Addressing the Impacts of Truck Idling and Searching for Parking on Environmental Justice Communities

Status

Complete

Project Timeline

January 1, 2022 - June 30, 2023

Principal Investigator

Project Team

Ivan Xiao, Carlos Otero, Daniel Rivera

Project Summary

Truck idling and searching for parking consume fuels and produce emissions that degrade air quality. In the U.S., more than 6 billion gallons of fuel at an estimated cost of $20 billion are wasted each year due to idling. An idling heavy‐duty diesel truck emits about 10 times more nitrogen oxides (NOx) than a passenger car, and truck idling emits more than 11 million tons of carbon dioxide and more than 180,000 tons of NOx per year, in addition to particulate matter and other air pollutants. Trucks usually idle near warehouses and distribution centers, and research has shown that these facilities are disproportionally located in disadvantaged communities. The California Air Resources Board (CARB) has been trying to address the negative consequences of community exposure to particulates from idling through various policies such as Airborne Toxic Control Measures. Moreover, emissions from idling or searching for parking are not the only problem; a recent study of disadvantaged communities in Southern California found that safety is also a critical factor. However, despite new regulations and technological improvements, the negative effects continue to occur, especially in disadvantaged communities. This research project addresses the issue of truck idling and searching for parking in disadvantaged communities in the Central Valley, specifically in Kern County, where the CARB has already identified the cities of Shafter, Arvin, and Lamont as environmental justice communities (as part of Assembly Bill 617 implementation). First, using publicly available information about parking and idling behavior from GeoTAB’s Intelligence Data tool, the team will conduct spatial analyses to identify truck parking and idling hotspots. This information will be enhanced with data from other public sources about the physical infrastructure, and socio‐demographic and economic conditions, to develop exploratory econometric models to identify the factors that contribute to idling time, or time and distance spent searching for parking. The team will use data from the San Joaquin Valley Air Pollution Control District’s Community Air Monitoring portal to determine whether higher emission levels are associated with locations with more idling or searching for parking. Using emission rates from the CARB’s Emission FACtor (EMFAC) model, the team will estimate the emissions from idling and searching for parking and quantify the vehicle mileage traveled in and around the hotspots. Second, the team will conduct fieldwork at the various locations (hotspots identified in AB 617 and other disadvantaged communities) to document actual truck parking/idling conditions to identify other factors that may affect this behavior, and any additional negative effects brought about. Through collaboration with the Kern Council of Governments and Caltrans, the team will gather input and feedback from the local impacted communities. It is expected that the process developed in this project could be replicated with other communities.

Assessing the Incorporation of Racial Equity into Analytical and Modeling Practices in Transportation Planning

Status

Complete

Project Timeline

February 15, 2021 - August 31, 2021

Principal Investigator

Project Team

Silvia González, Gian Claudia Sciara

The Spatial Dilemma of Sustainable Transportation and Just Affordable Housing

Status

Complete

Project Timeline

July 20, 2020 - June 30, 2021

Principal Investigator

Campus(es)

UCLA

Project Summary

Siting subsidized affordable housing in dense urban areas near transit can help the state meet its environmental goals by reducing vehicle travel and lowering the amount of vehicle miles traveled (VMT). However, more information is needed on exactly how best to allocate housing subsidies that both improve access to economic and educational opportunities for underrepresented groups, and improve mobility throughout the state more broadly while reducing VMT. This project will address the challenge of identifying neighborhoods that are best suited to promoting the state’s housing and environmental goals. The research will look at VMT rates in neighborhoods with affordable housing and examine the access and environmental benefits of subsidized affordable housing near transit in dense, urban areas. The project will assemble tract-level data and indicators, and will analyze changes in the location of subsidized and non-subsidized housing between 2007 and 2018 to determine if the current and expected future distribution of affordable housing is consistent with the state’s VMT reduction goals. Findings from this analysis will be used to identify target priority areas for renters at the policy and program levels, including the siting of new federal Low-Income Housing Tax Credit construction. In addition, the project will examine if and how transportation considerations are being incorporated into three important and innovative housing programs, which have a shared goal of increasing residential choice and mobility.

By Transit, By-Right: How Housing Development Approval Processes Can Support Higher Transit-Friendly Density

Status

Complete

Project Timeline

July 20, 2020 - June 30, 2021

Principal Investigator

Project Team

Michael Manville, Shane Phillips, Nolan Gray

Campus(es)

UCLA

Project Summary

Density is important for successful transit service, and recent state and local housing policies tie production to transit proximity. Multifamily housing, however, often faces many obstacles. One important obstacle is that most cities evaluate transit-adjacent multifamily housing developments with discretionary processes. Discretionary approval is slow and uncertain: developers and city officials negotiate project-by-project, sometimes adding years to project timelines. The resulting delays and conditions can depress housing production and raise costs, with the result being fewer transit-accessible homes. An alternative is by-right approvals, which automatically approve projects that meet published standards, bringing housing to market quicker and at a lower cost. By-right approval could deliver denser and more affordable housing to urban areas, supporting increased transit ridership and other mobility goals. Because by-right approval is relatively rare, however, estimates of how much more housing it could deliver remain vague. This project used the City of Los Angeles’ Transit-Oriented Communities (TOC) program to help identify the role of by-right approval in delivering more housing near transit. The TOC program presents a rare opportunity to compare the impact of by-right and discretionary approvals in a single political and market context. The analysis compared costs, project timelines, and community benefits of by-right and nearby discretionary projects. The research team estimated reductions in project costs and time to market resulting from by-right approvals compared to affordable units provided by developers. This quantitative analysis was complemented by interviews with developers, community-based organizations, lenders, city officials, and others. The research team found that by-right projects were permitted 28% faster than discretionary projects, controlling for project and neighborhood characteristics. By-right projects also had less variance in their approval times, suggesting that by-right approval offers not just more speed but more certainty.

Changes in Traffic Patterns and Localized Air Quality in Southern California

Status

Complete

Project Timeline

June 17, 2020 - December 1, 2021

Principal Investigator

Shams Tanvir

Project Summary

This project will develop an integrated analytical framework to determine changes in traffic at various scales (local, corridor level, and regional) due to the COVID-19 sheltering-in-place orders measures and conduct an analysis of the relationship of traffic-related changes to critical air pollutant concentrations. Traffic data and air quality data will be used from various existing sources, along with satellite-based measurements to complement the land-based measurements. The research team will estimate spatial-temporal changes in emissions for several traffic-related pollutants (e.g., NOX, CO, CO2, and HC). The team will then conduct a map-based relationship analysis between localized air-quality monitoring data and the estimated emissions. Finally, the team will overlay the map on CalEnviroScreen maps and correlate the changes with geographic locations of disadvantaged communities.

Autonomicity: A Modeling Framework for Equitable Policy Analysis for Future Transportation

Status

In Progress

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Campus(es)

UC Irvine

Project Summary

An agent‐based simulation platform (“Autonomicity”) has been under development at UCI with SB‐1 funds. This platform has the necessary modules with proper state‐of‐the art routing, ride‐matching, pricing and other algorithmic components, as well as the real‐time communication among them. While the platform itself is not network‐specific, future mobility requires a study context, and a network in the city of Irvine, CA, is currently incorporated. This proposal is to develop the platform as a policy tool to study efficient and equitable/fair allocation of transportation supply, with methodological focus on congestion pricing under traveler heterogeneity. Current congestion pricing schemes may cause social barriers for low‐income populations. Thus, this project devises a smart mobility platform to study equitable options where travelers desiring a faster travel option pay for it, and travelers willing to yield his/her fastest option receive incentives. New behavioral paradigms such as envy‐theory will be used. Two main modules introduced in Autonomicity will be: 1) a pricing module to find the optimal tolls/incentives and 2) a dynamic traffic assignment module to find optimal systemwide traffic patterns. The research will result utilities for a user‐friendly decision‐support tool for policymakers.

Identifying Types of Telecommuters based on Daily Travel and Activity Patterns

Status

Complete

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Campus(es)

UC Irvine

Project Summary

With the recent advent of telecommunications and information technologies, telecommuting becomes a rising trend as one of the most important alternative work arrangements. Moreover, due to the current worldwide outbreak of the COVID-19 disease, this choice has turned out to be a more vital one than ever. It is, therefore, crucial to identify the potential groups of workers who are more likely to be the telecommuters and to understand how the telecommuters schedule their daily activities and travel. The goal of this research is to address these issues. In particular, the team will perform the following three tasks: (1) identification of a number of distinct groups of telecommuters with a representative activity-travel pattern and a similar degree of telecommuting adoption (2) finding out similarities and differences in activity-travel behavior between national-level and regional-level (California) telecommuters and between commuters and telecommuters, and (3) investigation of impacts of telecommuting on individual’s time-use and tour behavior as well as the overall transportation system. Two large household travel survey datasets—2012 California Household Travel Survey (CHTS) and 2017 National Household Travel Survey (NHTS) will be used to conduct necessary analysis. This research is expected to provide valuable insights to policy makers on various telecommuter groups and their activity-travel patterns, adoption of telecommuting, and its impacts on travel.

COVID-19, Commuting, and E-Shopping: Understanding Current and Future Impacts in California

Status

Complete

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Project Team

Lu Xu

Project Summary

With widespread business closures and stay-at-home restrictions due to COVID-19, commuting has dropped while telecommuting and e-commerce have soared. This joint UC Berkeley/UC Irvine project seeks to understand opportunities and potential impacts of COVID-19 on commuting and e-commerce. The research team proposes a mixed-method approach comprised of expert interviews, focus groups in Northern and Southern California, an online survey of Californians (n=~1,000), and a survey of super commuters (n=up to 500). The survey of the California population will show how travelers have been affected by COVID-19 for commuting and shopping and provide vital information about mode shift, public transit use, and willingness to share transportation post COVID-19. Understanding how Californians work and shop is critical to informing a number of policies at various levels of government including: AB/SB 32 (California’s Climate Change Solutions Act); SB 375 (Smart Growth Strategies); SB 743 (Converting Level of Service to VMT metrics under the California Environmental Quality Act); and other local and state transportation demand management (TDM) and commute trip reduction laws, ordinances, and policies. The data collected on goods delivery behavior will also have widespread implications, such as recommending a new set of TDM policy strategies for retailers, freight/supply chains management, and other stakeholders.

Identifying Strategies to Preserve Transit-accessible Affordable Housing

Status

Complete

Project Timeline

August 19, 2020 - September 30, 2021

Principal Investigator

Project Team

Madeleine Parker

Campus(es)

UC Berkeley

Project Summary

California’s expiring affordable housing covenants pose a barrier to not only its affordable housing supply, but also its greenhouse gas reduction goals. Working with the Southern California Association of Governments, this study would address the following research questions to assist policymakers preserve the affordability of housing with expiring covenants, particularly near transit. First, which developments are important to prioritize, based on covenant expiry timing, public transit access, and other factors? Second, what strategies are most effective at preserving affordable housing with expiring covenants, and how might a regional entity best facilitate this process? Using datasets on affordability covenants, high-frequency transit access, job accessibility, and opportunity maps, this research will first determine the order in which developments should be targeted. By analyzing the developments that have been converted to market-rate in the past, the research team will identify the building, neighborhood, and market factors that best predict building conversion. Interviews with affordable housing intermediaries will help identify the optimum timing for outreach in order to prevent conversion. After a review of local and regional strategies to preserve affordable housing, this research will develop a framework for affordable housing preservation at the regional and local scales.

Measuring Changes in Air Quality from Reduced Travel in Response to COVID-19

Status

Complete

Project Timeline

May 1, 2020 - March 31, 2022

Principal Investigator

Project Summary

The major source of oxides of nitrogen (NOx) that produce ground-level ozone (O3) come from mobile sources. Model calculations and ambient measurements both suggest that major California cities are currently in a “NOx-limited” regime where decreasing NOx concentrations lead to higher O3 concentrations, making current emissions control programs counter-productive in the short term. Shifting traffic patterns associated with COVID-19 may have reduced NOx emissions from mobile sources by more than ~50% in densely populated urban areas in California. This “natural experiment” provides an opportunity to (i) test the ability of models to simulate O3 response to deep cuts to ambient NOx concentrations, (ii) more accurately predict the amount of NOx reduction needed to achieve O3 benefits, and (iii) improve confidence in the long-term benefits of emissions control plans. This project will collect air pollution measurements using a modular transportable smog chamber in urban locations adjacent to major freeways in the City of Sacramento and the City of Redlands both during and after COVID-19 stay-at-home orders. The project team will then use chemical transport models (CTMs) to predict O3 concentrations during the time period when COVID-19 shelter-in-place mandates have greatly reduced NOx emissions from mobile sources. Predictions will be compared to the actual air pollution measurements collected. The ability of the modeling systems to accurately predict ambient ozone concentrations in the presence of these large emissions perturbations will verify the completeness of the model chemical mechanism, the accuracy of the model emissions inventory, and the effectiveness of emissions control programs that seek to reduce O3 concentrations by reducing NOx emissions. The evaluated modeling systems will be used to predict how O3 concentrations respond to a range of NOx and volatile organic compounds emissions controls and predict how much further NOx emissions need to decrease in order to achieve O3 benefits and in what year those O3 benefits will start to appear.