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1.
Atmos Chem Phys ; 19(13): 8591-8617, 2019 Jul.
Article in English | MEDLINE | ID: mdl-33273898

ABSTRACT

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13% and -22% for updraft velocities 0.3 and 0.6 ms-1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂N d/∂N a) and to updraft velocity (∂N d/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂N d/∂N a and ∂N d/∂w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

2.
Sci Rep ; 5: 14628, 2015 Sep 28.
Article in English | MEDLINE | ID: mdl-26411261

ABSTRACT

A significant wetting trend since the early 1980s in Tibetan Plateau (TP) is most conspicuous in central and eastern Asia as shown in the instrumental data and the long-term moisture sensitive tree rings. We found that anomalies in the large-scale oceanic and atmospheric circulations do not play a significant role on the wetting trend in TP. Meanwhile, the weak correlation between local temperature and precipitation suggests that the temperature-induced enhancement of the local water cycle cannot fully explain the wetting trend either. This may indicate the presence of nonlinear processes between local temperature and precipitation. We hypothesize that the current warming may enhance the emissions of the biogenic volatile organic compounds (BVOC) that can increase the secondary organic aerosols (SOA), contributing to the precipitation increase. The wetting trend can increase the vegetation cover and cause a positive feedback on the BVOC emissions. Our simulations indicate a significant contribution of increased BVOC emissions to the regional organic aerosol mass and the simulated increase in BVOC emissions is significantly correlated with the wetting trend in TP.

3.
Proc Natl Acad Sci U S A ; 112(23): 7123-8, 2015 Jun 09.
Article in English | MEDLINE | ID: mdl-26015574

ABSTRACT

Oxidation products of monoterpenes and isoprene have a major influence on the global secondary organic aerosol (SOA) burden and the production of atmospheric nanoparticles and cloud condensation nuclei (CCN). Here, we investigate the formation of extremely low volatility organic compounds (ELVOC) from O3 and OH radical oxidation of several monoterpenes and isoprene in a series of laboratory experiments. We show that ELVOC from all precursors are formed within the first minute after the initial attack of an oxidant. We demonstrate that under atmospherically relevant concentrations, species with an endocyclic double bond efficiently produce ELVOC from ozonolysis, whereas the yields from OH radical-initiated reactions are smaller. If the double bond is exocyclic or the compound itself is acyclic, ozonolysis produces less ELVOC and the role of the OH radical-initiated ELVOC formation is increased. Isoprene oxidation produces marginal quantities of ELVOC regardless of the oxidant. Implementing our laboratory findings into a global modeling framework shows that biogenic SOA formation in general, and ELVOC in particular, play crucial roles in atmospheric CCN production. Monoterpene oxidation products enhance atmospheric new particle formation and growth in most continental regions, thereby increasing CCN concentrations, especially at high values of cloud supersaturation. Isoprene-derived SOA tends to suppress atmospheric new particle formation, yet it assists the growth of sub-CCN-size primary particles to CCN. Taking into account compound specific monoterpene emissions has a moderate effect on the modeled global CCN budget.


Subject(s)
Air Pollutants/chemistry , Volatile Organic Compounds/chemical synthesis , Atmosphere , Models, Theoretical , Ozone/chemistry
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