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Title: Modeling of Air Quality and Regional Climate Interactions


1
Modeling of Air Quality and Regional Climate
Interactions
  • Carey Jang, Sharon Phillips, Pat Dolwick, Norm
    Possiel, Tyler Fox
  • Air Quality Modeling Group, USEPA/OAQPS
  • Yang Zhang, Kai Wang, Yaosheng Chen
  • North Carolina State Univ.
  • CMAS Conference, Chapel Hill, NC, October 7, 2008

2
Background
  • Climate is emerging as an important factor in
    current integrated policy and one-atmosphere
    multi-pollutant air quality management
    perspectives
  • Recognize technical challenges to credibly
    address climate change for policy development
  • Linkages between global and regional/local
    systems
  • AQ-Climate interactions across physical,
    chemical, met, and econ disciplines

3
Objectives
  • Initiate EPA/OAQPS activities on climate-air
    quality interactions by leveraging efforts by ORD
    and scientific community to demonstrate
    capability for our regulatory assessments and
    inform policy relevant issues
  • 1. Conduct a proof of concept assessment of the
    potential impacts of climate change on regional
    air quality
  • 2. Conduct a preliminary modeling assessment of
    air pollution impacts on regional climate

4
Interactions of Air Quality and Regional Climate
Increased Temperature
Precipitation Changes
Cloud Changes
Transport Mixing Changes
Air Quality (PM, O3, Dep., etc.)
Changes to
and Feedbacks
5
OAQPS Climate-AQ Modeling
  • Potential Climate Impacts
  • on
  • Regional Air Quality

6
Current Future Climate Scenarios
  • Leveraged from EPA/ORD/NERLs Climate Impacts on
    Regional Air Quality (CIRAQ) Project (Gilliam
    and Cooter, 2007, Cooter et al., 2007, Gustafson
    and Leung, 2007, Nolte et al., 2007)
  • CIRAQ used global climate simulations from
    GISS-II model for 1950 2055, based on IPCC
    A1B SRES scenario (Mickley et al., GRL, 2004)
  • DOE/PNNL downscaled this GCM to
    Regional Climate Model (MM5) for the
    two periods of 1996-2005 and 2045-2055

IPCC SRES Scenario
A1B
7
Modeling of Climate Impact on AQ
  • Use downscaled regional meteorology for two
    CMAQ 5-year simulations
  • Current years 1999-2003
  • Future years 2048-2052
  • Emissions
  • 2002 Current Base Case
  • 2030 Future Control Scenarios
  • (National Control Programs)
  • CMAQ Configuration
  • CMAQ (version 4.6) Continental U.S. domain
    with 36-km resolution 14 vertical layers

Regional Downscaling of Met
8
Modeling Analysis Approach
  • Objectives
  • Climate Impacts on AQ and National Control
    Programs
  • Temporal
  • 5-year Ensemble
  • Annual
  • Seasonal
  • O3 season
  • (5, 6, 7, 8, 9)
  • PM quarterly
  • Monthly
  • Daily (time series)
  • Spatial
  • National
  • Regions
  • Northeast (NE), Southeast (SE), Midwest
    (MW), Central (CN), West (WE)

NE
CN
WE
MW
SE
9
  • Proof of Concept Modeling
  • Climate Impact on Air Quality Ozone Results

10
Summer Ozone (8-hr max 5-month avg.)2002 Base
w/ Current Climate
Summer 2002
Summer 1999
Summer 2003
Summer 2000
Ensemble (1999-2003)
Summer 2001
11
Summer Ozone (8-hr max 5-month avg.) 5-yr
Ensemble Meteorology
2030 Control Scenario w/ Current Climate
2002 Base w/ Current Climate
2030 Control Scenario w/ Future Climate
12
Climate Impact on Summer Ozone 2030 Control
Scenario (Future Current Climate)
Temperature (summer)
Future
Current
Precipitation (Summer)
Climate Penalty? Climate Benefit?
Caveat Confidence needs to be build on
predicting climate scenarios
13
Climate Impact on Summer Ozone 2030 Control
Scenario (Future Current Climate)
May
July
June
August
14
  • Proof of Concept Modeling
  • Climate Impact on Air Quality PM 2.5 Results

15
Annual Average PM2.5 5-yr Ensemble Meteorology
2030 Control Scenario w/ Current Climate
2002 Base w/ Current Climate
2030 Control Scenario w/ Future Climate
16
Climate Impact on Annual PM2.5 2030 Control
Scenario (Future Current Climate)
Caveat The results are highly subject to
underlying uncertainties of predicted current
and future climate scenarios
17
Climate Impact on Seasonal PM2.5 2030 Control
Scenario (Future Current Climate)
Winter
Summer
Spring
Fall
18
Climate Impact on PM2.5 (Summer)
D PM 2.5 (2030 future current)
Climate penalty? Climate benefit?
Confidence needs to be built on
predicting climate scenarios!
Precipitation
19
OAQPS Climate-AQ Modeling
  • Air Pollution Impacts
  • on
  • Regional Climate

20
Air Pollution Impacts on Climate
  • Direct Effects
  • Directly affects net solar radiation and
    photolysis (mainly PM species, e.g., sulfate PM
    induced cooling-scattering, Black Carbon induced
    warming-absorption, etc.)
  • Semi-direct Effects
  • Affects PBL meteorology, such as vertical mixing,
    temperature profile, atmospheric stability,
    winds, etc., because of changes in radiation
  • Indirect Effects (evolving research)
  • Aerosols serve as CCN, reduce drop size and
    increase drop number, reflectivity, and optical
    depth of low level clouds (LLC)
  • Aerosols act as CCN (cloud condensation nuclei)
    to increase low-level cloud cover, but spread
    cloud water vapor and thus decrease the
    probability of rain fall
  • Aerosols (particularly BC) can absorb sun energy
    to increase cloud evaporation and thus reduce
    cloud cover and probability of rain fall

21
OAQPS Climate-AQ Modeling
  • Air Pollution Impacts on Regional Climate
  • Initiate applications of fully coupled
    meteorology/ chemistry models (e.g., WRF/CHEM,
    WRF/CMAQ)
  • Conduct a preliminary WRF/CHEM modeling to study
    direct, semi-direct and indirect effects of air
    pollutants on regional climate by removing
  • (1) All man-made emissions (Air pollution
    impacts)
  • (2) SO2 emissions
  • (3) NOx emissions
  • (4) EC/OC/VOC emissions

22
Modeling of AQ-Climate interactions using
WRF/Chem (2001 Jan./Jul. continental US
simulations)
  • Period 1-31 Jan. and 1-31 Jul. 2001
  • Domain 148 112 grid cells
  • Horizontal resolution 36 km
  • Vertical resolution 34 layers
  • Emissions
  • 1999 NEI (v3)
  • Sea salt online calculation
  • Meteorology IC and BC
  • NCEP/NCAR Global Reanalysis
  • Chemical IC and BC
  • Gas modified CMAQ
  • Aerosol default (1 mg m-3)
  • Gas-phase chemistry
  • CBM-Z
  • Aerosol module
  • MOSAIC
  • Cloud chemistry module
  • Pandis, 1998
  • Data for model evaluation
  • SEARCH T, RH, WS, WD, O3, PM2.5 comp.
  • CASTNET T, RH, WS, WD, O3, PM comp.
  • AIRS-AQS O3
  • IMPROVE PM2.5 and composition
  • STN T, PM2.5, and composition
  • MOPITT CO
  • GOME NO2
  • TOMS Tropospheric Ozone Residual (TOR)
  • MODIS AOD


23
D PM2.5 (unit ug/m3)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
24
D GSW (Net shortwave flux at ground surface,
unit W/m2)
All man-made reduction
NOx reduction
EC/OC/VOC reduction
SO2 reduction
Control Case Base Case (July 2001 monthly avg.)
25
D Photolysis (NO2 Photolysis Rate J value unit
sec-1)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
26
D Mixing Height (PBL Height, unit meter)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
27
D Temp (2-meter surface temperature, unit oC)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
28
D CNN (Cloud Condensation Nuclei /cm3,
supersaturation rate S0.1)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
29
D Precipitation (unit mm/day)
All man-made reduction
NOx reduction
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
30
Impacts of Air Pollution () (All Man-Made
Reduction)
D Photolysis (NO2)
D GSW (radiation)



SO2 reduction
EC/OC/VOC reduction
D Mixing Height (PBL)
D Temp (surface 2m)


Control Case Base Case (July 2001 monthly avg.)
31
  • Summary Climate and Air Quality have signifcant
    effects on each other through their complex
    interactions
  • Our "Proof-of-Concept" approach provides a useful
    means to understand the impacts of potential
    climate change on national control programs for
    O3/PM2.5 multi-pollutant control strategies
  • Climate change can have significant impacts on
    AQ however, confidence needs to be built on
    predicting climate scenarios
  • Air pollution can also have significant impacts
    on regional climate through its direct indirect
    effects
  • Air pollution can aggravate air pollution itself
  • Key Issues and Challenges
  • Linking global regional modeling systems
  • Future climate/met scenarios
  • Future emission/economy projections
  • AQ-climate coupled modeling research

32
ThanksThe Endjang.carey_at_epa.gov
33
Modeling of Climate Impact on AQ
  • CMAQ Configuration
  • CMAQ (version 4.6), Continental U.S. domain with
    36-km resolution 14 vertical layers
  • Meteorology downscaled from GCM
  • Obtained from EPAs CIRAQ Project used GISS-II
    global climate model for 1950 2055, based on
    IPCC A1B SRES scenario
  • DOE/PNNL downscaled this GCM to Regional Climate
    Model (RCM-MM5) for the two periods (1996-2005
    and 2045-2055)
  • Use downscaled regional met for two CMAQ
    5-year simulations
  • Current years 1999-2003
  • Future years 2048-2052
  • Emissions
  • 2002 Current Base Case
  • 2030 Future Control Scenarios

Regional Downscaling of Met
34
Climate and Air Quality Interactions
  • Climate is emerging as an important factor in
    current policy and multi-pollutant
    one-atmosphere air quality management
    perspectives
  • Policy-makers rely upon collaboration with
    scientific/academic research community for
    scientific research and model development
  • Technical challenges span across regulatory
    assessments
  • Linkages between global and regional/local
    systems
  • AQ-Climate interactions across physical,
    chemical, met, and econ disciplines

35
Objectives
  • Initiate climate-AQ interactions modeling
    activities by leveraging efforts in ORD
    scientific communities to address policy relevant
    issues
  • Conduct a proof-of-concept modeling assessment
    of impacts of potential climate change on
    regional AQ and national control programs
  • Conduct a preliminary modeling assessment of air
    pollution impacts on regional climate

36
Annual (5-yr ensemble) (Future Current)
Summer (5-yr ensemble) (Future Current)
2-m Temp (K)
2-m Temp (K)
Precip. ( diff)
Precip. ( diff)
Source EPA/ORDs CIRAQ Project
37
Annual Averages
Temperature
Precipitation
Current
Future
Current
Future
Cloud Cover
Humidity
38
D Ozone (O3)
NOx reduction
All man-made reduction
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
39
D PM2.5 (unit ug/m3)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
40
D GSW (Net shortwave flux at ground surface,
unit W/m2)
All man-made reduction
NOx reduction
EC/OC/VOC reduction
SO2 reduction
Control Case Base Case (July 2001 monthly avg.)
41
D Photolysis (NO2 Photolysis Rate J value unit
sec-1)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
42
D Mixing Height (PBL Height, unit meter)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
43
D Temp (2-meter surface temperature, unit 0C)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
44
D CNN (Cloud Condensation Nuclei /cm3,
supersaturation rate S0.1)
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
45
D Precipitation (unit mm/day)
All man-made reduction
NOx reduction
All man-made reduction
NOx reduction
SO2 reduction
EC/OC/VOC reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
46
Aerosols Affect Clouds Formation (indirect
effects)
Sulfate Aerosols Cloud Enhancer
Sulfate gases from Volcanic Eruption of Mt.
Anatahan (NASA, May 2003, Saipan)
Biomass Burning (BC/OC) as Cloud Killers
Brazil
By NASA Aqua/MODIS, September 2005
http//www.sciencedaily.com/releases/2006/07/06071
4082130.htm
47
Annual Average PM2.52002 Base w/ Current Climate
Annual CM4
Annual CM1
Annual CM5
Annual CM2
Ensemble (CM1-CM5)
Annual CM3
48
Annual Precipitation Anomalies (Current Future)
1999
2000
2001
2002
2003
2048
2049
2050
2051
2052
EPA/ORDs CIRAQ Project
49
Climate Impact on O3
Ozone
July
July Cloud Cover
June
June
June Cloud Cover
50
D Ozone (O3)
All man-made reduction
NOx reduction
All man-made reduction
NOx reduction
Redo with better scale (10 20 ppb)
SO2 reduction
EC/OC/VOC reduction
SO2 reduction
EC/OC/VOC reduction
Control Case Base Case (July 2001 monthly avg.)
51
Potential Impacts Ozone PM 2.5 References
Temperature (insolation) Temp. h, O3 h higher photochemical oxidation rates, biogenic VOC mobile emissions Temp. h, PM2.5 h higher sulfate organic PM because higher atm. oxidation Temp. h, PM2.5 i Lower winter nitrate PM because of HNO3/nitrate PM partioning Genenral (climate impacts on AQ) EPA GCAQ 2007 Interim Assessment Report (IAR) IPCC Climate Change 2007 WG-I to 4th IPCC Assessment report Camalier Cox, AE, 2007 Tagaris et al., JGR, 2007 Nolte et al., JGR, 2008 Steiner et al., JGR, 2006 Hogrefe et al., JGR, 2004 Temperature Fiore et al, JGR, 2005 Leung Gustafson, GRL, 2005 Sanderson et al, GRL, 2003 Cox Chu, AE, 1996 Clouds Precip. Langner et al, AE, 2005 Sanderson et al, AE, 2006 Stevenson et al., JGR, 2005 Humidity Liao et al, JGR, 2006 Wise et al., AE, 2005 Ventilation Mickley et al., GRL, 2004 Ellis et al, Climate Res., 2000 Pun et al., JAWMA, 2000 Feedbacks GAO 2003 CCAQ report Hansen, PNAS, 2001 Jacobson, Nature, 2001
Precipitation Precip. h, O3 i higher scavenging of O3 and precursors Precip. h, PM2.5 i higher scavenging of PM2.5 and precursors Genenral (climate impacts on AQ) EPA GCAQ 2007 Interim Assessment Report (IAR) IPCC Climate Change 2007 WG-I to 4th IPCC Assessment report Camalier Cox, AE, 2007 Tagaris et al., JGR, 2007 Nolte et al., JGR, 2008 Steiner et al., JGR, 2006 Hogrefe et al., JGR, 2004 Temperature Fiore et al, JGR, 2005 Leung Gustafson, GRL, 2005 Sanderson et al, GRL, 2003 Cox Chu, AE, 1996 Clouds Precip. Langner et al, AE, 2005 Sanderson et al, AE, 2006 Stevenson et al., JGR, 2005 Humidity Liao et al, JGR, 2006 Wise et al., AE, 2005 Ventilation Mickley et al., GRL, 2004 Ellis et al, Climate Res., 2000 Pun et al., JAWMA, 2000 Feedbacks GAO 2003 CCAQ report Hansen, PNAS, 2001 Jacobson, Nature, 2001
Clouds Clouds h, O3 i lower photochemistry/actinic flux of O3 and precursors Clouds h, PM2.5 h higher sulfate PM formation via aqueous chemistry Clouds h, PM2.5 i lower PM2.5 and precursors because of higher scavenging Genenral (climate impacts on AQ) EPA GCAQ 2007 Interim Assessment Report (IAR) IPCC Climate Change 2007 WG-I to 4th IPCC Assessment report Camalier Cox, AE, 2007 Tagaris et al., JGR, 2007 Nolte et al., JGR, 2008 Steiner et al., JGR, 2006 Hogrefe et al., JGR, 2004 Temperature Fiore et al, JGR, 2005 Leung Gustafson, GRL, 2005 Sanderson et al, GRL, 2003 Cox Chu, AE, 1996 Clouds Precip. Langner et al, AE, 2005 Sanderson et al, AE, 2006 Stevenson et al., JGR, 2005 Humidity Liao et al, JGR, 2006 Wise et al., AE, 2005 Ventilation Mickley et al., GRL, 2004 Ellis et al, Climate Res., 2000 Pun et al., JAWMA, 2000 Feedbacks GAO 2003 CCAQ report Hansen, PNAS, 2001 Jacobson, Nature, 2001
Humidity Humidity h, O3 h higher O3 because of higher availability of H2O OH radical (O1D H2O -gtOH) Humidity h, O3 i lower O3 humidity because of higher scavenging Humidity h, PM2.5 h higher sulfate PM formation because of higher aqueous chem Humidity h, PM2.5 i lower PM2.5 and precursors because of higher scavenging Genenral (climate impacts on AQ) EPA GCAQ 2007 Interim Assessment Report (IAR) IPCC Climate Change 2007 WG-I to 4th IPCC Assessment report Camalier Cox, AE, 2007 Tagaris et al., JGR, 2007 Nolte et al., JGR, 2008 Steiner et al., JGR, 2006 Hogrefe et al., JGR, 2004 Temperature Fiore et al, JGR, 2005 Leung Gustafson, GRL, 2005 Sanderson et al, GRL, 2003 Cox Chu, AE, 1996 Clouds Precip. Langner et al, AE, 2005 Sanderson et al, AE, 2006 Stevenson et al., JGR, 2005 Humidity Liao et al, JGR, 2006 Wise et al., AE, 2005 Ventilation Mickley et al., GRL, 2004 Ellis et al, Climate Res., 2000 Pun et al., JAWMA, 2000 Feedbacks GAO 2003 CCAQ report Hansen, PNAS, 2001 Jacobson, Nature, 2001
Ventilation (transport Mixing) Ventilation h, O3 i lower O3 because of higher mixing (less stagnant) transport downwinds Vent. h, PM2.5 i lower PM2.5 because of higher mixing (less stagnant) transport downwinds Genenral (climate impacts on AQ) EPA GCAQ 2007 Interim Assessment Report (IAR) IPCC Climate Change 2007 WG-I to 4th IPCC Assessment report Camalier Cox, AE, 2007 Tagaris et al., JGR, 2007 Nolte et al., JGR, 2008 Steiner et al., JGR, 2006 Hogrefe et al., JGR, 2004 Temperature Fiore et al, JGR, 2005 Leung Gustafson, GRL, 2005 Sanderson et al, GRL, 2003 Cox Chu, AE, 1996 Clouds Precip. Langner et al, AE, 2005 Sanderson et al, AE, 2006 Stevenson et al., JGR, 2005 Humidity Liao et al, JGR, 2006 Wise et al., AE, 2005 Ventilation Mickley et al., GRL, 2004 Ellis et al, Climate Res., 2000 Pun et al., JAWMA, 2000 Feedbacks GAO 2003 CCAQ report Hansen, PNAS, 2001 Jacobson, Nature, 2001
Feedbacks O3 h , Temp. h O3 is important GHG PM 2.5 h , Temp. h BC/OC is important GHG PM 2.5 h , Temp. i, Clouds h, Precip. i Effects of Sulfate nitrate aerosols Genenral (climate impacts on AQ) EPA GCAQ 2007 Interim Assessment Report (IAR) IPCC Climate Change 2007 WG-I to 4th IPCC Assessment report Camalier Cox, AE, 2007 Tagaris et al., JGR, 2007 Nolte et al., JGR, 2008 Steiner et al., JGR, 2006 Hogrefe et al., JGR, 2004 Temperature Fiore et al, JGR, 2005 Leung Gustafson, GRL, 2005 Sanderson et al, GRL, 2003 Cox Chu, AE, 1996 Clouds Precip. Langner et al, AE, 2005 Sanderson et al, AE, 2006 Stevenson et al., JGR, 2005 Humidity Liao et al, JGR, 2006 Wise et al., AE, 2005 Ventilation Mickley et al., GRL, 2004 Ellis et al, Climate Res., 2000 Pun et al., JAWMA, 2000 Feedbacks GAO 2003 CCAQ report Hansen, PNAS, 2001 Jacobson, Nature, 2001
52
Effects of Air Pollution July avg (WRF/Chem)
Direct Effects on NO2 Photolysis
Semi-Direct Effects on PBL Height
Indirect Effects on Precipitation
Absolute Difference
Absolute Difference
Absolute Difference
Difference
Difference
Difference
Courtesy of Dr. Yang Zhang from NCSU
53
Direct Effects of Air Pollution on NO2 Photolysis
PM2.5 Surface Mass
Jan.
July
Absolute Difference
Jan.
Absolute Difference
July
Difference
Difference
NO2 photolysis decreases over EUS in July, but
increases over WUS in July and over CONUS in Jan.
54
Semi-Direct Effects of Air Pollution on
Near-Surface Temperature (T2)
Jan.
July
Absolute Difference
Difference
T2 decreases over CONUS except for Pacific N.W.
in Jan./Jul. and western TX in Jan.
55
Semi-Direct Effects of Air Pollution on PBL
Height (Mixing Layer)
Jan.
July
Absolute Difference
Difference
PBL Height decreases over EUS, particularly in
July Less impact in Jan.
56
Indirect Effects of Air Pollution on Precipitation
July
Jan.
Absolute Difference
Difference
Precipitation changes in both ways, stronger
impacts in July
57
PM2.5 Species WRF/CHEM (July 2001)
SO4
NO3
PM2.5
BC
OC
NH4
58
PM2.5 Species WRF/CHEM (Jan. 2001)
SO4
NO3
PM2.5
BC
OC
NH4
59
Model Evaluation against Satellite Data Aerosol
Optical Depth (AOD)
July
Jan.
MODIS
WRF/Chem
Obs Sim N NMB, NME,
Jan. 0.168 0.042 1760 -75 76
Jul. 0.247 0.207 2219 -16 71
Statistics
60
Evaluation of WRF Meteorological Predictions
Jan. (Top) and Jul. (Bottom)
T2
Precipitation
RH2
Parameters CASTNET CASTNET SEARCH SEARCH STN STN NADP NADP
Jan. Jul. Jan. Jul. Jan. Jul. Jan. Jul.
T2 -14.3 0.6 -3.3 -1.5 0.4 -6.1 -- --
RH2 9.7 -0.9 -0.2 -1.2 -- -- -- --
WSP 90.6 79.9 40.4 30.5 -- -- -- --
WDR -9.0 0.9 -0.8 5.6 -- -- -- --
Precip. -- -- -- -- -- -- 27.4 32.2
NMB ()
61
Evaluation of Chemical Predictions Spatial
Distribution and Statistics of Surface O3 and
PM2.5
Jul.
Jan.
Max 8-h O3
24-h PM2.5
NMB ()
62
Evaluation of WRF/Chem. Predictions Column O3
Jul.
Jan.
TOMS
WRF/Chem
Obs Sim N NMB, NME,
Jan. 27.81 35.38 1464 2.0 13.9
Jul. 46.36 46.23 1464 4.2 10.6
Statistics
63
Evaluation of WRF/Chem. Predictions Aerosol
Optical Depth (AOD)
Jul.
Jan.
MODIS
WRF/Chem
Obs Sim N NMB, NME,
Jan. 0.168 0.042 1760 -75 76
Jul. 0.247 0.181 2219 -26.7 63.9
Statistics
64
Direct Effects of PM2.5 on Shortwave Radiation
and NO2 photolysis
PM2.5 Surface Mass
Shortwave Radiation
NO2 photolysis
Jan.
Jul.
PM2.5 decreases shortwave radiation over EUS in
Jan/Jul, but increases it over WUS in Jan PM2.5
increases NO2 photolysis over WUS in Jan/Jul, but
decreases it over EUS in Jul Strong seasonality
65
Indirect Effects of PM2.5 on CCN and Precipitation
PM2.5 Surface Mass
CCN (S1)
Precipitation
Jan.
Jul.
CCN is proportional to supersaturation and PM
mass conc. PM2.5 can affect precipitation in
both ways, with stronger impacts in Jul. PM2.5
indirect effects are stronger in Jul. than Jan.
and over EUS than WUS.
66
Case 2WRF/Chem Application for 2005 July China
  • Period 1-31 Jul. 2005
  • Domain 164 97 grid cells
  • Horizontal resolution 36 km
  • Vertical resolution 30 layers
  • Emissions
  • US EPA SED-JES
  • Sea salt online calculation
  • Meteorology IC and BC
  • NCEP/NCAR Global Reanalysis
  • Chemical IC and BC
  • CMAQ
  • Gas-phase chemistry
  • CBM-Z
  • Aerosol module
  • MOSAIC
  • Cloud chemistry module
  • Pandis, 1998
  • Scenarios
  • Met MetGas MetGasPMCld. Aq.
  • Data for model evaluation
  • China/NCDC T, RH, WS, Precip, PM, API
  • Japan (2078 sites) T, RH, WS, SO2, NO2, CO, O3,
    PM
  • MOPITT CO
  • OMI NO2
  • TOMS Tropospheric Ozone Residual (TOR)
  • MODIS AOD

67
Spatial Distributions of WRF Meteorological
Predictions
2-m Temperature (degree C)
2-m Specific Humidity (kg/kg)
Obs. vs. Sim.
NMB
68
Spatial Distributions of WRF Meteorological
Predictions
10-m Wind Speed (m/s)
Daily Total Precipitation (mm/day)
Obs. vs. Sim.
NMB
69
Temporal Variations of MM5/WRF Meteorological
Predictions
2-m Temperature
2-m Specific Humidity
Beijing
Shanghai
Guangzhou
70
Spatial Distributions of CMAQ and WRF/Chem
Predictions at Surface
Max 1-hr O3
24-hr average PM2.5
CMAQ
WRF/ Chem
71
Evaluation of CMAQ and WRF/Chem Predictions
Column CO
CMAQ
MOPITT
Statistics
WRF/Chem
of data Corr. RMSE NMB,
MM5/CMAQ 15908 0.62 21.6 -58.3
WRF/Chem 15908 0.52 19.4 -50.4
72
Evaluation of CMAQ and WRF/Chem Predictions
Column NO2
CMAQ
OMI
WRF/Chem
Statistics
of data Corr. RMSE NMB,
MM5/CMAQ 15908 0.61 1.68 -22.0
WRF/Chem 15908 0.64 1.89 16.3
73
Evaluation of CMAQ and WRF/Chem Predictions
Column O3
CMAQ
TOMS Tropospheric O3 Residual
WRF/Chem
Statistics
of data Corr. RMSE NMB,
MM5/CMAQ 15908 0.71 17.1 -35.2
WRF/Chem 15908 0.28 11.2 -18.2
74
Aerosol Direct Effects on Radiation and NO2
Photolysis
Direct Effects on NO2 Photolysis
Direct Effects on Shortwave Radiation
Absolute Difference
PM2.5 Mass
Percent Difference
PM2.5 decreases shortwave radiation over China
PM2.5 decreases NO2 photolysis over China except
for NW
75
Aerosol Semi-Direct Effects on Temperature and
PBL Height
Semi-Direct Effects on PBL Height
Semi-Direct Effects on 2-m Temperature
Absolute Difference
PM2.5 Mass
Percent Difference
PM2.5 slightly decreases 2-m temperature over
China PM2.5 affects 2-m specific humidity in
both ways
76
Aerosol Indirect Effects on Precipitation and CCN
PM2.5 Mass
CCN (S 1)
Changes in Precipitation
China
US
Higher CCN concentrations over larger areas in
China Dominancy of suppression of precipitation
over China, either ways over US
77
Examples and Evidences of Important Feedbacks
  • Effects of Meteorology and Climate on Gases and
    Aerosols
  • Changes in tropospheric vertical temperature
    structure affect transport of species
  • Changes in temperature, humidity, and
    precipitation directly affect species conc.
  • Changes in vegetation alter dry deposition and
    emission rates of biogenic species
  • Effects of Gases and Aerosols on Meteorology and
    Climate
  • Decrease net downward solar radiation and
    photolysis (direct effect)
  • Affect PBL meteorology (e.g., near-surface air
    temperature, RH, wind speed, PBL height, and
    atmospheric stability) (semi-direct effect)
  • Aerosols serve as CCN, reduce drop size and
    increase drop number, reflectivity, and optical
    depth of low level clouds (LLC) (the Twomey or
    first indirect effect)
  • Aerosols increase liquid water content,
    fractional cloudiness, and lifetime of LLC
    suppress/increase precipitation (the second
    indirect effect)
  • Evidence of Feedbacks
  • Satellite data have shown smoke from rain forest
    fires in tropical areas and burning of
    agricultural vegetations can inhibit rainfall by
    shutting off warm rain-forming processes
  • Enhanced rainfall was also found downwind of
    urban areas or large sources and over major urban
    areas

78
Air Pollution Impact on Regional Climate
Katrina Hurricane, 8/29/2005
Smog in Beijing, China (9/4/2004)
Beijing
NASA MODIS (3/2007)
Pollutants
Clouds
Zhejiang, China (Aug. 11, 2006) aftermath of
Saomei Super-typhoon
Air Pollution Impact on Radiative Forcing (direct
effect), Clouds/Rainfalls Weather (indirect
effect)
79
Particles as Cloud Killers (indirect effects)
Large plumes of smoke can act as "cloud killers"
because of aerosols indirect effects. NASA's
Aqua satellite caught this cloud-suppression
process in action over western Brazil and Bolivia.
Brazil
By NASA Aqua/MODIS, September 2005
http//www.sciencedaily.com/releases/2006/07/06071
4082130.htm
80
Texas
Particles as Cloud Killers it may be
happening in the U.S. too!
Mexico
Brazil
May 9, 2003 By NASA MODIS
fires
(Courtesy of Engel-Cox and Jill, Battelle
Memorial Institute)
By NASA Aqua/MODIS, September 2005
81
Comparison of Daily Max Temperature
Distributions(Downscaled vs. Retrospective Met
at 85 representative sites)
Retrospective Downscaled (2 years v. 2 years)
Retrospective Downscaled (2 years v. 5 years)
Downscaled
Retrospective
  • Downscaled meteorology generates more extreme
    conditions
  • more cool highs (lt 285K) and more warm highs
    (gt305K)
  • Downscaled meteorology generates 5x more days
    with max temperatures gt 310K ( 100F)
  • Future climate modeling tends to show that max
    temperatures will increase in the future
  • 90th percentile gt 310K
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