Energy and exergy utilization efficiencies and emission performance of Canadian transportation sector, 1990–2035

Motasemi, F.; Afzal, Muhammad T.; Salema, Arshad Adam; Moghavvemi, Mahmoud; Shekarchian, M.; Zarifi, Farhad; Mohsin, Rahmat

doi:10.1016/j.energy.2013.09.064

Cited by 42 publications

(8 citation statements)

References 34 publications

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“…They suggest a formalisation of the methods for modelling the sectoral energy and exergy utilisation, starting from the listing of all energy and exergy inputs and outputs, then with a sub-grouping of the sectors into utility, industrial, commercial, residential & transportation, and a further splitting into each end-user. Other works focus on specific sectors, such as Dincer et al[2004b] and Liu et al[2014] on the residential sector of Saudi Arabia and China, while the one of Motasemi et al[2014] deals with the case of the transport sector of Canada. The studies that are the most relevant to the present work may be the ones of Al-Ghandoor et al[2010], who apply energy and exergy methods, as well as Sanaei et al[2012], Dincer et al[2003] and Oladiran and Meyer[2007], all focusing on the industrial sector of a country.…”

Section: Introductionmentioning

confidence: 99%

Energy and exergy analyses of the Danish industry sector

Bühler¹,

Nguyen²,

Elmegaard³

2016

Applied Energy

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Section: Introductionmentioning

confidence: 99%

Energy and exergy analyses of the Danish industry sector

Bühler¹,

Nguyen²,

Elmegaard³

2016

Applied Energy

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“…The system optimization method has been widely used in the forecasting of CO 2 emissions and energy demand [19][20][21]. Additionally, it has been used in the process of planning networks that can help in energy supply activities [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Application of a Adaptive Neuro-Fuzzy Technique for Projection of the Greenhouse Gas Emissions from Road Transportation

et al. 2019

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In the past, different forecasting models have been proposed to predict greenhouse gas (GHG) emissions. However, most of these models are unable to handle non-linear data. One of the most widely known techniques, the Adaptive Neuro-fuzzy inference system (ANFIS), can deal with nonlinear data. Its ability to predict GHG emissions from road transportation is still unexplored. This study aims to fulfil that gap by adapting the ANFIS model to predict GHG emissions from road transportation by using the ratio between vehicle-kilometers and number of transportation vehicles for six transportation modes (passenger cars, motorcycle, light trucks, single-unit trucks, tractors, and buses) from the North American Transportation Statistics (NATS) online database over a period of 22 years. The results show that ANFIS is a suitable method to forecast GHG emissions from the road transportation sector.

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“…Finally, the fourth method is system optimisation. This has been widely used in forecasting energy demand and CO 2 emissions (Hickman and Banister, 2007;Si et al, 2012;Ahanchian and Biona, 2014;Motasemi et al, 2014;Shakya and Shrestha, 2011); in analysing integrated energy planning for sustainable development (Szendro and Torok, 2014); and in the analysis of policy effect (Almodovar et al, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Growth in transport sector CO<SUB align="right">2 emissions in Tunisia: an analysis using a bounds testing approach

Abbes¹,

Bulteau²

2018

IJGEI

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This paper analyses the dynamic impacts of GDP growth, motorisation rate, transport pollution coefficient and energy intensity, on CO 2 emissions from the transport sector in Tunisia. Empirical results from the ARDL approach show that over the 1971-2014 period, energy intensity and pollution coefficient were the most significant variables. The elasticities of motorisation rate to CO 2 emissions were also significant and had the expected sign. These results not only contribute to advancing the existing literature but also provide important policy recommendations: to control transport emissions, policy-makers should invest in public transportation and reinforce the legislation on environmental standards of vehicles. Finally, the statistically insignificant effects of per capita GDP on transport carbon emissions in the long run suggest that it is possible to control these emissions without disrupting economic growth. This can be achieved by developing short sea shipping between the biggest cities to reduce road congestion and carbon emissions.

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Energy and exergy utilization efficiencies and emission performance of Canadian transportation sector, 1990–2035

Cited by 42 publications

References 34 publications

Energy and exergy analyses of the Danish industry sector

Energy and exergy analyses of the Danish industry sector

Application of a Adaptive Neuro-Fuzzy Technique for Projection of the Greenhouse Gas Emissions from Road Transportation

Growth in transport sector CO<SUB align="right">2 emissions in Tunisia: an analysis using a bounds testing approach

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