Individual exposure to traffic related air pollution across land-use clusters

In this study, we estimated the transportation-related emissions of nitrogen oxides (NO_x) at an individual level for a sample of the Montreal population. Using linear regression, we quantified the associations between NO_x emissions and selected individual attributes. We then investigated the relationship between individual emissions of NO_x and exposure to nitrogen dioxide (NO₂) concentrations derived from a land-use regression model. Factor analysis and clustering of land-uses were used to test the relationships between emissions and exposures in different Montreal areas. We observed that the emissions generated per individual are positively associated with vehicle ownership, gender, and employment status. We also noted that individuals who live in the suburbs or in peripheral areas generate higher emissions of NO_x but are exposed to lower NO₂ concentrations at home and throughout their daily activities. Finally, we observed that for most individuals, NO₂ exposures based on daily activity locations were often slightly more elevated than NO₂ concentrations at the home location. We estimated that between 20% and 45% of individuals experience a daily exposure that is largely different from the concentration at their home location. Our findings are relevant to the evaluation of equity in the generation of transport emissions and exposure to traffic-related air pollution. We also shed light on the effect of accounting for daily activities when estimating air pollution exposure.     

Energy use and emissions of two stroke-powered tricycles in Metro Manila

CO, CO₂, NO_x and HC emissions of two stroke-powered tricycles in Metro Manila are examined using an instantaneous emissions model. Results show that fuel consumption and HC emissions in middle class residential areas and main roads are similar but lower than levels in low income residential areas. On the average, tricycles in Metro Manila consume 24.41 km/l of fuel and produces 9.5, 9.7, 40.5 and 0.07 g/km of HC, CO, CO₂ and NO_x, respectively. They fail to satisfy HC, CO and NO_x emission limits set by reference standards in the Philippines and other Asian countries. They produce greater HC and CO emissions than gasoline fueled private cars and diesel powered public jeepneys, taxis and buses on a per passenger-km basis but significantly lower NO_x emissions. Tricycles account for 15.4% of the total HC emissions from mobile sources in the metropolis while their contributions to CO, CO₂ and NO_x are minimal.     

The costs and benefits of reducing SO2 emissions from ships in the US West Coastal waters

Potential costs and benefits of policy options for reducing offshore ship pollution are examined using a meta-analysis of studies synthesized regionally for the US West Coast. Net benefits of reducing SO₂ emissions from cargo ships in the US West Coast waters are found to range between $98 million and $284 million, annually; the benefit–cost ratio varies between 1.8 and 3.36, depending on the size of the control area and the sulfur content limit. The results show that about 21,000 tons of on-land equivalent SO₂ emissions or about 33% of SO₂ emissions from all mobile sources in California in 2005 can be reduced annually if the US West Coast exclusive economic zone is designated as an International Maritime Organization-compliant SO_x emission control area (SECA) with fuel-sulfur content not exceeding 1.5%. The analysis demonstrates that designating this area reduces more emissions than establishing a smaller zone at a lower but favorable benefit-cost ratio. Control measures that require 0.5% low-sulfur fuels reduce more SO₂ emissions, and also may have higher net benefits. Technological alternatives may achieve benefits of emissions reductions on the US West Coast across higher ranges of potential fuel prices. Combinations of fuel switching and control technology strategies provide the most cost-effective benefits from SECAs on the US West Coast and other world regions.     

Reducing emissions at land border crossings through queue reduction and expedited security processing

Vehicle border crossings between Mexico and the United States generate significant amounts of air pollution, which can pose health threats to personnel at the ports of entry (POEs) as well as drivers, pedestrians, and local inhabitants. Although these health risks could be substantial, there is little previous work quantifying detailed emission profiles at POEs. Using the Mariposa POE in Nogales, Arizona as a case study, light-duty and heavy-duty vehicle emissions were analyzed with the objective of identifying effective emission reduction strategies such as inspection streamlining, physical infrastructure improvements, and fuel switching. Historical traffic information as well as field data were used to establish a simulation model of vehicle movement in VISSIM. Four simulation scenarios with varied congestion levels were considered to represent real-world seasonal changes in traffic volume. Four additional simulations captured varying levels of expedited processing procedures. The VISSIM output was analyzed using the EPA’s MOVES emission simulation software for conventional air pollutants. For the highest congestion scenario, which includes a 200% increase in vehicle volume, total emissions increase by around 460% for PM_2.5 and NO_x, and 540% for CO, SO₂, GHGs, and NMHC over uncongested conditions for a two-hour period. Expedited processing and queue reduction can reduce emissions in this highest congestion scenario by as much as 16% for PM_2.5, 18% for NO_x, 20% for NMHC, 7% for SO₂ and 15% for GHGs and CO. Other potential mitigation strategies examined include fleet upgrades, fuel switching, and fuel upgrades. Adoption of some or all of these changes would not only reduce emissions at the Mariposa POE, but would have air-quality benefits for nearby populations in both the US and Mexico. Fleet-level changes could have far-reaching improvements in air quality on both sides of the border.     

Environmental,functional and economic criteria for comparing “target roundabouts” with one- or two-level roundabout intersections

The article describes a criterion based on functional, environmental and economic aspects for comparing conventional roundabouts with innovative one- or two-level roundabouts. We compared the performances of eight roundabout types, differing in geometric layout, number of lanes and traffic flow regulation from each other, with regard to vehicle delays and CO₂, NO_x, PM_2.5 and PM₁₀ pollutant emissions. Recently-designed roundabouts – target roundabouts and flyover roundabouts – have also been studied for their undoubted practical interest. By means of closed-form capacity models and CORINAIR methodology, several traffic simulations were carried out to examine a typical annual traffic demand curve in a suburban context, three different distribution test matrices for traffic flows (ρ1, ρ2, ρ3) and maximum annual traffic flow values Q_max ranging between 1300 and 3300 veh/h.Estimating vehicle delays and annual pollutant emissions, along with construction and management costs, allowed obtaining overall costs for each roundabout examined, in function of traffic demand and several other parameters. Thanks to these analyses, we identified the roundabout types which best suit to each traffic condition.     

Exploring transport carbon futures using population microsimulation and travel diaries: Beijing to 2030

Evaluating transport policy for cities in developing countries is often constrained by data availability that limits the use of conventional appraisal models. Here, we present a new ‘bottom-up’ methodology to estimate transport CO₂ emission from daily urban passenger travel for Beijing, a megacity with relatively sparse data on travel behaviour. A spatial microsimulation, based on an activity diary survey and two sample population censuses, is used to simulate, for Beijing’s urban districts, a realistic synthetic population, and their daily travel and CO₂ emission over 2000–2010. This approach provides greater insight into the spatial variability of transport CO₂ emission than has previously been possible for Beijing, and further, enables an examination of the role of socio-demographics, urban form and transport developments in contributing to emissions over the modelled period.Using the 2000–2010 CO₂ emission estimates as a baseline, CO₂ emissions from passenger travel are then modelled to 2030 under scenarios exploring politically plausible strategies on transport (public transport infrastructure investment, and vehicle constraint), urban development (compaction) and vehicle technology (faster adoption of clean vehicle technology). The results showed that, compared to the trend scenario, employing both transport and urban development policies could reduce total passenger CO₂ emission to 2030 by 24%, and by 43% if all strategies were applied together. The study reveals the potential of microsimulation in emission estimation for large cities in developing countries where data availability may constrain more traditional approaches.     

The value of travel time and reliability-evidence from a stated preference survey and actual usage

This research examined travel behavior of Managed Lane (ML) users to better understand the value travelers place on travel time savings and travel time reliability. We also highlight the importance of survey design techniques. These objectives were accomplished through a stated preference survey of Houston’s Katy Freeway travelers. Three stated choice experiment survey design techniques were tested in this study: Bayesian (D_b) efficient, random level attribute generation, and an adaptive random approach. Mixed logit models were developed from responses using each of those designs. The value of travel time savings (VTTSs) estimates do vary across the design strategies, with the VTTS estimates based on the D_b-efficient design being approximately half the estimates from the other two designs. However, among the three design strategies, the value of travel time reliability (VOR) was only significant in the D_b-efficient design.The estimated VTTS from actual Katy Freeway usage (as measured using actual tolls paid and travel time saved on the managed lanes) is $51/h. This likely also includes any value that travelers place on travel time reliability. In comparison, our combined estimate of VTTS and VOR based on the SP survey (D_b-efficient design) was $50/h, which is remarkably close to the estimate from the actual usage data. Based on our dataset, the D_b-efficient design technique proved superior to the other two techniques. Finally, this research also supports the importance of including both travel time and travel time reliability parameters when estimating the willingness to pay for, and therefore benefits derived from, ML travel.     

Development of models for predicting roadside nitrogen dioxide concentrations and their evaluation against datasets measured in Dublin,Ireland

Different methods for predicting levels of roadside NO₂ from NO_x concentrations have been proposed. Prior work suggests that either a linear or a logarithmic relationship exists among the roadside NO₂ and NO_x concentrations. We modify and compare those methods with new formulations based on the principles of the original methods for datasets pertaining to Dublin. A new relationship based on the power law is developed to better model the decay of the ratio of (NO₂/NO_x)_road ratio with increasing NO_x concentration. These formulations are compared and examined at two study sites: at an intermittently congested urban street canyon and a free-flowing motorway.     

Mining missing train logs from Smart Card data

This paper shows how to recover the arrival times of trains from the gate times of metro passengers from Smart Card data. Such technique is essential when a log, the set of records indicating the actual arrival and departure time of each bus or train at each station and also a critical component in reliability analysis of a transportation system, is missing partially or entirely. The procedure reconstructs each train as a sequence of the earliest exit times, called S-epochs, among its alighting passengers at each stations. The procedure first constructs a set of passengers, also known as reference passengers, whose routing choices are easily identifiable. The procedure then computes, from the exit times of the reference passengers, a set of tentative S-epochs based on a detection measure whose validity relies on an extreme-value characteristic of the platform-to-gate movement of alighting passengers. The tentative S-epochs are then finalized to be a true one, or rejected, based on their consistencies with bounds and/or interpolation from prescribed S-epochs of adjacent trains and stations. Tested on 12 daily sets of trains, with varying degrees of missing logs, from three entire metro lines, the method restored the arrival times of 95% of trains within the error of 24 s even when 100% of logs was missing. The mining procedure can also be applied to trains operating under special strategies such as short-turning and skip-stop. The recovered log seems precise enough for the current reliability analysis performed by the city of Seoul.     

A velocity and payload dependent emission model for heavy-duty road freight transportation

The paper develops a forecasting model of emissions from traffic flows embracing the dynamics of driving behavior due to variations in payload. To measure of emissions at the level of individual vehicles under varying payloads a portable emission measurement system is used. This paper reports on a model based on data at the level of individual vehicles for a representative road trajectory. The model aggregates the data to the level of a homogeneous flow dependent of velocity and specific power, which is dependent on payload weight. We find a lean specification for the model that provides emission factors for CO₂, NO_x, HC, CO, and NO₂. The results indicate that, in comparison with earlier models, NO_x emissions in particular tend to be underestimated.     

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.     

Assessing the impacts of infrastructural road changes on air quality: A case study

Air quality (CO, NO, NO₂, NO_X, PM10 and C₂–C₆ hydrocarbons) was assessed in the Irish town of Monasterevin, before and after the location was by-passed with a new national motorway (M7). Prior to the opening of the motorway, transport between the cities of Dublin and Cork was facilitated by the N7 which ran through Monasterevin, leading to frequent congestion. Weekday air quality improved in the town following the opening of the M7 by-pass, with a reduction in ambient concentrations observed for all compounds except ethane and propane. Slight decreases in average weekend concentrations were observed for CO, NO_X, NO, and NO₂.     

The impact of Low Emission Zones on particulate matter concentration and public health

A common policy for reducing particulate matter concentrations in the European Union is the introduction of Low Emission Zones (LEZs), which may only be entered by vehicles meeting predefined emission standards. This paper examines the effectiveness of LEZs for reducing PM₁₀ levels in urban areas in Germany and quantifies the associated health impacts from reduced air pollution within the zones. We employ a fixed effects panel data model for daily observations of PM₁₀ concentrations from 2000 to 2009 and control, inter alia, for local meteorological conditions and traffic volume. We apply the regression outputs to a concentration response function derived from the epidemiological literature to calculate associated health impacts of the introduction of LEZs in 25 German cities with 3.96 million inhabitants. Associated uncertainties are accounted for in Monte-Carlo simulations. It is found that the introduction of LEZs has significantly reduced inner city PM₁₀ levels. We estimate the total mean health impact from reduced air pollution in 2010 due to the introduction of stage 1 zones to be ∼760 million EUR in the 25 LEZ cities in the sample, whereas total mean health benefits are ∼2.4 billion EUR for the more stringent stage 2 zones when applied in the same cities.     

What’s your type: a multidimensional cyclist typology

Increasing bicycle use for utilitarian trips is a common city objective for health and environmental improvement and congestion reduction, but cyclists react heterogeneously to interventions and infrastructure. Understanding cyclist types helps in comprehending and planning for this diverse population. This study uses data from 2004 surveyed Montreal cyclists to generate a multidimensional cyclist typology based on seven factors derived from 35 variables, mostly proven determinants of the intensity of bicycle usage. The analysis revealed four distinct cyclist types: dedicated cyclists, path-using cyclists, fairweather utilitarians, and leisure cyclists. The cycling frequencies of each group respond differently to potential interventions and vary within commuting rate ranges with apparent minima and maxima. Building a network adapted to different cyclist types and emphasizing its convenience, flexibility and speed, could be an effective strategy to increase cycling mode share and frequency among the various groups. Findings from this study can be of benefit to transportation engineers, planners and policy makers as they help in better understanding the impacts of various interventions on the different groups of cyclists.     

Effects of the 80 km/h and variable speed limits on air pollution in the metropolitan area of barcelona

In 2008 the regional government of Catalonia (Spain) reduced the maximum speed limit on several stretches of congested urban motorway in the Barcelona metropolitan area to 80 km/h, while in 2009 it introduced a variable speed system on other stretches of its metropolitan motorways. We use the differences-in-differences method, which enables a policy impact to be measured under specific conditions, to assess the impact of these policies on emissions of NO_x and PM₁₀. Empirical estimation indicate that reducing the speed limit to 80 km/h causes a 1.7–3.2% increase in NO_x and 5.3–5.9% in PM₁₀. By contrast, the variable speed policy reduced NO_x and PM₁₀ pollution by 7.7–17.1% and 14.5–17.3%. As such, a variable speed policy appears to be a more effective environmental policy than reducing the speed limit to a maximum of 80 km/h.     

A new probability statistical model for traffic noise prediction on free flow roads and control flow roads

A new traffic noise prediction approach based on a probability distribution model of vehicle noise emissions and achieved by Monte Carlo simulation is proposed in this paper. The probability distributions of the noise emissions of three types of vehicles are obtained using an experimental method. On this basis, a new probability statistical model for traffic noise prediction on free flow roads and control flow roads is established. The accuracy of the probability statistical model is verified by means of a comparison with the measured data, which has shown that the calculated results of L_eq, L₁₀, L₅₀, L₉₀, and the probability distribution of noise level occurrence agree well with the measurements. The results demonstrate that the new method can avoid the complicated process of traffic flow simulation but still maintain high accuracy for the traffic noise prediction.     

Passing Bays for Slow Moving Vehicles on Rural Two‐lane Roads

Abstract

Slow‐moving vehicles, including agricultural vehicles, on arterial highways can cause serious delays to other traffic as well as posing an extra safety risk. This paper elaborates on a small‐scale solution for these problems: the passing bay. It investigates the impacts of a passing bay on the total delay for other motorized vehicles, the number of passing manoeuvres and hindered vehicles, and the mean delay per hindered vehicle. The latter is also considered to be an indicator for traffic safety. The calculations are performed for two characteristic trips with a slow‐moving vehicle. The passing bay is an effective solution to reducing delays on arterial highways when two‐way hourly volumes exceed 600–1000 vehicles. The effects depend on the trip length and speed of the slow‐moving vehicle, and on the passing sight distance limitations of the road. A distance of 2–4?km between the passing bays seems an acceptable compromise between the reduction of delay for other motorized vehicles and the extra discomfort and delay for drivers of slow‐moving vehicles. This result also shows that passing bays are not effective in regions where slow‐moving vehicles mainly make trips shorter than this distance.     

Development of an emissions inventory model for mobile sources

Traffic represents one of the largest sources of primary air pollutants in urban areas. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentrations of a wide range of pollutants. A mutual characteristic of most of these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emissions inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for a wide range of vehicle types. The majority of inventories are compiled using ‘passive’ data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. Current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this paper, a methodology for estimating emissions from mobile sources using real-time data is described. This methodology is used to calculate emissions of sulphur dioxide (SO₂), oxides of nitrogen (NO_x), carbon monoxide (CO), volatile organic compounds (VOC), particulate matter less than 10 μm aerodynamic diameter (PM₁₀), 1,3-butadiene (C₄H₆) and benzene (C₆H₆) at a test junction in Dublin. Traffic data, which are required on a street-by-street basis, is obtained from induction loops and closed circuit televisions (CCTV) as well as statistical data. The observed traffic data are compared to simulated data from a travel demand model. As a test case, an emissions inventory is compiled for a heavily trafficked signalized junction in an urban environment using the measured data. In order that the model may be validated, the predicted emissions are employed in a dispersion model along with local meteorological conditions and site geometry. The resultant pollutant concentrations are compared to average ambient kerbside conditions measured simultaneously with on-line air quality monitoring equipment.     

Does emission control area policy reduce sulfur dioxides concentration in Shanghai?

As an important measure to abate ship-source air emissions, the establishment of Emission Control Area (ECA) has been adopted not only at international level, but also at national and regional level. However, there exists a research gap of employing econometric models to enrich the ECA policy evaluation research by testing the effectiveness of an ECA policy based on the empirical data. This paper focuses on the effectiveness of the ECA policy in shanghai port by adopting regression discontinuity (RD) approach. The RD design is considered as a wonderful substitution for the randomized control trial, which usually serves as a conventional and effective tool to address endogeneity. The causal effect of the ECA policy on the SO₂ concentration reduction can be detected by the RD approach. According to the estimated results, there is a discontinuity around the ECA policy cutoff point, and it is indicated that the SO₂ concentration in Shanghai decreased by at least 0.229 μg/m³ daily on average due to the implementation of the ECA policy. The positive role that the ECA policy plays in reducing SO₂ concentration in Shanghai is well demonstrated. This paper also puts forward an agenda for the future studies in the domain of the ECA policy evaluation.     

Evaluating the effects of green port policy: Case study of Kaohsiung harbor in Taiwan

The paper evaluates the effectiveness of strategies designed to reduce these pollutants in port areas, based on a newly developed assessment model to calculate emissions. The case study found that the strategy of reducing the ship’s speed to 12 knots is most effective in cutting fuel consumption and costs, as well as emissions. Adopting an onshore power supply system could reduce CO₂ emission by 57.16% and PM by 39.4%. By adopting the strategies of both reduced speed and cold ironing emissions control, a reduction in emissions of 71% to 91% can be achieved with a 20 nautical mile reduced speed zone. Therefore, the goals of reductions in emissions to improve port areas air quality could be achieved through adopting a green port policy in the future.