scholarly journals Two new submodels for the Modular Earth Submodel System (MESSy): New Aerosol Nucleation (NAN) and small ions (IONS) version 1.0

2018 ◽  
Author(s):  
Sebastian Ehrhart ◽  
Eimear M. Dunne ◽  
Hanna E. Manninen ◽  
Tuomo Nieminen ◽  
Jos Lelieveld ◽  
...  
Keyword(s):  
Pair Production ◽  
Production Rate ◽  
Aerosol Particle ◽  
Atmospheric Chemistry ◽  
Particle Formation ◽  
Ion Pair ◽  
New Particle Formation ◽  
Production Rates ◽  
Organic Species ◽  
Good Agreement

Abstract. Two new submodels for the Modular Earth Submodel System (MESSy) were developed. The New Aerosol Nucleation submodel (NAN) includes new parameterisations of aerosol particle formation rates published in recent years. These parameterisations include ion-induced nucleation and nucleation of pure organic species. NAN calculates the rate of new particle formation based on the aforementioned parameterisations for aerosol submodels in the ECHAM/MESSy Atmospheric chemistry - Climate (EMAC) model. The Ion pair production rate, needed to calculate the ion-induced or -mediated nucleation, is described using the new submodel IONS, which provides ion pair production rates for other submodels within the MESSy framework. Both new submodels were tested in EMAC simulations. These simulations showed good agreement with ground based observations.

scholarly journals Two new submodels for the Modular Earth Submodel System (MESSy): New Aerosol Nucleation (NAN) and small ions (IONS) version 1.0

2018 ◽  
Vol 11 (12) ◽  
pp. 4987-5001
Author(s):  
Sebastian Ehrhart ◽  
Eimear M. Dunne ◽  
Hanna E. Manninen ◽  
Tuomo Nieminen ◽  
Jos Lelieveld ◽  
...  
Keyword(s):  
Pair Production ◽  
Production Rate ◽  
Aerosol Particle ◽  
Atmospheric Chemistry ◽  
Particle Formation ◽  
Ion Pair ◽  
New Particle Formation ◽  
Production Rates ◽  
Organic Species ◽  
Good Agreement

Abstract. Two new submodels for the Modular Earth Submodel System (MESSy) were developed. The New Aerosol Nucleation (NAN) submodel includes new parameterisations of aerosol particle formation rates published in recent years. These parameterisations include ion-induced nucleation and nucleation of pure organic species. NAN calculates the rate of new particle formation based on the aforementioned parameterisations for aerosol submodels in the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. The ion pair production rate, needed to calculate the ion-induced or ion-mediated nucleation, is described using the new submodel IONS, which provides ion pair production rates for other submodels within the MESSy framework. Both new submodels were tested in EMAC simulations. These simulations showed good agreement with ground-based observations.

scholarly journals New particle formation in the sulfuric acid–dimethylamine–water system: reevaluation of CLOUD chamber measurements and comparison to an aerosol nucleation and growth model

2018 ◽  
Vol 18 (2) ◽  
pp. 845-863 ◽  
Author(s):  
Andreas Kürten ◽  
Chenxi Li ◽  
Federico Bianchi ◽  
Joachim Curtius ◽  
António Dias ◽  
...  
Keyword(s):  
Sulfuric Acid ◽  
Detection Threshold ◽  
Sulfuric Acid Concentration ◽  
Water System ◽  
Particle Formation ◽  
New Particle Formation ◽  
Flow Tube ◽  
Aerosol Model ◽  
Wide Range ◽  
Good Agreement

Abstract. A recent CLOUD (Cosmics Leaving OUtdoor Droplets) chamber study showed that sulfuric acid and dimethylamine produce new aerosols very efficiently and yield particle formation rates that are compatible with boundary layer observations. These previously published new particle formation (NPF) rates are reanalyzed in the present study with an advanced method. The results show that the NPF rates at 1.7 nm are more than a factor of 10 faster than previously published due to earlier approximations in correcting particle measurements made at a larger detection threshold. The revised NPF rates agree almost perfectly with calculated rates from a kinetic aerosol model at different sizes (1.7 and 4.3 nm mobility diameter). In addition, modeled and measured size distributions show good agreement over a wide range of sizes (up to ca. 30 nm). Furthermore, the aerosol model is modified such that evaporation rates for some clusters can be taken into account; these evaporation rates were previously published from a flow tube study. Using this model, the findings from the present study and the flow tube experiment can be brought into good agreement for the high base-to-acid ratios (∼ 100) relevant for this study. This confirms that nucleation proceeds at rates that are compatible with collision-controlled (a.k.a. kinetically controlled) NPF for the conditions during the CLOUD7 experiment (278 K, 38 % relative humidity, sulfuric acid concentration between 1 × 106 and 3 × 107 cm−3, and dimethylamine mixing ratio of ∼ 40 pptv, i.e., 1 × 109 cm−3).

scholarly journals Concentrations and fluxes of aerosol particles during the LAPBIAT measurement campaign at Värriö field station

2007 ◽  
Vol 7 (14) ◽  
pp. 3683-3700 ◽  
Author(s):  
T. M. Ruuskanen ◽  
M. Kaasik ◽  
P. P. Aalto ◽  
U. Hõrrak ◽  
M. Vana ◽  
...  
Keyword(s):  
Kola Peninsula ◽  
Aerosol Particle ◽  
Aerosol Particles ◽  
Particle Formation ◽  
Nucleation Event ◽  
New Particle Formation ◽  
Air Ions ◽  
Field Station ◽  
Air Mass ◽  
Measurement Campaign

Abstract. The LAPBIAT measurement campaign took place in the Värriö SMEAR I measurement station located in Eastern Lapland in the spring of 2003 between 26 April and 11 May. In this paper we describe the measurement campaign, concentrations and fluxes of aerosol particles, air ions and trace gases, paying special attention to an aerosol particle formation event broken by a air mass change from a clean Arctic air mass with new particle formation to polluted one approaching from industrial areas of Kola Peninsula, Russia, lacking new particle formation. Aerosol particle number flux measurements show strong downward fluxes during that time. Concentrations of coarse aerosol particles were high for 1–2 days before the nucleation event (i.e. 28–29 April), very low immediately before and during the observed aerosol particle formation event (30 April) and increased moderately from the moment of sudden break of the event. In general particle deposition measurements based on snow samples show the same changes. Measurements of the mobility distribution of air ions showed elevated concentrations of intermediate air ions during the particle formation event. We estimated the growth rates in the nucleation mode size range. For particles <10 nm, the growth rate increases with size on 30 April. Dispersion modelling made with model SILAM support the conclusion that the nucleation event was interrupted by an outbreak of sulphate-rich air mass in the evening of 30 April that originated from the industry at Kola Peninsula, Russia. The results of this campaign highlight the need for detailed research in atmospheric transport of air constituents for understanding the aerosol dynamics.

scholarly journals Simulation of organics in the atmosphere: evaluation of EMACv2.54 with the Mainz Organic Mechanism (MOM) coupled to the ORACLE (v1.0) submodel

2021 ◽  
Author(s):  
Andrea Pozzer ◽  
Simon Reifenberg ◽  
Vinod Kumar ◽  
Bruno Franco ◽  
Domenico Taraborrelli ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Circulation Model ◽  
Organic Aerosol ◽  
Efficient Estimation ◽  
Chemical Degradation ◽  
Aerosol Formation ◽  
Organic Species ◽  
Volatile Organic ◽  
Good Agreement

Abstract. An updated and expanded representation of organics in the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) has been evaluated. First, the comprehensive Mainz Organic Mechanism (MOM) in the submodel MECCA (Module Efficiently Calculating the Chemistry of the Atmosphere) was activated with explicit degradation of organic species up to five carbon atoms and a simplified mechanism for larger molecules. Second, the ORACLE submodel (version 1.0) considers now condensation on aerosols for all organics in the mechanism. Parameterizations for aerosol yields are used only for the lumped species that are not included in the explicit mechanism. The simultaneous usage of MOM and ORACLE allows an efficient estimation, not only of the chemical degradation of the simulated volatile organic compounds, but also of the contribution of organics to the growth and fate of (organic) aerosol, with a complexity of the mechanism largely increased compared to EMAC simulations with more simplified chemistry. The model evaluation presented here reveals that the OH concentration is well reproduced globally, while significant biases for observed oxygenated organics are present. We also investigate the general properties of the aerosols and their composition, showing that the more sophisticated and process-oriented secondary aerosol formation does not degrade the good agreement of previous model configurations with observations at the surface, allowing further research in the field of gas-aerosol interactions.

scholarly journals Lifetime and production rate of NOx in the upper stratosphere and lower mesosphere in the polar spring/summer after the solar proton event in October–November 2003

2012 ◽  
Vol 12 (7) ◽  
pp. 17703-17721
Author(s):  
F. Friederich ◽  
T. von Clarmann ◽  
B. Funke ◽  
H. Nieder ◽  
J. Orphal ◽  
...  
Keyword(s):  
Production Rate ◽  
Polar Region ◽  
Solar Proton ◽  
Ion Pair ◽  
Solar Proton Event ◽  
Proton Event ◽  
Production Rates ◽  
Model Simulations ◽  
D Model ◽  
Ionization Rates

Abstract. We present altitude dependent lifetimes of NOx, determined with MIPAS/ENVISAT, for the southern polar region after the solar proton event in October–November 2003. Varying in latitude and decreasing in altitude they range from about two days at 64 km to about 20 days at 44 km. The lifetimes are controlled by transport, mixing and photolysis. We infer dynamical lifetimes by comparison of the observed decay to photolytical lifetimes calculated with the SLIMCAT 3-D Model. Photochemical loss contributes to the observed NOx depletion by 10% at 44 km, increasing with altitude to 35% at 62 km at a latitude of –63° S. At higher latitudes, the contribution of photochemical loss can be even more important. In addition, we show the correlation of modeled ionization rates and observed NOx densities under consideration of the determined lifetimes of NOx, and calculate altitude dependent effective production rates of NOx due to ionization. For that we compare ionization rates of the AIMOS data base with the MIPAS measurements for the whole Austral polar summer 2003/04. We derive effective NOx-production rates to be applied to the AIMOS ionization rates which range from about 0.2 NOx-molecules per ion pair at 44 km to 0.9 NOx-molecules per ion pair at 54 km at a latitude of –63° S. At –73° S, the NOx-production rate ranges from about 0.2 NOx-molecules per ion pair at 44 km to 1.0 NOx-molecules per ion pair at 60 km. These effective production rates are considerably lower than predicted by box model simulations which could hint at an overestimation of the modeled ionization rates.

Formation and growth of aerosol particles in boreal forest of Siberia

2021 ◽  
Author(s):  
Anastasiia Demakova ◽  
Olga Garmash ◽  
Ekaterina Ezhova ◽  
Mikhail Arshinov ◽  
Denis Davydov ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Size Distribution ◽  
Atmospheric Chemistry ◽  
Boreal Forests ◽  
Aerosol Particles ◽  
Particle Formation ◽  
Atmospheric Environment ◽  
Environmental Research ◽  
New Particle Formation ◽  
Number Size Distribution

&lt;p&gt;New Particle Formation (NPF) is a process in which a large number of particles is formed in the atmosphere via gas-to-particle conversion. Previous research shows the important role of formation of new particles for atmosphere, clouds and climate (Kerminen, V.-M. et al. 2018).&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; There exist measurements from different parts of the world which show that NPF is happening worldwide (Kerminen, V.-M. et al. 2018). Measurements at SMEAR II station in Hyyti&amp;#228;l&amp;#228;, Finland (Hari P. and Kulmala M., 2005), show that NPF is a common process in Finland&amp;#8217;s boreal forests. However, measurements at Zotto station in Siberia, Russia, show that NPF events are very rare in that area (Wiedensohler A. et al., 2018). Measurements in Siberian boreal forests are sparse. We have conducted new measurements at Fonovaya station near Tomsk (Siberia, Russia) using Neutral cluster Air Ion Spectrometer (NAIS), Particle Size Magnifier (PSM), Differential Mobility Particle Sizer (DMPS) and the Atmospheric Pressure interface Time-Of-Flight mass spectrometer (APi-TOF). Those instruments measure aerosol particle number size distribution (NAIS, DMPS), ion number size distribution (NAIS), size distribution of small particles (PSM) and chemical composition of aerosol particles (APi-TOF). The novelty of this work is that such complex measurements have not been done in Siberia before.&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; Here we report the first results of our research on NPF phenomenon in Siberian boreal forest. We present detailed statistics of NPF events, as well as formation rates (J) and growth rates (GR) of aerosol particles. The results from Fonovaya station are compared with those from SMEAR II station and from SMEAR Estonia station in J&amp;#228;rvselja, Estonia.&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Literature&lt;/p&gt;&lt;ul&gt;&lt;li&gt;[1] Kerminen V.-M. et al. &amp;#8220;Atmospheric new particle formation and growth: review of field observations&amp;#8221;. In: Environmental Research Letters 10 (2018), p. 103003.&lt;/li&gt; &lt;li&gt;[2] Wiedensohler A. et al. &amp;#8220;Infrequent new particle formation over the remote boreal forest of Siberia&amp;#8221;. In: Atmospheric Environment 200 (2019), pp. 167&amp;#8211;169.&lt;/li&gt; &lt;li&gt;[3] Dada L. et al. &amp;#8220;Long-term analysis of clear-sky new particle formation events and nonevents in Hyyti&amp;#228;l&amp;#228;&amp;#8221;. In: Atmospheric Chemistry and Physics 10 (2017), pp. 6227&amp;#8211;6241.&lt;/li&gt; &lt;/ul&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Saharan Dust Aerosols Change Deep Convective Cloud Prevalence, Possibly by Inhibiting Marine New Particle Formation

2020 ◽  
Vol 33 (21) ◽  
pp. 9467-9480
Author(s):  
Lauren M. Zamora ◽  
Ralph A. Kahn
Keyword(s):  
North Atlantic ◽  
Atmospheric Chemistry ◽  
Dimethyl Sulfide ◽  
Global Climate ◽  
Spatial Scales ◽  
Particle Formation ◽  
Meteorological Factor ◽  
Saharan Dust ◽  
New Particle Formation ◽  
Tropical North Atlantic

AbstractDeep convective clouds (DCCs) are important to global climate, atmospheric chemistry, and precipitation. Dust, a dominant aerosol type over the tropical North Atlantic, has potentially large microphysical impacts on DCCs over this region. However, dust effects are difficult to identify, being confounded by covarying meteorology and other factors. Here, a method is developed to quantify DCC responses to dust and other aerosols at large spatial and temporal scales despite these uncertainties. Over 7 million tropical North Atlantic cloud, aerosol, and meteorological profiles from CloudSat satellite data and MERRA-2 reanalysis products are used to stratify cloud observations into meteorological regimes, objectively select a priori assumptions, and iteratively test uncertainty sensitivity. Dust is robustly associated with a 54% increase in DCC prevalence. However, marine aerosol proxy concentrations are 5 times more predictive of dust-associated increases in DCC prevalence than the dust itself, or any other aerosol or meteorological factor. Marine aerosols are also the most predictive factor for the even larger increases in DCC prevalence (61%–87%) associated with enhanced dimethyl sulfide and combustion and sulfate aerosols. Dust-associated increases in DCC prevalence are smaller at high dust concentrations than at low concentrations. These observations suggest that not only is dust a comparatively ineffective CCN source, but it may also act as a condensation/coagulation sink for chemical precursors to CCN, reducing total CCN availability over large spatial scales by inhibiting new particle formation from marine emissions. These observations represent the first time this process, previously predicted by models, has been supported and quantified by measurements.

Airborne observations of the effect of a cold front on the aerosol particle size distribution and new particle formation

2010 ◽  
Vol 136 (649) ◽  
pp. 944-961 ◽  
Author(s):  
Justin R. Peter ◽  
Steven T. Siems ◽  
Jørgen B. Jensen ◽  
John L. Gras ◽  
Yutaka Ishizaka ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Aerosol Particle ◽  
Cold Front ◽  
Particle Formation ◽  
New Particle Formation ◽  
Aerosol Particle Size

Data mining and machine learning to enhance new-particle formation identification and analysis

2020 ◽  
Author(s):  
Martha A. Zaidan ◽  
Pak L. Fung ◽  
Darren Wraith ◽  
Tuomo Nieminen ◽  
Tareq Hussein ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Atmospheric Chemistry ◽  
Data Science ◽  
Large Data ◽  
Particle Formation ◽  
Linear Process ◽  
Data Sets ◽  
New Particle Formation ◽  
Area Of Interest

&lt;p&gt;Data Mining (DM) and Machine Learning (ML) have become very popular modern statistical learning tools in solving many complex scientific problems. In this work, we present two case studies that used DM and ML techniques to enhance new-particle formation (NPF) identification and analysis. Extensive measurements and large data sets related to NPF and other ambient variables have been collected in arctic and boreal regions. The focus area of our studies is the SMEAR II station located in Hyyti&amp;#228;l&amp;#228; forest, Finland that is in the area of interest of the Pan-Eurasian Experiment (PEEX).&lt;/p&gt;&lt;p&gt;Atmospheric NPF is an important source of climatically relevant atmospheric aerosol particles. NPF is typically observed by monitoring the time-evolution of ambient aerosol particle size distributions. Due to the noisiness of the real-world ambient data, currently the most reliable way to classify measurement days into NPF event/non-event days is through a manual visualisation method. However, manual labour, with long multi-year time series, is extremely time-consuming and human subjectivity poses challenges for comparing the results of different data sets. In this case, ML classifier is used to classify event/non-event days of NPF using a manually generated database. The results demonstrate that ML-based approaches point towards the potential of these methods and suggest further exploration in this direction.&lt;/p&gt;&lt;p&gt;Furthermore, NPF is a very non-linear process that includes atmospheric chemistry of precursors and clustering physics as well as subsequent growth before NPF can be observed. Thanks to ongoing efforts, now there exists a tremendous amount of atmospheric data, obtained through continuous measurements directly from the atmosphere. This fact makes the analysis by human brains difficult, on the other hand, enables the usage of modern data science techniques. Here, we demonstrate the use of DM method, named mutual information (MI) to understand NPF events and a wide variety of simultaneously monitored ambient variables. The same results are obtained by the proposed MI method which operates without supervision and without the need of understanding the physics deeply.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document