Seventy-five diesel vehicles were measured in China using a portable emissions measurement system (PEMS). Particular matter (PM) emission factors and gaseous emission factors for Euro 0 (E0), Euro 1 (E1), Euro 2 (E2), and Euro 3 (E3) trucks were obtained under highway, urban, and rural driving conditions. Vehicle emission regulations in China have successfully reduced carbon monoxide (CO), hydrocarbons (HC) and PM by 62, 56, and 72% on average. Most of the emission reductions were achieved when the control technology went from E0 to E1 in Xi'an, and E2 to E3 in Beijing, which resulted in PM reductions of 79% associated with highway driving and 60% associated with urban or rural driving. Emission levels of oxides of nitrogen (NO(X)) were not improved from previous emission control steps. Compared with Xi'an, the emission rate is lower in Beijing, which is strong evidence of the effectiveness of the present comprehensive emission control strategy in Beijing. Emissions were grouped into driving bins that corresponded to the energy demand placed on the vehicles. By using this binning approach, it was found that E3 trucks were successfully controlling the high emission rates in aggressive driving bins, which led to the low average emission for E3 trucks.

Rapid vehicle growth in developing nations makes it necessary for these nations to address the transportation and environmental impacts of on-road mobile sources. To estimate the air quality impact of their fleets, many nations have adopted modified versions of U.S. or European emissions models or factors. In most cases, these models can lead to significant errors in emissions estimates. To address this problem, a new on-road mobile source emissions model, called the international vehicle emissions (IVE) model, designed for use in developing countries has been developed. The IVE model was developed jointly by researchers at the International Sustainable Systems Research Center and the University of California at Riverside. The IVE model uses local vehicle technology distributions, power-based driving factors, vehicle soak distributions, and meteorological factors to tailor the model to the local situation. In addition, an intensive 2-week field study was designed to collect the necessary fleet and activity data to populate the model with critical local information. The IVE model, along with the field study process, has proved highly effective in providing an improved estimate of mobile source emissions in an urban area and allows the effective analysis of local policy options. The studies have served to transfer tools and knowledge on the process of creating and improving mobile source inventories in an efficient manner. The rationale behind the development of the model, the development and application of the field studies, an overview of the results obtained to date, and planned next steps are described in this paper.

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Vehicle emission inventory is a critical element for air quality study. This study created systemic methods to establish a vehicle emission inventory in Chinese cities. The methods were used to obtain credible results of vehicle activity in Beijing and Shanghai. On the basis of the vehicle activity data, the International Vehicle Emission model is used to establish vehicle emission inventories. The emissions analysis indicates that 3 t of particulate matter (PM), 199 t of nitrogen oxides (NO x ), 192 t of volatile organic compounds (VOCs), and 2403 t of carbon monoxide (CO) are emitted from on-road vehicles each day in Beijing, whereas 4 t of PM, 189 t of NO x , 113 t of VOCs, and 1009 t of CO are emitted in Shanghai. Although common features were found in these two cities (many new passenger cars and a high taxi proportion in the fleet), the emission results are dissimilar because of the different local policy regarding vehicles. The method to quantify vehicle emission on an urban scale can be applied to other Chinese cities. Also, knowing how different policies can lead to diverse emissions is beneficial knowledge for other city governments. INTRODUCTIONSince the 1990s, many large Chinese cities have experienced serious air pollution problems due to the rapid growth of automobile ownership. 1 Because of the absence of a database in China, the vehicle emission inventory is difficult to establish with high temporal or spatial resolution. The MOBILE emission model is currently used in China to develop vehicle emission inventory. 2 However, because the emission factors are based on the average speed, the unreliability of MOBILE-modeled results was indicated by a number of independent evaluation field studies. [3][4][5] The International Vehicle Emissions (IVE) model is instead based on driving cycle. It uses secondby-second driving data to obtain the bin distribution and related emission factors. 6 The basic theory of the model is credible, and several of the theories have been accepted by U.S. Environmental Protection Agency (EPA) to develop a next generation model. 7 Because the emission factors are based on detailed vehicle technology classification, the IVE model can be used by different countries if a detailed vehicle fleet is available. The temporal resolution of the emission inventory is by hour and the spatial resolution is by road types, which are better than with the MOBILE model. A systemic data collection method was created to obtain a basic input data for the IVE model.Because of the increasingly serious air pollution and the important roles of both Beijing and Shanghai, this study was designed to support estimates of the air pollution impacts of on-road transportation in the two cities. It is also hoped that after the comparison between Beijing and Shanghai, the methodology, conclusions, and policy suggestions can be extrapolated to other Chinese cities.

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Emissions from "low emitting" modern vehicles were measured on-road using a Fourier transform infrared (FTIR) on-board emissions measurement system. Twenty vehicles were tested on road and on a chassis dynamometer. A subset of four vehicles was tested on a test track as well as on the dynamometer. Comparison of on-board measurements with laboratory measurements while operating on the dynamometer showed agreement within measurement and test to test variability. Comparison of dynamometer measurements with test track measurements showed some larger differences attributable to track test conditions. On-road and dynamometer tests were conducted on the remaining 16 vehicles, with the on-road testing including freeway, arterial, and residential streets. The on-road testing showed that most of the low emitting vehicles under most operating conditions are operating below certification levels. Most vehicles reached a hot stabilized condition within 60 to 100 s. Hot running emissions were on average very low once the catalyst lights off. For NMHC, the majority of the "certification" emissions occur during the start-up, especially for PZEVs. NOx and CO also showed a high fraction of "certification" emissions during start-up, but also showed emission spikes under hot running conditions, especially during transients.

India continues to experience substantial economic growth, with increased travel demand for both passengers and goods. As a result, roadway congestion is increasing in many cities and putting significant pressure on India's transportation infrastructure. One key concern is air pollution related to the increased transportation activity. To understand the transportation impacts on air quality, it is necessary to develop and apply appropriate modeling tools to the area of concern. Recently, a new on-road mobile source emissions model designed for use in developing countries has been developed: the international vehicle emissions (IVE) model. The IVE model was developed jointly by researchers at the International Sustainable Systems Research Center and the University of California at Riverside. This paper describes a research program that applied the IVE modeling approach to the city of Pune, India. As part of the approach, an extensive vehicle activity–fleet composition study took place in Pune; it consisted of videotaping and measuring traffic patterns, tracking representative vehicles with Global Positioning System data loggers, monitoring start–stop patterns in instrumented vehicles, and conducting surveys in the field. In this paper, the methodology and results of the study are described in detail, followed by mobile-source emissions predictions based on the calibrated IVE model. This overall effort was designed to support estimates of the air pollution impacts of on-road transportation in Pune that can now be used extensively in the development of air quality and transportation management plans for the region. It is also hoped that the collected data can be extrapolated to other Indian cities to support further environmental improvement efforts.

Portable emission measurement systems (PEMS) are increasingly being used in a variety of transportation research projects to determine the impact of real-world vehicle emissions. One of the key questions that remain is how well these systems perform compared with testing that occurs in controlled laboratory conditions. To help answer this question, three PEMS were carefully evaluated for both gasoline and diesel light-duty vehicles in a dynamometer test facility. The evaluation was focused on the systems’ accuracy, time correspondence, and suitability for measuring transient emissions. Both cumulative mass emissions and modal emissions for carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NOx), and carbon dioxide (CO2) were measured for three gasoline and three diesel vehicles on three widely varying driving cycles. All of the PEMS proved to be both reasonably accurate and precise. The CO2 emissions measured by the PEMS were in excellent agreement (within 98%) with measurements from the laboratory system. Other pollutants measured were found to be in reasonable agreement (within 20% or better) for NOx and HC on diesel vehicles and CO on gasoline vehicles. The second-by-second emission rate measured with the PEMS matched well with the corresponding laboratory modal analyzer data for CO2, NOx, and CO under all driving cycles. Transient emissions of all pollutants agreed within 10% of the two systems for more than 6,000 data points from each vehicle. The results suggest that when properly set up and calibrated, PEMS are capable of measuring emissions from both gasoline and diesel vehicles to an accuracy within 20% of conventional laboratory modal analyzer systems.