An Integrated Modeling System for the Estimation of Motor Vehicle Emissions

ABSTRACT

The paper provides a summary of accomplished and ongoing activities in the field of motor vehicle emission modeling in Europe. These activities have led to the development of a system of methods and conesponding computer models that address all the issues related to motor vehicle emissions that are of interest to policy-makers, institutions, and the automotive and oil industries. The Coordination of Information on Air Emissions/Computer Program to Calculate Emissions from Road Traffic (CORLNAIR/COPERT) methodology for the estimation of emissions from road vehicles is presented and compared with other models. A COPERT-based approach for microscale traffic emission estimation, with direct application in regional and urban emission inventories, is outlined, and relevant case studies are briefly discussed. The FOREMOVE model, developed for forecasts of motor vehicle emissions, is presented, together with some results from its application in the European Auto/Oil program. Particular attention is given to modeling the deterioration of in-use vehicles. Finally, the major areas of further research in the field of vehicle emissions in Europe are indicated.     

Real-world vehicle emissions: a summary of the Ninth Coordinating Research Council On-Road Vehicle Emissions Workshop

In April 1999, the Coordinating Research Council sponsored a workshop focusing on our understanding of real-world emissions from motor vehicles. This summary presents the latest information on in-use light- and heavy-duty vehicle tailpipe and evaporative emissions, the effects of fuels on emissions, field programs designed to understand the contribution of mobile sources to emission inventories, efforts to evaluate and improve mobile source emission models, progress of vehicle inspection/maintenance programs, and topics for future research. While significant progress has been made in understanding in-use vehicle emissions, further improvements are necessary. Moreover, the impact of current and future changes in emission control technologies and control programs will have to be monitored for effectiveness and incorporated into the emission factor models.     

Real-World Vehicle Emissions: A Summary of the Ninth Coordinating Research Council On-Road Vehicle Emissions Workshop

ABSTRACT

In April 1999, the Coordinating Research Council sponsored a workshop focusing on our understanding of real-world emissions from motor vehicles. This summary presents the latest information on in-use light- and heavy-duty vehicle tailpipe and evaporative emissions, the effects of fuels on emissions, field programs designed to understand the contribution of mobile sources to emission inventories, efforts to evaluate and improve mobile source emission models, progress of vehicle inspection/ maintenance programs, and topics for future research. While significant progress has been made in understanding in-use vehicle emissions, further improvements are necessary. Moreover, the impact of current and future changes in emission control technologies and control programs will have to be monitored for effectiveness and incorporated into the emission factor models.     

An Evaluation of the Fuel Factor Through Direct Measurement of Photochemical Reactivity of Emissions

Findings in research at the Bureau of Mines Bartlesville Petroleum Research Center show that photochemical reactivities of vehicular emissions are reliably measured in laboratory experiments in which smog manifestations are observed directly. Results of the direct smog-chamber measurements reveal that the photochemical behavior of emissions may differ significantly from the behavior that is predicted from the exhaust composition using reactivity scales. The concept of direct measurement of reactivity was applied to determine differences in characteristics of emissions from 20 passenger vehicles, each tested using 10 different fuels. The primary objective of the fuel study was to assess the over-all effect on vehicle emissions of fuel modifications designed to reduce the photochemical pollution associated with automotive evaporative losses. A similar, brief, comparative study of leaded and nonleaded fuels was also made. Reducing volatility was found to reduce the over-all smog potential of vehicle emissions but involved some penalty by way of increased exhaust emissions. Replacing light olefin with the corresponding paraffin also reduced over-all smog potential and in this case exhaust reactivity was not affected. In general greater smog potential was found to be associated with prototype nonleaded fuels than with leaded fuels typical of products currently marketed.     

Comprehensive analysis of the carbon impacts of vehicle intelligent speed control

In recent years sophisticated technologies have been developed to control vehicle speed based on the type of road the vehicle is driven on using Global Positioning Systems and in-car technology that can alter the speed of the vehicle. While reducing the speed of road vehicles is primarily of interest from a safety perspective, vehicle speed is also an important determinant of vehicle emissions and thus these technologies can be expected to have impacts on a range of exhaust emissions. This work analyses the results from a very large, comprehensive field trial that used 20 instrumented vehicles with and without speed control driven almost 500,000 km measuring vehicle speed at 10 Hz. We develop individual vehicle modal emissions models for CO₂ for 30 Euro III and Euro IV cars at a 1-Hz time resolution. Generalized Additive Models were used to describe how emissions from individual vehicles vary depending on their driving conditions, taking account of variable interactions and time-lag effects. We quantify the impact that vehicle speed control has on-vehicle emissions of CO₂ by road type, fuel type and driver behaviour. Savings in CO₂ of ≈6% were found on average for motorway-type roads when mandatory speed control was used compared with base case conditions. For most other types of road, speed control has very little effect on emissions of CO₂ and in some cases can result in increased emissions for low-speed limit urban roads. We also find that there is on average a 20% difference in CO₂ emission between the lowest and highest emitting driver, which highlights the importance of driver behaviour in general as a means of reducing emissions of CO₂.     

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.     

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.     

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

Implications: Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.     

Comparison of on-road emissions for B-0, B-10, and B-20 in transit buses

Biodiesels are often marketed as being cleaner than regular diesel for emissions. Emission test results depend on the biodiesel blend, but laboratory tests suggest that biodiesels decrease particulate matter, carbon monoxide, hydrocarbons, and air toxins when compared to regular diesel. Results for the amount of oxides of nitrogen (NOx) have been less conclusive. Tests have also not evaluated the commonly available ranges of biodiesel blends in the laboratory. Additionally, little information is available from on-road studies, so the effectiveness of using biodiesels to reduce actual emissions is unknown. A more complex relationship exists between engine operation and the rate of emission production than is typically evaluated using engine or chassis dynamometer tests. On-road emissions can vary dramatically because emissions are correlated to engine mode. Additionally, activity such as idling, acceleration, deceleration, and operation against a grade can produce higher emissions than more stable engine operating modes. Because these modes are not well captured in a laboratory environment, understanding on-road relationships is critical in evaluating the emissions reductions that may be possible with biodiesels. More tests and quantifications of the effects of different blends on engine and vehicle performance are required to promote widespread use of biodiesel. The objective of this research was to conduct on-road tests to compare the emission impacts of different blends of biodiesel to regular diesel fuel under different operating conditions. The team conducted on-road tests that utilized a portable emissions monitoring system that was used to instrument transit buses. Regular diesel and different blends of biodiesel were evaluated during on-road engine operation by instrumenting three in-use transit buses, from the CyRide system of Ames, Iowa, along an existing transit route.     

Developing a high-resolution vehicular emission inventory by integrating an emission model and a traffic model: Part 1--Modeling fuel consumption and emissions based on speed and vehicle-specific power

To improve the accuracy and applicability of vehicular emission models, this study proposes a speed and vehicle-specific power (VSP) modeling method to estimate vehicular emissions and fuel consumption using data gathered by a portable emissions monitoring system (PEMS). The PEMS data were categorized into discrete speed-VSP bins on the basis of the characteristics of vehicle driving conditions and emissions in Chinese cities. Speed-VSP modal average rates of emissions (or fuel consumption) and the time spent in the corresponding speed-VSP bins were then used to calculate the total trip emissions (or fuel consumption) and emission factors (or fuel economy) under specific average link speeds. The model approach was validated by comparing it against measured data with prediction errors within 20% for trip emissions and link-speed-based emission factors. This analysis is based on the data of light-duty gasoline vehicles in China; however, this research approach could be generalized to other vehicle fleets in other countries. This modeling method could also be coupled with traffic demand models to establish high-resolution emissions inventories and evaluate the impacts of traffic-related emission control measures.     

Factors affecting heavy-duty diesel vehicle emissions

Societal and governmental pressures to reduce diesel exhaust emissions are reflected in the existing and projected future heavy-duty certification standards of these emissions. Various factors affect the amount of emissions produced by a heterogeneous charge diesel engine in any given situation, but these are poorly quantified in the existing literature. The parameters that most heavily affect the emissions from compression ignition engine-powered vehicles include vehicle class and weight, driving cycle, vehicle vocation, fuel type, engine exhaust aftertreatment, vehicle age, and the terrain traveled. In addition, engine control effects (such as injection timing strategies) on measured emissions can be significant. Knowing the effect of each aspect of engine and vehicle operation on the emissions from diesel engines is useful in determining methods for reducing these emissions and in assessing the need for improvement in inventory models. The effects of each of these aspects have been quantified in this paper to provide an estimate of the impact each one has on the emissions of diesel engines.     

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.     

Static and dynamic instantaneous emission modelling

Emission models can be categorised into three categories: average speed models; traffic situation models, used at macro-scale or meso-scale level (national, regional, city level); and instantaneous (modal) models, useful at micro-scale level (street, vehicle level). To improve the existing instantaneous emission models, some preconditions must be fulfilled: the emission signals should be measured on a 10 Hz basis, due to their frequency content. Additionally, the transport dynamics from the engine to the analysers must be compensated by time-varying approaches. With these preconditions fulfilled, a new static instantaneous emission model is developed and the improvement in quality is checked by comparing it statistically with older models. A dynamic instantaneous model, able to include the transient generation of emissions, is subsequently created and the quality of prediction of engine-out emissions is determined. When a catalyst model is added, more accurate predictions of emissions for vehicles with after-treatment systems should be obtained.     

enforcement of diesel smoke emissions for the state of new jersey

This paper reports on the research program undertaken by the State of New Jersey to determine those tests and instruments which can be used by authorized state agencies for the enforcement of diesel smoke emissions. The state agencies under consideration for the enforcement of diesel smoke emissions are the following: (1) The Division of Motor Vehicles, in its system of state owned inspection stations, will be able to inspect all diesel-powered trucks, and tractors which are registered in New Jersey. (2) The Public Utilities Commission will be able to inspect at their home garages all buses registered in the State. (3) The New Jersey State Police will be able to inspect diesel-powered vehicles on the road. It was decided that the maximum inspection time for each vehicle was not to exceed one minute. On the basis of the one minute per vehicle requirement, eight different tests were evaluated to determine which ones correlated well with normal vehicle operation. These tests included acceleration of a fixed external inertia, free acceleration of only the moving parts of the engine, three ramp tests, a test in which a heavy vehicle was towed, and a driving test in which the vehicle being tested was actually accelerated. The results of tests demonstrated that the modified free acceleration method correlates reasonably well with a loaded steady state cycle, distinguishes the high emitters and is simple to perform. Consequently, the free acceleration test method is recommended for use in inspection stations and on the road. Finally, nearly two hundred vehicles have been tested by this procedure to determine present and potential levels of diesel smoke emissions. Another phase of the program consisted of the determination of smoke measuring techniques and instrumentation. The use and design of smokemeters were extensively investigated, as well as the use of the visual and photographic techniques. Of the various smokemeters tested for this application, several measured smoke satisfactorily in the laboratory, but none were found adequate for field use; they either lacked portability or were unstable due to the deposition of soot on the optics. At the time of writing, specifications for the necessary smokemeter have been drafted and published for bid to interested manufacturers.     

Tomato Root: Site of Initial Alteration in Minor Elements in Cadmium Treated Plants

Abstract

Societal and governmental pressures to reduce diesel exhaust emissions are reflected in the existing and projected future heavy-duty certification standards of these emissions. Various factors affect the amount of emissions produced by a heterogeneous charge diesel engine in any given situation, but these are poorly quantified in the existing literature. The parameters that most heavily affect the emissions from compression ignition engine-powered vehicles include vehicle class and weight, driving cycle, vehicle vocation, fuel type, engine exhaust aftertreatment, vehicle age, and the terrain traveled. In addition, engine control effects (such as injection timing strategies) on measured emissions can be significant. Knowing the effect of each aspect of engine and vehicle operation on the emissions from diesel engines is useful in determining methods for reducing these emissions and in assessing the need for improvement in inventory models. The effects of each of these aspects have been quantified in this paper to provide an estimate of the impact each one has on the emissions of diesel engines.     

Real-World Vehicle Emissions: A Summary of the Sixth Coordinating Research Council On-Road Vehicle Emissions Workshop

The Coordinating Research Council (CRC) has conducted a series of workshops on real-world vehicle emissions. This article summarizes findings from the most recent research regarding on-road emissions from mobile sources, presented at the CRC workshop held in March 1996. Among the topics discussed were efforts to improve and update emission models, results from field studies designed to understand the contribution of mobile sources to emission inventories, results from gas-and particle-phase emissions studies from in-use motor vehicles, and areas of future research.

The Sixth Coordinating Research Council (CRC) On-Road Vehicle Emissions Workshop was held March 18-20, 1996, in San Diego, CA. More than 160 representatives from academia, industry, government, and consulting firms in the United States, Canada, and Europe participated in the three-day meeting. The objective of the Workshop was to present the most recent information from research programs on:

mobile source contributions to the emission inventory

emission factor models and activity data

model comparison and development

emission reduction programs

new developments in remote sensing

studies of on-road vehicle exhaust and non-tailpipe emissions

off-cycle Federal Test Procedure (FTP) studies and revisions to the FTP

particle emissions from the light- and heavy-duty fleets

future research needs

Nine sessions were devoted to vehicle emissions models, improvements to the emission inventory, on-road and tunnel studies, off-cycle emissions, non-tailpipe and diesel emissions, emission reduction programs, and remote sensing. Overall workshop coordination was provided by Timothy Belian and the CRC staff, with Steven Cadle and Robert Gorse serving as cochairmen. Individual session chairmen were Brent Bailey (National Renewable Energy Laboratory), Mark Carlock (California Air Resources Board), Harold Haskew (General Motors), Kenneth Knapp and Philip Lorang (U.S. Environmental Protection Agency), Douglas Lawson (Colorado State University), Alan Lloyd (Desert Research Institute), Robert Slott (Shell Oil), and Timothy Truex (University of California, Riverside). In addition, during the Workshop, Lesha Hrynchuk of the California Air Resources Board (CARB) presented a hands-on demonstration using the Internet to obtain motor vehicle emissions information from groups throughout the world. The complete Workshop proceedings are available from the Coordinating Research Council, 219 Perimeter Center Parkway, Atlanta, GA 30346; phone: (770) 396-3400; fax: (770) 396-3404. The following summarizes each session and includes a short synopsis of all the papers that were presented.     

A Chassis Test Procedure to Mimic the Heavy-Duty Engine Transient Emissions Certification Test

ABSTRACT

In-use emissions from vehicles using heavy-duty diesel engines can be significantly higher than the levels obtained during engine certification. These higher levels may be caused by a combination of degradation of engine components, poor engine maintenance, degradation or failure of emissions after-treatment devices, and engine and emissions system tampering. A direct comparison of in-use vehicle emissions with engine certification levels, however, is not possible without removing an engine from the vehicle in order to perform engine dynamometer emissions testing. The goal of this research was to develop a chassis test procedure that mimics the engine performance, and as such the expected emissions levels, from the engine certification emissions test prescribed in the U.S. Code of Federal Regulations. Emissions measurements were taken from two engines during testing on an engine dynamometer using the transient heavy-duty Federal Test Procedure (FTP). Additionally, each engine was installed in an appropriate vehicle, and emissions measurements were taken using a chassis dynamometer while employing a vehicle driving schedule     

Further Validation of Artificial Neural Network-Based Emissions Simulation Models for Conventional and Hybrid Electric Vehicles

Abstract

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO₂] and oxides of nitrogen [NO_x]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO₂ and NO_x in the case of a class-8 truck but were more accurate as the truck weight increased.     

An Investigation of Idle Emissions Inspection and Maintenance at Altitude

Idle emissions inspection and maintenance was evaluated using a sample of 300 privately owned 1964 through 1973 model-year vehicles operating in the Denver metropolitan area. Ten privately owned stations, licensed by the State of Colorado to perform vehicle safety inspections, were utilized to conduct idle emissions inspection and subsequent maintenance of failed vehicles. Exhaust hydrocarbon (HC) and carbon monoxide (CO) reduction as measured by the 1975 Environmental Protection Agency (EPA) mass emission testing procedures was indicated to be 13% and 8% respectively at a 50 % rejection rate. The average maintenance cost to achieve the reduction was $11.32 per failed vehicle.

The adjustment and repair procedures provided to participating garages were sufficient to achieve significant emissions reduction and training provided to garage personnel was adequate. However, several problems were experienced with station personnel relative to data transmittal and inspection pass/fail limits. Problems were also experienced with respect to correlations between laboratory and garage-type analytical instrumentation.