| 1. |
- Fanourgakis, George S., et al.
(författare)
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Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation
- 2019
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 19:13, s. 8591-8617
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Tidskriftsartikel (refereegranskat)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 3nm) 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 120nm). 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 0.6ms-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 (Nd=Na) and to updraft velocity (Nd=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 Nd=Na and Nd=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 intermodel biases on the aerosol indirect effect.
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| 2. |
- Fuzzi, S., et al.
(författare)
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Particulate matter, air quality and climate : lessons learned and future needs
- 2015
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 15:14, s. 8217-8299
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Tidskriftsartikel (refereegranskat)abstract
- The literature on atmospheric particulate matter (PM), or atmospheric aerosol, has increased enormously over the last 2 decades and amounts now to some 1500-2000 papers per year in the refereed literature. This is in part due to the enormous advances in measurement technologies, which have allowed for an increasingly accurate understanding of the chemical composition and of the physical properties of atmospheric particles and of their processes in the atmosphere. The growing scientific interest in atmospheric aerosol particles is due to their high importance for environmental policy. In fact, particulate matter constitutes one of the most challenging problems both for air quality and for climate change policies. In this context, this paper reviews the most recent results within the atmospheric aerosol sciences and the policy needs, which have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-aerosol interactions and effects of PM on human health and the environment. However, while airborne particulate matter is responsible for globally important influences on premature human mortality, we still do not know the relative importance of the different chemical components of PM for these effects. Likewise, the magnitude of the overall effects of PM on climate remains highly uncertain. Despite the uncertainty there are many things that could be done to mitigate local and global problems of atmospheric PM. Recent analyses have shown that reducing black carbon (BC) emissions, using known control measures, would reduce global warming and delay the time when anthropogenic effects on global temperature would exceed 2 degrees C. Likewise, cost-effective control measures on ammonia, an important agricultural precursor gas for secondary inorganic aerosols (SIA), would reduce regional eutrophication and PM concentrations in large areas of Europe, China and the USA. Thus, there is much that could be done to reduce the effects of atmospheric PM on the climate and the health of the environment and the human population. A prioritized list of actions to mitigate the full range of effects of PM is currently undeliverable due to shortcomings in the knowledge of aerosol science; among the shortcomings, the roles of PM in global climate and the relative roles of different PM precursor sources and their response to climate and land use change over the remaining decades of this century are prominent. In any case, the evidence from this paper strongly advocates for an integrated approach to air quality and climate policies.
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