Model for the Part Manufacturing and Vehicle Assembly Component of the Vehicle Life Cycle Inventory

Sullivan, J. L.; Burnham, Andrew; Wang, Michael Q.

doi:10.1111/j.1530-9290.2012.00515.x

Cited by 21 publications

(5 citation statements)

References 7 publications

(28 reference statements)

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“…We modelled device assembly assuming an electricity input of approximately 1.5 kWh/kg with an assumed electrical energy/ heat ratio of 2:1 (Sullivan et al 2013) 1 for the assembly of structural components, PTO components, mooring and foundations and the electrical connection.…”

Section: Assembly and Manufacturingmentioning

confidence: 99%

Life cycle assessment of ocean energy technologies

Uihlein

2016

Int J Life Cycle Assess

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Purpose Oceans offer a vast amount of renewable energy. Tidal and wave energy devices are currently the most advanced conduits of ocean energy. To date, only a few life cycle assessments for ocean energy have been carried out for ocean energy. This study analyses ocean energy devices, including all technologies currently being proposed, in order to gain a better understanding of their environmental impacts and explore how they can contribute to a more sustainable energy supply. Methods The study followed the methodology of life cycle assessment including all life cycle steps from cradle to grave. The various types of device were assessed, on the basis of a functional unit of 1 kWh of electricity delivered to the grid. The impact categories investigated were based on the ILCD recommendations. The life cycle models were set up using detailed technical information on the components and structure of around 180 ocean energy devices from an in-house database.Results and discussion The design of ocean energy devices still varies considerably, and their weight ranges from 190 to 1270 t, depending on device type. Environmental impacts are closely linked to material inputs and are caused mainly by mooring and foundations and structural components, while impacts from assembly, installation and use are insignificant for all device types. Total greenhouse gas emissions of ocean energy devices range from about 15 to 105 g CO 2 -eq. kWh −1 . Average global warming potential for all device types is 53 ± 29 g CO 2 -eq. kWh −1 . The results of this study are comparable with those of other studies and confirm that the environmental impacts of ocean energy devices are comparable with those of other renewable technologies and can contribute to a more sustainable energy supply. Conclusions Ocean energy devices are still at an early stage of development compared with other renewable energy technologies. Their environmental impacts can be further reduced by technology improvements already being pursued by developers (e.g. increased efficiency and reliability). Future life cycle assessment studies should assess whole ocean energy arrays or ocean energy farms.

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Section: Assembly and Manufacturingmentioning

confidence: 99%

Life cycle assessment of ocean energy technologies

Uihlein

2016

Int J Life Cycle Assess

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“…Hence, the only factor which contributes to energy variance in this period is the change in vehicle fuel economy which ranged between 9.23 to 10.55 km/L. Additionally, Sullivan et al (2012) found that the vehicle assembly phase of the vehicle life cycle inventory shows a coefficient of variance of 8.4% for energy intensity. Lastly, the end-of-life portion of the vehicle's life cycle usually has the least total energy consumption.…”

Section: Monte Carlo Simulations and Analysis Of Variance (Temporality)mentioning

confidence: 95%

The Effects of Temporality and Spatiality Due to Aged Data in LIfe Cycle Assessments

Pryshlakivsky¹

2021

Preprint

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Life cycle assessment is a relatively new—although decades old—method for assessing the environmental impacts of goods and services. It seeks to quantify these impacts in such a manner as to facilitate informed decisions regarding different, yet equally viable, options. However, this aim must be conditional on the notion that these impacts are measured with a number of associated qualifications or caveats, two of which is subject of this work. As subject matter, temporality and spatiality in life cycle assessment are both very broad, although this dissertation focuses specifically on temporality and spatiality due to age of data. The structure of the dissertation follows three distinct phases. The first phase contextualized the subject matter and its relation towards standardization of life cycle assessment methods. In doing so, it identifies and contextualizes the subject matter. The second phase identified Greenhouse gases, Regulatory Emissions, and Energy use in Transportation 2 as an ideal model on which to assess temporality and spatiality due to age of data since it models the life cycle assessment of an assortment of different vehicles. This phase also involved data collection, and uses a platform of assessment tools including Monte Carlo simulations, analysis of variance, F tests, regression analysis, and tests for non-normality (kurtosis and skewness). Building on the second phase, the third phase moved beyond the original phases by more than doubling the amount of materials of manufacture to be studied and adding further tools for assessment, the mainstay of which are regression analyses. Overall, this study found that the use of Monte Carlo simulations and analysis of variance are useful for identifying long term variation in energy intensity of materials. F-tests were useful in identifying which materials showed effects owing to spatiality. Although not in all instances, tests for non-normality identified which circumstances merit log transformation to bring about more accurate results. Linear regression techniques were used as a posterior test to confirm the origins of the variation seen in the Monte Carlo simulations and the analysis of variation. Moving ahead, this study pointed to the need for more concerted efforts in data promulgation.

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“…Most existing studies on the transport energy consumption in cities have focused on the tank to wheel (TTW) energy consumption during the operational phase. Meanwhile, the significant impact of energy consumption during the manufacturing phase, especially material structure, has been widely highlighted [28,[42][43][44]. As such, this study considers energy consumption during the phases of material structure and operation among all lifecycle stages.…”

Section: Boundary Of Energy Consumptionmentioning

confidence: 99%

Chronological Transition of Relationship between Intracity Lifecycle Transport Energy Efficiency and Population Density

2020

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Interests in evaluating lifecycle energy use in urban transport have been growing as a research topic. Various studies have evaluated the relationship between the intracity transport energy use and population density and commonly identified its negative correlation. However, a diachronic transition in an individual city has yet to be fully analyzed. As such, this study employed transport energy intensity widely used for evaluating transport energy efficiency and obtained the transport energy intensity for each transportation means including walk, bicycle, automobile (conventional vehicles, electric vehicles, hybrid vehicles, and fuel cell vehicles), bus and electric train by considering the lifecycle energy consumption. Then, the intracity lifecycle transport energy intensity of 38 cities in Japan in 1987–2015 was computed, assuming that the cause of diachronic transition of intracity transport energy efficiency is the modal shifting and electricity mix change. As a result, the greater level of population density was associated with the lower intracity transport energy intensity in Japanese cities. The negative slope of its regression line increased over time since the intracity lifecycle transport energy intensity in cities with low population density continuously increased without any significant change of population density. Finally, this study discussed the strategic implications particularly in regional areas to improve the intracity lifecycle transport energy efficiency.

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Model for the Part Manufacturing and Vehicle Assembly Component of the Vehicle Life Cycle Inventory

Cited by 21 publications

References 7 publications

Life cycle assessment of ocean energy technologies

Life cycle assessment of ocean energy technologies

The Effects of Temporality and Spatiality Due to Aged Data in LIfe Cycle Assessments

Chronological Transition of Relationship between Intracity Lifecycle Transport Energy Efficiency and Population Density

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