Life Cycle Assessment of Commercial Delivery Trucks: Diesel, Plug-In Electric, and Battery-Swap Electric

Yang, Lei; Hao, Caixia; Chai, Yina

doi:10.3390/su10124547

Cited by 37 publications

(34 citation statements)

References 40 publications

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“…More information on the environmental impacts of various products or materials can also be found in the literature. Regarding transportation, the share of transport in global greenhouse gases (GHG) in typical modes of transport [74][75][76][77] as well as electric vehicles [76,78,79] was analyzed in a search for ways of reducing emissions and global energy consumption [1]. Despite a considerable amount of literature studies concerning the environmental impact of different transportation modes [76,[80][81][82], most of the studies are focused only on the level of greenhouse gas emissions expressed in the Global Warming Potential (GWP) index.…”

Section: Eco-efficiency Concept and Life Cycle Assessment To Measure mentioning

confidence: 99%

Are Short Food Supply Chains More Environmentally Sustainable than Long Chains? A Life Cycle Assessment (LCA) of the Eco-Efficiency of Food Chains in Selected EU Countries

et al. 2020

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Improving the eco-efficiency of food systems is one of the major global challenges faced by the modern world. Short food supply chains (SFSCs) are commonly regarded to be less harmful to the environment, among various reasons, due to their organizational distribution and thus the shortened physical distance between primary producers and final consumers. In this paper, we empirically test this hypothesis, by assessing and comparing the environmental impacts of short and long food supply chains. Based on the Life Cycle Assessment (LCA) approach, we calculate eco-efficiency indicators for nine types of food distribution chains. The analysis is performed on a sample of 428 short and long food supply chains from six European countries. Our results indicate that, on average, long food supply chains may generate less negative environmental impacts than short chains (in terms of fossil fuel energy consumption, pollution, and GHG emissions) per kg of a given product. The values of eco-efficiency indicators display a large variability across analyzed chains, and especially across different types of SFSCs. The analysis shows that the environmental impacts of the food distribution process are not only determined by the geographical distance between producer and consumer, but depend on numerous factors, including the supply chain infrastructure.

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Section: Eco-efficiency Concept and Life Cycle Assessment To Measure mentioning

confidence: 99%

Are Short Food Supply Chains More Environmentally Sustainable than Long Chains? A Life Cycle Assessment (LCA) of the Eco-Efficiency of Food Chains in Selected EU Countries

et al. 2020

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“…However, some of these studies use a rational behavior framework (such as the rational choice theory) to determine positive and negative perceptions, while others inspect the perception effect, which is either positive or negative [17]. Furthermore, a large body of previous studies covers the industrial policy from the perspective of supply [32][33][34][35][36], rather than discussing consumers' purchase behavior of BEVs from the perspective of demand. Table 1 presents the different opinions of major studies on the perceptions and experience of BEVs.…”

Section: Purchase Intentions For a Battery Electric Vehicle (Bev)mentioning

confidence: 99%

A SEM–Neural Network Approach to Predict Customers’ Intention to Purchase Battery Electric Vehicles in China’s Zhejiang Province

Zhang

Bao

et al. 2019

Sustainability

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As part of the increasing efforts toward the prevention and control of motor vehicle pollution, the Chinese government has practiced a range of policies to stimulate the purchase and use of battery electric vehicles (BEVs). Zhejiang Province, a key province in China, has proactively implemented and monitored an environmental protection plan. This study aims to contribute toward streamlining marketing and planning activities to introduce strategic policies that stimulate the purchase and use of BEVs. This study considers the nature of human behavior by extending the theory of planned behavior model to identify its predictors, as well as its non-linear relationship with customers' purchase intention. To better understand the predictors, a substantial literature review was given to validate the hypotheses. A quantitative study using 382 surveys completed by customers in Zhejiang Province was conducted by integrating a structural equation model (SEM) and a neural network (NN). The initial analysis results from the SEM revealed five factors that have impacted the customers' purchase intention of BEVs. In the second phase, the normalized importance among those five significant predictors was ranked using the NN. The findings have provided theoretical implications to scholars and academics, and managerial implications to enterprises, and are also helpful for decision makers to implement appropriate policies to promote the purchase intention of BEVs, thereby improving the air quality.

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“…Also, to facilitate vehicles, it is not compulsory to confine infrastructure deployment to charging stations only as battery swapping stations (BSSs) can also fulfill EVs demands by exchanging depleted battery with a fully charged battery pack. The study conducted in [50] defines the composition of average investment on a single BSS which includes similar investment areas for charging stations. The investment details are given in Table V.…”

Section: ) Capital Costsmentioning

confidence: 99%

“…Since the goods movement under the CPEC is expected to be colossal, the ownership cost associated with trucks will be highlighted to estimate trucks' cost with different powertrain technologies. The analysis conducted in [52] compares the ownership costs between diesel trucks (DTs), plug-in electric trucks (PETs), and battery swapping based electric trucks (SETs). All of these vehicles are compared in their two variants which are light and mediumduty trucks.…”

Section: ) Capital Costsmentioning

confidence: 99%

Electric Transportation in Pakistan Under CPEC Project: Technical Framework and Policy Implications

et al. 2020

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Transportation sector in Pakistan has been rapidly growing, leading to an increase in diesel and petroleum consumption, heightened energy import bill, air pollution, and traffic congestion. The China-Pakistan economic corridor (CPEC) is a cluster of different multi-billion-dollar projects with a significant emphasis on enhancing regional connectivity, and the transportation sector is considered its backbone. Electric road transportation appears to be a game-changer to tackle energy, economy, and environmental issues of a country. This research paper is focused on a scheme and valuation of deploying electric transportation (e-trans) for mass transit under the CPEC umbrella in Pakistan. This paper identifies barriers and challenges and explores various technological options for adopting suitable electric vehicles (EVs) for mass transportation. The paper investigates technical infrastructural requirements, financial, and policy implications for the successful deployment of the proposed electric transportation. In particular, it proposes an EV charging infrastructure based on solar power generation to avoid any electricity burden to recharge EVs from the national power grid. In order to be comprehensive, it presents a case study to develop an EV charging station network with an estimation of the cost for accommodating charging requirements of one thousand electric trucks and hundred mobile charging trucks. Obtained results demonstrate that merely 0.29% of the CPEC's energy sector approved budget will be incurred for deploying the proposed charging station network to support e-trans over the studies road segment, which appears to be a feasible initiative. Important factors which may influence the proposed scheme for implementation of e-trans under the CPEC is analyzed using SWOT analysis. The recommended set of policies for deploying electric transportation and its quantitative financial analysis will help the concerned stakeholders to discover and execute the necessary steps to ensure sustainable electric transportation under the CPEC in Pakistan.

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Life Cycle Assessment of Commercial Delivery Trucks: Diesel, Plug-In Electric, and Battery-Swap Electric

Cited by 37 publications

References 40 publications

Are Short Food Supply Chains More Environmentally Sustainable than Long Chains? A Life Cycle Assessment (LCA) of the Eco-Efficiency of Food Chains in Selected EU Countries

Are Short Food Supply Chains More Environmentally Sustainable than Long Chains? A Life Cycle Assessment (LCA) of the Eco-Efficiency of Food Chains in Selected EU Countries

A SEM–Neural Network Approach to Predict Customers’ Intention to Purchase Battery Electric Vehicles in China’s Zhejiang Province

Electric Transportation in Pakistan Under CPEC Project: Technical Framework and Policy Implications

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