International Industrial Ecology Day 2021

How can we take advantage of industry data sources to assist Industrial Ecology Community to better define materials and building assemblies for use in MFA and MSA studies?

Since construction practices are regionally driven, it is difficult to describe patterns of resource consumption. When conducting research for material flow analysis (MFA) and material stock analysis (MSA) in the built environment, there is a dearth of data to describe expected building material composition by typologies. We investigated multiple industry data sources to describe potential building material flows (Marcellus-Zamora, Gallagher et al. 2020) by accessing completed USGBC (LEED) project database and partnered with industry for their data. It is ideal for IE Researchers to work with industry to access building data to inform MFA and MSA studies; thus, providing directly sourced data. One option, RS Means, is an industry tool referenced for estimating costs in construction projects throughout North America. The data are obtainable in several ways: square foot models, assembly and unit material types to calculate regional construction cost defined by building typologies. Adopting this methodology would greatly benefit IE researchers to streamline data collection (categorizing data by magnitude, area, or volume) and collect for a central database usable in MFA and MSA models. Construction estimators can input building properties in square foot cost models and output expected materials and costs related to the building use. In previous work, building stock (MSA) were analyzed at the block scale for six majority land use types in Philadelphia (Marcellus-Zamora, Gallagher et al. 2016). We sourced City of Philadelphia building database and defined the study with these parameters. There is an opportunity to develop and model data for MFA and MSA studies populated with industry sources thereby engaging collaboration and enabling more avenues for data collection. If IE researchers and construction industries are communicating with common metrics this may enable a better connection between industry data and IE research data informing the IE community thus contributing to a more circular economy.

Author(s)

Name Affiliation
Kimberlee Zamora Thomas Jefferson University

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