Mapping pm 2 5 methods and uncertainties
Download
1 / 10

Mapping PM 2.5 – Methods and Uncertainties - PowerPoint PPT Presentation


  • 524 Views
  • Uploaded on

Presented by: Tami H. Funk Timothy S. Dye Alan C. Chan Craig B. Andersen Bryan M. Penfold Sonoma Technology, Inc. Petaluma, CA U.S. EPA National Air Quality Conference: It’s Not Just About Ozone Anymore February 2-5, 2003 San Antonio, TX Mapping PM 2.5 – Methods and Uncertainties

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Mapping PM 2.5 – Methods and Uncertainties' - andrew


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Mapping pm 2 5 methods and uncertainties l.jpg

Presented by:

Tami H. Funk

Timothy S. Dye

Alan C. Chan

Craig B. Andersen

Bryan M. Penfold

Sonoma Technology, Inc.

Petaluma, CA

U.S. EPA National Air Quality Conference:

It’s Not Just About Ozone Anymore

February 2-5, 2003

San Antonio, TX

Mapping PM2.5 – Methods and Uncertainties

902090-2324


Slide2 l.jpg

Overview

  • Mapping issues

  • Uncertainty analysis of common mapping methods

  • A method to improve PM2.5 mapping

  • Understanding PM2.5 characteristics can improve mapping

  • Alternative displays of PM2.5 data


Mapping issues 1 of 2 l.jpg

Continuous PM2.5 Monitors

Continuous Ozone Monitors

Mapping Issues (1 of 2)

  • Limited number of continuous PM2.5 monitors in the U.S.


Mapping issues 2 of 2 l.jpg
Mapping Issues (2 of 2)

  • PM2.5 is a regional and local pollutant

  • PM2.5 characteristics vary from region to region (e.g. urban vs. rural)

  • Varying terrain and seasonal characteristics also affect consistency of mapping


Uncertainty analysis mapping l.jpg

0.06

4.5

5.2

8.6

5.5

3.7

Base Map

1.0

8.0

PM2.5 Data Points

Interpolation Uncertainty

(µg/m3)

6.0

PM2.5 Contours

PM2.5 – July 18, 2002

24-hr Averages

Uncertainty Analysis

Overall Uncertainty of Interpolation

Uncertainty Analysis - Mapping

Ozone, PM2.5,Temperature

Inverse Distance Weighted (IDW) & Kriging

July 15 – 19, 2002 (regional PM episode)


Uncertainty analysis results l.jpg
Uncertainty Analysis - Results

Summary of IDW results:

Summary of kriging results:

*RMSE = Root Mean Square Error


A method to improve pm 2 5 mapping l.jpg
A Method to Improve PM2.5 Mapping

Cokriging: surrogate data used to augment spatial coverage of PM2.5 monitors:

  • visibility data as a mapping surrogate

  • population density or urban boundaries as surrogates

  • topography to define regions of influence


Example cokriging l.jpg

Base Map

Data Points

Surrogate Data

Contours

Ozone – July 18, 2002

Average 8-hr Maximum

Reduced Uncertainty?

Temperature °F

Example - Cokriging


Understanding the characteristics of pm 2 5 l.jpg
Understanding the Characteristics of PM2.5

  • A better understanding of PM2.5 by region is needed to improve mapping results

  • Explore relationships with possible surrogate data sets

    • ASOS visibility data, satellite data, digital elevation data, etc.


Alternative displays of pm 2 5 data l.jpg

PM2.5 AQI as Point Values

PM2.5 AQI Values by County

Alternative Displays of PM2.5 Data


ad