This paper aims to present a synergistic approach that combines both construction and environmental expertise to lay the groundwork for a model that can be used to estimate the productivity rate and emissions from construction equipment activities.
The proposed estimating tool is developed by combining the productivity rate model from a reliable construction estimating data sources and the calculation algorithm employed by the EPA's NONROAD model. In order to develop productivity models, simple earthwork activities involving bulldozer, excavator, and dump truck were selected.
The MLR approach proved to be a useful alternative for estimating productivity rate of three pieces of equipment. The MLR models for the productivity rate can explain high percentage of the variability in the data. The models are good to be used as a benchmark for estimating NOX and PM emissions from some certain types of construction equipment performing earthwork activities. The productivity rate from this model (lcy/hr) is used with emission factors (g/hp‐hr) from EPA's NONROAD model to estimate the total emissions.
The estimating tool proposed in this paper will be an effective means for assessing the environmental impacts of construction activities and will allow equipment owners or fleet managers, policy makers, and project stakeholders to evaluate more sustainable alternatives. The tool will help the contractor to estimate the total expected pollutant emissions for the project, which would be valuable information for a preliminary environmental assessment of the project.
Although there are already methods and models for estimating productivity for construction equipment, there currently is not a means for doing estimates of air pollutant emissions at the same time, particularly for NOX and PM.
Hajji, A.M. (2013), "Estimating the emissions of nitrogen oxides (NOX) and particulate matter (PM) from diesel construction equipment by using the productivity model", World Journal of Science, Technology and Sustainable Development, Vol. 10 No. 3, pp. 212-228. https://doi.org/10.1108/WJSTSD-04-2013-0019
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