Jan 3, 2017

Applied Technology Council (ATC) 58-2: Integrating Seismic and Environmental Impacts

A Comprehensive Database of Structural and Non-Structural Building Component Repair
In evaluating the life cycle environmental impacts of buildings, the contributions of seismic damage are rarely considered. This project developed and analyzed the largest known environmental impact database of building component seismic damage.  By extending established methods of probabilistic seismic performance evaluation to include environmental impacts, a more comprehensive assessment of a building’s expected seismic performance can be evaluated. To calculate the environmental impacts, data from Carnegie Mellon University’s Green Design Institute’s Economic Input-Output Life Cycle Analysis (LCA) database were connected to previously established repair cost estimate data.  Environmental impacts, including embodied carbon, embodied energy, and other metrics, were calculated for the repair of nearly 800 building components under three or more different seismic damage levels.
The 95% draft of the reports and database to ATC/FEMA are under review for publication and integration into FEMA’s Performance Assessment Calculation Tool (PACT). Expected publication in 2017.
Research Team
Simonen, UW (PI), M. Huang, UW, P. Morris, AECCOM
Aknowledgements
This material is based upon work funded by the Federal Emergency Management Agency and managed by the Applied Technology Council (ATC) through the ATC 58-2 Project, the substance of which is dedicated to the public.  Any opinions, findings, and conclusions or recommendations expressed in the material are those of the authors and do not necessarily reflect the views of the Federal Emergency Management Agency or the Applied Technology Council.
Additional contributions from John Hooper, Anthony Court, Wayne Trusty, Mark Webster and Jon Heinz.  We thank Chris Aicher and Professor Paul Sampson from the Department of Statistics at the University of Washington for their assistance and advisement in the statistical component of this work.  We also thank Ibrahim Almufti, his team at ARUP, and Kristen Strobel, a graduate student at the University of Washington, for their work in providing the data for the case study building as well as H. Scott Matthews at Carnegie Mellon University for his advice regarding the use of their EIO LCA database.

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