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| Titel |
The AeroCom evaluation and intercomparison of organic aerosol in global models |
| VerfasserIn |
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H. Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell  , S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. Van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, X. Zhang |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 14, no. 19 ; Nr. 14, no. 19 (2014-10-15), S.10845-10895 |
| Datensatznummer |
250119101
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| Publikation (Nr.) |
 copernicus.org/acp-14-10845-2014.pdf |
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| Zusammenfassung |
This paper evaluates the current status of global modeling of the organic
aerosol (OA) in the troposphere and analyzes the differences between models
as well as between models and observations. Thirty-one global chemistry
transport models (CTMs) and general circulation models
(GCMs) have participated in this intercomparison, in the framework of
AeroCom phase II. The simulation of OA varies greatly between models in terms
of the magnitude of primary emissions, secondary OA (SOA) formation, the
number of OA species used (2 to 62), the complexity of OA parameterizations
(gas-particle partitioning, chemical aging, multiphase chemistry, aerosol
microphysics), and the OA physical, chemical and optical properties. The
diversity of the global OA simulation results has increased since earlier
AeroCom experiments, mainly due to the increasing complexity of the SOA
parameterization in models, and the implementation of new, highly uncertain,
OA sources. Diversity of over one order of magnitude exists in the modeled
vertical distribution of OA concentrations that deserves a dedicated future
study. Furthermore, although the OA / OC ratio depends on OA sources and
atmospheric processing, and is important for model evaluation against OA and
OC observations, it is resolved only by a few global models.
The median global primary OA (POA) source strength is 56 Tg a−1 (range
34–144 Tg a−1) and the median SOA source strength (natural and
anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the
models that take into account the semi-volatile SOA nature, the median source
is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much
larger than the median value of the models that calculate SOA in a more
simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model
at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24
models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a
median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported
both OA and sulfate burdens, the median value of the OA/sulfate burden ratio
is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9
models higher than 1. For 26 models that reported OA deposition fluxes, the
median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which
is on average 85% of the total OA deposition.
Fine aerosol organic carbon (OC) and OA observations from continuous
monitoring networks and individual field campaigns have been used for model
evaluation. At urban locations, the model–observation comparison indicates
missing knowledge on anthropogenic OA sources, both strength and seasonality.
The combined model–measurements analysis suggests the existence of increased
OA levels during summer due to biogenic SOA formation over large areas of the
USA that can be of the same order of magnitude as the POA, even at urban
locations, and contribute to the measured urban seasonal pattern.
Global models are able to simulate the high secondary character of OA
observed in the atmosphere as a result of SOA formation and POA aging,
although the amount of OA present in the atmosphere remains largely
underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51)
based on the comparison against OC (OA) urban data of all models at the
surface, −0.15 (+0.51) when compared with remote measurements, and
−0.30 for marine locations with OC data. The mean temporal correlations
across all stations are low when compared with OC (OA) measurements: 0.47
(0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for
marine stations with OC data. The combination of high (negative) MNB and
higher correlation at urban stations when compared with the low MNB and lower
correlation at remote sites suggests that knowledge about the processes that
govern aerosol processing, transport and removal, on top of their sources, is
important at the remote stations. There is no clear change in model skill
with increasing model complexity with regard to OC or OA mass concentration.
However, the complexity is needed in models in order to distinguish between
anthropogenic and natural OA as needed for climate mitigation, and to
calculate the impact of OA on climate accurately. |
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