<?xml version="1.0" encoding="utf-8" standalone="no"?>
<!DOCTYPE article SYSTEM "http://www.atmos-chem-phys-discuss.net/inc/acpd/copernicus.dtd">
<article language="en">
	<journal>
		<journal_title>Atmospheric Chemistry and Physics Discussions</journal_title>
		<journal_url>www.atmos-chem-phys-discuss.net</journal_url>
		<issn>1680-7367</issn>
		<eissn>1680-7375</eissn>
		<volume_number>6</volume_number>
		<issue_number>4</issue_number>
		<publication_year>2006</publication_year>
	</journal>
	<doi>10.5194/acpd-6-5933-2006</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/6/5933/2006/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/6/5933/2006/acpd-6-5933-2006.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/6/5933/2006/acpd-6-5933-2006.pdf</fulltext_pdf>
	<start_page>5933</start_page>
	<end_page>5998</end_page>
	<publication_date>2006-07-10</publication_date>
	<article_title content_type="html">Implementation of a Markov Chain Monte Carlo Method to inorganic aerosol modeling of observations from the MCMA-2003 Campaign. Part&amp;nbsp;I: Model description and application to the La Merced Site</article_title>
	<authors>
		<author numeration="1" affiliations="1,7">
			<name>F. M. San Martini</name>
		</author>
		<author numeration="2" affiliations="2">
			<name>E. J. Dunlea</name>
		</author>
		<author numeration="3" affiliations="3">
			<name>M. Grutter</name>
		</author>
		<author numeration="4" affiliations="4">
			<name>T. B. Onasch</name>
		</author>
		<author numeration="5" affiliations="4">
			<name>J. T. Jayne</name>
		</author>
		<author numeration="6" affiliations="4">
			<name>M. R. Canagaratna</name>
		</author>
		<author numeration="7" affiliations="4">
			<name>D. R. Worsnop</name>
		</author>
		<author numeration="8" affiliations="4">
			<name>C. E. Kolb</name>
		</author>
		<author numeration="9" affiliations="4">
			<name>J. H. Shorter</name>
		</author>
		<author numeration="10" affiliations="4">
			<name>S. C. Herndon</name>
		</author>
		<author numeration="11" affiliations="4">
			<name>M. S. Zahniser</name>
		</author>
		<author numeration="12" affiliations="1,8">
			<name>J. M. Ortega</name>
		</author>
		<author numeration="13" affiliations="5">
			<name>G. J. McRae</name>
		</author>
		<author numeration="14" affiliations="1,6">
			<name>L. T. Molina</name>
		</author>
		<author numeration="15" affiliations="1,9">
			<name>M. J. Molina</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA</affiliation>
		<affiliation numeration="2" content_type="html">Cooperative Institute for Research in the Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, CO, USA</affiliation>
		<affiliation numeration="3" content_type="html">Centro de Ciencias de la Atm&amp;oacute;sfera, Universidad Nacional Aut&amp;oacute;noma de M&amp;eacute;xico, Mexico City, Mexico</affiliation>
		<affiliation numeration="4" content_type="html">Aerodyne Research Inc., Billerica, MA, USA</affiliation>
		<affiliation numeration="5" content_type="html">Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA</affiliation>
		<affiliation numeration="6" content_type="html">Molina Center on Energy and the Environment, La Jolla, CA, USA</affiliation>
		<affiliation numeration="7" content_type="html">now at: the Board on Chemical Sciences and Technology, National Academies, Washington D.C., USA</affiliation>
		<affiliation numeration="8" content_type="html">now at: Sandia National Laboratory, Livermore, CA, USA</affiliation>
		<affiliation numeration="9" content_type="html">now at: University of California San Diego, La Jolla, CA, USA</affiliation>
	</affiliations>
	<abstract content_type="html">The equilibrium inorganic aerosol model ISORROPIA was embedded in a Markov
Chain Monte Carlo algorithm to produce 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 for a formal framework to combine measurements of different
quality. The method was applied to aerosol- 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. 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).</abstract>
	<references>
	</references>
</article>

