Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Life-cycle portfolio choice with liquid and illiquid financial assets

Traditionally, quantitative models that have studied households׳ portfolio choices have focused exclusively on the different risk properties of alternative financial assets. We introduce differences in liquidity across assets in the standard life-cycle model of portfolio choice. More precisely, in our model, stocks are subject to transaction costs, as considered in recent macroliterature. We show that when these costs are calibrated to match the observed infrequency of households׳ trading, the model is able to generate patterns of portfolio stock allocation over age and wealth that are constant or moderately increasing, thus more in line with the existing empirical evidence.

Building from building waste: The development of an instrument to determine the circularity of materials from the existing building stock in order to maximise high quality reuse

On a global level the population growth and increase of the middle class lead to a growing demand on material resources. The built environment has an enormous impact on this scarcity. In addition, a surplus of construction and demolition waste is a common problem. The construction industry claims to recycle 95% of this waste but this is in fact mainly downcycling. Towards the circular economy, the quality of reuse becomes of increasing importance. Buildings are material warehouses that can contribute to this high quality reuse. However, several aspects to achieve this are unknown and a need for more insight into the potential for high quality reuse of building materials exists. Therefore an instrument has been developed that determines the circularity of construction waste in order to maximise high quality reuse. The instrument is based on three principles: ‘product and material flows in the end of life phase’, ‘future value of secondary materials and products’ and ‘the success of repetition in a new life cycle’. These principles are further divided into a number of criteria to which values and weighting factors are assigned. A degree of circularity can then be determined as a percentage. A case study for a typical 70s building is carried out. For concrete, the circularity is increased from 25% to 50% by mapping out the potential for high quality reuse. During the development of the instrument it was clarified that some criteria are difficult to measure. Accurate and reliable data are limited and assumptions had to be made. To increase the reliability of the instrument, experts have reviewed the instrument several times. In the long-term, the instrument can be used as a tool for quantitative research to reduce the amount of construction and demolition waste and contribute to the reduction of raw material scarcity.