PM2.5 Source Apportionment Using a Hybrid Environmental Receptor Model
Document Type
Conference Proceeding
Publication Date
1-1-2017
Publication Title
Proceedings of the Air and Waste Management Association's Annual Conference and Exhibition, AWMA
Publisher
Air and Waste Management Association
Abstract
The development of the Hybrid Environmental Receptor Model (HERM), which takes into account both source profiles and uncertainties, was evaluated. Unlike Effective-Variance Chemical Mass Balance (EV-CMB), which solves the CMB equation using effective-variance regression, HERM solves the CMB equation using an iterative non-negative algorithm similar to Positive Matrix Factorization (PMF). PM2.5 were monitored in the Shing Mun tunnel (SMT) in Hong Kong during the winter of 2015 to quantify emission factors of diesel, gasoline, and LPG vehicles. The major sources contributing to SMT samples are vehicle exhaust, road dust, and background air. For the simulated data, HERM yielded identical SCEs as the EV-CMB when all 5 source profiles were used. On the other hand, PMF results are biased from the EV-CMB values and show more fluctuations.
Language
english
Repository Citation
Chen, L. W.,
Wang, X.,
Chow, J. C.,
Watson, J. G.,
Cao, J.
(2017).
PM2.5 Source Apportionment Using a Hybrid Environmental Receptor Model.
Proceedings of the Air and Waste Management Association's Annual Conference and Exhibition, AWMA
Air and Waste Management Association.
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