Estimating Carbon Emissions from Construction Equipment Fuel Consumption at Construction Sites
Year: 2026
Type: article
Abstract: The planning-stage estimation of fuel-related carbon emissions from construction equipment is constrained by a mismatch between the detailed operational data required for high-resolution methods and the limited information available before construction begins. This study develops a transparent, deterministic framework that converts basic project information and bill of quantities (BOQ) data into equipment workloads, operating hours, fuel consumption, and fuel-related carbon emissions. Standardized productivity values from the 2025 Standard Production Unit System for Construction Works, hourly fuel-consumption rates from the 2025 Construction Equipment Cost Estimation Table, the IPCC fuel-combustion methodology, and an ecoinvent-based upstream fuel factor are integrated through process-level conversion rules. The methodological contribution lies in operationalizing these existing data sources as a traceable low-data estimation chain rather than introducing new productivity or emission factors. In a residential-building case study, earthwork and retaining works and reinforced concrete works accounted for most of the recorded diesel consumption. The predicted fuel-consumption intensity was 10.5 L/m2 compared with an actual value of 13.9 L/m2, while the excavator estimate showed a substantially larger equipment-level deviation. Analytical sensitivity analysis indicates that workload and fuel-rate assumptions affect estimates proportionally, whereas productivity assumptions have an inverse effect. The framework is therefore intended as a preliminary planning and screening tool; equipment-level calibration requires higher-resolution operating-hour and refueling records.
Source: Buildings
Institutions: Hanyang University, Hokkaido University
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G2057357528
OpenAlex ID: W7204944642
