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Cleaner Engineering and Technology
Article . 2021 . Peer-reviewed
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Cleaner Engineering and Technology
Article
License: CC BY NC ND
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Routing on-road heavy vehicles for alleviating greenhouse gas emissions

Authors: Hoda Karimipour; VivianW.Y. Tam; Khoa N. Le; Helen Burnie;

Routing on-road heavy vehicles for alleviating greenhouse gas emissions

Abstract

The increasing demand for freight transport leads to rising fuel consumption and additional greenhouse gas (GHG) emissions. This study aims to evaluate the impact of route optimization of heavy vehicles on fuel consumption and GHG emissions. The regular routes of two piloted trucks were extracted and compared with the optimized distances from the simulated model by Network Analyst in Arc GIS. By using Network Analyst and combining it with the Fuel Consumption Rate (FCR) and GHG emission, this study takes a step forward to quantify the amount of fuel usage and GHG emitted from heavy vehicles in the optimized routes versus their regular paths. For this purpose, two different trucks of Blacktown City (Australia) were selected: a waste collector and a tree maintenance truck. The result of the study shows that using the optimized route instead of the regular one can reduce the distance driven by tree maintenance truck by 60%, fuel consumption by 62%, and GHG emissions by 62% per month. In addition, the optimized route shows a 10% reduction in distance travelled, 11% in fuel consumption, and 10% in GHG emission per month. This study also compares fixed-mission and changing-mission trucks. . The results in this part show that the fixed mission truck is much more efficient. Therefore, implementing any efficient vehicle routing system will have considerable impacts on the changing-mission trucks.

Keywords

Route optimization, TJ807-830, Environmental engineering, TA170-171, GIS, Renewable energy sources, GHG emissions, XXXXXX - Unknown, Heavy vehicles, Fuel efficiency

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
gold