Freight Movement & Air Quality

End Notes

Federal Highway Administration, Highway Statistics, various years.
American Association of Railroads, Railroad Facts, 2004
American Association of State Highway and Transportation Officials (AASHTO), Freight-Rail Bottom Line Report, undated.
U.S. Army Corps of Engineers, Waterborne Commerce of the United States.
According to the Port of Los Angeles, total TEUs handled (loaded and empty) increased 92 percent between 1999 and 2004.
U.S. Department of Transportation Maritime Administration, Intermodal Access to U. S. Ports; Report on Survey Findings, August 2002.
Bureau of Transportation Statistics, National Transportation Statistics 2004.
Bureau of Transportation Statistics, Airline On-Time Statistics and Delay Causes.
Between 1982 and 2002, truck energy use per vehicle mile declined 3.6 percent, freight railroad energy use per ton-mile declined 37.6 percent, and domestic waterborne commerce energy use per ton-mile increased 51.9 percent. Source: U.S. Department of Energy, Oak Ridge National Laboratory, Transportation Energy Data Book, 24^th Edition. Truck freight energy intensity improvements are likely to be greater because of improvements in utilization (ton-miles per vehicle mile). No data available for foreign waterborne commerce or air freight, although gains in aviation fuel efficiency and utilization are widely recognized.
U.S. EPA, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Highway Heavy-Duty Engines, EPA420-R-00-010, July 2000. ; U.S. EPA, Locomotive Emissions Standards, Regulatory Support Document, April 1998.; U.S. EPA, Final Regulatory Impact Analysis: Control of Emissions from Marine Diesel Engines, EPA420-R-99-026, November 1999; Federal Aviation Administration, Aviation & Emissions, A Primer, 2005.
U.S. EPA, National Emission Inventory.
According to EPA’s National Emission Inventory, light duty vehicle NOx emissions declined 55 percent between 1982 and 2002. Emissions from electric utility fuel combustion declined 31 percent over this period.
U.S. EPA, National Emission Inventory.
Bureau of Transportation Statistics, National Transportation Statistics 2004.
Class I railroads are defined as line haul freight railroads with operating revenue greater than $277.7 million.
U.S. EPA, Locomotive Emissions Standards, Regulatory Support Document, April 1998.
We assume an average weight per passenger of 240 lbs, based on a FAA sponsored weight survey (March 21, 2003) of more than 6,000 passengers. The weight includes an average adult passenger weight of 196 lbs, 16 lbs of carry-on items, and 29 lbs of checked baggage.
Bureau of Transportation Statistics, The Changing Face of Transportation, BTS00-007, Washington, DC, 2000.
Forecasts for rail ton-miles are based on 1990 through 1998 BTS data, using damped trend exponential smoothing. Forecasts for truck ton-miles are based on two forecast models: linear trend based on 1990 through 1997 data and double (Brown) exponential smoothing based on 1960 through 1995 data in five year increments; the two forecasts are combined with equal weights. Forecasts for air ton-miles are based on two forecasting methodologies: linear trend based on 1990 through 1998 data and damped trend exponential smoothing based on 1960 through 1995 data in five year increments; the two forecasts are combined with equal weights.
American Association of State Highway and Transportation Officials, Freight-Rail Bottom Line Report, undated.
American Trucking Associations, Freight Transportation Forecasts to 2014, 2004.
ICF Consulting, 2010 and Beyond: A Vision of America’s Transportation Future, 21st Century Freight Mobility, NCHRP Project 20-24(33) A, Final Report, August 2004.
For references to this literature, see Natural Resources Defense Council, Harboring Pollution: Strategies to Clean Up U.S. Ports, August 2004.
Federal Aviation Administration, Aviation & Emissions, A Primer, 2005.
In addition to emission standards, reduction in PM-10 emissions in this figure reflects the effects of non-road ULSD by locomotives and Category 1 and 2 commercial marine engines. PM-10 emissions are estimated to be 12.1% lower in 2010 and 15.3% lower in 2020, based on U.S. EPA, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Nonroad Diesel Engines and Fuel, EPA420-R-04-007, May 2004. Category 1 and 2 commercial marine emissions estimated to be 40% of total commercial marine emissions, based on EPA regulatory support documents.
U.S. EPA, Locomotive Emissions Standards, Regulatory Support Document, April 1998.
U.S. EPA, Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control Requirements, EPA420-R-00-026, December 2000.
U.S. EPA, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Highway Heavy-Duty Engines, EPA420-R-00-010, July 2000.
U.S. EPA, Locomotive Emissions Standards, Regulatory Support Document, April 1998.
U.S. EPA, Final Regulatory Impact Analysis: Control of Emissions from Marine Diesel Engines, EPA420-R-99-026, November 1999.
U.S. EPA, Final Regulatory Support Document: Control of Emissions from New Marine Compression-Ignition Engines at or Above 30 Liters per Cylinder, EPA420-R-03-004, January 2003.
U.S. EPA, Regulatory Impact Analysis: Control of Emissions of Air Pollution from Nonroad Diesel Engines and Fuel, EPA420-R-04-007, May 2004.
In addition to emission standards, these figures reflect the PM-10 reductions achieved by the use of ULSD in locomotives and most Category 1 and 2 marine engines in 2010 and 2020.
The vast majority of GHG emissions from transportation sources are CO2. Transportation sources also emit small amounts of other GHG emissions, such as methane (CH4) and nitrous oxide (N2O). Emissions of non-CO2 GHGs are weighted by their respective global warming potential to determine total GHG emissions in terms of CO2 equivalents.
For a detailed description of the emission estimation methodology, see Task 4 Technical Memorandum prepared for FHWA by ICF Consulting dated October 15, 2004.
For a detailed description of the emission estimation methodology, see Task 4 Technical Memorandum prepared for FHWA by ICF Consulting dated October 15, 2004.
Texas Natural Resources Conservation Commission (now the Texas Commission on Environmental Quality), “Locomotive Emission Inventory: Update and Discussion,” Memo from Sam Wells, Starcrest Consulting Group and Rick Baker, ERG, Inc., August 30, 2002.
U.S. EPA, “Procedures for Emission Inventory Preparation. Volume VI Mobile Sources,” 1992.
U.S. EPA, Locomotive Emission Standards, Regulatory Support Document, April 1998.
ARCADIS Geraghty & Miller (1999a), Commercial Marine Activity for Deep Sea Ports in the United States, Prepared for U.S. EPA, 1999.
ARCADIS Geraghty & Miller (1999b), Commercial Marine Activity for Great Lake and Inland River Ports in the United States, Prepared for U.S. EPA, 1999.
Environ International Corporation, Commercial Marine Emission Inventory Development, Prepared for U.S. EPA, 2002.
Starcrest Consulting Group, Port-Wide Baseline Air Emissions Inventory, Prepared for the Port of Los Angeles, 2004.
Starcrest Consulting Group, 2001 Cargo Handling Equipment Emissions Inventory: Methodology Comparison, Prepared for the Port of Houston Authority, 2004.
Starcrest Consulting Group, Port-Wide Baseline Air Emissions Inventory, Prepared for the Port of Los Angeles, 2004.
Starcrest Consulting Group, 2002 Baseline Emissions Inventory: Cargo Handling Equipment, Rail Locomotives, and Heavy-Duty Vehicles, Prepared for the Port of Long Beach, 2004.
For a detailed description of the emission estimation methodology, see Task 4 Technical Memorandum prepared for FHWA by ICF Consulting dated October 15, 2004.
For a detailed description of the emission estimation methodology, see Task 4 Technical Memorandum prepared for FHWA by ICF Consulting dated October 15, 2004.
An average weight per passenger of 240 lbs was used based on a FAA sponsored weight survey (March 21, 2003) of more than 6,000 passengers. The weight includes an average adult passenger weight of 196 lbs, 16 lbs of carry-on items, and 29 lbs of checked baggage.
The EDMS model does not currently estimate PM emissions for aircraft and therefore most airports and air agencies do not report aircraft PM emissions. In order to facilitate comparison across modes, we developed a rough estimate of aircraft PM emissions using the ratio of PM to SOx emissions from a California Air Resources Board research study. This study, called the Southern California Ozone Study (SCOS97), estimated PM emissions from jet aircraft at Southern California airports using fuel use data obtained from airports; emissions of other pollutants were estimated using EDMS. Using the results of this study, we calculated the average PM and SOx emissions for all study days and airports, and used these averages to estimate a ratio of 0.311 tons of aircraft PM emissions per ton of aircraft SOx emissions. We applied this ratio to the SOx emissions reported for each of the study airports to estimate PM emissions.
Stodolsky, Frank, Linda Gaines and Anant Vyas, Analysis of Technology Options to Reduce the Fuel Consumption of Idling Trucks, Center for Transportation Research, Argonne National Laboratory, US DOE, June 2000.
Lutsey, Nicholas, Christie-Joy Broderick, Daniel Sperling, Carollyn Oglesby, “Heavy-Duty Truck Idling Characteristics – Results from a Nationwide Truck Survey,” paper submitted for the 2004 Annual Meeting of the Transportation Research Board, 2004.
Taylor, Dr. John C. et al. “The U.S.-Canada Border: Cost Impacts, Causes, and Short to Long Term Management Options.” May, 2003, p.14. Available at http://www.fhwa.dot.gov/uscanada/studies/taylor/costrpt_2003.pdf.
Tennessee Department of Transportation, “Speed Limits Reduced in Shelby County to Improve Air Quality,” Press Release, ,March 14, 2005. Available at http://www.tdot.state.tn.us/news/2005/031405.htm
U.S. EPA, Locomotive Emission Standards, Regulatory Support Document, April 1998.
English Gordon, Charles Schwier, and Richard Lake, Survey of Railway Industry Technological and Operational Improvements and Socio-Economic Issues Affecting GHG Emission Performance, Prepared for the Trucking Sub-Group of National Climate Change Transportation Table, Canada, June 1999.
Stephens, Bill. “BNSF lowers intermodal train speeds as part of fuel consumption experiment,” Trains Newswire (online), 1/25/2001.
Jack Homer, et al., “Evaluating strategies to improve railroad performance—A system dynamics approach”, Proceedings of the 1999 Winter Simulation Conference, P. A. Farrington, H. B. Nembhard, D. T. Sturrock, and G. W. Evans, eds., IEEE.
TRB Committee for the Study of Freight Capacity for the Next Century, Freight Capacity for the 21^st Century, Special Report 271, Transportation Research Board, 2003.
“Union Pacific turning away some freight traffic; giant fights congestion at ‘key terminals,’ mainly in West and Southwest,” Trains, October 2004.
In addition to the longer Union Pacific example given, see, for just two examples: “Rail congestion diverts coal to trucks,” Toledo Blade, August 10, 2004; Suzanne Marta, “Rail shippers struggle with congestion woes”, Dallas Morning News, August 27, 2004.
TRB Committee for the Study of Freight Capacity for the Next Century, Freight Capacity for the 21^st Century, Special Report 271, Transportation Research Board, 2003.
As long as they are not idling, locomotive emissions are largely independent of train speed; as diesel-electrics, the speed of the diesel engine is independent of the speed of the electric motors that actually power the wheels. The operating mode, efficiency, and emissions of the diesel engine itself (called the “prime mover”) are largely determined by the load on the locomotive, and not its speed.
Starcrest Consulting Group, Houston-Galveston Area Vessel Emissions Inventory, Prepared for the Port of Houston Authority, 2000.
Starcrest Consulting Group, Port-Wide Baseline Air Emissions Inventory, Prepared for the Port of Los Angeles, 2004.
Argus Air Daily, Vol. 11, 187, September 30, 2004.
Federal Aviation Administration, Aviation & Emissions, A Primer, 2005.
Sierra Research, Inc., Technical Support for Development of Airport Ground Support Equipment Emission Reductions, May 1999, Prepared for the U.S. EPA, Office of Mobile Sources. EPA420-R-99-007.
United States General Accounting Office. 2003. Aviation and the Environment: Strategic Framework Needed to Address Challenges Posed by Aircraft Emissions, February. Report to the Chairman, Subcommittee on Aviation, Committee on Transportation and Infrastructure, House of Representatives. GAO-03-252.
Partner News, Partnership for AiR Transportation Noise and Emissions Reduction, The Center of Excellence for Aircraft Noise and Aviation Emissions Mitigation, Volume 1, Issue 1, January-June 2004.
Imperial County is also officially part of the SCAG region but was excluded from this analysis because it is distant and distinct from the greater Los Angeles metropolitan area.
U.S. Census Bureau, County Business Patterns.
U.S. Bureau of Economic Analysis, Regional Economic Accounts (county-level data)
U.S. Census Bureau, County Business Patterns.
Commodity flow data summary tables for each region developed from: FHWA Freight Analysis Framework (trucking and rail); Bureau of Transportation Statistics, Air Carrier Statistics T-100 database (air); U.S. Army Corps of Engineers, Waterborne Commerce of the United States database (marine) (2003 marine freight estimated using 2001Corps data, the domestic marine freight annual growth rate from the FAF specific to the region, and the total U.S. international marine freight historic growth rate from Corps data.)
Federal Highway Administration, Highway Statistics 2002. Calculated as the sum of the Los Angeles-Long Beach-Santa Ana, Riverside-San Bernardino, and Oxnard federal aid urbanized areas.
Southern California Association of Governments, Goods Movement Program White Paper, January 2002.
Southern California Association of Governments, Goods Movement Program White Paper, January 2002.
Southern California Association of Governments, Goods Movement Program White Paper, January 2002.
Data from the American Association of Port Authorities.
Data from the American Association of Port Authorities.
Federal Aviation Administration, CY 2003 Passenger Boarding and All-Cargo Data.
For the analyses of commodity flow data, entire counties must be used. For that reason, all of Ellis and Johnson counties were included in the analyses and Parker and Kaufman counties were excluded.
U.S. Census Bureau (data for all 9 counties that lie wholly or partially in the region).
U.S. Bureau of Economic Analysis, Regional Economic Accounts (data for all 9 counties that lie wholly or partially in the region).
County Business Patterns, U.S. Census Bureau (data for the Dallas and Fort Worth-Arlington MSAs).
Federal Highway Administration, Highway Statistics 2002. Calculated as the sum of the Dallas-Fort Worth-Arlington and Denton-Lewisville federal aid urbanized areas.
Union Pacific Railroad website, http://www.uprr.com/aboutup/usguide/usa-tx.shtml.
North Central Texas Council of Governments, Mobility 2025 Update: The Metropolitan Transportation Plan.
U.S. Census Bureau
U.S. Bureau of Economic Analysis, Regional Economic Accounts (county-level data).
U.S. Census Bureau, County Business Patterns.
Federal Highway Administration, Highway Statistics 2002. Calculated as the sum of the Houston, Texas City, Beaumont, and Port Arthur federal aid urbanized areas.
Houston Galveston Area Council, Draft 2025 Regional Transportation Plan, Freight Appendix.
Union Pacific web site, http://www.uprr.com/aboutup/usguide/usa-tx.shtml.
Houston Galveston Area Council, Draft 2025 Regional Transportation Plan, Freight Appendix.
American Association of Port Authorities.
U.S. Census Bureau (data for entire 7 counties).
U.S. Bureau of Economic Analysis, Regional Economic Accounts.
County Business Patterns, U.S. Census Bureau (data for Chicago MSA).
Federal Highway Administration, Highway Statistics 2002. Calculated for the Chicago federal aid urbanized area.
Illinois Department of Transportation, “Chicago Region Environmental and Transportation Efficiency Project (CREATE)”, slide presentation, available at http://www.aar.org/Create/Create_main.asp.
American Association of Port Authorities.
U.S. Army Corps of Engineers, Waterborne Commerce of the United States database.
Bureau of Transportation Statistics, Air Carrier Statistics T-100 database.
City of Chicago, Department of Aviation, Chicago Airport System 2002 Annual Report.
Bureau of Transportation Statistics, Air Carrier Statistics T-100 database.
U.S. Census Bureau
U.S. Bureau of Economic Analysis, Regional Economic Accounts.
U.S. Census, County Business Patterns.
Federal Highway Administration, Highway Statistics 2002. Calculated for the Detroit federal aid urbanized area.
Information provided by the Southeast Michigan Council of Governments.
Bureau of Transportation Statistics, Transborder Surface Freight Dataset.
Southeast Michigan Council of Governments, 2025 Regional Transportation Plan.
U.S. Army Corps of Engineers, Waterborne Commerce of the United States database.
U.S. Census Bureau.
U.S. Bureau of Economic Analysis, Regional Economic Accounts (county level data).
U.S. Census Bureau, County Business Patterns.
Baltimore Metropolitan Council, “Changing Freight Transportation Requirements for the Baltimore Metro Region,” Prepared by the Louis Berger Group, 2001.
Federal Highway Administration, Highway Statistics 2002. Calculated for the Baltimore federal aid urbanized area.
Baltimore Metropolitan Council, 2001 Baltimore Regional Transportation Plan, October 2001.
Baltimore Metropolitan Council, 2001 Baltimore Regional Transportation Plan, October 2001.
American Association of Port Authorities.
U.S. Army Corps of Engineers, Waterborne Commerce of the United States database.
Maryland Aviation Administration, BWI Airport website, http://www.bwiairport.com/8abtbwi/in_gs.shtml.
Baltimore Metropolitan Council, 2001 Baltimore Regional Transportation Plan, October 2001.