eHighway GHG Savings Calculator

Concept

A specialized carbon-accounting calculator for freight operators. Instead of generic industry averages, it uses the scaling and comparison logic derived from real-world eHighway field tests to predict GHG savings from the percentage of a trip spent under overhead contact lines [0]. Fleet managers input their route and the length of electrified stretches; the tool returns per-shipment savings estimates with confidence bounds rather than a single 'exact' number.

Methodological upgrade — marginal grid intensity. O-trucks draw grid power at specific hours, so net savings depend on the marginal CO2 intensity of the German grid at those times, not a yearly average. New research provides two complementary ways to estimate hourly marginal emission factors: a fundamental energy-systems model (accurate but computationally intensive) and a faster Markov Switching Dynamic Regression, both demonstrated for the German electricity market [2]. The tool embeds the fast statistical method for day-to-day route calculations and reserves the fundamental model for audited reporting runs — making the numbers defensible to regulators and corporate clients.

Why partial-route accounting is the right granularity. Network-design research on eHighway adoption shows corridor electrification will be rolled out selectively under tight budget constraints, and that adoption hinges on public-private collaboration [1]. Two implications for this tool: (a) real routes will only ever be partially electrified, so savings must be computed from the electrified share of each trip — precisely the tool's core logic; (b) logistics companies need credible, quantified per-fleet savings to justify committing O-trucks to electrified arcs. The tool's outputs can inform such network-level conversations, but the tool itself remains a per-route accounting calculator, not a corridor-selection planner.

Why now

Field tests show that even 5% trip electrification yields 14–17% emission reductions [0]. Germany's net-zero mandate for 2045 creates compliance demand for precise, evidence-based quantification [0]. Marginal-emission-factor estimation methods are now mature enough for the German market to embed in a commercial tool [2].

Honest limits

• The 5% → 14–17% scaling ratio comes from pilot trucks; whether it holds across load weights and vehicle types is unverified. The tool presents savings as ranges and flags low-confidence configurations.
• Willingness of corporate shippers to pay a premium for low-carbon shipping, and O-truck conversion economics, remain unproven — premium pricing is an upside scenario, not the core value proposition. Near-term buyer value is regulatory and sustainability reporting.
• No confirmed ISO/EU certification pathway for these specific calculations yet; the tool targets auditability (transparent methodology, sourced marginal factors) rather than claiming certification upfront.
• Dead-head (empty return) kilometers are included in the denominator so headline savings percentages are not overstated.