Review of Regional Locomotive Emission Modeling and the Constraints Posed by Activity Data

Document Type

Journal Article

Publication Date


Subject Area

operations - traffic, policy - environment, mode - rail


Railroad transportation, Rail transportation, Pollutants, Mobile sources, Locomotive operations, Greenhouse gases, Goods movement, Freight transportation, Freight traffic, Environmental justice, Emissions modeling, Emissions, Diesel motor exhaust gas, Diesel exhaust emissions, Diesel engine exhaust gases, Diesel electric locomotives, Air pollution, Air pollutants


Diesel–electric locomotives used by U.S. freight railroads are relatively low emitters of criteria air pollutants and greenhouse gases when compared with competing modes. However, the continuous growth in goods movement is cause for concern because locomotive emissions may grow. Railroads account for only a small fraction of all mobile source emissions, but the concentration of emissions along rail facilities raises questions about equity, in particular, environmental justice, and the relative benefits of competing modes of goods movement. This paper provides a synthesis and review of current data and methods used to account for regional locomotive activity. Understanding data limitations and methodological issues at the regional scale provides a starting point for development of more spatially detailed locomotive emission models. Methods developed by the U.S. Environmental Protection Agency and the California Air Resources Board are considered. It is found that each method produces different results and is inadequate for use at the regional (or smaller) spatial scale. Problems arise from activity measures that ignore differences in geography and freight rail services between regions or that depend on detailed operational data that are no longer available. Although detailed activity data do exist, they are not always available because they are owned by private railroads. New methods should minimize the use of detailed or confidential railroad data yet still be sensitive to local factors. Fuel-based methods provide the most hope, but greater cooperation between regulatory agencies and railroads is required.