Section: New Results

Downscaling Material Flow Analysis: the case of the cereals supply chain in France

The spatial reconstruction of the production, trade, transformation and consumption flows of a specific material can become an important decision-help tool for improving resource management and for studying environmental pressures from the producer's to the consumer's viewpoint. One of the obstacles preventing its actual use in the decision-making process is that building such studies at various geographical scales proves to be costly both in time and manpower. We propose a semi-automatic methodology to overcome this issue. First a supply chain model at the national level has to be designed. Supply and use tables are used to handle the data consistently. Finding the appropriate level of detail for both products and industries is an iterative process: with a small number of highly aggregated product categories, the study isn't likely to provide useful information while with a very detailed list of products and industries, finding input data, especially at local scales, won't be feasible. Secondly, national production, transformation, trade and consumption data have to be reconciled in order to respect the law of mass conservation: this is done through constraint optimization. Thirdly, regional supply and use tables are generated (either with direct data or through downscaling of national data using local proxies, e.g. employment statistics) and reconciled, taking into account the additional constraint that regional data must add up to national one.

We applied the methodology on the case of cereals and reconstructed the supply chain flows of the 22 French regions as well as the flows of four nested territories: France, the Rhône-Alpes région, the Isère département and the territory of the SCOT of Grenoble. Uncertainties of output data were estimated via Monte-Carlo simulations. We display the results using our Sankey diagram vizualisation tool. A research paper is in the reviewing process for one of the major journals in this field.

Future steps include coupling this model with economic (added value), social (local employment) and environmental (environmental pressures) aspects in order to provide new information to decision-makers at various administrative levels (from a group of cities to the national level).