(326g) A Pseudo-Equilibrium Approach for Process-to-Planet Design Under Environmental Tax Policies

Environmental tax policies are intended to increase the prices of emissions-intensive products relative to less polluting products, thereby driving demand towards the less polluting products and reducing the environmental impact of the economy as a whole. Such a policy will affect decisions made by consumers within manufacturing industries as well as by consumers of final demand, and several companies are already accounting for a carbon price in internal decision-making. It is therefore of interest to determine how an economically optimal engineering system design will change under an environmental tax policy, and how changes in the design will in turn affect emissions produced by the system and its life cycle. Knowledge about this economic-engineering-environmental interaction will provide insight into the true effects of environmental taxes and can provide guidance as to what kind of environmental tax policy - a tax on fuels according to carbon content, on carbon dioxide and greenhouse gas emissions, or on energy use - and at what magnitude, is most effective at reducing environmental impacts at the economy scale.

Current studies on the effect of environmental tax policies on engineering systems model environmental taxes as an additional cost of emitting. [1, 2] Optimizing for process or supply chain economics under a tax of sufficient magnitude forces the system to a new optimal design. However, such methods implicitly assume that the tax is applied only to the system of interest. In reality, tax policies are implemented at a macro-economic scale and the effects of the policy on an engineering system depend not only on the nature of the policy itself but also on the response of the economy and of consumers to the policy. An environmental tax will thus affect the system indirectly, through changes in the prices of chemical feedstocks, fuels and other inputs, as well as directly through the additional cost of emitting. In general, sustainable engineering methods do not extend to the economy scale at which tax policies are implemented. Interactions between economic and engineering systems are rarely modeled explicitly, and in particular the top-down effects of an economy scale environmental tax policy on smaller scale engineering systems are not captured.

This work develops an approach for design and optimization under environmental tax policies that accounts for the top-down effects of a policy on the engineering system of interest. The proposed approach uses the process-to-planet (P2P) multi-scale modeling framework [3] that integrates fundamental engineering models at the equipment scale, empirical value chain models at the regional scale and a national scale economic model. Currently, the P2P framework relies on an environmentally-extended input-output (EEIO) model at the national scale, which treats all prices in the economy as fixed. Some aspects of market equilibrium are incorporated into the P2P modeling framework with a pseudo-equilibrium procedure that uses price elasticity of demand information to model the short-term effects of an environmental tax policy at the economy scale. [4] The effects are in the short term only, as they include changes in prices throughout the economy (monetary flows) rather than changes in sectoral production technologies (physical flows). The amount each sector is taxed is calculated from physical data on the amount of carbon dioxide emissions generated by each sector, and this tax is modeled as an increase in value added. Following the increase in value added, the Leontief cost-push model is applied to calculate a new set of commodity prices, from which the emissions factors (kg carbon dioxide/dollar sector output) for each sector in the economy are updated. Price elasticity of demand information for final consumers is used to calculate the change in final demand and in total sector output. The result of the pseudo-equilibrium procedure is a post-tax EEIO model of the economy after the tax policy is implemented, including the updated sectoral emissions factors. This post-tax EEIO model is then used in the P2P modeling framework in place of the original, pre-tax EEIO model. Changes in commodity prices are propagated to the equipment (plant) scale of the P2P model, thereby influencing the economic objective function through the cost of inputs. The life cycle emissions are also affected by the tax policy through the change in sectoral emissions factors and any changes in the level of equipment scale inputs.

Corn ethanol is widely viewed as a less polluting alternative to fossil transportation fuels, but the production of ethanol relies heavily on fossil fuels throughout its life cycle: in the corn farming stage, for transportation of corn, other inputs, and the final ethanol product, and in processing the corn to ethanol. An environmental tax policy, such as an emissions tax on carbon dioxide, will therefore affect both the economic feasibility and the environmental performance of corn ethanol plants. To demonstrate the application of the proposed P2P pseudo-equilibrium approach, a dry grind corn ethanol plant [5, 6] is optimized under three tax scenarios: no emissions tax, an equipment scale tax on carbon dioxide emissions and an economy scale tax on carbon dioxide emissions.

In the no tax or base case scenario, there is no payment for carbon dioxide emissions and all input and feedstock prices are at their baseline levels. The plant design is optimized for maximum profits, and emissions from the plant and from the life cycle (equipment, value chain and economy) are calculated. The second scenario, in which a carbon dioxide tax is imposed at the equipment scale, is the conventional method for design and optimization under an environmental tax policy. In this scenario, the policy is modeled by imposing an additional cost proportional to the quantity of carbon dioxide emitted at the equipment scale only; input and feedstock prices remain at their baseline levels. The plant design is optimized for maximum profits, using the economic objective function that represents the equipment scale tax policy, and the plant and life cycle emissions are calculated for this new plant design. It is expected that in this scenario, the plant scale emissions will decrease relative to the base case, but the life cycle emissions will increase indicating that the production of emissions is being shifted to the life cycle.

The final scenario is the P2P pseudo-equilibrium approach, in which the emissions tax is imposed at the economy scale and creates indirect changes in the plant's economic objective function through changes in input prices. The tax also directly affects the objective function via the cost of emitting carbon dioxide, which is captured under the conventional method. Optimizing for maximum profits with this new economic objective function will produce a third plant design that is expected to have higher production costs and lower carbon dioxide emissions at both the equipment and the life cycle scales, relative to the base case and conventional method plant designs. Finally, the conventional method design will be evaluated using the post-tax P2P model and economic objective function. The purpose of this evaluation is to demonstrate that neglecting the effects of tax policies at the economy scale leads to an economically sub-optimal plant design and higher life cycle emissions.

[1] Saif Benjaafar, Yanzhi Li, and Mark Daskin. Carbon footprint and the management of supply chains: Insights from simple models. Automation Science and Engineering, IEEE Transactions on, 10(1):99–116, 2013.

[2] Hamid Ghanbari, Henrik Sax ́en, and Ignacio E Grossmann. Optimal design and operation of a steel plant integrated with a polygeneration system. AIChE Journal, 59(10):3659–3670, 2013.

[3] Rebecca J. Hanes and Bhavik R. Bakshi. From process to planet: A multiscale modeling framework for sustainable engineering applications. AIChE Journal, 2015. Submitted.

[4] Jun-Ki Choi, Bhavik R Bakshi, and Timothy Haab. Effects of a carbon price in the US on economic sectors, resource use, and emissions: An input–output approach. Energy Policy, 38(7):3527–3536, 2010.

[5] Ramkumar Karuppiah, Andreas Peschel, Ignacio E Grossmann, Mariano Martin, Wade Martinson, and Luca Zullo. Energy optimization for the design of corn-based ethanol plants. AIChE Journal, 54(6):1499–1525, 2008.

[6] Rebecca J. Hanes and Bhavik R. Bakshi. Sustainable process design by the process to planet framework. AIChE Journal, 2015. Submitted.