Freight Emission Scaling Calculator

Concept

The calculator supports the infrastructure-planning decision — which road segments to electrify with overhead catenary (OC) lines, and at what budget — rather than merely tallying savings on routes that already have catenary. Its core is a bi-level multi-objective network electrification design (BM-NED) model: the upper level selects segment investments under budget constraints and public-private cost-sharing arrangements, while the lower level models how hybrid OC trucks reroute and adopt in response, so investment options are evaluated against realistic fleet behavior rather than fixed demand assumptions.

Net, not just tailpipe, emission accounting. New evidence [1] provides two complementary methods for estimating hourly marginal CO2 emission factors in electricity systems: a fundamental energy systems model that emulates electricity market dynamics on both the supply and demand sides (highly accurate but computationally intensive at high temporal resolution), and a Markov Switching Dynamic Regression (MSDR) statistical model that estimates marginal factors much faster, benchmarked against the dynamic linear regression approach widely used in the literature. The tool uses the fast statistical estimator for broad scenario screening across candidate corridors and time horizons, and the fundamental model to validate investment-grade numbers for shortlisted segments. This converts what was previously a stated caveat — "accuracy depends on integration of real-time grid carbon intensity" — into a computed input: eHighway driving in hours when the marginal generator is dirty yields larger net savings than average-intensity figures suggest, while clean hours shrink them, and the tool can flag both.

Why now

• Even minimal electrification (5% of a trip) can yield 14–17% direct emission reductions [0], so corridor selection has outsized leverage per euro invested.
• Germany's KSG (2019) mandates net-zero by 2045, and the marginal-factor methodologies in [1] are benchmarked specifically for the German electricity market — the same market hosting the eHighway pilots — making hourly net-emission scoring implementable now rather than hypothetical.

Constraints and honest limits

• Accuracy vs. speed trade-off. The energy systems model in [1] is computationally intensive at high temporal resolution; the MSDR estimator is faster but remains a statistical approximation. The tool therefore presents net savings as ranges with uncertainty bounds, not point estimates, and states which estimator produced each figure.
• Strategic, not real-time. Fast marginal-factor estimation does not make the bi-level network design suitable for dispatch. The tool is a planning instrument for annual or quarterly corridor-portfolio decisions; real-time route optimization remains out of scope.
• Market specificity. The benchmarked estimators are calibrated to the German electricity market; applying the tool elsewhere requires re-estimation and re-validation of marginal factors, which the tool surfaces as a per-region data-readiness check.
• Still-open questions. How overhead catenary economics compare with rapidly cheapening Megawatt Charging Systems; the legal structure of public-private cost-sharing for infrastructure benefiting specific private fleets; and whether operators accept the operational rigidity of fixed catenary lines. No new evidence addresses these, so the tool treats them as sensitivity inputs (e.g., MCS cost trajectories) rather than assumptions.