Background O3 Scientific Assessment Workshop Denver, March 28-29, 2017

Tom Moore, WESTAR-WRAP

Photo of LA smog from citiesspeak.org

High ozone day in Gothic, Colorado

High ozone day in southern California

High ozone day in western U.S.

Definitions • U.S. background O3 (USBO): O3 formed from all natural sources plus

anthropogenic sources in countries outside the U.S. , plus impacts from CH4.

• North American Background (NAB) is defined as O3 formed from all natural sources plus anthropogenic sources in countries outside North America, plus impacts from CH4.

• USB and NAB must be determined using chemical transport models or source apportionment.

• Baseline O3: O3 measured at relatively remote sites that have little or no recent influence from US domestic emissions.

• Non-Controllable O3 sources (NCOS): These are sources of O3, or its precursors, that could not be reasonably controlled by domestic legislation. Examples of NCOS are intrusions of stratospheric air or emissions from wildfires.

• All of the terms above can be expressed as seasonal, monthly or daily means, maximum daily 8-hour averages (MDA8) or using other statistical metrics.

Goals for this assessment • Summarize key spatial and temporal patterns of baseline O3. • Review published work on USBO for the continental U.S. and

summarize consistent and robust patterns. • Identify discrepancies between estimates of USBO and, if

possible, the causes for these discrepancies. • Examine different approaches used to get USBO and

evaluate strengths/weaknesses of these approaches. • Examine evidence for NCOS and their role in daily and

seasonal O3 concentrations. • Review methods to quantify NCOS and evaluate

strengths/weaknesses of each approach. • Develop a set of recommendations for future research in this

area. • Emphasis on new research since 2011 since NAS and UT-

Austin assessments.

BOSA Core Team • Prof. Dan Jaffe (University of Washington) • Dr. Owen Cooper (University of Colorado /NOAA ESRL) • Prof. Arlene Fiore (Columbia University) • Dr. Barron Henderson (EPA OAQPS) • Prof. Daven Henze (University of Colorado) • Dr. Andrew Langford (NOAA-ESRL) • Dr. Meiyun Lin (Princeton University / NOAA GFDL) • Mr. Tom Moore (WESTAR-WRAP) • Dr. Gail Tonnesen (EPA Region 8) • Prof. Ted Russell (Georgia Institute of Technology) Our goal is submission of critical review paper to EST or other journal by end of Summer 2017.

Why does background O3 matter? • Background O3 represents the endpoint in health and

ecosystem risk analysis or cost-benefit analyses as emissions are reduced;

• Knowledge on background O3 is needed to set reasonable and achievable air quality standards;

• Knowledge on background O3 and non-controllable sources is needed to determine when exceedances might be beyond local control.

• A model's ability to capture baseline ozone indicates that we are capturing the key processes and increases our confidence in assessing reduction strategies for O3 as well as other air pollutants.

Baseline concentrations of tropospheric O3 have risen above pre-industrial levels by 40 - 100%.

‘Imported’ pollution mixes to the surface and contributes to increased concentrations of O3 over populated regions, with detrimental impacts on human health and ecosystems.

U.S. NAAQS O3 violations are caused primarily by domestic emissions, but concentrations are augmented by the changing baseline and episodic non-domestic sources. The influence of imported O3 will become more acute if the US NAAQS continues to get tighter and background concentrations increase due to increasing emissions in developing countries.

National Academy of Sciences (2009) selected findings on O3

Changing O3 NAAQS: 1979: 120 ppb -1 hr 1997: 85 ppb - 8 hr 2008: 75 ppb - 8 hr 2015: 70 ppb - 8 hr

UT Panel: Policy and Research Findings on O3 (McDonald-Buller 2011)

Research recommendations: • Multi-model comparisons; • Better integration of modeling and baseline observations

(obs at “Relatively remove sites”); • Observations on commercial aircraft in the U.S. Policy recommendations: Clarity on definition of background O3; Need for improved knowledge on BGO including spatial and

inter-annual variability and significance w.r.t. standards; Better communication between federal and state agencies

on BGO.

Goals for the Denver Workshop • Provide a forum for broader input to the assessment from all

knowledgeable experts; • Provide a forum for discussion of key uncertainties; • Identify new methods and tools that the core group might not be

aware of; • Identify specific scientific publications that we may have missed; • Make specific recommendations for future research that the

committee should consider.

• Approximately 150 participants (~50% in-person/~50% online); • 18 oral presentations+ handful of posters; • Extensive time for discussion.

Current US Design Values vs Altitude

Design Values for 2013-2015 (3-year average of annual 4th highest)

Mt. Bachelor

Key questions/controversies • All models have uncertainties and biases. Can we develop an estimate of

uncertainty for model derived estimates of USBO? What are the assumptions made in using “relative response” method and are these assumptions valid?

• Trends in O3 are complex and depend on location and period of record. Can we reconcile observed trends with changes in emissions, climate, wildfires, etc? Why are there strong downward trends at California sites, but essentially no trends at sites downwind?

• Regional modeling of controllable sources depends critically on boundary conditions. So propagation of boundary uncertainties can cause significant problems for regional modeling.

• We generally assume that USBO requires a model. David Parrish presented a method that derives USBO from observations and gets much higher values, eg USBO DVs of 60-72 for sites in California. Is this reasonable? What assumptions are inherent in this approach?

• NCOS include stratospheric influence, wildfires and international transport. Models are starting to show good progress for capturing strat influence on surface O3, but not from wildfires. How can we improve our estimates of NCOS on a daily basis?

• While current satellites have little sensitivity to key species in the BL, how can we utilize current and future satellite data to improve our estimates of O3 sources?

AM3 (~2°x2°)

GEOS-Chem (½°x⅔°)

AM3: More O3-strat + PBL-FT exchange? Too high over some regions

GC: More lightning NOx (~10x over SWUS; too high)

Summer (JJA)

Spring (MAM)

ppb

Model estimates of North American background for 2006: zero out method (from Arlene Fiore, Columbia)

Usually highest in WUS, at altitude Differences/uncertainty associated with influences from lightning NOx,

fires, stratosphere, isoprene chemistry Fiore et al., Atm. Env., 2014

J. Oberman

Las Vegas Ozone Study (LVOS) From Andy Langford, NOAA

NOAA/NESDIS RAQMS model (Brad Pierce) and NOAA/GFDL AM3 model (Meiyun Lin) FLEXPART (Jerome Brioude and Stephanie Evan)

RAQMS and AM3 bracket the observed values.

AM3 and FLEXPART find STT contribution of 20-40 ppbv on May 24-25.

Simultaneous model bias at rural-urban sites in regional models simulations show that “background“ like cause the observed bias (Barron Henderson, EPA)

WRF model over-predictions of O3 Baker et al 2016

Sensitivity runs (in blue) used reduced photolysis rates, but this had little impact on over-prediction. This reflects complexity substantial complexity in modeling smoke plumes.

Fires, HMS Smoke and PM2.5 for Aug 20, 2015

Graphics from AIRNOW-Tech site. PM2.5 with HMS smoke product.

The observations show that PM decreases away from the fire.

MDA8 O3 for 8/20/15 with HMS Smoke overlay

The observations show that O3 increases away from the fire. Highest in urban centers. Models do not usually capture this correctly.

<55 ppbv 56-71 ppbv 72-85 ppbv

Work of Dan Jaffe, University of Washington

Estimated wildfire contribution to MDA8 for Aug. 20, 2015

-1

+13 +11

+6 +7 +16 +14

The wildfire O3 is estimated using a “Generalized Additive Model” (GAM) that calculates O3 as a function of numerous meteorological variables. The residual is an estimate of the additional O3 that is not considered by the model (Gong, Jaffe et al 2017)

BG O3 Assessment: draft summary recommendations 1. Continue to improve observation network:

a) Low cost improvements; b) Improvements requiring larger investments;

2. Better coordination within and between experimentalists and modeling groups;

3. Improved use of existing data to evaluate, for example, key discrepancies in our understanding of USBO, statistical relationships between tracers and meteorological conditions, etc.

4. Targeted studies on background O3; 5. Continue to improve models; 6. Models should be extensively evaluated with observations that

are most relevant to the application; 7. Need for planning and integration of future satellite observations; 8. Need further development of integrated air quality management

systems.