VOC speciation of vehicle emissions: what is the impact on air quality modelling?

1998 ◽  
Vol 20 (1/2/3/4) ◽  
pp. 115 ◽  
Author(s):  
Anne Jaecker Voirol ◽  
Bernard Jouve ◽  
Philippe Quandatle ◽  
Julien Salles
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Air Quality Modelling ◽  
The Impact

Estimating Vehicular Emission Impact of Nighttime Construction with VISSIM and Different MOVES Emission Estimation Approaches

2018 ◽  
Vol 2672 (25) ◽  
pp. 174-186 ◽  
Author(s):  
Chaoyi Gu ◽  
Reza Farzaneh ◽  
Geza Pesti ◽  
Gabriel Valdez ◽  
Andrew Birt
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Operating Mode ◽  
Emission Model ◽  
Test Bed ◽  
Work Zones ◽  
Traffic Emission ◽  
Emission Estimation ◽  
The Impact ◽  
Nighttime Construction

Shifting work zones from daytime to nighttime is a potential solution to air quality issues on roadway with high traffic volume and where it is undesirable to close lanes during peak hours. The expected benefit of such shifting is to reduce total fuel consumption and on-road vehicle emissions. However, the magnitude of emission reductions and air quality impacts has not been examined comprehensively at work zones. The study presented in this paper investigated the traffic-related emission impacts of work zones using an urban freeway case study. A VISSIM test bed combined with the Environmental Protection Agency’s MOVES emission model was used to estimate total emissions assuming daytime and nighttime lane-closure scenarios. Vehicle emissions were estimated using a link-based method and operating mode-based method. The results from both methods demonstrated that nighttime construction has a significant impact on both traffic speeds and vehicle emissions, primarily as a result of reductions in vehicle miles traveled. In addition, a horizontal comparison between the results from the two methods was made to assess the impact of different emission estimation approaches. The outcomes from the comparison highlight the potential importance of the operating mode-based approach for accurately estimate total traffic emission quantities when data or simulations are available.

scholarly journals Development of a real-time on-road emission (ROE v1.0)model for street-scale air quality modeling based on dynamic traffic big data

2019 ◽  
Author(s):  
Luolin Wu ◽  
Ming Chang ◽  
Xuemei Wang ◽  
Jian Hang ◽  
Jinpu Zhang
Keyword(s):  
Big Data ◽  
Air Quality ◽  
Real Time ◽  
Urban Areas ◽  
Vehicle Emissions ◽  
Eastern China ◽  
Heavy Duty ◽  
Rapid Urbanization ◽  
The Impact ◽  
Road Emission

Abstract. Rapid urbanization in China has led to heavy traffic flows in street networks within cities, especially in eastern China, the economically developed region. This has increased the risk of exposure to vehicle-related pollutants. To evaluate the impact of vehicle emissions and provide an on-road emission inventory with higher spatial–temporal resolution for street-network air quality models, in this study, we developed the Real-time On-road Emission (ROE v1.0) model to calculate street-scale on-road hot emissions by using real-time big data for traffic provided by the Gaode map navigation application. This Python-based model obtains street-scale traffic data from the map application programming interface (API), which are open-access and updated every minute for each road segment. The results of application of the model to Guangzhou, one of the three major cities in China, showed on-road vehicle emissions of carbon monoxide (CO), nitrogen oxide (NOx), hydrocarbons (HC), PM10, and PM2.5 to be 35.22 × 104 Mg/a, 12.05 × 104 Mg/a, 4.10 × 104 Mg/a, 0.49 × 104 Mg/a, and 0.55 × 104 Mg/a, respectively. The spatial distribution reveals that the emission hotspots are located in some highway-intensive area and suburban town centers. Emission contributions show that the dominant contributors are light-duty vehicles (LDVs) and heavy-duty vehicles in urban areas and LDVs and heavy-duty trucks in suburban areas, indicating that the traffic control policies regarding duty trucks in urban areas are effective. In this study, the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) was applied to investigate the impact of traffic volume change on street-scale photochemistry in the urban area by using the on-road emission results from the ROE model. The modeling results indicate that the daytime NOx concentrations on national holidays are 26.5 % and 9.1 % lower than those on normal weekdays and normal weekends, respectively. Conversely, the national holiday O3 concentrations exceed normal weekday and normal weekend amounts by 13.9 % and 10.6 %, respectively, owing to changes in the ratio of emission of VOCs and NOx. Thus, not only the on-road emission, but other emissions should be controlled in order to improve the air quality in Guangzhou. More significantly, the newly developed ROE model may provide promising and effective methodologies for analyzing real-time street-level traffic emissions and high-resolution air quality assessment for more typical cities or urban districts.

Biofuels, vehicle emissions, and urban air quality

2016 ◽  
Vol 189 ◽  
pp. 121-136 ◽  
Author(s):  
Timothy J. Wallington ◽  
James E. Anderson ◽  
Eric M. Kurtz ◽  
Paul J. Tennison
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Urban Air Quality ◽  
Biodiesel Fuel ◽  
Urban Air ◽  
Mobile Source ◽  
Engine Calibration ◽  
Diesel Vehicles ◽  
Light Duty Vehicles ◽  
The Impact

Increased biofuel content in automotive fuels impacts vehicle tailpipe emissions via two mechanisms: fuel chemistry and engine calibration. Fuel chemistry effects are generally well recognized, while engine calibration effects are not. It is important that investigations of the impact of biofuels on vehicle emissions consider the impact of engine calibration effects and are conducted using vehicles designed to operate using such fuels. We report the results of emission measurements from a Ford F-350 fueled with either fossil diesel or a biodiesel surrogate (butyl nonanoate) and demonstrate the critical influence of engine calibration on NOx emissions. Using the production calibration the emissions of NOx were higher with the biodiesel fuel. Using an adjusted calibration (maintaining equivalent exhaust oxygen concentration to that of the fossil diesel at the same conditions by adjusting injected fuel quantities) the emissions of NOx were unchanged, or lower, with biodiesel fuel. For ethanol, a review of the literature data addressing the impact of ethanol blend levels (E0–E85) on emissions from gasoline light-duty vehicles in the U.S. is presented. The available data suggest that emissions of NOx, non-methane hydrocarbons, particulate matter (PM), and mobile source air toxics (compounds known, or suspected, to cause serious health impacts) from modern gasoline and diesel vehicles are not adversely affected by increased biofuel content over the range for which the vehicles are designed to operate. Future increases in biofuel content when accomplished in concert with changes in engine design and calibration for new vehicles should not result in problematic increases in emissions impacting urban air quality and may in fact facilitate future required emissions reductions. A systems perspective (fuel and vehicle) is needed to fully understand, and optimize, the benefits of biofuels when blended into gasoline and diesel.

scholarly journals Development of the Real-time On-road Emission (ROE v1.0) model for street-scale air quality modeling based on dynamic traffic big data

2020 ◽  
Vol 13 (1) ◽  
pp. 23-40
Author(s):  
Luolin Wu ◽  
Ming Chang ◽  
Xuemei Wang ◽  
Jian Hang ◽  
Jinpu Zhang ◽  
...  
Keyword(s):  
Big Data ◽  
Air Quality ◽  
Real Time ◽  
Urban Areas ◽  
Vehicle Emissions ◽  
Heavy Duty ◽  
Spatiotemporal Resolution ◽  
The Real ◽  
The Impact ◽  
Road Emission

Abstract. Rapid urbanization in China has led to heavy traffic flows in street networks within cities, especially in eastern China, the economically developed region. This has increased the risk of exposure to vehicle-related pollutants. To evaluate the impact of vehicle emissions and provide an on-road emission inventory with higher spatiotemporal resolution for street-network air quality models, in this study, we developed the Real-time On-road Emission (ROE v1.0) model to calculate street-scale on-road hot emissions by using real-time big data for traffic provided by the Gaode Map navigation application. This Python-based model obtains street-scale traffic data from the map application programming interface (API), which are open-access and updated every minute for each road segment. The results of application of the model to Guangzhou, one of the three major cities in China, showed on-road vehicle emissions of carbon monoxide (CO), nitrogen oxide (NOx), hydrocarbons (HCs), PM2.5, and PM10 to be 35.22×104, 12.05×104, 4.10×104, 0.49×104, and 0.55×104 Mg yr−1, respectively. The spatial distribution reveals that the emission hotspots are located in some highway-intensive areas and suburban town centers. Emission contribution shows that the dominant contributors are light-duty vehicles (LDVs) and heavy-duty vehicles (HDVs) in urban areas and LDVs and heavy-duty trucks (HDTs) in suburban areas, indicating that the traffic control policies regarding trucks in urban areas are effective. In this study, the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) was applied to investigate the impact of traffic volume change on street-scale photochemistry in the urban areas by using the on-road emission results from the ROE model. The modeling results indicate that the daytime NOx concentrations on national holidays are 26.5 % and 9.1 % lower than those on normal weekdays and normal weekends, respectively. Conversely, the national holiday O3 concentrations exceed normal weekday and normal weekend amounts by 13.9 % and 10.6 %, respectively, owing to changes in the ratio of emission of volatile organic compounds (VOCs) and NOx. Thus, not only the on-road emissions but also other emissions should be controlled in order to improve the air quality in Guangzhou. More significantly, the newly developed ROE model may provide promising and effective methodologies for analyzing real-time street-level traffic emissions and high-resolution air quality assessment for more typical cities or urban districts.

scholarly journals The impact of China's vehicle emissions on regional air quality in 2000 and 2020: a scenario analysis

2011 ◽  
Vol 11 (4) ◽  
pp. 13141-13192 ◽  
Author(s):  
E. Saikawa ◽  
J. Kurokawa ◽  
M. Takigawa ◽  
D. L. Mauzerall ◽  
L. W. Horowitz ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Road Transport ◽  
Transport Sector ◽  
Vehicle Emission ◽  
Mixing Ratios ◽  
Emission Standards ◽  
Regional Air Quality ◽  
The Impact ◽  
Surface O3

Abstract. The number of vehicles in China has been increasing rapidly. We evaluate the impact of current and possible future vehicle emissions from China on Asian air quality. We modify the Regional Emission Inventory in Asia (REAS) for China's road transport sector in 2000 using updated Chinese data for vehicle numbers, annual mileage and emission factors. We develop two scenarios for 2020: a scenario where emission factors remain the same as they were before any regulation was implemented (business-as-usual, BAU), and a scenario where Euro 3 vehicle emission standards are applied to all vehicles (except motorcycles and rural vehicles). The Euro 3 scenario is an approximation of what may be the case in 2020 as, starting in 2008, all new gasoline and diesel vehicles in China (except motorcycles) were required to meet the Euro 3 emission standards. Using the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem), we examine the regional air quality response to China's vehicle emissions in 2000 and in 2020 for the BAU and Euro 3 scenarios. We evaluate the 2000 model results with observations in Japan, China, Korea, and Russia. Under BAU in 2020, emissions of carbon monoxide (CO), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs), black carbon (BC) and organic carbon (OC) from China's vehicles more than double compared to the 2000 baseline. If all vehicles meet the Euro 3 regulations in 2020, however, these emissions are reduced by more than 50% relative to BAU. The implementation of stringent vehicle emission standards leads to a large, simultaneous reduction of the surface ozone (O3) mixing ratios and particulate matter (PM2.5) concentrations. In the Euro 3 scenario, surface O3 is reduced by more than 10 ppbv and surface PM2.5 is reduced by more than 10 μg m−3 relative to BAU in Northeast China in all seasons. In spring, surface O3 mixing ratios and PM2.5 concentrations in neighboring countries are also reduced by more than 3 ppbv and 1 μg m−3, respectively. We find that effective regulation of China's road transport sector will be of significant benefit for air quality both within China and across East Asia as well.

scholarly journals The impact of China's vehicle emissions on regional air quality in 2000 and 2020: a scenario analysis

2011 ◽  
Vol 11 (18) ◽  
pp. 9465-9484 ◽  
Author(s):  
E. Saikawa ◽  
J. Kurokawa ◽  
M. Takigawa ◽  
J. Borken-Kleefeld ◽  
D. L. Mauzerall ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Road Transport ◽  
Transport Sector ◽  
Vehicle Emission ◽  
Mixing Ratios ◽  
Emission Standards ◽  
Regional Air Quality ◽  
The Impact ◽  
Surface O3

Abstract. The number of vehicles in China has been increasing rapidly. We evaluate the impact of current and possible future vehicle emissions from China on Asian air quality. We modify the Regional Emission Inventory in Asia (REAS) for China's road transport sector in 2000 using updated Chinese data for the number of vehicles, annual mileage, and emission factors. We develop two scenarios for 2020: a scenario where emission factors remain the same as they were in 2000 (No-Policy, NoPol), and a scenario where Euro 3 vehicle emission standards are applied to all vehicles (except motorcycles and rural vehicles). The Euro 3 scenario is an approximation of what may be the case in 2020 as, starting in 2008, all new vehicles in China (except motorcycles) were required to meet the Euro 3 emission standards. Using the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem), we examine the regional air quality response to China's vehicle emissions in 2000 and in 2020 for the NoPol and Euro 3 scenarios. We evaluate the 2000 model results with observations in Japan, China, Korea, and Russia. Under NoPol in 2020, emissions of carbon monoxide (CO), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs), black carbon (BC), and organic carbon (OC) from China's vehicles more than double compared to the 2000 baseline. If all vehicles meet the Euro 3 regulations in 2020, however, these emissions are reduced by more than 50% relative to NoPol. The implementation of stringent vehicle emission standards leads to a large, simultaneous reduction of the surface ozone (O3) mixing ratios and particulate matter (PM2.5) concentrations. In the Euro 3 scenario, surface O3 is reduced by more than 10 ppbv and surface PM2.5 is reduced by more than 10 μg m−3 relative to NoPol in Northeast China in all seasons. In spring, surface O3 mixing ratios and PM2.5 concentrations in neighboring countries are also reduced by more than 3 ppbv and 1 μg m−3, respectively. We find that effective regulation of China's road transport sector will be of significant benefit for air quality both within China and across East Asia as well.

scholarly journals The impact of measures to reduce ambient air PM<sub>10</sub> concentrations originating from road dust, evaluated for a street canyon in Helsinki

2019 ◽  
Vol 19 (17) ◽  
pp. 11199-11212 ◽  
Author(s):  
Ana Stojiljkovic ◽  
Mari Kauhaniemi ◽  
Jaakko Kukkonen ◽  
Kaarle Kupiainen ◽  
Ari Karppinen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Street Canyon ◽  
Dust Emission ◽  
Road Dust ◽  
Ambient Air ◽  
Air Quality Measurements ◽  
Emission Models ◽  
The Impact ◽  
Quality Measurements

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

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