A Modeling Investigation of the A Modeling Investigation of the Climate Effects of Air PollutantsClimate Effects of Air Pollutants

Aijun XiuAijun Xiu11, Rohit Mathur, Rohit Mathur22, Adel Hanna, Adel Hanna11, , Uma ShankarUma Shankar11, Frank Binkowski, Frank Binkowski11, Carlie , Carlie

CoatsCoats33

1. University of North Carolina at Chapel Hill1. University of North Carolina at Chapel Hill2. ASMD, ARL/NOAA, NERL/US EPA2. ASMD, ARL/NOAA, NERL/US EPA

3. Baron Advanced Meteorological Systems3. Baron Advanced Meteorological Systems

Presentation TopicsPresentation Topics

• Air quality modeling componentsAir quality modeling components• What is non-integrated meteorology/chemistry What is non-integrated meteorology/chemistry

modeling?modeling?• The integrated meteorology/chemistry modelThe integrated meteorology/chemistry model• Optical properties of aerosols and radiative feedbackOptical properties of aerosols and radiative feedback• Case study simulation for July 1995 episodeCase study simulation for July 1995 episode• Analysis (model vs. observations) and evaluationAnalysis (model vs. observations) and evaluation• Summary and on going researchSummary and on going research

Offline Air Quality ModelingOffline Air Quality Modeling

CTM (MAQSIP, CMAQ)

Advection, Chemical TransformTurbulence and Diffusion, Dry

Deposition, Wet Deposition, Clouds;Aqueous Chemistry

Met. CoupleMCPL, MCIP

MeteorologyMM5

Emissions ProcessingSMOKE

Typical Air Quality Modeling Typical Air Quality Modeling ApproachApproach

• Meteorological data are prepared offline and used as input Meteorological data are prepared offline and used as input to the chemistry transport modelto the chemistry transport model

• Meteorological model outputs are processed to comply Meteorological model outputs are processed to comply with the chemistry-transport formatwith the chemistry-transport format

• Meteorological data output are less frequent than internal Meteorological data output are less frequent than internal model time stepmodel time step

• Temporal interpolation may lead to misleading results; Temporal interpolation may lead to misleading results; may not capture the evolution of the PBL or may cause may not capture the evolution of the PBL or may cause erroneous wind directionerroneous wind direction

• Physical inconsistencies may occur (e.g., mass Physical inconsistencies may occur (e.g., mass conservation if re-diagnosis of wind is required)conservation if re-diagnosis of wind is required)

• Radiative feedbacks of atmospheric constituents such as Radiative feedbacks of atmospheric constituents such as aerosols are not accounted foraerosols are not accounted for

ObjectivesObjectives

• Develop and apply an air quality modeling Develop and apply an air quality modeling system with integrated meteorology, system with integrated meteorology, emissions, and chemistry emissions, and chemistry

• Examine the feedback due to the direct effect Examine the feedback due to the direct effect of aerosolsof aerosols

• Provide a platform for air pollution/climate Provide a platform for air pollution/climate feedback studies, e.g., examination of the feedback studies, e.g., examination of the indirect effects of aerosols indirect effects of aerosols

Integrated Meteorology-Chemistry Integrated Meteorology-Chemistry ModelModel

CTM (MAQSIP)Advection, Chemical TransformTurbulence and Diffusion, Dry

Deposition, Wet Deposition, Clouds;Aqueous Chemistry

Met. CoupleMCPL

MeteorologyMM5

Emissions ProcessingSMOKE

Radiative Feedback of AerosolsRadiative Feedback of Aerosols

Multiscale Air Quality Simulation Multiscale Air Quality Simulation Platform (MAQSIP)Platform (MAQSIP)

• Modular/generalized coordinateModular/generalized coordinate• Prototype for Models3/CMAQPrototype for Models3/CMAQ• Gas-phase and heterogeneous chemistryGas-phase and heterogeneous chemistry

– Modified CBM-IV; modified QSSA, modal PM approachModified CBM-IV; modified QSSA, modal PM approach• Processes/modulesProcesses/modules

– Advection Bott’s schemeAdvection Bott’s scheme– Turbulent mixing; K-theoryTurbulent mixing; K-theory– Clouds/aqueous chemistry; Kuo and Kain and FritschClouds/aqueous chemistry; Kuo and Kain and Fritsch– Dry depositionDry deposition– Wet depositionWet deposition

Radiation SchemeRadiation Scheme

• CCM2 radiation scheme in MM5CCM2 radiation scheme in MM5• Delta-Eddington approximation to calculate solar Delta-Eddington approximation to calculate solar

absorption with the solar spectrum divided into 18 absorption with the solar spectrum divided into 18 discrete intervalsdiscrete intervals

• Absorption of OAbsorption of O33, CO, CO22, O, O22, and H, and H22OO• Scattering and absorption of cloud water dropletScattering and absorption of cloud water droplet• Direct radiative forcing of aerosols is included using Direct radiative forcing of aerosols is included using

Mie approximation to calculate scattering and Mie approximation to calculate scattering and extinction efficiencies using aerosol effective radius extinction efficiencies using aerosol effective radius and refractive indexand refractive index

Refractive IndexRefractive Index

• Refractive index is the particle optical property Refractive index is the particle optical property relative to the atmosphere and is used in the Mie relative to the atmosphere and is used in the Mie scattering calculation to provide optical propertiesscattering calculation to provide optical properties

• A complex number, the real part represents the A complex number, the real part represents the scattering and the imaginary part the absorbing scattering and the imaginary part the absorbing propertiesproperties

• In the integrated model, the refractive index is In the integrated model, the refractive index is calculated with the scattering and absorbing effects of calculated with the scattering and absorbing effects of a variety of aerosols (NHa variety of aerosols (NH44, SO, SO44, NO, NO33, H, H22O, organic O, organic aerosol, elemental carbon, and dust). Sea salt will be aerosol, elemental carbon, and dust). Sea salt will be included later.included later.

Case StudiesCase Studies36 km simulation36 km simulation

• Eastern US case study; 36 km horizontal grid Eastern US case study; 36 km horizontal grid resolution; 21 layersresolution; 21 layers

• July 2-15, 1995 periodJuly 2-15, 1995 period

• SMOKE; anthropogenic and biogenicSMOKE; anthropogenic and biogenic

• MAQSIP is called every MM5 time step (100 MAQSIP is called every MM5 time step (100 Seconds)Seconds)

• Three days model spin-upThree days model spin-up

Air Quality MonitoringAir Quality Monitoring

CASTNet IMPROVE

PM2.5PM2.5

0

5

10

15

20

25

30

0 5 10 15 20 25 30

IMPROVE

PM 2.5

y = 0.65x R2= 0.84

Observed (ug/m3)

SOSO44

0

5

10

15

20

25

0 5 10 15 20 25

SO4

CASTNetIMPROVE

y = -0.71 + 0.98x R2= 0.49

y = -1.7 + 1.2x R2= 0.83

Observed (ug/m3)

NHNH44

0

1

2

3

4

5

0 1 2 3 4 5

NH4

CASTNet

Model (ug/m3)

NONO33

0

0.5

1

1.5

2

0 0.5 1 1.5 2

NO3

CASTNetIMPROVE

Observed (ug/m3)

Aerosol CompositionsAerosol Compositions

0

5

10

15

20

25

0 5 10 15 20 25

CASTNet

SO4NO3NH4

Observed (ug/m3)

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

CASTNet

SO4NO3NH4

Observed Fraction

Aerosol optical depth comparisons

Analysis of the Radiative FeedbackAnalysis of the Radiative Feedback

Short Wave Radiation Boundary Layer Average(No Feedback – Feedback) PM Fine Mass

Radiation FeedbackRadiation Feedback

Short Wave Radiation Boundary Layer Average(No Feedback – Feedback) PM particle size

Radiation FeedbackRadiation Feedback

Short Wave Radiation Boundary Layer Average(No Feedback – Feedback) Number Density

Reduction in Shortwave RadiationReduction in Shortwave Radiation

0

5

10

15

20

25

30

0 5 10 15

Re

duc

tion

in S

ho

rtw

ave

Ra

dia

tion

Re

ach

ing

the

Gro

un

d (W

/m2 )

Concentration (ug/m3)

0

5

10

15

20

25

30

0.05 0.1 0.15 0.2 0.25 0.3

Re

duc

tion

in S

ho

rtw

ave

Ra

dia

tion

Re

ach

ing

the

Gro

un

d (W

/m2 )

Diameter (um)

0

5

10

15

20

25

30

100 200 300 400 500 600

Re

duc

tion

in S

ho

rtw

ave

Ra

dia

tion

Re

ach

ing

the

Gro

un

d (W

/m2 )

Number Density (Number/cm3)

Concentration

Size

Number Density

SummarySummary

• Presented results from an episodic (10 days) Presented results from an episodic (10 days) integrated meteorology/chemistry regional scale integrated meteorology/chemistry regional scale modelmodel

• Comparisons with observations suggest the ability Comparisons with observations suggest the ability of the model to capture spatial gradients in of the model to capture spatial gradients in concentrationsconcentrations

• The model simulations show the direct effect of The model simulations show the direct effect of aerosols causing reduction in surface short-wave aerosols causing reduction in surface short-wave energy which contributes to lower planetary energy which contributes to lower planetary boundary layer (PBL) heightsboundary layer (PBL) heights

• The aerosol size distribution parameters (number The aerosol size distribution parameters (number and mean diameter) seem to be as important as and mean diameter) seem to be as important as mass concentration in the direct radiative forcingmass concentration in the direct radiative forcing

Ongoing/Future WorkOngoing/Future Work

• Studying the effects of 1995 Canadian Studying the effects of 1995 Canadian wildfireswildfires

• Application to the Indian subcontinent Application to the Indian subcontinent (NSF)(NSF)– Radiative effects of carbonaceous aerosolRadiative effects of carbonaceous aerosol– Comparisons with INDOEX measurementsComparisons with INDOEX measurements

• Study effects of aircraft emissions (NASA)Study effects of aircraft emissions (NASA)– Comparisons with SONEXComparisons with SONEX

R825388

Case Studies Case Studies 108 km simulation108 km simulation

• 1995 summer Canadian fire1995 summer Canadian fire• Canada and US domain; 108 km horizontal Canada and US domain; 108 km horizontal

resolution; 21 vertical layersresolution; 21 vertical layers• One month simulations (June 15 – July 15)One month simulations (June 15 – July 15)• SMOKE for anthropogenic and biogenic emissions SMOKE for anthropogenic and biogenic emissions • MAQSIP is called every MM5 time step (300 MAQSIP is called every MM5 time step (300

Seconds)Seconds)• Simulations with and without estimated wildfire Simulations with and without estimated wildfire

emissionsemissions– Speciated wildfire emissions scaled to CO emission Speciated wildfire emissions scaled to CO emission

estimates from McKeen et al. (2002)estimates from McKeen et al. (2002)

(a) CO (b) O3

(c) Carbonaceous particulate matter

Simulated increases in surface level concentration (difference between simulations with and without fire emissions) resulting from the transport and chemical evolution of emissions

from large Canadian forest fires at 1900 GMT on July 2, 1995.