PREDICTION OF RUNNING EMISSION FACTORS FROM PASSENGER VEHICLES IN AN URBAN AREA USING INTERNATIONAL VEHICLE EMISSIONS MODEL AS A COMPUTATIONAL TOOL (original) (raw)

Vehicles Emissions Under Different Driving Conditions in Urban Areas

Revista de Chimie

The road traffic is one of the main sources of atmospheric pollution in urban areas. This study aims to identify the emissions level for different driving regimes of diesel-powered vehicles that run into urban areas. The study has been performed in laboratory conditions and simulates various driving modes. This paper investigates the effects of vehicle speed, fuel consumption, acceleration, vehicle load on gaseous pollutant emissions (NOx, CO2, CO). The different pollution levels with smoke are also analyzed between idling regimes (maximum opacity index for fast acceleration between minimum and maximum speed) and different loads. The paper states some recommendations concerning the optimal operating regimes of the cars in urban areas, based on the conclusions on the measured levels of pollution.

On-Road Vehicle Emissions Forecast Using Ive Simulation Model

International Journal of Environmental Research, 2013

During the recent decades, rapid urbanization growth has led to even faster growth of motorvehicles and especially in large cities. Hence, evaluation of the actual level of traffic emissions has gained more interest. This paper, for the first time, presents a bottom-up approach for evaluation of vehicular emissions in Tehran- the capital of Iran- using the International Vehicle Emission (IVE) model. The IVE model uses local vehicle technology levels and its distributions, power based driving factors, vehicle soak distributions and meteorological parameters to tailor the model for specific evaluation of emissions. The results of this study demonstrate that carbon monoxide (CO) emission with 244.45 ton/hr during peak traffic hour is the most abundant criteria pollutant. About 25% of this quantity is emitted during start-up periods. Other pollutants such as NOX, VOCs, PM, VOCevap and SOX are ranked after CO accordingly. Also, carbon dioxide (CO2) emissions of 1744.22 ton/hr during the ...

Development and Application of an International Vehicle Emissions Model

Vehicle growth in developing nations is increasing rapidly, making 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 fleet, many nations have adopted modified versions of U.S.-or European-based 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 designed for use in developing countries has been developed, called 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. 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 two-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 have proven to be 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 rational behind the development of the model, development and application of the field studies, overview of the results to date, and planned next steps are described in this paper.

© Science and Education Publishing DOI:10.12691/ajvd-3-1-5 Variability in Vehicle ’ Exhaust Emissions and Fuel Consumption in Urban Driving Pattern

2015

Over the past several decades, Egypt observed rapid expansion of the transportation sector and increased fuel consumption triggered by rapid growth in population and urban areas. This has led to massive increase in number of vehicles and private vehicle per capita. In this paper, data for statistical analysis have been collected, where the remote sensing measurements based on one international cycle for urban area in Cairo, Egypt. Investigation of exhaust emission pollutants emitted by gasoline vehicles in metropolitan area of Cairo, Egypt has revealed four major pollutants affecting the emission rates of nitrogen oxide (NOx), carbon monoxide (CO), carbon dioxide (CO2) and hydrocarbon (HC). The variables affecting these pollutants are vehicle age, fuel delivery system, fuel composition and availability of catalytic converter. Moreover, Fuel consumption of three in-use passenger vehicles under laboratory driving conditions is estimated using the emission pollutants derived from remot...

Road vehicle emission factors development: A review

Atmospheric Environment, 2013

h i g h l i g h t s < The accuracy of road emission models is directly linked to the quality of their emission factors. < Road vehicles have a large natural variability in their emission profiles. < Emission factors may have different resolution according to their intended use. < Emission modellers should combine laboratory data with real-world measurements.

Variability in Vehicle' Exhaust Emissions and Fuel Consumption in Urban Driving Pattern

Over the past several decades, Egypt observed rapid expansion of the transportation sector and increased fuel consumption triggered by rapid growth in population and urban areas. This has led to massive increase in number of vehicles and private vehicle per capita. In this paper, data for statistical analysis have been collected, where the remote sensing measurements based on one international cycle for urban area in Cairo, Egypt. Investigation of exhaust emission pollutants emitted by gasoline vehicles in metropolitan area of Cairo, Egypt has revealed four major pollutants affecting the emission rates of nitrogen oxide (NO x), carbon monoxide (CO), carbon dioxide (CO2) and hydrocarbon (HC). The variables affecting these pollutants are vehicle age, fuel delivery system, fuel composition and availability of catalytic converter. Moreover, Fuel consumption of three in-use passenger vehicles under laboratory driving conditions is estimated using the emission pollutants derived from remote sensing and the fuel consumption formulation. The results indicate that the estimate of fuel consumption due to NOx emission pollutant ranged between 0.116-4.139 kg/km, due to CO emission pollutant ranged between 2.288-8.964 kg/km and due to HC emission pollutant ranged between 2.440-10.893 kg/km.

Evaluation Euro IV of effectiveness in transportation systems of Tehran on air quality: Application of IVE model

The quick growth of vehicles is due to fast urbanization in mega cities during last decades. This phenomenon has serious impacts on air quality, as emission from mobile vehicles is the major source of air pollution. As a result, any attempt to reduce the emitted air pollutants is needed. This study aims at improving the fuel quality in transporting system with particular emphasis on taxis in Tehran in 2014. As a clean fuel, Euro IV is being used to reduce the emission of pollution, toxic substances, and greenhouse gases. A bottom-up approach to evaluate vehicular emission, using IVE (International Vehicle Emission) model in Tehran, has been presented, which employs the local vehicle technology and its distributions, vehicle soak distributions, power based driving factors, and meteorological parameters to evaluate the emission, itself. Results show that the most abundant air pollutant (CO) has been reduced by 87.6% due to the clean fuel consumption (Euro IV). Also, the emission rates of the predominant toxic pollutant (Benzene) decreased by 98.7%. As a clean fuel, Euro IV managed to increase the emitted amount of CO 2 and NH 3. It can be concluded that upgrading transportation system with updated fuel quality is an essential step to improve air quality in Tehran.

Determination of fleet hourly emission and on-road vehicle emission factor using integrated monitoring and modeling approach

Atmospheric Research, 2008

Roadside air quality and vehicle emission are important and challenging issues in urban air quality management which need to be adequately characterized. This study involves designing a monitoring program that produces suitable data to determine the on-road hourly fleet emission and emission factors of individual vehicles in a street canyon. Simultaneous hourly monitoring of roadside gaseous pollutants (both windward and leeward sides), traffic volume and speed, and wind in a busy street of Bangkok was conducted in the rainy season when traffic emission was predominant in the city. Higher pollutant concentrations often occurred at midday (11:00 to 14:00h) when higher traffic density (3700-3800vehicles h − 1 , weekdays) was observed. The levels of toluene and xylenes found in this study are higher than the roadside levels reported in other Asian cities. Hourly maximum concentrations reached 258ppb for toluene, 51ppb for m,p-xylenes, 15ppb for o-xylene, 526ppb for NO x , and 10.5ppm for CO. Hourly monitoring data during the periods when the street canyon effects were pronounced were selected for determination of the fleet hourly emission and vehicle emission factors by back calculation using a street canyon model (Operational Street Pollution Model). The average fleet hourly emission at daytime of NO x (6.2kg km − 1 h − 1), CO (54kg km − 1 h − 1), toluene (2.1kg km − 1 h − 1), m,p-xylenes (0.73kg km − 1 h − 1) and o-xylene (0.27kg km − 1 h − 1) did not vary much. However, the emission rates were substantially reduced at nighttime following the traffic pattern. The obtained pollutant emission factors varied within each group of vehicles with the average values agreed reasonably with the chassis dynamometer results for NO x but somewhat higher for CO and TX. The model estimated results are, however, considered to better represent the real driving conditions in the street at the average vehicle travel speed of around 20km h − 1. A statistical sampling design is proposed to generate necessary data for the traffic emission inventory in a city.

Developing Speed Dependent Emission Factors for Real World Driving Conditions in India

Vehicular emission models are important tools in several environmental impact studies. Although several studies have been conducted for emission control purposes, few attempts have been made on the planning side. For instance, long-term transportation network capacity improvement models do not explicitly consider emission in the objective function. Incorporating vehicular emission into the objective function is effective only if speed dependent emission factor is used in the estimation of emission. Although this issue is well addressed in the developed countries, owing to the heterogeneity of vehicles and absence of speed dependent emission factors the benefit from network investment is often underestimated in developing countries like India. Therefore, an attempt is made to explore the possibility of developing speed dependent emission factor for Indian conditions and vehicles. For accurate measurement an onboard test is conducted on typical vehicles; namely, a passenger car, a sports utility vehicle, and a truck. On board test equipment collected the data while the vehicle traversed with different speed ranges. The data obtained is processed and used for developing emission factor in the form of second degree polynomial with speed as the dependent variable. The emission factors for the three types of vehicles and for CO, CO 2 , NO X , and HC are developed. The results have been compared with Indian driving cycle based emission factors as well as UK based speed dependent emission factors for car in particular. The study gave a preliminary insight into the behaviors of pollutants with respect to speed. However, there is a need to develop such factor using large spectrum of vehicles and diverse driving conditions.