scholarly journals Modeling Ozone in the Eastern U.S. using a Fuel-Based Mobile Source Emissions Inventory

2018 ◽  
Vol 52 (13) ◽  
pp. 7360-7370 ◽  
Author(s):  
Brian C. McDonald ◽  
Stuart A. McKeen ◽  
Yu Yan Cui ◽  
Ravan Ahmadov ◽  
Si-Wan Kim ◽  
...  
Keyword(s):  
Mobile Source ◽  
Emissions Inventory ◽  
Mobile Source Emissions

Mobile-Source Emissions: Analysis of Spatial Variability in Vehicle Activity Patterns and Vehicle Fleet Distributions

2003 ◽  
Vol 1842 (1) ◽  
pp. 91-98 ◽  
Author(s):  
Carrie Malcolm ◽  
Theodore Younglove ◽  
Matthew Barth ◽  
Nicole Davis
Keyword(s):  
Spatial Variability ◽  
Activity Patterns ◽  
Mobile Source ◽  
Data Set ◽  
Emissions Inventory ◽  
Mobile Source Emissions ◽  
Total Vehicle ◽  
Vehicle Fleet ◽  
Vehicle Activity ◽  
South Coast Air Basin

Accurately estimating mobile-source emissions requires a good understanding of vehicle activity and the characteristics of the on-road vehicle fleet. Spatial variability in vehicle activity patterns and vehicle fleet composition can have significant effects on the overall emissions inventory. Simply determining total vehicle miles traveled is insufficient for emissions inventory calculations from the new-generation models of mobile-source emissions. Improvements in emissions-control technology over the past 20 years have led to large decreases in the emissions of light-duty cars and trucks, resulting in large variations in vehicle emissions depending on model year and technology type. In addition, research indicates that the accurate characterization of vehicle activity is necessary in conjunction with better spatial resolution of vehicle fleet characteristics because of the differing modal behavior of the vehicles within various vehicle and technology groups. Vehicle activity and vehicle fleet data were collected in the South Coast Air Basin in southern California. Vehicle activity was characterized primarily using a large second-by-second speed and acceleration data set collected from probe vehicles operated within the flow of traffic. In addition, three sets of vehicle fleet data were collected and used for spatial comparison. The results of the analysis show spatial and temporal differences in vehicle activity patterns and vehicle fleet characteristics; differences in speed and congestion affect the speed–acceleration profiles as well as associated emissions.

scholarly journals Simulation of Air Pollution from Mobile Source Emissions in the City of Rio de Janeiro

1999 ◽  
Vol 10 (3) ◽  
pp. 203-208 ◽  
Author(s):  
I.C.B. Campos ◽  
A.S. Pimentel ◽  
S.M. Corrêa ◽  
G. Arbilla
Keyword(s):  
Air Pollution ◽  
Rio De Janeiro ◽  
Mobile Source ◽  
Mobile Source Emissions ◽  
The City
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