DTCI completes Clean Truck Fund Rate Study for Ports of Los Angeles and Long Beach
The Port of Los Angeles’ and Port of Long Beach’s (Ports or POLA/POLB) 2017 Clean Air Action Plan Update (2017 CAAP Update) committed to a strategy to update the Clean Truck Programs at both ports to build upon the existing, successful programs. The objective of the Ports’ updated Clean Truck Programs, as stated in the 2017 CAAP Update, is to transition the current drayage truck fleet to near-zero technologies in the near-term and ultimately zero-emissions technologies by 2035. A key component of the updated Clean Truck Programs is the implementation of a Clean Truck Fund (CTF) Rate. As proposed in the 2017 CAAP Update, beginning in 2020, a rate will be charged to the beneficial cargo owners for loaded heavy duty container trucks to enter or exit the ports’ terminals, with rebates for trucks that have CARB-certified low NOx engines or better. The added cost of this CTF Rate is expected to help incentivize the transition of drayage trucks operating at the Ports to cleaner equipment.
DTCI was engaged by the Ports to assesses how a range of potential rates, from $5/TEU to $70/TEU, could: (i) affect the Ports’ economic competitiveness, including the potential for cargo diversion, (ii) impact the drayage industry, and (iii) generate revenue from collection of the rate. The Ports are soliciting comments on the Draft Economic Clean Truck Fund Rate Study and anticipate a vote by the Boards of Harbor Commissioners from each port on establishing a Clean Truck Rate. It is anticipated to be instituted later in 2020 and would apply to cargo owners that hire trucks to transport loaded containers, with rebates if they use trucks that meet low-nitrogen oxide (NOx) or zero-emissions standards.
The Draft Economic Study for the Clean Truck Fund Rate can be downloaded from the Clean Air Action Plan website at cleanairactionplan.org The full DTCI study is included as a Technical Appendix.
DTCI completes study on Modelling Port Elasticity for Transport Canada
DTCI was engaged by Transport Canada Economic Analysis to provide advice on methodology for estiamting the elasticity of marine cargo traffic through Canada’s major ports. In economics, elasticity is the measurement of how an economic variable responds to a change in another. In the context of port traffic, elasticity is a measure of the extent to which a change in variables such as transportation costs or transit time for cargo shipped through the port gateway affects the volume of traffic. The typical objectives of research on port traffic elasticity include:
- Evaluation of the impact of changes in transportation costs due to the imposition of fees (for example environmental or infrastructure fees) or port charges on the volume of port traffic; or
- Evaluation of the extent to which investments in transportation infrastructure, etc. can increase port traffic as a result of reductions in transportation costs or improvements in transit time or reliability for shipments transiting the gateway.
The main model categories include:
- Disaggregate or Aggregate Models: Disaggregate models focus on the elasticity of different segments of port traffic; aggregate models focus on total port traffic.
- Discrete Choice, Continuous or Qualitative Models: Discrete choice models focus on modelling the choice of firms between mutually exclusive alternatives (i.e. for example shipping via the Ports of Los Angeles and Long Beach or shipping via the Port of new York/New Jersey) i.e. “which one”. Continuous models focus on the choice of quantity shipped through a port i.e. “how much”. Qualitative models rely on the judgement of the study’s author(s).
- Deterministic or Stochastic Models: In deterministic models the results are completely determined by the specifications and inputs to the model. Stochastic models use statistical methods which can also account for the influence of unobserved factors through an error term.
- Cross-sectional or Time Series Models: Cross-sectional models are used to assess the relationship between variables associated with one period or point in time. In time series models the variables are considered to be associated with a sequence of points in time.
This study evaluates examples of the various model types and assesses the advantages and disadvantages of each, focusing on data requirements, accuracy and reproducibility of results.
The results of the study were presented at the Metrans International Urban Freight conference on October 17, 2019. A copy of the full report is available on request.