Atmospheric Chemistry and Physics
www.atmos-chem-phys.net
1680-7316
1680-7324
6
12
2006
10.5194/acp-6-4867-2006
http://www.atmos-chem-phys.net/6/4867/2006/
http://www.atmos-chem-phys.net/6/4867/2006/acp-6-4867-2006.html
http://www.atmos-chem-phys.net/6/4867/2006/acp-6-4867-2006.pdf
4867
4888
2006-10-30
Implementation of a Markov Chain Monte Carlo method to inorganic aerosol modeling of observations from the MCMA-2003 campaign – Part I: Model description and application to the La Merced site
F. M. San Martini
ico@alum.mit.edu
E. J. Dunlea
M. Grutter
T. B. Onasch
J. T. Jayne
M. R. Canagaratna
D. R. Worsnop
C. E. Kolb
J. H. Shorter
S. C. Herndon
M. S. Zahniser
J. M. Ortega
G. J. McRae
L. T. Molina
M. J. Molina
Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México, Mexico City, Mexico
Aerodyne Research Inc., Billerica, MA, USA
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
Molina Center on Energy and the Environment, La Jolla, CA, USA
Department of Chemistry and Biochemistry, University of California, San Diego, CA, USA
now at: the Board on Chemical Sciences and Technology, National Academies, Washington, D.C., USA
Cooperative Institute for Research in the Environmental Sciences (CIRES), Univ. of Colorado at Boulder, Boulder, CO, USA
now at: Sandia National Laboratory, Livermore, CA, USA
The equilibrium inorganic aerosol model ISORROPIA was embedded in a Markov
Chain Monte Carlo algorithm to develop a powerful tool to analyze aerosol
data and predict gas phase concentrations where these are unavailable. The
method directly incorporates measurement uncertainty, prior knowledge, and
provides a formal framework to combine measurements of different quality.
The method was applied to particle- and gas-phase precursor observations
taken at La Merced during the Mexico City Metropolitan Area (MCMA) 2003
Field Campaign and served to discriminate between diverging gas-phase
observations of ammonia and predict gas-phase concentrations of hydrochloric
acid. The model reproduced observations of particle-phase ammonium, nitrate,
and sulfate well. The most likely concentrations of ammonia were found to
vary between 4 and 26 ppbv, while the range for nitric acid was 0.1 to 55 ppbv.
During periods where the aerosol chloride observations were
consistently above the detection limit, the model was able to reproduce the
aerosol chloride observations well and predicted the most likely gas-phase
hydrochloric acid concentration varied between 0.4 and 5 ppbv. Despite the
high ammonia concentrations observed and predicted by the model, when the
aerosols were assumed to be in the efflorescence branch they are predicted
to be acidic (pH~3).
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