The GLEC Framework provides a harmonized approach for calculating a logistics carbon footprint by defining how to combine transport activity data with fuel- and vehicle-specific emission factors. It aligns with the ISO 14083 standard and the Greenhouse Gas Protocol, enabling shippers and carriers to quantify Scope 3 emissions from road, rail, air, sea, and inland waterways using a single, auditable methodology.
Glossary
GLEC Framework

What is the GLEC Framework?
The Global Logistics Emissions Council (GLEC) Framework is the globally recognized, universal methodology for calculating and reporting greenhouse gas emissions across multi-modal logistics supply chains, ensuring consistent and comparable carbon accounting.
By standardizing the calculation of well-to-wheel emissions, the framework allows for the credible comparison of carbon performance across different carriers and transport modes. It serves as the foundational accounting backbone for advanced optimization engines, such as carbon-aware routing and modal shift algorithms, by providing the consistent emission intensity data required for automated decision-making.
Key Features of the GLEC Framework
The Global Logistics Emissions Council (GLEC) Framework provides a universal, transparent methodology for calculating and reporting logistics emissions across multi-modal supply chains. These key features ensure consistent, auditable carbon accounting.
Multi-Modal Coverage
The framework provides a unified calculation approach across all transport modes—air, road, rail, sea, and inland waterways—as well as logistics hubs like warehouses and transshipment terminals. This eliminates the inconsistency of using disparate methodologies for different legs of a single shipment, enabling a true end-to-end carbon footprint from raw material extraction to final delivery. It harmonizes with existing mode-specific standards (e.g., IATA for air, Clean Cargo for sea) under one roof.
Well-to-Wheel (WTW) Accounting
Unlike Tank-to-Wheel (TTW) methods that only measure tailpipe emissions, the GLEC Framework mandates a Well-to-Wheel scope. This accounts for the full lifecycle of the energy source:
- Well-to-Tank (WTT): Emissions from fuel extraction, production, refining, and distribution.
- Tank-to-Wheel (TTW): Emissions from fuel combustion in the vehicle. This prevents carbon leakage by capturing upstream energy impacts, making it essential for accurately comparing fossil fuels with alternative energies like electricity or hydrogen.
Granular Emission Factor Defaults
The framework provides a tiered system of default emission intensity factors (gCO2e/tonne-km) for use when primary data is unavailable. These factors are segmented by:
- Transport mode and vehicle/vessel type
- Fuel type and energy source
- Load factor and empty running percentage
- Geographic region This allows companies to move from basic spend-based estimates to more accurate activity-based calculations as their data maturity improves, following the GLEC Maturity Curve.
Alignment with Global Standards
The GLEC Framework is the logistics sector's implementation guide for leading global accounting protocols. It is fully aligned with:
- Greenhouse Gas Protocol: The foundational corporate accounting standard.
- ISO 14083: The new international standard that formally superseded EN 16258, making GLEC the de facto industry guide for ISO compliance.
- CDP Reporting: It structures data to meet the Carbon Disclosure Project's logistics-specific reporting requirements.
- Science Based Targets initiative (SBTi): It provides the granular data needed to set and track science-based emission reduction targets for transport.
Allocation Logic for Shared Transport
A critical feature is its methodology for allocating emissions to individual shipments on shared services like Less-than-Truckload (LTL) or container shipping. The framework defines allocation factors based on weight, volume, or a combination, ensuring that a single pallet on a shared truck is assigned a fair and defensible share of the total journey's emissions. This is essential for accurate product-level carbon footprinting and customer reporting.
Scope 3 Category 4 & 9 Focus
The framework is specifically designed to address the most challenging parts of a corporate carbon footprint: Scope 3 emissions. It provides the methodology for:
- Category 4 (Upstream Transportation & Distribution): Emissions from inbound logistics and supplier transport.
- Category 9 (Downstream Transportation & Distribution): Emissions from outbound logistics to customers. This makes it the primary tool for companies seeking to manage the indirect emissions that often constitute the majority of their total carbon impact.
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Frequently Asked Questions
Clear, technical answers to the most common questions about the Global Logistics Emissions Council Framework, the universal standard for calculating and reporting multi-modal logistics emissions.
The Global Logistics Emissions Council (GLEC) Framework is a universally recognized methodology for calculating and reporting greenhouse gas emissions across a multi-modal logistics supply chain. It works by providing a harmonized set of rules, emission factors, and calculation methods that allow shippers, carriers, and logistics service providers to consistently quantify their carbon footprint. The framework aligns with the Greenhouse Gas Protocol and the ISO 14083 standard, ensuring that emission data is comparable, auditable, and actionable. It covers all transport modes—road, rail, air, ocean, and inland waterways—and includes both well-to-wheel (WTW) and tank-to-wheel (TTW) emission scopes, enabling end-to-end carbon accounting from raw material extraction to final delivery.
Related Terms
The GLEC Framework does not operate in isolation. It is the central accounting spine that connects to reporting protocols, calculation engines, and decarbonization strategies. The following concepts are essential for implementing a GLEC-compliant logistics emissions program.
ISO 14083 Protocol
The international standard that formally superseded the EN 16258 standard and now incorporates the GLEC Framework as its default implementation guideline. It specifies a universal methodology for quantifying and reporting greenhouse gas emissions from transport chain operations, ensuring global consistency in carbon accounting across all modes.
Emission Factor Matching Engine
A software component that automates the core GLEC calculation step: selecting the correct CO2e conversion factor. It matches transport activity data—mode of transport, fuel type, distance, and vehicle load—against a managed database to compute emissions without manual lookups.
Well-to-Wheel Calculation
The life-cycle analysis boundary mandated by the GLEC Framework for comprehensive accounting. It captures emissions from two distinct stages:
- Well-to-Tank (WTT): Fuel production, refining, and distribution
- Tank-to-Wheel (TTW): Fuel combustion during vehicle operation Together, they provide the total energy pathway footprint.
Scope 3 Emission Modeling
The computational process of quantifying indirect greenhouse gas emissions in a company's value chain. The GLEC Framework is the primary methodology for calculating Scope 3, Category 4 (Upstream Transportation and Distribution) and Category 9 (Downstream Transportation and Distribution) emissions for corporate GHG inventories.
Emission Inventory Boundary
Defines the organizational and operational perimeter for carbon accounting. The GLEC Framework requires a clear boundary definition based on either the equity share approach or the operational control approach, determining which logistics assets and activities are included in the emissions total.
Carbon Data Provenance
A cryptographically secured, immutable record of the origin and transformation history of an emission data point. When applying the GLEC Framework, maintaining a verifiable chain of custody for every activity data input and emission factor ensures audit-readiness and prevents greenwashing claims.

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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