(35e) Developing a Systemic Methodological Framework for the Sustainability Assessment of Biobased Fuels and Chemicals

In the last two decades, there has been some effort in academia and industrial practice to provide tools that can deal with the challenges of designing sustainable chemical processes. Taking into account the diversity of the sustainability objectives, data availability and, therefore, modelling detail, it is inevitable that the structure of the developed tools varies significantly, ranging from simple indicators to holistic frameworks for an overall process assessment. These sustainability frameworks have also been applied in the field of biorefineries, in particular for biofuels, bioethanol, methanol and syngas production, incorporating process integration and life cycle assessment (LCA), exergy and inherent safety analysis, and life cycle energy and environmental analysis. However, perhaps the most striking difference between biobased and conventional chemical production in terms of sustainability assessment is the availability of process data, even for single biobased production lines, not to mention for integrated biorefinery concepts.

From this perspective, the aim of this study is (i) to present the methodological steps for the development of a model-based database of LCA related sustainability impacts in biomass based production, (ii) to demonstrate the use of this database in single- and integrated multi-production lines and (iii) to provide a first generation of surrogate models that correlate available input to desirable output process parameters and assessment metrics with computationally inexpensive algebraic forms.

In particular, this study presents detailed cradle-to-gate inventory analysis in biomass based production using protocols for process flowsheeting and filling of data gaps (e.g., for cradle-to-gate production steps and waste treatment of process effluents), considers various environmental impact allocation methods for the resulting joint and co-production biorefinery systems, applies a wide list of sustainability impact assessment metrics and tests multiple surrogate modelling approaches (i.e., from simple linear regression to partial least squares, Kriging and neural network approaches) on the basis of model generated data and sampling plans.

The overall methodological framework comprises an accessible, modular and expandable database of biobased production lines, including mass and energy balances, other process related information and various allocation approaches for the calculation of life cycle inventories in single- and multi-production systems. The resulting data structures are integrated with a reporting mechanism which offers information about the environmental impacts expressed by relevant indicators proposed by life cycle impact assessment methods such as the RECIPE and Cumulative Energy Demand methods and provides an environment for benchmarking alternative choices.

Molreover, metrics of â??green chemistryâ?Â assessing the efficiency of processes (yield, mass intensity, E-factor etc.) as well as other process-related variables are extracted from the data structures aiming at the development of a first generation of surrogate models  to provide guidance for a fast screening of innovative biobased processes and products.

The data structures, assessment results and surrogate modelling performance is demonstrated for a series of platform chemicals (e.g., syngas, sugars and lignin) and biofuels (e.g., biodiesel, biogas, and alcohols), starting from diverse biomass sources (e.g., wood chips, wheat straw, vegetable oil) and biomass availability scenarios, in single and integrated multi-production lines.