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EPA Positive Matrix Factorization (PMF) 3.0 Fundamentals & User Guide
Citation:
NORRIS, G. A., R. VEDANTHAM, K. Wade, S. Brown, J. Prouty, AND C. FOLEY. EPA Positive Matrix Factorization (PMF) 3.0 Fundamentals & User Guide. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-08/108, 2008.
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA′s mission to protect human health and the environment. HEASD′s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA′s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Positive matrix factorization (PMF) is a multivariate factor analysis tool that decomposes a matrix of ambient data into two matrices - factor contributions and factor profiles - which then need to be interpreted by an analyst as to what source types are represented using measured source profile information, wind direction analysis, and emission inventories.The method is reviewed briefly here and described in greater detail.