(375p) Optimal Design and Planning of Integrated Bioethanol-Sugar Supply Chains with Economic and Environmental Concerns. A Case Study of the Sugar Cane Industry in Argentina

Authors: 
Kostin, A. - Presenter, Universitat Rovira i Virgili
Guillén-Gosálbez, G. - Presenter, University Rovira i Virgili
Mele, F. D. - Presenter, Universidad Nacional de Tucuman
Jiménez, L. - Presenter, Universitat Rovira i Virgili


The need for reducing the fossil fuel consumption along with the associated enviromental impact is driving the development of alternative ?green? systems for energy production. One of the most succesful examples of such shift is bioethanol, a fuel that has already proved its potential for replacing oil-based fuels in Brazil and the US. Despite the effort made so far in the transition process towards a new energy system based on biofuels, there are still some important industrial aspects that merit further attention. In particular, one of the key points that still remains open is how to determine the optimal configuration of the production-distribution network capable of fulfilling a given ethanol demand in the growing markets. This is not a trivial task, since it requires the understanding of the complex temporal and spatial interdependencies arising between the supply chain (SC) entities. The problem is further complicated by the need to account for different conflictive criteria at the design stage. Particularly, biofuels such as bioethanol are considered as ?carbon sinks? that can help in mitigating global warming. Unfortunately, they can also cause negative effects on soils and groundwaters [1]. Hence, the assessment of their envirnonmental benefits requires the application of holistic methods capable of accounting for different enviromental impacts that can occurr throughout the entire biofuel production chain.

With these observations in mind, the aim of this work is to provide a decision-support tool for the strategic planning of integrated bioethanol-sugar SCs considering economic and environmental concerns simultaneously. The design task consists of determining the number, location and capacities of the SC facilities to be set up in each sub-region of a given country, their expansion policy for a given forecast of prices and demands over the planning horizon, the transportation links and number of trucks that need to be established in the network, and the production rates and flows of the involved feedstocks, wastes and final products.

The design problem is mathematically formulated as a mixed-integer linear programming (MILP) model. To encompass all possible conversion pathways, the proposed model includes production facilities of two types: sugar mills and distilleries. Depending on the utilized technology, the sugar mills can give two main by-products: molasses or honey, both of which can be fermented to obtain bioethanol. The liquid and solid materials require different storage conditions, so the model considers two options of warehouses depending on the physical state of the stored material. The region of interest (i.e., Argentina) is subdivided into a number of sub-regions, where the SC facilities can be installed. Different trucks are also considered for transporting materials between the sub-regions of the country. The environmental impact of the SC is assessed by applying Life Cycle Assessment (LCA) principles [2-3]. Particularly, different environmental metrics are calculated based on the Eco-indicator 99 [4] and CML 2001 methodologies [5] (e.g. global warming potential, acidification, depletion of natural resources, etc.) that provide a whole picture of the environmental performance of the system. The resulting multi-objective optimization model is solved via the epsilon constraint method.

The capabilities of the proposed approach are tested through a real case study based on the Argentinean sugar cane industry. The Pareto solutions calculated by our method provided valuable insights into the design problem, showing SC alternatives that may lead to significant environmental improvements. The tool presented is intended to guide policy-makers towards the adoption of more sustainable design alternatives in the transition process towards a biofuels energy system.

References

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2. Azapagic A, Clift R.,(1999). The application of life cycle assessment to process optimisation. Comput Chem Eng. 10, 1509?1526.

3. Lankey R., Anastas P., (2002). Life-cycle approaches for assessing green chemistry technologies. Ind Eng Chem Res. 41, 4498?4502.

4. PRex-Consultants, The Eco-indicator 99, A damage oriented method for life cycle impact assessment.Methodology Report and Manual for Designers. Technical Report, PRex Consultants, Amersfoort, The Netherlands, 2000.

5. Guinée J. Handbook on Life Cycle Assessment: Operational Guide to the ISO Standards (Eco-Efficiency in Industry and Science), Springer, 2002.