Composite Exhaust Emissions Rates: Sensitivity to Vehicle Population and Mileage Accrual Assumptions

2003 ◽  
Vol 1842 (1) ◽  
pp. 73-82
Author(s):  
Tom Kear ◽  
Deb Niemeier
Keyword(s):  
Environmental Protection Agency ◽  
Population Data ◽  
Mobile Source ◽  
Vehicle Miles Traveled ◽  
Small Perturbations ◽  
Mobile Source Emissions ◽  
Metropolitan Planning ◽  
Light Duty ◽  
Vehicle Fleet ◽  
Model Year

In the California Air Resources Board’s newest model of mobile-source emissions, EMFAC 2002, vehicle population and mileage accrual data have been revised such that regional vehicle miles traveled (VMT) are calculated from vehicle population and accrual data [rather than directly, using metropolitan planning organization (MPO) estimates]. Calculated VMT is forced to match the MPO VMT estimate by scaling the mileage accrual rates and altering vehicle population data. Vehicle population and mileage accrual data also determine how VMT is allocated across the vehicle model years present in the vehicle fleet; thus, modification of these data also changes the fraction of the VMT associated with each model year in the vehicle fleet. Composite emissions rates were estimated based on various vehicle population and mileage accrual data. Small perturbations in age distributions and accrual data have a larger-than-expected impact on the composite emissions rates for light-duty automobiles. For example, total organic gas emissions varied by nearly a factor of 3 between the lowest and highest estimated emissions rates, and either emissions rate could justifiably be used in an inventory. Recommendations for VMT and accrual data in subsequent release of EMFAC 2002 are provided, giving preference to the methods used by the U.S. Environmental Protection Agency.

scholarly journals High Emitter Light Duty Vehicle Contributions to On-road Mobile Emissions in 2018 and 2030

2015 ◽  
Vol 2 (1) ◽  
pp. 47 ◽  
Author(s):  
Susan Collet ◽  
Toru Kidokoro ◽  
Yukio Kinugasa ◽  
Prakash Karamchandani ◽  
Allison DenBleyker
Keyword(s):  
Air Quality ◽  
Environmental Protection Agency ◽  
Protection Agency ◽  
Vehicle Miles Traveled ◽  
Improvement Strategy ◽  
Quality Improvement Strategy ◽  
Light Duty ◽  
Air Quality Improvement ◽  
Light Duty Vehicle ◽  
Tier 3

Quantifying the proportion of normal- and high-emitting vehicles and their emissions is vital for creating an air quality improvement strategy for emission reduction policies. This paper includes the California LEV III and United States Environmental Protection Agency Tier 3 vehicle regulations in this projection of high emitter quantification for 2018 and 2030. Results show high emitting vehicles account for up to 6% of vehicle population and vehicle miles traveled. Yet, they will contribute to over 75% of exhaust and 66% of evaporative emissions. As these high emitting vehicles are gradually retired from service and are removed from the roads, the overall effect on air quality from vehicle emissions will be reduced.

Geographic Information System Framework for Modeling Mobile-Source Emissions

1996 ◽  
Vol 1551 (1) ◽  
pp. 123-132 ◽  
Author(s):  
William Bachman ◽  
Wayne Sarasua ◽  
Randall Guensler
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Environmental Protection Agency ◽  
Functional Model ◽  
Geographic Information ◽  
Metropolitan Region ◽  
Hard Copy ◽  
Mobile Source ◽  
Mobile Source Emissions ◽  
Operating Modes

Because vehicle activities and the emissions associated with them can be correlated with specific points in time and space, the modeling capabilities of a geographic information system (GIS) are well suited to the modeling of mobile-source emissions. A GIS-based modeling approach can provide emissions estimates for both on-network and off-network vehicle activities on a modal basis (as a function of various vehicle operating modes that significantly affect vehicle emission rates). An entire metropolitan region can be modeled on a zone, link, and point basis. Vehicle subfleet composition can be tracked or estimated and combined with estimates of vehicle activity and characteristic operating modes to provide emissions estimates in a spatial and temporal context. Emissions from various modal activities are aggregated into grid cells to be used as input to an airshed model. Identifying spatial and temporal distributions of these activities adds to a greater understanding of emissions impacts. A research prototype of this modeling concept was produced to illustrate its capabilities and identify difficulties that must be addressed in the development of a fully functional model. The GIS-based displays and hard-copy maps that present the spatial variability of emissions levels help improve the communication of research findings to decision makers and the public. The effort being undertaken at Georgia Institute of Technology in conjunction with the Environmental Protection Agency to develop a next-generation modal emissions model within a GIS framework is described.

On-Road Portable Emission Measurement Systems Test Data Analysis and Light-Duty Vehicle In-Use Emissions Development

2020 ◽  
Vol 9 (2) ◽  
pp. 111-131
Author(s):  
SoDuk Lee ◽  
◽  
Carl R Fulper ◽  
Daniel Cullen ◽  
Joseph McDonald ◽  
...  
Keyword(s):  
Test Data ◽  
Real World ◽  
Environmental Protection Agency ◽  
Emission Measurement ◽  
Mobile Source ◽  
Measurement Systems ◽  
Light Duty ◽  
Light Duty Vehicle ◽  
Inventory Development ◽  
Light Duty Vehicles

Portable emission measurement systems (PEMS) [1] are used by the US Environmental Protection Agency (EPA) to measure gaseous and particulate matter mass emissions from vehicles in normal, in-use, on-the-road, and “real-world” operations to support many of its programs. These programs include vehicle modeling, emissions compliance, regulatory development, emissions inventory development, and investigations of the effects of real, in-use driving conditions on NOx, CO2, and other regulated pollutants. This article discusses EPA’s analytical methodology for evaluating light-duty vehicle energy and EU Real Driving Emissions (RDE). A simple, data-driven model was developed and validated using measured PEMS emissions test data. The work also included application of the EU RDE procedures and comparison to the PEMS test methodologies and FTP and other chassis dynamometer test data used by EPA for characterizing in-use light- and heavy-duty vehicle emissions. This work was conducted as part of EPA’s participation in the development of UNECE Global Technical Regulations and also supports EPA mobile source emission inventory development. This article discusses the real-world emissions of light-duty vehicles with 12V Start-Stop technology and light-duty vehicles using both gasoline and diesel fuels.

Diesel Particulate Emissions: Landmark Research 1994-2001

2002 ◽  
Keyword(s):  
Environmental Protection Agency ◽  
Diesel Emissions ◽  
Particulate Emissions ◽  
Heavy Duty ◽  
Protection Agency ◽  
Mobile Source ◽  
Emissions Reductions ◽  
Diesel Particulate ◽  
The Past ◽  
Light Duty

The need for manufacturers to meet U.S. Environmental Protection Agency (EPA) mobile source diesel emissions standards for on-highway light duty and heavy duty vehicles has been the driving force for the control of diesel particulate and NOx emissions reductions. Diesel Particulate Emissions: Landmark Research 1994-2001 contains the latest research and development findings that will help guide engineers to achieve low particulate emissions from future engines. Based on extensive SAE literature from the past seven years, the 45 papers in this book have been selected from the SAE Transactions Journals.

scholarly journals VMT-Mix Modeling for Mobile Source Emissions Forecasting: Formulation and Empirical Application

2000 ◽  
Vol 1738 (1) ◽  
pp. 39-48 ◽  
Author(s):  
Chandra R. Bhat ◽  
Harikesh S. Nair
Keyword(s):  
Operating Conditions ◽  
Metropolitan Region ◽  
Fort Worth ◽  
Mobile Source ◽  
Vehicle Miles Traveled ◽  
Vehicle Class ◽  
Mobile Source Emissions ◽  
Physical Attributes ◽  
The Empirical Analysis

A fractional split model is proposed and implemented that predicts the vehicle miles traveled (VMT) mix on links as a function of the functional roadway classification of the link, the physical attributes of the link, the operating conditions on the link, and the attributes of the traffic analysis zone in which the link lies. The fractional split model is a useful formulation for VMT-mix analysis because it accommodates boundary values of fractional VMT in a vehicle class, is easy to estimate using commonly available econometric software, and is easy to apply in forecasting mode to predict the VMT mix on each link of a network. The empirical analysis applies the fraction split model structure to estimate a VMT-mix model for the Dallas–Fort Worth metropolitan region in Texas. The results of model evaluation also are presented.

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

Impact of Asset Management in a Green Supply Chain

2021 ◽  
Author(s):  
Sara Hajihashemi ◽  
Reza Alizadeh ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Supply Chain ◽  
Asset Management ◽  
Environmental Protection Agency ◽  
Low Cost ◽  
Operating Cost ◽  
Ghg Emissions ◽  
Population Data ◽  
Green Supply Chain ◽  
Large Area ◽  
Greenhouse Gasses

Abstract With increasing concerns about global warming caused by greenhouse gasses (GHGs), organizations have become more responsible for their operations. According to the U.S. Environmental Protection Agency (EPA), companies with a supply chain (SC) generate about 42% of GHGs in their transportation (30%) and inventory systems (12%), which makes mitigating climate change through a green supply chain (GSC) management a reasonable solution. To design a GSC, we model the SC as a customer and store network, with customers driving in cars to and from stores and the retailer resupplying the stores from a central warehouse. The number and location of stores are determined to find a low-cost and low emission configuration for the SC. The key findings are (1) SCs with more small stores generate less emission than ones with fewer large stores; (2) when minimizing the operating cost is more important than mitigating GHG emissions, fewer large stores are preferred than having more small stores; (3) a SC with two warehouses reduces the number of open stores in a large area such as Puerto Rico. Our contributions are (1) building a model of a GSC based on population data; (2) modeling a GSC in a two-echelon network which can be solved simultaneously using the k-median approach; (3) evaluating the effect of multiple warehouses on the overall GHGs emissions; (4) managing the incompleteness and inaccuracy of the data through implementing the compromise Decision Support Problem construct to identify satisficing solutions. The model mentioned earlier highlights the important parameters that impact the green GHG emissions reduction from a SC that describe in this paper. We also discuss how this approach can be employed for other design problems, including manufacturing and healthcare.

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