Decision support tools for urban air quality management

This thesis developed and applied tools to bridge the gap between available data and action for urban air quality management, focusing on strategies to reduce particle concentrations. One of the principal thesis contributions is a Bayesian method to exploit the asymmetry between the rich aerosol dataset and the relatively poor dataset on gas-phase precursors. A Markov Chain Monte Carlo algorithm was combined with the equilibrium inorganic aerosol model ISORROPIA 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. Applying the method to data from Mexico City, evidence for stable and metastable aerosols was found. Gas phase concentrations were estimated including, for the first time in Mexico City, hydrochloric acid. The MIT Inorganic Aerosol Model was developed based on the work of Resch (1995). The equilibrium treatment of ammonia and nitric acid is included in the model, as is the partial dissociation of bisulfate. Model predictions were critically compared with available models and data, and the role of complexes and hydrates investigated. For the first time, a model that includes complexes and hydrates was applied to an urban environment. Based on 1997 data from Mexico City, it was found that complexes and hydrates are predicted to form in a majority of cases.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Chemical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• San Martini, Federico M. (Federico Matteo), 1973-

Advisor dc:contributor.advisor

• Gregory J. McRae.

• Chemical Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/29444

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/29444