A Vehicle Emissions System Using a Car Simulator and a Geographical Information System: Part 1—System Description and Testing

Abstract

A methodology for estimating vehicular emissions comprising a car simulator, a basic traffic model, and a geographical information system is capable of estimating vehicle emissions with high time and space resolution. Because of the extent of the work conducted, this article comprises two sections: In Part 1 of this work, we describe the system and its components and use examples for testing it. In Part 2 we will study in more detail the emissions of the sample fleet using the system and will make comparisons with another emission model. The experimental data for the car simulator is obtained using on-board measuring equipment and laboratory Fourier transform IR (FTIR) measurements with a dynamometer following typical driving cycles. The car simulator uses this data to generate emission factors every second. These emission factors, together with information on car activity and velocity profiles of highways and residential and arterial roads in Mexico City in conjunction with a basic traffic model, provide emissions per second of a sample fleet. A geographical information system is used to localize these road emissions.     

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.     

Emission factors of PCDD and PCDF for road vehicles obtained by tunnel experiment

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDF) were determined in air at the inlet and outlet of a longitudinally ventilated tunnel with separate tubes for each traffic direction. In addition, measurements of traffic density, traffic composition, ventilation rate and other air pollutants were carried out. The data allowed to estimate the PCDD/PCDF emissions based on a car fleet of about 20'–30'000 cars. Furthermore, the varying percentage of heavy duty vehicles made it possible to differentiate between emission factors for light (LDV) and heavy duty (diesel) vehicles (HDDV). Depending on driving conditions, the estimated emission factors were in the order of 0.04–0.5 ng/km 2,3,7,8-TEQ (Nordic model) for LDV and 0.8–9.5 ng/km for HDDV.     

Characterization of urban air quality using GIS as a management system

Keeping the air quality acceptable has become an important task for decision makers as well as for non-governmental organizations. Particulate and gaseous emissions of pollutant from industries and auto-exhausts are responsible for rising discomfort, increasing airway diseases, decreasing productivity and the deterioration of artistic and cultural patrimony in urban centers. A model to determine the air quality in urban areas using a geographical information system will be presented here. This system permits the integration, handling, analysis and simulation of spatial and temporal data of the ambient concentration of the main pollutant. It allows the users to characterize and recognize areas with a potential increase or improvement in its air pollution situation. It is also possible to compute past or present conditions by changing basic input information as traffic flow, or stack emission rates. Additionally the model may be used to test the compliance of local standard air quality, to study the environmental impact of new industries or to determine the changes in the conditions when the vehicle circulation is increased.     

Sensitivity analysis and evaluation of microFacCO: a microscale motor vehicle emission factor model for CO emissions

This paper presents a sensitivity analysis of a microscale emission factor model (MicroFacCO) for predicting real-time site-specific motor vehicle CO emissions to input variables, as well as a limited field study evaluation of the model. The sensitivity analysis has shown that MicroFacCO emission estimates are very sensitive to vehicle fleet composition, speed, and ambient temperature. For the present U.S. traffic fleet, the CO emission rate (g/mi) is increased by more than 500% at 5 mph in comparison with a speed greater than 40 mph and by approximately 67% at ambient temperatures of 45 degrees F and > or = 95 degrees F in comparison with an ambient temperature of 75 degrees F. The input variable "emission failure standard rate" is more sensitive to estimating emission rates in the 1990s than in the 2000s. The estimation of emission rates is not very sensitive to relative humidity. MicroFacCO can also be applied to examine the contribution of emission rates per vehicle class and model year. The model evaluation is presented for tunnel studies at five locations. In general, this evaluation study found good agreement between the measured and the modeled emissions. These analyses and evaluations have identified the need for additional studies to update the high-speed (>35 mph) air conditioning (A/C) correction factor and to add effects due to road grades. MicroFacCO emission estimates are very sensitive to the emission standard failure rate. Therefore, the model performance can be greatly improved by using a local emission standard failure rate.     

Identification of brake wear particles and derivation of a quantitative tracer for brake dust at a major road

Traffic-generated air pollutant emissions can be classified into exhaust and non-exhaust emissions. Increased attention is focussing on non-exhaust emissions as exhaust emissions are progressively limited by regulations. To characterise metal-rich emission from abrasion processes, size-segregated analysis of atmospheric aerosol particles sampled with micro-orifice uniform deposit impactors (MOUDI) in March 2007 in London was performed. The samples were collected at a roadside and a background site and were analysed for Al, Ba, Cu, Fe, Sb, Ti, V, Zn, Ca²⁺, K⁺, Mg²⁺, Na⁺, and NH₄⁺. Most components showed a clear roadside increment, which was evident as a higher mass concentration and a change in the size distribution. In particular, Fe, Cu, Ba, and Sb correlated highly, indicative of a common traffic-related source. Using complementary information on the fleet composition, vehicle number and average speed, the brake wear emission was calculated using the EMEP/CORINAIR emission database. The total PM₁₀ and barium emission of the traffic was determined by ratio to NO_x whose source strength was estimated from published emission factors. Barium was found to comprise 1.1% of brake wear (PM₁₀) particles from the traffic fleet as a whole, allowing its use as a quantitative tracer of brake wear emissions at other traffic-influenced sites.     

Modeling In-Use Vehicle Emissions and the Effects of Inspection and Maintenance Programs

Different ways for modeling the impact of vehicle emission inspection and maintenance programs on fleet hydrocarbon emissions are examined. A dynamic model is developed for forecasting fleet emissions in which individual vehicle performance is modeled as a stochastic process and vehicle emissions are tracked over time. Emissions inspection and repair are incorporated into the model, allowing for the stochastic aspects of both testing and repair. This model is compared to EPA’s model for evaluating the impact of vehicle emissions inspection and maintenance. We find that the way vehicle emission equipment deterioration overtime is modeled is important for forecasting emissions from the fleet and for assessing the success of inspection and maintenance programs. For inspection programs, we find that factors such as the proportion of vehicles tested, and repair effectiveness and duration have the greatest impact on emission reductions. The ability of different emission testing regimes to identify polluting vehicles has less impact on a program’s overall potential for emissions reduction. Policy recommendations for I&M testing and predictions of emission reduction credits from these tests will depend in important ways on the methods used in the underlying emissions models.     

Estimating Full IM240 Emissions from Partial Test Results: Evidence from Arizona

ABSTRACT

The expense and inconvenience of enhanced-vehicle-emissions testing using the full 240-second dynamometer test has led states to search for ways to shorten the test process. In fact, all states that currently use the IM240 allow some type of fast-pass, usually as early in the test as second 31, and Arizona has allowed vehicles to fast-fail after second 93. While these shorter tests save states millions of dollars in inspection lanes and driver costs, there is a loss of information since test results are no longer comparable across vehicles. This paper presents a methodology for estimating full 240-second results from partial-test results for three pollutants: HC, CO, and NO_x. If states can convert all tests to consistent IM240 readings, they will be able to better characterize fleet emissions and to evaluate the impact of inspection and maintenance and other programs on emissions over time. Using a random sample of vehicles in Arizona which received full 240-second tests, we use regression analysis to estimate the relationship between emissions at second 240 and emissions at earlier seconds in the test. We examine the influence of other variables such as age, model-year group, and the pollution level itself on this relationship. We also use the estimated coefficients in several applications. First, we try to shed light on the frequent assertion that the results of the dynamometer test provide guidance for vehicle repair of failing vehicles. Using a probit analysis, we find that the probability that a failing vehicle will pass the test on the first retest is greater the longer the test has progressed. Second, we test the accuracy of our estimates for forecasting fleet emissions from partial-test emissions results in Arizona. We find forecasted fleet average emissions to be very close to the actual fleet averages for light-duty vehicles, but not quite as good for trucks, particularly when NO_x emissions are forecast.     

Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 microns, either from published data or from user-defined size distributions. A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM10, PM5, PM2.5, and PM1] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway). A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM10 was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Estimation of particle resuspension source strength on a major London Road

Non-exhaust particles from road traffic arise from both abrasion sources and the resuspension of particles from the road surface. This paper reports a new combination of existing methods for indirect estimation of resuspension emission factors for Marylebone Road, London, a busy multi-lane highway in a street canyon. The method involves firstly estimating the total source strength of coarse particles (PM_2.5–10) arising from the road by calculating the roadside incremental concentration of coarse particles above the urban background. This is converted to a source strength by its ratio to NO_x whose source strength is estimated from the knowledge of the traffic mix and mean speed. This coarse particle source strength is assumed to represent the sum of resuspension emissions and the coarse particle component of abrasion emissions. Using information on the traffic mix and speed, the abrasion emissions have been calculated from the EMEP/CORINAIR emissions factor database, the result subtracted from the total coarse particle emissions in order to yield resuspension emissions, and combined with traffic count data to derive fleet-average emission factors. Using the fact that the traffic mix differs substantially between weekdays and weekends, separate average emission factors for light- and heavy-duty vehicles have been estimated. In addition to traffic mix, the influence of wind speed and the time elapsed since the last rainfall upon resuspension have been estimated. Wind speed was found to have by far the larger influence, although this was still secondary to the number of heavy-duty vehicles. Uncertainties arising from the choice of urban background site and poor data quality are discussed.     

Ammonia emissions from a representative in-use fleet of light and medium-duty vehicles in the California South Coast Air Basin

We used Fourier Transform Infrared Spectroscopy (FTIR) to measure tailpipe ammonia emissions from a representative fleet of 41 light and medium-duty vehicles recruited in the California South Coast Air Basin. A total of 121 chassis dynamometer emissions tests were conducted on these vehicles and the test results were examined to determine the effects of several key variables on ammonia emissions. Variables included vehicle type, driving cycle, emissions technology, ammonia precursor emissions (i.e. CO and NOx) and odometer readings/model year as a proxy for catalyst age. The mean ammonia emissions factor was 46 mg km^?1 (σ = 48 mg km^?1) for the vehicle fleet. Average emission factors for specific vehicle groups are also reported in this study. Results of this study suggest vehicles with the highest ammonia emission rates possess the following characteristics: medium-duty vehicles, older emissions technologies, mid-range odometer readings, and higher CO emissions. In addition, vehicles subjected to aggressive driving conditions are likely to be higher ammonia emitters. Since the vehicles we studied were representative of recent model year vehicles and technologies in urban airsheds, the results of our study will be useful for developing ammonia emissions inventories in Los Angeles and other urban areas where California-certified vehicles are driven. However, efforts should also be made to continue emissions testing on in-use vehicles to ensure greater confidence in the ammonia emission factors reported here.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

An evaluation of the LPG vehicles program in the metropolitan area of Mexico City

The environmental agency in the metropolitan area of Mexico City has launched a program to introduce more energy-efficient modes of transport, one of which is the use of alternative and less polluting fuels. With the perspective in mind, a liquefied petroleum gas (LPG) fleet of vehicles is exempt of the mandatory "one day without a car" program if the emission of pollutants is below the standard authorized for that specific purpose. Today, about 28,000 light-duty vehicles and heavy-duty trucks circulate in the area, most of them as aftermarket converted vehicles. In this work, we evaluated regulated exhaust emission and other parameters on 134 representative vehicles of that fleet. From the data obtained, an estimate of emission factors and their contribution to the global emission in the metropolitan area is provided. It is concluded that more than 95% of the in-use vehicles using LPG presented regulated emissions which exceeded in one or more the environmental regulations values required for certification. The poor maintenance of the vehicles and the type of conversion kit installed could be the culprits of the results obtained.     

Cold-start emissions of modern passenger cars at different low ambient temperatures and their evolution over vehicle legislation categories

The emissions of modern gasoline and diesel passenger cars are reduced by catalysts except in cold-starting. Since catalysts require a certain temperature (typically above 300 °C) to work to full efficiency, emissions are significantly higher during the warm-up phase of the car. The duration of this period and the emissions produced depend on the ambient temperature as well as on the initial temperature of the car's propulsion systems.The additional emissions during a warm-up phase, known as “cold-start extra emissions” (CSEEs) for emission inventory modelling, are mostly assessed by emission measurements at an ambient temperature of 23 °C. However, in many European countries average ambient temperatures are below 23 °C. This necessitates emission measurements at lower temperatures in order to model and assess cold-start emissions for real-world temperature conditions.This paper investigates the influence of regulated pollutants and CO₂ emissions of recent gasoline and diesel car models (Euro-4 legislation) at different ambient temperatures, 23, ?7 and ?20 °C. We present a survey and model of the evolution of cold-start emissions as a function of different car generations (pre-Euro-1 to Euro-4 legislations). In addition the contribution of CSEEs to total fleet running emissions is shown to highlight their increasing importance.For gasoline cars, it turns out that in average real-world driving the majority of the CO (carbon monoxide) and HC (hydrocarbon) total emissions are due to cold-start extra emissions. Moreover, the cold-start emissions increase considerably at lower ambient temperatures. In contrast, cold-start emissions of diesel cars are significantly lower than those of gasoline cars. Furthermore, the transition from Euro-3 to Euro-4 gasoline vehicles shows a trend for a smaller decline for cold-start extra emissions than for legislative limits. Particle and NO_x emission of cold-starts are less significant.     

A new approach to in-situ determination of roadside particle emission factors of individual vehicles under conventional driving conditions

A method for continuous on-road measurements of particle number emissions for both diesel- and petrol-fuelled vehicles is presented. The setup allows the determination of particle number emission factors on an individual vehicle basis by the simultaneous measurement of CO₂ and particle concentrations. As an alternative to previous measurements on the kerbside, the sample is taken directly in the street, with the advantage of sampling in-situ within the exhaust plumes of passing vehicles, allowing the separation of the individual high-concentration plumes. The method was tested in two experiments that were conducted in the Gothenburg area. In the first study, which was performed at an urban roadside, we were able to determine particle emission factors from individual vehicles in a common car fleet passing the measurement site. The obtained emission factors were of the same order of magnitude (between 1.4 × 10¹² and 1.8 × 10¹⁴ particles km^?1) as values published in the recent literature for light duty vehicles. An additional on-road experiment was conducted at a rural road with four light duty reference vehicles (three of them petrol-powered and one diesel-powered) at driving speeds of 50 and 70 km h^?1, realised with different engine speeds. The results of the traffic emission studies show that the method is applicable provided that instruments with an adequate dynamic range are used and that the traffic is not too dense. In addition, the variability in particle emissions for a specified driving condition was estimated.     

Sensitivity Analysis and Evaluation of MicroFacCO: A Microscale Motor Vehicle Emission Factor Model for CO Emissions

ABSTRACT

This paper presents a sensitivity analysis of a microscale emission factor model (MicroFacCO) for predicting realtime site-specific motor vehicle CO emissions to input variables, as well as a limited field study evaluation of the model. The sensitivity analysis has shown that MicroFacCO emission estimates are very sensitive to vehicle fleet composition, speed, and ambient temperature. For the present U.S. traffic fleet, the CO emission rate (g/mi) is increased by more than 500% at 5 mph in comparison with a speed greater than 40 mph and by ~67% at ambient temperatures of 45 °F and ≥95 °F in comparison with an ambient temperature of 75 °F.     

Hot emission model for mobile sources: application to the metropolitan region of the city of Santiago, Chile

Depending on the final application, several methodologies for traffic emission estimation have been developed. Emission estimation based on total miles traveled or other average factors is a sufficient approach only for extended areas such as national or worldwide areas. For road emission control and strategies design, microscale analysis based on real-world emission estimations is often required. This involves actual driving behavior and emission factors of the local vehicle fleet under study. This paper reports on a microscale model for hot road emissions and its application to the metropolitan region of the city of Santiago, Chile. The methodology considers the street-by-street hot emission estimation with its temporal and spatial distribution. The input data come from experimental emission factors based on local driving patterns and traffic surveys of traffic flows for different vehicle categories. The methodology developed is able to estimate hourly hot road CO, total unburned hydrocarbons (THCs), particulate matter (PM), and NO(x) emissions for predefined day types and vehicle categories.     

Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES

The Motor Vehicle Emission Simulator (MOVES) quantifies emissions as a function of vehicle modal activities. Hence, the vehicle operating mode distribution is the most vital input for running MOVES at the project level. The preparation of operating mode distributions requires significant efforts with respect to data collection and processing. This study is to develop operating mode distributions for both freeway and arterial facilities under different traffic conditions. For this purpose, in this study, we (1) collected/processed geographic information system (GIS) data, (2) developed a model of CO₂ emissions and congestion from observations, (3) implemented the model to evaluate potential emission changes from a hypothetical roadway accident scenario. This study presents a framework by which practitioners can assess emission levels in the development of different strategies for traffic management and congestion mitigation.

Implications: This paper prepared the primary input, that is, the operating mode ID distribution, required for running MOVES and developed models for estimating emissions for different types of roadways under different congestion levels. The results of this study will provide transportation planners or environmental analysts with the methods for qualitatively assessing the air quality impacts of different transportation operation and demand management strategies.