Role of aerosol chemical composition on the formation of cloud condensation nuclei during biomass burning periods

Role of aerosol chemical composition on the formation of cloud condensation nuclei during biomass burning periods

Swen Metzger1, Ivonne Trebs1, Laurens Ganzeveld1,

Jos Lelieveld1, Philip Stier2, Franz X. Meixner1, Meinrat O. Andreae1, Paulo Artaxo3

Swen Metzger1, Ivonne Trebs1, Laurens Ganzeveld1,

Jos Lelieveld1, Philip Stier2, Franz X. Meixner1, Meinrat O. Andreae1, Paulo Artaxo3

Wednesday, 28/07/04, III LBA Scientific Conference - Brasília, July 27-29, 2004

Wednesday, 28/07/04, III LBA Scientific Conference - Brasília, July 27-29, 2004

11Max-Planck Institute for Chemistry, Mainz, GermanyMax-Planck Institute for Chemistry, Mainz, Germany22Max-Planck Institute for Meteorology, Hamburg, GermanyMax-Planck Institute for Meteorology, Hamburg, Germany

33Instituto de Fisica, Universidade de Sao Paulo, BrasilInstituto de Fisica, Universidade de Sao Paulo, Brasil

© Greg Roberts

Introduction

The chemical composition of atmospheric aerosols plays an The chemical composition of atmospheric aerosols plays an

important role for the hygroscopic growth and the aerosol-important role for the hygroscopic growth and the aerosol-

associated water mass. associated water mass.

Biomass burning events are likely to alter the chemical Biomass burning events are likely to alter the chemical

composition due to the emission of inorganic cations, such as composition due to the emission of inorganic cations, such as

potassium, and organic acids.potassium, and organic acids.

We therefore investigate their impact on the chemical We therefore investigate their impact on the chemical

composition and on the aerosol water mass, which is important composition and on the aerosol water mass, which is important

for the cloud formation.for the cloud formation.

Thermodynamical aerosol model: EQSAM;

Gas/liquid/solid partitioning

HNO3, NH3, H2SO4, HCl,

organic acids (g) Ions, liquid phase

NO3-, NH4

+, SO42-, Cl-,

lumped Low Molecular Weight (LMW) organic acids (e.g., HCOOH), Na+, K+, Ca2+, Mg2+,

H2O, pH

Salts, Solid phase

NH4NO3, NH4HSO4, (NH4)2SO4,

NH4 & organic acids

Temperature & relative humidityTemperature & relative humidity

R1

NH4NO3, NH4HSO4, (NH4)2SO4,

NH4 & organic acids

NO3-, NH4

+, SO42-, Cl-,

LMW organic acids (e.g., HCOOH), Na+, K+, Ca2+, Mg2+, H2O,

pH

R2

Model Application - SMOCC Data

Na/Cl-NH3/NH4-HNO3/NO3-H2SO4/SO4-H2O-System

Reduced aerosol systems compare relatively good for the wrong reason !Reduced aerosol systems compare relatively good for the wrong reason !

Model simulations:

box model constrained with observed T, RH & total gas-particulate mass (Trebs et al., in prep.)

K-Ca-Mg-Na/Cl-NH3/NH4-HNO3/NO3-H2SO4/SO4-H2O-Systemwith K-Ca-Mg as equivalent Na

All models compare reasonable well when applied with the same complexityAll models compare reasonable well when applied with the same complexity

Model Application - SMOCC Data

But they all underestimate the But they all underestimate the observed aerosol NHobserved aerosol NH44

++ concentration!concentration!

Model Application - SMOCC Data

K-Ca-Mg-Na/Cl-NH3/NH4-HNO3/NO3-H2SO4/SO4-H2O-Systemwith K-Ca-Mg considered explicitly in EQSAM/SCAPE2

Crustal elements considered in EQSAM; same ammonium loss as SCAPE2Crustal elements considered in EQSAM; same ammonium loss as SCAPE2KK++ drives NH4 drives NH4++ out of the aerosol phase, out of the aerosol phase, in contrast to the observationsin contrast to the observations! !

Reduced aerosol systems for Isorropia Reduced aerosol systems for Isorropia compares relatively good for the compares relatively good for the

wrong reason !wrong reason !

Model Application - SMOCC Data

LMW organic acids gets the ammonium back in the aerosol phaseLMW organic acids gets the ammonium back in the aerosol phase

Including LMW organic acids in EQSAM

Reduced aerosol systems for Isorropia Reduced aerosol systems for Isorropia compares relatively good for the compares relatively good for the

wrong reason !wrong reason ! Consistent inclusion of KConsistent inclusion of K++ and LMW and LMW organic acids in EQSAMorganic acids in EQSAM

MModular odular EEarth arth SSubmodel ubmodel SySystem (MESSy) coupled to GCM stem (MESSy) coupled to GCM ECHAM5ECHAM5

http://www.messy-interface.orghttp://www.messy-interface.org

MModular odular EEarth arth SSubmodel ubmodel SySystem (MESSy) coupled to GCM stem (MESSy) coupled to GCM ECHAM5ECHAM5

http://www.messy-interface.orghttp://www.messy-interface.org

ECHAM5ECHAM5

Polar Stratospheric Cloudsmicro-physics and sedimentation

Polar Stratospheric Cloudsmicro-physics and sedimentation

Aerosol Physics (& chemistry) Thermodynamical aerosol

composition module and size-resolving dynamical module

Aerosol Physics (& chemistry) Thermodynamical aerosol

composition module and size-resolving dynamical module

14CO / Radonnatural atmospheric tracer, evaluation

of tropospheric OH. STE / PBL transport

14CO / Radonnatural atmospheric tracer, evaluation

of tropospheric OH. STE / PBL transport

Eulerian Transport Schemes Eulerian Transport Schemes

Lagrangian Transport Scheme

Lagrangian Transport Scheme

Natural and Anthropogenic Emissionsbiogenic surface emissions and anthropogenic emissions

Natural and Anthropogenic Emissionsbiogenic surface emissions and anthropogenic emissions

Gas-phase and Heterogeneous Chemistry

using Kinetic PreProcessor (KPP)

Gas-phase and Heterogeneous Chemistry

using Kinetic PreProcessor (KPP)

MBL Chemistryswitchable extension with chemistry

scheme

MBL Chemistryswitchable extension with chemistry

scheme

Photolysisfast on-line scheme

Photolysisfast on-line scheme

Diagnostic and Output(e.g., PBL and tropopause height)

Diagnostic and Output(e.g., PBL and tropopause height)

ScavengingBelow and in-cloud scavenging of

gases and aerosols

ScavengingBelow and in-cloud scavenging of

gases and aerosols

Dry Depositiondry deposition of gases and aerosols

Dry Depositiondry deposition of gases and aerosols

Convection & Tracer Transport

Convection & Tracer Transport

Stratospheric Water VaporStratospheric Water Vapor

Lightning NOxLightning NOx

Coupled chemistry-GCM

G: 6N: 7M: 34total: 471. N

2. BC-OA1a3. BC-OA2a4. NO3 5.NH4 6. SO4

7. SOA1 8. SOA2

1. N2. SO43. BC => BC-OA1a, BC-OA2a4. OC => SOA1 8. SOA25. SS => SS-Na 12.SS-Cl6. DU => DU1, DU27./8./9. NO3, NH4, H2O

1. N2. BC-OA1a3. BC-OA2a4. NO3 5. NH4 6. SO4

7. SOA1 8. SOA29. DU1 10.DU2 11. SS-Na 12.SS-Cl

1. N2. H2SO4Nucleation

Aitken

Accumulation

Coarse

H2SO4

NH3

HNO3

SOA1SOA2HCl

soluble (liquid/solid)

1. N 2. BC-OA1 (primary) 3. BC-OA2 (primary)

1. N 2. DU3 (solid Si-core)

1. N 2. DU3 (solid Si-core)

insoluble (solid)

2.

1.

3.

4.

5.

6.

7.

<=>

GasphaseNew M7/EQSAM Structure

Coupled chemistry-GCM: Aerosol modeling

As an example:

EQSAM-M7: Aerosol Water [1e-9 kg/kg] (ug/kg) (PBL monthly mean, august)

Coupled chemistry-GCM: Aerosol modeling

M7: Aerosol Water [1e-9 kg/kg]

Coupled chemistry-GCM: Aerosol modeling

ECHAM5: Cloud Water [1e-6 kg/kg]

Coupled chemistry-GCM: Aerosol modeling

EQSAM-M7: Aerosol Water [1e-9 kg/kg] M7: Aerosol Water [1e-9 kg/kg]

Qualitive comparison of cloud and aerosol water spatial distributionQualitive comparison of cloud and aerosol water spatial distribution

There is a larger spatial variability in the global distribution of the EQSAM-M7 There is a larger spatial variability in the global distribution of the EQSAM-M7 aerosol water compared to M7, which only includes non-volatile sodium and aerosol water compared to M7, which only includes non-volatile sodium and sulfatesulfate

Conclusion/Outlook

Comparison of the aerosol NHComparison of the aerosol NH44++ content simulated with EQSAM and LBA- content simulated with EQSAM and LBA-

SMOCC observations shows the aerosol chemical composition needs to be SMOCC observations shows the aerosol chemical composition needs to be included consistently, e.g., for biomass burning including not only potassium included consistently, e.g., for biomass burning including not only potassium but also LMW acids.but also LMW acids.

For detailed questions/remarks: metzger@mpch-mainz.mpg.deFor detailed questions/remarks: metzger@mpch-mainz.mpg.de

The spatial variability in the EQSAM-M7 aerosol water is more similar The spatial variability in the EQSAM-M7 aerosol water is more similar compared to the spatial variability in ECHAM5’s cloud water, suggesting that compared to the spatial variability in ECHAM5’s cloud water, suggesting that the more detailed representation of the aerosol chemical composition in the more detailed representation of the aerosol chemical composition in EQSAM-M7 will facilitate a direct coupling of the aerosol model to ECHAM5’s EQSAM-M7 will facilitate a direct coupling of the aerosol model to ECHAM5’s cloud representation with respect to CCN activation.cloud representation with respect to CCN activation.

Evaluation of the ECHAM5 water/cloud fields, coupled to EQSAM-M7, with Evaluation of the ECHAM5 water/cloud fields, coupled to EQSAM-M7, with satellite observations (satellite observations (R. LangR. Lang). ).

Calculations of CCN and ICN in MESSy-ECHAM5 by explicitly coupling the Calculations of CCN and ICN in MESSy-ECHAM5 by explicitly coupling the cloud- and aerosol water content based on the ionic composition that reflects cloud- and aerosol water content based on the ionic composition that reflects the actual aerosol composition (incl. gas/liquid/solid aerosol partitioning)the actual aerosol composition (incl. gas/liquid/solid aerosol partitioning)

Outlook

For detailed questions/remarks: metzger@mpch-mainz.mpg.deFor detailed questions/remarks: metzger@mpch-mainz.mpg.de

MESSy – coupling chemistry etc. to GCMsMax-Planck Institute for Chemistry, Mainz, Germanyin collaboration withDLR Oberpfaffenhofen, GermanyMPI for Meteorology, Hamburg, Germany

Chemistry: R. Sander, A. Kerkweg, R. von Kuhlmann, B. Steil, R. von Glasow

Lagrangian Advection: C. Reithmeier, V. Grewe,G. Erhardt, R. Sausen, P. Jöckel, M. Traub

Aerosols: S. Metzger, P. Stier, A. Kerkweg,J. Wilson+, E.Vignati+, J. Feichter

Emission/Deposition: L. Ganzeveld, P. Stier,J. van Aardenne, Y. Balkanski+, M. Schulz+,W. Guelle+, V. Grewe, P. Jöckel, S. Metzger,G. J. Roelofs+

Polar stratospheric clouds: J. Buchholz,S. Meilinger, K. Carslaw

Photolysis: J. Landgraf, C. Brühl, P. Jöckel,R. Sander

Scavenging: H. Tost, L. Ganzeveld

Convective tracer transport: M. Lawrence, H. Tost,P. Jöckel, S. Brinkop, M. Ponater, C. Kurz

14CO, 222Rn, and passive tracer diagnostics:P. Jöckel

Tropopause diagnostics: P. Jöckel, M. TraubStratospheric H2O: C. Brühl, B Steil, P. JöckelTracer assimilation: L. Ganzeveld, P. JöckelFlexible data output: A. Rhodin, R. Sander,

P. Jöckel

Automatic rediscretization of input data: P. Jöckel

http://www.messy-interface.org

+external contribution, current maintainer/coordinator

... to be extended ...

more detailed references: see web-page

Scientific Coordination: Jos LelieveldTechnical Coordination: Patrick Jöckel & Rolf Sander

Contributions to the program code:

1. Metzger, S. M., Gas/Aerosol Partitioning: A simplified Method for Global Modeling, Ph.D. Thesis,

University Utrecht, The Netherlands, 2000.

http://www.library.uu.nl/digiarchief/dip/diss/1930853/inhoud.htm

2. Metzger, S. M., F. J. Dentener, J. Lelieveld, and S. N. Pandis, Gas/aerosol Partitioning I:

A Computationally Efficient Model. J Geophys. Res., 107, D16, 10.1029/2001JD001102, 2002.

http://www.agu.org/journals/jd/jd0216/2001JD001102/index.html

3. Metzger, S. M., F. J. Dentener, A. Jeuken, and M. Krol, J. Lelieveld, Gas/aerosol Partitioning II:

Global Modeling Results. J Geophys. Res., 107, D16, 10.1029/2001JD001103, 2002.

http://www.agu.org/journals/jd/jd0216/2001JD001103/index.html

4. Metzger, S. M., Gas/aerosol partitioning III: Model development (EQSAM) and comparison (MINOS

Data), in preparation.

The new version of EQSAM has been successfully applied within the EMEP modelling framework.

Results are included in the EMEP reports, http://www.emep.int/common_publications.html, 2003.

5. Trebs, I., S. Metzger, F. X. Meixner, G. Helas, A. Hoffer, M. O. Andreae, M. A.L. Moura, R. S. da Silva

(Jr.), J. Slanina, Y. Rudich, A. Falkovich, P. Artaxo, The NH4+-NO3–-Cl–-SO42–-H2O system and its gas

phase precursors at a rural site in the Amazon Basin: How relevant are crustal species and soluble organic

compounds?, in preparation for JGR.

References