Decision support tools for urban air quality management

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2004.

Bibliographic Details
Main Author: San Martini, Federico M. (Federico Matteo), 1973-
Other Authors: Gregory J. McRae.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2005
Subjects:
Online Access:http://hdl.handle.net/1721.1/29444
_version_ 1826208270944043008
author San Martini, Federico M. (Federico Matteo), 1973-
author2 Gregory J. McRae.
author_facet Gregory J. McRae.
San Martini, Federico M. (Federico Matteo), 1973-
author_sort San Martini, Federico M. (Federico Matteo), 1973-
collection MIT
description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2004.
first_indexed 2024-09-23T14:03:12Z
format Thesis
id mit-1721.1/29444
institution Massachusetts Institute of Technology
language eng
last_indexed 2024-09-23T14:03:12Z
publishDate 2005
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/294442019-04-11T06:04:07Z Decision support tools for urban air quality management San Martini, Federico M. (Federico Matteo), 1973- Gregory J. McRae. Massachusetts Institute of Technology. Dept. of Chemical Engineering. Massachusetts Institute of Technology. Dept. of Chemical Engineering. Chemical Engineering. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2004. Includes bibliographical references (p. 269-283). 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. (cont.) Despite their frequent formation, their effect on model predictions is small given the uncertainties in thermodynamic parameters and field observations. Reductions in ammonia concentrations are likely to be less effective at reducing PM2.5 in Mexico City than expected, while reductions in nitrate and sulfate are expected to be effective. This conclusion is robust including or excluding complexes and hydrates and assuming stable or metastable aerosols, although the best model performance is achieved assuming efflorescence. An inverse technique to estimate the emission rate of a point source using field observations was developed. The relatively simple model minimizes data requirements and is broadly applicable. By incorporating the uncertainty in wind direction, the emissions rate of a tracer was recovered within measurement uncertainty. y Federico M. San Martini. Ph.D. 2005-10-14T20:35:17Z 2005-10-14T20:35:17Z 2004 2004 Thesis http://hdl.handle.net/1721.1/29444 56205083 eng 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. http://dspace.mit.edu/handle/1721.1/7582 283 p. 14736611 bytes 14736411 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
spellingShingle Chemical Engineering.
San Martini, Federico M. (Federico Matteo), 1973-
Decision support tools for urban air quality management
title Decision support tools for urban air quality management
title_full Decision support tools for urban air quality management
title_fullStr Decision support tools for urban air quality management
title_full_unstemmed Decision support tools for urban air quality management
title_short Decision support tools for urban air quality management
title_sort decision support tools for urban air quality management
topic Chemical Engineering.
url http://hdl.handle.net/1721.1/29444
work_keys_str_mv AT sanmartinifedericomfedericomatteo1973 decisionsupporttoolsforurbanairqualitymanagement