A hybrid Data Quality Indicator and statistical method for improving uncertainty analysis in LCA of a small off-grid wind turbine

Ozoemena, Matthew, Cheung, Wai Ming, Hasan, Reaz and Hackney, Philip (2014) A hybrid Data Quality Indicator and statistical method for improving uncertainty analysis in LCA of a small off-grid wind turbine. In: ARCOM Doctoral Workshop on Sustainable Urban Retrofit and Technologies, 19 June 2014, London South Bank University.

This is the latest version of this item.

[img]
Preview
Text
arcom-paper.pdf - Accepted Version

Download (609kB) | Preview

Abstract

In Life Cycle Assessment (LCA) uncertainty analysis has been recommended when choosing sustainable products. Both Data Quality Indicator and statistical methods are used to estimate data uncertainties in LCA. Neither of these alone is however adequate enough to address the challenges in LCA of a complex system due to data scarcity and large quantity of material types. This paper applies a hybrid stochastic method, combining the statistical and Data Quality Indicator methods by using a pre-screening process based on Monte Carlo rank-order correlation sensitivity analysis, to improve the uncertainty estimate in wind turbine LCA with data limitations. In the presented case study which performed the stochastic estimation of CO2 emissions, similar results from the hybrid method were observed compared to the pure Data Quality Indicator method. Summarily, the presented hybrid method can be used as a possible alternative for evaluating deterministic LCA results like CO2 emissions, when results that are more reliable are desired with limited availability of data.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: CO2 emission, data quality indicator, lca, statistical, Monte Carlo, simulation
Subjects: H100 General Engineering
H300 Mechanical Engineering
H700 Production and Manufacturing Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Related URLs:
Depositing User: Wai Ming Cheung
Date Deposited: 23 Jun 2014 08:25
Last Modified: 17 Dec 2023 15:19
URI: https://nrl.northumbria.ac.uk/id/eprint/16687

Available Versions of this Item

  • A hybrid Data Quality Indicator and statistical method for improving uncertainty analysis in LCA of a small off-grid wind turbine. (deposited 23 Jun 2014 08:25) [Currently Displayed]

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics