This project will create 'hybrid' life cycle models of the environmental implications of construction process activities. Input-output models function by considering a change in economic activity in a primary sector, and estimating the implications in that sector and all other sectors in the supply chain. Further, these models then link with other data (e.g. emissions, energy use) on a sector basis to link primary production with all secondary impacts in the supply chain. However these models are highly aggregate (e.g. there are a small number of construction sectors). Thus the estimates from input-output models may not accurately reflect the specific activities within a particular process. In this project, we will integrate an existing input-output model with process-specific data from existing inventories (e.g. BEES). The data from these various process-based inventory sources will act as substitutes for the estimates that come from the very average and aggregated input-output based models. This should make the overall estimates much better.

There are several broader impacts expected from the research. The construction industry has a significant impact on resource use, environmental emissions, and energy use in the United States. The products of construction activity (e.g. buildings, roads) further contribute to impacts in these areas. By using the model and framework described above, more detailed information about the impacts of various construction process activities will be created. The result of this project will be freely accessible on the Internet to aid in public and private decision making issues related to the implications of construction. For example, someone trying to construct a 'green building' can see estimate of the overall environmental effects of various processes (e.g. transportation of materials to the site) and be more informed about which of these processes has the smallest environmental burden. In the longer term, such results could better inform and define the ways in which green building/construction projects are rated via a better understanding of the relative impacts of various processes. Finally, the model will be widely disseminated through public availability on the web, similar to the fashion in which the EIO-LCA model is used.

Agency
National Science Foundation (NSF)
Institute
Division of Civil, Mechanical, and Manufacturing Innovation (CMMI)
Application #
0833803
Program Officer
Dennis Wenger
Project Start
Project End
Budget Start
2007-08-31
Budget End
2009-08-31
Support Year
Fiscal Year
2008
Total Cost
$51,546
Indirect Cost
Name
University of Florida
Department
Type
DUNS #
City
Gainesville
State
FL
Country
United States
Zip Code
32611