Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants

When modelling pollutants in the atmosphere, it is nearly impossible to get perfect results as the chemical and mechanical processes that govern pollutant concentrations are complex. Results are dependent on the quality of the meteorological input as well as the emissions inventory used to run th...

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Main Author: Ambachtsheer, Pamela
Format: Others
Language:en
Published: University of Waterloo 2006
Subjects:
Online Access:http://hdl.handle.net/10012/1261
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spelling ndltd-WATERLOO-oai-uwspace.uwaterloo.ca-10012-12612013-01-08T18:49:25ZAmbachtsheer, Pamela2006-08-22T14:35:07Z2006-08-22T14:35:07Z20042004http://hdl.handle.net/10012/1261When modelling pollutants in the atmosphere, it is nearly impossible to get perfect results as the chemical and mechanical processes that govern pollutant concentrations are complex. Results are dependent on the quality of the meteorological input as well as the emissions inventory used to run the model. Also, models cannot currently take every process into consideration. Therefore, the model may get results that are close to, or show the general trend of the observed values, but are not perfect. However, due to the lack of observation stations, the resolution of the observational data is poor. Furthermore, the chemistry over large bodies of water is different from land chemistry, and in North America, there are no stations located over the great lakes or the ocean. Consequently, the observed values cannot accurately cover these regions. Therefore, we have combined model output and observational data when studying ozone concentrations in north eastern North America. We did this by correcting model output at observational sites with local data. We then interpolated those corrections across the model grid, using a Kriging procedure, to produce results that have the resolution of model results with the local accuracy of the observed values. Results showed that the corrected model output is much improved over either model results or observed values alone. This improvement was observed both for sites that were used in the correction process as well as sites that were omitted from the correction process.application/pdf6268755 bytesapplication/pdfenUniversity of WaterlooCopyright: 2004, Ambachtsheer, Pamela. All rights reserved.ChemistryAir Quality ForecastingKrigingFour Dimensional Data AssimilationOzoneCombined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of PollutantsThesis or DissertationChemistry and BiochemistryMaster of Science
collection NDLTD
language en
format Others
sources NDLTD
topic Chemistry
Air Quality Forecasting
Kriging
Four Dimensional Data Assimilation
Ozone
spellingShingle Chemistry
Air Quality Forecasting
Kriging
Four Dimensional Data Assimilation
Ozone
Ambachtsheer, Pamela
Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants
description When modelling pollutants in the atmosphere, it is nearly impossible to get perfect results as the chemical and mechanical processes that govern pollutant concentrations are complex. Results are dependent on the quality of the meteorological input as well as the emissions inventory used to run the model. Also, models cannot currently take every process into consideration. Therefore, the model may get results that are close to, or show the general trend of the observed values, but are not perfect. However, due to the lack of observation stations, the resolution of the observational data is poor. Furthermore, the chemistry over large bodies of water is different from land chemistry, and in North America, there are no stations located over the great lakes or the ocean. Consequently, the observed values cannot accurately cover these regions. Therefore, we have combined model output and observational data when studying ozone concentrations in north eastern North America. We did this by correcting model output at observational sites with local data. We then interpolated those corrections across the model grid, using a Kriging procedure, to produce results that have the resolution of model results with the local accuracy of the observed values. Results showed that the corrected model output is much improved over either model results or observed values alone. This improvement was observed both for sites that were used in the correction process as well as sites that were omitted from the correction process.
author Ambachtsheer, Pamela
author_facet Ambachtsheer, Pamela
author_sort Ambachtsheer, Pamela
title Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants
title_short Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants
title_full Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants
title_fullStr Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants
title_full_unstemmed Combined Use of Models and Measurements for Spatial Mapping of Concentrations and Deposition of Pollutants
title_sort combined use of models and measurements for spatial mapping of concentrations and deposition of pollutants
publisher University of Waterloo
publishDate 2006
url http://hdl.handle.net/10012/1261
work_keys_str_mv AT ambachtsheerpamela combineduseofmodelsandmeasurementsforspatialmappingofconcentrationsanddepositionofpollutants
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