Date of Award

2020

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Civil Engineering (PhD)

Administrative Home Department

Department of Civil and Environmental Engineering

Advisor 1

Amlan Mukherjee

Committee Member 1

Heather Dylla

Committee Member 2

David Shonnard

Committee Member 3

Zhanping You

Committee Member 4

Jacob Hiller

Committee Member 5

John Harvey

Committee Member 6

Richard Willis

Committee Member 7

Ezra Kahn

Abstract

The objective of this dissertation is to develop Life Cycle Information Models (LCIMs) to promote consistent and credible communication of potential environmental impacts quantified through Life-Cycle Assessment (LCA) methodology. The introduction of Life Cycle Information Models (LCIMs) will shift the focus of pavement LCA stakeholders to collect reliable foreground data and adapt to consistent background data present within LCIMs. LCA methodology requires significant Life Cycle Inventory (LCI) data to model real world systems and quantify potential environmental impacts. The lack of guidance in ISO standards on consistently compiling LCI data and defining protocols for modeling lowers the reliability of LCA outcomes. In addition, LCA outcomes are communicated as point estimates despite the variations associated with input data. These limitations provided two motivations for this dissertation. The first motivation is to develop an information modeling approach to support the formal specification of relationships between pavement LCA flows and processes, while mapping them to a consistent set of background LCI and foreground process parameters. The second motivation is to develop the margins of error within LCA outcomes by propagating different types of uncertainties. An illustration of the discussed methodology is provided for the case of Hot-Mix Asphalt (HMA) mixtures containing varying amounts of Reclaimed Asphalt Pavement (RAP) and Recycled Asphalt Shingles (RAS). LCIMs serve as a building block for a complete LCA and formalizing the underlying model and upstream datasets. This builds trust among pavement LCA stakeholders by promoting the use of consistent underlying relationships between unit product systems, processes, and flows within pavement LCA system boundary and mapping them to consistent, transparent public background datasets. Pavement LCA stakeholders are empowered to develop context-specific LCA outcomes using LCIMs and can reliably incorporate these outcomes within decision-making by highlighting the margins of error associated with the results. The methodology discussed in this dissertation is timely with emerging legislations such as the Buy Clean Act (2017) in California that requires highway construction contractors to produce LCA based Environmental Product Declarations (EPDs), at the point of installation, for a list of all eligible construction materials.

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