Purpose -This paper aims to present the framework for a model that can be used to estimate the production rate, activity duration, total fuel use, and total pollutants emissions from earthwork activities. A case study and sensitivity analysis for an excavator performing excavations are presented. Design/methodology/approach -The tool is developed by combining the multiple linear regressions (MLR) approach for modeling the productivity with the EPA's NONROAD model. The excavator data were selected to build the productivity model, and emission factors of all type of pollutants from NONROAD model were used to estimate the total fuel use and emissions. Findings -Results indicate that the excavator productivity model had high precision and accuracy, low bias, with trench depth and bucket size are in the model, it can explain 92 per cent variability of productivity rate data, and can be used as the basis for estimating the fuel quantities that will be required and the total expected pollutant emissions for the project. Practical implications -The estimating tool proposed in this paper will be an effective means for assessing the fuel consumptions and air emissions of earthwork activities and will allow equipment owners or fleet managers, policy makers, and project stakeholders to evaluate their construction projects. The tool will help the contractors to estimate the fuel quantities and pollutant emissions, which would be valuable information for a preliminary environmental assessment of the project. Originality/value -Although there are already methods and models for estimating productivity rate and emissions for heavy duty diesel (HDD) construction equipment, there currently is not a means for doing all of these at once.
Earthwork activities are typically performed by heavy duty diesel (HDD) construction equipment that consumes large quantities of diesel fuel use and emits large quantities of pollutants, including nitrogen oxides (NOx), particulate matters (PM), hydrocarbon (HC), carbon monoxide (CO), and carbon dioxide (CO 2). This paper presents the framework for a model that can be used to estimate the production rate, activity duration, total fuel use, and total pollutants emissions for earthwork activities. A case study and sensitivity analysis for an excavator performing excavations are presented. The tool is developed by combining the multiple linear regressions (MLR) approach for modeling the productivity with the EPA's NONROAD model. The excavator data from RSMeans Heavy Construction Data were selected to build the productivity model, and emission factors of all type of pollutants from NONROAD model were used to estimate the total fuel use and emissions. The MLR model for the productivity rate can explain 92% of the variability in the data. Based on the model, the fuel use and emissions of excavator increase as the trench depth increase, but as the bucket size increase, the fuel use and emissions decrease.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.