CRC Report No. A-34 - Coordinating Research Council

April 2005
5. CONCLUSIONS
The experiments conducted for CRC Project A-34 are the first to test quantitatively the ability of
a receptor model to source apportion VOCs under simulated “real-world” conditions. Important
features of the experiments were:
• The presence of 4-D spatial/temporal source-receptor relationships simulated using the
photochemical grid model with mass-consistent and mass-conservative meteorological
fields.
• Known source contributions of 22 source categories to 55 VOC species monitored by the
EPA’s Photochemical Assessment Monitoring Stations (PAMS).
• Photochemical decay of VOCs by reactions with OH radicals, ozone and NO 3 radicals.
Experiments investigated how receptor model performance depended upon modeling
assumptions and simulated “ambient” conditions.
The receptor model evaluated was the Chemical Mass Balance (CMB) model version 8. The
CMB model has been applied to VOC source apportionment in numerous studies (Watson, Chow
and Fujita, 2001). The CMB developers have presented six assumptions (Watson, Chow and
Fujita, 2001) that underlie the application of the model for VOCs:
1. The composition of source emissions is constant over the period of ambient and source
sampling.
2. Chemical species do not react with each other, i.e., they add linearly.
3. All significant sources have been identified and had their emissions characterized.
4. The number of source categories is less than the number of species, i.e., there are degrees
of freedom available in the analysis.
5. The source profiles are sufficiently different one from another.
6. Measurement errors are random, uncorrelated and normally distributed.
Similar assumptions apply to other receptor models except that factor analysis methods do not
rely upon the third assumption, but make other assumptions (Watson and Chow, 2004).
The findings from the experiments conducted for this study are summarized below and then
compared to the six assumptions listed above. We consider whether the experimental results
confirm the CMB assumptions, whether there are other CMB assumptions that need to be
considered, how well these assumptions were met for the conditions of our experiments, and
whether there are other factors external to the CMB analysis that should be considered when
interpreting the results.
5.1 REVIEW OF FINDINGS
The findings developed throughout Section 4 are presented here so that they may be considered
together.
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