Preliminary results of the project “Supersito” concerning the atmospheric aerosol composition in Emilia-Romagna region, Italy: PM source apportionment and aerosol size distribution

Author(s):  
V. Poluzzi ◽  
A. Trentini ◽  
F. Scotto ◽  
I. Ricciardelli ◽  
S. Ferrari ◽  
...  
2015 ◽  
Vol 15 (12) ◽  
pp. 6943-6958 ◽  
Author(s):  
E. Crosbie ◽  
J.-S. Youn ◽  
B. Balch ◽  
A. Wonaschütz ◽  
T. Shingler ◽  
...  

Abstract. A 2-year data set of measured CCN (cloud condensation nuclei) concentrations at 0.2 % supersaturation is combined with aerosol size distribution and aerosol composition data to probe the effects of aerosol number concentrations, size distribution and composition on CCN patterns. Data were collected over a period of 2 years (2012–2014) in central Tucson, Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are typically lowest in spring (233 cm−3), highest in winter (430 cm−3) and have a secondary peak during the North American monsoon season (July to September; 372 cm−3). There is significant variability outside of seasonal patterns, with extreme concentrations (1 and 99 % levels) ranging from 56 to 1945 cm−3 as measured during the winter, the season with highest variability. Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with size and number alone able to predict 82 % of the variance in CCN concentration. Changes in aerosol chemical composition are typically aligned with changes in size and aerosol number, such that hygroscopicity can be parameterized even though it is still variable. In summer, models based on fixed chemical composition explain at best only 41 % (pre-monsoon) and 36 % (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol (SOA) production, the competition between new particle formation and condensational growth, the complex interaction of meteorology, regional and local emissions and multi-phase chemistry during the North American monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on longer timescales in winter. Parameterized models typically exhibit improved predictive skill when there are strong relationships between CCN concentrations and the prevailing meteorology and dominant aerosol physicochemical processes, suggesting that similar findings could be possible in other locations with comparable climates and geography.


2007 ◽  
Vol 64 (2) ◽  
pp. 441-459 ◽  
Author(s):  
Craig A. Stroud ◽  
Athanasios Nenes ◽  
Jose L. Jimenez ◽  
Peter F. DeCarlo ◽  
J. Alex Huffman ◽  
...  

Abstract Measurements of aerosol size distribution, chemical composition, and cloud condensation nuclei (CCN) concentration were performed during the Chemical Emission, Loss, Transformation, and Interactions with Canopies (CELTIC) field program at Duke Forest in North Carolina. A kinetic model of the cloud activation of ambient aerosol in the chamber of the CCN instrument was used to perform an aerosol–CCN closure study. This study advances prior investigations by employing a novel fitting algorithm that was used to integrate scanning mobility particle sizer (SMPS) measurements of aerosol number size distribution and aerosol mass spectrometer (AMS) measurements of the mass size distribution for sulfate, nitrate, ammonium, and organics into a single, coherent description of the ambient aerosol in the size range critical to aerosol activation (around 100-nm diameter). Three lognormal aerosol size modes, each with a unique internally mixed composition, were used as input into the kinetic model. For the two smaller size modes, which control CCN number concentration, organic aerosol mass fractions for the defined cases were between 58% and 77%. This study is also unique in that the water vapor accommodation coefficient was estimated based on comparing the initial timing for CCN activation in the instrument chamber with the activation predicted by the kinetic model. The kinetic model overestimated measured CCN concentrations, especially under polluted conditions. Prior studies have attributed a positive model bias to an incomplete understanding of the aerosol composition, especially the role of organics in the activation process. This study shows that including measured organic mass fractions with an assumed organic aerosol speciation profile (pinic acid, fulvic acid, and levoglucosan) and an assumed organic aerosol solubility of 0.02 kg kg−1 still resulted in a significant model positive bias for polluted case study periods. The slope and y intercept for the CCN predicted versus CCN observed regression was found to be 1.9 and −180 cm−3, respectively. The overprediction generally does not exceed uncertainty limits but is indicative that a bias exists in the measurements or application of model. From this study, uncertainties in the particle number and mass size distributions as the cause for the model bias can be ruled out. The authors are also confident that the model is including the effects of growth kinetics on predicted activated number. However, one cannot rule out uncertainties associated with poorly characterized CCN measurement biases, uncertainties in assumed organic solubility, and uncertainties in aerosol mixing state. Sensitivity simulations suggest that assuming either an insoluble organic fraction or external aerosol mixing were both sufficient to reconcile the model bias.


2006 ◽  
Vol 6 (6) ◽  
pp. 11845-11875 ◽  
Author(s):  
E. Debry ◽  
K. Fahey ◽  
K. Sartelet ◽  
B. Sportisse ◽  
M. Tombette

Abstract. We briefly present in this short paper a new SIze REsolved Aerosol Model (SIREAM) which simulates the evolution of atmospheric aerosol by solving the General Dynamic Equation (GDE). SIREAM segregates the aerosol size distribution into sections and solves the GDE by splitting coagulation and condensation/evaporation. A moving sectional approach is used to describe the size distribution change due to condensation/evaporation and a hybrid method has been developed to lower the computational burden. SIREAM uses the same physical parameterizations as those used in the Modal Aerosol Model, MAM sartelet05development. It is hosted in the modeling system POLYPHEMUS (Mallet et al., 2006) but can be linked to any other three-dimensional Chemistry-Transport Model.


2012 ◽  
Vol 12 (8) ◽  
pp. 3783-3790 ◽  
Author(s):  
Q. Zhang ◽  
J. Meng ◽  
J. Quan ◽  
Y. Gao ◽  
D. Zhao ◽  
...  

Abstract. The impact of aerosol composition on cloud condensation nuclei (CCN) activity were analyzed in this study based on field experiments carried out at downtown Tianjin, China in September 2010. In the experiments, the CCN measurements were performed at supersaturation (SS) of 0.1%, 0.2% and 0.4% using a thermal-gradient diffusion chamber (DMT CCNC), whereas the aerosol size distribution and composition were simultaneously measured with a TSI SMPS and an Aerodyne Aerosol Mass Spectrometer (AMS), respectively. The results show that the influence of aerosol composition on CCN activity is notable under low SS (0.1%), and their influence decreased with increasing SS. For example, under SS of 0.1%, the CCN activity increases from 4.5±2.6% to 12.8±6.1% when organics fraction decrease from 30–40% to 10–20%. The rate of increase reached up to 184%. While under SS of 0.4%, the CCN activity increases only from 35.7±19.0% to 46.5±12.3% correspondingly. The calculated NCCN based on the size-resolved activation ratio and aerosol number size distribution correlated well with observed NCCN at high SS (0.4%), but this consistence decreased with the falling of SS. The slopes of linear fitted lines between calculated and observed NCCN are 0.708, 0.947, and 0.995 at SS of 0.1%, 0.2% and 0.4% respectively. Moreover, the stand deviation (SD) of calculated NCCN increased with the decreasing of SS. A case study of CCN closure analyses indicated that the calculated error of NCCN could reach up to 34% at SS of 0.1% if aerosol composition were not included, and the calculated error decreased with the raising of SS. It is decreased to 9% at SS of 0.2%, and further decreased to 4% at SS of 0.4%.


2012 ◽  
Vol 12 (1) ◽  
pp. 1493-1516
Author(s):  
Q. Zhang ◽  
J. Meng ◽  
J. Quan ◽  
Y. Gao ◽  
D. Zhao ◽  
...  

Abstract. The impact of aerosol composition on cloud condensation nuclei (CCN) activity was analyzed in this study based on field experiments carried out at downtown Tianjin, China, in September 2010. In the experiments, the CCN measurements were performed at supersaturation (SS) of 0.1%, 0.2% and 0.4% using a thermal-gradient diffusion chamber (DMT CCNC), whereas the aerosol size distribution and composition were simultaneously measured with a TSI SMPS and an Aerodyne Aerosol Mass Spectrometer (AMS), respectively. The results show that the influence of aerosol composition on CCN activity is notable under low SS (0.1%), and their influence decreased with increasing SS. For example, under SS of 0.1%, the CCN activity increases from 4.5 ± 2.6% to 12.8 ± 6.1% when organics fraction decrease from 30–40% to 10–20%. The rate of increase reaches up to 184%. While under SS of 0.4%, the CCN activity increases only from 35.7 ± 19.0% to 46.5 ± 12.3%, correspondingly. The calculated NCCN based on the size-resolved activation ratio and aerosol number size distribution correlates well with observed NCCN at high SS (0.4%), but this correlation decreases with the falling of SS. The slopes of linear fitted lines between calculated and observed NCCN are 0.708, 0.947, and 0.995 at SS of 0.1%, 0.2% and 0.4%, respectively. Moreover, the standard deviation (SD) of calculated NCCN increases with the decreasing of SS. A case study of CCN closure analyses indicates that the calculated error of NCCN can reach up to 34% at SS of 0.1% if aerosol composition is not included, and the calculated error decreases with the raising of SS. It decreases to 9% at SS of 0.2%, and further decreases to 4% at SS of 0.4%.


2014 ◽  
Vol 14 (5) ◽  
pp. 5611-5651 ◽  
Author(s):  
Y. Y. Cui ◽  
A. Hodzic ◽  
J. N. Smith ◽  
J. Ortega ◽  
J. Brioude ◽  
...  

Abstract. Formation and growth of ultrafine particles is crudely represented in chemistry-climate models, which contributes to uncertainties in aerosol composition, size distribution, and aerosol effects on cloud condensation nuclei (CCN) concentrations. Measurements of ultrafine particles, their precursor gases, and meteorological parameters were performed in a ponderosa pine forest in the Colorado Front Range in July–August 2011, and were analyzed to study processes leading to Aitken-mode Particle burst Events (APEs). These measurements suggest that APEs were associated with the arrival at the site of anthropogenic pollution plumes around noon or in the early afternoon. Number concentrations of ultrafine (4 to 30 nm diameter) particles typically exceeded 10 000 cm−3 during APEs, and these elevated concentrations coincided with increased SO2 and monoterpene concentrations, and led to a factor of two increase in CCN concentrations at 0.5% supersaturation. The APEs were simulated using the regional WRF-Chem model, which was extended to account for ultrafine particle sizes starting at 1 nm in diameter, to include an empirical activation nucleation scheme in the planetary boundary layer, and to explicitly simulate the subsequent growth of Aitken particles by condensation of organic and inorganic vapors. Comparisons with aerosol size distribution measurements showed that simulations using the activation nucleation parameterization reasonably captured aerosol number concentrations and size distribution during APEs, as well as ground level CCN concentrations. Results suggest that sulfuric acid from anthropogenic SO2 triggers APEs, and that the condensation of monoterpene oxidation products onto freshly nucleated particles drives their growth. The simulated growth rate of 3.4 nm h−1 for small particles (4–30 nm in diameter) was comparable to the measured average value of 2.3 nm h−1. Model results also suggest that the presence of APEs tends to modify the composition of sub-100 nm diameter particles, leading to generally higher absolute mass concentrations of sulfate as well as organic aerosols with a higher sulfate content. Sensitivity simulations suggest that the representation of nucleation processes in the model largely influences the predicted number concentrations and thus CCN concentrations. We estimate that nucleation contributes to 65% of surface CCN at 0.5% supersaturation in this pine forest environment.


2010 ◽  
Vol 10 (2) ◽  
pp. 4189-4223 ◽  
Author(s):  
D. S. Ward ◽  
T. Eidhammer ◽  
W. R. Cotton ◽  
S. M. Kreidenweis

Abstract. Variations in the chemical composition of atmospheric aerosols alter their hygroscopicity and can lead to changes in the cloud-active fraction of the aerosols, or cloud condensation nuclei (CCN) number concentration. To investigate the importance of this effect under different atmospheric conditions, cloud droplet formation was simulated with a Lagrangian parcel model. Initial values of updraft speed and temperature were systematically varied along with aerosol number concentration, size and hygroscopicity (represented by the hygroscopicity parameter, κ). A previous study classifies the sensitivity of CCN activity to compositional changes based on the supersaturation reached in the parcel model. We found that these classifications could not be generalized to a range of aerosol size distribution median radii. Instead, variations in sensitivity with size depend on the location of the dry critical radius for droplet activation relative to the size distribution median radius. The parcel model output was used to construct droplet activation lookup tables based on κ that were implemented in the Regional Atmospheric Modeling System (RAMS) microphysical scheme. As a first application of this system, aerosol hygroscopicity and size were varied in a series of RAMS mesoscale simulations designed to investigate the sensitivity of a mixed-phase orographic cloud case to the parameter variations. Observations from a recent field campaign in northwestern Colorado provided the basis for the aerosol field initializations. Model results show moderate sensitivity in the distribution of total case precipitation to extreme changes in κ, and minimal sensitivity to observed changes in estimated κ. The impact of varying aerosol hygroscopicity diminished with increasing median radius, as expected from the parcel model results. The conclusions drawn from these simulations could simplify similar research in other cloud regimes by defining the need, or lack of need, for detailed knowledge of aerosol composition.


2015 ◽  
Vol 15 (13) ◽  
pp. 18109-18149 ◽  
Author(s):  
E. Asmi ◽  
V. Kondratyev ◽  
D. Brus ◽  
T. Laurila ◽  
H. Lihavainen ◽  
...  

Abstract. Four years of continuous aerosol number size distribution measurements from an Arctic Climate Observatory in Tiksi Russia are analyzed. Source region effects on particle modal features, and number and mass concentrations are presented for different seasons. The monthly median total aerosol number concentration in Tiksi ranges from 184 cm-3 in November to 724 cm-3 in July with a local maximum in March of 481 cm-3. The total mass concentration has a distinct maximum in February–March of 1.72–2.38 μg m-3 and two minimums in June of 0.42 μg m-3 and in September–October of 0.36–0.57 μg m-3. These seasonal cycles in number and mass concentrations are related to isolated aerosol sources such as Arctic haze in early spring which increases accumulation and coarse mode numbers, and biogenic emissions in summer which affects the smaller, nucleation and Aitken mode particles. The impact of temperature dependent natural emissions on aerosol and cloud condensation nuclei numbers was significant. Therefore, in addition to the precursor emissions of biogenic volatile organic compounds, the frequent Siberian forest fires, although far are suggested to play a role in Arctic aerosol composition during the warmest months. During calm and cold months aerosol concentrations were occasionally increased by nearby aerosol sources in trapping inversions. These results provide valuable information on inter-annual cycles and sources of Arctic aerosols.


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