(394e) Accounting for Spatial Variability of Ecosystem Services in Sustainable Supply Chain Design

Supply chain design problems determine environmental impact by performing life cycle assessment as an addendum to the framework. Moreover, these frameworks never consider the limits of ecosystems to provide environmental impact remediating services or supply resources. Not including ecosystems results in these designs eventually exceeding nature’s capacity resulting in ecological degradation. Previous work (1) has demonstrated the benefits of including ecosystems in process design. The key benefits are that designs with ecosystems can be ecologically and economically superior to conventional techno-centric designs. However, the spatial variability of ecosystems has not been considered in these studies.

Objective:

In this research work, spatial variability of ecosystem services is considered while designing supply chains as well as manufacturing processes. With a goal to perform sustainable process design of any manufacturing process as well as determine upstream material and service pathways to that process, we develop a matrix based mathematical framework that uses upstream process based life cycle network as a platform for supply chain design The framework also allows the incorporation of ecosystem services as unit operations during optimization as a measure of environmental sustainability and designing of ecological systems.

Background:

Sustainable Process Design (SPD) is used to design manufacturing processes while accounting for environmental impacts as an optimization objective along with conventional objectives such as profit or production quantity. (2) Process to Planet (P2P) framework is applied to perform SPD which calculates environmental impact using a hybrid approach to life cycle assessment. (3)

Techno-Ecological Synergy: Techno-Ecological Synergy(TES) framework (4) considers supply of ecosystem services while satisfying the environmental sustainability condition of maintaining that demand of ecosystem services by technological systems do not exceed the capacity of ecosystems to provide the same.

Approach:

This research combines process design, supply chain design (SPD), technology choices, hybrid life cycle assessment (LCA) as well as incorporation of ecosystem services in a comprehensive optimization model. It is achieved by development of the P2P-TES framework that combined the sustainable process design and hybrid LCA characteristics of P2P with the ecosystem service integration of TES.

Results:

We perform a sustainable supply chain design study to determine the distribution of biorefineries within a spatial region, design the bioethanol conversion process and simultaneously determine upstream raw material network while considering tradeoff between food – energy demands. Farming practice choice of till versus no till was explored as well as effect of ecosystem services such as wetlands for mitigation of N runoff. Other ecosystem services being explored are food provisioning, C sequestration and air quality regulation by forests, etc. For this presentation, we apply this optimization framework to the watershed region of Maumee river in Northern Ohio to analyze spatial distribution of biorefineries and corn farming to reduce P output – a leading cause for eutrophication in Lake Erie.

References:

(1) Gopalakrishnan, Varsha, Bhavik R. Bakshi, and Guy Ziv. "Assessing the capacity of local ecosystems to meet industrial demand for ecosystem services." AIChE Journal 62.9 (2016): 3319-3333.

(2) Bakshi, B. R., “Methods and tools for sustainable process design, “Current Opinion in Chemical Engineering, vol. 6, pp. 69–74, 2014. [Online]. Available: http://linkinghub.elsevier.com/retrieve/pii/S2211339814000768 \\\vspace*{0.3cm}

(3) Hanes, Rebecca J., and Bhavik R. Bakshi. "Sustainable process design by the process to planet framework." AIChE Journal 61.10 (2015): 3320-3331.

(4) Bakshi, Bhavik R., Guy Ziv, and Michael D. Lepech. "Techno-ecological synergy: A framework for sustainable engineering." Environmental Science and Technology Letters 49.3 (2015): 1752-1760.

(5) Nurjanni, K.P., Carvalho, M.S. and Costa, L., 2017. Green supply chain design: A mathematical modeling approach based on a multi-objective optimization model. International Journal of Production Economics, 183, pp.421-432.