Life Cycle Assessment in the Built Environment

Crawford, Robert H.

doi:10.4324/9780203868171

Cited by 175 publications

(230 citation statements)

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“…The uncertainty on the embodied energy data is set to ±20% for process analysis data and ±50% for the input-output analysis data based on Crawford [16]. The variability in operational energy figures is set to ±20% based on Pettersen [17] and assumed to be the same for transport energy.…”

Section: A Multi-scale Life Cycle Energy Analysismentioning

confidence: 99%

Multi-scale life cycle energy analysis of a low-density suburban neighbourhood in Melbourne, Australia

Stephan

Crawford

Myttenaere

2013

Building and Environment

112

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There is an increasing pressure on cities worldwide to accommodate the increasing population.Most cities are likely to expand in the coming decades and this expansion will probably take place as low-density neighbourhoods. It is therefore crucial to assess the energy demand and related greenhouse gas emissions of such development from a comprehensive perspective. This paper uses a representative low density case study neighbourhood near Melbourne, Australia, to assess its energy consumption and greenhouse gas emissions over 100 years. Different housing typologies, such as row houses and low-rise apartment buildings, are tested. Results show that the energy required to produce and replace building materials and infrastructures constitutes nearly 26.9% of the total energy consumption while operational and transport requirements represented 39.4% and 33.7% respectively. Variations to the housing types reveal that apartment buildings reduce the energy consumption per capita by 19.6% compared to the one-storey single family detached house typical pattern. Regardless of the uncertainty in the data, the main conclusion is that each of the embodied, operational and transport energy demand and associated greenhouse gas emissions should be lowered in order effectively reduce the environmental impacts of new urban neighbourhoods.

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Section: A Multi-scale Life Cycle Energy Analysismentioning

confidence: 99%

Multi-scale life cycle energy analysis of a low-density suburban neighbourhood in Melbourne, Australia

Stephan

Crawford

Myttenaere

2013

Building and Environment

112

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“…The magnitude of these contributions is termed truncation error. There are broadly three types of truncation error (Crawford 2011):…”

Section: Truncation Errormentioning

confidence: 99%

An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics

Palmer

Floyd²

2017

Biophys Econ Resour Qual

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Solar photovoltaics (PV) is widely regarded as one of the most promising renewable energy technologies. Net energy analysis (NEA) is a tool to evaluate the energetic performance of all energy supply technologies, including solar PV. Results across studies can appear to diverge sharply, which leads to contestation of NEA's relevance to energy transition feasibility assessment and contributes to ongoing uncertainty in relation to the critical issue of the sustainability of PV. This study explores how PV NEA approaches differ, including in relation to goal definitions, methodologies and boundaries of analysis. It focuses on two principal NEA metrics, energy return on investment (EROI) and energy payback time (EPBT). Here we show that most of the apparent divergence between studies is accounted for by six factors-life-cycle assessment methodology, age of the primary data, PV cell technology, the treatment of intermittency, equivalence of investment and output energy forms, and assumptions about real-world performance. The apparent divergence in findings between studies can often be traced back to different goal definitions. This study reviews the differing approaches and makes the case that NEA is important for assessing the role of PV in future energy systems, but that findings in the form of EROI or EPBT must be considered with specific reference to the details of the particular study context, and the research questions that it seeks to address. NEA findings in a particular context cannot definitively support general statements about EROI or EPBT of PV electricity in all contexts.

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“…The environmentally extended input-output analysis is one of the possible approaches of life-cycle analyses (LCA) that measure the direct and indirect environmental impacts, i.e., the impacts from cradle to grave, of a functional unit under consideration [19,20]. Besides the environmentally extended input-output analysis, LCAs can be done with a process-based life-cycle analysis, and these two when combined are referred to as hybrid-analysis [19].…”

Section: Environmentally Extended Input-output Modelmentioning

confidence: 99%

“…The EE I-O method is often referred to as a -top-down‖ method, and it measures the product flows in monetary units [20,21]. Usually the benefits of the EE I-O method are said to be its capability to give an overview of the life-cycle effects of production and consumption of an economy, lack of problems related to system boundaries and truncation errors, and the easiness and repeatability of calculations once the model is developed [19,22].…”

Section: Environmentally Extended Input-output Modelmentioning

confidence: 99%

Greenhouse Gas Implications of Urban Sprawl in the Helsinki Metropolitan Area

2013

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Suburban households living in spacious detached houses and owing multiple cars are often seen as main culprits for negative greenhouse consequences of urban sprawl. Consequently, the effects of sprawl have been mostly studied from the viewpoints of emissions from home energy consumption and private driving. Little attention has been paid to the changes in other consumption. In this paper, urban sprawl is linked to the proliferation of semi-detached and detached housing, described as a low-rise lifestyle, at the expense of apartment house living i.e., high-rise lifestyle. We analyze differences between the low-rise and the high-rise lifestyles and their environmental effects in the Helsinki Metropolitan Area, taking into account all consumption activities. Environmental effects are assessed by combining greenhouse gas intensities from a consumption-based environmentally-extended input-output (EE I-O) model with expenditure data. Then these carbon footprints are further elucidated with regression analysis. We find that low-rise lifestyles causes approximately 14% more emissions than high-rise lifestyles. However, the relative contributions of emissions from different sources, whether direct or indirect, are almost equal for both. Furthermore, when controlling the level of expenditure, the differences between the two lifestyles unexpectedly disappear and in certain cases are even reversed. We believe that our consumption-based approach facilitates the understanding of sprawling lifestyles and offers important insights for sustainable policy-design and urban planning.

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Life Cycle Assessment in the Built Environment

Cited by 175 publications

References 0 publications

Multi-scale life cycle energy analysis of a low-density suburban neighbourhood in Melbourne, Australia

Multi-scale life cycle energy analysis of a low-density suburban neighbourhood in Melbourne, Australia

An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics

Greenhouse Gas Implications of Urban Sprawl in the Helsinki Metropolitan Area

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