References

ACP

Atmospheric Chemistry and Physics

ACP

1680-7324

Copernicus GmbH

Göttingen, Germany

10.5194/acp-6-4867-2006

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

San Martini

F. M.

¹ ⁷ Dunlea

E. J.

¹ ⁸ Grutter

² Onasch

T. B.

³ Jayne

J. T.

³ Canagaratna

M. R.

³ Worsnop

D. R.

³ Kolb

C. E.

³ Shorter

J. H.

³ Herndon

S. C.

³ Zahniser

M. S.

³ Ortega

J. M.

¹ ⁹ McRae

G. J.

⁴ Molina

L. T.

¹ ⁵ Molina

M. J.

¹ ⁶

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

30 10 2006

6 12 4867 4888

This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

This article is available from http://www.atmos-chem-phys.net/6/4867/2006/acp-6-4867-2006.html

The full text article is available as a PDF file from http://www.atmos-chem-phys.net/6/4867/2006/acp-6-4867-2006.pdf

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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