Abstract
A hybrid environmental receptor model (HERM) that unifies the theory of effective-variance chemical mass balance (EV-CMB) and positive matrix factorization (PMF) models was developed to support the weight-of-evidence approach of air pollution source apportionment. The HERM software is capable of (1) conducting EV-CMB analysis for multiple samples in a single model run; (2) calculating EV-CMB and PMF source contributions, as well as middle grounds between the two (i.e., hybrid mode), using partial source information available for the study region; (3) reporting source contribution uncertainties and sample-/species-specific fitting performance measures; and (4) interfacing with MS Excel for convenient data inputs/outputs and analysis. Initial testing with simulated and real-world PM2.5 (fine particulate air pollutants with aerodynamic diameter <2.5 μm) data sets show that HERM reproduces EV-CMB results from existing software but with more tolerance to collinearity and better uncertainty estimates. It also shows that partial source information helps reduce rotational ambiguity in PMF, thus producing more accurate partitioning between highly correlated sources. Moreover, source profiles generated from the hybrid mode can be more representative of the study region than those acquired from other locales or calculated by PMF with no source information. Strategies to use HERM for source apportionment are recommended.
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