Increasing Secondary and Renewable Material Use: A Chance Constrained Modeling Approach To Manage Feedstock Quality Variation

• Published in: Environmental science & technology Vol. 45; no. 9; pp. 4118 - 4126
• Main Authors: Olivetti, Elsa A, Gaustad, Gabrielle G, Field, Frank R, Kirchain, Randolph E
• Format: Journal Article
• Language: English
• Published: Washington, DC American Chemical Society 01.05.2011
• Subjects: Aluminum - chemistry; Animals; Applied sciences; Collagen - chemistry; Exact sciences and technology; Gelatin - chemistry; Global environmental pollution; Manufactured Materials - economics; Models, Theoretical; Pollution; Quality; Raw materials; Recycling; Recycling - economics; Recycling - trends; Renewable resources; Rubber - chemistry; Sustainability Engineering and Green Chemistry; Sustainable development; Sustainable materials; Waste management; Material recovery; Upgrading; Waste reuse; Sustainable management; Recycling; Resource management; Sustainable development; Modeling; Renewable resources
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es103486s

The increased use of secondary (i.e., recycled) and renewable resources will likely be key toward achieving sustainable materials use. Unfortunately, these strategies share a common barrier to economical implementation − increased quality variation compared to their primary and synthetic counterparts. Current deterministic process-planning models overestimate the economic impact of this increased variation. This paper shows that for a range of industries from biomaterials to inorganics, managing variation through a chance-constrained (CC) model enables increased use of such variable raw materials, or heterogeneous feedstocks (hF), over conventional, deterministic models. An abstract, analytical model and a quantitative model applied to an industrial case of aluminum recycling were used to explore the limits and benefits of the CC formulation. The results indicate that the CC solution can reduce cost and increase potential hF use across a broad range of production conditions through raw materials diversification. These benefits increase where the hFs exhibit mean quality performance close to that of the more homogeneous feedstocks (often the primary and synthetic materials) or have large quality variability. In terms of operational context, the relative performance grows as intolerance for batch error increases and as the opportunity to diversify the raw material portfolio increases.