Review of factors affecting earthworks greenhouse gas emissions and fuel use

Adrien Roy, Brenda Y. McCabe, Shoshanna Saxe and I. Daniel Posen

Renewable and Sustainable Energy Reviews, 2024, vol. 194, issue C

Abstract: Research on greenhouse gas (GHG) emissions in the building sector has concentrated on the use phase of buildings, and more recently embodied emissions from construction materials. Much less research has focused on reducing GHG emissions from onsite fuel use during construction, in part because predicting and measuring fuel use is complex and lacks guidance to help modelers focus on key factors that drive variability in results. This paper addresses that challenge by examining the state-of-the-art in onsite fuel use accounting with a focus on earthworks, one of the largest drivers of onsite fuel consumption. It provides a comprehensive summary of the existing literature, describes and quantifies the ways in which factors influence fuel use, and fills several gaps identified during the review process by drawing from research in related fields. The result is a new taxonomy for categorizing fifteen factors which influence fuel use, including equipment factors (e.g., engine specifications, attachment selection), operational factors (e.g., operator skill, fleet configuration), and site factors (e.g., soil type, excavation depth). Drawing on earthwork productivity and productivity/fuel use in related fields (e.g., freight hauling, military equipment) to augment the construction emissions literature, most notably to investigate the influence of weather on earthwork GHG emissions. Across case studies, soil type, attachment selection, engine specifications, weather and hauling conditions arise as the most influential factors. Finally, this work presents recommendations for structured fuel use data collection to improve the consistency of future data collection and reporting, along with subsequent fuel use modelling and optimization efforts.

Keywords: Earthworks; Construction equipment; Greenhouse gas emissions; Fuel use; Data collection; Infrastructure; Influencing factors (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.rser.2024.114290

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