Exhaust emissions and fuel consumption of a triple-fuel spark-ignition engine powered passenger car

This paper examines the influence of compressed natural gas, liquefied petroleum gas and gasoline fuel on the exhaust emissions and the fuel consumption of a spark-ignition engine powered passenger car. The vehicle was driven according to the urban driving cycle and extra urban driving cycle speed profiles with the warmed-up engine. Cause and effect based analysis reveals potential for using different fuels to reduce vehicle emission and deficiencies associated with particular fuels. The highest tank to wheel efficiency and the lowest CO₂ emission are observed with the natural gas fuelled vehicle, that also featured the highest total hydrocarbon emissions and high NO_x emissions because of fast three way catalytic converter aging due the use of the compressed natural gas. Retrofitted liquefied petroleum gas fuel supply systems feature the greatest air-fuel ratio variations that result in the lowest TtW efficiency and in the highest NO_x emissions of the liquefied gas fuelled vehicle.     

Simulating the air quality impacts of traffic calming schemes in a dense urban neighborhood

In this study, the effects of isolated traffic calming measures and area-wide calming schemes on air quality in a dense neighborhood were estimated using a combination of microscopic traffic simulation, emission, and dispersion modeling. Results indicated that traffic calming measures did not have as large an effect on nitrogen dioxide (NO₂) concentrations as the effect observed on nitrogen oxide (NO_x) emissions. Changes in emissions resulted in highly disproportional changes in pollutant levels due to daily meteorological conditions, road geometry and orientation with respect to the wind. Average NO₂ levels increased between 0.1% and 10% with respect to the base-case while changes in NO_x emissions varied between 5% and 160%. Moreover, higher wind speeds decreased NO₂ concentrations on both sides of the roadway. Among the traffic calming measures, speed bumps produced the highest increases in NO₂ levels.     

Integrating multi-source maritime information to estimate ship exhaust emissions under wind,wave and current conditions

How to accurately calculate ship exhaust emissions has become urgent needs. In this paper, multi-source maritime information is integrated to estimate ship exhaust emissions under ocean environment. Influences of wind, wave and current on ship speed are firstly analyzed and mathematically modeled. Based on the influences, ocean environment information and ship trajectories are integrated to identify ship activities exactly. After that, ship activity based calculation method is present to obtain exhaust emissions from ship in various activities. Contribution ratios of different ship type and ship activities have been further discussed. In a case study of Ningbo-Zhoushan port in China, greenhouse gas (CO₂, CO, SO_x, NO_x and PM) emissions from ships in 2014 calculated by the proposed method are 8.72 × 10⁵ ton, 2.07 × 10³ ton, 1.47 × 10⁴ ton, 2.60 × 10⁴ ton and 1.40 × 10³ ton respectively. The maximum error is under 10%. Experimental results illustrate that the proposed method can produce more accurate ship exhaust emissions than traditional method under ocean environment conditions.     

Urban roadside monitoring and prediction of CO,NO2 and SO2 dispersion from on-road vehicles in megacity Delhi

The study inspects the traffic-induced gaseous emission dispersion characteristics from the urban roadside sites in Delhi, India. The concentration of pollutants viz. CO, NO₂ and SO₂ along with traffic and ambient atmospheric conditions at five selected local urban road sites were simultaneously measured. A developed General Finite Line Source Model (GFLSM) was used to predict the local roadside CO, NO₂ and SO₂ concentrations. A comparison of the observed and predicted values emission parameters using GFLS model has shown that the predicted values for SO₂, CO and NO₂ at all the selected local urban roadside locations are found to lie within the error bands of 5%, 6%, and 7% respectively. A high level of agreement was found between the monitored and estimated CO, NO₂ and SO₂ concentration data. From the study, it has also been established that the developed model exhibits the capability of reasonably predicting the characteristics of gaseous pollutants dispersion from on-road vehicles for the urban city air quality.     

Impacts of traffic-flows on vehicular-exhaust emissions at traffic junctions

This paper examines the impact of traffic-flow on CO, NO₂ and PM emissions at two distinct traffic junctions and evaluates the use of emission factors. The study includes three scenarios regarding pollutant emissions, which combine a field, experimental and semi-empirically estimated traffic parameters for free, interrupted and congested traffic-flow conditions. It evaluates the emission patterns for heterogeneity in traffic characteristics of both junctions. The results suggest the corrections to be made to emission factors at traffic junctions for better forecast of air quality.     

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.     

The economy of alternative fuels when including the cost of air pollution

In this study, the costs involved in the use of petrol, diesel, natural gas, biogas, and methanol (produced from natural gas and biomass) in cars and heavy trucks are compared. The cost includes fuel cost, extra capital cost for vehicles using alternative fuels, and the environmental cost of VOC, NO_x, particulate and CO₂ emission based on actual 1996 and estimated 2015 emission factors. The costs have been calculated separately for rural, urban and city-centre traffic. A complete macroeconomic assessment of the effect of introducing alternative fuels is not, however, included in the study. The study shows that no alternative fuel can compete with petrol and diesel in rural traffic when the economic valuation of CO₂ emission is taken as current Swedish CO₂ taxes ($200/tonne C). In cities with a natural gas network, natural gas is the fuel with the lowest cost for both cars and heavy trucks, based on 1996 emission factors. Methanol from natural gas and biogas from waste products can also compete with diesel in urban traffic. With predicted improvements in technology and subsequent emission reductions, no alternative fuel can compete with petrol in any of the traffic situations studied by 2015, and only in city-centre traffic will alternative fuels be less costly than diesel in heavy vehicles. Of the biomass-based fuels studied, low-cost biogas from waste products is the most competitive one and is, already at current CO₂ taxes, the fuel with lowest cost for heavy trucks in urban traffic in areas where natural gas networks do not exist. To enable the more widespread use of biomass-based fuels, i.e. using feedstocks such as energy crops or logging residues that are available in larger amounts, the economic valuation of CO₂ emission has to be 2–2.5 times higher than current Swedish CO₂ tax level.     

Use of Bayesian inference method to model vehicular air pollution in local urban areas

Traffic Related Air Pollution (TRAP) studies are usually investigated using different categories such as air pollution exposure for health impacts, urban transportation network design to mitigate pollution, environmental impacts of pollution, etc. All of these subfields often rely on a robust air pollution model, which also necessitates an accurate prediction of future pollutants. As is widely accepted by the heath authorities, TRAP is considered to be the major health issue in urban areas, and it is difficult to keep pollution at harmless levels if the time sequenced dynamic pollution and traffic parameters are not identified and modelled efficiently. In our work here, artificial intelligence techniques, such as Bayesian Networks with an optimized configuration, are used to deliver a probabilistic traffic data analysis and predictive modelling for air pollution (SO₂, NO₂ and CO) at very local scale of an urban region with up to 85% accuracy. The main challenge for traditional data analysis is a lack of capability to reveal the hidden links between distant data attributes (e.g. pollution sources, dynamic traffic parameters, etc.), whereas some subtle effects of these parameters or events may play an important role in pollution on a long-term basis. This study focuses on the optimisation of Bayesian Networks to unveil hidden links and to increase the prediction accuracy of TRAP considering its further association with a predictive GIS system.     

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.     

How wide should be the adjacent area to an urban motorway to prevent potential health impacts from traffic emissions?

In recent years, several studies show that people who live, work or attend school near the main roadways have an increased incidence and severity of health problems that may be related with traffic emissions of air pollutants. The concentrations of near-road atmospheric pollutants vary depending on traffic patterns, environmental conditions, topography and the presence of roadside structures. In this study, the vertical and horizontal variation of nitrogen dioxide (NO₂) and benzene (C₆H₆) concentration along a major city ring motorway were analysed. The main goal of this study is to try to establish a distance from this urban motorway considered “safe” concerning the air pollutants human heath limit values and to study the influence of the different forcing factors of the near road air pollutants transport and dispersion. Statistic significant differences (p = 0.001, Kruskal–Wallis test) were observed between sub-domains for NO₂ representing different conditions of traffic emission and pollutants dispersion, but not for C₆H₆ (p = 0.335). Results also suggest significant lower concentrations recorded at 100 m away from roadway than at the roadside for all campaigns (p < 0.016 (NO₂) and p < 0.036 (C₆H₆), Mann–Whitney test). In order to have a “safe” life in homes located near motorways, the outdoor concentrations of NO₂ must not exceed 44–60.0 μg m⁻³ and C₆H₆ must not exceed 1.4–3.3 μg m⁻³. However, at 100 m away from roadway, 81.8% of NO₂ receptors exceed the annual limit value of human health protection (40 μg m⁻³) and at the roadside this value goes up to 95.5%. These findings suggest that the safe distance to an urban motorway roadside should be more at least 100 m. This distance should be further studied before being used as a reference to develop articulated urban mobility and planning policies.     

The cumulative effect of nuisances from road transportation in residential sectors on the Island of Montreal – Identification of the most exposed groups and areas

Air pollution and road traffic noise are considered to be the two most important nuisances that could negatively affect the quality of life. A prolonged exposure to high concentrations of these pollutants could conduct to various health problems. Studies in environmental equity have often considered these nuisances individually whenever it comes from the same source. The main objective of this paper is to determine if the 15 years of age, those aged 65 and over, visible minorities and low income individuals located in a portion of the Island of Montreal are overrepresented in city blocks characterized by having among the highest levels of transportation-related air pollutants (i.e., ambient concentrations of NO₂ and road traffic noise in decibels (dB(A)). The results show that low-income individuals and, to a lesser extent, visible minorities, are significantly overrepresented in city blocks characterized by the higher levels of NO₂ and road traffic noise in dB(A). Multinomial logistic regression analysis confirms these results, and also shows that young people under 15 years are under-represented in the most polluted areas. However, contrary to the previous bivariate results, people aged 65 and over are negatively and significantly associated with the likelihood of their living in a city block located in an advantaged area after controlling for the independent effects of the other explanatory variables. Moreover, visible minorities are significantly overrepresented in advantaged areas. Considering the observed results, some solutions are identified to reduce road traffic noise and air pollution in the city blocks localized near major traffic arteries.     

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.     

The potential health,financial and environmental impacts of dieselgate in Ireland

ABSTRACT

The transportation sector is the greatest contributor to air pollution. With the booming demand for transportation, reducing the pollution has become one of the main concerns of researchers. EPA emission standards are designed to protect air quality and human health. Diesel Euro 5 NO_x has become a matter of disquiet since it has been found that NO_x emissions are significantly exceeding the standard limit. This paper presents a study to estimate the disparity in real-world NO_x emission levels resulted from all diesel Euro 5 passenger cars (PC) and light commercial vehicles (LCV) that are present in Ireland. NO_x emission levels calculated based on laboratory test results, on-road measurements and the COPERT 4 model were compared. Additionally, NO_x emission levels from the defective Volkswagen models have been calculated to quantify the effect of the Volkswagen scandal on Ireland. Impacts of excess NO_x emissions on health and cost have also been presented.     

Exhaust emissions generated under actual operating conditions from a hybrid vehicle and an electric one fitted with a range extender

The paper describes exhaust emission tests performed on a PHEV (Plug-in Hybrid Electric Vehicle) and a BEV (Battery Electric Vehicle), in which the combustion engine was used as a range extender. The measurements of the exhaust emissions were performed for CO₂/fuel consumption, CO, THC and NO_x. The RDE measurements were performed including the engine operating parameters and emissions analysis. This analysis shows that the engines of BEVs and PHEVs operate in a different parameter range when under actual operating conditions, which directly translates into the exhaust emission values. This is particularly the case for the emission of NO_x. The investigations were carried out for two routes differentiated by the length and share of the urban and extra-urban cycles. For both routes, the emission of THC and CO were lower for the PHEV engine – HC by 69% (22 mg/km, route 1) and 6% (15 mg/km, route 2), CO by 69% (0.12 mg/km, route 1) and 80% (0.1 mg/km, route 2). For route 1, characterized by a greater share of the urban cycle, the emission of NO_x was lower by 70% (2 mg/km) for the BEV engine, and (route 2) lower by 60% (8 mg/km) for the PHEV engine. Additionally, the curves of the exhaust emissions in time for individual exhaust components have been presented that indicate that in the motorway cycle the emission of THC and CO from the BEV vehicle increases significantly up to ten times compared to urban cycle.     

A system based approach to develop hybrid model predicting extreme urban NOx and PM2.5 concentrations

One of the major drawbacks of conventional air quality models is their inability in accurately predicting extreme air pollutant concentrations. Hybrid modelling is one of the techniques that estimates/predicts the ‘entire range’ of the distribution of pollutant concentrations by combining the deterministic based models (capable in predicting average range) with suitable statistical (probability) distribution models (capable in predicting extreme range). This research paper describes system based approach in developing hybrid model to predict hourly averages as well as extreme percentile ranges of NO_x and PM_2.5 concentrations at two urban locations having complex traffic heterogeneity, highly variable tropical meteorology and different geographical characteristics. At one of the selected locations i.e. Delhi megacity, during winters, hybridization of AERMOD and Lognormal predicts NO_x and PM_2.5 concentrations satisfactorily with index of agreement ‘d’ values of 0.98–0.99, respectively; however, during summers, AERMOD-Log-logistic and AERMOD-Lognormal are best predicting NO_x and PM_2.5 concentrations with d values of 0.98–0.96, respectively. In another, i.e., Chennai, a coastal megacity, AERMOD-Lognormal predicts PM_2.5 concentrations satisfactorily with d values of 0.98 and 0.99 during winter and summer seasons, respectively. Further, hybrid model has also been used to evaluate regulatory compliance.     

Port-city exhaust emission model: An application to cruise and ferry operations in Las Palmas Port

Exhaust emissions cause air pollution and climate change. The exhausts of shipboard fuel combustion are equally damaging particularly, so close to the environmentally sensitive mainland and island coasts, as well as at ports due to their urbanized character. This paper estimates, for the first time, exhaust pollutants related to cruise and ferry operations in Las Palmas Port and, in an island context. Emission assessment is based on a full bottom-up model and messages transmitted by the Automatic Identification System during 2011. Results are described as a breakdown of NOx, SOx, PM_2.5, CO and CO₂, according to ship classes, operative type and time, providing valuable information to environmental policy makers in port-city areas and islands under similar conditions. It is generally concluded that vessel traffic and passenger shipping in particular are a source of air pollution in Las Palmas Port. Emission maps confirm location of hot spots in quays assigned for cruise and ferry operations. Policy recommendations encourage regular monitoring of exhaust emissions and market-based incentives supported by details on polluting and operative profiles. On the other hand, feasibility studies are suggested for automated mooring, LNG bunkering facilities and also shore-side energy services, prioritizing berthing of shipping sectors (or sub-sectors) with the highest share of exhaust emissions once their local effects have been confirmed by a dispersion, exposure and impact assessment.     

Comparing air pollution from ferry and landside commuting

Recent and anticipated growth in passenger ferry service has been complicated by concerns about air pollution from marine engines that are only starting to be regulated. While marine engines are known to be a significant and growing source category in some locations, sparse data and analytical difficulties have prevented rigorous comparisons of marine and on-land passenger travel. Using data gathered in the San Francisco Bay Area, we model emissions from three passenger ferries and the matching on-land travel that would be used by commuters if ferry service were not available. The results are analyzed parametrically for levels of ridership and induced travel demand, and for new technologies, including selective catalytic reduction and natural gas fuel. Results indicate that under some conditions, passenger ferries reduce some emissions (including particulate matter emissions) relative to the matching on-land service but increase others. Emissions of NO_X are particularly problematic––all the technologies examined lead to increased NO_X emissions due to ferry commuting. Some of the emissions comparisons are sensitive to mode split, ridership, or induced travel demand. However, NO_X emissions are not––ferry commuting always raises NO_X emissions, even with the most advanced technologies. Implications for local air quality regulators and for technology development are discussed.     

Investigating the link between cyclist volumes and air pollution along bicycle facilities in a dense urban core

In this paper we explore the air pollution levels along types of bicycle facilities using a NO₂ land use model previously developed for Montreal. We explore potential associations between bicycle volumes through signalized intersections and pollution levels at those intersections. We further investigate this relationship through the comparison of over thirty cycling corridors as well as an evaluation of the potential exposure of cyclists to air pollution along five routes. We observe NO₂ concentrations to be positively correlated with bicycle flows at the intersection level. We also observe that corridors with either a bicycle path or cycle track generally rank higher in terms of bicycle volume and also have higher NO₂ concentrations than corridors without bicycle facilities. This indicates that intersections and bicycle facilities with a large number of cyclists are also those characterized with the highest air pollution levels.     

Metropolitan sprawl measurement and its impacts on commuting trips and road emissions

This study measures urban form as indicators of metropolitan sprawl and explores its impact on commuting trips and NO_x and CO₂ emissions from road traffic in all metropolitan statistical areas (MSAs) and four groups’ MSAs separated by population in the continental United States. Encompassing all MSAs, the study adds the accessibility factor to four existing factors: density, land use mix, centeredness, and street connectivity. The study establishes multivariate regression models between urban form, commuting trips, and emissions from road traffic while controlling for socioeconomic conditions. The study shows that urban form index and five urban form factors have a statistically significant association with commuting trips, NO_x and CO₂ emissions from road traffic. In four MSA groups as determined by MSA population size, higher values of urban form factors (i.e., lower sprawl) are statistically associated with more walking commuters. On the other hand, higher values of urban form factors are associated with fewer commuting vehicles per household in large MSAs with the moderate effect, a lower average commuting drive time in medium and small MSAs, and more commuters using public transportation in medium and large MSAs. This study provides an urban form index covering all metropolitan areas in the continental United States by adding another urban form factor, and the findings show that urban form factors have different effects on mode choices, drive time, and emission from road traffic depending on the MSA population size.     

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.