(620e) Integrating Market Effects into Sustainable Process Design – Application to Urea Production

Lee, K. - Presenter, The Ohio State University
Ghosh, T., The Ohio State University
Bakshi, B., Ohio State University
Conventional engineering analysis and design approaches try to identify and develop production systems that have high efficiency, low cost, and low environmental impacts. The conventional approaches assume those production systems can be adopted by the market due to the above technological advances. However, the market does not always choose the “best” technology. The advanced technology may not be adopted as much as industry may like or assume because of market constraints. For example, the production of a key resource for the advanced technology may not be enough to satisfy the market demand. Other economic factors, such as labor, capital, land area, and regulations, along with competing alternatives may limit the use of the technology as well. In that case, the market selects among multiple technologies to satisfy its demand. In this sense, there are some gaps between engineering decisions based on technological excellence and market decisions based on the economy and human preferences.

The Rectangular Choice-of-Technology (RCOT) framework has been developed to account for those market constraints and multiple technology uses in analyzing economic systems [1]. In the traditional economic input-output model, economic transaction matrix that contain commodity exchanges between economic sectors is the square matrix. In the RCOT model, the transaction matrix becomes the rectangular matrix with additional columns. The additional columns represent multiple technologies that produce the same product. Also, by constraining the maximum available amounts of economic factors, multiple technologies are chosen together to satisfy the market demand in case the cheapest option is not able to satisfy the demand due to the constraints. The RCOT framework has also been applied to process-based life cycle assessment (LCA) model in a value chain scale [2]. However, none of the previous studies applies the RCOT framework to multiscale models and solves engineering design problems.

In this work, the RCOT framework is applied to a multiscale model based on the Process-to-Planet (P2P) framework [3] to account for the resource availability and environmental regulations in designing process engineering models. A methodology for the RCOT-P2P model and its toy example are described and the RCOT-P2P model is applied to the urea manufacturing process. The urea P2P model has been developed by including inputs from value chain and economy scales to the urea manufacturing engineering model. Those inputs include ammonia and carbon dioxide resources and electricity and natural gas uses. As for multiple technology options, different technologies that produce those inputs are considered. Specifically, different fuel and boiler types for electricity generation, natural gas extraction options between conventional NG and shale gas, different hydrogen sources for ammonia manufacturing, different sources of carbon dioxide are considered as multiple technology choices. The available amounts of relevant economic factors are constrained in limiting each of those technology uses. Also, to account for environmental regulations, environmental interventions, such as emissions and use of natural resources, are constrained as well [2].

Since this work reflects the market effect by considering economic factors in choosing technologies, this would inform better insights and understanding on how technologies are adopted in certain economic conditions and how they need to be developed. In particular, this work could be beneficial for modeling emerging technologies that need to substitute the conventional one, because emerging technologies will replace the conventional one gradually. Also, since the availability of natural resources can be considered as constraints, this work could be useful for the regional analysis of specific areas where the amounts of resources are limited and for solving spatial optimization problems.


[1] Duchin, F. & Levine, S. H. Sectors may use multiple technologies simultaneously: The rectangular choice-of-technology model with binding factor constraints. Econ. Syst. Res. 23, 281–302 (2011).

[2] Kätelhön, A., Bardow, A. & Suh, S. Stochastic Technology Choice Model for Consequential Life Cycle Assessment. Environ. Sci. Technol. 50, 12575–12583 (2016).

[3] Hanes, R. J. & Bakshi, B. R. Process to planet: A multiscale modeling framework toward sustainable engineering. AIChE J. 61, 3332–3352 (2015).