Ensemble-Trained PM2.5 Source Apportionment Approach for Health Studies
D Lee, S Balachandran, J Pachon… - … science & technology, 2009 - ACS Publications
An ensemble-trained chemical mass balance (CMB) approach is developed for particulate
matter (PM) source apportionment (SA), particularly for use in health studies. The approach
uses results from a short-term emission-based chemical transport model (CTM) and multiple
receptor-based approaches. Ensemble results have less day-to-day variation in source
impacts and fewer biases between observed and estimated PM2. 5 mass compared to the
original receptor model results. Ensemble results show increases in road dust, biomass …
matter (PM) source apportionment (SA), particularly for use in health studies. The approach
uses results from a short-term emission-based chemical transport model (CTM) and multiple
receptor-based approaches. Ensemble results have less day-to-day variation in source
impacts and fewer biases between observed and estimated PM2. 5 mass compared to the
original receptor model results. Ensemble results show increases in road dust, biomass …
Ensemble-trained PM2.5 source apportionment approach for health studies.
LDH Lee DongHo, S Balachandran, J Pachon… - 2009 - cabidigitallibrary.org
An ensemble-trained chemical mass balance (CMB) approach is developed for particulate
matter (PM) source apportionment (SA), particularly for use in health studies. The approach
uses results from a short-term emission-based chemical transport model (CTM) and multiple
receptor-based approaches. Ensemble results have less day-to-day variation in source
impacts and fewer biases between observed and estimated PM2. 5 mass compared to the
original receptor model results. Ensemble results show increases in road dust, biomass …
matter (PM) source apportionment (SA), particularly for use in health studies. The approach
uses results from a short-term emission-based chemical transport model (CTM) and multiple
receptor-based approaches. Ensemble results have less day-to-day variation in source
impacts and fewer biases between observed and estimated PM2. 5 mass compared to the
original receptor model results. Ensemble results show increases in road dust, biomass …
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