The data below tracks the total tonnage and value of commodities shipped on the Maritime Transportation System between 2012 to 2018. The Maritime Transportation System includes the Great Lakes, St. Lawrence Seaway, and St. Lawrence River downstream to Les Escoumins, QC. The figures below illustrate how this cargo tonnage and value was broken down by different commodities. Changes in commodity tonnage handled and value of cargo reflect changing global and regional economic forces.
More information on commodity tonnage and value
Bulk cargoes such as iron ore, stone, grain, and coal make up the majority of the tonnage of goods moving on the MTS. However, containers carried on the MTS make up the largest share of value. This difference in the shares of value and tonnage reflect the fact that bulk cargoes have a relatively low-value per ton, while containerized cargos are usually manufactured products that have a greater value per ton. A further discussion of MTS container traffic and trends is here.
While the value metric above presents the market value of cargo moving on the MTS, it is important to remember that the true value of this cargo is greater than its market value. This “hidden” value is due to the fact that many of the commodities moving on the MTS are crucial inputs to manufacturers producing higher-value goods. For example, the iron ore moved on the MTS has a relatively low value based on market price, but this iron ore is the critical component to higher-value US and Canadian steelmaking, and thus secondary manufacturing industries such as automotive, machinery, and appliance producers. Without access to the materials, many of the region’s manufacturers would not be able to operate.
Information about data
The tonnage and value estimates presented here are estimates, and their full accuracy is not guaranteed. There are no publicly-available, comprehensive sources of data on the tonnage or value of cargo carried on the MTS. Estimates of tonnage and value must be created using multiple data sources, which often have differing reporting or collection methodologies, or restrictions on how data may be disclosed.
This estimate of tonnage and value was created using the following sources:
USACE WCSC data was used to identify tonnage handled at US ports on the Great Lakes and St. Lawrence River.
USACE Foreign Cargo data was used to identify tonnage that was (1)handled at ports in Ontario that are not organized as Canada Port Authorities (CPA), and (2) that was moved to or from US Great Lakes ports.
MIS data was used to identify tonnage handled at the four Quebec CPAs that are included in the GLSLS. These five CPAs are Montreal, Trois-Riveres, Quebec City, Saguenay. Sept-Iles is not included because it lies outside of the system boundaries defined for this project. Due to confidentiality restrictions, the tonnages for these 4 ports are combined into one estimate, and information on tonnages at specific ports is unavailable for this project.
4. Ontario CPAs
Data from Ontario CPAs was used to improve the estimate of tonnage handled in Ontario. Data was collected from websites for Thunder Bay and Windsor. Hamilton-Oshawa and Toronto Port Authorities also provided data in a format compatible with the commodity classifications used here. Due to confidentiality issues, port-level tonnage breakdowns are not provided, only provincial-level breakdowns with USACE Foreign Cargo data added.
5. Martin Associates' Economic Impacts of Maritime Shipping in the Great Lakes St. Lawrence Region(2018).
This report contains a state/provincial-level estimate of tonnage handled, and was used to double-check tonnage estimates from USACE WCSC data, as well as improve our understanding of the share of tonnage that was unaccounted for in other data sources listed above. Martin's estimates of each commodity group's value per ton also serve as the foundation for this sheet's value calculations.
StatCan's Shipping in Canada reports were used to understand tonnage trends prior to 2011, and understand the share of tonnage
6. USA Trade Online Data
USA Trade Online data was used to calculate changes in the value per ton of general commodity groups over time.