scholarly journals How much does traffic contribute to benzene and PAH air pollution? Results from a high-resolution North American air quality model centered on Toronto, Canada

2019 ◽  
Author(s):  
Cynthia H. Whaley ◽  
Elisabeth Galarneau ◽  
Paul A. Makar ◽  
Michael D. Moran ◽  
Junhua Zhang
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Motor Vehicle ◽  
Ambient Air ◽  
Motor Vehicles ◽  
Road Vehicle ◽  
Model Domain ◽  
Pollutant Concentrations ◽  
Atmospheric Processing ◽  
Emissions Inventories

Abstract. Benzene and polycyclic aromatic hydrocarbons (PAHs) are toxic air pollutants that have long been associated with motor vehicle emissions, though the importance of such emissions has never been quantified over an extended domain using a chemical transport model. Herein we present the first application of such a model (GEM-MACH-PAH) to examine the contribution of motor vehicles to benzene and PAHs in ambient air. We have applied the model over a region that is centered on Toronto, Canada, and includes much of southern Ontario and the northeastern United States. The resolution (2.5 km) was the highest ever employed by a model for these compounds in North America, and the model domain was the largest at this resolution in the world to date. Using paired model simulations that were run with vehicle emissions turned on and off (while all other emissions were left on), we estimated the absolute and relative contributions of motor vehicles to ambient pollutant concentrations. Our results provide estimates of motor vehicle contributions that are realistic as a result of the inclusion of atmospheric processing, whereas assessing changes in benzene and PAH emissions alone would neglect effects caused by shifts in atmospheric oxidation and particle/gas partitioning. A secondary benefit of our scenario approach is in its utility in representing a fleet of zero emission vehicles (ZEV), whose adoption is being encouraged in a variety of jurisdictions. Our simulations predicted domain-average on-road vehicle contributions to benzene and PAH concentrations of 4–21 % and 14–24 % in the spring–summer and fall–winter periods, respectively, depending on the aromatic compound. Contributions to PAH concentrations up to 50 % were predicted for the Greater Toronto Area, with a domain maximum of 91 %. Such contributions are substantially higher than those reported in national emissions inventories, and they also differ from inventory estimates at the sub-national scale because those do not account for the physico-chemical processing that alters pollutant concentrations in the atmosphere. The removal of on-road vehicle emissions generally led to decreases in benzene and PAH concentrations during both periods that were studied, though atmospheric processing (such as chemical reactions and changes to gas/particle partitioning) contributed to non-linear behaviour at some locations or times of year. Such results demonstrate the added value associated with regional air quality modelling relative to examinations of emissions inventories alone. We also found that removing on-road vehicle emissions reduced spring–summertime surface O3 volume mixing ratios and fall–wintertime PM10 concentrations each by ~ 10 % in the model domain, providing further air quality benefits. Toxic equivalents contributed by vehicle emissions of PAHs were found to be substantial (20–60 % depending on location), and this finding is particularly relevant to the study of public health in the urban areas of our model area where human population, ambient concentrations, and traffic volumes tend to be high.

scholarly journals How much does traffic contribute to benzene and polycyclic aromatic hydrocarbon air pollution? Results from a high-resolution North American air quality model centred on Toronto, Canada

2020 ◽  
Vol 20 (5) ◽  
pp. 2911-2925 ◽  
Author(s):  
Cynthia H. Whaley ◽  
Elisabeth Galarneau ◽  
Paul A. Makar ◽  
Michael D. Moran ◽  
Junhua Zhang
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Motor Vehicle ◽  
Motor Vehicles ◽  
Road Vehicle ◽  
Model Domain ◽  
Pollutant Concentrations ◽  
Atmospheric Processing ◽  
Polycyclic Aromatic ◽  
Emissions Inventories

Abstract. Benzene and polycyclic aromatic hydrocarbons (PAHs) are toxic air pollutants that have long been associated with motor vehicle emissions, though the importance of such emissions has never been quantified over an extended domain using a chemical transport model. Herein we present the first application of such a model (GEM-MACH-PAH) to examine the contribution of motor vehicles to benzene and PAHs in ambient air. We have applied the model over a region that is centred on Toronto, Canada, and includes much of southern Ontario and the northeastern United States. The resolution (2.5 km) was the highest ever employed by a model for these compounds in North America, and the model domain was the largest at this resolution in the world to date. Using paired model simulations that were run with vehicle emissions turned on and off (while all other emissions were left on), we estimated the absolute and relative contributions of motor vehicles to ambient pollutant concentrations. Our results provide estimates of motor vehicle contributions that are realistic as a result of the inclusion of atmospheric processing, whereas assessing changes in benzene and PAH emissions alone would neglect effects caused by shifts in atmospheric oxidation and particle–gas partitioning. A secondary benefit of our scenario approach is in its utility in representing a fleet of zero-emission vehicles (ZEVs), whose adoption is being encouraged in a variety of jurisdictions. Our simulations predicted domain-average on-road vehicle contributions to benzene and PAH concentrations of 4 %–21 % and 14 %–24 % in the spring–summer and fall–winter periods, respectively, depending on the aromatic compound. Contributions to PAH concentrations up to 50 % were predicted for the Greater Toronto Area, and the domain maximum was simulated to be 91 %. Such contributions are substantially higher than those reported at the national level in Canadian emissions inventories, and they also differ from inventory estimates at the subnational scale in the US. Our model has been run at a finer spatial scale than reported in those inventories, and furthermore includes physico-chemical processing that alters pollutant concentrations after their release. The removal of on-road vehicle emissions generally led to decreases in benzene and PAH concentrations during both periods that were studied, though atmospheric processing (such as chemical reactions and changes to particle–gas partitioning) contributed to non-linear behaviour at some locations or times of year. Such results demonstrate the added value associated with regional air quality modelling relative to examinations of emissions inventories alone. We also found that removing on-road vehicle emissions reduced spring–summertime surface O3 volume mixing ratios and fall–wintertime PM10 concentrations each by ∼10 % in the model domain, providing further air quality benefits. Toxic equivalents contributed by vehicle emissions of PAHs were found to be substantial (20 %–60 % depending on location), and this finding is particularly relevant to the study of public health in the urban areas of our model domain where human population, ambient concentrations, and traffic volumes tend to be high.

scholarly journals Estimasi Beban Pencemar Dari Emisi Kendaraan Bermotor di Ruas Jalan Kota Pekanbaru

2014 ◽  
Vol 1 (2) ◽  
pp. 71
Author(s):  
Nurhadi Hodijah ◽  
Bintal Amin ◽  
Mubarak Mubarak
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Motor Vehicle ◽  
Ambient Air ◽  
Motor Vehicles ◽  
Vehicle Emission ◽  
Pollutant Load ◽  
Diesel Vehicles ◽  
Motor Vehicle Emissions ◽  
Pm 10

Increasing population and economy in Pekanbaru City was clearly followed by anincrease in the number of motor vehicles has the potential to cause air pollution andendanger human health. This research was aimed to analyze the pollutant load gases of CO,HC, NO 2 , SO 2 and PM 10 emissions from motor vehicles at at Pekanbaru City. Survey on thevolume of motor vehicles, roadside air quality and vehicle emission test was conducted onthree different road in Pekanbaru city. The volume of motor vehicles and pollutants loadsfrom motor vehicle emissions was highest at Sudirman road and the lowest at Diponegororoad. There are very significant differences between Sudirman road with Diponegoro roadand Tuanku Tambusai road with Diponegoro road. Higher pollutant load was found for gasCO (76,4 %), than gas HC (19,4 %), gas NO 2 (3,6 %), gas SO 2 (0,1 % ) and PM 10 ( 0,7 % ).The largest contribution of pollutant load gas CO, HC and PM 10 comes from motorcycles, gasNO 2 from the city cars and gas SO 2 coming from the truck. The quality of roadside air in thethird road to the gases CO, NO 2 , SO 2 and PM 10 are still below the ambient air qualitystandards, whilest gas HC had passed the ambient air quality standard. A positive correlationbetween concentrations of roadside air pollutants with a load of motor vehicle emissions wasfound. The percentage of motor vehicle emission test results explain that the rates of vehiclesfueled with gasoline were higher than diesel vehicles and that do not pass of the emission testwere generally produced before 2007, while for diesel vehicles that do not pass the emissionstest opacity value that were produced in the 2010 onward. 

scholarly journals Trends in on-road vehicle emissions and ambient air quality in Atlanta, Georgia, USA, from the late 1990s through 2009

2014 ◽  
Vol 64 (7) ◽  
pp. 808-816 ◽  
Author(s):  
Krish Vijayaraghavan ◽  
Allison DenBleyker ◽  
Lan Ma ◽  
Chris Lindhjem ◽  
Greg Yarwood
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Road Vehicle

scholarly journals Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 788
Author(s):  
Rong Feng ◽  
Hongmei Xu ◽  
Zexuan Wang ◽  
Yunxuan Gu ◽  
Zhe Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Rural Areas ◽  
Vehicle Emissions ◽  
Motor Vehicle ◽  
Northwest China ◽  
Air Pollutant ◽  
Capital City ◽  
Air Pollution Control ◽  
Motor Vehicle Emissions

In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.

On the spread of ultrafine particulate matter: A mathematical model for motor vehicle emissions and their effects as an asthma trigger

2021 ◽  
Author(s):  
Michelle N. Rosado-Pérez ◽  
Karen Ríos-Soto
Keyword(s):  
Mathematical Model ◽  
Ultrafine Particles ◽  
Motor Vehicle ◽  
Traveling Wave Solutions ◽  
Reaction Diffusion ◽  
Ambient Air ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Motor Vehicles ◽  
Diffusion Type

Asthma is a respiratory disease that affects the lungs, with a prevalence of 339.4 million people worldwide [G. Marks, N. Pearce, D. Strachan, I. Asher and P. Ellwood, The Global Asthma Report 2018, globalasthmareport.org (2018)]. Many factors contribute to the high prevalence of asthma, but with the rise of the industrial age, air pollutants have become one of the main Ultrafine particles (UFPs), which are a type of air pollutant that can affect asthmatics the most. These UFPs originate primarily from the combustion of motor vehicles [P. Solomon, Ultrafine particles in ambient air. EM: Air and Waste Management Association’s Magazine for Environmental Managers (2012)] and although in certain places some regulations to control their emission have been implemented they might not be enough. In this work, a mathematical model of reaction–diffusion type is constructed to study how UFPs grow and disperse in the environment and in turn how they affect an asthmatic population. Part of our focus is on the existence of traveling wave solutions and their minimum asymptotic speed of pollutant propagation [Formula: see text]. Through the analysis of the model it was possible to identify the necessary threshold conditions to control the pollutant emissions and consequently reduce the asthma episodes in the population. Analytical and numerical results from this work prove how harmful the UFEs are for the asthmatic population and how they can exacerbate their asthma episodes.

Air Quality Profile in an Enclosed Car Park

2014 ◽  
Vol 567 ◽  
pp. 3-7 ◽  
Author(s):  
Nurul Izma Mohammed ◽  
Nurfadhilah Othman ◽  
Khairul Bariyah Baharuddin
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Health Effects ◽  
Sulphur Dioxide ◽  
Motor Vehicle ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Kuala Lumpur ◽  
Short Supply ◽  
Car Park

Complaints on poor air quality in an enclosed car park have been raised up among the public, which might cause serious health effects to the drivers, passengers, and labours who are working at the premises. Improper design of mechanical ventilation systems in a car park would result in a poor indoor environment. The exhaust emission of motor vehicle contains a variety of potentially harmful substances encompassing carbon monoxide, nitrogen oxides, sulphur dioxide, hydrocarbons, and fine particulates. In Kuala Lumpur, there is a great demand but a short supply of lands and building spaces. Thus, a large multi-storey underground car parks is a common solution for both, the government and developers. Although the health effects of the motor vehicle emissions and ambient air pollution are already known, but due to the nature of enclosed multi-storey car parks, these health risks are predicted to be intensified. Thus, it is crucial to investigate and evaluate the status of the air pollution in the enclosed car parks with emphasis on sulphur dioxide (SO2) and nitrogen dioxides (NO2). Samples were collected in one of the famous shopping malls in Kuala Lumpur using a GrayWolf Advanced Sense Direct Sense; Toxic Gas Test Meters from 8 am until 5 pm on weekdays and weekends. The results demonstrate that the concentrations of SO2 and NO2 on weekends is higher than weekdays. Besides, the concentrations for both weekdays and weekends have exceeded the standard limit set by the Malaysian Ambient Air Quality Guideline (MAAQG).

scholarly journals A review on Assessment of Air Pollution due to Vehicular Emission in Traffic Area

2018 ◽  
Vol 8 (02) ◽  
Author(s):  
Aneri A. Desai
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Ambient Air ◽  
Pollution Monitoring ◽  
Motor Vehicles ◽  
Monitoring And Control ◽  
Ambient Air Quality ◽  
Vehicular Emission ◽  
Rapid Urbanization ◽  
Air Pollution Monitoring

In Indian metropolitan cities, the extensive growth of the motor vehicles has resulted in the deterioration of environmental quality and human health. The concentrations of pollutants at major traffic areas are exceeding the permissible limits. Public are facing severe respiratory diseases and other deadly cardio-vascular diseases In India. Immediate needs for vehicular air pollution monitoring and control strategies for urban cities are necessary. Vehicular emission is the main source of deteriorating the ambient air quality of major Indian cities due to rapid urbanization. Total vehicular population is increased to 15 Lacks as per recorded data of Regional Transport Organization (RTO) till 2014-2015. This study is focused on the assessment of major air pollution parameters responsible for the air pollution due to vehicular emission. The major air pollutants responsible for air pollution due to vehicular emissions are PM10, PM2.5, Sox, Nox, HC, CO2 and CO and Other meterological parameters like Ambient temperature, Humidity, Wind direction and Wind Speed. Sampling and analysis of parameters is carried out according to National Ambient Air Quality Standards Guidelines (NAAQS) (2009) and IS 5128.

scholarly journals Near-road vehicle emissions air quality monitoring for exposure modeling

2020 ◽  
Vol 224 ◽  
pp. 117318 ◽  
Author(s):  
Jennifer L. Moutinho ◽  
Donghai Liang ◽  
Rachel Golan ◽  
Stefanie E. Sarnat ◽  
Rodney Weber ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Road Vehicle ◽  
Exposure Modeling

scholarly journals Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): emissions of particulate matter and sulfur dioxide from vehicles and brick kilns and their impacts on air quality in the Kathmandu Valley, Nepal

2019 ◽  
Vol 19 (12) ◽  
pp. 8209-8228 ◽  
Author(s):  
Min Zhong ◽  
Eri Saikawa ◽  
Alexander Avramov ◽  
Chen Chen ◽  
Boya Sun ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Air Pollutant ◽  
Kathmandu Valley ◽  
So2 Emissions ◽  
Emissions Inventory ◽  
Brick Kilns ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations ◽  
Local Emissions

Abstract. Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emissions (IVE) model with local emissions factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emissions factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. HTAP_v2.2 does not include the brick sector and we found that our sulfur dioxide (SO2) emissions estimates from brick kilns are comparable to 70 % of the total SO2 emissions considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emissions scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model's boundary-layer representation, to capture strong spatial gradients of air pollutant concentrations.

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