Positive Matrix Factorization (PMF) is a statistical technique used to decompose a matrix into the product of two smaller matrices with non-negative constraints, making it ideal for parts-based representation tasks where interpretability of the factors is important. It is widely used in environmental studies for source apportionment, providing insight into the contribution of different sources to observed data through meaningful and physically interpretable factors.