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Modeling Analysis of Multi-Decadal Trends in Ozone and Precursor Species Across the Northern Hemisphere and the United States Rohit Mathur, Jia Xing, Daiwen Kang, Sergey Napelenok, Christian Hogrefe, Golam Sarwar, Jonathan Pleim Computational Exposure Division National Exposure Research Laboratory U.S. Environmental Protection Agency ENV-VISION Conference Washington, DC May 10-11, 2016 1

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Page 1: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Modeling Analysis of Multi-Decadal Trends in Ozone and Precursor Species Across the Northern Hemisphere and the United StatesRohit Mathur, Jia Xing, Daiwen Kang, Sergey Napelenok,

Christian Hogrefe, Golam Sarwar, Jonathan PleimComputational Exposure Division

National Exposure Research LaboratoryU.S. Environmental Protection Agency

ENV-VISION ConferenceWashington, DCMay 10-11, 2016 1

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Outline

• Importance of accounting for long-range transport (LRT) in regional air pollution analysis • Multi-decadal (1990-2010) trends in model & observed surface-level O3 across the northern hemisphere• Initial look at how changing emission patterns across the northern hemisphere may be impacting LRT and background pollution• A call for better observational characterization of LRT of pollution –an “aloft network”

2

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Motivation

3

Courtesy: P. Dolwick; (http://www.epa.gov/airtrends/values.html )

2013 8-Hour Ozone Design Values across the U.S.70-75ppb >75ppb

Tightening of air quality standards places greater emphasis on the ability of air quality models to simulate the entire spectrum of concentrations

The relative importance of “Background pollution” to the NAAQS becomes more important

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Model’s view of “Background” Pollution:Spatial Variability

4

“FT” fractional contribution to background

Modeled “background”

• Added diagnostic tracers to track impact of lateral boundary conditions: surface-3km (BL), 3km-model top (FT), top-model layer (ST) – mixing, transport, deposition mimics O3Summer average: 2006 O3 vertical profile at Huntsville, Alabama

Spatial variability in “background” value ~80% of the surface/BL background is

dictated by LRT occurring above the nominal daytime BL

Page 5: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Model’s view of “Background” Pollution:Temporal Variability

5

“Background” values vary on daily to seasonal time-scales Contributions of LRT and stratosphere vary seasonally

Seasonal variation in LBC Fractional Contribution to simulated O3 at Trinidad Head

Hourly Tracer Concentrations over the Four Corners Region

BLFT

ST

Page 6: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

WRF-CMAQ Coupled Model Setup

6

Horizontal• Northern Hemisphere

• Polar Stereographic projection• 108 km resolution (187x187)

• Nested CONUS: 36km resolutionVertical

• 44 layers between surface & 50mbEmissions

• NH: EDGARv4.2; Xing et al, 2015 (ACP)• CONUS: Xing et al., 2013 (ACP)

Time Period: 1990-2010

kg/km2/yr

Increa

se

Decrease

1990-2010 Emission Trends

NOx

NMVOC

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Simulated and Observed Trends in NO2 Column across the Northern Hemisphere:2003-2010

7

SCIAMACHY WRF-CMAQ 1015 molec/cm2/yr

• Model captures decrease in the U.S & increase in E. China and N. India• Discrepancies in Africa

Page 8: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Simulated and Observed Trends in NO2 Column across the U.S: 2003-2010

8

SCIAMACHY WRF-CMAQ

1015 molec/cm2/yr

2003

2010

Trend

1015 molec/cm2

Both observations & model show reductions in NO2 in urban areas and regionally

Model estimated NO2column as well as trend are lower than retrievals

Page 9: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

9

1990-2010 Trends in Surface O3 at Different Percentiles; 36km resolution DomainSpring (MAM) Summer (JJA)

5th Perc

entile

50th Perc

entile

Increa

sing T

rend

Decre

asing

Tren

d

Page 10: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Comparison of Model and Observed DM8hr O3 Trend at Different Percentiles: Seasonal Contrast at AQS sites in the U.S

10

Trend at 5th Percentile Trend at 50th Percentile Trend at 95th Percentile

During Spring, both model & observations show increases at lower end of the concentration distribution at majority of the sites

Summer trends at the median concentration and high ranges show decreases across majority of sites

Increasing trend at many locations during Spring

At the upper end of the concentration distribution, decreasing trends at most locations during the warmer months

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Comparison of Model and Observed DM8hr O3 Trend at Different Percentiles: Seasonal Contrast at CASTNET sites in the U.S

11

During Spring, both model & observations show increases at lower end of the concentration distribution at many sites

At the upper end of the concentration distribution, decreasing trends at most locations during the warmer months

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Impact of Resolution and Emission Improvements on Simulated Trends (JJA-avg at CASTNET)

12Finer resolution and improved emission trends results in better capturing spatial

variability in observed trends

Daily Max. 8-Hr O3

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Trends in Springtime DM8hr O3 at the Surface & Aloft

13

5th Percentile Trend at Surface 25th Percentile Trend at Surface

5th Percentile Trend at ~1.5km 25th Percentile Trend at ~1.5km

― Increasing trend in surface O3 at several CASTNET monitor locations in the western U.S.― Model simulations also show increasing trends at many of these locations

― Increasing trends aloft (~1.5km) suggestive of influence of LRT effects

Page 14: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Approach• Use the direct decoupled method

(DDM) to track sensitivity (Sj) of O3 to emissions from source region j

• Estimate long-range transport O3 to a receptor region n as

• Examine the relative contributions of the different source regions to the background for the receptor region

How do different source regions influence background pollution?

14

Seven source regions

(following the HTAP source region definitions)

njjS

NAMEUR/RUS

SASEAS/SEA

NAF/MDECAMOTH

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PBL & Seasonal-average O3 & Source-region Contributions : Spring 2006

FractionalContribution

Spring PBL Average O3

EUR+RUS

EAS+SEA

NAM

SASNAF+MDE STRAT

CAM

15

Page 16: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Are changing emission patterns impacting LRT and background pollution-levels?

16

Combine:Single-year source sensitivities

+Multi-decadal Emission and Concentration Changes

,   

 

Concentration due to LRT at cells in receptor m for year N approximated as:

first-order Taylor series

re-normalizing factor

Sj – normalized sensitivityΔEj – Emission changeCN – simulated conc. for year N

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Approximate O3 from Long-Range Transport: SpringSeasonal and PBL mean

17

1990 2000 2010

ppb/yr

Preliminary Results

1990 – 2010 Trend in LRT O3

Increasing contributions of LRT to surface O3 over the past two decades

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Need for Observational Information on LRTCharacterizing Nocturnal Aloft O3 is Important

18

WRAL Tower Observations, Raleigh, NC: 1996

NOAA BAO Tower, CO: 2014 DISCOVER-AQDecoupling of BL from residual layer

Well-mixed BL ― Surface O3 = Background [transport] + In-situ production

― Transport constitutes a large fraction of night time O3 in residual layer

― Local background influenced by downward mixing of O3 from the residual layer

Impact of Assimilation of Aloft O3Downwind of WRAL siteReduces over prediction (6/21)Reduces under prediction (6/22) O 3

(ppm)

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Can Lower Cost Technology Fill a Critical Observational Gap?

19

10m 215m 480mCMAQ estimated e-folding distance for nocturnal O3 (7 GMT, May-September 2010)

Location of tall towers (> 400m)

[Wikipedia: List of tallest structures in the world - 400-500 meters]

e-folding distances aloft nocturnally are several hundred of kilometers

Can existing tall structures be instrumented with “lower cost” sensors to provide a critical continuous aloft observation?

~20x20 array of aloft measurements

Page 20: D } o ] v P v o Ç ] } ( D µ o ] r o d v E } Z v , u ] Z Mathur_US EPA.pdf · d } ] À ] } v &rxuwhv\ 3 'rozlfn kwws zzz hsd jry dluwuhqgv ydoxhv kwpo î ì í ï ô r, } µ k Ì

Summary• Multi-decadal (1990-2010) model calculations suggest large (& contrasting) changes in tropospheric composition over the northern hemisphere

– Significant reductions in air pollution over N. America and western Europe and increases in large portions of Asia– Quantitative trends inferred from the model agree well with those from measurements

• The model is able to capture the changing seasonal distributions in surface O3in the U.S. during 1990-2010 arising from changing emissions and LRT– Increasing trends during Spring and Winter and at the lower end of concentration distributions

• Changing emission patterns across the northern hemisphere will impact background pollution in a region. Sensitivity analysis indicates that– the background is increasing in N. America and varies seasonally– the source region contributions and their relative importance also vary seasonally

• Measurements to characterize aloft transport (and subsequent downward mixing) are needed20


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