Browsing by Subject "HYYTIALA"

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  • Kontkanen, Jenni; Olenius, Tinja; Lehtipalo, Katrianne; Vehkamäki, Hanna; Kulmala, Markku; Lehtinen, Kari E. J. (2016)
    We simulated the time evolution of atmospheric cluster concentrations in a one-component system where not only do clusters grow by condensation of monomers, but cluster-cluster collisions also significantly contribute to the growth of the clusters. Our aim was to investigate the consistency of the growth rates of sub-3aEuro-nm clusters determined with different methods and the validity of the common approach to use them to estimate particle formation rates. We compared the growth rate corresponding to particle fluxes (FGR), the growth rate derived from the appearance times of clusters (AGR), and the growth rate calculated based on irreversible vapor condensation (CGR). We found that the relation between the different growth rates depends strongly on the external conditions and the properties of the model substance. The difference between the different growth rates was typically highest at the smallest, sub-2aEuro-nm sizes. FGR was generally lower than AGR and CGR; at the smallest sizes the difference was often very large, while at sizes larger than 2aEuro-nm the growth rates were closer to each other. AGR and CGR were in most cases close to each other at all sizes. The difference between the growth rates was generally lower in conditions where cluster concentrations were high, and evaporation and other losses were thus less significant. Furthermore, our results show that the conventional method used to determine particle formation rates from growth rates may give estimates far from the true values. Thus, care must be taken not only in how the growth rate is determined but also in how it is applied.
  • Heikkinen, Liine; Äijälä, Mikko; Riva, Matthieu; Luoma, Krista Hannele; Dällenbach, Kaspar; Aalto, Juho; Aalto, Pasi; Aliaga Badani, Diego Alonso; Aurela, Minna; Keskinen, Helmi-Marja; Makkonen, Ulla; Rantala, Pekka; Kulmala, Markku; Petäjä, Tuukka; Worsnop, Douglas; Ehn, Mikael (2020)
    The Station for Measuring Ecosystem Atmosphere Relations (SMEAR) II is well known among atmospheric scientists due to the immense amount of observational data it provides of the Earth atmosphere interface. Moreover, SMEAR II plays an important role for the large European research infrastructure, enabling the large scientific community to tackle climate- and air-pollution-related questions, utilizing the high-quality long-term data sets recorded at the site. So far, this well-documented site was missing the description of the seasonal variation in aerosol chemical composition, which helps understanding the complex biogeochemical and physical processes governing the forest ecosystem. Here, we report the sub-micrometer aerosol chemical composition and its variability, employing data measured between 2012 and 2018 using an Aerosol Chemical Speciation Monitor (ACSM). We observed a bimodal seasonal trend in the sub-micrometer aerosol concentration culminating in February (2.7, 1.6, and 5.1 mu g m(-3) for the median, 25th, and 75th percentiles, respectively) and July (4.2, 2.2, and 5.7 mu g m(-3) for the median, 25th, and 75th percentiles, respectively). The wintertime maximum was linked to an enhanced presence of inorganic aerosol species (ca. 50 %), whereas the summertime maximum (ca. 80 % organics) was linked to biogenic secondary organic aerosol (SOA) formation. During the exceptionally hot months of July of 2014 and 2018, the organic aerosol concentrations were up to 70 % higher than the 7-year July mean. The projected increase in heat wave frequency over Finland will most likely influence the loading and chemical composition of aerosol particles in the future. Our findings suggest strong influence of meteorological conditions such as radiation, ambient temperature, and wind speed and direction on aerosol chemical composition. To our understanding, this is the longest time series reported describing the aerosol chemical composition measured online in the boreal region, but the continuous monitoring will also be maintained in the future.
  • Mohr, Claudia; Thornton, Joel A.; Heitto, Arto; Lopez-Hilfiker, Felipe D.; Lutz, Anna; Riipinen, Ilona; Hong, Juan; Donahue, Neil M.; Hallquist, Mattias; Petaja, Tuukka; Kulmala, Markku; Yli-Juuti, Taina (2019)
    Particles formed in the atmosphere via nucleation provide about half the number of atmospheric cloud condensation nuclei, but in many locations, this process is limited by the growth of the newly formed particles. That growth is often via condensation of organic vapors. Identification of these vapors and their sources is thus fundamental for simulating changes to aerosol-cloud interactions, which are one of the most uncertain aspects of anthropogenic climate forcing. Here we present direct molecular-level observations of a distribution of organic vapors in a forested environment that can explain simultaneously observed atmospheric nanoparticle growth from 3 to 50 nm. Furthermore, the volatility distribution of these vapors is sufficient to explain nanoparticle growth without invoking particle-phase processes. The agreement between observed mass growth, and the growth predicted from the observed mass of condensing vapors in a forested environment thus represents an important step forward in the characterization of atmospheric particle growth.
  • Kristensson, Adam; Johansson, Martin; Swietlicki, Erik; Kivekas, Niku; Hussein, Tareq; Nieminen, Tuomo; Kulmala, Markku; Dal Maso, Miikka (2014)
    Particle number size distributions at various field sites are used to identify atmospheric new-particle formation (NPF) event days. However, the spatial distribution of regionally extensive events is unknown. To remedy this situation, the NanoMap method has been developed to enable the estimation of where NPF occurs within 500 km from any field station using as input size distribution and meteorological trajectories only. Also, the horizontal extension of NPF can be determined. An open-source program to run NanoMap is available on the internet. NanoMap has been developed using as an example the Finnish field site at Hyytiala. It shows that there are frequent NPF events over the Baltic Sea, but not as frequent as over Finland for certain wind directions; hence NanoMap is able to pinpoint areas with a low or high occurrence of NPF events. The method should be applicable to almost any field site.
  • SU, Peifeng; Joutsensaari, Jorma; Dada, Lubna; Zaidan, Martha Arbayani; Nieminen, Tuomo; Li, Xinyang; Wu, Yusheng; Decesari, Stefano; Tarkoma, Sasu; Petäjä, Tuukka; Kulmala, Markku; Pellikka, Petri (2022)
    Atmospheric new particle formation (NPF) is an important source of climate-relevant aerosol particles which has been observed at many locations globally. To study this phenomenon, the first step is to identify whether an NPF event occurs or not on a given day. In practice, NPF event identification is performed visually by classifying the NPF event or non-event days from the particle number size distribution surface plots. Unfortunately, this day-by-day visual classification is time-consuming and labor-intensive, and the identification process renders subjective results. To detect NPF events automatically, we regard the visual signature (banana shape) which has been observed all over the world in NPF surface plots as a special kind of object, and a deep learning model called Mask R-CNN is applied to localize the spatial layouts of NPF events in their surface plots. Utilizing only 358 human-annotated masks on data from the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II station (Hyytiala, Finland), the Mask R-CNN model was successfully generalized for three SMEAR stations in Finland and the San Pietro Capofiume (SPC) station in Italy. In addition to the detection of NPF events (especially the strongest events), the presented method can determine the growth rates, start times, and end times for NPF events automatically. The automatically determined growth rates agree with the manually determined growth rates. The statistical results validate the potential of applying the proposed method to different sites, which will improve the automatic level for NPF event detection and analysis. Furthermore, the proposed automatic NPF event analysis method can minimize subjectivity compared with human-made analysis, especially when long-term data series are analyzed and statistical comparisons between different sites are needed for event characteristics such as the start and end times, thereby saving time and effort for scientists studying NPF events.
  • Chu, Biwu; Dada, Lubna; Liu, Yongchun; Yao, Lei; Wang, Yonghong; Du, Wei; Cai, Jing; Dällenbach, K.R.; Chen, Xuemeng; Simonen, Pauli; Zhou, Ying; Deng, Chenjuan; Fu, Yueyun; Yin, Rujing; Li, Haiyan; He, Xucheng; Feng, Zeming; Yan, Chao; Kangasluoma, Juha; Bianchi, Federico; Jiang, Jingkun; Kujansuu, Joni; Kerminen, Veli-Matti; Petäjä, Tuukka; He, Hong; Kulmala, Markku (2021)
    Secondary aerosol formation in the aging process of primary emission is the main reason for haze pollution in eastern China. Pollution evolution with photochemical age was studied for the first time at a comprehensive field observation station during winter in Beijing. The photochemical age was used as an estimate of the time scale attributed to the aging process and was estimated from the ratio of toluene to benzene in this study. A low photochemical age indicates a fresh emission. The photochemical age of air masses during new particle formation (NPF) days was lower than that on haze days. In general, the strongest NPF events, along with a peak of the formation rate of 1.5 nm(J(1.5)) and 3 nmparticles (J(3)), were observed when the photochemical age was between 12 and 24 h while rarely took place with photochemical ages less than 12 h. When photochemical age was larger than 48 h, haze occurred and NPF was suppressed. The sources and sinks of nanoparticles had distinct relation with the photochemical age. Our results show that the condensation sink (CS) showed a valley with photochemical ages ranging from 12 to 24 h, while H2SO4 concentration showed no obvious trend with the photochemical age. The high concentrations of precursor vapours within an air mass lead to persistent nucleation with photochemical age ranging from 12 to 48 h in winter. Coincidently, the fast increase of PM2.5 mass was also observed during this range of photochemical age. Noteworthy, CS increased with the photochemical age on NPF days only, which is the likely reason for the observation that the PM2.5 mass increased faster with photochemical age on NPF days compared with other days. The evolution of particles with the photochemical age provides new insights into understanding how particles originating from NPF transform to haze pollution. (C) 2020 Elsevier B.V. All rights reserved.
  • Dada, Lubna; Chellapermal, Robert; Mazon, Stephany Buenrostro; Paasonen, Pauli; Lampilahti, Janne; Manninen, Hanna E.; Junninen, Heikki; Petäjä, Tuukka; Kerminen, Veli-Matti; Kulmala, Markku (2018)
    Atmospheric new-particle formation (NPF) is a worldwide-observed phenomenon that affects the human health and the global climate. With a growing network of global atmospheric measurement stations, efforts towards investigating NPF have increased. In this study, we present an automated method to classify days into four categories including NPF events, non-events and two classes in between, which then ensures reproducibility and minimizes the hours spent on manual classification. We applied our automated method to 10 years of data collected at the SMEAR II measurement station in Hyytiala, southern Finland using a Neutral cluster and Air Ion Spectrometer (NAIS). In contrast to the traditionally applied classification methods, which categorize days into events and non-events and ambiguous days as undefined days, our method is able to classify the undefined days as it accesses the initial steps of NPF at sub-3 nm sizes. Our results show that, on similar to 24% of the days in Hyytiala, a regional NPF event occurred and was characterized by nice weather and favourable conditions such as a clear sky and low condensation sink. Another class found in Hyytiala is the transported event class, which seems to be NPF carried horizontally or vertically to our measurement location and it occurred on 17% of the total studied days. Additionally, we found that an ion burst, wherein the ions apparently fail to grow to larger sizes, occurred on 18% of the days in Hyytiala. The transported events and ion bursts were characterized by less favourable ambient conditions than regional NPF events and thus experienced interrupted particle formation or growth. Non-events occurred on 41% of the days and were characterized by complete cloud cover and high relative humidity. Moreover, for regional NPF events occurring at the measurement site, the method identifies the start time, peak time and end time, which helps us focus on variables within an exact time window to better understand NPF at a process level. Our automated method can be modified to work in other measurement locations where NPF is observed.
  • Baranizadeh, Elham; Arola, Antti; Hamed, Amar; Nieminen, Tuomo; Mikkonen, Santtu; Virtanen, Annele; Kulmala, Markku; Lehtinen, Kari; Laaksonen, Ari (2014)
  • Leino, Katri; Lampilahti, Janne; Poutanen, Pyry; Väänänen, Riikka; Manninen, Antti; Mazon, Stephany Buenrostro; Dada, Lubna; Franck, Anna; Wimmer, Daniela; Aalto, Pasi P.; Ahonen, Lauri R.; Enroth, Joonas; Kangasluoma, Juha; Keronen, Petri; Korhonen, Frans; Laakso, Heikki; Matilainen, Teemu; Siivola, Erkki; Manninen, Hanna E.; Lehtipalo, Katrianne; Kerminen, Veli-Matti; Petäjä, Tuukka; Kulmala, Markku (2019)
    This work presents airborne observations of sub-3 nm particles in the lower troposphere and investigates new particle formation (NPF) within an evolving boundary layer (BL). We studied particle concentrations together with supporting gas and meteorological data inside the planetary BL over a boreal forest site in Hyytiala, southern Finland. The analysed data were collected during three flight measurement campaigns: May-June 2015, August 2015 and April-May 2017, including 27 morning and 26 afternoon vertical profiles. As a platform for the instrumentation, we used a Cessna 172 aircraft. The analysed flight data were collected horizontally within a 30 km distance from SMEAR II in Hyytiala and vertically from 100 m above ground level up to 2700 m. The number concentration of 1.5-3 nm particles was observed to be, on average, the highest near the forest canopy top and to decrease with increasing altitude during the mornings of NPF event days. This indicates that the precursor vapours emitted by the forest play a key role in NPF in Hyytiala. During daytime, newly formed particles were observed to grow in size and the particle population became more homogenous within the well-mixed BL in the afternoon. During undefined days with respect to NPF, we also detected an increase in concentration of 1.5-3 nm particles in the morning but not their growth in size, which indicates an interrupted NPF process during these undefined days. Vertical mixing was typically stronger during the NPF event days than during the undefined or non-event days. The results shed light on the connection between boundary layer dynamics and NPF.