Life cycle inventory regionalization and uncertainty characterization: A multilevel modeling approach

Dai, Tao; Fleischer, Amy S.; Lee, Ross; Wemhoff, Aaron P.

doi:10.1016/j.jclepro.2019.118459

Cited by 16 publications

(7 citation statements)

References 45 publications

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“…Another approach to address the uncertainties that are associated with WBLCA developments, especially the challenge on LCA database and impact method variances, is to conduct uncertainty D r a f t analysis. There are two main directions to conduct uncertainty analysis: The first one is to conduct sensitivity analysis, and the second one is to conduct uncertainty assessment through mathematical methods (Dai et al 2020;Harter et al 2020). Sensitivity analysis is to monitor the changes of total WBLCA results while revising single or limited LCA input parameters by certain percentage (Morales et al 2020).…”

Section: Approaches To Reduce Uncertainty From Lca Database and Methodsmentioning

confidence: 99%

Exploring the current challenges and emerging approaches in whole building life cycle assessment

2022

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The environmental impacts of building stock has received significant attention as buildings release one third of total greenhouse gas emissions. Whole-building life cycle assessment (WBLCA) has become a trend to address this limitation by ensuring best environmental performance of a building However, the current WBLCA development faces many challenges which makes it hard to create reliable and comparable results. The study aims to conduct a critical literature review to summarize the current challenges on WBLCA applications, and the emerging approaches that might address these challenges. Three main challenges are listed: variances on goal and scope definition, building structure complexity, and varieties on LCA database and methods. Emerging approaches are also presented to address these challenges including integration of BIM into WBLCA and EPD applications in impact assessments. Findings of this study could support researchers and decision makers with the most popular approaches to conduct WBLCA and achieve reliable outputs.

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Section: Approaches To Reduce Uncertainty From Lca Database and Methodsmentioning

confidence: 99%

Exploring the current challenges and emerging approaches in whole building life cycle assessment

2022

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“…However, such methods still rely on data compiled via the semi-quantitative pedigree approach that depends in part on subjective evaluations to determine temporal and geographic representativeness. Dai et al introduced multilevel modeling regression to address the temporal and geographical variations simultaneously and proposed to use the prediction interval for full quantification of uncertainty, but their model did not address proxy data usage …”

Section: Introductionmentioning

confidence: 99%

“…Dai et al introduced multilevel modeling regression to address the temporal and geographical variations simultaneously and proposed to use the prediction interval for full quantification of uncertainty, but their model did not address proxy data usage. 31 In this study, we introduce a framework to obtain the best-fit secondary data and to characterize the associated uncertainty based on the prediction of a Gaussian process regression (GPR) model. GPR, as a powerful machine learning regression algorithm, can utilize information from small data sets and obtain out-of-sample predictions with high accuracy.…”

Section: Introductionmentioning

confidence: 99%

Gaussian Process Regression as a Replicable, Streamlined Approach to Inventory and Uncertainty Analysis in Life Cycle Assessment

Dai

Jordaan

Wemhoff

2022

Environ. Sci. Technol.

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Life cycle assessment plays a critical role in quantifying environmental impacts, but its credibility remains challenged when data and uncertainty analysis are lacking. In this study, we propose a data compilation framework to address these two issues. The framework first quantifies the correlations of production activities among existing data in temporal, geographical, and taxonomic dimensions. The framework then introduces covariance functions to convert these correlations to a similarity matrix, and the Gaussian process regression model is adopted to predict new data based on these covariance functions. The associated uncertainty is automatically characterized using the posterior distribution of predictions. The framework is demonstrated on the nitrogen fertilizer application rate for food productionan activity recognized for its environmental burdenwith results capable of reflecting temporal and geographical variations. By introducing the concept of phylogenetic distance as a correlation of taxonomy, the framework provides a quantitative basis for predictions in a proxy data usage scenario. The framework can be used in developing temporally and regionally representative life cycle inventories and databases and can facilitate consistent uncertainty quantification in future life cycle assessment methodologies.

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“…In this regard, under the life cycle thinking focus, life cycle assessment (LCA) is accepted as a powerful approach for the holistic assessment of the environmental impacts of anthropogenic activities that provides valuable environmental indicators to policymakers and other economic agents (Gava et al, 2020;Sala et al, 2021a). LCA is preferred over other environmental tools because it aims to assess products and considers all the environmental burdens caused by production and consumption systems (Dai et al, 2020;Roches et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…In fact, different researchers consider LCI as the most complex step when developing an LCA (e.g. Dai et al, 2020;Kuka et al, 2020;Yang, 2016). A dilemma is, thus, presented between working with global and generic data (less effort needed to obtain the data but more inaccuracy in the results) versus site-specific data (greater effort to obtain the data but greater accuracy in the results), which, in turn, determines how data are collected (Meron et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Developing indicators to assess agricultural sustainability. Application to the Spanish context

Sinisterra Solis

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Life cycle inventory regionalization and uncertainty characterization: A multilevel modeling approach

Cited by 16 publications

References 45 publications

Exploring the current challenges and emerging approaches in whole building life cycle assessment

Exploring the current challenges and emerging approaches in whole building life cycle assessment

Gaussian Process Regression as a Replicable, Streamlined Approach to Inventory and Uncertainty Analysis in Life Cycle Assessment

Developing indicators to assess agricultural sustainability. Application to the Spanish context

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