ESAT: Environmental Source Apportionment Toolkit Python package

Source apportionment is an important tool in environmental science where sample or sensor data are often the product of many, often unknown, contributing sources.Source apportionment is used to understand the relative contributions of air sources (Bhandari et al., 2022) like vehicle emissions, industrial activities, or dust; as well as particulate matter pollution and to identify relative contributions of point sources and non-point sources in water bodies such as lakes, rivers, and estuaries (Jiang et al., 2019;Mamun & An, 2021).Using non-negative matrix factorization (NMF), source apportionment models estimate potential source profiles and contributions providing a cost-efficient method for further strategic data collection or modeling.Environmental Source Apportionment Toolkit (ESAT) is an open-source Python package that provides a flexible and transparent workflow for source apportionment using NMF algorithms, developed to replace the EPA's Positive Matrix Factorization version 5 (PMF5) application (EPA, 2014;Pentti Paatero, 1999).ESAT recreates the source apportionment workflow of PMF5 including pre-and post-processing analytical tools, batch modeling, uncertainty estimations and customized constraints.ESAT offers a simulator for generating datasets from synthetic profiles and contributions, allowing for model output evaluation.The synthetic profiles can be randomly generated, use a pre-defined set of profiles, or be a combination of the two.The random synthetic contributions can follow specified curves and value ranges.By running ESAT using the synthetic datasets, users are able to accurately assess ESAT's ability to find a solution that recreates the original synthetic profiles and contributions.