The use of construction equipment productivity rate model for estimating fuel use and carbon dioxide (CO<sub>2</sub>) emissionsCase study: bulldozer, excavator and dump truck

Hajji, Apif M.

doi:10.1080/19397038.2014.962645

Cited by 14 publications

(5 citation statements)

References 7 publications

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“…A eet containing backhoes, motor graders and wheel loaders was used as a case study to monitor fuel usage and emission rates. Similarly, [19] employed multiple regression (MLR) to predict fuel consumption and emissions for numerous construction equipment based on earthwork productivity. The equipment used in their analysis were bulldozer, excavator, and dump truck.…”

Section: Results and Interpretationsmentioning

confidence: 99%

A Review on Machine Learning for Sustainable Construction Equipment

Khan,

Afzal

2023

Preprint

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The construction sector is producing enormous amount of emission due to usage of heavy machinery. To address global climate concerns, mitigating these greenhouse gas (GHG) emissions is important. The latest technological advancement offers an opportunity to improve the sustainability of equipment operation, often deployed in large scale construction projects. Thus, this research evaluates machine learning algorithms to decrease equipment emission and encourages construction practitioners to adopt innovative tools to replace existing practices. A systematic review was conducted upon a collection of 15 publications related to the subject. Future research direction was given for improvement meeting real-world cases.

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Section: Results and Interpretationsmentioning

confidence: 99%

A Review on Machine Learning for Sustainable Construction Equipment

Khan,

Afzal

2023

Preprint

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“…The model proposed will be [13] an effective predictive tool for monitoring the fuel use rate and air emissions of infrastructure project activities and will assist equipment owners or fleet managers, policy makers, and project stakeholders to evaluate their construction projects. The model will also help the contractors to estimate the fuel quantities they need and possible pollutant emissions, which would be vital information for a preliminary environmental evaluation of the project [14,15]. The MLR approach proved to be a useful alternative for estimating the productivity rate of some types of equipment.…”

Section: Methodsmentioning

confidence: 99%

PEMS-on board and E3 Modeling: A Comparison between Real-World Measurement and Emissions Estimates from Construction Equipment

Hajji

Larasati

Lewis

et al. 2019

ced

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Vehicles in construction industry are typically powered by diesel engines and are considered to be an off-road source of air pollution. Air pollutant emissions include nitrogen oxides (NOx), particulate matter (PM), hydrocarbons (HC), and carbon monoxide (CO). Any engine that combusts a nonrenewable carbonaceous fuel will have net emissions of carbon dioxide (CO2). Economic-Energy-Environmental (E3) model, a statistical-modeled tool, is developed by combining a multiple linear regression (MLR) approach for modeling equipment productivity with the emissions calculation algorithm from Environment Protection Agency (EPA)’s NONROAD model. This paper compares emissions data between the field data to E3 model outputs, and determines the similarity of the two sources of fuel use data. It is expected the two data are not narrowly similar since the field data are for individual vehicles, while E3 results are based on NONROAD model, which was intended to estimate average fuel use for a fleet of Heavy-Duty Diesel (HDD) equipment.

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“…Zhang et al (2014) developed a simulation method to estimate the emissions and noise by reflecting the uncertainty, randomness and dynamics in construction. Heidari and Marr (2015) employed a portable emission measurement system (PEMS) for real-time emission measurement of construction equipment under actual operating conditions on site, while Hajji (2015) proposed a methodology for estimating fuel use and CO 2 emissions for some common earthwork activities performed by bulldozer, excavator and dump truck to help the contractor estimate the total expected pollutant emissions for the project.…”

Section: Environmentmentioning

confidence: 99%

A Thematic Review of the Main Research on Construction Equipment over Recent Years

Naskoudakis

Petroutsatou

2017

Period. Polytech. Arch.

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A considerable body of literature has been dedicated to research studies on construction equipment. Many topics were discussed and analysed, and various conclusions have been reported. However, research papers published regarding construction equipment, are highly diversified, and there is a lack of systematic analysis and classification. Hence, a complete understanding of the topic is not possible, nor is the assessment of any future research direction. A meta-analysis of the latest journal papers dedicated to construction machinery would not only delineate the fields the academic research was concentrated on but would additionally reveal potential gaps for future research. In the current study, through a systematic review of the academic literature published over the last decade, primarily identified via online databases, main research themes such as optimisation, maintenance/downtime, productivity, robotics and automation, operator competence, innovation, and environment are determined and discussed, with future research directions suggested. The outcome of this paper will facilitate future researchers to develop a body of knowledge of progress on construction equipment and its potential functions and provide future research directions on this issue. Furthermore, some pointers will be provided regarding the optimum selection of fleet equipment as a key factor for the success of any construction project. These will be given as part of the necessary holistic and strategic approach required to deliver a construction project successfully.

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The use of construction equipment productivity rate model for estimating fuel use and carbon dioxide (CO₂) emissionsCase study: bulldozer, excavator and dump truck

Cited by 14 publications

References 7 publications

A Review on Machine Learning for Sustainable Construction Equipment

A Review on Machine Learning for Sustainable Construction Equipment

PEMS-on board and E3 Modeling: A Comparison between Real-World Measurement and Emissions Estimates from Construction Equipment

A Thematic Review of the Main Research on Construction Equipment over Recent Years

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The use of construction equipment productivity rate model for estimating fuel use and carbon dioxide (CO2) emissionsCase study: bulldozer, excavator and dump truck

Cited by 14 publications

References 7 publications

A Review on Machine Learning for Sustainable Construction Equipment

A Review on Machine Learning for Sustainable Construction Equipment

PEMS-on board and E3 Modeling: A Comparison between Real-World Measurement and Emissions Estimates from Construction Equipment

A Thematic Review of the Main Research on Construction Equipment over Recent Years

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Product

Resources

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The use of construction equipment productivity rate model for estimating fuel use and carbon dioxide (CO₂) emissionsCase study: bulldozer, excavator and dump truck