# Presentation: 313554

## A Comparison of AirNow and AQS Particulate Matter Databases

**Katina Gracien****     Brian Hare**
- Graduate Assistants : Atina Brooks, John White & Andrew Moore
- Faculty Advisor : William F. Hunt Jr. & Dr. Kimberly Weems
**Clients: USEPA**
- Chet Wayland
- David Mintz
- Tim Hanley
- Lewis Weinstock
- Scott Jackson

## Background

- Methods of Monitoring Fine Particulate Matter
**FRM (federal reference method)**
**A single 24 hour measurement (midnight to midnight)**
**Continuous**
**TEOM ( Tapered Element Oscillating Microbalance)**
**Hourly measurements**
- RAMS
- Speciated
- Used Air Quality Index Reporting
- Health Advisory
- Reported in USA Today

## AQI Chart for Fine PM

## Purpose

- Compare AQS FRM with AirNow concentration levels on a national level
**How well does the AirNow prediction agree with the FRM measurement?**
- How well do methods in different regions and/or states compare during the summer and winter seasons?
- Which regions and/or states need improvement in the way they predict fine PM?
- Is an Early Warning System needed to improve the accuracy of AiRNow reporting?

## Analysis of the Federal Reference Method: Accuracy of AirNow Predictions

## Map of Percentage Correct using AQI

- District of Columbia

## Map of Percentage correct using AQI

- Percent Correct by Seasons (AirNow vs FRM)

## Differences in Concentration Levels (ug/m3)

## Differences in Concentration Levels

**Average difference of AirNow – FRM by County ****(ug/m****3****)**

## Surrounding Lake Michigan Counties

**Average difference of AirNow – FRM**

## Local ComparisonsMI and NC by County

## FRM vs. AirNow Correlations

## FRM Correlation Coefficients by Season

## Examples of AirNow Reporting

## Chronic Under-reporting of AirNow

**District of Columbia**
**Wrong Level =72/342 = 24.8 %**
**AirNow < FRM  = 331/342 = 96.7%**
**Texas**
**Wrong Level 153/1241 = 15.16%**
**AirNow < FRM 1156/1241 = 93.2%**

## Chronic Over-reporting of AirNow

**Michigan**
**Wrong Level 364/1913 = 19.02%**
**AirNow > FRM 1496/1913 = 78.2%**
**Indiana**
**Wrong Level 211/962 = 21.93% **
**AirNow > FRM 699/962 = 72.7%**

## How Accurately Does AirNow Report the AQI?

## AQS FRM vs. AirNow with AQI code Black = difference in AQI level

## AirNow Levels vs. FRM by AQI Category

- out of 23,262 obs.

- out of 8,666 obs.

- out of 286 obs.

- out of 19 obs.

**1 occurrence**

**7  occurrences**

**5 occurrences**

## Recommendations

**Explore the possibility of developing a QC procedure to pair “problem sites” with sites that consistently report data accurately.**
**3.  Provide an early warning system that data has not been properly adjusted at problem site****.**

**Recommendations**

## Early Warning System Approach

**Examine the correlation matrix for all PM fine sites using FRM(s):**
**Find sites in States with high reporting accuracy (using continuous PM fine instruments) that can be paired to sites in States with low reporting accuracy (Indiana, Michigan, etc.).**
**Develop regression equations predicting FRM measurements at a site in a county with poor reporting accuracy as a function of a PM fine measurements at an adjacent county with “good” reporting accuracy.**

## Average Differences by CountyWinter

- Washtenaw

- Wayne

- Ingham

## Correlation Matrix for Selected FRM Sites

**frm1=Washtenaw, frm2=Ingham, frm3=Wayne**

**0.92821**

**0.92821**

## WINTERAn Early Warning System

## Winter

- Wayne

**Wake**

## Average Differences by CountyWinter

**Washtenaw**

**Wayne**

- Ingham

## STEP 1

## STEP 1

- Obtain the AirNow values for both of           the sites, “good” and “bad”.

## STEP 2

## Step 2 {pred.FRM Washtenaw=F(Airnow Washtenaw)}

## Step 2 Validation 

- Predicted FRM Washtenaw, from the regression equation in previous slide

- Actual observed FRM Washtenaw

## STEP 3

## Step 3 {FRM Wayne= F(FRM Washtenaw)}

- Make sure this is predicted FRM Wayne value not the observed FRM Wayne value

## Step 3 Validation

- Predicted FRM Wayne from the regression equation in previous slide

- Actual observed FRM Wayne

## Next Steps & Recommendations

- Continue to work on QC Procedure.
- Further evaluate the effectiveness of this approach.
- Identify other pairs of “good” & “bad” sites to apply to this QC procedure to.

## Additional Materials

## Locations of the 5 Occurrences of when AirNow Reported Unhealthy for Sensitive and FRM forecasted Good Air Quality 

| site | date | state | city | FRM | AirNow | FRM | AirNow |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 60190008 | 3/9/2004 | California | Fresno | 15 | 41 | Good | Unhealthy for Sensitive |
| 181630012 | 5/18/2004 | Indiana | Evansville | 11.2 | 43 | Good | Unhealthy for Sensitive |
| 181630012 | 5/6/2004 | Indiana | Evansville | 14.9 | 46 | Good | Unhealthy for Sensitive |
| 181630012 | 5/21/2004 | Indiana | Evansville | 13.8 | 49 | Good | Unhealthy for Sensitive |
| 181630012 | 4/30/2004 | Indiana | Evansville | 11.7 | 55 | Good | Unhealthy for Sensitive |

## Locations of the 7 Occurrences of when AirNow Reported Good and FRM forecasted Unhealthy for Sensitive Air Quality

| site | date | state | city | FRM | AirNow | FRM | AirNow |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 131350002 | 11/29/2004 | Georgia | Lawrenceville | 42.7 | 7.4 | Unhealthy for Sensitive | Good |
| 132450091 | 1/4/2005 | Georgia | Augusta | 46.9 | 12.9 | Unhealthy for Sensitive | Good |
| 371830014 | 8/6/2004 | North Carolina | Raleigh | 41.7 | 6 | Unhealthy for Sensitive | Good |
| 390950024 | 2/18/2004 | Ohio | Toledo | 41.6 | 13 | Unhealthy for Sensitive | Good |
| 530050002 | 1/10/2004 | Washington | Kennewick | 42.1 | 13 | Unhealthy for Sensitive | Good |
| 550270007 | 2/18/2004 | Wisconsin | Not in a city | 44.2 | 11 | Unhealthy for Sensitive | Good |
| 550270007 | 2/19/2004 | Wisconsin | Not in a city | 46.8 | 11 | Unhealthy for Sensitive | Good |
| 551330027 | 2/18/2004 | Wisconsin | Waukesha | 49.2 | 15 | Unhealthy for Sensitive | Good |

## Location of the 1 Occurrence of when AirNow Reported Good and FRM forecasted Unhealthy Air Quality

| site | date | state | city | FRM | AirNow | FRM | AirNow |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 100032004 | 9/6/2004 | Delaware | Wilmington | 68.5 | 7.7 | Unhealthy | Good |

## Map of Regression CoefficientsModel : AQS(frm-primary) = β*AirNow

## Regression Coefficients by EPA Region with Season Model : AQS(frm-primary) = β*AirNow

## Air Quality Monitoring Sites Accuracy AirNow Correctly Predicts AQI