Research in Action
EPA Positive Matrix Factorization (PMF) Model
EPA’s Positive Matrix Factorization (PMF) Model is one of several receptor models developed by EPA scientists that provide scientific support for current ambient air quality standards and implementation of those standards by identifying and quantifying the relative contributions that various air pollution sources contribute to ambient air quality in a community or region.
Ambient air quality datasets have improved greatly due to the ability to measure more air pollution species, stratify species by particle size, and conduct shorter sampling sessions. Receptor model algorithms have improved greatly to take advantage of these higher quality datasets.
Users of EPA’s PMF model provide files of sample species concentrations and uncertainties which the model uses to calculate the number of sources types, profiles, relative contributions, and a time-series of contributions. Algorithms used in the PMF model to compute profiles and contributions have been peer reviewed by leading air quality management scientists.
The PMF model software uses graphical user interfaces that ease data input, generation, evaluation and exporting of results. The model is free of charge, and does not require a license or other software to use.
Version 3.0 of EPA’s Positive Matrix Factorization Model works on Windows XP and Windows Vista. The computer should have at least a 2.0 GHz processor, 1 GB of memory, and a 800x600 pixel display.
The EPA Positive Matrix Factorization (PMF) 3.0 Fundamentals & User Guide provides references and details on how to use PMF.