# Presentation: 139394

## Designations for the 2006 PM2.5 Standards: Evaluating the Nine Factors in Setting Nonattainment Area Boundaries

*Part 2 – Conceptual Model for Evaluating High PM**2.5** Days and its Influencing Emission Sources*
- Neil Frank
- EPA Office of Air Quality Planning and Standards
- For Presentation at
- EPA State / Local / Tribal Training Workshop: PM 2.5 Final Rule Implementation and 2006 PM 2.5 Designation Process
- June 20-21, 2007

##  The 9 Designation Factors To  Help Determine Nearby Area of Influence for 24-hr NAAQS Violations

- Air Quality is one of the most Important Designation Factors

## Topics to be Covered

- Conceptual model for high PM days
- Seasons when exceedances occur
- Composition of the high days
- Analytical tools
- SLICE technique - for evaluating urban contributions to high days
- Residence time analysis – for assessing nearby contributing source regions using back trajectories and emissions data
- Gradient analysis – for identifying days with potential high source-oriented impacts

## Conceptual Model for High PM2.5 Days

- How to define high PM2.5 days?
- What is the typical “daily increment” for high PM days in relation to the annual average?
- What is the urban contribution above regional levels?

## Conceptual Model for High PM2.5 Days What high PM2.5 days to consider?

- “High PM2.5 Days” Associated with the 98th percentile
- Not just one day per year
- Select all candidate days
- 	e.g.  top 5% or days > 30 - 35ug/m3
- Summarize by season to distinguish varying conditions

## High Daily PM2.5 has Urban and Regional Components

***Typical Daily Increment - Example***

-  The annual average PM2.5 (urban background) is the stuff that is there on a day-to-day basis.
- Comes from nearby and more distant areas
- Can be estimated by seasonal average PM2.5 concentration of non-high days
- Includes contributions from _all_ nearby surrounding counties
- Can be estimated using the traditional urban increment approach
-  The daily increment (on top of annual average urban background) also has regional and local contributions.
*- Key issue:  what counties and sources from the urban area contribute to the typical daily increment?*

- Conceptual Model for High PM2.5 Days** **
**High Daily PM2.5 has Urban and Regional Components**

## Conceptual Model for High PM2.5 Days  An approach to partition typical levels into urban and regional components

- Conceptual Model for High PM2.5 Days  ***An approach to partition ***_***typical***_*** levels into ******urban and regional components***

- Urban Increment Analyses as used               in 2004/2005 PM2.5 Designations
- Urban sources in the Eastern US contribute at least 4-6 ug/m3 to annual average PM2.5
- Probably even larger urban contribution in western US cities
- Carbon is significant component of average PM2.5 mass, but metro area emissions typically are much less than SO2 and NOx
- Weighted emissions score developed to give additional weight to _nearby_ direct carbon emissions as they contribute to the urban background

## Conceptual Diagram -  Annual Average PM2.5 

- PM [μg/m3]

- natural background

**Urban areas**
- ~14-20 ug/m3

**Countryside**
- ~10-12 ug/m3

- Conceptual Diagram -  Annual Average PM2.5** **

- Air Quality -  Annual Average PM2.5

- regional contribution

- Western US urban areas may have smaller regional contribution

## Conceptual Diagram -  High Daily PM2.5 Concentrations 

- PM [μg/m3]

- natural background

- Conceptual Diagram -  High Daily PM2.5 Concentrations** **

- Air Quality  -  High Daily PM2.5 Concentrations

- regional contribution

**Urban areas**
- ~30-40 ug/m3

**Countryside**
- ~18-30 ug/m3

**Larger    “urban island” on peak days**

***Focus of new analyses:  understanding what ***
***emissions contribute to urban increment***

- Western US urban areas may have smaller regional contribution

## Conceptual Model for High PM2.5 Days  Source region considerations

**Role of Regional vs Urban vs Micro-scale Influences**
- On high days particularly in the east, regional emissions often provide a “base” amount of pollution
- Urban-wide and nearby emissions _also_ contribute significantly to high days:  “urban island” effect
- In some cases, there may be a micro-scale effect from a single source or small group of sources
- Does not help define NA boundaries, unless it is the only contributing source
- (Note:  “urban” can mean large metropolitan area or smaller city)

**Air **
**Quality**

## Conceptual Model for High PM2.5 Days  Seasons when exceedances occur

- Time of Year for Exceedances- varies by Geographic Region
***SE***:  Mostly summer
***Industrial Midwest (IMW), Mid-Atlantic, So. CA***:  Winter and summer
***NW, UT, NM, Middle CA***:  Mostly or exclusively Winter

## Percent of 2003-05 FRM Days > 35 ug/m3 by Month Based on all sites which violate 24-hr NAAQS

_**% **_**50**
**  **
**25**
**0**

- NW

- UT

- IMW

- Mid CA

- S.CA

- SE

- MidAtl

**Percent of 2003-05 FRM Days > 35 ug/m3 by Month **Based on all sites which violate 24-hr NAAQS

- J  F  M  A  M  J  J  A  S  O  N  D

-     J  F  M  A  M  J  J  A  S  O  N  D

- J  F  M  A  M  J  J  A  S  O  N  D

- La Cruces, NM

_**% **_**50**
**  **
**25**
**0**

- J  F  M  A  M  J  J  A  S  O  N  D

## Conceptual Model for High PM2.5 Days  Composition data are important

- Composition
- Indicate which sources are contributing to average _and_ high PM2.5 values
- Varies across country
***Warm season exceedances:*****  **Mostly sulfate + organic carbon
***Cold season exceedances*****:****  **Nitrate (at higher latitudes and in Western US) + sulfate + carbon; Carbon may dominate in some locations (e.g. MT, ID)
- Gaps in speciation data for certain areas

**Air **
**Quality**

## Composition on Annual  Average and High PM2.5 Days (From PM Staff Paper)Some source categories and regional influences may be more important for high concentration days

- Comparing average of 5 highest days during 2003, regional sources of sulfates and nitrates are larger contributors to peak day concentrations than to annual average (selected city analysis)
- Composition can vary from high day to high day
- Carbon can be smaller as %  -- but  still larger in absolute concentration values --  compared to the average
- Note: All the _new_ analyses present “FRM” composition with the p*eer-reviewed “SANDWICH” Technique*
*As used in CAIR and PM**2.5** RIA*

- S

- MW

- CA

- NE

*From PM Staff Paper (Rao et al)*

- Birm
- Atlanta
- NYC
- Cleveland
- Chicago
- St .Louis
- SLC
- Fresno

- UT

- More Sulfate

- More Nitrate

- High PM2.5 _days have_:

- This analysis shows
- PM2.5 Composition of the ambient aerosol
- (_not_ adjusted to represent FRM mass)

**Air **
**Quality**

##  “Example” Composition for High Days [“Warm” Season (May-Sept) & “Cold”]

- NW

- UT

- IMW

- Mid CA

- S.CA

- La Cruces
- NM

- SE

- MidAtl

** “****Example” Composition for High Days **[“Warm” Season (May-Sept) &** ****“**Cold”]
- But sites can be different within each “domain”

- Cold

- Cold        Warm

- Cold        Warm

- Warm

- Cold        Warm

- Cold

- Cold

- Cold

- El Paso STN

**or**

-     J  F  M  A  M  J  J  A  S  O  N  D

- J  F  M  A  M  J  J  A  S  O  N  D

_**% **_**50**
**  **
**25**
**0**

_**% **_**50**
**  **
**25**
**0**

**Pies represent average of 3 highest days per year per season, using SANDWICH**

**or**

## Composition is often similar among the high days

- 3 highest PM2.5 days > 30ug/m3
- Per season, Milwaukee, WI  (2003-05)

**Average   Cool Season   Warm Season**

**Measured**
**PM2.5 mass, ug/m3**

- Black line is difference between OCMmb and OCM14

**Milwaukee, 2003-05**

- PM2.5 days > 30ug/m3

## Conceptual Model for High PM2.5 Days  An approach to partition total daily increment into 

- Conceptual Model for High PM2.5 Days** ** ***An approach to partition total daily increment into ***
***urban and regional components***

## Analytical Toolsto help identify boundaries and develop SIPs

- SLICE technique - for evaluating urban contributions to high days
- Residence time analysis – for assessing nearby contributing source regions using back trajectories and emissions data
- Urban gradient analysis – for identifying whether there are any sites predominantly affected by a single source

## “SLICE” to identify “urban island” days and relative urban amount of PM2.5 mass
Evidence of urban source contributions 
Urban “gradient” technique 
Evidence of predominant strong nearby source influence

- Evidence of urban source contributions
- Urban “gradient” technique
- Evidence of predominant strong nearby source influence

- Analytical Tools***Identify urban PM******2.5****** and gradients ***

**Air **
**Quality**

**Air **
**Quality**

**Emissions**

**Met**

- Daily urban portion of PM2.5

## Analytical Tools - Residence Time Analysis Where did the air parcel come from on high concentration days?

- Transport patterns producing a potential source region
- Use trajectories and “Residence-Time Analysis” to find upwind probability fields.
- For PM2.5 mass or its components
- Focus on the ensemble of “High PM2.5 days”, by season for subsequent linking to composition pattern.
- Days with identified “urban islands” are more important
- Local pollution roses (annual vs. high days) would also be helpful to identify nearby sources.

**Met**

**Air **
**Quality**

- Residence time probability plots with HYSPLIT trajectories have been used by Kinski, Poirot and others to identify potential source regions.

## Analytical Tools- Residence time weighted emissionsWhat are the most likely contributing emissions?

- Spatial distribution of emissions by season
- Developed from monthly emissions for precursors and direct PM:  (SO2, NOx, Carbon, Crustal )
- The importance of each precursor pollutant can be guided by the composition of the high PM2.5 day.
- consider monthly emissions corresponding to the affected PM component  according to typical composition by season.
- Some precursors will not be considered or could be down-weighted. e.g. crustal (year-round) and NOX (summer).
- Residence time weighted emissions
- Use probability that air parcel passed over an area to weight emissions as potential contributors to the high day concentration impacts
- High probability nearby contributing emissions can be identified for each PM2.5 contributor

**Emissions**

**Met**

**Emissions**

**Air **
**Quality**

## Summary

- Identifying the area of emission influence considers contributions for
- each “high PM2.5 day” and
- urban average background on top of which are the daily impacts
- High concentration days with evidence of urban influence (i.e. with urban islands) are more important
- The magnitude of urban island can help define the daily urban contributions.
- In combination with daily and average speciation data, by season of the year
- Emissions with high probability of trajectory residence time are important to assess high day impacts.
- Average emissions and typical wind patterns help understand the sources contributing to the urban “background”
- Both used to understand the _relative_ importance of the various nearby contributing emissions (e.g. direct PM vs SO2 vs NOx).