Quantitative approaches in life cycle assessment—part 2—multivariate correlation and regression analysis
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This study examines the use of inferential statistics, specifically multivariate correlation and regression, as a means of interpreting LCA data. It is believed that these methods provide additional context in understanding data and results, and may serve as a way to present the uncertain results that are inherent to LCA.
Nine building envelope combinations were analyzed according to five service life models (N = 45). Three environmental indicators were used: global warming potential, atmospheric ecotoxicity, and atmospheric acidification from the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts assessment method. Multivariate correlation was performed using nine variables, including cumulative life cycle impact, major replacement, major replacement (frequency), minor replacement, major repairs, minor repairs, inspections 1 and 2, and total transportation (N = 45, 405 data points). The same data set was used for the regression analysis, although the variables were limited to major replacement, minor replacement, major repair, and minor repair (N = 45, 225 data points). SPSS software was used for all statistical calculations.
Results and discussion
Multivariate correlation analysis showed strong, statistically significant correlations between cumulative life cycle impact and major replacement across all environmental indicators. Similarly, the regression analysis showed strong R 2 values between cumulative life cycle impact and major replacement, such that the influence of all other variables was considerably diminished.
The use of inferential statistics provides useful information with respect to the strength and statistical significance of correlations between variables as in multivariate correlation, and allows for predictive capacity of impact, as demonstrated through regression analysis. Further studies should be conducted to confirm the added value of these analytical tools.
KeywordsBuilding materials Construction Inferential statistics Life cycle assessment Uncertainty
- Dell‘Isola AJ, Stephen JK (2003) Life Cycle Costing for Facilities: Economic Analysis for Owners and Professionals in Planning, Programming, and Real Estate Development: Designing, Specifying, and Construction: Maintenance, Operations, and Procurement. Reed Construction Data, Kingston, MAGoogle Scholar
- Fillie C, Lane S, Parham A, Sullivan J, Wahl J (2004) Analysis for gate-to-market effects for building materials in the Orlando, FL, Region. Report prepared for the Athena Sustainable Materials Institute (unpublished). August 2004Google Scholar
- IBM Corp (2010) Released 2012. IBM SPSS statistics for windows, version 21.0. IBM Corp, ArmonkGoogle Scholar
- International Organization for Standardization (2006) Environmental management—life cycle assessment—principles and framework. ISO 14040:2006(E)Google Scholar
- Meyers LS, Gamst G, Guarino AJ (2006) Applied multivariate research. Sage Publications, Inc., Thousand OaksGoogle Scholar
- Morrison Hershfield in collaboration with the Athena Sustainable Materials Institute (2002) Maintenance, Repair and Replacement Effects for Building Envelope Materials. Prepared by Morrison Hershfield for Athena Sustainable Materials Institute, Merrickville, Ontario, Canada, January 2002Google Scholar
- Neely ES, Neathammer RD, Stirn JR, Winkler RP (1991) Maintenance task data base for buildings: architectural systems. United States Army Corps of Engineers. USACERL Special Report P-91/23Google Scholar
- Noori M, Tatari O, Nam B, Golestani B, Greene J (2014) A stochastic optimization approach for the selection of reflective cracking mitigation techniques. Transport Res 69:367–378Google Scholar
- RS Means (1996) Cost planning and Estimating for Facility Maintenance. Rs means, Kingston, MaGoogle Scholar
- Sustainable Buildings Industry Council (SBIC) (2005) Energy-10 software. The Building Performance Group. (1999). ―BPG Building Fabric Component Life Manual. E & FN Spon. London, EnglandGoogle Scholar
- USEPA (United States Environmental Protection Agency) (1989) Exposure factors handbook. Report EPA/600/8-89/043. US EPA, Washington, DCGoogle Scholar