473748 Process to Planet Framework for Sustainable Design: Systematic Approach for Developing a Multiscale Model and for Multiobjective Optimization

Wednesday, November 16, 2016: 8:30 AM
Union Square 13 (Hilton San Francisco Union Square)
Tapajyoti Ghosh and Bhavik R. Bakshi, William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH

Over the last decade, sustainable process design (SPD) research has utilized life cycle assessment(LCA) methods to incorporate an environmental dimension in process systems engineering(PSE). Conventional SPD involves a “bottom up approach” of modeling the system of interest at a smaller scale with detailed process specific fundamental engineering models, while the upstream life cycle of the product is modeled at a larger scale using process based LCA. System boundary selection is a significant challenge for process LCA due to infinite nature of the upstream life cycle network for any process [1]. Process based LCA can lead to significant truncation errors in life cycle resource consumption and emissions, leaving a wide margin for shifting of impacts across narrow system boundaries and leading to illusive optimal design solutions that may in fact be inferior due to incomplete life cycle information [2]. Hybrid LCA(HLCA) methods aim to address the boundary selection problem by combining process level life cycle inventories with environmentally extended input-output analysis(EEIO), which allows for a significant part of the product life cycle to be included in the assessment. The Process to Planet (P2P) framework [3] was developed by introducing the concept of integrated hybrid LCA [4] to SPD. Detailed engineering models of the primary process being designed and other key processes in the supply chain are integrated within a macroeconomic system represented by economic input-output (EIO) model. This ensures solution of process design problems while reducing chances of environmental impacts being neglected due to incomplete life cycle inventories. While bridging the knowledge gap between PSE and LCA, the P2P framework not only improves upon the life cycle assessment component of SPD, but also addresses a major weakness in Hybrid LCA. HLCA is limited to the impact assessment stage of life cycle assessment. Very few studies have dealt with the fourth and final stage of LCA, improvement analysis. This situation is lamentable because inventory scope and impact analysis provide little benefit if not followed by recommendations and decisions that should be adopted to reduce environmental burden. The P2P framework can be visualized as an extension of HLCA method where it enables the incorporation of design variables through process design and allows optimization of the system to improve its environmental footprint. It was successfully demonstrated by application to a corn based ethanol production plant and highly insightful results were obtained that proved the efficacy of the framework [2].

This presentation proposes extensions and modifications that address some of the inadequacies that are inherent in the original P2P framework. While strictly applied to P2P, these extensions can be extrapolated to answer challenges that exist in broad areas of literature, like HLCA. The selection of significant processes that are modeled at the process based life cycle scale and the insignificant processes that are studied at the economy scale is arbitrary. In other words, delineation of the boundary between the different scales of the P2P framework was a subjective task. Previously, this was done based on data availability, accuracy and detail requirements and the complexity of the overall problem which is proportional to the solving time [5,6]. The problem was first mentioned and some methods were proposed for addressing it in a paper by Suh [7]. Lenzen proposed Structural Path Analysis (SPA) involving the decomposition of the Leontief Inverse for addressing this problem [8]. Treloar also used this method to study energy use of individual residential buildings in Australia [9,10]. Lave et al. [11] and Lenzen [12] used SPA to quantify the truncation errors in process-based LCA. A path exchange method using SPA was also developed as an alternative to the method of combining process LCA and IO LCA within integrated hybrid LCA as proposed by Suh. We intend to address this knowledge gap by proposing a path analysis algorithm where the P2P framework superstructure model generation is guided by a hierarchical structural path decomposition method which determines the coverage of the different scales. It is one of the first applications of SPA for solving the boundary selection problem involving the distribution of different upstream processes between multiple scales.

A large number of studies have dealt with multi objective optimization in process design and energy systems involving environmental and economic impacts. A comprehensive list of such literature can be found in Diwekar et al.[13] Reviewing these articles, it becomes apparent that it is necessary to simultaneously work towards both economic profitability and environmental sustainability of the system. Previously, the P2P framework focused only on the environmental dimension of process design. In this work, we propose a multi objective optimization problem, involving the trade-off between an economic objective and an environmental objective function. The novelty in this addendum is that it makes the P2P framework more fruitful for designing any generic process while exercising control over both the economic and environmental scope.

Preliminary results have provided insightful views on the application of SPA algorithm for model generation as well as exposed existing deficiencies to work on. While SPA is successful in mapping the upstream networks of the process to be designed and calculate their contributions to the entire life cycle, the quantification of the quality of the generated model still needs to be addressed. For example, considering two scenarios where an upstream sector is modeled at the IO model scale and process LCA scale respectively, we need to develop parameters that can quantitatively compare between the two cases and rank them objectively. As of now, subjective decisions are being used to build the model, but we intend to develop an algorithm based on error analysis or uncertainty information to determine the model quality. Multiobjective optimization solutions demonstrated that, highly erroneous optimal solutions and counter intuitive results are obtained from practicing conventional SPD approach rather than P2P. In addition to this, it was observed that there is a 59% chance of choosing an inferior solution over the optimal solution when solving the design problem using conventional SPD.


[1] Sangwon Suh. Functions, commodities and environmental impacts in an ecological economic model. 48:451-467, 2004.

[2] Rebecca J Hanes and Bhavik R Bakshi. Sustainable process design by the process to planet framework. AIChE Journal, 61(10):3320-3331, 2015.

[3] Rebecca J Hanes and Bhavik R Bakshi. Process to planet: A multiscale modeling framework toward sustainable engineering. AIChE Journal, 61(10):3332-3352, 2015.

[4] Sangwon Suh and Shinichiro Nakamura. Five years in the area of input-output and hybrid lca. The international journal of life cycle assessment, 12(6):351-352, 2007.

[5] H Hondo and S Sakai. Preliminary life cycle inventory analysis (pre-lci) using an economic input-output table. In The Fourth International Conference on EcoBalance, Tsukuba, Japan, pages 181-4, 2000.

[6] G Norris. Selecting and evaluating boundaries for life cycle assessment using economic input-output analysis. In Proceedings from the SETAC 17th Annual Meeting, Washington, DC, pages 17-21, 1996.

[7] Sangwon Suh, Manfred Lenzen, Graham J Treloar, Hiroki Hondo, Arpad Horvath, Gjalt Huppes, Olivier Jolliet, Uwe Klann, Wolfram Krewitt, Yuichi Moriguchi, et al. System boundary selection in life-cycle inventories using hybrid approaches. Environmental Science & Technology, 38(3):657-664, 2004.

[8] Manfred Lenzen. A guide for compiling inventories in hybrid life-cycle assessments: some australian results. Journal of Cleaner Production, 10(6):545-572, 2002.

[9] Graham J Treloar. Extracting embodied energy paths from input-output tables: to-wards an input-output-based hybrid energy analysis method. Economic Systems Re-search, 9(4):375-391, 1997.

[10] GJ Treloar, PED Love, OO Faniran, and U Iyer-Raniga. A hybrid life cycle assessment method for construction. Construction Management & Economics, 18(1):5-9, 2000.

[11] Lester B Lave. Using input-output analysis to estimate economy-wide discharges. Environmental Science & Technology, 29(9):420A-426A, 1995.

[12] Manfred Lenzen. Errors in conventional and input-output based lifecycle inventories. Journal of Industrial Ecology, 4(4):127-148, 2000.

[13] Urmila Diwekar and Yogendra Shastri. Design for environment: a state-of-the-art re-view. Clean Technologies and Environmental Policy, 13(2):227-240, 2011.

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See more of this Session: Advances in Life Cycle Optimization for Process Development
See more of this Group/Topical: Environmental Division