A Modeling Investigation of the Climate Effects of Air Pollutants Aijun Xiu 1, Rohit Mathur 2, Adel Hanna 1, Uma Shankar 1, Frank Binkowski 1, Carlie Coats 3 1. University of North Carolina at Chapel Hill 2. ASMD, ARL/NOAA, NERL/US EPA 3. Baron Advanced Meteorological Systems

Presentation Topics Air quality modeling components Air quality modeling components What is non-integrated meteorology/chemistry modeling? What is non-integrated meteorology/chemistry modeling? The integrated meteorology/chemistry model The integrated meteorology/chemistry model Optical properties of aerosols and radiative feedback Optical properties of aerosols and radiative feedback Case study simulation for July 1995 episode Case study simulation for July 1995 episode Analysis (model vs. observations) and evaluation Analysis (model vs. observations) and evaluation Summary and on going research Summary and on going research

Offline Air Quality Modeling CTM (MAQSIP, CMAQ) Advection, Chemical Transform Turbulence and Diffusion, Dry Deposition, Wet Deposition, Clouds; Aqueous Chemistry Met. Couple MCPL, MCIP Meteorology MM5 Emissions Processing SMOKE

Typical Air Quality Modeling Approach Meteorological data are prepared offline and used as input to the chemistry transport model Meteorological data are prepared offline and used as input to the chemistry transport model Meteorological model outputs are processed to comply with the chemistry-transport format Meteorological model outputs are processed to comply with the chemistry-transport format Meteorological data output are less frequent than internal model time step Meteorological data output are less frequent than internal model time step Temporal interpolation may lead to misleading results; may not capture the evolution of the PBL or may cause erroneous wind direction Temporal interpolation may lead to misleading results; may not capture the evolution of the PBL or may cause erroneous wind direction Physical inconsistencies may occur (e.g., mass conservation if re-diagnosis of wind is required) Physical inconsistencies may occur (e.g., mass conservation if re-diagnosis of wind is required) Radiative feedbacks of atmospheric constituents such as aerosols are not accounted for Radiative feedbacks of atmospheric constituents such as aerosols are not accounted for

Objectives Develop and apply an air quality modeling system with integrated meteorology, emissions, and chemistry Develop and apply an air quality modeling system with integrated meteorology, emissions, and chemistry Examine the feedback due to the direct effect of aerosols Examine the feedback due to the direct effect of aerosols Provide a platform for air pollution/climate feedback studies, e.g., examination of the indirect effects of aerosols Provide a platform for air pollution/climate feedback studies, e.g., examination of the indirect effects of aerosols

Integrated Meteorology-Chemistry Model CTM (MAQSIP) Advection, Chemical Transform Turbulence and Diffusion, Dry Deposition, Wet Deposition, Clouds; Aqueous Chemistry Met. Couple MCPL Meteorology MM5 Emissions Processing SMOKE Radiative Feedback of Aerosols

Multiscale Air Quality Simulation Platform (MAQSIP) Modular/generalized coordinate Modular/generalized coordinate Prototype for Models3/CMAQ Prototype for Models3/CMAQ Gas-phase and heterogeneous chemistry Gas-phase and heterogeneous chemistry – Modified CBM-IV; modified QSSA, modal PM approach Processes/modules Processes/modules – Advection Bott’s scheme – Turbulent mixing; K-theory – Clouds/aqueous chemistry; Kuo and Kain and Fritsch – Dry deposition – Wet deposition

Radiation Scheme CCM2 radiation scheme in MM5 CCM2 radiation scheme in MM5 Delta-Eddington approximation to calculate solar absorption with the solar spectrum divided into 18 discrete intervals Delta-Eddington approximation to calculate solar absorption with the solar spectrum divided into 18 discrete intervals Absorption of O 3, CO 2, O 2, and H 2 O Absorption of O 3, CO 2, O 2, and H 2 O Scattering and absorption of cloud water droplet Scattering and absorption of cloud water droplet Direct radiative forcing of aerosols is included using Mie approximation to calculate scattering and extinction efficiencies using aerosol effective radius and refractive index Direct radiative forcing of aerosols is included using Mie approximation to calculate scattering and extinction efficiencies using aerosol effective radius and refractive index

Refractive Index Refractive index is the particle optical property relative to the atmosphere and is used in the Mie scattering calculation to provide optical properties Refractive index is the particle optical property relative to the atmosphere and is used in the Mie scattering calculation to provide optical properties A complex number, the real part represents the scattering and the imaginary part the absorbing properties A complex number, the real part represents the scattering and the imaginary part the absorbing properties In the integrated model, the refractive index is calculated with the scattering and absorbing effects of a variety of aerosols (NH 4, SO 4, NO 3, H 2 O, organic aerosol, elemental carbon, and dust). Sea salt will be included later. In the integrated model, the refractive index is calculated with the scattering and absorbing effects of a variety of aerosols (NH 4, SO 4, NO 3, H 2 O, organic aerosol, elemental carbon, and dust). Sea salt will be included later.

Case Studies 36 km simulation Eastern US case study; 36 km horizontal grid resolution; 21 layers Eastern US case study; 36 km horizontal grid resolution; 21 layers July 2-15, 1995 period July 2-15, 1995 period SMOKE; anthropogenic and biogenic SMOKE; anthropogenic and biogenic MAQSIP is called every MM5 time step (100 Seconds) MAQSIP is called every MM5 time step (100 Seconds) Three days model spin-up Three days model spin-up

Air Quality Monitoring CASTNet IMPROVE

PM2.5

SO 4

NH 4

NO 3

Aerosol Compositions

Aerosol optical depth comparisons

Analysis of the Radiative Feedback Short Wave RadiationBoundary Layer Average (No Feedback – Feedback) PM Fine Mass

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

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

Reduction in Shortwave Radiation Concentration Size Number Density

Summary Presented results from an episodic (10 days) integrated meteorology/chemistry regional scale model Presented results from an episodic (10 days) integrated meteorology/chemistry regional scale model Comparisons with observations suggest the ability of the model to capture spatial gradients in concentrations Comparisons with observations suggest the ability of the model to capture spatial gradients in concentrations The model simulations show the direct effect of aerosols causing reduction in surface short-wave energy which contributes to lower planetary boundary layer (PBL) heights The model simulations show the direct effect of aerosols causing reduction in surface short-wave energy which contributes to lower planetary boundary layer (PBL) heights The aerosol size distribution parameters (number and mean diameter) seem to be as important as mass concentration in the direct radiative forcing The aerosol size distribution parameters (number and mean diameter) seem to be as important as mass concentration in the direct radiative forcing

Ongoing/Future Work Studying the effects of 1995 Canadian wildfires Studying the effects of 1995 Canadian wildfires Application to the Indian subcontinent (NSF) Application to the Indian subcontinent (NSF) – Radiative effects of carbonaceous aerosol – Comparisons with INDOEX measurements Study effects of aircraft emissions (NASA) Study effects of aircraft emissions (NASA) – Comparisons with SONEX

R825388

Case Studies 108 km simulation 1995 summer Canadian fire 1995 summer Canadian fire Canada and US domain; 108 km horizontal resolution; 21 vertical layers Canada and US domain; 108 km horizontal resolution; 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 Seconds) MAQSIP is called every MM5 time step (300 Seconds) Simulations with and without estimated wildfire emissions Simulations with and without estimated wildfire emissions – Speciated wildfire emissions scaled to CO emission estimates from McKeen et al. (2002)

(a) CO(b) O 3 (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.