The significant impacts on traffic and emissions of ferrying children to school in Beijing

After having implemented numerous regulations, e.g., coercive policies on vehicle use and purchase, it is becoming increasingly difficult to find further potential to control vehicle emissions in Beijing, as the air quality is still poor. This research provides a different approach for policy-makers to reduce vehicle emissions by managing demand. We found that parents ferrying their children to and from school is an important but long-neglected contributor to traffic congestion and vehicle emissions. This phenomenon is very common in China because of the social culture. In this research, parallel tests during both the school season and the non-school season were adopted, and emissions in both seasons were calculated based on travel demand and emission models. The results revealed that emissions factors (in g/km) for criteria pollutants and CO₂ increased by over 10% during rush hours during the school season due to traffic condition deterioration compared with non-school season. Daily HC, CO, NO_x, PM and CO₂ emissions from the passenger car fleet were 8.3%, 7.8%, 6.4%, 6.3% and 6.5% higher compared with those during the non-school season, respectively. These differences are greater than the total vehicular emission reduction by other control measures in 2014 in Beijing. For policy makers, providing safe and efficient ways to ferry children would be a useful and harmonious strategy for future vehicle emission control.     

Telecommuting and environmental policy: Lessons from the ecommute program

In 1999 the National Air Quality and Telecommuting Act established pilot telecommuting programs (ecommute) in five major US metropolitan areas. The major goal of the ecommute program was to examine whether a particular type of economic incentive, tradable emissions credits from telecommuting, represents a viable strategy for reducing vehicle miles traveled and improving air quality. A context is established for evaluating whether the envisioned trading scheme represents a feasible approach to reducing mobile source emissions and promoting telecommuting and a review of the limited experience with mobile source emissions trading programs is provided. Using two-and-one-half years of data collected in the ecommute program, telecommuting frequency, mode choice, and emissions reductions are examined. It is found that from a regulatory perspective, the most substantial drawback to such a program is its questionable environmental integrity, resulting from difficulties in designing sufficiently rigorous quantification protocols to accurately measure the emissions reductions from telecommuting. Such a program is not likely to be cost-effective because the emissions reductions from a single telecommuter are very small.     

Vehicle restrictions and CO2 emissions in Beijing – A simple projection using available data

The Beijing Government launched a new policy on restricting vehicle ownership in late 2010 to regulate the faster motorization and the excessive vehicular carbon dioxide (CO₂) emissions. In this paper, we first analyzed this policy and its effect on private passenger vehicle population. The private passenger vehicle population in Beijing from 2011 to 2020 was predicted under three different scenarios: no constraint (NC), current constraint (CC) and tighter constraint (TC). Then the assessment of vehicular emissions reduction benefits was made on the basis of private passenger vehicle population, vehicle kilometers traveled and CO₂ emission factors. It was projected that the CO₂ emissions in 2020 will reach 23.90, 15.55 and 13.23 million tons under NC, CC and TC respectively. The policy is very effective in controlling the faster motorization and reducing CO₂ emissions.     

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.     

Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach

Although telecommuting has become a popular option as a new mode of working, no theoretical or empirical consensus has been reached on its potential for substituting or generating travel. This study aims to evaluate the impact of a household head’s telecommuting on household travel while controlling for the interdependence within a household and across travel purposes, by applying seemingly unrelated censored regression models to data from the 2006 Household Travel Survey in the Seoul Metropolitan Area. In terms of vehicle kilometers traveled, the analysis shows that telecommuters’ non-commute and non-work trips as well as his/her household members’ non-work trips are greater than those of non-telecommuters and their household members’, whereas telecommuting partially reduces commuting trips. However, an analysis stratified by household type reveals that the difference for household members is significant only in households with less than one vehicle per employed member: in such households (with insufficient vehicles available), the vehicle otherwise used for mandatory travel, such as for the household head’s commute, can be used for non-commute purposes or by other household members if the household head does not use it for commuting. This implies that, when vehicle travel budgets of a given household are limited, this compensatory travel mechanism can make optimum use of limited resources (i.e., vehicles), but offsets the travel-substituting effect of telecommuting. Accordingly, to more precisely estimate the impact of telecommuting-promotion policies and apply them as part of travel demand management strategies, their counteracting effects among household members should be considered.     

Emission evaluation of inter-vehicle safety warning information systems

Driver inattentiveness is one of critical factors contributing to vehicle crashes. The inter-vehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards using connected vehicle environments. A novel feature of the proposed ISWS is its ability to detect hazardous driving events, such as abrupt accelerations and lane changes, which are defined as moving hazards with a higher potential of causing crashes. This study evaluated the effectiveness of the ISWS in reducing vehicle emissions and its potential for traffic congestion mitigation. This study included a field experiment that documented actual vehicle maneuvering patterns for abrupt accelerations and lane changes, which were used for more realistic simulation evaluations, in addition to normal accelerations and lane changes. Probe vehicles equipped with customized on-board units consisting of a global positioning system (GPS) device, accelerometer, and gyro sensor were used to obtain the vehicle maneuvering data. A microscopic simulator, VISSIM, was used to simulate a driver’s responsive behavior when warning messages were delivered. A motor vehicle emission simulator (MOVES) was then used to estimate vehicle emissions. The results show that reduction in vehicle emissions increased when the ISWS’s market penetration rate (MPR) and the congestion level of the traffic conditions increased. The maximum CO and CO₂ emission reductions achieved were approximately 6% and 7%, respectively, under LOS D traffic conditions. The outcomes of this study can be valuable for deriving smarter operational strategies for ISWS to account for environmental impacts.     

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.     

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

The influence of e-carsharing schemes on electric vehicle adoption and carbon emissions: An emerging economy study

Moving toward sustainable mobility, the sharing economy business model emerges as a prominent practice that can contribute to the transition to sustainability. Using a system dynamics modeling approach, this paper investigates the impacts of an e-carsharing scheme in carbon emissions and in electric vehicle adoption. We study the VAMO scheme located in Fortaleza, Brazil, as the first e-carsharing scheme in the country. We study two policies combined: a VAMO planned growth policy and a retirement policy for conventional vehicles. Our results show that the VAMO incentive policy is an important factor to reduce emissions and to increase awareness of electric vehicles, highlighting the role of the government as an institutional entrepreneur, stimulating and sustaining the VAMO scheme. The retirement policy in combination with the VAMO incentive policy obtained the best results in our simulations, reducing 29% of CO₂ emissions and increasing 36% electric vehicle adoption, when compared to the business-as-usual scenario. The main conclusions are that such e-carsharing schemes offer direct and indirect benefits to urban mobility (specially to electric vehicle adoption) and that they depend on how the government supports them.     

Estimating transboundary economic damages from climate change and air pollution for subnational incentives for green on-road freight

Subnational incentives to adopt zero emission vehicles (ZEVs) are critical for reducing the external economic damages posed by transportation to air quality and the climate. Few studies estimate these damages for on-road freight, especially at scales relevant for subnational policies requiring cross-border cooperation. Here, we assess the damages to US receptors from emissions of air pollutants (PM_2.5, NO_x, SO₂, NH₃), and greenhouse gases (CO₂, CH₄, N₂O) from medium and heavy duty freight trucking, and the benefits of ZEV adoption by census division in the Province of Ontario. We develop an integrated modelling framework connecting a travel demand model, a mobile emissions simulator, and a regression based marginal damages model of air pollutants and climate change. We estimate $1.9 billion (2010 USD) in annual cross-border damages, or $0.16/VKT, resulting from scaled up atmospheric emissions from a ‘typical day’ of medium and heavy duty truck traffic volume for Ontario in 2012. This implies approximately $8000 per truck per year in damages, which could inform an economic incentive for emission reduction. The provincial goal of 5% ZEV adoption would reduce GHG emissions in 2012 by 800 ktCO₂e, yielding $89 Million (2010 USD) in cross-border benefits annually, with air quality co-benefits of $83/tCO₂e. This result varies between −19% and 22% based on sensitivity analysis for travel and emissions models, though economic damages are likely the largest uncertainty source. Such advances in subnational scale integrated modeling of the environmental impacts of freight can offer insights into the sustainable design of clean freight policy and programs.     

Time-based life-cycle assessment for environmental policymaking: Greenhouse gas reduction goals and public transit

As decision-makers increasingly embrace life-cycle assessment (LCA) and target transportation services for regional environmental goals, it becomes imperative that outcomes from changes to transportation infrastructure systems are accurately estimated. Greenhouse gas (GHG) reduction policies have created interest in better understanding how public transit systems reduce emissions. Yet the use of average emission factors (e.g., grams CO₂e per distance traveled) persists as the state-of-the-art masking the variations in emissions across time, and confounding the ability to accurately estimate the environmental effects from changes to transit infrastructure and travel behavior. An LCA is developed of the Expo light rail line and a competing car trip (in Los Angeles, California) that includes vehicle, infrastructure, and energy production processes, in addition to propulsion. When results are normalized per passenger kilometer traveled (PKT), life-cycle processes increase energy use and GHG emissions up to 83%, and up to 690% for smog and respiratory impact potentials. However, the use of a time-independent PKT normalization obfuscates a decision-maker’s ability to understand whether the deployment of a transit system reduces emissions below a future year policy target (e.g., 80% of 1990 emissions by 2050). The year-by-year marginal effects of the decision to deploy the Expo line are developed including reductions in automobile travel. The time-based marginal results provide clearer explanations for how environmental effects in a region change and the critical life-cycle processes that should be targeted to achieve policy targets. It shows when environmental impacts payback and how much reduction is achieved by a policy-specified future year.     

Improving fuel consumption and CO2 emissions calculations in urban areas by coupling a dynamic micro traffic model with an instantaneous emissions model

Τhis study demonstrates the combination of a microscopic traffic simulator (AIMSUN) with an instantaneous emissions model (AVL CRUISE) to investigate the impact of traffic congestion on fuel consumption on an urban arterial road. The micro traffic model was enhanced by an improved car-following law according to Morello et al. (2014) and was calibrated to replicate measured driving patterns over an urban corridor in Turin, Italy, operating under adaptive urban traffic control (UTC). The method was implemented to study the impact of congestion on fuel consumption for the category of Euro 5 diesel <1.4 l passenger cars. Free flow and congested conditions led to respective consumption differences of −25.8% and 20.9% over normal traffic. COPERT 5 rather well predicted the impact of congestion but resulted to a much lower relative reduction in free flow conditions. Start and stop system was estimated to reduce consumption by 6% and 11.9% under normal and congested conditions, respectively. Using the same modelling approach, UTC was found to have a positive impact on CO₂ emissions of 8.1% and 4.5% for normal and congested conditions, respectively, considering the Turin vehicle fleet mix for the year 2013. Overall, the study demonstrates that the combination of detailed and validated micro traffic and emissions models offers a powerful combination to study traffic and powertrain impacts on greenhouse gas and fuel consumption of on road vehicles over a city network.     

Projecting adoption of truck powertrain technologies and CO2 emissions in line-haul networks

In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO₂ emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO₂ emissions by more than 25% throughout the period of study.     

Prospects for plug-in hybrid electric vehicles in the United States and Japan: A general equilibrium analysis

The plug-in hybrid electric vehicle (PHEV) may offer a potential near term, low-carbon alternative to today’s gasoline- and diesel-powered vehicles. A representative vehicle technology that runs on electricity in addition to conventional fuels was introduced into the MIT Emissions Prediction and Policy Analysis (EPPA) model as a perfect substitute for internal combustion engine (ICE-only) vehicles in two likely early-adopting markets, the United States and Japan. We investigate the effect of relative vehicle cost and all-electric range on the timing of PHEV market entry in the presence and absence of an advanced cellulosic biofuels technology and a strong (450 ppm) economy-wide carbon constraint. Vehicle cost could be a significant barrier to PHEV entry unless fairly aggressive goals for reducing battery costs are met. If a low-cost PHEV is available we find that its adoption has the potential to reduce CO₂ emissions, refined oil demand, and under a carbon policy the required CO₂ price in both the United States and Japan. The emissions reduction potential of PHEV adoption depends on the carbon intensity of electric power generation. Thus, the technology is much more effective in reducing CO₂ emissions if adoption occurs under an economy-wide cap and trade system that also encourages low-carbon electricity generation.     

Impact of telecommuting on spatial and temporal patterns of household travel

A spatial and temporal analysis of travel diary data collected during the State of California Telecommuting Pilot Project is performed to determine the impacts of telecommuting on household travel behavior. The analysis is based on geocoded trip data where missing trips and trip attributes have been augmented to the extent possible. The results confirm the earlier finding that the Pilot Project telecommuters substantially reduced travel; on telecommuting days, the telecommuters made virtually no commute trips, reduced peak-period trips by 60%, total distance traveled by 75%, and freeway miles by 90%. The spatial analysis of the trip records has shown that the telecommuters chose non-work destinations that are closer to home; they exhibited contracted action spaces after the introduction of telecommuting. Importantly, this contraction took place on both telecommuting days and commuting days. The telecommuters distributed their trips, over the day and avoided peak-period travel on telecommuting days. Non-work trips, however, show similar patterns of temporal distribution on telecommuting days and commuting days. Non-work trips continued to be made during the lunch period and late afternoon and evening hours.     

Does winter road maintenance help reduce air emissions and fuel consumption?

Winter road maintenance (WRM) has been shown to have significant benefits of improving road safety and reducing traffic delay caused by adverse weather conditions. It has also been suggested that WRM is also beneficial in terms of reducing vehicular air emissions and fuel consumptions because snow and ice on road surface often cause the drivers to reduce their vehicle speeds or to switch to high gears, thus decreasing fuel combustion efficiency. However, there has been very limited information about the underlying relationship, which is important for quantifying this particular benefit of a winter road maintenance program. This research is focused on establishing a quantitative relationship between winter road surface conditions and vehicular air emissions. Speed distribution models are developed for the selected Ontario highways using data from 22 road sites across the province of Ontario, Canada. The vehicular air emissions under different road surface conditions are calculated by coupling the speed models with the engine emission models integrated in the emission estimation model - MOVES. It was found that, on the average, a 10% improvement in road surface conditions could result in approximately 0.6–2% reduction in air emissions. Application of the proposed methodology is demonstrated through a case study to analyse the air emission and energy consumption effects under specific weather events.     

Evaluating the impacts of urban corridor traffic signal optimization on vehicle emissions and fuel consumption

This study investigates the impacts of traffic signal timing optimization on vehicular fuel consumption and emissions at an urban corridor. The traffic signal optimization approach proposed integrates a TRANSIMS microscopic traffic simulator, the VT-Micro model (a microscopic emission and fuel consumption estimation model), and a genetic algorithm (GA)-based optimizer. An urban corridor consisting of four signalized intersections in Charlottesville, VA, USA, is used for a case study. The result of the case study is then compared with the best traffic signal timing plan generated by Synchro using the TRANSIMS microscopic traffic simulator. The proposed approach achieves much better performance than that of the best Synchro solution in terms of air quality, energy and mobility measures: 20% less network-wide fuel consumption, 8–20% less vehicle emissions, and nearly 27% less vehicle-hours-traveled (VHT).     

On modeling telecommuting behavior: option, choice, and frequency

The current study contributes to the already substantial scholarly literature on telecommuting by estimating a joint model of three dimensions—option, choice and frequency of telecommuting. In doing so, we focus on workers who are not self-employed workers and who have a primary work place that is outside their homes. The unique methodological features of this study include the use of a general and flexible generalized hurdle count model to analyze the precise count of telecommuting days per month, and the formulation and estimation of a model system that embeds the count model within a larger multivariate choice framework. The unique substantive aspects of this study include the consideration of the “option to telecommute” dimension and the consideration of a host of residential neighborhood built environment variables. The 2009 NHTS data is used for the analysis, and allows us to develop a current perspective of the process driving telecommuting decisions. This data set is supplemented with a built environment data base to capture the effects of demographic, work-related, and built environment measures on the telecommuting-related dimensions. In addition to providing important insights for policy analysis, the results in this paper indicate that ignoring the “option” dimension of telecommuting can, and generally will, lead to incorrect conclusions regarding the behavioral processes governing telecommuting decisions. The empirical results have implications for transportation planning analysis as well as for the worker recruitment/retention and productivity literature.     

Transitioning to energy efficient vehicles: An analysis of the potential rebound effects and subsequent impact upon emissions

Given the shift toward energy efficient vehicles (EEVs) in recent years, it is important that the effects of this transition are properly examined. This paper investigates some of these effects by analyzing annual kilometers traveled (AKT) of private vehicle owners in Stockholm in 2008. The difference in emissions associated with EEV adoption is estimated, along with the effect of a congestion-pricing exemption for EEVs on vehicle usage. Propensity score matching is used to compare AKT rates of different vehicle owner groups based on the treatments of: EEV ownership and commuting across the cordon, controlling for confounding factors such as demographics. Through this procedure, rebound effects are identified, with some EEV owners found to have driven up to 12.2% further than non-EEV owners. Although some of these differences could be attributed to the congestion-pricing exemption, the results were not statistically significant. Overall, taking into account lifecycle emissions of each fuel type, average EEV emissions were 50.5% less than average non-EEV emissions, with this reduction in emissions offset by 2.0% due to rebound effects. Although it is important for policy-makers to consider the potential for unexpected negative effects in similar transitions, the overall benefit of greatly reduced emissions appears to outweigh any rebound effects present in this case study.     

Metropolitan size and the impacts of telecommuting on personal travel

Telecommuting has been proposed by policy makers as a strategy to reduce travel and emissions. In studying the metropolitan size impact of telecommuting on personal travel, this paper addresses two questions: (1) whether telecommuting is consistently a substitute or complement to travel across different MSA sizes; and (2) whether the impact of telecommuting is higher in larger MSAs where telecommuting programs and policies have been more widely adopted. Data from the 2001 and 2009 National Household Travel Surveys are used. Through a series of tests that address two possible empirical biases, we find that telecommuting consistently had a complementary effect on one-way commute trips, daily total work trips and daily total non-work trips across different MSA sizes in both 2001 and 2009. The findings suggest that policies that promote telecommuting may indeed increase, rather than decrease, people’s travel demand, regardless of the size of the MSA. This seems to contradict what telecommuting policies are designed for. In addition, model results show that the complementary impact of telecommuting on daily travel is lower in larger MSAs, in terms of both daily total work trips and daily total non-work trips.