Macro-Level Construction Material Supply Chain Analysis for Dynamic Cradle-to-Site A4 Transport Carbon Assessment

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a macro-level method for dynamic A4 assessment and identifies data requirements for traceable carbon accounting.

🏢実務担当者:Construction firms and logistics providers can use the framework to improve transport emission reporting and identify hotspots.

🏛政策担当者:Highlights the need for standardized logistics data and digital infrastructure to support accurate carbon accounting in construction.

Construction materials move in large volumes, over varying distances and through fragmented logistics chains. Yet EN 15804 Module A4, which covers transport to the building site, is still often calculated with static assumptions rather than verified transport data. This creates a gap between declared and project-specific cradle-to-site emissions, especially when circular strategies shift flows from factory-to-site towards site-to-site, site-to-processing and processing-to-site logistics. This paper focuses on dynamic A4 assessment, using macro-level analysis to identify the material flows, spatial patterns, transport modes and digital data needed for traceable logistics-based carbon accounting. The framework connects construction material-flow analysis with Digital Product Passports, ISO 14083 logistics data, GS1 Digital Link, GS1 EPCIS and digital-twin concepts. Building-permit data are used as spatial indicators of material sinks and transport-demand hotspots. The analysis uses Slovenian road, rail and maritime freight statistics, operational railway data for construction-related material categories, CDW data and building-permit data for 2020–2024. Results show that domestic road transport accounts for 93–95% of transported construction-material tonnage, while the smaller international freight volume generates nearly half of total ton-kilometers. Macro-level analysis is essential for locating material demand, potential transport hotspots and 5R strategies: refuse, reduce, reuse, repurpose and recycle. This study defines key information needs for product identification, transported mass, transport legs, distance, mode, energy pathway, load factor, empty running, logistics events and traceability. The results support policymakers, standardization bodies, contractors, logistics providers, manufacturers, researchers and software developers.

• openalex https://doi.org/10.3390/su18168285first seen 2026-08-14 05:07:45