International Vehicle Emission Model Research Articles

Assessing the Additional Benefits of Thailand’s Approaches to Reduce Motor Vehicle Emissions

Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to curb greenhouse gas (GHG) emissions in line with the requirements and commitments of the Paris Agreement. The evaluation of specific air pollutants and GHG emissions originating from road vehicles utilises the Thailand database, referencing the year 2019. Data intersections from 2019 to 2022 are grounded in actual data collected from relevant departments in Thailand, while projections for 2023–2030 are forecasted based on the baseline year. The secondary database used in the International Vehicle Emission model is adjusted according to real-world driving data to accurately reflect country-specific emission factors. Dynamic emission factors for specific air pollutants and GHGs are evaluated and integrated with the average Vehicle Kilometres Travelled (VKT) for each vehicle category. The Business-As-Usual (BAU) scenario is then examined, based on existing policies aimed at reducing air pollutants and GHG emissions in Thailand’s transport sector. These policies include strategies for the adoption of electric vehicles and the promotion of public transport to reduce VKT. Under the BAU scenario, the overall number of road vehicles in Thailand, including passenger cars, motorcycles, pickups, vans, trucks, and buses, is expected to increase by approximately 6.58% by 2030, leading to a rise in specific air pollutants and GHG emissions compared to the 2019 baseline. However, by adhering to Thailand’s strategies and transitioning to new electric passenger cars and buses, greenhouse gas emissions and specific air pollutants from the road transport sector will be significantly reduced.

Estimation of on-road mobile emissions based on the vehicle technology in a high-traffic avenue in Panama City, Panama

This study addresses the emissions from mobile sources in a busy avenue. Latest mobile emission inventories estimated pollutants based on fuel sales activities in the country. While this is an approved methodology, it does not consider the characteristics of vehicles and their emissions control systems. Applying the International Vehicle Emissions (IVE) model involves low costs, the vehicle fleet’s technology features, and the study region’s environmental parameters. The IVE model allows a better understanding of how vehicle technology impacts air quality. This study aims to generate information about vehicle emissions in Panama using a model that considers factors like vehicle technology, driving patterns, and local conditions, all of which influence air pollution in the region. The focuses are on passenger vehicles, the most common in the country, particularly in one of the densest districts. Carbon monoxide (CO), sulfates (SOx), nitrogen oxide (NO, and particulate matter (PMx) emissions were estimated with the IVE model, the first one stood out, represented 98% (6479.82 g/km) of the air pollutants emitted into the atmosphere by these four gases. Finally, it is established that the combination of emission control technologies and vehicle features is what will determine its emission reduction efficiency. Only in diesel vehicles, an increase in PMx emissions was identified.

Assessment of sustainable school transport policies on vehicular emissions using the IVE model

The increased vehicle demand leads to a rise in congestion, exhaust emissions and travel duration. It makes countries adopt policies to reduce vehicular exhaust emissions to achieve sustainable development with improved air quality. The present study identifies factors that influence student's preferences, estimate vehicular emissions and examine policies to minimize use of passive school transport (PST). The responses of 945 students are statistically examined using the Multinominal Logit (MNL) model with factors that affect preferences of school transport. The MNL model revealed that private transports are preferred more by female students. Students covering up to 3 km distance preferred more to use active school transport (AST) than students with travel distance of above 5 km. The model has predicted that students with travel distance of 4 km or above are mostly opted for public travel modes. The representative driving cycle was developed for morning and afternoon school trips and used as an input parameter for the International Vehicle Emission (IVE) model to estimate exhaust emissions. School policies are proposed to reduce PST modes associated student kilometer travelled (SKT) and emissions. The study outcomes revealed that neighborhood school policy predicted significant reduction in yearly SKT for AST (6.07%) and PST (36.03%) modes. While increased walkability policy anticipates modest impact in minimizing the PST mode associated total exhaust emissions (3.18–40.34%). The private vehicle associated SKT and total exhaust emissions are reduced by nearly 27.58% and 34.66% under increased use of public transport policy respectively.

On-road vehicle emission inventory and its spatial and temporal distribution in the city of Guayaquil, Ecuador

Emissions from mobile sources have become a major concern for health, environmental sustainability and climate change and high-resolution inventories are needed to support the design and assessment of abatement measures in urban areas. This study addresses the development of a traffic emissions inventory for Guayaquil, the second largest city in Ecuador, using the International Vehicle Emissions Model (IVE). Emissions are allocated with a spatial resolution of 1 km × 1 km and a temporal resolution of 1 h using a top-down methodology. This application combines traffic statistics already available in the city with the data from a field campaign to characterize vehicle fleet composition and activity patterns. The estimated annual emissions for the city were 237.1 kt of CO, 46.4 kt of NOx, 28.5 kt of VOC, 7.7 kt of PM10, 0.70 kt of SO2 and 4549.7 kt of CO2. 92.3 % of CO and 85.4 % of VOC were emitted by light gasoline vehicles, including private passenger vehicles and taxis, which represents 68.6 % and 8.8 %, respectively of the total fleet and contributes 52 % and 22 % of the total vehicle kilometer traveled (VKT), respectively. 48.9 % of NOx and 82 % of PM10 were emitted by the bus fleet although buses only represent 7.5 % of the total fleet and contribute 10.6 % of total VKT in the city. 41.1 % and 36.5 % of CO2 were emitted by buses and private vehicles, respectively. Even though, the average age of the fleet is below 10 years, the fleet in Guayaquil presents outdated emission standards and high emission factors. We found the higher emission rates in dense populated areas are associated to secondary roads. There is not much variability of emissions between months, but the typical daily pattern of emissions shows a peak in the morning and another in the afternoon.

Assessment of different methods in analyzing motor vehicle emission factors.

To explore the emission characteristics of vehicle's pollutants is of great significance to prevent and control the diffusion of pollutants. Limited by geographic location and economic condition, the model- and guideline-based studies on vehicle's emission factor have become more concerned measures than the actual measurement. By analyzing the actual operating conditions of motor vehicles, this study obtains the emission factors of typical pollutants from different motor vehicles by adopting international vehicle emission (IVE) model and guideline method, respectively. Furthermore, the resulting emission factors by the above methods were compared and analyzed with on-road method. The results show that: (1) the emission factors of vehicle pollutants change regularly with velocity, emission standard, and accumulated mileage. Taking CO as an example, its emission factor shows a downward trend with the increase of velocity and emission standard and an upward trend with the increase of accumulated mileage; (2) compared with the actual measurement, the vehicle emission factor obtained by the guideline method has a large error, while the IVE model is close to the actual.

Effects of meteorological parameters and fuel composition on the air pollution production from motor vehicles.

The aim of this study was to investigate the effect of changes in meteorological parameters and fuel composition on the emission rate of air pollutants in the vehicle fleet of the Tehran Metropolis. The results of this study can be used in management decisions to reduce the emission of air pollutants. In this paper, based on the international vehicle emission model and using mathematical equations, the effects of changing meteorological parameters and fuel composition on the emission of pollutants were modeled. The emission rates of CO, VOCs, and NOx pollutants were the most sensitive to the changes in meteorological parameters, respectively. Among all parameters studied in this research, the changes in sulfur level had the greatest effect on the emission of pollutants from the vehicle fleet of Tehran Metropolis. If the fuel was replaced with Euro 5 standard instead of Euro 3, the emission rates of CO, VOCs, NOx, PM, and SOx pollutants from the vehicle fleet of Tehran Metropolis would be reduced by 9%, 6%, 5%, 14%, and 90%, respectively. Managing and reducing the sources of production and emission of air pollution is one of the best ways to reduce the air pollution. In general, since the emission of pollutants from the fleet of Tehran Metropolis in the cold seasons of the year is greater than during hot seasons and the problem of air pollution is exacerbated by air stability, using Euro 5 fuel in cold seasons is one of the efficient ways to reduce the air pollution.

Emissions Control Scenarios for Transport in Greater Cairo.

Air pollution is a major cause of premature death in Greater Cairo, but studies on emission control are limited. We used local and international data to predict the impact of transport emission control measures on sector parameters including congestion. The International Vehicle Emission model accordingly estimated quantities of criteria, toxic and global warming emissions produced by on-road vehicles. Emissions were estimated for 2019 base case (2019-BC) and projected for 2030 under the ‘do nothing’ scenario (2030-DNS) and five scenarios: fuel subsidy removal (2030-FSR), road expansions (2030-RE), public transport improvements (2030-PTI), inspection and maintenance (I/M) programs (2030-I/MP), and fuel enhancements (2030-FE). The 2030-FSR would reduce emissions by 11.2% versus 2030-DNS. The 2030-RE resulted in an average increase of 37% in emissions compared with 2030-DNS since it induces more traffic. The 2030-PTI provides alternatives to car travel; hence, cars result in an average drop of 32.8% for all emission types compared with 2030-DNS. The 2030-I/MP exhibited reductions in PM10 and toxic pollutants, of 35–54.8% compared with 2030-DNS. The 2030-FE reduced SOx, benzene and N2O emissions by 91.8%, 81% and 39.1%, respectively, compared with 2030-DNS. The 2030-I/MP is most effective in reducing health damaging pollutants while 2030-PTI positively impacts commuters’ lifestyle.

Estimation of Pollutant Emissions in Real Driving Conditions Based on Data from OBD and Machine Learning.

This article proposes a methodology for the estimation of emissions in real driving conditions, based on board diagnostics data and machine learning, since it has been detected that there are no models for estimating pollutants without large measurement campaigns. For this purpose, driving data are obtained by means of a data logger and emissions through a portable emissions measurement system in a real driving emissions test. The data obtained are used to train artificial neural networks that estimate emissions, having previously estimated the relative importance of variables through random forest techniques. Then, by the application of the K-means algorithm, labels are obtained to implement a classification tree and thereby determine the selected gear by the driver. These models were loaded with a data set generated covering 1218.19 km of driving. The results generated were compared to the ones obtained by applying the international vehicle emissions model and with the results of the real driving emissions test, showing evidence of similar results. The main contribution of this article is that the generated model is stronger in different traffic conditions and presents good results at the speed interval with small differences at low average driving speeds because more than half of the vehicle’s trip occurs in urban areas, in completely random driving conditions. These results can be useful for the estimation of emission factors with potential application in vehicular homologation processes and the estimation of vehicular emission inventories.

The emission factor adjustments of the passenger cars in multi-story car parks under drive modes.

The drive mode is an important factor that affects the adjustment requirements for emission factors of the conventional simulation methods in multi-story car parks. In order to propose comprehensive emission factor adjustments for passenger cars based on the drive modes, the present study is aimed to investigate the effects of different drive modes on emission factors for multi-story car parks. Thus, to achieve this aim, the tailpipe emissions based on the on-board measurement and international vehicle emission (IVE) model are obtained. The results indicate that the drive modes significantly affect the emissions. Accordingly, the change in drive mode from minimum to maximum leads to an increase in the vehicle-specific power (VSP) by 106%. Furthermore, the results of emission factors show the discrepancy between on-board measurement and IVE model with the maximum and minimum adjustment factors by 3.28 and 1.28 for carbon monoxide (CO) and carbon dioxide (CO2), respectively.

ESTIMATION OF CARBON DIOXIDE EMISSIONS ON HETEROGENEOUS TRAFFIC BASED ON METROPOLITAN TRAFFIC EMISSIONS INVENTORY MODEL

Traffic on the arterial roads of Makassar City is categorized as heterogeneous traffic and can increase motor vehicle emissions. This study aims to estimate CO2 emissions from vehicles during morning and evening rush-hour traffic on nine arterial roads. This study used the MARNI model approach, which is a prediction model of vehicle emissions in heterogeneous traffic based on moving vehicles, and adapted it to the International Vehicle Emission Model (IVEM). The four factors that are considered to predict vehicle emissions are emission factors, driving cycle as a reference for vehicle speed, vehicle operational characteristics, and travel time. As a result, from 31 vehicle categories, the highest CO2 emissions are CV24: MPFI, 3 Way/EGR, Medium, and 0–6 years. The highest and lowest vehicle volumes and total CO2 emissions occurred on the RD3 and RD5 roads, respectively. This indicates a linear correlation between the vehicle volume and the levels of CO2 emissions. For future studies, the MARNI model can be used as a reference for predicting the emissions of motorcycles and heavy vehicles.

Unregulated Emissions from Natural Gas Taxi Based on IVE Model

Emissions from motor vehicles have gained the attention of government agencies. To alleviate air pollution and reduce the petroleum demand from vehicles in China, the policy of “oil to gas” was vigorously carried out. Qingdao began to promote the use of natural gas vehicles (NGVs) in 2003. By the end of 2016, there were 9460 natural gas (NG) taxis in Qingdao, which accounted for 80% of the total taxis. An understanding of policy implementation for emission reductions is required. Experiments to obtain the taxi driving conditions and local parameters were investigated and an international vehicle emissions (IVE) localization model was established. Combined with vehicle mass analysis system (VMAS) experiments, the IVE localization model was amended and included the taxi pollutant emission factors. The result indicates that annual total carbon monoxide (CO) emissions from actual taxis are 6411.87 t, carbureted hydrogen (HC) emissions are 124.85 t, nitrogen oxide (NOx) emissions are 1397.44 t and particulate matter (PM) emissions are 8.9 t. When the taxis are running on pure natural gas, the annual emissions of CO, HC, NOx and PM are 4942.3 t, 48.15 t, 1496.01 t and 5.13 t, respectively. Unregulated emissions of annual total formaldehydes, benzene, acetaldehyde, 1,3-butadience emissions from an actual taxi are 65.99 t, 4.68 t, 1.04 t and 8.83 t. When the taxi is running on pure natural gas, the above unregulated emissions are 12.11 t, 1.27 t, 1.5 t and 0.02 t, respectively.

Climate co-benefits of alternate strategies for tourist transportation: The case of Murree Hills in Pakistan.

This study explores the climate impacts of on-road tourist transportation with alternate mitigation strategies. To this end, greenhouse gas (GHG) emissions for 2016 and emissions under four "what-if" scenarios were estimated for a popular tourist site in Pakistan, i.e., Murree Hills, using the international vehicle emissions model. Alternate scenarios included occupancy optimization, bus transit system, and Euro II and Euro IV implementation. The emissions were further decomposed using the log mean Divisia index method to study the drivers of global warming potential (GWP) mitigation. As per the results, the total 20-year GWP for 2016 was equal to 51,262 tons CO2 equivalent, and maximum reduction was achieved under the bus transit system scenario having a 20-year GWP of 25,736 tons CO2 equivalent, i.e., 49.8% reduction. Relative to the base year, GWP reductions were also quite significant for Euro IV (46.8%), Euro II (45.8%), and occupancy optimization (32.3%) scenarios. For the base year, CO2 held a share of 87.3% in total emissions; however, its share in the 20-year GWP was 39.7% indicating its reduced impact on total GWP as compared to N2O, CO, NOx, VOC, and CH4. Based on the decomposition results for alternate scenarios, GWP mitigation was mainly driven by CO, CH4, NOx, VOCs, and partially by CO2, while N2O negatively affected GWP mitigation. These results provide several policy-level instruments for developing countries to design a transition to an eco-friendly tourist transport management system. The policy implications from this study can be used to promote an eco-tourism industry.

Influences of accumulated mileage and technological changes on emissions of regulated pollutants from gasoline passenger vehicles

In this study, the influences of accumulated mileage (deterioration) and technological changes (emission standards) on emission factors (EFs) of regulated pollutants (CO, HC, and NOx) from gasoline passenger vehicles were investigated based on Inspection and Maintenance (I/M) data using the chassis dynamometer method. The accumulated mileage of passenger vehicles was significantly linearly correlated with vehicle age. For most cases, the average EFs of CO, HC and NOx were significantly linearly correlated with accumulated mileage, indicating that emission deterioration had a significant impact on pollutant EFs. Implemented emission standards markedly influenced the EFs of regulated pollutants, and EFs markedly decreased with progressing emission standards. The present study also compared EFs of regulated pollutants between this study and the International vehicle emission (IVE) model, and marked differences in EFs were seen with variations in emission standards, vehicle types and accumulated mileage; NOx EFs in this study were higher than in the IVE model. The results provide new insight into estimating regulated pollutant emissions using the IVE model.

Investigation and sensitivity analysis of air pollution caused by road transportation at signalized intersections using IVE model in Iran

IntroductionThe development of urbanization has had many negative outcomes in different societies. Population growth and the increase in the transportation are the consequences of urban growth which has resulted into problems. Vehicles are responsible for 90% of air pollution in Iran and it is essential to use authentic models of traffic emissions in accordance with the current conditions to predict this and future emissions. Iran has a lot of different air pollution dispersion parameters compared with the developed countries.MethodIn this paper air pollution emission parameters in signalized intersections have been modelled and results have been compared to measured concentrations of air pollution in intersections. For this purpose the use of IVE (International Vehicle Emission) model that is common air pollution modelling and besides, Sensitivity Analysis has been performed to show modeling accuracy in comparison with current emissions.ResultBy modeling and measurement results, it’s easily understood in warm seasons emission concentration is more than cold seasons. Minimum and maximum rate of Carbon-monoxide (CO) and Nitrogen-oxides (NOX) has been evaluated.ConclusionIVE model has shown a bit difference amount of pollutions by comparison with field measurement emission. It could be said it is appropriate for model vehicle emission in Iran.

The effects of deterioration and technological levels on pollutant emission factors for gasoline light-duty trucks

ABSTRACTVehicle deterioration and technological change influence emission factors (EFs). In this study, the impacts of vehicle deterioration and emission standards on EFs of regulated pollutants (carbon monoxide [CO], hydrocarbon [HC], and nitrogen oxides [NOx]) for gasoline light-duty trucks (LDTs) were investigated according to the inspection and maintenance (I/M) data using a chassis dynamometer method. Pollutant EFs for LDTs markedly varied with accumulated mileages and emission standards, and the trends of EFs are associated with accumulated mileages. In addition, the study also found that in most cases, the median EFs of CO, HC, and NOx are higher than those of basic EFs in the International Vehicle Emissions (IVE) model; therefore, the present study provides correction factors for the IVE model relative to the corresponding emission standards and mileages.Implications: Currently, vehicle emissions are great contributors to air pollution in cities, especially in developing countries. Emission factors play a key role in creating emission inventory and estimating emissions. Deterioration represented by vehicle age and accumulated mileage and changes of emission standards markedly influence emission factors. In addition, the results provide collection factors for implication in the IVE model in the region levels.

Human health risk due to variations in PM10-PM2.5 and associated PAHs levels

WHO (2012) reports that chronic exposure to air pollutants, including particulate matter (PM), causes the death of 7 million people, constituting the most important environmental risk for health in the world. IARC classifies contaminated outdoor air as carcinogenic, Group 1 category. However, in our countries there are few studies regarding air pollution levels and possible associated effects on public health.The current study determined PM and associated polycyclic aromatic hydrocarbons (PAHs) levels in outdoor air, identified their possible emission sources and analysed health risks in the city of Tandil (Argentina). PM10 and PM2.5 samples were collected using a low volume sampler (MiniVol TAS) in three areas: city centre, industrial and residential. Concentrations were determined by gravimetric methods and the content of the US EPA 16 priority PAHs was found by high performance liquid chromatography (HPLC). Description of the main emission sources and selection of monitoring sites resulted from spatial analysis and the IVE (International Vehicle Emissions) model was used in the characterisation of the traffic flow. Median values of 35.7 μgm-3 and 9.6 μgm-3 in PM10 and PM2.5 respectively and characteristic profiles were found for each area. Local values PAHs associated to PM10 and PM2.5, in general, were lower than 10ngm-3. The estimated Unit Risk for the three areas exceeds US EPA standards (9 × 10−5). The number of deaths attributable to short term exposure to outdoor PM10 was 4 cases in children under 5 years of age, and 21 cases in total population, for a relative risk of 1.037.

DYNAMIC AIR TOXIC EMISSION FACTOR OF MOTORCYCLES IN BANGKOK, THAILAND

Average emission factors of air toxic compounds, emitted from motorcycles in Bangkok, Thailand were analyzed using the IVE (International Vehicle Emission) model. The model was utilized taking into account the actual fleet and characteristics of motorcycles of the study area. Four air toxic compounds (namely benzene, 1,3 butadiene, acetaldehyde and formaldehyde) and their emission rates were calculated under two main pollution abatement scenarios (the improvement of fuel quality and switching of fuel types). The results were then compared with the BAU (Business as Usual) case to illustrate the effectiveness and appropriateness of proposed measures. In the BAU scenario the average emission factors of air toxics from motorcycles were greatly reduced by the replacement of engine technology from the carburetor system with the electronically controlled fuel injection system. Improvement of fuel quality standard (from EURO II to EURO IV) resulted in a decrease in average emission factors of air toxics from motorcycles. Calculated results indicated that the average emission factors of air toxic compounds in the year 2012 when this policy began as implemented by the Thai government were approximately 93 %, 62 %, 59 % and 59 %, a decrease as compared to the BAU case in the same year for benzene, 1,3-butadiene, acetaldehyde and formaldehyde, respectively. The introduction of gasohol as alternative fuel was found to greatly influence the emission factors of acetaldehyde and formaldehyde. Calculated results in the year 2012 indicated that acetaldehyde average emission factor increased from 123mg/km (BAU case) to 2,272 mg/km (gasohol scenario) in the same year. However, the average emission factors of benzene and 1,3 butadiene that were the result of gasohol usage were less when compared with the BAU case.

Real world vehicle emissions: Their correlation with driving parameters

Vehicular population in developing countries is expected to proliferate in the coming decade, centred on Tier II and Tier III cities rather than large metropolis. WLTP is being introduced as a global instrument for emission regulation to reduce gap between standard test procedures and actual road conditions. This work aims at quantifying and discernment of the gap between WLTC and real-world conditions in an urban city in a developing country on the basis of driving cycle parameters and simulated emissions for gasoline fuelled light passenger cars. Real world driving patterns were recorded on different routes and varying traffic conditions using car-chasing technique integrated with GPS monitoring and speed sensors. Real-world driving patterns and ambient conditions were used to simulate emissions using International Vehicle Emissions model for average rate (g/km) and Comprehensive Modal Emissions Model for instantaneous emission (g/s) analysis. Cycle parameters were mathematically calculated to compare WLTC and road trips. The analyses revealed a large gap between WLTC and road conditions. CO emissions were predicted to be 155% higher than WLTC and HC and NOx emissions were estimated to be 63% and 64% higher respectively. These gaps were correlated to different driving cycle parameters. It was observed that road driving occurs at lower average speeds with higher frequency and magnitudes of accelerations. The positive kinetic energy required by road cycles, was 100% higher than WLTC and the Relative Positive Acceleration (RPA) demanded by road cycles, was found to be 60% higher in real-world driving patterns and thereby contribute to higher emissions.

EFFECT OF SPEED ON EMISSIONS OF AIR POLLUTANTS IN URBAN ENVIRONMENT: CASE STUDY OF TRUCK EMISSIONS

Dynamic emission factors and emission inventories of CO, VOC, VOCevap., NOx, SOx and PM of truck in Bangkok, Thailand were developed using IVE (International vehicle emission) model for the year 2012 to 2024. The year 2012 was chosen as base year since fuel quality had been improved from Euro II to Euro IV standard from that year. Speed of truck driven in study area was chosen as variable parameter for sensitivity analysis of its influence to the emissions of air pollutants because there are no further plans in upgrading or improvement of fuel quality during this period. Truck's Bangkok driving cycle was used as input data in the IVE model. Average speeds used in the model simulation were varied from existing condition (15 km/hr) to the maximum of 80 km/hr. It was found that an average speed of 40 km/hr was the optimal speed in reducing of air pollutants emitted from truck. At this speed, reduction of emission factors of air pollutants as compared with current average velocity of 15 km/hr were about 46%, 54%, 16%, 51%, 53% and 27% for CO, VOC, VOCevap., NOx, SOx and PM, respectively. Therefore, efforts in increasing average speed of at least to about 40 km/hr can be used as a measure to achieve the sustainable transport particularly in the green logistic businesses.

SUCCESS OF FUEL QUALITY IMPROVING POLICY IN REDUCING BENZENE AIR CONCENTRATIONS IN BANGKOK

The Thai's policy in improving of fuel quality to the changing of emissions and concentrations of air pollutants in Bangkok is evaluated in this study. Benzene content in gasoline had been decreased from 3.5% (EURO II standard) to less than 1.0% (EURO IV standard) since the year 2012. The IVE (International Vehicle Emission) model was applied to develop emission factor of benzene taking into consideration actual fleets and characteristics of vehicles in Bangkok. These vehicles consisted of passenger car, motorcycle, van and pick up, taxi, bus and truck. Then, emission inventory of benzene emitted from mobile sources was calculated. It was found that about 83% of total emissions of benzene were contributed from motorcycle (43%) and passenger car (40%). Emission amounts were reduced from 1.32 x 10 3 ton/year to 0.57 x 10 3 ton/year as resulted from changing of fuel quality from EURO II to EURO IV standard. AERMOD dispersion model was used to simulate ambient ground level concentration of benzene prior and after implementing this policy. Results revealed significantly reduction of benzene concentrations in Bangkok's environment. Spatial distribution of benzene pollution map illustrated that areas having annual concentration higher than 1.7 g/m 3 (the Thai's air quality standard for benzene) were still only found in traffic-congested zone of the central business district in the metropolitan area.