Greenhouse Gas Emissions from Onsite Equipment Usage in Road Construction

Kim, Byungil; Lee, Hyounkyu; Park, Hyungbae; Kim, Hyoungkwan

doi:10.1061/(asce)co.1943-7862.0000515

Cited by 66 publications

(53 citation statements)

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“…Equipment categorization, age and horsepower and as well as type of fuel used, can greatly affect rates of emissions [11]. Based on the previous study, it was determined that during construction phase, earthwork produces highest percentage of GHG emissions [4].…”

Section: Onsite Emissions and Their Hazardous Effectsmentioning

confidence: 99%

“…The past studies have shown that environmental focus in construction was more on material selection, structure design, materials recycling rather than GHG emissions [4]. Furthermore, previous efforts to reach sustainability have primarily focused on the environmental performance of facilities in the "use" phase, and such efforts are lately being expanded to mitigate environmental impacts from the "construction" phase [5].…”

Section: Onsite Emissions and Their Hazardous Effectsmentioning

confidence: 99%

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Environmental implications of onsite mechanization in the Malaysian construction industry

Waris

Liew

Khamidi

et al. 2014

WIT Transactions on Ecology and the Environment

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In Malaysia, there has been a growing need for mechanization in recent years due to the high construction demand under the Economic Transformation Programme. Onsite mechanization in construction implies the use of equipment and machinery that are powered by fossil fuels with the aim of reducing the dependency on manual labour and to increase productivity, quality and efficiency. However, this heavy equipment and machinery are also responsible for issues pertaining to environment, health and safety of human beings. All nonroad diesel engine machinery emits hazardous gases, particulate matters, solid waste and contaminate land, water and the environment. Prior research on environmental impacts of construction works was more focused on raw materials, its manufacturing and operational phase of the facility. Therefore, the aim of this research is to focus on environmental concerns that are important during construction and mainly due to the operation of onsite heavy construction equipment. Data for the analysis was collected through a questionnaire survey from Malaysian G7 class 'A' contractors. The results of the survey show that despite the good awareness of Malaysian contractors towards a green environment, their practices for controlling energy consumption and greenhouse gases (GHG) are still in their infancy stages. It was also found that environment management systems are not highly implemented by the contractors. The survey results further indicate that energy saving, GHG and black smoke emission are the top ranking concerns of contractors when operating onsite equipment and

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Section: Onsite Emissions and Their Hazardous Effectsmentioning

confidence: 99%

Section: Onsite Emissions and Their Hazardous Effectsmentioning

confidence: 99%

Environmental implications of onsite mechanization in the Malaysian construction industry

Waris

Liew

Khamidi

et al. 2014

WIT Transactions on Ecology and the Environment

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show abstract

“…Since new GTs are constantly being developed and companies are not prone to open their data due to concerns of intellectual property [5], the database of the present study is established on the basis of a review of previous studies and other accessible information available from several construction companies. In addition, when a new technology applicable to the key work item is not found in the current database, an existing construction method is selected instead by comparing the carbon emissions of conventional construction methods.…”

Section: Proposition Of Frameworkmentioning

confidence: 99%

“…According to the divided stages of a construction project, the planning stage focuses on the management of the carbon emission that will be applied in the following stage that predicts and estimates the amount [2,3]. The construction stage focuses on the calculation of the actual amount of the emission to compare between the different technologies applied [4][5][6]. On the other hand, the maintenance stage covers a long-term management method that impacts the carbon emissions over the usage time of the facility [7][8][9].…”

Section: Literature On Carbon Emissions In the Construction Fieldmentioning

confidence: 99%

Quantitative Decision Making Model for Carbon Reduction in Road Construction Projects Using Green Technologies

2015

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Numerous countries have established policies for reducing greenhouse gas emissions and have suggested goals pertaining to these reductions. To reach the target reduction amounts, studies on the reduction of carbon emissions have been conducted with regard to all stages and processes in construction projects. According to a study on carbon emissions, the carbon emissions generated during the construction stage of road projects account for approximately 76 to 86% of the total carbon emissions, far exceeding the other stages, such as maintenance or demolition. Therefore, this study aims to develop a quantitative decision making model that supports the application of green technologies (GTs) to reduce carbon emissions during the construction stage of road construction projects. First, the authors selected environmental soundness, economic feasibility and constructability as the key assessment indices for evaluating 20 GTs. Second, a fuzzy set/qualitative comparative analysis (FS/QCA) was used to establish an objective decision-making model for the assessment of both the quantitative and qualitative characteristics of the key indices. To support the developed model, an expert survey was performed to assess the applicability of each GT from a practical perspective, which was verified with a case study using two additional GTs. The proposed model is expected to support practitioners in the application of suitable GTs to road projects and reduce carbon emissions, resulting in better decision making during road construction projects. OPEN ACCESSSustainability 2015, 7 11241

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“…Heavy construction machines account for more than 50% of the total emissions from construction operations [4]. According to reports from the National Institute of Environmental Research (NIER) and the Korean Statistical Information Service (KSIS), construction equipment consumes the largest quantity of diesel fuel of all industries in the construction sector in Korea [5], and on-site construction equipment produced 6.8% of the total emissions generated in Korea, with carbon dioxide being a main component of these emissions [6]. In Denmark in 2004, construction machinery accounted for 71% of most fuel use, accounting for 50% of all CO 2 emissions produced by the construction industry [7].…”

Section: Introductionmentioning

confidence: 99%

Predicting Energy Consumption and CO2 Emissions of Excavators in Earthwork Operations: An Artificial Neural Network Model

Jassim

Olofsson

2017

Sustainability

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Excavators are one of the most energy-intensive elements of earthwork operations. Predicting the energy consumption and CO 2 emissions of excavators is therefore critical in order to mitigate the environmental impact of earthwork operations. However, there is a lack of method for estimating such energy consumption and CO 2 emissions, especially during the early planning stages of these activities. This research proposes a model using an artificial neural network (ANN) to predict an excavator's hourly energy consumption and CO 2 emissions under different site conditions. The proposed ANN model includes five input parameters: digging depth, cycle time, bucket payload, engine horsepower, and load factor. The Caterpillar handbook's data, that included operational characteristics of twenty-five models of excavators, were used to develop the training and testing sets for the ANN model. The proposed ANN models were also designed to identify which factors from all the input parameters have the greatest impact on energy and emissions, based on partitioning weight analysis. The results showed that the proposed ANN models can provide an accurate estimating tool for the early planning stage to predict the energy consumption and CO 2 emissions of excavators. Analyses have revealed that, within all the input parameters, cycle time has the greatest impact on energy consumption and CO 2 emissions. The findings from the research enable the control of crucial factors which significantly impact on energy consumption and CO 2 emissions.

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Greenhouse Gas Emissions from Onsite Equipment Usage in Road Construction

Cited by 66 publications

References 1 publication

Environmental implications of onsite mechanization in the Malaysian construction industry

Environmental implications of onsite mechanization in the Malaysian construction industry

Quantitative Decision Making Model for Carbon Reduction in Road Construction Projects Using Green Technologies

Predicting Energy Consumption and CO2 Emissions of Excavators in Earthwork Operations: An Artificial Neural Network Model

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