Quantifying Photolysis Rates in the Troposphere and Stratosphere by chenshu

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									Quantifying Photolysis Rates in the
 Troposphere and Stratosphere
          (An Overview)


            William H. Swartz
  Department of Chemistry and Biochemistry
             Friday, November 1, 2002
Important Chemical Processes in the
  Troposphere and Stratosphere




                           Tropospheric Ozone:

                            P : jNO2 (polluted)
                            L : jO3 (remote)

                          j-values are critical
Important Chemical Processes in the
     Stratosphere (continued)
                 PSC

    HCl + ClONO2  HNO3(s) + Cl2(g)
                  h
              Cl2  2Cl


                                       Stratospheric Ozone:

                                      P : jO2 (tropics)
                                      L : jClOOCl (polar vortex)


                                      j-values are critical
               ―j-Values‖: Definition

             NO2 + h  NO + O ( < 424 nm)

                              d [NO2 ]
                                       j NO2 [NO2 ]
                                 dt

           j NO2   F ( ) NO2 ( ,T )NO2 NOO ( ,T )d


―actinic‖ flux (photons cm-2 s-1 nm-1)

                         absorption cross section (cm2)

                                            photolysis quantum yield (photons-1)
   Components of the Radiation Field



                                           Actinic Flux F =
                                     A (direct attenuated flux) +
                                     B (scattered flux) +
                                     C (reflection of direct) +
                                     D (reflection of scattered)




(Adapted from Meier et al. [1982])
Factors Affecting Actinic Flux

    • solar zenith angle
    • observer altitude
    • ozone profile/amount
    • other absorbers/scatterers (O2, air)
    • surface reflectivity (albedo)
    • surface altitude
    • aerosol morphology/optical properties
    • cloud morphology/optical properties
      (including polar stratospheric clouds)
    • atmospheric refraction
        Sensitivity: Surface Albedo/Height




[Swartz et al., 1999]
                        Sensitivity: Ozone Profile




[Swartz et al., 1999]
                     Determining j-Values
      Why measurements?                                Why modeling?

          Chemical Actinometry                      Radiative Transfer Modeling

(measure chemical                                                  (model solar flux)
change)
                             Photolysis Rate Coefficient


                                      Radiometry
                                                               (measure solar flux)

                Irradiance                                   Actinic Flux


 Eppley Radiometer    Spectroradiometer        Filter Radiometer    Spectroradiometer
     APL Radiative Transfer Model
• developed over 20+ years, for the calculation of j-values in the
  stratosphere and troposphere [Anderson and Meier, 1979; Meier et
  al., 1982; Anderson, 1983; Anderson and Lloyd, 1990; Anderson et
  al., 1995; DeMajistre et al., 1995; Swartz et al., 1999]
• direct solar deposition and reflection from Lambertian surface
  calculated in a spherical, refracting atmosphere
• multiple scattering using a plane-parallel approximation
• integral solution to radiative transfer
• parameterization of solar transmission through O2 Schumann–Runge
  bands (175–204 nm) developed by R. DeMajistre,
  based on work of K. Minschwaner
• wavelength range: 175–850 nm
• 75 altitude layers, 0–120 km
                      Objectives
1   j-Values
How do various factors affect j-values important to the ozone
balance of the troposphere and stratosphere?
How well can we measure/model j-values?
How well can we model j-values with the APL model, over a range
of wavelengths, altitudes, and solar zenith angles?


2   Polar Ozone Loss
Can we use stellar occultation remote sensing to measure polar
stratospheric ozone loss rates?
How can j-value measurement and modeling help elucidate factors
influencing photochemical ozone loss within the polar vortex?
                  lower strat;               SOLVE 1999/2000
                  moderate SZA




POLARIS 1997            lower strat;
                          high SZA




               IPMMI
               1998



                                       surface;
                                       low SZA
      Is jNO2 Known Accurately Enough?
             The State of the Art?!




[Lantz et al., 1996]
    International Photolysis Frequency
       Measurement and Modeling
         Intercomparison (IPMMI)




NCAR Marshall Field Site, 39°N 105°W, elevation: 1.8 km; June 15–19, 1998

 Objectives: j [NO2  NO + O], j [O3  O2 + O(1D)], spectral actinic flux.
    Measurements by 21 researchers (US, UK, Germany, New Zealand).
Modeling by 18 researchers (US, UK, Canada, Germany, Austria, Netherlands,
                             France, Norway).
                      My Objectives




1.   Measure jNO2 at the surface and compare with other measurements
2.   Model jNO2 and jO3 at the surface with APL model
3.   Evaluate model by comparing modeled j-values with measurements
4.   Evaluate model by comparing modeled j-values with other models
IPMMI: Measurements and Modeling

          Chemical Actinometry                      Radiative Transfer Modeling

(measure chemical                                                  (model solar flux)
change)
                             Photolysis Rate Coefficient


                                      Radiometry
                                                               (measure solar flux)

                Irradiance                                   Actinic Flux


 Eppley Radiometer   Spectroradiometer         Filter Radiometer    Spectroradiometer
                     IPMMI Measurement Site




Photo by Chris Cantrell (NCAR)
 UMD jNO2
Actinometer
 Schematic


NO2 + h  NO + O


              NO
  j NO2 
            [NO2 ]0 t
Trailer #2
       UMD Actinometer
         UMD Actinometer



                                       on top




inside




              quartz photolysis tube
UMD jNO2 Actinometer Data
     June 15–19, Overlaid




High day-to-day precision in clear-sky periods.
UMD vs. NCAR Actinometers



                  NCAR actinometer
                       failed




    June 16          June 19
jNO2 Measurement Comparison
   vs. Composite Actinometer



                                      JPL97
                                              Harder
                                              et al. 97




                                      JPL97
                                              Harder
                                              et al. 97




Larger NO2 absorption cross sections lead to better
    spectroradiometer–actinometer agreement.
IPMMI June 19 Model Specifications




                                                   (APL*)               (APL)
                                     AOD
aerosol optical depth:   I  I 0e
                                             aerosol Ångström parameter:
aerosol asymmetry factor:
                                              AOD  dependence
 1 = completely forward-scattering,
 0 = isotropic scattering,                   aerosol single-scattering albedo:
-1 = completely backward-scattering           fraction of photons scattered
    Model vs. Measurement:
Effects of Aerosol Optical Depth


                        Though optically
                        thin, aerosols did
                        have a
                        measurable
                        impact on jNO2.
   jNO2 Model Comparison (June 19)
     ―composite‖ actinometer



                                                     +
                                                     




                        Good high-SZA behavior.




                                                         (ACDTUV)


Excellent overall agreement with TUV and model consensus. Larger NO2
absorption cross sections lead to better model–actinometer agreement.
    jO3 Model Comparison (June 19)

Excellent overall
agreement with
TUV and model
consensus, when
IPMMI aerosol
specification and
ATLAS
extraterrestrial
solar flux are
used.
     IPMMI: Summary & Conclusions
• first ―blind,‖ international intercomparison of many j-value measurement
  and modeling techniques
• UMD chemical actinometer measured jNO2 with excellent precision, and in
  good agreement with NCAR actinometer
• APL model calculated jNO2 in excellent agreement with spectroradiometers
  (<1–2% on average)
• APL model calculated jO3 in excellent agreement with actinometer and
  spectroradiometers (<1–2% on average)
• spectroradiometers and models underestimated actinometer jNO2 by a
  significant amount (APL model –14%; though within combined
  uncertainties)
• larger NO2 absorption cross sections (e.g., Harder et al. [1997]) lead to
  better agreement—We need to re-evaluate laboratory measurements!
• aerosol parameters must be accurately determined in order to reach
  model–measurement agreements of <~5%
• ATLAS extraterrestrial irradiance gives best j-value agreement (esp. jO3)
                        Arctic Ozone Depletion




[Newman et al., 1997]
            Summertime Arctic Ozone Loss




[Lloyd et al., 1999]
Photochemistry of Ozone Loss in the
Arctic Region in Summer (POLARIS)




     Based in Fairbanks, Alaska, 65°N 148°W; April–September 1997

Objectives: evaluate (measure and model) naturally occurring summertime
  ozone loss at high northern latitudes, to determine contributions from
                    chemical loss cycles and transport.
NASA ER-2 high-altitude aircraft, balloons, ground-based, and space-based
                               observations.
                     My Objectives




1. Model j-value sensitivity in the lower stratosphere
2. Model jNO2 and jO3 along ER-2 flight tracks (20 km) with APL model
3. Evaluate model by comparing modeled j-values with
   measurements, particularly in light of modeled sensitivities
New Challenges:
 Characterizing aircraft geophysical environment
                        Sensitivity: Ozone Profile




[Swartz et al., 1999]
                 POLARIS:
         Measurements and Modeling
          Chemical Actinometry                      Radiative Transfer Modeling

(measure chemical                                                  (model solar flux)
change)
                             Photolysis Rate Coefficient


                                      Radiometry               (measure solar flux)

                Irradiance                                   Actinic Flux


 Eppley Radiometer   Spectroradiometer         Filter Radiometer    Spectroradiometer
  CPFM Spectroradiometer
   (Environment Canada)




CPFM             • surface albedo
                 • overhead ozone column
                 • j-values
                          jNO2 along
                        June 29, 1997
                         Flight Track

                          APLCPFM, APLTOMS
                             vs. CPFM




[Swartz et al., 1999]
POLARIS: Summary & Conclusions

• modeled sensitivity of jNO2 and jO3 to surface albedo, surface
  altitude, total ozone, ozone and temperature profiles, and
  refraction, in the context of the POLARIS mission

• jNO2: albedo > surface altitude » total ozone (at 20 km)

• jO3: total ozone » albedo > surface altitude (at 20 km)

• jNO2: APLCPFM > CPFM by 6%; APLTOMS > CPFM by 9% (average)

• jO3: APLCPFM > CPFM by 7%; APLTOMS > CPFM by 1% (average)

• model–measurement agreement has improved to the point
  where variability along flight tracks can be attributed to
  geophysical variability
SAGE III Ozone Loss and Validation
       Experiment (SOLVE)




   Based in Kiruna, Sweden, 68°N 20°E; November 1999–March 2000

Objectives: study the development of the polar vortex and PSCs, quantify
         chlorine activation, and measure and model ozone loss.
 NASA ER-2 high-altitude and DC-8 aircraft, balloons, ground-based, and
                        space-based observations.
                     My Objectives




1. Add new geophysical inputs to the APL model
2. Model jNO2 and jO3 along ER-2 flight tracks (20 km) with APL model
3. Model jNO2 and jO3 along DC-8 flight tracks (11 km) with APL model
4. Evaluate model by comparing modeled j-values with measurements
New Challenges:
 Twilight conditions (wintertime); fewer direct ancillary measurements
             APL Model Input Data


Mode             Albedo           Ozone
APLclim          climatology      climatology
APLTOMS          TOMS             TOMS (total ozone)
APLPOAM          TOMS             POAM III (O3–PV reconstruction)
APLCPFM          CPFM             CPFM (overhead ozone, TOMS total)


APLclim*, APLTOMS*, APLPOAM*, and APLCPFM* also use in situ ozone.
SOLVE: Measurements and Modeling

          Chemical Actinometry                      Radiative Transfer Modeling

(measure chemical                                                  (model solar flux)
change)
                             Photolysis Rate Coefficient


                                      Radiometry               (measure solar flux)

                Irradiance                                   Actinic Flux


 Eppley Radiometer   Spectroradiometer         Filter Radiometer    Spectroradiometer
SAFS Spectroradiometer (DC-8)
           (NCAR)


              (downwelling)




              (upwelling)
Model–SAFS Agreement (DC-8)
 jNO2      jO3



                   TOMS albedo and
                   POAM III O3
                   reconstructions,
                   as well as in situ
                   O3, lead to the
                   best agreements
                   with SAFS.
 Attenuation of (Measured) jNO2




Outlying points (from PSC flights) indicate attenuated
 actinic flux, relative to clear-sky model calculations.
Polar Stratospheric Clouds (PSCs)
    SOLVE: Summary & Conclusions
• unique set of measured j-values at high SZAs in the wintertime Arctic




• new temperature/pressure/ozone/albedo climatologies, POAM III O3–PV
  reconstructions, and in situ O3 constraints added to model
• measured O3 (POAM, in situ) and albedo (TOMS) were superior to
  climatologies for calculating j-values in nearly all cases
• jNO2: model–SAFS agreement: 2–4% (<85°), 4–6% (>85°) (average)
• jO3: model–SAFS agreement: 0–13% (<85°), 3–15% (>85°) (average)
• attenuation of jNO2 up to 75% (attributed to PSCs)
              Objectives (revisited)
  1    j-Values
 How do various factors affect j-values important to the ozone
  balance of the troposphere and stratosphere?
 How well can we measure/model j-values?
 How well can we model j-values with the APL model, over a range
  of wavelengths, altitudes, and solar zenith angles?


  2    Polar Ozone Loss
  Can we use stellar occultation remote sensing to measure polar
  stratospheric ozone loss rates?
  How can j-value measurement and modeling help elucidate factors
  influencing photochemical ozone loss within the polar vortex?
Photochemical Ozone Loss using
MSX/UVISI Stellar Occultation
(during SOLVE)      UVISI WFOV and
                   NFOV imager - visible          Mass
                                               Spectrometer


                    Xenon            Krypton
                                                              UVISI
                    lamp              lamp
                                                          spectrographic
                                                           imagers (5)




                                                               UVISI WFOV
                                                                and NFOV
                                                               imager - UV

                                                                    Space
                                                              infrared imaging
                                                                  telescope
                                                                 (SPIRIT III)


                                                         Space-based
                                                         visible (SBV)
                                                          instrument

             MSX
Extinction:




Refraction:
                     Minimum Ray Height (km)




Wavelength (nm)
                                                      Observed Stellar Spectra




                  Star Equivalent Brightness (R/nm)
        Sampling of the Polar Region
               during SOLVE




25 in-vortex
occultations,
Jan 23–Mar 4
       MSX–POAM III Ozone Comparison




                        POAM III ozone based on ozone–PV reconstruction.
[Swartz et al., 2002]
Air Parcel Trajectories Jan 15–Mar 31


                         Diabatic forward
                         and back
                         trajectories of air
                         parcels sampled
                         with the January
                         23 occultation.
                        Ozone Change since Jan 23




[Swartz et al., 2002]
                        Ozone Loss using
                           Individual
                          Trajectories

                        Average ozone loss rates
                        on 3 surfaces derived
                        from occultation
                        measurements and
                        related by individual
                        diabatic trajectories.



[Swartz et al., 2002]
                        SOLVE Ozone Loss Profiles




[Swartz et al., 2002]
               Stellar Occultation
             Summary & Conclusions
• first science application of space-based stellar occultation

• 25 profiles within the polar vortex during SOLVE

• good temperature agreement with UKMO analysis

• good ozone agreement with POAM III ozone–PV reconstructions

• analysis using diabatic descent trajectory calculations to derive
  photochemical ozone loss rates in the Arctic during SOLVE: up to ~24
  ppbv/day (average) at 400–500 K over 1/23/2000 to 3/4/2000, or about
  1 ppmv, consistent with other analyses

• demonstrates the utility of extinctive–refractive stellar occultation for
  ozone monitoring, having several advantages over other techniques
              Objectives (revisited)
  1    j-Values
 How do various factors affect j-values important to the ozone
  balance of the troposphere and stratosphere?
 How well can we measure/model j-values?
 How well can we model j-values with the APL model, over a range
  of wavelengths, altitudes, and solar zenith angles?


  2    Polar Ozone Loss
 Can we use stellar occultation remote sensing to measure polar
  stratospheric ozone loss rates?
  How can j-value measurement and modeling help elucidate factors
  influencing photochemical ozone loss within the polar vortex?
     What Are the (Optical) Effects of
    PSCs on Photolysis and Ozone Loss?




               PSCs, over Kiruna, Sweden, January 2000
Photo by Jim Ross (NASA/Dryden)
     Identification of PSC Effects




Modeled/measured jNO2 > 1.18 considered PSC-attenuated.
         Temperature Dependence


                                   all flights:




            March 8, 2000

PSC attenuation coincides with
cold temperatures (13–25 km)
relative to the saturation point
of nitric acid trihydrate (NAT).
j-Value fdirect
Dependence                           jNO2



                  c


              b                    jNO2

 a




                            jNO2



PSC attenuation as
a function of
jdirect/jtotal (fdirect).
   Slant Path (SZA) Dependence




                                              e s


SZA dependence follows Beer–Lambert relationship as a
    function of the slant path (through 13–25 km).
           2-D Fit




PSC effect as functions of j-value
direct fraction and slant path only.
ClOOCl Loss Cycle
   and jClOOCl




                                                    Source: P. A. Newman (NASA/Goddard)




 d [O 3 ]    d [O 3 ]    j ClOOCl,PSC                  PSC-affected
                                                      vs. clear-sky
                            j
 dt PSC  dt  clear -sky  ClOOCl,cle ar-sky 
                                                            jClOOCl.
                                PSC Probability
     UKMO meteorological
      temperature fields




January 25, 2000; 68.1 mb (18 km)
Diurnal PSC jClOOCl Effect




          × PPSC




          January 25, 2000
       Diurnally Integrated jClOOCl Effect

 Integrated photolysis:

ClOOCl,c -s  day j ClOOCl,c -sdt
ClOOCl,PSC day j ClOOCl,PSCdt             polar night




 Photolysis affected within
 the cold vortex, when
 the Sun is present.                  vortex edge


 January 25, 2000; 68.1 mb (18 km)
Vortex-Averaged jClOOCl Effect
    SOLVE: Summary & Conclusions

• attenuation of jNO2 up to 75% (attributed to PSCs)

• attenuation correlated with cold temperatures along solar line of sight

• attenuation also related to the slant path through PSC layer

• putative PSCs have up to 10% effect on daily ClOOCl photolysis
  (ozone loss) within the Arctic polar vortex, during SOLVE

• we are ready and in a unique position to accurately model j-values
  during SOLVE-2, even in the presence of PSCs….
                 SOLVE-2 (2003):
               Modeling is All There Is
          Chemical Actinometry                      Radiative Transfer Modeling

(measure chemical                                                  (model solar flux)
change)
                             Photolysis Rate Coefficient


                                      Radiometry               (measure solar flux)

                Irradiance                                   Actinic Flux


 Eppley Radiometer   Spectroradiometer         Filter Radiometer    Spectroradiometer
                       Final Remarks
• if you want to get modeled j-values right, you need to know: altitude,
  solar zenith angle, day of year (Earth–Sun distance), ozone profile,
  pressure/temperature profile, surface altitude, spectral surface albedo,
  spectral aerosol properties (optical depth, single-scattering albedo,
  scattering phase function)…in cloud-free skies

• we need to learn how to better handle clouds, including PSCs

• we need to measure the optical effects of PSCs throughout the
  stratosphere and model their impact in chemistry–transport models

• we need to consider using stellar occultation as a means of monitoring
  long-term trends in ozone
                       Acknowledgments
COLLABORATORS:
Measurements:
 Russ Dickerson, Jeff Stehr, Shobha Kondragunta (UM)
Modeling:
 Steve Lloyd, Don Anderson, Tom Kusterer (APL)
Data Analysis:
 Sam Yee, Ron Vervack (APL)
 Paul Newman (Goddard)
IPMMI:
 Rick Shetter, Sasha Madronich (NCAR)
POLARIS:
 Tom McElroy, Clive Midwinter
 (Environment Canada)
SOLVE:
 Rick Shetter (NCAR)
 Karl Hoppel (NRL), Cora Randall (LASP)
 Stacey Hollandsworth Frith, Gordon Labow
 (Goddard)
$$$: NASA OES, C4 (NSF), APL, ….                       T = –30°C
               Acknowledgments


ADVISOR:

Russ Dickerson (UM)




MENTORS:

Steve Lloyd (APL)
Don Anderson (APLNASA/HQ)




                                 T = –30°C

								
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