The solution of several operations research problems requires the creation of a quantitative
model. Sensitivity analysis is a crucial step in the model building and result communication …

Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model
can be attributed to variations of its input factors. SA is increasingly being used in …

Investors and financial regulators are increasingly aware of climate-change risks. So far,
most of the attention has fallen on whether controls on carbon emissions will strand the …

Abstract Implementing Circular Economy (CE) is a promising solution to tackle
environmental challenges in the construction industry. On the way towards a circular built …

Variance-based approaches are widely used for Global Sensitivity Analysis (GSA) of
environmental models. However, methods that consider the entire Probability Density …

Modelling the economics of climate change is daunting. Many existing methodologies from
social and physical sciences need to be deployed, and new modelling techniques and ideas …

Modeling is a crucial approach for understanding the past and exploring the future of
coupled human-natural systems. However, uncertainty in various forms challenges …

The economics of climate change involves a vast array of uncertainties, complicating our
understanding of climate change. This study explores uncertainty in baseline trajectories …

In a previous paper we introduced a distribution-based method for Global Sensitivity
Analysis (GSA), called PAWN, which uses cumulative distribution functions of model outputs …

How does climate-change mitigation affect the aggregate consumption risk borne by future
generations? In other words, what is the 'climate beta'? In this paper we argue using a …