Toxic Air Pollutant Vehicle Exhaust Emissions with Reformulated Gasolines

1991 ◽  
Author(s):  
Robert A. Gorse ◽  
Jack D. Benson ◽  
Vaughn R. Burns ◽  
Albert M. Hochhauser ◽  
William J. Koehl ◽  
...  
Keyword(s):  
Exhaust Emissions ◽  
Air Pollutant ◽  
Vehicle Exhaust

Air Environmental Impact Research of Urban Traffic Development – A Case Study

2010 ◽  
Vol 113-116 ◽  
pp. 854-858
Author(s):  
Qing Song Wang ◽  
Xue Liang Yuan ◽  
Chun Yuan Ma
Keyword(s):  
Motor Vehicle ◽  
Exhaust Emissions ◽  
Air Pollutant ◽  
Urban Traffic ◽  
Motor Vehicles ◽  
Urban Air ◽  
Vehicle Exhaust ◽  
Air Pollutions ◽  
Speed Up ◽  
Pm2.5 And Pm10

With the speed-up of urbanization, the number of motor vehicles has increased rapidly, which is the main urban air pollutant source because of too much emitted exhaust gas. Based on the motor vehicle exhaust emissions in Shandong Province in 2006, using trend extrapolation and scenario analysis, predict the motor vehicle exhaust emissions for future planning. The results show that the motor vehicles in 2015and 2020 are 27.52 million and 34.53 million, which is 1.9times and 2.38 times of the motor vehicles in 2006, respectively. For the specific air pollutants from motor vehicles exhaust in 2020, SO2, NOx, PM2.5 and PM10 will reach 28.4 thousand tons, 356.7 thousand tons, 10.8 thousand tons and 12.2 thousand tons, which will be 3 times, 1.2 times, 5 times and 5 times of the emissions in 2006. The urban air pollutions caused by motor vehicles exhaust will be very serious.

scholarly journals Spatiotemporal distribution of light-absorbing carbon and its relationship to other atmospheric pollutants in Stockholm

2011 ◽  
Vol 11 (22) ◽  
pp. 11553-11567 ◽  
Author(s):  
P. Krecl ◽  
A. C. Targino ◽  
C. Johansson
Keyword(s):  
Exhaust Emissions ◽  
Atmospheric Pollutants ◽  
Spatiotemporal Variability ◽  
Rural Site ◽  
Strong Increase ◽  
Population Exposure ◽  
Emission Sources ◽  
Vehicle Exhaust ◽  
Urban Background ◽  
Urban Sites

Abstract. Carbon-containing particles have deleterious effects on both Earth's climate and human health. In Europe, the main sources of light-absorbing carbon (LAC) emissions are the transport (67%) and residential (25%) sectors. Information on the spatiotemporal variability of LAC particles in urban areas is relevant for air quality management and to better diagnose the population exposure to these particles. This study reports on results of an intensive field campaign conducted at four sites (two kerbside stations, one urban background site and a rural station) in Stockholm, Sweden, during the spring 2006. Light-absorbing carbon mass (MLAC) concentrations were measured with custom-built Particle Soot Absorption Photometers (PSAP). The spatiotemporal variability of MLAC concentrations was explored by examining correlation coefficients (R), coefficients of divergence (COD), and diurnal patterns at all sites. Simultaneous measurements of NOx, PM10, PM2.5, and meteorological variables were also carried out at the same locations to help characterize the LAC emission sources. Hourly mean (± standard deviation) MLAC concentrations ranged from 0.36±0.50 at the rural site to 5.39±3.60 μg m−3 at the street canyon site. Concentrations of LAC between urban sites were poorly correlated even for daily averages (R<0.70), combined with highly heterogeneously distributed concentrations (COD>0.30) even at spatial scales of few kilometers. This high variability is connected to the distribution of emission sources and processes contributing to the LAC fraction at these sites. At urban sites, MLAC tracked NOx levels and traffic density well and mean MLAC/PM2.5 ratios were larger (26–38%) than at the background sites (4–10%). The results suggest that vehicle exhaust emissions are the main responsible for the high MLAC concentrations found at the urban locations whereas long-range transport (LRT) episodes of combustion-derived particles can generate a strong increase of levels at background sites. To decrease pollution levels at kerbside and urban background locations in Stockholm, we recommend abatement strategies that target reductions of vehicle exhaust emissions, which are the main contributors to MLAC and NOx concentrations.

scholarly journals Impact of freeway weaving segment design on light-duty vehicle exhaust emissions

2018 ◽  
Vol 68 (6) ◽  
pp. 564-575 ◽  
Author(s):  
Qing Li ◽  
Fengxiang Qiao ◽  
Lei Yu ◽  
Shuyan Chen ◽  
Tiezhu Li
Keyword(s):  
Exhaust Emissions ◽  
Vehicle Exhaust ◽  
Light Duty ◽  
Light Duty Vehicle

scholarly journals Pollution Characteristics of Atmospheric Carbonyls in Urban Linfen in Winter

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 685
Author(s):  
Fanxiu Li ◽  
Hengyuan Wang ◽  
Xuezhong Wang ◽  
Zhigang Xue ◽  
Liqin Duan ◽  
...  
Keyword(s):  
Urban Area ◽  
Atmospheric Chemistry ◽  
Mass Concentration ◽  
High Performance ◽  
Exhaust Emissions ◽  
Photochemical Reactions ◽  
Vehicle Exhaust ◽  
Pollution Characteristics ◽  
The North ◽  
Mass Concentrations

Atmospheric carbonyls (aldehyde and ketone compounds) can be precursors for ozone and PM2.5, and they play an essential role in atmospheric chemistry. Linfen is a basin between mountains on the east and west, and there are many coking plants on the north and south sides of its urban area. The special topography and unfortunate industrial layout have frequently contributed to serious air pollution in Linfen. In order to investigate the pollution characteristics of atmospheric carbonyls in winter in urban Linfen, the carbonyl compounds were collected from the Municipal Committee site (MC) and the Yaowangtai site (YWT) from 16 to 25 January 2019, and their concentrations were analyzed by a high performance liquid chromatography-ultraviolet detector (HPLC-UV). The results show that formaldehyde, acetaldehyde, and acetone were the most abundant compounds, accounting for more than 70% of the total mass concentration of carbonyls in urban Linfen. Levels of these three carbonyls increased during the morning and evening traffic rush hours. The mass concentration of formaldehyde at both sites reached peak values at around noon (10:00–14:00). In addition, the mass concentrations of formaldehyde, acetaldehyde, and acetone were positively correlated with CO mass concentrations, whereas only formaldehyde and acetaldehyde were positively correlated with temperature. Therefore, atmospheric formaldehyde in urban Linfen’s winter mainly came from vehicle exhaust emissions and the secondary generation of photochemical reactions. Most of the acetaldehyde came from vehicle exhaust emissions, and photochemical reactions also partially contributed to it. For acetone, vehicle exhaust emissions were the main source. In addition, coking industry emissions from Northern Linfen′s Hongtong County may also have contributed to the atmospheric carbonyls in the urban area of Linfen. For the first time, this study found that formaldehyde showed different behavior to acetaldehyde and acetone; that is, the nighttime decrease in formaldehyde mass concentration was greater than that of acetaldehyde and acetone.

scholarly journals Source Profiles for PM10-2.5 Resuspended Dust and Vehicle Exhaust Emissions in Central India

2018 ◽  
Vol 18 (7) ◽  
pp. 1660-1672 ◽  
Author(s):  
Shamsh Pervez ◽  
Shahina Bano ◽  
John G. Watson ◽  
Judith C. Chow ◽  
Jeevan Lal Matawle ◽  
...  
Keyword(s):  
Central India ◽  
Exhaust Emissions ◽  
Vehicle Exhaust ◽  
Source Profiles

scholarly journals Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods

2020 ◽  
Vol 12 (19) ◽  
pp. 8118
Author(s):  
Tu Peng ◽  
Xu Yang ◽  
Zi Xu ◽  
Yu Liang
Keyword(s):  
Sustainable Development ◽  
Environmental Pollution ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Intelligent Transportation ◽  
Exhaust Emissions ◽  
Low Carbon ◽  
Vehicle Exhaust ◽  
The Sustainable Development ◽  
Low Carbon Emission

The sustainable development of mankind is a matter of concern to the whole world. Environmental pollution and haze diffusion have greatly affected the sustainable development of mankind. According to previous research, vehicle exhaust emissions are an important source of environmental pollution and haze diffusion. The sharp increase in the number of cars has also made the supply of energy increasingly tight. In this paper, we have explored the use of intelligent navigation technology based on data analysis to reduce the overall carbon emissions of vehicles on road networks. We have implemented a traffic flow prediction method using a genetic algorithm and particle-swarm-optimization-enhanced support vector regression, constructed a model for predicting vehicle exhaust emissions based on predicted road conditions and vehicle fuel consumption, and built our low-carbon-emission-oriented navigation algorithm based on a spatially optimized dynamic path planning algorithm. The results show that our method could help to significantly reduce the overall carbon emissions of vehicles on the road network, which means that our method could contribute to the construction of low-carbon-emission intelligent transportation systems and smart cities.

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