Impacts of freeway accidents on CO2 emissions: A case study for Orange County,California, US

Traffic congestion caused by traffic accidents contributes to CO₂ emissions. Generally, more efficient and prompt responses to accidents lead to reduced traffic congestion as well as CO₂ emissions. Here we assess the CO₂ emissions impacts of freeway accidents, applies an existing model to capture spatio-temporally congested regions caused by freeway accidents. A case study for the assessment of CO₂ emissions impacts of based on the results from the model is presented.     

Mathematical characterization of spatiotemporal congested traffic patterns: mixed speed data analysis in the greater Toronto and Hamilton area,Canada

This paper formulates a comprehensive methodology for analyzing, quantifying and identifying congestion characteristics based on speed distribution. Utilizing vehicle speed data, a mathematical approach is applied, in order to characterize roadway segments, in terms of travel reliability, congestion severity and duration. We argue that the Gaussian mixture model (GMM) and its parameter combination is the appropriate tool if we are to obtain quantitative congestion measures and rank roadway performance. A significant contribution of our approach is that it is based on assumptions regarding mixed components as well as speed distribution and can be applied to large databases. We test our framework on the greater Toronto and Hamilton area in Ontario, Canada, and conclude that congestion quantification through the application of the GMM can be successfully accomplished. Results indicate that speed patterns differ significantly between counties as well as days of the week.     

Computing the cost of traffic congestion: a microsimulation exercise of the City of Antofagasta,Chile

Abstract

This paper computes the cost of traffic congestion in the city of Antofagasta in Chile. A microsimulation is implemented where all the agents of the system travel across the transport network. The congestion cost is computed through the aggregation of the opportunity cost of people waiting within the transport system, as a consequence of traffic congestion. Monte Carlo experiments produced an approximated congestion cost of US$1.02 million during a typical working day. Moreover, the simulation provides useful information about the average traveling time for the 14 districts of the city.     

Modeling NOx and NO2 emissions from mobile sources: A case study for Hamilton, Ontario, Canada

This study characterizes the dispersion of emissions of oxides of nitrogen and nitrogen dioxide from traffic sources in the Hamilton census metropolitan area. The Integrated Model of Urban Landuse and Transportation for Environmental Analysis software was used to estimate emissions of oxides of nitrogen from traffic sources. The Air Pollution Model, was used to simulate dispersion of the traffic emissions over the city. The models account for the two primary wind directions in this region – the prevailing southwest and a secondary northeast direction. The results show a prominent triangle of high pollution defined by major roads and highways along the periphery of the Hamilton Harbour, at peak-hour. With southwest winds, residential areas along the northern shoreline of the Harbour are affected, while the western sections of the city are affected by northeast winds. High concentrations are persistent in some areas, for both wind directions. The resulting dispersion surfaces characterize the spatial distribution of traffic emissions and thus provide a means of assessing population exposure over the Hamilton area.     

The role of volume-delay functions in forecasting and evaluating congestion charging schemes: the Stockholm case

This paper uses observations from before and during the Stockkholm congestion charging trial in order to validate and improve a transportation model for Stockholm. The model overestimates the impact of the charges on traffic volumes while at the same time it substantially underestimates the impact on travel times. These forecast errors lead to considerable underestimation of economic benefits which are dominated by travel time savings. The source of error lies in the static assignment that is used in the model. Making the volume-delay functions (VDFs) steeper only marginally improves the quality of forecast but strongly impacts the result of benefit calculations. We therefore conclude that the dynamic assignment is crucial for an informed decision on introducing measures aimed at relieving congestion. However, in the absence of such a calibrated dynamic model for a city, we recommend that at least a sensitivity analysis with respect to the slope of VDFs is performed.     

Exploring the link between the neighborhood typologies,bicycle infrastructure and commuting cycling over time and the potential impact on commuter GHG emissions

This paper investigates the evolution of urban cycling in Montreal, Canada and its link to both built environment indicators and bicycle infrastructure accessibility. The effect of new cycling infrastructure on transport-related greenhouse gas (GHG) emissions is then explored. More specifically, we aim at investigating how commuting cycling modal share has evolved across neighborhood built-environment typologies and over time in Montreal, Canada. For this purpose, automobile and bicycle trip information from origin–destination surveys for the years 1998, 2003 and 2008 are used. Neighborhood typologies are generated from different built environment indicators (population and employment density, land use diversity, etc.). Furthermore, to represent the commuter mode choice (bicycle vs automobile), a standard binary logit and simultaneous equation modeling approach are adopted to represent the mode choice and the household location. Among other things, we observe an important increase in the likelihood to cycle across built environment types and over time in the study region. In particular, urban and urban-suburb neighborhoods have experienced an important growth over the 10 years, going from a modal split of 2.8–5.3% and 1.4–3.0%, respectively. After controlling for other factors, the model regression analysis also confirms the important increase across years as well as the significant differences of bicycle ridership across neighborhoods. A statistically significant association is also found between the index of bicycle infrastructure accessibility and bike mode choice – an increase of 10% in the accessibility index results in a 3.7% increase in the ridership. Based on the estimated models and in combination with a GHG inventory at the trip level, the potential impact of planned cycling infrastructure is explored using a basic scenario. A reduction of close to 2% in GHG emissions is observed for an increase of 7% in the length of the bicycle network. Results show the important benefits of bicycle infrastructure to reduce commuting automobile usage and GHG emissions.     

Estimating the environmental costs of port related emissions: The case of Kaohsiung

This study estimates the emission costs of ships and trucks in the Port of Kaohsiung, Taiwan, focusing mainly on particular matter and volatile organic compounds. By calculating annual ship and truck emissions we find that the major contributors are tankers, container ships and bulk ships and trucks. Using a bottom-up methodology, the combined environmental costs of ships and trucks are estimated to be over $123 million per year.     

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

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

Optimal toll locations and toll levels in congestion pricing schemes: a case study of Stockholm

As congestion pricing has moved from theoretical ideas in the literature to real-world implementation, the need for decision support when designing pricing schemes has become evident. This paper deals with the problem of finding optimal toll levels and locations in a road traffic network and presents a case study of Stockholm. The optimisation problem of finding optimal toll levels, given a predetermined cordon, and the problem of finding both optimal toll locations and levels are presented, and previously developed heuristics are used for solving these problems. For the Stockholm case study, the possible welfare gains of optimising toll levels in the current cordon and optimising both toll locations and their corresponding toll levels are evaluated. It is shown that by tuning the toll levels in the current congestion pricing cordon used in Stockholm, the welfare gain can be increased significantly, and furthermore improved by allowing a toll on a major bypass highway. It is also shown that, by optimising both toll locations and levels, a congestion pricing scheme with welfare gain close to what can be achieved by marginal social cost pricing can be designed with tolls being located on only a quarter of the tollable links.     

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

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

Influence of driving patterns on vehicle emissions: A case study for Latin American cities

On-board real-time emission experiments were conducted on 78 light-duty vehicles in Bogota. Direct emissions of carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_x) and hydrocarbons (HC) were measured. The relationship between such emissions and vehicle specific power (VSP) was established. The experimental matrix included both gasoline-powered and retrofit dual fuel (gasoline–natural gas) vehicles. The results confirm that VSP is an appropriate metric to obtain correlations between driving patterns and air pollutant emissions. Ninety-five percent of the time vehicles in Bogota operate in a VSP between −15.2 and 17.7 kW ton⁻¹, and 50% of the time they operate between −2.9 and 1.2 kW ton⁻¹, representing low engine-load and near-idling conditions, respectively. When engines are subjected to higher loads, pollutant emissions increase significantly. This demonstrates the relevance of reviewing smog check programs and command-and-control measures in Latin America, which are widely based on static (i.e., idling) emissions testing. The effect of different driving patterns on the city’s emissions inventory was determined using VSP and numerical simulations. For example, improving vehicle flow and reducing sudden and frequent accelerations could curb annual emissions in Bogota by up to 12% for CO₂, 13% for CO and HC, and 24% for NO_x. This also represents possible fuel consumption savings of between 35 and 85 million gallons per year and total potential economic benefits of up to 1400 million dollars per year.     

Public financing of private freight rail infrastructure to reduce highway congestion: A case study of public policy and decision making in the United States

As goods movement continues to increase it is expected to outpace infrastructure capacity in the United States. Moving a larger share of goods by rail rather than truck is a potentially cost effective part of a solution. Freight rail not only offers a substitute for truck trips but is a cleaner, more energy efficient, and safer alternative. Recently a number of private freight rail projects have received public funding. The public funds are aimed at increasing freight rail capacity with the goal of diverting some goods currently moved by truck to rail. While the benefits of moving goods by rail are relatively clear, it is unclear if public decision makers can effectively identify strategic rail investments that will achieve their policy goals. This study critically examines the analytical methods, models, and data that are commonly used to support decisions to provide public funds for private freight rail projects. This is accomplished through a case study of California’s Trade Corridors Improvement Fund program which provided $680 million for 11 freight rail projects. The study’s contributions include identifying critical analytical flaws and challenges affecting the benefit estimates that public funding decisions rely on. Improvements to current evaluation methods are also identified as are regulatory reforms and policy interventions that may offer more effective and reliable outcomes.     

Examining the effects of the built environment and residential self-selection on commuting trips and the related CO2 emissions: An empirical study in Guangzhou,China

Numerous studies have established the link between the built environment and travel behavior. However, fewer studies have focused on environmental costs of travel (such as CO₂ emissions) with respect to residential self-selection. Combined with the application of TIQS (Travel Intelligent Query System), this study develops a structural equations model (SEM) to examine the effects of the built environment and residential self-selection on commuting trips and their related CO₂ emissions using data from 2015 in Guangzhou, China. The results demonstrate that the effect of residential self-selection also exists in Chinese cities, influencing residents’ choice of living environments and ultimately affecting their commute trip CO₂ emissions. After controlling for the effect of residential self-selection, built environment variables still have significant effects on CO₂ emissions from commuting although some are indirect effects that work through mediating variables (car ownership and commuting trip distance). Specifically, CO₂ emissions are negatively affected by land-use mix, residential density, metro station density and road network density. Conversely, bus stop density, distance to city centers and parking availability near the workplace have positive effects on CO₂ emissions. To promote low carbon travel, intervention on the built environment would be effective and necessary.     

Well-to-wheel costs,primary energy demand,and greenhouse gas emissions for the production and operation of conventional and alternative vehicles

This study provides a comprehensive comparison of well-to-wheel (WTW) energy demand, WTW GHG emissions, and costs for conventional ICE and alternative passenger car powertrains, including full electric, hybrid, and fuel cell powertrains. Vehicle production, operation, maintenance, and disposal are considered, along with a range of hydrogen production processes, electricity mixes, ICE fuels, and battery types. Results are determined based on a reference vehicle, powertrain efficiencies, life cycle inventory data, and cost estimations. Powertrain performance is measured against a gasoline ICE vehicle. Energy carrier and battery production are found to be the largest contributors to WTW energy demand, GHG emissions, and costs; however, electric powertrain performance is highly sensitive to battery specific energy. ICE and full hybrid vehicles using alternative fuels to gasoline, and fuel cell vehicles using natural gas hydrogen production pathways, are the only powertrains which demonstrate reductions in all three evaluation categories simultaneously (i.e., WTW energy demand, emissions, and costs). Overall, however, WTW emission reductions depend more on the energy carrier production pathway than on the powertrain; hence, alternative energy carriers to gasoline for an ICE-based fleet (including hybrids) should be emphasized from a policy perspective in the short-term. This will ease the transition towards a low-emission fleet in Switzerland.     

Travel,transport and energy implications of university-related student travel: A case study approach

This study highlighted significant cultural differences and complexity in travel behaviour associated with travel to university across the UK and Ireland. This paper examines university travel behaviours and the implications for emissions, across the 2012–2013 academic year, based on responses from 1049 students across 17 universities in Ireland and the UK. Surveys were analysed to examine the trips of students both during term time and when accessing the universities each year. The data analysis in this paper examines three aspects of the transport implications of travel to and from university. Firstly the journey between university and term time address (or permanent address if the respondent does not have a separate term time address), secondly the journey between the university area and a separate permanent address where relevant; and thirdly implications for emissions resulting from university-related travel.The study found that student car users were more likely to be female, older students, or studying part time; male students were more likely to use active modes. The study indicated interesting differences between students living in different parts of the UK and Ireland. For example, it was found that there was a higher level of car dependence amongst Northern Irish students compared to other areas; and a greater variability in travel distances in Scotland and Northern Ireland. In England, car use was more pronounced when students travelled from their permanent address to term time address, and, as in Ireland, there was evidence of more car sharing on such trips. Public transport usage was more pronounced amongst Scottish students. The effect of these transport choices on emissions is significant and demonstrates the importance of education related trips to the development of a transport policy response. The analysis shows that annual emissions are highest for regular travel to and from university when a student has a permanent address rather than a separate term time and permanent address.     

The case for space: the measurement of capacity utilisation,its relationship with reactionary delay and the calculation of the capacity charge for the British rail network

In Britain, capacity charges are levied on train operators to cover the costs imposed by increased reactionary delays – i.e. the delay that an already late train causes to a following train. These charges are based on the link between capacity utilisation and the level of reactionary delay. An established method for measuring capacity utilisation was adopted called The Capacity Utilisation Index (CUI). In this paper, we propose an alternative methodology based on the theory that the level of reactionary delay will be determined by the minimum gaps that exist between trains. We test this measure with a new data-set for the East Coast Main Line and show that it performs better than CUI. Finally, we comment on the implications of this finding for charging and for the construction of timetables.     

Impacts of rail transit access on land and housing values in China: a quantitative synthesis

ABSTRACT

Rail transit investment has been viewed as a prominent policy instrument for local and regional development. However, little is known about to what extent the theorised changes in land and housing values arising from rail transit access can be substantiated by evidence in a large developing country context. This paper presents a quantitative review of empirical studies that analysed the impacts of rail transit access on land and housing values in China. We review empirical analyses in 67 studies from 1997 to 2018 for which we encode quantitative results along with a range of theoretically combinations of spatially contextual characteristics, data and methodological-design characteristics. The results show that there are significant variations in the size estimates of effects of rail transit access across studies. Such variations are associated with rail project types, data and methodological designs. Our study provides the insights on what has already been known and what needs to be known on evaluating real estate consequences of rail transit improvements in developing countries.     

Temporal trends and the effect of weather on pedestrian volumes: A case study of Montreal,Canada

This study examines the impact of weather on pedestrian activity, as well as the temporal trends of pedestrian flows in the city of Montreal, Canada. The direct and lagged effects of weather variables on hourly volumes are determined for the temperate and cold months, as well as for weekdays and weekends. Pedestrian hourly volumes are found to decrease in the winter. In downtown locations, there are three weekday pedestrian hourly peaks; a pattern distinctive from those observed in other surveys. Also, temperature, humidity, wind speed as well as direct and lagged effects of precipitation are the main factors affecting pedestrian activity. In winter, pedestrian flows are more sensitive to wind speeds and precipitation, and also during weekends than weekdays. Built environment plays a role not only in the magnitude but also in the temporal profile of pedestrian sidewalk activity. In comparison to bicycle ridership, pedestrian flows seem to be much less sensitive to weather.     

The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste,Italy

Universities, like other types of public and private institutions, when located in a city, have both positive and negative impacts on the area where they are situated. On the one hand, they contribute to the prestige of the area; on the other hand, they are large generators/attractors of traffic. The ability to successfully balance the pros and cons of the urban location of these large traffic-generating institutions is crucial for their success and for the livability of the city. In this paper this issue has been analyzed selecting as a representative case the University of Trieste.The aim of the research is to understand: (a) how mode choice decisions are made by the teaching and administrative staff and by the students at the various locations where academic activities take place, and (b) how they would be affected by 8 different transport management policies. It is found that changing the parking regulations (via the annual permit cost, the hourly parking fee, the number of parking spaces and the location of the parking lots) greatly influences mode choice in favor of bus use, especially for teaching and administrative staff and in the suburban locations. The students would be impacted by such changes only if an hourly parking tariff is introduced. The alternative approach of fully subsidizing the bus services would also have a large impact on bus ridership, affecting the mode choice in particular of the teaching staff and in the main university suburban sites.Since the implementation of these bus-favoring policies could face the opposition either of the university staff or of the bus company, two more balanced policy mixes were tested: the first one, increasing parking price and imposing new parking restrictions, would increase bus ridership by 19%; the second one, reducing both bus and parking subsidies, would increase bus ridership by 13%.     

Impacts of the urban parking system on cruising traffic and policy development: the case of Zurich downtown area,Switzerland

Transportation - Cruising-for-parking is a common phenomenon in many urban areas worldwide. Properly understanding and mitigating cruising can reduce travel times, alleviate traffic congestion, and...