# Presentation: 921739

## Local Ozone Forecasting and theNOx SIP Call Rule

- William F. Ryan
- Department of Meteorology
- The Pennsylvania State University

- National Air Quality Conference, Orlando, 2007

## Background

- In 1998, EPA finalized the "Finding of Significant Contribution and Rulemaking for Certain States in the Ozone Transport Assessment Group Region for Purposes of Reducing Regional Transport of Ozone." (Commonly called the “NOx SIP Rule”.)
- The NOx SIP Rule was designed to mitigate the transport of NOx, one of the precursors of ozone.
- The obligations under this Rule can be, and have been, met through a cap and trade program (EPA NOx Budget Trading Program, or NBP).
- The SIP Rule is part of a suite of control programs including the Acid Rain program and OTC NOx Budget Program.

## Phase In of the NOx SIP Rule

- Compliance with the SIP Rule set for May, 2003 in the OTC (Northeast Corridor) and May 31, 2004 in most other states.  Litigation was extensive.
- By 2005, the rule affected ~ 2,500 units.
- 85% electric generating units
- 15% large industrial units
- Continuous emissions monitoring system (CEMS) used to verify emissions.

## SIP Rule Phase In

## Extent of NOx Reductions

- EPA estimates that, by 2005, NOx emissions from sources regulated by the NOx SIP Rule area have decreased by 57% over 2000 emissions.
- EPA also estimates that O3 concentrations have been reduced, on average, by 14%, after adjustments for meteorology, for the period 1997-2004.

## Estimates of NOx Emissions Reductions

- Estimates of NOx Emissions Reductions

## NOx Emissions Come From Many Sources

- NOx Emissions Come From Many Sources

## Effect of Regional NOx Controls

- Scientific consensus was that O3 concentrations in the eastern US, outside of large urban areas, is NOx-limited.
- Therefore, reductions in NOx emissions regionwide will reduce the “background” or “regional scale” O3 concentrations.
- Local emissions and photochemistry will still lead to “spikes” in O3, often Code Orange or higher, but these spikes will build on a lower base and be of reduced magnitude.

## S.T. Rao’s Famous Slide

## Can We See Effects of the NOx SIP Rulein Local Areas?

## Hypotheses

- If regional NOx reductions work as planned, we should see:
- Slight decrease in urban mean peak O3 (why slight?)
- Decrease in extreme O3 days.
- Decrease in the areal extent of high O3 on bad air days (fewer monitors > threshold).
- Decrease in O3 measured at regional scale monitors.

## Caveats

- Results can only be considered provisional.  Time series, or time since controls enacted, is too short to support final conclusions.
- High O3 in the mid-Atlantic is a complicated combination of meteorological and chemical influences and we cannot conclusively “adjust” for seasonal and sub-seasonal meteorological variations.
- e.g., Temperature, wind speed and relative humidity, common meteorological correction factors, only explain ~ 58% of variance in PHL peak O3.

## Why Will Regional Rule Affect PHL O3?

- Source region for air parcels
- arriving in PHL during summer
- pollution events is typically
- from the west.  Example from
- 2000 shown at right.

## Observed O3 in Regional Transport Cases

- Surface observations at Shenandoah
- NP (above) during a westerly transport
- regional pollution episode in 1998
- showed high O3 concentrations coupled
- with high SO2 – a signature of coal
- combustion.

- Aircraft observations in central VA
- during a 1995 O3 episode show
- high concentrations of O3 coupled
- with high SO2 and NOy – consistent
- with coal combustion source

## NOx SIP Rule Emissions Reductions Occurred in Source Region of Interest

- NOx SIP Rule Emissions Reductions Occurred in Source Region of Interest

## EPA Analysis Show Reductions in O3

- EPA Analysis Show Reductions in O3

## Slight Reduction in Urban Peak O3

- 1994-2002:  70 ppbv

- 2003-2006:  63.2 ppbv

- Reduction on order of
- 10% - consistent with
- EPA regionwide findings

- Mean summer season metro-wide peak 8-hour O3 concentrations in PHL

## Decrease in Extreme O3 Days:  Philadelphia Metropolitan Area

- Frequency of
- Days ≥ 115 ppbv
- 1994-2002:  4.8 days/year
- 2003-2006:  0.8 days/year

## Decrease in Areal Extent of High O3:  Number of Monitors ≥ 100 ppbv

- Average = 61 monitors/yr

- Average = 15

## Frequency of High O3 Cases per SeasonVaries with Temperature Regime

- Cool Summer
- 1996
- T925 - JJA

- Warm Summer
- 1999
- T925 - JJA

- Temperature Anomaly

- Hot

- Cold

- Number of Monitors
- ≥ 100 ppbv

## But, Warm Season of 2006 Did Not Show Similar Response as Earlier Years

- Warm Season
- 2006
- T925 - JJA

- Cool Season
- 2004
- T925 - JJA

## Overall:  Post NOx SIP Rule Summer Seasons As Warm or Warmer than Previous Years

- Average number of monitors ≥
- 100 ppbv 8-hour average:
- 1994-2002:  61.3
- 1997-2002:  71.0
- 2003-2006:  15.2

- T925 Anomaly
- 1997-2002
- JJA

- T925 Anomaly
- 2003-2006
- JJA

## Hot Weather Not Always = High O3:Fraction Decreases after 2002

- Code Red days
- (May-September) divided by
- the number of days ≥ 90o F
- during same period.
- 1994-2002:  0.40 (40%)
- 2003-2006:  0.09 (9%)
- Hot summers less likely to
- be smoggy summers

## Temperature-O3 Relationship in PHL:  

**80-84        85-89         90-94        ****≥ 95**
**         ****Maximum Temperature (F)**

- Temperature-O3 Relationship in PHL:
- Distribution of O3 for Given Temperature Ranges (1997-2002)
- Arrows show mean O3 for temperature range for 2003-2006.

- Box is interquartile
- (25-75%) range

## After 2003, Almost All High O3 Cases are Limited to Code Orange

- Percentage of monitors
- exceeding the Code
- Orange threshold
- (85 ppbv) that **also**
- exceed 100 ppbv.
- 1994-2003: 27%
- 2004-2006:  5%

**Notes:**
1994-2002:  27%
2003-2006:  15%
2004-2006:  5%

## Shenandoah National Park O3

- Mean Daily 8-Hour
- Maximum O3
**May-September**
-      1994-2002:  60 ppbv
-      2003-2006:  54 ppbv
- 	***15% reduction***
**June-August**
-      1994-2002:  61 ppbv
-      2003-2006:  55 ppbv
- 	***15% reduction***

## Large Reduction in Frequency and Spatial Extent of High O3 Periods at SNP

- Average Number of Days
- with 1-hour O3 ≥ 70 ppbv:
-      1994-2002:  38
-      2003-2006:  12
-        ***224% Reduction***
- Average Number of Hours
- with O3 ≥ 70 ppbv:
-      1994-2002:  392
-      2003-2006:  106
-        ***268% Reduction***

## Effect on Forecasts (1)

- PHL regression model forecast bias for concentration bins of observed
- peak 8-hour O3 (Model R0302)

## Effect on Statistical Forecasts (2)

- Same as in previous slide but for another PHL statistical model (Ln2001)

## Effect on NOAA Numerical Forecast Model

- NOAA Forecast Model
- Assumes Large NOx Reductions

## Verification During Summer, 2006:  PHL Domain Maximum O3 

- Bias + 3.1 ppbv
- Mean absolute error 8.5 ppbv and median absolute error 6.0 ppbv.
- Best statistical model for same days:  Bias = +4.9 ppbv, Mean AE = 9.1 ppbv, Median AE = 7.7 ppbv.
- Performance in PHL is good compared to statistical models and does not under-predict.

## Performance in High O3 Cases

- Model results not available for two cases.
- Correctly forecast Code Orange cases on 14 of 17 days (Consensus forecast 13/17).
- Cost of only 3 False Alarms (convection an issue in one case).
- Under-predicted 2 Code Red cases but did not wildly over-predict during heat wave of July 31-August 3.

## Domain Maximum Ozone:  PHL

## Monitor Specific Forecasts

- For set of 9 monitors:
- Range of Bias:  - 2 to + 6.8 ppbv
- Underpredicted at PNE (urban) and overpredicted at Collier’s Mills (exurban)
- Range of Mean AE:  8.6-11.7 ppbv
- Best at Fair Hill (MD) and worst at PNE.
- Range of Median AE:  6-8 ppbv
- Best at Rider, NJ along I-95 Corridor.

## Further Reductions Likely with CAIR

## Conclusions

- Preliminary observations suggest that NOx SIP Rule has reduced urban scale as well as regional scale O3 concentrations.
- Effect is seen most dramatically in frequency and extent of high O3 cases.
- Impact on statistical forecast guidance is limited – on the order of a few ppbv.
- Numerical models that adjust for NOx reductions perform adequately.

## Acknowledgements

- Thanks to Amy Huff (Penn State) for forecasting assistance and to Chad Bahrmann (Penn State) for analysis of NOAA model data.
- Thanks to the Delaware Valley Regional Planning Commission (DVRPC) and member states (DE, PA, NJ) for their support of air quality forecasting.