Zhang, Qi

Headshot of Qi Zhang


Email: dkwzhang@ucdavis.edu
Office: 4251A Meyer Hall
Phone: (530) 752-5779

Welcome to Qi Zhang's Web Site!!!


Qi_at_SantaBarbara.jpg


QI ZHANG
Professor

Department of Environmental Toxicology

University of California, Davis

 

4251A Meyer Hall

Davis,California 95616
Tel: (530) 752-5779 (O)
E-mail: dkwzhang@ucdavis.edu

 

GROUP WEBPAGE

https://sites.google.com/site/qizhanggroup/

AMS GLOBAL DATABASE

AMS ORGANIC DATA ANALYSIS:

1. AMS Organic Analysis Basics:

· Tutorial presentation at the 6th AMS User's Meeting in Juelich, Germany, Fall, 2005.

2. AMS Organic Analysis Software

· This code resolves the mass spectra and time series of 2 organic aerosol components, which correspond to hydrocarbon-like and oxygenated organic aerosol (HOA and OOA) in applicable locations.

Version Date of Release Release Notes* Installer

v 1.2

March 16, 2007

modified 04/19/07

Release Notes

1. Download ExtractWavesMatrices v1.2 (for SQUIRREL)

2. Download AMS Organic Analysis Software v1.2

v 1.1

Nov. 20, 2005

Release Notes
Notes on AMS Organic Analysis Toolkit v 1.1.

1. Download ExtractWaves&matrices v1.1

2. Download AMS Organic Analysis Software v1.1

v 1.0

Aug. 26, 2005

Notes on AMS Organic Analysis Toolkit v 1.0.

1. Download ExtractWaves&matrices v1.0

2. Download AMS Organic Analysis Software v1.0

 

* Important: Please carefully check all the diagnostic information, especially the relative and absolute residuals in the time trend (see Figures 4 & 5 in our EST paper) and the extracted mass spectra, before presenting/publishing results from this software. It is also important that you examine the diagnostic plots such as Figures 7 & 8 in our EST paper. The presence of significant negative peaks in the extract mass spectra, for example, is typically a sign of lack of fit between the model (assumptions) and the real data. It is highly recommended that you CONTACT us if you see strange results and/or you have questions about interpretation.

 

Most importantly, this code will NOT give reasonable results in a situation where more than two distinct components clearly make an impact in the data. It is therefore NOT recommended to use for rural or remote locations, when we find that in general the two-component method is insufficient, as we discussed at the 6th users meeting in Juelich. We found this code works properly for several urban locations and yields physically and chemically meaningful results on HOA and OOA (e.g., in Pittsburgh (Zhang et al., 2005), Mexico City (Volkamer et al., 2006), and Tokyo (Takegawa et al. 2006, Kondo et al., 2006)). However, at some urban locations (as shown in our Mexico City data) the code is applicable for some periods of time, but not for others in which biomass burning made a clear impact. So, when you see large absolute residuals in the time trend and/or if you know the presence of significant amounts of other source components from observations or from other measurements, you will need to use a method that can find more than 2 components.

 

A new version of this algorithm has been developed to do more than 2-component analysis. It has successfully identified 4 meaningful components in the Houston AMS data from summer 2000. If time permits, this new algorithm can be applied to other datasets in collaboration with AMS Users.

PEER-REVIEWED PUBLICATIONS

https://sites.google.com/site/qizhanggroup/publications

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