Explores uncertainty analysis in Life Cycle Assessment, covering sensitivity, probability functions, parameter estimation, pedigree approach, and uncertainty propagation.
Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.
