(Anthroposphere-)Biosphere-aerosolcloud interactions and feedbacks in ESMs

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1 (Anthroposphere-)Biosphere-aerosolcloud interactions and feedbacks in ESMs Risto Makkonen University of Helsinki Ari Asmi, Veli-Matti Kerminen, Michael Boy, Almut Arneth, Markku Kulmala, Alex Guenther, Jón Egill Kristjánsson, Tuija Jokinen many others MERGE Summer meeting 2015

2 Anthroposphere-biosphere interactions

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5 Sources of organic aerosol Grow Direct aerosol effect th Indirect aerosol effects Forest fires Methanesulfonic acid (MSA) VOCs Anthropogenic influence: Oxidants, precursors, aerosol size distribution,... Fossil fuels Biofuels Cooking Solvents Biogenic VOCs Fulgan spores Bacteria Aspen Global Change Institute

6 Emission of primary organic particles Emission of organic vapours

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8 Spracklen et al., 2011 Global models are missing (potentially a lot of) secondary organic aerosol Spracklen et al., 2011 Tsigaridis et al., 2014

9 Spracklen et al., 2011 Global models are missing (potentially a lot of) secondary organic aerosol Spracklen et al., 2011 Guenther et al. (1995): 127 Tg/yr monoterpenes 0.15 * 127 = 19.1 Tsigaridis et al., 2014

10 Additional 100 Tg/year SOA source: best match against observations

11 Organics account for a major fraction of the growth of ultrafine particles. Riipinen et al., Atmos. Chem. Phys., 2011.

12 Nucleation event in Hyytiälä, Finland, April 2007 ORGANICS? Riipinen et al., ACP, 2011

13 Additional details needed from land-vegetation models to address formation of Extremely Low Volatility Organic Compounds (ELVOCs) Ehn et al., Nature, 2014

14 How do organics contribute to nucleation and growth in global models? Secondary organics modeled as primary particles Thermodynamic partitioning of organic vapours Usually contributes to organic mass only in large particles Volatility-basis set Can treat volatility of primary OA Difficulty of constraining free parameters in global scale Kinetic non-reversible condensation according to condensation sink No contribution to particle growth Unable to treat semivolatile vapours Organic nucleation Usually implemented as JNUC = A*[H2SO4]B C*[ORG]D Requires assumptions on nucleating organic vapour concentration

15 How do organics contribute to nucleation and growth in global models? Secondary organics modeled as primary particles Thermodynamic partitioning of organic vapours ofvolatility SOA formation on Can treat of primary OA cloud condensation nuclei (CCN) concentration? Difficulty of constraining free parameters in global scale Kinetic non-reversible condensation according to condensation sink Usually contributes to organic mass only in large particles Volatility-basis Simple set question: what is the global effect No contribution to particle growth Unable to treat semivolatile vapours Organic nucleation Usually implemented as JNUC = A*[H2SO4]B C*[ORG]D Requires assumptions on nucleating organic vapour concentration

16 MPI-ESM (ECHAM5.5-HAM2) Jokinen et al., 2015, PNAS

17 Number concentration (cm-3) Hyytiälä, May 2000: organics mostly condensing to Aitken mode Organic condensation Nucleation Aitken Diameter dp 0 Accumulation Coarse 15 Day of May

18 ELVOCs increase cloud condensation nuclei concentrations ELVOCs have been implicitly in global models for ~10 years, but now their formation pathways can be explicitly incorporated according to laboratory results Increase in CCN(1.0%) due to ELVOCs Jokinen et al., 2015, PNAS %

19 Earth System Feedbacks via Organic Aerosols

20 COBACC feedback mechanism (continental biosphere-aerosol-cloud-climate feedback) CO2 TEMPERATURE Cloud albedo and properties Biogenic Volatile Organic compounds (BVOC) Clound condensation Nuclei (CCN) Biogenic Secondary Organic Aerosols (BSOA) Aerosol loading PHOTOSYNTHESIS Diffuse radiation Global radiation Kulmala et al. (2014) Boreal Env. Res. 19, suppl. B,

21 Some uncertainties in global scale quantification: COBACC feedback mechanism Spatial distribution of SOA CO2 Cloud albedo and properties SOA size distribution, Clound condensation Nuclei (CCN) CCN-activity TEMPERATURE Biogenic Volatile Organic compounds (BVOC) CO2 inhibition Ozone stress, physical stress, monoterpene speciation PHOTOSYNTHESIS Biogenic Secondary Organic Aerosols (BSOA) Aerosol yields, product volatility Diffuse radiation Global radiation Kulmala et al. (2014) Boreal Env. Res. 19, suppl. B, Aerosol loading

22 An increase in BVOC emission can partly counteract aerosol forcing reduction MPI-ESM (ECHAM5.5-HAM2) Year Makkonen et al., ACP, 2012

23 Norwegian Earth System Model (NorESM) MEGAN (Model of Emissions of Gases and Aerosols from Nature) Emissions of 1) Isoprene 2) Monoterpenes 3) Other reactive VOCs 4) Other VOCs

24 NorESM simulates mid-range global monoterpene emissions Annual total monoterpene emission NorESM (this study): Carslaw et al. (2011): MEGAN-CLM-MACC: 76 TgC yr TgC yr-1 93 TgC yr-1

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27 2xCO2

28 2xCO2

29 2xCO2 ΔMT (kg/kg) Monoterpene concentration (w.r.t. 1xCO2) BV ck a b eed f OC CTRL (1xCO2) No BVOC-feedback ΔT (K)

30 76 Tg yr-1 2xCO2 For equilibrium climate change (ΔT 3.2 K) monoterpene emission increases by 32% 100 Tg yr -1 Heald et al. (2008): 19% (1.8K) Liao et al. (2006): 58% (4.8K)

31 Aerosol number concentration (w.r.t. 1xCO2) 2xCO2

32 CDNC: FEEDBACK NO FEEDBACK 2xCO2

33 Summary Coupled Earth System Models can be used to quantify biosphereaerosol-cloud interactions in a changing climate Global aerosol models generally underestimate total SOA formation Applications for paleo-climate, recent climate change, extreme climate events Missing SOA could be explained by anthropogenic modification, unaccounted precursors, heterogenous SOA formation Organics are essential in providing aerosol growth: ELVOCs Oxidantion pathway (OH vs. O3) and precursor structure (endocyclicity) Observed ELVOC yields are implemented in MPI-ESM But, Lack of mechanistic understanding of anthropogenic influence on SOA formation (~100 Tg/yr) Uncertainties in precursor emissions (factor of 4 for monoterpenes) and their response to climate change Earth System Models can only include a limited amount of details on chemistry/aerosol dynamics