NDLI: A Synoptic Climatological Approach to Assess Climatic Impact on Air Quality in South-central Canada. Part I: Historical Analysis

Content Provider	Springer Nature Link
Author	Cheng, Chad Shouquan Campbell, Monica Li, Qian Li, Guilong Auld, Heather Day, Nancy Pengelly, David Gingrich, Sarah Yap, David
Copyright Year	2007
Abstract	Automated synoptic weather typing and robust orthogonal stepwise regression analysis (via principal components analysis) were applied together to develop within-weather-type air pollution prediction models for a variety of pollutants (specifically, carbon monoxide – CO, nitrogen dioxide – NO$_{2}$, ozone – O$_{3}$, sulphur dioxide – SO$_{2}$, and suspended particles – SP) for the period 1974–2000 in south-central Canada. The SAS robust regression procedure was used to limit the influence of outliers on air pollution prediction algorithms. Six-hourly Environment Canada surface observed meteorological data and 6-hourly US National Centers for Environmental Prediction (NCEP) reanalysis data of various weather elements were used in the analysis. The models were developed using two-thirds of the total years for meteorological and air pollution data; the remaining one-third (randomly selected) was used for model validation. Robust stepwise regression analysis was performed to analytically determine the meteorological variables that might be used to predict air pollution concentrations. There was a significant correlation between observed daily mean air pollution concentrations and model predictions. About 20, 50, and 80% of the 80 prediction models across the study area possessed R $^{2}$ values ≥ 0.7, 0.6, and 0.5, respectively. The results of model validation were similar to those of model development, with slightly smaller model R $^{2}$ values.
Starting Page	131
Ending Page	148
Page Count	18
File Format	PDF
ISSN	00496979
Journal	Water, Air, and Soil Pollution
Volume Number	182
Issue Number	1-4
e-ISSN	15732932
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2007-01-03
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	synoptic weather typing air pollution prediction robust orthogonal regression south-central Canada Hydrogeology Terrestrial Pollution Waste Water Technology Water Pollution Control Water Management Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Environment
Content Type	Text
Resource Type	Article
Subject	Ecological Modeling Environmental Chemistry Pollution Environmental Engineering Water Science and Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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A Synoptic Climatological Approach to Assess Climatic Impact on Air Quality in South-central Canada. Part II: Future Estimates

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A Synoptic Climatological Approach to Assess Climatic Impact on Air Quality in South-central Canada. Part II: Future Estimates

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