitoring studies, encompassing more than 700 air pollutant concentration measurements, published as of June 2008. Two types of normalization, background and edge-of-road, were applied to the observed concentrations. Local regression models were specified to the concentration-distance relationship and analysis of variance was used to determine the statistical significance of trends. Using an edge-of-road normalization, almost all pollutants decay to background by 115-570 m from the edge of road; using the more standard background normalization, almost all pollutants decay to background by 160-570 m from the edge of road. Differences between the normalization methods arose due to the likely bias inherent in background normalization, since some reported background values tend to underpredict (be lower than) actual background. Changes in pollutant concentrations with increasing distance from the road fell into one of three groups: at least a 50% decrease in peak/edge-of-road concentration by 150 m, followed by consistent but gradual decay toward background (e.g., carbon monoxide, some ultrafine particulate matter number concentrations); consistent decay or change over the entire distance range (e.g., benzene, nitrogen dioxide); or no trend with distance (e.g., particulate matter mass concentrations).

Modeling Bicycle Facility Operation: Cellular Automaton Approach

Current concerns surrounding regional air pollution, climate change, rising gasoline prices, and urban congestion could presage a substantial increase in the bicycle mode share. However, state-of-the-art methods for the safe and efficient design of bicycle facilities are based on difficult-to-collect data and potentially dubious assumptions regarding cyclist behavior. Simulation models offer a way forward, but existing bicycling models in the academic literature have not been validated with actual data. These shortcomings are addressed by obtaining real-world bicycle data and implementing a multilane, inhomogeneous cellular automaton simulation model that can reproduce observations. The existing literature is reviewed to inform the data collection and model development. It is found that the model emulates field conditions while possibly underpredicting bike path capacity. Since the simulation model can “observe” individual cyclists, it is ideally suited to determine level of service based on difficult-to-observe cycling events such as passing. Future work on data collection and model development is suggested.

Low-wage jobs-housing fit: identifying locations of affordable housing shortages

ABSTRACT Finding the right jobs-housing balance has long been an important concern for urban planners. More recently, attention has turned to jobs-housing fit – the extent to which housing price is well matched to local job quality. Prior analyses have been constrained by a lack of local data on job quality, making it difficult to identify the geography and scale of the problem. We introduce a new methodology for calculating the low-wage jobs-housing fit at both a jurisdiction and neighborhood scale that was designed in collaboration with affordable housing advocates and has been directly applied in urban planning and affordable housing policy efforts. Low-wage fit is particularly important because of ongoing difficulties with affordable housing provision and the disproportionate benefits of reducing transportation costs for low-income earners. We use the calculated metric at both a city and neighborhood scale to identify what can be learned from a low-wage jobs-housing fit metric that is not evident in traditional measures of jobs-housing balance. In contrast to jobs-housing balance, the low-wage fit analysis clearly highlights those jurisdictions and neighborhoods where there is a substantial shortage of affordable housing in relation to the number of low-wage jobs. Because of the geographic coverage of the data sources used, the results can be widely applied across the United States by affordable housing advocates, land-use planners, and policy makers.

Rural Communities and Transportation Equity in California's San Joaquin Valley

Smart growth policy and planning have tended to emphasize urban centers and regions, yet rural communities can also be important sites of innovation. Recent work demonstrated that these communities had surprisingly high levels of current and potential nonmotorized travel. Legislation in California mandates reductions in greenhouse gas emissions across all of the states metropolitan planning organization (MPO) regions, including the heavily rural San Joaquin Valley. Advocates for rural communities are finding common cause with more traditional environmental organizations around the vision of investing in and enhancing extant rural places as an alternative to leapfrog patterns of urban and suburban sprawl. Because of existing patterns of extreme disparity and legion underserved unincorporated communities, analyses that can help integrate social equity within regional planning are needed to serve and empower rural residents. This paper presents the results of several new analyses of the social equity dimensions of regional transportation plans in the San Joaquin Valley. Activity-based travel model data were used to analyze equity, with a particular focus placed on eight disadvantaged unincorporated communities identified by community advocates to be important demonstration sites. The investigators showed how improvements to traditional equity analysis could enhance the consideration of equity in the planning process and compared the results developed by innovative techniques with those obtained by use of their traditional counterparts. The methods outlined here can make substantial contributions to reduce disparities in rural communities, which would likely be overlooked in typical regional equity analyses because of their small size, and offer lessons for MPOs serving rural areas across the country.

Comparison of Two Common Approaches to Public Transit Service Equity Evaluation

Understanding the equity effects of transit service changes requires good information about the demographics of transit ridership. Onboard survey data and census data can be used to estimate equity effects, although there is no clear reason to conclude that these two sources will lead to the same findings. Guidance from the FTA recommends the use of either of these data sources to estimate equity impacts. This study made a direct comparison of the two methods for the public transit system in the Phoenix, Arizona, metropolitan area. The results indicated that although both sources were acceptable for FTA compliance, the use of one or the other could affect whether a proposed service change was deemed equitable. In other words, the outcome of a service change equity analysis could differ as a result of the data source used. To ensure the integrity and meaning of such analyses, FTA should recommend the collection and use of ridership data for conducting service change analyses to supplement approaches that are based on census data.

Mitigating Diesel Truck Impacts in Environmental Justice Communities: Transportation Planning and Air Quality in Barrio Logan, San Diego, California

This paper describes a series of sequentially implemented policies to mitigate local diesel truck impacts resulting from goods movement activity at two port facilities and simultaneously to improve traffic operations in the communities of Barrio Logan in San Diego, California, and Old Town in National City, California, both low-income communities of color. The paper provides the first comprehensive documentation of the unique process and solutions that emerged following the collaboration of all major stakeholders. Local impacts in Barrio Logan comprised air pollution, noise, and decreased pedestrian safety, while traffic operations in both communities were affected by congestion on the main freeway access, interchanges with insufficient capacity, and heavily mixed land uses both within and adjacent to the communities. These issues provided the impetus for the mitigation effort, the final implementation of which involved a permanent rerouting of all trucks weighing more than 5 tons to roads external to the community. Previous assessments of the project have described the extent to which mitigation strategies are expected to improve traffic operations or have assumed air quality improvements without carrying out an air quality analysis. A local-scale analysis of diesel particulate matter (DPM) emissions in Barrio Logan is given. The results show that while the mitigation did not result in improved regional air quality, it did significantly improve air quality in the primary affected corridor and resulted in a 99% reduction in DPM emissions and an 87% reduction in diesel truck vehicle miles traveled.

A multiobjective optimization model for locating affordable housing investments while maximizing accessibility to jobs by public transportation

This paper develops a new optimal location model for siting affordable housing units to maximize the accessibility of low-income workers to appropriate jobs by public transportation. Transit-accessible housing allows disadvantaged populations to reduce their reliance on automobiles, which can lead to savings on transportation-related expenditures. The housing location model developed here maximizes transit accessibility while reducing the clustering of affordable housing units in space. Accessibility is maximized using a high-resolution space-time metric of public transit accessibility, originally developed for service equity analysis. The second objective disperses subsidized housing projects across space using a new minimax dispersion model based on spatial interaction principles. The multiobjective model trades off accessibility maximization and affordable housing dispersion, subject to upper and lower bounds on the land acquisition and construction budget. The model is tested using data for Tempe, AZ including actual data for vacant parcels, travel times by light rail and bus, and the location of low-wage jobs. This model or similar variants could provide insightful spatial decision support to affordable-housing providers or tax-credit administrators, facilitating the design of flexible strategies that address multiple social goals.

Achieving Transportation Equity: Meaningful Public Involvement to Meet the Needs of Underserved Communities:

Civil rights and environmental justice laws and regulations aim to ensure fair processes and outcomes in regional transportation planning. Despite these requirements, people of color and low income tend to be disproportionately burdened while receiving few benefits. We argue that a key factor driving this disconnect is the nature of public involvement, in particular, a near-absence of meaningful public involvement through which affected residents can influence and shape decisions. We propose a new model for public involvement in transportation planning, based on a review of the literature and two policy and planning case studies. Our model identifies addressing the priority unmet needs of underserved communities as a fundamental touchstone of equity and argues for dedicating a stream of funding to meet those needs. Widespread application of this model, at the regional level and elsewhere, would likely result in improvements to both the general welfare and transportation equity conditions.

Miles per Gallon Illusions and Corporate Average Fuel Economy Distortions: When Even Transport Experts Have Trouble

Correctly interpreting the fuel consumption implications of improvements in vehicle fuel economy is important for the optimal selection of policies to achieve greenhouse gas reductions and energy independence. The findings of two surveys of transportation professionals are reported. It was found that transportation professionals—those individuals charged with the design and implementation of transportation policy—correctly interpreted fuel savings of vehicle replacement policies more often when fuel economy was presented in gallons per 100 mi than when it was presented in miles per gallon. By means of a discrete choice model, it was shown that transportation experts were more likely to calculate fuel savings with a linear approach when given fuel economy in miles per gallon. One important implication of this finding can be seen in how the standard fuel economy metrics have resulted in distorted incentives in U.S. corporate average fuel economy (CAFE) standards. It was found that CAFE standards did not directly motivate fuel savings in determining penalties, credit transfers between model years, and maximum allowable adjustments for both flex-fueled vehicles and credit transfers for different vehicle classes. The most notable result is an overemphasis on incentives for improvements in fuel economy to passenger vehicles and an under-emphasis on improvements for light trucks. These effects are distinct from well-known distortions associated with setting different standards for each vehicle class. Further, they might have been avoided had standards been written for gallons per mile. These findings point to the importance of understanding how people process information to improve policies targeting fuel savings.

‘Pray for transit’: Seeking transportation justice in metropolitan Atlanta:

On 4 November 2014, voters in Clayton County, Georgia, approved a referendum to join the Metropolitan Atlanta Rapid Transit Authority (MARTA), Atlanta’s regional transit agency. The historic vote was won by a margin not often seen in US electoral politics – 73% in favour with only 27% opposed. The vote was significant because it resulted from the sustained effort of Clayton County residents, non-profit advocacy organisations and elected officials to replace a public transit service that had been completely eliminated in early 2010. After opting not to join MARTA in 1971, Clayton County became increasingly Black and low-income as the economic centre of Atlanta shifted northwards. This demographic transition made public transit a necessity, and a bus service began in the county in 2001 in the wake of an air quality conformity lapse that jeopardised the region’s transportation funding. The rebirth of transit in 2014 and the success of the advocacy effort extends extant notions of urban regimes and governance in Atlanta and provides a unique example of a transportation equity win not forced by a legal challenge. Using primary and secondary source materials, this article illuminates precisely what made the Clayton County effort a success and looks to the future of public transit in the metropolitan region. While the precise conditions leading to MARTA’s expansion are not likely to be replicated elsewhere, the work highlights the potential for coalitions composed of elected officials and non-profit organisations supported by philanthropic capital to make broad and lasting changes to regional transportation systems.