Lessons Learned in Developing an Environmental Product Declaration Program for the Asphalt Industry in North America

The objective of this paper is to report the technical and organizational challenges involved in the development of the North American Environmental Product Declaration program for asphalt mixtures. Developing a Life Cycle Assessment (LCA) for asphalt mixtures presents the challenge of coordinating consistent assumptions across industries and stakeholders, and requiring a harmonized decision-making process that accounts for the impacts of materials across the supply and value chain. While, the methods of LCA are rational and well defined, the decisions defining the various assumptions are often arrived at through a negotiation process shaped by stakeholder relationships and priorities. There is much discussion in the literature regarding the technical challenges of conducting an LCA involving choice of system boundary, functional unit, and allocation procedures used for co-products and recycled products. However, the formulation process of these technical questions within the context of stakeholder biases and heuristics are seldom explicitly discussed, even though they play an important role in how the technical challenges are resolved. Hence, the paper explores how differences in stakeholder priorities and perspectives, in the pavement construction industry, directly shape the Product Category Rules (PCR) defining the program by drawing attention to specific LCA related technical questions and highlights how the solutions were negotiated. The primary challenge identified is how to ensure technical rigor of the underlying LCA, while recognizing the interests of the stakeholders and ensuring the delivery of a program that is effective. The paper discusses how technical issues regarding system boundary choice, data use and allocation presented challenges for the PCR Development Working Group accounting for different stakeholder interests. Within this context the paper will highlight the developed PCR and present relevant results from the underlying LCA.