An approach to estimate the water footprint of the Bioethanol supply chain and its dynamic simulation

  1. Trujillo-Mata, A. 1
  2. Cortés-Robles, G. 1
  3. Sánchez-Ramírez, C. 1
  4. Blanco-Fernández, J. 2
  5. Jiménez-Macías, E. 2
  1. 1 Instituto Tecnologico de Orizaba
    info

    Instituto Tecnologico de Orizaba

    Orizaba, México

    ROR https://ror.org/05vpj2s72

  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Libro:
4th International Workshop on Simulation for Energy, Sustainable Development and Environment, SESDE 2016

ISBN: 9788897999720

Año de publicación: 2016

Páginas: 42-48

Congreso: 4th International Workshop on Simulation for Energy, Sustainable Development and Environment, SESDE 2016

Tipo: Aportación congreso

Repositorio institucional: lock_openAcceso abierto Editor

Resumen

The Supply Chain Management as a source of competitiveness evolves continually. In the last decade, the sustainability of the supply chain represents a key success factor. The energy industry is not an exception. The global pressure to reduce emissions combined with the negative tendency in the world oil reserves is impelling the improvement and development of renewable sources of energy. The bioethanol industry is one of the most active sectors. Under this environment, the market is facing a conflict: To increase productivity (more resources consumed), without compromising the future natural resources. As the bioethanol industry accelerates its productivity and market share, another renewable resource suffers for this expansion: The water reserves. This work proposes to integrate the Bioethanol Supply Chain Analysis with the Water Footprint Assessment. Since water changes in time under the influence of several factors, the System Dynamics approach is very useful to deal with variables that change continually over time. Consequently, a model to evaluate the water footprint of the bioethanol supply chain through the system dynamics approach enables the capacity to simulate the impact of bioethanol production on water resources over time. This work presents a Causal-Loops Diagram useful to observe and analyze the complex relationship that the components of the bioethanol supply chain have.