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In this study, we examine if observed line-level changes in OCTA bus boardings could be partly attributed to AB 60, while controlling for differences in transit supply, socioeconomic variables, gas prices, and the built environment. Using fixed effects panel data models, we analyzed monthly boardings on different OCTA route classifications—local, community, Express, and station link routes—one year before (2014) and two years after (2015 and 2016) AB 60’s implementation.

Much has been written about the potential benefits of electric and connected vehicles. However, one important, but often overlooked, implication of electrifying trucks is that if they are powerful enough (such as the Tesla semi), they can eliminate the moving bottleneck or queuing effect created by slow-moving conventional heavy-duty trucks because electric trucks are much more responsive compared to conventional diesel trucks because electric motors provide maximum torque from a standstill. This could substantially increase road capacity in areas with high commercial truck traffic, especially around major ports or logistics complexes, thus alleviating the need to add new lanes to local freeways.

Health concerns and government restrictions during the COVID-19 pandemic caused a sharp increase in telecommuting (i.e., doing paid work at home or possibly an alternate worksite). In addition to reducing vehicle miles traveled (VMT), decreasing energy use, and lowering emissions of air pollutants and greenhouse gases (GHG), telecommuting may offer numerous other co-benefits, including increasing the worker pool, decreasing time and costs associated with travel, improving work-life balance, and decreasing stress. It may also stimulate greater use of non-motorized and active modes of travel (e.g., walking, biking, taking transit).

Concerns about the environmental impacts of transportation have made reducing vehicle miles traveled (VMT) a policy priority. One way to decrease VMT is to decrease the length of commuting trips, and to get commuters out of their private vehicles. Unfortunately, the average one-way commute keeps getting longer in the U.S., increasing from 25.1 to 27.6 minutes between 2005 and 2019. The percentage of work trips made by private vehicle has also soared, jumping from 66.9 percent in 1960 to 84.8 percent in 2019. As commuting typically occurs during traffic peaks, it is a major contributor to congestion and air pollution.

Shared micromobility (e.g., e-scooters, bikes, e-bikes) offers moderate-speed, space-efficient, and “carbon-light” mobility, promoting environmental sustainability and healthy travel. While the popularity and use of shared micromobility has grown significantly over the past decade, it represents a small share of total trips in urban areas. To better understand shared micromobility ridership, researchers from across the U.S. and the world have analyzed statistical associations between shared micromobility usage and various explanatory factors, including socio-demographic and -economic attributes, land use and built environment characteristics, surrounding transportation options (e.g., public transit stations), geography (e.g., elevation), and micromobility system characteristics (e.g., station capacity). To understand what these studies collectively mean in terms of expanding shared micromobility usage, we conducted a meta-analysis of 30 empirical studies and then developed robust estimates of factors that encourage ridership across different markets.

In spite of the popularity of e-shopping, only 16% of US adults have ordered groceries online, and 7 out of 10 of those who currently buy groceries online do so at most twice a month. Understanding the determinants of e-grocery shopping is important for grocers, supply chain managers, and urban planners. In this context, we first explore how deliveries from online shopping have been changing over time. From our analysis of the 2009 and 2017 National Household Travel Surveys, we found that online shopping has been embraced by increasingly diverse households, although income, education, and some racial/ethnic differences persist. Our analysis of the 2017 American Time Use Survey shows that Americans are 24 times more likely to shop for groceries in stores than online. Moreover, in-store grocery shoppers are more likely to be female and unemployed, but less likely to belong to younger generations, to have less than a college degree, or to be African American. The gender imbalance in grocery shopping is larger online than in stores, but e-grocery shoppers do not otherwise differ from the general population. Future travel and e-shopping surveys (especially for e-grocery) should combine time use and travel questions with retrospective questions about online purchases.

The purpose of this report is to provide a research-driven analysis of options that can put California on a pathway to achieve carbon-neutral transportation by 2045. The report comprises thirteen sections. Section 1 provides an overview of the major components of transportation systems and how those components interact. Section 2 discusses the impacts the COVID-19 pandemic has had on transportation. Section 3 discusses California’s current transportation-policy landscape. These three sections were previously published as a synthesis report. Section 4 analyzes the different carbon scenarios, focusing on “business as usual” (BAU) and Low Carbon (LC1). Section 5 provides an overview of key policy mechanisms to utilize in decarbonizing transportation. Section 6 is an analysis of the light-duty vehicle sector, section 7 is the medium- and heavy-duty vehicle sectors, section 8 is reducing and electrifying vehicle miles traveled, and section 9 is an analysis of transportation fuels and their lifecycle. The following sections are an analysis of external costs and benefits: section 10 analyzes the health impacts of decarbonizing transportation, section 11 analyzes equity and environmental justice, and section 12 analyzes workforce and labor impacts. Finally, future research needs are provided in section 13. The study overall finds that cost-effective pathways to carbon-neutral transportation in California exist, but that they will require significant acceleration in a wide variety of policies.

The purpose of this study overall is to explore the policy pathways to achieve a zero carbon transportation system in California by 2045. The purpose of this synthesis report is to describe the existing state of knowledge and policy related to energy use and greenhouse gas (GHG) emissions in the transportation sector, especially in California. It is an interim product of the larger study, which will use this report as the baseline and policy context sections. The report comprises four sections. Section 1 provides an overview of the major components of transportation systems and how those components interact. Section 2 explores key underlying concepts in transportation, including equity, health, employment, and environmental justice (EJ). Section 3 discusses California’s current transportation-policy landscape. Section 4 analyzes projected social, environmental, and economic outcomes of transportation under a “business as usual (BAU)” scenario—i.e., a scenario with no significant transportation-policy changes.

The purpose of this study overall is to explore the policy pathways to achieve a zero carbon transportation system in California by 2045. The purpose of this synthesis report is to describe the existing state of knowledge and policy related to energy use and greenhouse gas (GHG) emissions in the transportation sector, especially in California. It is an interim product of the larger study, which will use this report as the baseline and policy context sections. The report comprises four sections. Section 1 provides an overview of the major components of transportation systems and how those components interact. Section 2 explores key underlying concepts in transportation, including equity, health, employment, and environmental justice (EJ). Section 3 discusses California’s current transportation-policy landscape. Section 4 analyzes projected social, environmental, and economic outcomes of transportation under a “business as usual (BAU)” scenario—i.e., a scenario with no significant transportation-policy changes.

The trucking industry serves as the backbone of the nation’s economy. In 2018, approximately 3.5 million truck drivers were delivering over 70% of all freight tonnage in the United States, generating close to $800 billion in gross revenue annually.1 While 3.5 million truck drivers represents a significant number of jobs, it is not enough to satisfy demand. The trucking industry suffers from a chronic shortage of drivers. Nearly 70,000 additional heavy-duty tractor-trailer drivers in the United States were needed at the end of 2018, according to the American Trucking Associations. And COVID-19 has brought new challenges that may amplify or dampen the driver shortage and in turn impact supply chains. For example, what if a small percentage of long-haul truck drivers became ill? Would it cripple the industry? Would it significantly delay the delivery of essential medical supplies and equipment? New research from UC Irvine explored the challenges imposed by COVID-19 on truck drivers by conducting a literature review, looking at past crises, and interviewing academic and industry experts.

In spite of the critical importance of mobility for quality of life and economic well-being, the travel behavior of households without motor vehicles has received insufficient attention even though “carlessness” may bethe most vivid expression of mobility disadvantage in our car-centric society. Approximately 10.6 million (9 %) of U.S. households do not own a motor vehicle (car, pickup, van, SUV, or motorbike), including over one million in California. These “carless” households form two groups: (1) involuntarily carless households who are forced to live without cars, and (2) voluntarily carless households who chose to do so. Since one of the strategic goals of federal transportation policy is “to increase transportation choices and access to transportation services for all” it is essential to understand the travel behavior of households who are unable to own a motor vehicle. Indeed, many involuntarily carless households are experiencing economic hardship, disabilities, racial and age discrimination, or cultural barriers. Understanding the travel pattern of voluntarily carless households is also necessary to formulate policies aimed at decreasing vehicle use. Reducing personal vehicle use would help relieve congestion, decrease road accidents, improve air quality, cut emissions of greenhouse gases, and improve the health of people who switch to more active modes, such as walking and biking.

Free or reduced-fare transit passes have the potential to increase transit ridership, enhance the mobility of underserved groups (e.g., low-income, seniors, and youth), and reduce the environmental footprint of transportation. Under the right conditions, these programs can also help reduce traffic congestion and motor vehicle use. Transit agencies in different parts of the world have been experimenting with free or reduced-fare transit for decades, yet there are still substantial concerns about the impacts of free or reduced-fare transit on ridership as well as on the fiscal health of transit agencies. Some of these concerns linger partly because rigorous academic studies on free and reduced-fare transit passes are still rare.

To gain a better understanding of the current use and performance of free and reduced-fare transit pass programs, researchers at UC Irvine surveyed California transit agencies with a focus on members of the California Transit Association (CTA) during November and December 2019. Fifty-nine agencies, representing a broad cross-section of California transit operators, responded. Three quarters of respondents offered one or more free or reduced-fare transit pass programs in fiscal year 2018-19. While most respondents stated that free or reduced-fare transit passes increase ridership, many had concerns about the effect on their agency’s farebox recovery ratio, and to some extent on the fiscal health of their agency, though almost half of the respondents did not know the actual impacts. Those agencies offering student pass programs funded by student fees or employee programs funded by employers did not report any negative impact on ridership or on farebox recovery ratios. This confirms that free or reduced-fare transit pass programs structured like insurance programs (where a large group of potential transit riders—such as all students at a college or all employees in a large firm—periodically pays a lump sum to a transit agency while only a subset of that group actually uses transit) can be good for both riders and transit agencies. Free or reduced fare pass programs have an important role to play in transportation policy in California, but we should not ask too much from these programs. To achieve their full potential, they should be integrated into comprehensive policies to achieve California’s social and environmental goals.

Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM10 (PMx refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM2.5, and estimates selected human health impacts from PM2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM10 emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries.

In spite of their substantial number in the U.S., our understanding of the travel behavior of households who do not own motor vehicles (labeled “carless” herein) is sketchy. The goal of this paper is to start filling this gap for California. We perform parametric and non-parametric tests to analyze trip data from the 2012 California Household Travel Survey (CHTS) after classifying carless households as voluntarily carless, involuntarily carless, or unclassifiable based on a CHTS question that inquires why a carless household does not own any motor vehicle. We find substantial differences between our different categories of carless households. Compared to their voluntarily carless peers, involuntarily carless households travel less frequently, their trips are longer and they take more time, partly because their environment is not as well adapted to their needs. They also walk/bike less, depend more on transit, and when they travel by motor vehicle, occupancy is typically higher. Their median travel time is longer, but remarkably, it is similar for voluntarily carless and motorized households. Overall, involuntarily carless households are less mobile, which may contribute to a more isolated lifestyle with a lower degree of well-being. Compared to motorized households, carless households rely a lot less on motor vehicles and much more on transit, walking, and biking. They also take less than half as many trips and their median trip distance is less than half as short. This study is a first step toward better understanding the transportation patterns of carless households.

Local transportation agencies typically rely on traditional travel demand forecasting models that focus on highway and roadway improvements to optimize vehicular traffic.  These models are not equipped to evaluate active transportation strategies which align with current State of California policies such as reducing vehicle miles traveled to cut greenhouse gas emissions and fostering active transportation modes.  In this context, ITS at UC Irvine (ITS Irvine) was invited by Orange County Transportation Authority (OCTA) to propose, develop, and apply an approach to better model active transportation. This report represents the first phase of this work, which is a review of the recent literature on how to model demand for active transportation and an examination of OCTAM’s (OCTA’s own regional travel demand model) Active Transportation (AT) modeling tool to evaluate its potential for modification or incorporation into a new active transportation model.The following observations/suggestions are offered in this report: First, that OCTAM AT does not include variables that could impact people’s decision to leave their vehicles at home in favor of transit. Second, a number of conditions need to be jointly met for people to walk or bike. Third, OCTAM AT does not capture residential self-selection, which could be important here as people who do not plan to walk/bike self-select into car-oriented neighborhoods.

New forms of infrastructure are needed in a world characterized by the burdens of global climate change, a growing population, increasing socio-technical complexity, and natural and human stressors to our human systems. Enabling communities to transition to a more resilient configuration of infrastructures is crucial for establishing a distributed portfolio of processes and systems by which human needs may be met. This paper proposes a potential way to increase infrastructure resilience by supporting the creation of alternative, decentralized infrastructures (ADIs) composed of small-scale, heterogeneous systems and processes. We see two possible roles for these ADIs: first, they could be integrated with existing infrastructures in the industrialized world, thereby providing some redundancy during times of strain on larger centralized systems; and second, they could help developing communities leapfrog centralized and more capital intensive conventional infrastructure. We present a model for how ADI systems may be built, based on principles from software engineering. Finally, we identify some challenges that go beyond technical implementation details in the instantiation of ADIs, and offer some thoughts on how to address them. Copyright is held by the owner/author(s).

The Millennium Drought in Southeast Australia forced greater Melbourne, a city of 4.3 million people, to find innovative ways of increasing water supply and decreasing water demand. This article explores how water managers in Melbourne reacted to the crisis and evaluates the short-and long-term impacts of their decisions. Reduced water demand occurred primarily through residential and industrial water conservation programs, restrictions, together with emergency reductions in the environmental release of water to streams. The city also experimented with using recycled water, in place of surface water, to support agriculture in the Werribee Irrigation District. Water pricing was not strengthened during the drought, and thus not regarded as a drought demand management tool, primarily because Melbourne water companies lacked independent price-setting powers. Today, five years after the end of the Millennium Drought, gains in water conservation appear to be holding steady, but recycled water for irrigation has declined for various reasons. We contend that the Millennium Drought provided Melbourne with the opportunity to develop and implement a more integrated approach to water management. Many of the innovations it forged (e.g., distributed harvesting and use of stormwater) will continue to enhance the city’s resilience to drought and reduce its vulnerability to climate variability for years to come. Nevertheless, a challenge going forward is how to sustain these achievements in light of anticipated population growth and continued climatic change. This challenge—coupled with Melbourne’s successes—hold important lessons for water-stressed cities around the world.

Do U.S. households with battery electric vehicles (BEVs) drive less or more than U.S. households with internal combustion engine vehicles (ICEVs)? Answering this question is important to policymakers and transportation planners concerned with reducing vehicle miles traveled and the emissions of greenhouse gases from transportation. So far, this question has not been answered satisfactorily, possibly because of the relatively low number of EVs in the U.S. until recently, but also because of methodological issues. In this paper, we aim to fill this gap by analyzing data from the 2017 National Household Travel Survey (NHTS). We apply propensity score matching (PSM), a quasi-experimental method, to examine the differences in self-reported annual mileage and calculated daily mileage for various trip purposes among households with only BEVs (BEV-only), households with both BEVs and ICEVs (BEV+), and households without BEVs (non-BEV households). Our findings indicate that households with BEVs drive fewer annual miles than non-BEV households, but typically travel no less than they do for daily activities. This apparent discrepancy is likely due to taking fewer longer trips because the public charging infrastructure was still in its infancy in 2017, and its reliability was questionable. As technological progress is helping to overcome current battery limitations, policymakers may consider measures for fostering fast charging technologies while pondering new measures to fund both the charging infrastructure and the road network. [ABSTRACT FROM AUTHOR]

This paper explores how the Millennium Drought changed the way Melburnians source and use their water resources and discuss what these changes may portend for other large cities in water-scarce and climate-change-vulnerable regions of the world, in particular, the Southwest region of the United States.

Using RIO Tronics utility meter products as an industrial case study, the numeric Fraunhofer Toxic Potential Indicator (TPI) assessment tool is used to determine high impact materials with the aim of reducing the content of inherently toxic substances in these products. However, because product redesign with alternative materials affects entire components, overall component toxicity potential must also be explored. To achieve this, material TPI scores are aggregated into component TPI scores by 2 methods: 1) the Sum-Weighted Component TPI method, which considers the mass of materials in the component to assign an overall score, and 2) the Max Component TPI method, which scores the component with the highest impact material. With consideration of uncertainties from materials' toxicity information and mass estimates, key results from both scoring methods prioritized components that contain acrylonitrile-based polymers, polyvinyl chloride (PVC), and stainless steel. Furthermore, an alternative materials assessment is carried out to identify less-toxic substitutes to meet cost and technical constraints. Substitute materials such as Al alloys for stainless steel and high-density polyethylene for PVC show promise for a combination of toxicity reduction and cost-effectiveness. The new screening methodology described can help product designers systematically benchmark toxicity potential in parallel to cost and functionality.

Humans create vast quantities of wastewater through inefficiencies and poor management of water systems. The wasting of water poses sustainability challenges, depletes energy reserves, and undermines human water security and ecosystem health. Here we review emerging approaches for reusing wastewater and minimizing its generation. These complementary options make the most of scarce freshwater resources, serve the varying water needs of both developed and developing countries, and confer a variety of environmental benefits. Their widespread adoption will require changing how freshwater is sourced, used, managed, and priced.

The goal of this paper is to predict the fraction of time vehicles spend in different operating conditions from readily observable emission specific characteristics (ESC), which include geometric design, roadway environment, traffic characteristics, and driver behavior. We rely on a calibrated micro-simulation model to generate second-by-second vehicle trajectory data and use structural equation modeling to understand the influence of observed link ESC on vehicle operation. Our results reveal that 67 percent of link speed variance is explained by emission specific characteristics. At the aggregate level, geometric design elements exert a greater influence on link speed than traffic characteristics, the roadside environment, and driving style. Moreover, the speed limit has the strongest influence on vehicle operation, followed by facility type and driving style. This promising approach can be used to predict vehicle operation for models like MOVES, which was recently released by the Environmental Protection Agency.

The goal of this paper is to predict the fraction of time vehicles spend in different operating conditions from readily observable emission specific characteristics (ESC), which include geometric design, roadway environment, traffic characteristics, and driver behavior. We rely on a calibrated micro-simulation model to generate second-by-second vehicle trajectory data and use structural equation modeling to understand the influence of observed link ESC on vehicle operation. Our results reveal that 67 percent of link speed variance is explained by emission specific characteristics. At the aggregate level, geometric design elements exert a greater influence on link speed than traffic characteristics, the roadside environment, and driving style. Moreover, the speed limit has the strongest influence on vehicle operation, followed by facility type and driving style. This promising approach can be used to predict vehicle operation for models like MOVES, which was recently released by the Environmental Protection Agency.

Currently, there is no efficient way to estimate emissions from traffic on big transportation networks, such as the freeway links that connect downtown Los Angeles to the San Pedro Bay Ports complex. This transportation corridor is particularly vital because the ports handle more than a third of the U.S. container trade. Yet the economic vitality of this area is threatened by congestion and air pollution from freight operations.

We couple EMFAC with a dynamic mesoscopic traffic model to create an efficient tool for generating information about traffic dynamics and emissions of various pollutants (CO2, PM10, NOX, and TOG) on large scale networks. Our traffic flow model is the multi-commodity discrete kinematic wave (MCDKW) model, which is rooted in the cell transmission model but allows variable cell sizes for more efficient computations. This approach allows us to estimate traffic emissions and characteristics with a precision similar to microscopic simulation but much faster. To assess the performance of this tool, we analyze traffic and emissions on a large freeway network located between the ports of Los Angeles/Long Beach and downtown Los Angeles. Comparisons of our mesoscopic simulation results with microscopic simulations generated by TransModeler under both congested and free flow conditions show that hourly emission estimates of our mesoscopic model are within 4 to 15 percent of microscopic results with a computation time divided by a factor of 6 or more. Our approach provides policymakers with a tool more efficient than microsimulation for analyzing the effectiveness of regional policies designed to reduce air pollution from motor vehicles.

We couple EMFAC with a dynamic mesoscopic traffic model to create an efficient tool for generating information about traffic dynamics and emissions of various pollutants (CO2, PM10, NOX, and TOG) on large scale networks. Our traffic flow model is the multi-commodity discrete kinematic wave (MCDKW) model, which is rooted in the cell transmission model but allows variable cell sizes for more efficient computations. This approach allows us to estimate traffic emissions and characteristics with a precision similar to microscopic simulation but much faster. To assess the performance of this tool, we analyze traffic and emissions on a large freeway network located between the ports of Los Angeles/Long Beach and downtown Los Angeles. Comparisons of our mesoscopic simulation results with microscopic simulations generated by TransModeler under both congested and free flow conditions show that hourly emission estimates of our mesoscopic model are within 4 to 15 percent of microscopic results with a computation time divided by a factor of 6 or more. Our approach provides policymakers with a tool more efficient than microsimulation for analyzing the effectiveness of regional policies designed to reduce air pollution from motor vehicles.

Transportation system produces a large percentage of local pollutants including hydrocarbons (HC), carbon monoxide (CO), carbon dioxide from switching to alternative fuels, one measure would be to apply information and communication technologies to help us drive more smoothly so as to decrease pollutants emissions. This paper studies potential benefits of two green driving strategies based on inter-vehicle communication (IVC). Here green driving strategies are similar to intelligent speed adaptation , but we assume that an IVC-equipped vehicle is able to receive detailed trajectory information from other such vehicles with the help of IVC. For the purpose of evaluation, we integrate Newell’s car-following model and VT-Micro to establish a simulation platform. Market penetration rates of IVC-equipped vehicles and delivery delays of messages are two prominent features of IVC systems. We simulate stop-and-go traffic to calculate potential reductions in air pollutant emissions and fuel consumption under different market penetration rates and delivery delays. Results show that significant savings under frequent stop-and-go traffic conditions may be obtained with our strategies (HC: -88.3%, CO: -95.8%, NOx: -91.5%, CO2: -36.3%, Fuel Consumption: -71.3%) for the same travel time and almost the same overall travel distance. It is also shown that relatively large savings can be achieved even for a market penetration rate as low as 1% and communication delays larger than 2 minutes. In the future we will investigate environmental benefits of green driving strategies for more traffic scenarios and realistic communication scenarios.

The San Pedro Bay Port (SPBP) of Los Angeles and Long Beach is the largest container port in the U.S. Although the benefits of handling and hauling freight are enjoyed by the nation as a whole, the traffic congestion and air pollution created by the port falls mostly on the people who live and work nearby and along connecting freight corridors. These corridors include two busy freeways, the I-710 and the I-110, and an active rail link, the Alameda corridor. This research studied the environmental and health impacts of freight operations between the SPBP and downtown Los Angeles, some 22 miles to the north. In our analysis of health impacts, we focused on nitrogen oxide (NOX), a contributor to the formation of photo-chemical smog, and fine-grain particulates (PM10), which can lodge in peoples’ lungs with repeated exposure. We combined estimates of air pollutants from the I-710 and I-110 freeways, line-haul rail lines, and rail yards and looked at them for summer and winter. Four models were linked together to assess impacts: a microscopic traffic simulation model (TransModeler), which describes vehicle behavior; an emissions model (EMFAC 2007), which estimates the impacts of congestion on air pollution; a pollutant dispersion model (CALPUFF), which calculates how emissions move in a region’s atmosphere; and a health impact model (BenMAP), which calculates various pollutants’ effects on health using the incidence of various pollution-related illnesses.

The San Pedro Bay Ports (SPBP) complex of Los Angeles and Long Beach is the largest container port in the U.S., and a very important contributor to both California’s and the nation’s economies. Although the benefits of the SPBP activities are enjoyed by the whole country, the burden of the congestion and air pollution it generates falls mostly on the shoulders of people who live and work in the transportation corridor serving the SPBP. This corridor includes two busy freeways, the I-710 and the I-110, and a busy rail link, the Alameda corridor. The objective of this paper is to explore an integrated approach for evaluating the environmental and health impacts of freight operations between the SPBP complex and downtown Los Angeles, some 22 miles north. Our integrated approach combines a number of models, including a microscopic traffic simulation model and an emissions model to better estimate the impacts of congestion on air pollution, emission estimates from line-haul and switching train activities, a spatial dispersion model, and a health impact model. We analyze emissions for year 2005, which serves as a baseline in various air pollution inventories of the SPBP complex. Our results show that emissions concentrations are strongly affected by meteorological conditions and seasonal variations (winter is worse than summer); moreover, we found that health impacts from NOx and PM exposure exceed 200 million dollars, which justifies a number of regional initiatives to improve air quality. Our analysis is a starting point for analyzing the economic efficiency of these initiatives, which include modal shift (from trucks to trains) and the Clean Trucks Program.

The San Pedro Bay Ports (SPBP) of Los Angeles and Long Beach in Southern California is one of the largest port container complexes in the world, and the largest one is the United States. To decrease the air pollution associated with port operations, a number of measures have been adopted, including the Clean Trucks Program, which was introduced in 2008 to clean up the fleet of drayage trucks serving the SPBP. The objective of this paper is to quantify the reduction in emissions attributable to the Clean Trucks Program, with a focus on Nitrogen Oxide (NOx) and Particulate Matter (PM2.5). Our approach is innovative as it relies on micro-simulation to capture the link between congestion and pollutant emissions. We find that the Clean Trucks Program could contribute significantly to the emissions of NOx (~27%) and PM2.5 (~25%) for all the freeway traffic in our study area. These preliminary results suggest that the Clean Trucks Program is promising, but its cost-effectiveness should be analyzed.

Escalating concerns about air quality in Southern California have led authorities of the Ports of Los Angeles and Long Beach, also known as the San Pedro Bay Ports (SPBP), to consider and adopt a number of emission mitigation measures. One possibility is to shift to trains some of the containers currently transported by drayage trucks. This alternative is attractive because it would decrease congestion and air pollution on the main freeways (I-710 and I-110) and arterials that serve the SPBP. In addition, it would increase road safety along the busy Alameda freight corridor between the SBBP and downtown Los Angeles. One drawback would be an increase in pollutant emissions from train operations in the Alameda corridor, but trains tend to pollute less than trucks per ton-mile and new federal regulations are tightening the emission standards for diesel locomotives. The goal of this paper is to quantify the net impact of such a modal shift on the emissions of PM and NOx, which are the two air pollutants of most concern in the SPBP area. Our analysis relies on microscopic simulation to better capture emissions resulting from stop-and-go traffic on the freeways serving the SPBP. We find that emissions of both NOX and PM2.5 can be significantly reduced by switching from drayage trucks to trains. This suggests that modal shift should be encouraged, especially if there is unused 16 train capacity, and as long as it does not conflict with the shippers’ interests.