Reducing the carbon footprint of urban bus fleets using multi-objective optimization

Ribau, João P.; Sousa, J.M.; Silva, Carla M.

doi:10.1016/j.energy.2015.09.112

Cited by 22 publications

(12 citation statements)

References 28 publications

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“…The Delphi approach was used in five instances to analyze the decision context while using AHP (Hsueh and Yan, 2011;Jain et al, 2014), WSM (Haruvy and Shalhevet, 2007;, and WASPAS for alternative comparison. Development was also found between MODM/SODM and other MCDA methods in four studies, where WSM Ribau et al, 2015;, ER , and PWV and GC helped select solutions resulting from optimization calculations. This was also stated as a reason for choosing these methods.…”

Section: Methods Combinationsmentioning

confidence: 99%

Multicriteria Decisions in Urban Energy System Planning: A Review

et al. 2017

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Urban energy system planning (UESP) is a topic of growing concern for cities in deregulated energy markets, which plan to decrease energy demand, reduce their dependency on fossil fuels, and increase the share of renewable energy sources. UESP being a highly multisectoral and multi-actor task, multicriteria decision analysis (MCDA) methods are frequently used in the decision processes. These methods may provide support in organizing and identifying solutions to problems with conflicting objectives. However, knowing which method to use is generally not straightforward, as the appropriateness of a method or combination of methods depends on the decision problem's context. Therefore, this article reviewed scientific papers to characterize and analyze MCDA problems and methods in the context of UESP. The review systematically explores issues such as the scope of the problems, the alternatives and criteria considered, the expected decision outcomes, the decision analysis methods and the rationales for selecting and combining them, and the role of values in driving the decision problems. The final outcome is a synthesis of the data and insights obtained, which may help potential users identify appropriate decision analysis methods based on given problem characteristics.

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Section: Methods Combinationsmentioning

confidence: 99%

Multicriteria Decisions in Urban Energy System Planning: A Review

et al. 2017

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“… The use of aggregated process-based WTT inventories from literature or model databases [43,44] is prevalent in many studies, where the quantifiable environmental impact is used as a model input and not mapped for specific pathways [11,12,16,[19][20][21][45][46][47]. However, WTT environmental impacts are highly location specific and can vary with time, for example the GHG impacts of electric vehicles are dependent on grid composition, which can fluctuate daily and change significantly annually [7,48].…”

Section: Life Cycle Modelling Of Bus Technologiesmentioning

confidence: 99%

“… Although life cycle impacts can be significantly affected by operational factors, such as auxiliary loads [14,15,20,46] and drivetrain component replacement frequency [5,6,11,17,24,25,49], many models use static inputs of fuel economy [13,17,21,23,42,50] and battery replacements [9][10][11]17,46]. However, other research has used vehicle simulation models that are sensitive to varying input parameters to predict the fuel or energy consumption, costs and emissions criteria over a drive cycle [5,6,11,14,46,49]. Further developments have integrated the simulation models into life cycle models to calculate battery replacements [5,6,49].…”

Section: Life Cycle Modelling Of Bus Technologiesmentioning

confidence: 99%

“… With all LCAs it is important to avoid double counting. This is of particular concern in the quantification of the environmental impacts associated with scheduled repair and maintenance as there is relatively limited literature on the subject [9,10,17,18,46,51]. Previous work used hybrid LCA, but the methodology has not been fully developed and double counting was apparent.…”

Section: Life Cycle Modelling Of Bus Technologiesmentioning

confidence: 99%

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Assessing life cycle impacts and the risk and uncertainty of alternative bus technologies

Harris

Soban

Best³

2018

Renewable and Sustainable Energy Reviews

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“…Thomas Wiedmann and Jan Minx [21] proposed a scientific definition for carbon footprint: a measure of the exclusive total amount of carbon dioxide emissions that are directly or indirectly caused by an activity or are accumulated over the life stages of a product. Numerous studies have proposed different ways of calculating the carbon footprint, as well as analyzed the factors influencing GHG emissions [22][23][24][25][26][27][28][29][30]. One study, for example, analyzed the carbon footprint of eight categories of products and services: construction, shelter, food, clothing, mobility, manufactured products, services, and trade [31].…”

Section: Introductionmentioning

confidence: 99%

Ecological Pressure of Carbon Footprint in Passenger Transport: Spatio-Temporal Changes and Regional Disparities

Wang

Sun

et al. 2018

Sustainability

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Abstract:Passenger transport has become a significant producer of carbon emissions in China, thus strongly contributing to climate change. In this paper, we first propose a model of ecological pressure of the carbon footprint in passenger transport (EP cfpt ). In the model, the EP cfpt values of all the provinces and autonomous regions of China are calculated and analyzed during the period of 2006-2015. For the outlier EP cfpt values of Beijing, Shanghai and Tianjin, the research areas are classified into two scenarios: the first scenario (all the provinces and autonomous regions) and the second scenario (not including Beijing, Shanghai and Tianjin). The global spatial autocorrelation analysis of the first scenario shows that the EP cfpt might be randomly distributed, while it shows positive spatial autocorrelation in the second scenario. Furthermore, we carry out the local spatial autocorrelation analysis of the second scenario, and find that the low aggregation areas are the most common type and are mainly located in the west of China. Then the disparities in EP cfpt between China's Eight Comprehensive Economic Zones are further analyzed. Finally, we put forward a number of policy recommendations in relation to the spatio-temporal changes and the regional disparities of EP cfpt in China. This study provides related references for proposing effective policy measures to reduce the ecological pressure of carbon emissions from the passenger transport sector.

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Reducing the carbon footprint of urban bus fleets using multi-objective optimization

Cited by 22 publications

References 28 publications

Multicriteria Decisions in Urban Energy System Planning: A Review

Multicriteria Decisions in Urban Energy System Planning: A Review

Assessing life cycle impacts and the risk and uncertainty of alternative bus technologies

Ecological Pressure of Carbon Footprint in Passenger Transport: Spatio-Temporal Changes and Regional Disparities

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