•  ATMOSPHERIC CHEMISTRY
and AEROSOLS
Peter Hess
Cornell University
•  WHOLE ATMOSPHERE
COMMUNITY CLIMATE MODEL
Michael Mills
NCAR
Chemical Effluents to the Atmosphere Where does it go? What are the impacts? What are the processes to be modeled? Where do Pollutants Go? -­‐Chemically transformed -­‐Deposited onto surface through contact (dry deposi;on) -­‐Dissolved in rain and deposited onto surface (wet deposi;on)   How are these processes simulated in a CESM ?
Atmospheric Chemistry and Aerosols - Climate – Biosphere - Hydrological Cycle-
Wetland Emissions (CH4)
Soil Emissions (NO, N2O)
Biogenic Emissions
Earth System •
Paths to sustainability often involve chemically active species
- Biofuels: CO2 , N2O
•
Climate – Health – Air Pollution Interactions
- Emission Tradeoffs
Radiative Impacts (1)
RF (w/m2)
CO2:
1.66
Ozone:
0.35
Methane: 0.48
N2O:
0.16
CFCs:
0.34
GWP
1.0
25
298
100 - >10000
Radiative Impacts (2)
AEROSOLS
Smoke from forest fires burning in
Alaska and the Yukon, travelling into the
Arctic over ice-covered areas
Partly absorbing dust aerosol
downwind of Sahara
Absorbing aerosols (black carbon, dust) warm the climate by absorbing solar
Radiation, other aerosols (sulfate) cool the climate by reflecting solar radiation
NET FORCING: -0.5 W/m2
Radiative Impacts (3)
Indirect Effect Ramanthan et al., Science, 2001
Radiative Impacts (4)
Indirect Effects:
-Clouds Brighter
-Precipitation Suppressed:
More Persistent Clouds
N ~ 100 cm-3
W ~ 0.75 g m-3
re ~ 10.5 µm
N ~ 40 cm-3
W ~ 0.30 g m-3
re ~ 11.2 µm
from D. Rosenfeld
NET FORCING: -0.7 W/m2
Radiative Impacts (5)
SATELLITE IMAGES OF SHIP TRACKS NASA, 2002
Atlantic, France, Spain
AVHRR, 27. Sept. 1987, 22:45 GMT
US-west coast
Radiative Impacts (6)
  Direct radiaFve forcing: ozone and methane, aerosols   Aerosol indirect effects Radiative Impacts (7)
Chemistry to climate Biogeochemical Impacts (1)
Ozone -Detrimental for plants and crops•  Approximately a 20-30% reduction of winter wheat in the Yangtze
Delta region due to ozone exposure (Huixang et al)
Biogeochemical Impacts (2)
Ozone and vegetaFon Radiative impact of ozone on CO2 cycle may exceed its direct radiative impact (-0.35 W/m^2)
Sitch et al., 2007
Biogeochemical Impacts (3)
Nitrogen DeposiFon and Response of Carbon Data from 20,067 plots
remeasured during the early
1980s to mid-1990s by the US
Forest Service Forest
Inventory and Analysis (FIA)
Program
-Quinn Thomas, Nature Geoscience
Biogeochemical Impacts (3)
Diffuse FracFon of RadiaFon Simulated percentage change
(colour scale) in diffuse fraction
between 1950 and 1980
Mercado et al., 2009
Diffuse fraction contribution to
land carbon accumulation
between 1950 and 1980
(grams C/m^2-year)
Model Specification
∂µ/ ∂t = Explicit
Transport
·
V µ +T + Ω µ + S(x,y,z,t) + L
Param.
Chemistry Emissions Physical
Losses
Transport
µ: vector of constituents, typically ~100
V: velocity field
Ω: reaction matrix: reaction coefficients, photolysis rates,
species concentrations
S: emissions
L: physical losses: dry and wet deposition
Emissions  Chemistry  Physical Losses
Emissions Natural
Lightning (NO)
Wetlands (CH4)
Trees (VOCs)
Soils (NO)
Anthropogenic
-Biomass Burning
-Agriculture
- NH3, CH4, N2O,
-Landuse Change
Combustion (NO, CO)
--Cars, Factories
Emission Specification:
-User-specified netcdf files -No explicit response to climate change
• Namelist Control Parameter
-Lightning, calculated internally
• Strength Namelist Control Parameter
OR
Emissions  Chemistry  Physical Losses
InteracFve Emissions Atmosphere Atmospheric Feedback
-Temperature
-Precipitation
-Chemical Deposition
Emissions Interactive Emissions in Model
Lightning, Biogenic VOC, Biomass burning, Soil NO (partially)
Interactive Emissions in Development
Methane, Full Suite of Odd Nitrogen
Future
Human component?
Emissions  Chemistry  Physical Losses
• Chemistry consists of highly coupled stiff differential equations
d[NO2]/dt = k1[NO][O3] + k2[NO][HO2] –j[NO2] –k4[NO2][OH]+…
d[HO2]/dt = k5[CO][OH] – k2[NO][HO2] –k6[HO2][O3] + …
-> increases cost by ~ 5x for reasonably complex mechanisms
• Vastly different time-scales [O(sec) – O(years)] occur in chemical
equations
• Coupled equations solved w/ implicit and explicit solvers
• Chemical mechanism (i.e., the selected chemistry) is a parameterization of
the full chemistry
• Selection depends on the problem addressed
Emissions  Chemistry  Physical Losses
Deposition
not known
rate
uncertain
to ~10x
yield
not
known
Deposition
not known
yield uncertain
by ~2
Thousands of
Atmospheric
Reactions:
Isoprene ~50,000
Emissions  Chemistry  Physical Losses
Select Chemical Mechanism (problem dependent) i) Predefined mechanism in build configura;on -chem trop_mozart | trop_ghg | trop_bam | trop_mam3 |
trop_mam7 | waccm_mozart | waccm_ghg | super_fast_llnl | none ii) User-­‐specified mechanism defined in build -usr_mech_infile $mechanism_file   Allow user to specify a customized preprocessor input file   Determines the number of advected tracers Emissions  Chemistry  Deposition
Example of preprocessor input file mechanism file:
SPECIES
Solution
CO
End Solution
Fixed
OH
End Fixed
END SPECIES
CHEMISTRY
Reactions
[usr8] CO + OH -> CO2 + HO2
End Reactions
Ext Forcing
CO<-dataset
End Ext Forcing
END CHEMISTRY
Emissions  Chemistry  Physical Losses
Preprocessor Preprocessor input file Preprocessor Chemistry code Build CAM-­‐chem Emissions  Chemistry  Physical Losses
DeposiFon processes •  Dry deposiFon: uptake of chemical consFtuents by plants and soil (handled by CLM), water -­‐Depends: species solubility, reacFvity, surface characterisFcs, meteorology -­‐Impacted species: Namelist control parameter •  Wet deposiFon: uptake of chemical consFtuents in rain or ice (linked to precipitaFon, both large-­‐scale and convecFve) -­‐ Depends: species solubility -­‐Impacted species: Namelist control parameter Aerosols (1)
Precursor
Emissions
AEROSOLS Aerosol Microphysics
Primary
Emissions
Deposition
(wet, dry)
Aerosols (2)
Bulk Aerosol Model (BAM)
•  External mixtures of all important aerosol types: 26
sulfate, sea salt, dust, hydrophobic and hydrophilic OC & BC •  PredicFon of aerosol mass •  Number proporFonal to mass   Prescribed size distribuFon •  Aerosol aging set diagnosFcally (through a Fmescale) •  Coupled to 2-­‐moment cloud microphysics •  Tuned to produce an acceptable climate Aerosols (3)
Benchmark 7-Mode Modal Aerosol Model (MAM)
Simplied 3-Mode Scheme also implemented
Accumulation
number
sulfate
ammonium
secondary OM
hydrophobic OM
BC
sea salt
Aitken
number
sulfate
ammmonium
secondary OM
sea salt
Fine Soil Dust
number
soil dust
sulfate
ammonium
Fine Sea Salt
number
sea salt
sulfate
ammonium
Coarse Soil Dust
number
soil dust
sulfate
ammonium
Coarse Sea Salt
number
sea salt
sulfate
ammonium
coagulation
condensation
All modes log-normal
with prescribed width.
Total transported
aerosol tracers: 31
Primary Carbon
number
hydrophobic OM
BC
Cloud-borne aerosol
and aerosol water
predicted but not
27
transported.
7-mode: Computer time is ~100% higher than BAM
3-mode: Computer time is ~30% higher than BAM
Aerosols (4)
•
•
•
•
•
•
•
•
•
•
Changes w/ Modal Formulation
Prediction of Number and Mass
Consistent coupling with Morrison-Gettlemen
microphysics
Consistent simulation of the indirect effect (-­‐1.0 to -­‐1.8 W/m2)
Aging of primary carbon to accumulation mode based on
sulfate coating from condensation & coagulation
Radiation based on mixed phase aerosols (from Ghan and
Zaverhi, 2007)
Coagulation within, between modes
Dynamic condensation of trace gas (H2SO4, NH3) on
aerosols
New particle formation (in UT and BL)
Ultrafine sea salt emissions from Martensson et al.
A new secondary organic aerosol treatment: reversible
condensation of SOA (gas)
Example of build configuraFon Predefined chemistry packages:
-chem trop_mozart | trop_ghg | trop_bam | trop_mam3 |
trop_mam7 | waccm_mozart | waccm_ghg |
super_fast_llnl | none
Predefined bulk aerosol/GHG packages:
-prog_species
CARBON16
SO4 | DST | SSLT | OC | BC | GHG |
Configure will generate a preprocessor input file for any combination
of these predefined prognostic aerosol and GHG packages.
Examples: Chemistry-Climate Interactions (1)
Temperature
Ozone Exceedances
Netherlands: 1000-­‐1400 deaths, 400–
600 air polluFon-­‐related deaths (Fischer et al.) Driven by: stagnation, biogenic
hydrocarbon emissions, forest
fires, chemistry Examples: Chemistry-Climate Interactions (2)
Examples: Chemistry-Climate Interactions (3)
O3 (Ozone) OH hν NO2 h ν, H2O NO Hydrocarbon OxidaFon <.1 pptv HO2 CO, CH4 1.8 ppm CO2, H2O Examples: Chemistry-Climate Interactions (4)
2030: GHG Increase + MFR Aerosols 2030: GHG Increase Only Kloster et al., 2009 Examples: Chemistry-Climate Interactions (4)
Climate amplifier due
CH4 emissions from
wetlands
Examples: Chemistry-Climate Interactions (5)
Change in Soil Temperature, 2050, GFDL
-permafrost melting, permafrost pool ~1/3 global soil carbon
-additional emission of 1-4 PC/year over 100 years if ½ permafrost thaws
-release of CO2 or CH4
-CH4 favored in wet conditions
‘World is running out of
nitrogen…’
Sir William Crooks, president
of the British Association for
the Advancement of Science
Haber-Bosch
BNF
Slide courtesy Marina Molodvskaya
Namelist control parameters •
•
•
•
•
•
•
Photolysis rates: LUT or inline Surface emissions/Other sources Species affected by dry deposiFon Species affected by wet deposiFon Lightning strength Lower boundary condiFons Stratosphere overwriFng Possibility of using observed meteorology (campaign) •  Goal: use meteorological fields as close as possible to observed condiFons •  Method 1) CAM: processing of meteorological fields through dynamical core 2) WACCM: relaxaFon Chemistry in CAM •  Must be done in FV dynamical core (tracer conservaFon) •  Requires to build CAM with specific opFon •  Requires use of pre-­‐defined chemistry or user-­‐
specified