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You searched for subject:(short heavy haul). Showing records 1 – 2 of 2 total matches.

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University of Saskatchewan

1. Couraud, Amelie. Truck transport emissions model.

Degree: 2007, University of Saskatchewan

In the past, transportation related economic analysis has considered agency related costs only. However, transportation managers are moving towards more holistic economic analysis including road user and environmental costs and benefits. In particular, transportation air pollution is causing increasing harm to health and the environment. Transport managers are now considering related emissions in transport economical analyses, and have established strategies to help meet Kyoto Protocol targets, which specified a fifteen percent reduction in Canada's emissions related to 1990 levels within 2008-2012.The objectives of this research are to model heavy vehicle emissions using a emissions computer model which is able to assess various transport applications, and help improve holistic economic transport modeling. Two case studies were evaluated with the model developed.Firstly, the environmental benefits of deploying weigh-in-motion systems at weigh stations to pre-sort heavy vehicles and reduce delays were assessed. The second case study evaluates alternative truck sizes and road upgrades within short heavy oilfield haul in Western Canada. The model developed herein employed a deterministic framework from a sensitivity analysis across independent variables, which identified the most sensitive variables to primary field state conditions. The variables found to be significant included idling time for the weigh-in-motion case study, road stiffness and road grades for the short heavy haul oilfield case study.According to this research, employing WIM at weigh stations would reduce annual Canadian transportation CO2 emissions by nearly 228 kilo tonnes, or 1.04 percent of the Canadian Kyoto Protocol targets. Regarding direct fuel savings, WIM would save from 90 to 190 million litres of fuel annually, or between 59 and 190 million of direct operating costs.Regarding the short heavy oil haul case study, increasing allowable heavy vehicle sizes while upgrading roads could decrease the annual emissions, the fuel consumption, and their associated costs by an average of 68 percent. Therefore, this could reduce each rural Saskatchewan municipality's annual CO2 emissions from 13 to 26.7-kilo tonnes, which translates to 0.06 and 0.12 percent of the Canadian Kyoto Protocol targets or between 544,000 and 1.1 million annually. Based on these results, the model demonstrates its functionality, and was successfully applied to two typical transportation field state applications. The model generated emissions savings results that appear to be realistic, in terms of potential Kyoto targets, as well as users cost reductions and fuel savings. Advisors/Committee Members: Berthelot, Curtis, Sparks, Gordon A., Pufahl, Dennis E., Hertz, P. Barry.

Subjects/Keywords: truck size; deterministic model; road uprgades; short heavy haul; emissions costs; weigh-in-motion system; sustainable develpment; emissions rates

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Couraud, A. (2007). Truck transport emissions model. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/etd-09072007-101348

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Couraud, Amelie. “Truck transport emissions model.” 2007. Thesis, University of Saskatchewan. Accessed March 04, 2021. http://hdl.handle.net/10388/etd-09072007-101348.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Couraud, Amelie. “Truck transport emissions model.” 2007. Web. 04 Mar 2021.

Vancouver:

Couraud A. Truck transport emissions model. [Internet] [Thesis]. University of Saskatchewan; 2007. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10388/etd-09072007-101348.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Couraud A. Truck transport emissions model. [Thesis]. University of Saskatchewan; 2007. Available from: http://hdl.handle.net/10388/etd-09072007-101348

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Victoria

2. Lajevardi, S. Mojtaba. An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia.

Degree: Department of Mechanical Engineering, 2020, University of Victoria

Heavy-duty trucks (HDTs) are vital in delivering products to the consumers around the world and help maintain the quality of life. However, they are heavily depending on fossil diesel use, which causing global climate change as well as local air pollutions. Although they represent a small percentage of vehicle population, they emit more than 30% of GHGs in road transportation or 5% of global greenhouse gas (GHG) emissions. Furthermore, GHG emissions from this sector are expected to steadily grow due to economic growth, globalization, industrialization, online shopping, and fast delivery expectations. This study was focused on the Canadian province of British Columbia (BC) as a case study where HDTs are responsible for more than 4% of total provincial GHGs. BC, along with many regions around the world, has been committed to reduce its GHG emissions by 80% below 2007 levels by 2050. The goal of this study was to evaluate the potential of meeting this objective for BC HDTs using alternative drivetrain technologies. First, a component-level model was developed in Matlab to compute on-road energy consumption and CO2 emissions of compressed natural gas and diesel HDTs based on their physical parameters (e.g. mass) over several selected drive cycles. Results of the first contribution indicated a compressed natural gas (CNG) drivetrain emits 13-15% fewer GHG than a comparable diesel. Road grades of several main BC routes were included in the drive cycle simulations, which is an important factor that can increase the fuel consumption and CO2 emission by as much as 24% relative to a flat route assumption. In the second contribution, the physical energy consumption model was extended to compare 16 diverse drivetrain technologies, including a pure battery electric. The comparison metrics were also extended to well-to-wheel GHG emissions, total ownership costs (TOC) (including infrastructure), and abatement costs (based on incremental TOC cost over GHG emissions reduction), and cargo capacity impacts. The 16 considered drivetrains were distinguished by their fuel types, combustion technology, drivetrain architecture, and connection to the electricity grid (e.g. catenary vs fast charging stations). Next, the activity data of 1,616 HDTs operating in BC with sparse recording intervals was used to select 6 representative freight routes with different ranges of 120-950 km split into short and long haul routes. A combination of filtering and interpolation techniques was used to develop 1-Hz drive cycles compatible with the characteristic of HDTs categorized by the U.S. National Renewable Energy Laboratory. Results indicated a battery electric and battery electric catenary using hydroelectricity emits 95–99% lower GHGs than a baseline diesel. Furthermore, the parallel hybrid diesel was found to have both the lowest TOC and abatement costs for both short and long haul routes. Moreover, plug-in parallel hybrid fuel cell and conventional diesel drivetrains were found to have the highest cargo capacity on short and long haul routes… Advisors/Committee Members: Crawford, Curran (supervisor), Axsen, Jonn (supervisor).

Subjects/Keywords: Alternative drivetrains; CO2 emissions; Compressed natural gas (CNG); Diesel; Energy consumption; Physical energy consumption model; Drive cycle; Freight; Battery electric; Fuel cell; Greenhouse gas (GHG) emissions; Heavy-duty truck; Hybrid; Parallel; Series; Hydrogen; Long haul; Monte Carlo; Market share; ZEV mandate; Winner; Well to wheel; Short haul; Tractor-trailer; Infrastructure; Total ownership cost; Vehicle adoption model; Consumer behavior; Intangible cost; Plug-in hybrid

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lajevardi, S. M. (2020). An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia. (Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/11446

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lajevardi, S Mojtaba. “An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia.” 2020. Thesis, University of Victoria. Accessed March 04, 2021. http://hdl.handle.net/1828/11446.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lajevardi, S Mojtaba. “An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia.” 2020. Web. 04 Mar 2021.

Vancouver:

Lajevardi SM. An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia. [Internet] [Thesis]. University of Victoria; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1828/11446.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lajevardi SM. An examination of heavy-duty trucks drivetrain options to reduce GHG emissions in British Columbia. [Thesis]. University of Victoria; 2020. Available from: http://hdl.handle.net/1828/11446

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.