1. from bulk-mass towards size resolved aerosols
EMEP-MAFOR:
from bulk-mass towards size resolved aerosols
(Matthias Karl and Svetlana Tsyro)
TFMM 16-th meeting
Kraków, Poland, May 5-8, 2015

2. Motivation
Knowing the aerosol number concentrations (NC) and size distribution is highly relevant for studies of:
Health implications of air pollution:
“epidemiological and toxicological studies show clear correlation between ultrafine particles (UF) and health endpoints “ Daher et al., Environ. Science, 2013
Note: UF particles contribute negligibly to PM mass – described by PNC
Aerosol optical properties and radiative effects
Estimations of climate relevant effects of aerosols, acting as SLCF
AOD and aerosol extinction profile measurements from satellite and ground-based instruments offers new opportunity for models’ evaluation (global coverage, high resolution, 3D)
and for adequate modelling of aerosol processes such as aerosol- clouds interaction, formation of new particles and secondary aerosols, dry deposition ..
Knowing the aerosol size distribution on high temporal and spatial resolution is of great importance for the assessment of health risks from air pollution.
Ultrafine particles, ie the small particles of less than 100 nm size contribute negligible to the particle mass, and are better represented in terms of particle number. UFP penetrate deep into the lung, where they can accumulate in the lymph nodes. Although causal relationships are not proven, there is increasing evidence for a correlation between UFP and health end points.

3. MAFOR Aerosol Dynamics
Solves size distribution of a mixed multicomponent aerosol on a fixed sectional grid (1 nm – 10 µm; 16 – 60 bins tested)
Consistent time integration of particle number and mass concentrations
Flexible with respect to number of size sections and aerosol components; and computationally efficient
Stand-alone module – easily implemented
Documentation: Karl et al., Tellus, 2011;
Evaluated with chamber data, nucleation event observations on central Arctic Ocean (Karl et al., 2012), PNC measurements at motorway (Keuken et al., AE, 2012)
EMEP-MAFOR:
still on-going work (first report EMEP Status Report 1/2014)
evaluated with continuous PNC and size distribution (EUCAARI/EUSAAR) + campaigns/episodes (from 2003 onwards)
Presented at several conferences (EAC-2013, IAMA-2013, IAC-2014, EGU-2014)

4. Computational structure of EMEP-MAFOR
Gas emissions
Advection
PM emissions
SO2
NOx
NH3
Gas & aqueous chemistry EC
POM
PMXX(n)
Sea salt
Min. Dust
H2SO4
LV Org
VOC
MARS (Equilibrium)
Inorg. dust
SO4, HNO3/NO3, NH3/NH4
SOA (VBS)
MAFOR Aerosol Dynamics
Nucleation Condensation Coagulation
dPNC(n)/dt dSO4(n)/dt, dSOA(n)/dt
PMXX
gmd(m) 
nucl
Ait
acc
coar
AFT: aerosol formation treatment
ADM: aerosol dynamic model
Output: PM2.5, PM10, PNC,
number size distribution (16bins)
+ chem. composition (4 modes)
Dry /wet deposition

5. Model: particle number and mass concentrations 2008 mean
Total PNC
PM2.5
Nucleation PNC
Aitken PNC
Accumulation PNC

6. EMEP-MAFOR evaluation with measurements:
Asmi et al. Year: 2008 (annual/seasonal PNC & size distribution)
EUSAAR/ACTRIS/EBAS: Year 2010, dN/dlogDp
SPC (San Pietro Capofiume): Year 2010, dN/dlogDp
SmartSMEAR (Hyytiälä) : Summer 2010, VOC, H2SO4, OH
Ny_Alesund2
Pallas
Hyytiala
Birkenes
Aspvreten
Vavihill
MaceHead
Waldhof
Harwell
Finokalia
Zugspitze
Jungfraujoch
Hohenpeissenberg
Puy_deDome
Schauinsland
Mt_Cimone
Melpitz
Kosetice
K_Puszta
Boesel
Cabauw
Ispra
Modelled vs. observed total PNC (d>10nm) in 2008
Measurements as in Asmi et al., ACP, 2011
Model compared to measured PNCs:
Underestimates at polluted sites (C. Europe)
Quite close at less polluted sites (N. Europe)
Overestimates at mountain sites
1:1
ISP
Modelled total PNC for EUSAAR sites correlate quite well with observations presented by Asmi et al (available through the link here). It shows very good agreement for many remote sites including the mountain sites – while PNC at more polluted sites are underestimated by roughly a factor of two.
KPT
MPZ
CBW
BOS
OBK

7. Seasonal median size distribution (2008)
Birkenes
Hyytiälä O
Modelled PNCs compared to the measurements:
bimodal size distribution (observed is closer to unimodal)
Discrepancies in seasonality
Summer: too many newly formed particles <20nm, whereas too few > 50nm. Indicates slow growth
Winter: quite close at cleaner sites, but too low at polluted sites (wood burning for residential heating??
Melpitz
Ispra O O
Looking at seasonal median size distributions from European sites, modelled size distributions show a distinct bimodal shape while in particulat at the more polluted sites Ispra, K-Puszta and Melpitz the observations resemble an unimodal distribution. At these sites, particles between nm are underestimated, which points to missing biomass burning emissions in winter and in summer, not represented in the EMEP model.
For the remote sites, EMEP-MAFOR does not capture secondary particle formation in summer. Despite the particles are formed in the model – they just did not grow to the observed sizes.

8. Nucleation Event Frequency
The Frequency of new particle formation events defined as fraction of event days in each month for the selected sites Hyytiala, SP Capofiume, Birkenes in Norway and Pallas in N.-Finland.
Blue bars are observed event day fraction, red for Reference simulation, green for BIO and orange for SO4 Tests. On average BIO overestimates the number of events, in particular in summer.

9. Birkenes, 2010 (EBAS) OBS MODEL Total PNC (>10nm) PN distribution
PNC evolution
Total PNC (>10nm)

10. Hyytiälä, 2010 (EBAS) OBS MODEL Total PNC (>10nm) PN distribution
PNC evolution
Total PNC (>10nm)

11. AOD & Extinction profiles
Bulk-mass aerosol
3D concentrations of fine and coarse aerosols
Specific Extinction Efficiencies for aerosol components (Hess et al, 1998)
Effective cross-sections; implicit account for the effect of relative humidity (Chin et al, 2002)
Size-resolved aerosol (using Mie-theory)
Effective complex refractive index- volume weighted for internal mixture: Bruggeman (1935) mixing rule for homogeneous mixtures (Chylek et al., 2000); Maxwell&Garnett (1904) rule for EC and min. dust inclusions
Extinction Efficiency from Mie-scattering look-up table
Applied to particles distribution in 4 size modes – provisionally!!
First evaluation of AOD with satellite / AERONET sun-photometer data and extinction vertical profiles with EARLINET LIDAR data

12. 42% overestimation …. despite general underestimation of aerosol mass
AOD at 550 nm (2012)
EMEP-MAFOR
EMEP bulk-mass
AATSR (2011)
Bias map
Bias map
25% underestimation … can be explained by PNC underestimation and provisional Mie-implementation
42% overestimation … despite general underestimation of aerosol mass

13. AOD 550nm: Model vs. AERONET
EMEP bulk-mass
EMEP-MAFOR
Correlation
Correlation
Spatial
Correlation

14. EMEP-MAFOR calculated aerosol extinction profiles compared with EARLINET measured (533 nm; seasonal means 2012)

15. Summary of main findings
First results from EMEP-MAFOR for PNC and size distribution are in fair agreement with observations…given the model is still under development. A number of caveats:
Discrepancy in PNC seasonality:
Summer – too many of smallest (<20 nm) particles and too few of >50 nm in the model
Model predicts too frequent new particle formation in summer with efficient initial growth 1-5 nm to 15-20nm, which then then stops
Winter – model max for >50nm (largely due to seasonal variation of anthropogenic emissions), observed max - summer
Missing particle sources in winter (wood burning for residential heating) and in summer (agricultural residuals burning, SOA from Biogenic VOSc
EMEP-MAFOR currently underestimated nm sized particles in summer, independent of nucleation & condensation configuration.
Based on the event analysis it cannot be decided whether biogenic or aromatic organics are involved in nucleation. However, on average too many events are predicted if nucleation depends on biogenic organics.
We have indications that EMEP model’s BVOC chemistry at night is the reason for interruption of particle growth during simulated events at Hyytiala.

16. «Golden Day Events» Hyytiälä, 24-30 March 2003
Observations:
Figure from:
O’Dowd et al., ACP, 2009
Model (Ref):
Growth stops in the night
Now let’s have a look at the event series, the Golden Days from March 2003, showing a series of banana type growth.
The sequential plot for the same time period from the reference simulation reveals that practically almost all features of the observed distribution are captured by the model, although with somewhat lower numbers. The timing is perfect.
But: Growth of the particles stops at the beginning of the night. We are still in the process of further investigating this. The most likely reason is the monoterpene chemistry in the model at night.
The growth of nucleated particles terminates too early
BVOC chemistry at night identified as possible reason for interruption of particle growth and the improvements have recently been made

17. Summary of main findings
EMEP-MAFOR reasonably describes AOD (satellites, AERONET) and Extinction profiles (EARLINET)
EMEP standard model tends to overestimate AOD (30- 40%) though the aerosol mass is underestimated – exaggerated effect rel. humidity??
EMEP-MAFOR underestimates AOD ( by 25%)
Can be explained by underestimation of Aitken/ accumulation PNC, missing SOA contribution, uncertainties in anthropogenic PN

18. Outlook of further development:
Improvement of size distribution calculations:
improvement of SOA formation (more testing BVOC and aromatic VOCs with measurements)
Implementation of size-resolved PM emissions
implementation of dynamic formation of size resolved ammonium nitrate (condensation-evaporation)
Improvement of extinction:
Calculate Mie-scattering based on full size distribution (16 sections) using improved refractive indices
Comparison with multi-year measurements of AOD and Extinction profiles (satellites, Aeronet, Earlinet etc.)

19. Thank you for your attention!
EMEP-MAFOR currently underestimated nm sized particles in summer, independent of nucleation & condensation configuration.
Based on the event analysis it cannot be decided whether biogenic or aromatic organics are involved in nucleation. However, on average too many events are predicted if nucleation depends on biogenic organics.
We have indications that EMEP model’s BVOC chemistry at night is the reason for interruption of particle growth during simulated events at Hyytiala.