Air quality impact assessment of NOx and PM due to diesel vehicles in Delhi

The impact of diesel vehicles on NO_x and PM emissions at various locations in Delhi is assessed using two line source models; the California line source version 4 and the Indian Institute of Technology Line Source. The models offer comparable results but both under predicting the observed values with the Indian Institute of Technology model predictions being slightly better. The analysis also identifies hotspots due to concentrations of NO_x and PM and their diurnal variations is found to be greater in at night hours.     

On-road emissions from urban buses with SCR + Urea and EGR + DPF systems using diesel and biodiesel

Due to growing concerns about NO_x and particulate matter (PM) emissions from diesel engines, stricter regulations are being introduced requiring advanced emission control technology. In response the diesel industry has begun testing various emission control technologies and applying them. To assess vehicle renewal policies of bus companies, two exhaust after-treatment technologies are compared: the combination of a diesel particulate filter and an exhaust gas re-circulation system and the combination of a selective catalytic reduction and urea. On-board emission measurements were conducted under real-world driving conditions on a specific bus route in the city of Madrid.     

Bottleneck congestion and distribution of work start times: The economics of staggered work hours revisited

Since the seminal work of Henderson (Henderson, J.V., 1981. The economics of staggered work hours. Journal of Urban Economics 9 (3), 349–364), a number of studies have examined the effect of staggered work hours by analyzing models of work start time choice that consider the trade-off between negative congestion externalities and positive production externalities. However, these studies employed flow congestion models to describe traffic congestion. This study develops a model of work start time choice with bottleneck congestion and discloses the intrinsic properties of the model. To this end, this study extends Henderson’s model to incorporate bottleneck congestion. By utilizing the properties of a potential game, we characterize equilibrium and optimal distributions of work start times. We also show that Pigouvian tax/subsidy policies generally yield multiple equilibria and that the first-best optimum must be a stable equilibrium under Pigouvian policies, whereas the second-best optimum in which policymakers cannot eliminate queuing congestion can be unstable.     

User-centric interdependent urban systems: Using time-of-day electricity usage data to predict morning roadway congestion

Urban systems are interdependent as individuals’ daily activities engage using those urban systems at certain time of day and locations. There may exist clear spatial and temporal correlations among usage patterns across all urban systems. This paper explores such a correlation among energy usage and roadway congestion. We propose a general framework to predict congestion starting time and congestion duration in the morning using the time-of-day electricity use data from anonymous households with no personally identifiable information. We show that using time-of-day electricity data from midnight to early morning from 322 households in the City of Austin, can make reliable prediction of congestion starting time of several highway segments, at the time as early as 2 am. This predictor significantly outperforms a time-series predictor that uses only real-time travel time data up to 6 am. We found that 8 out of the 10 typical electricity use patterns have statistically significant affects on morning congestion on highways in Austin. Some patterns have negative effects, represented by an early spike of electricity use followed by a drastic drop that could imply early departure from home. Others have positive effects, represented by a late night spike of electricity use possible implying late night activities that can lead to late morning departure from home.     

Reducing port-related truck emissions: The terminal gate appointment system at the Ports of Los Angeles and Long Beach

Growth in international trade and changing patterns of production have resulted in greatly increased volumes of freight traffic in urban areas. Metropolitan areas serving as major nodes within the international trade network are particularly affected. In California, state regulation was imposed on port operations in an effort to mitigate congestion and air pollution associated with increased port-related trade. This paper presents an evaluation of the outcomes of California Assembly Bill (AB) 2650 at the Ports of Los Angeles and Long Beach. The legislation permitted terminals to adopt either gate appointments or off-peak operating hours as a means of reducing truck queues at gates. There is no evidence of reduced queuing or transaction times, and hence that AB 2650 did not result in reduced truck emissions.     

A forecast air pollution model applied to a hypothetical urban road pricing scheme: An empirical study in Madrid

Reducing the air pollution from increases in traffic congestion in large cities and their surroundings is an important problem that requires changes in travel behavior. Road pricing is an effective tool for reducing air pollution, as reflected currently urban road pricing outcomes (Singapore, London, Stockholm and Milan). A survey was conducted based on establishing a hypothetical urban road pricing system in Madrid (a random sample size n = 1298). We developed a forecast air pollution model with time series analysis to evaluate the consequences of possible air pollution decreases in Madrid. Results reveal that the hypothetical road pricing for Madrid could have highly significant effects on decreasing air pollution outside of the city and in the inner city during the peak operating time periods of maximum congestion (morning peak hours from 7:00 to 10:00 and evening peak hours from 18:00 to 20:00). Furthermore, this system could have significant positive effects on a shift toward using public transport and non-motorized modes inside the hypothetical toll zone. This reveals that the system has a high capacity to motivate a decrease in air pollution and impose more sustainable behavior for public transport users.     

Effects of the Los Angeles transit strike on highway congestion

In this paper we investigate the effect of the Los Angeles transit strike on highway congestion through analysis of highway sensor data, using both a before-and-after comparison, and a control group comparison. We found that average 5:00 a.m. to 10:00 p.m. traffic speeds declined by as much as 20% during the strike, and the average length of the rush period increased by as much as 200%, even though increases in traffic were small, despite the fact that transit riders constitute a small fraction of the traveling population. Speeds declined the most at locations upstream from the places where queues normally end. We believe that highways are especially susceptible to congestion during strikes because travelers have little opportunity to adjust and equilibrate their travel patterns, as is possible during ordinary periods of traffic growth.     

Trucking industry perceptions of congestion problems and potential solutions in maritime intermodal operations in California

Efficient maritime transportation is heavily dependent on the smooth operation of land transportation. Swift modal transfers are key to successful intermodal operations. In this paper we examine the efficiency of maritime intermodal transfer facilities in California, from the point of view of the trucking companies that use these facilities. We also examine the perceived effects of traffic network congestion on intermodal carriers' operations. Conclusions are based on a recent survey of nearly 1200 private and for-hire carriers operating in California. Over 450 of the companies surveyed had operations involving maritime ports in California. These provided a rich sample of responses and significant insights into the current state of the industry.     

Anticipating plug-in hybrid vehicle energy impacts in California: Constructing consumer-informed recharge profiles

Plug-in hybrid electric vehicles (PHEVs) can be powered by gasoline, grid electricity, or both. To explore potential PHEV energy impacts, a three-part survey instrument collected data from new vehicle buyers in California. We combine the available information to estimate the electricity and gasoline use under three recharging scenarios. Results suggest that the use of PHEV vehicles could halve gasoline use relative to conventional vehicles. Using three scenarios to represent plausible conditions on PHEV drivers’ recharge patterns (immediate and unconstrained, universal workplace access, and off-peak only), tradeoffs are described between the magnitude and timing of PHEV electricity use. PHEV electricity use could be increased through policies supporting non-home recharge opportunities, but this increase occurs during daytime hours and could contribute to peak electricity demand. Deferring all recharging to off-peak hours could eliminate all additions to daytime electricity demand from PHEVs, although less electricity is used and less gasoline displaced.     

Impacts of highway congestion on freight operations: perceptions of trucking industry managers

To better understand how road congestion adversely affects trucking operations, we surveyed approximately 1200 managers of all types of trucking companies operating in California. More than 80% of these managers consider traffic congestion on freeways and surface streets to be either a “somewhat serious” or “critically serious” problem for their business. A structural equations model (SEM) is estimated on these data to determine how five aspects of the congestion problem differ across sectors of the trucking industry. The five aspects were slow average speeds, unreliable travel times, increased driver frustration and morale, higher fuel and maintenance costs, and higher costs of accidents and insurance. The model also simultaneously estimates how these five aspects combine to predict the perceived overall magnitude of the problem. Overall, congestion is perceived to be a more serious problem by managers of trucking companies engaged in intermodal operations, particularly private and for-hire trucking companies serving airports and private companies serving rail terminals. Companies specializing in refrigerated transport also perceive congestion to be a more serious overall problem, as do private companies engaged in LTL operations. The most problematic aspect of congestion is unreliable travel times, followed by driver frustration and morale, then by slow average speeds. Unreliable travel times are a significantly more serious problem for intermodal air operations. Driver frustration and morale attributable to congestion is perceived to be more of a problem by managers of long-haul carriers and tanker operations. Slow average speeds are also more of a concern for airport and refrigerated operations.     

Substitution of bus for car travel in urban Britain: an economic evaluation of bus and car exhaust emission and other costs

Car exhaust emissions cause serious air pollution problems in many regions and, at a global level, contribute to climate change. Car use is also an important factor in other problems including traffic congestion, road accidents, noise pollution, community severance, and loss of countryside from road building. Forecasts of further increases in car ownership and use have prompted calls for policy-makers to encourage car users to switch to other forms of transport, particularly the bus. The effects of substituting bus for car travel in urban areas are simulated by specifying a spreadsheet model incorporating two types of car (petrol and diesel engine) and three types of bus (mini-, midi- and large bus). Six types of exhaust emission are considered for each vehicle type for the years 1992, 1995 and 1999: carbon monoxide, volatile organic compounds, nitrogen oxides, sulphur dioxide, (small) particulate matter and carbon dioxide. The paper provides a synthesis of monetary estimates of these exhaust emission and other costs. The other costs considered are traffic congestion, fuel consumption, noise pollution, road accidents and road damage. The exhaust emission monetary cost estimates, mainly from the United States and the United Kingdom, are discussed within the context of a sensitivity analysis which allows for changes in parameters such as load factors, emission factors and the individual exhaust emission cost estimates. The simulation results show that substitution of bus for car travel generally decreases the overall costs, particularly the costs of congestion, but increases exhaust emission costs if bus load factors are insufficiently high. In order to reduce exhaust emission costs from car to bus transfer at given load factors, the most effective policy option is to encourage the reduction of particulate emissions from bus engines. In terms of the overall costs, increasing bus load factors by relatively modest amounts can lead to substantial reductions in these overall costs. These results should be regarded as illustrative rather than definitive, given the uncertainties in a number of parameter estimates and the need for further research in areas not covered by the paper.     

A framework to evaluate policy options for supporting electric vehicles in urban freight transport

Electric vehicles (EVs) are considered as a feasible alternative to traditional vehicles. Few studies have addressed the impacts of policies supporting EVs in urban freight transport. To cast light on this topic, we established a framework combining an optimization model with economic analysis to determine the optimal behavior of an individual delivery service provider company and social impacts (e.g., externalities and welfare) in response to policies designed to support EVs, such as purchase subsidy, limited access (zone fee) to congestion/low-emission zones with exemptions for EVs, and vehicle taxes with exemptions for EVs. Numerical experiments showed that the zone fee can increase the company’s total logistics costs but improve the social welfare. It greatly reduced the external cost inside the congestion/low-emission zone with a high population, dense pollution, and heavy traffic. The vehicle taxes and subsidy were found to have the same influence on the company and society, although they have different effects with low tax/subsidy rates because their different effects on vehicle routing plans. Finally, we performed a sensitivity analysis. Local factors at the company and city levels (e.g., types of vehicle and transport network) are also important to designing efficient policies for urban logistics that support EVs.     

A methodology for planning bus service

A methodology to assist transportation planners in designing bus services is developed. The methodology is most relevant for use in locations where bus service of the type being studied does not currently exist and therefore no information is available on past choice behavior, or in instances when transferability of travel models estimated in another location is difficult. The methodology assesses the sensitivity of bus service characteristics upon intended bus usage using survey data collected in Orange County, California, by the Orange County Transit District (OCTD). The methodology is based on a nonparametric statistical test developed by Kolmogorov and Smirnov.Scenarios describing hypothetical operations of bus service are presented to survey respondents who indicate their intended levels of bus usage under each situation. Significant differences between the response distributions associated with pairs of scenarios are identified and potential ridership levels, as bus operations become more favorable, are assessed. Various user segments are then identified on the basis of their levels of intended bus usage and the corresponding marketing implications associated with each segment are discussed.     

Overcoming public aversion to congestion pricing

We have completed a survey of Southern California residents designed to examine whether the details of policy design can make congestion pricing more attractive to the motoring public. A congestion fee proposal is often regarded as simply a tax increase; also, especially in the US, motorists apparently regard the use of congestion fees as coercive, in that they often have few if any practical alternatives to paying the fee. Unlike most opinion surveys on congestion pricing, our survey was quite explicit about the fate of the collected revenues. For example, we presented respondents with policies that returned a substantial portion of the revenues to the public, either in the form of cash (through reductions in sales taxes and vehicle registration fees or through income tax credits) or in the form of coupons to be used for vehicle emissions equipment repair, transit, and the like. In addition, we examined whether the typically intense opposition to congestion pricing if applied only to a part of a roadway, leaving the motorist free to choose between free lanes and toll lanes. We find that a promise to offset the imposition of congestion fees by other taxes can result in a 7% point increase in support for congestion pricing policies, and the restriction of congestion pricing to a single lane on a freeway attracts from 9% to 17% points of additional support.     

Analysis of telecommuting behavior and impacts on travel demand and the environment

The discussion of whether, and to what extent, telecommuting can curb congestion in urban areas has spanned more than three decades. This study develops an integrated framework to provide the empirical evidence of the potential impacts of home-based telecommuting on travel behavior, network congestion, and air quality. In the first step, we estimate a telecommuting adoption model using a zero-inflated hierarchical ordered probit model to determine the factors associated with workers’ propensity to adopt telecommuting. Second, we implement the estimated model in the POLARIS activity-based framework to simulate the potential changes in workers’ activity-travel patterns and network congestion. Third, the MOVES mobile source emission simulator and Autonomie vehicle energy simulator are used to estimate the potential changes in vehicular emissions and fuel use in the network as a result of this policy. Different policy adoption scenarios are then tested in the proposed integrated platform. We found that compared to the current baseline situation where almost 12% of workers in Chicago region have flexible working time schedule, in the case when 50% of workers have flexible working time, telecommuting can reduce total daily vehicle miles traveled (VMT) and vehicle hours traveled (VHT) up to 0.69% and 2.09%, respectively. Considering the same comparison settings, this policy has the potential to reduce greenhouse gas and particulate matter emissions by up to 0.71% and 1.14%, respectively. In summary, our results endorse the fact that telecommuting policy has the potential to reduce network congestion and vehicular emissions specifically during rush hours.     

Impacts of commuting efficiency on congestion and emissions: case of the Hamilton CMA, Canada

This study uses IMULATE (Integrated Model of Urban LAnd use, Transportation, energy and Emissions) to examine the impacts of commuting efficiency on congestion and automobile emissions—specifically, non-methane hydrocarbons, carbon monoxide and nitrogen oxides—in the Hamilton Census Metropolitan Area. Estimates of these externalities are compared for two commuting scenarios: a base scenario of estimated commuting flows for 1991 and an optimal scenario in which the mean commuting time for all workers is minimized. The findings indicate that significant reductions in congestion and automobile emissions are possible by advocating policies that encourage greater commuting efficiency in the locational choices of workers. The analysis of jobs–housing balance as one such means suggests that a considerable proportion of commuting cannot be explained by geographical imbalances in the distributions of jobs and housing, and that workers consider many factors besides commuting costs in their locational choices. It is concluded that policies promoting jobs–housing balance as the principal strategy for facilitating more efficient commuting may not meet the expectations of policy-makers.     

Environmental equity in participation of the Clean Air School Bus Program: The case of New York State

The vast majority of American children rely on school buses for their daily trips to and from school, and almost all of these school buses operate on diesel fuel. Research has found that during their daily commute, children are exposed to unhealthy levels of diesel exhaust. We assess equity among school districts that chose to apply to the New York State Clean Air School Bus Program and those that did not. Binary logistic regression was employed to reveal the effects of demographics and other social economical factors on the choice of applying when controlling for other factors that are likely to affect a school district’s decision process. It was found that economic variables had a significant impact on the likelihood of a school district applying to the program.     

Factors driving public support for road congestion reduction policies: Congestion charging,free public transport and more roads in Stockholm,Helsinki and Lyon

Based on an across-the-board survey conducted among residents of Stockholm, Helsinki and Lyon, we explore the opinions on three policy measures to combat road congestion: congestion charging, free public transport and building more roads. The support for the two latter policies is substantially higher than the support for congestion charging, which is only supported by a majority in Stockholm. Self-interest is important for the formation of the opinion to all three policies. However, fundamental values and general political views, indicated by four attitudinal factors, are even more important in forming opinions towards the three transport policies. Of all attitudinal factors, the one indicating environmental concern most influences the support for all policies. Equity concerns, however, increase the support for free public transport and opposition to taxation increases the support for building more roads.Our results further suggest that the opinions towards free public transport and building more roads can be mapped along the left–right political axis, where Environment and Equity are to the left and Pricing and Taxation are to the right. However, the opinion towards congestion charging cuts right through the political spectrum. The impact of the fundamental values and self-interest variables are similar for Stockholm and Helsinki, indicating that even if experience increases the overall support for charging, it does not change the relative strength of different political arguments to any major extent.     

Freeway ramp control using fuzzy set theory for inexact reasoning

This paper presents a fuzzy controller for freeway ramp metering, which uses rules of the form: IF “freeway condition” THEN “control action.” The controller has been designed to consider varied levels of congestion, a downstream control area, changing occupancy levels, upstream flows, and a distributed detector array in its rule base. Through fuzzy implication, the inference of each rule is used to the degree to which the condition is true. Using a dynamic simulation model of conditions0fj at the San Francisco-Oakland Bay Bridge, the action of the fuzzy controller is compared to the existing “crisp” control scheme, and an idealized controller. Tests under a variety of scenarios with different incident locations and capacity reductions show that the fuzzy controller is able to extract 40 to 100% of the possible savings in passenger-hours. In general, the fuzzy algorithm displays smooth and rapid response to incidents, and significantly reduces the minute-miles of congestion.     

Bottleneck congestion pricing and modal split: Redistribution of toll revenue

The paper examines the question of the redistribution of toll revenue as seen in a bottleneck congestion model. Our objective is to analyse the impact of this redistribution on total cost and on modal split between railroad and road. Following Tabuchi’s two-mode model (Tabuchi, T., 1993. Bottleneck congestion and modal split. Journal of Urban Economics 34, 414-431.), we integrate a redistribution of toll revenue towards public transport into our study. In this context, we investigate two kinds of road toll regimes: a fine toll and a uniform toll. We will consider two types of railroad fare: when it is set equal to the marginal cost and when it is set equal to average cost. These models allow us to show that toll policy to be more efficient as long as toll revenue is directed towards public transport when the railroad fare is equal to average cost.