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Showing papers by "Tuukka Petäjä published in 2022"


Journal ArticleDOI
Matthew D. Shupe, Markus Rex, Byron Blomquist, P. Ola G. Persson, Julia Schmale, Taneil Uttal, Dietrich Althausen, Hélène Angot, Stephen D. Archer, Ludovic Bariteau, Ivo Beck, John Bilberry, Silvia Bucci, Clifton S. Buck, Matthew Boyer, Zoé Brasseur, Ian M. Brooks, Radiance Calmer, John J. Cassano, Vagner Castro, David Chu, D. Costa, Christopher J. Cox, Jessie M. Creamean, Susanne Crewell, Sandro Dahlke, Ellen Damm, Gijs de Boer, H. Deckelmann, Klaus Dethloff, Marina Dütsch, Kerstin Ebell, André Ehrlich, Jody Ellis, Ronny Engelmann, Allison A. Fong, Markus M. Frey, Michael Gallagher, Laurens Ganzeveld, Rolf Gradinger, Jürgen Graeser, Vernon Greenamyer, Hannes Griesche, Steele Griffiths, Jonathan D. Hamilton, Günther Heinemann, Detlev Helmig, Andreas Herber, Céline Heuzé, Julian Hofer, Todd Houchens, Dean Howard, Jun Inoue, Hans-Werner Jacobi, Ralf Jaiser, Tuija Jokinen, Olivier Jourdan, Gina Jozef, Wessley King, Amélie Kirchgaessner, Marcus Klingebiel, Misha Krassovski, Thomas Krumpen, Astrid Lampert, William M. Landing, Tiia Laurila, D. Lawrence, Michael Lonardi, Brice Loose, Christof Lüpkes, Maximilian Maahn, Andreas Macke, Wieslaw Maslowski, Chris M. Marsay, Marion Maturilli, Mario Mech, Sara M. Morris, Manuel Moser, Marcel Nicolaus, Paul Ortega, J. Osborn, Falk Pätzold, Donald K. Perovich, Tuukka Petäjä, Christian Pilz, Roberta Pirazzini, Kevin Posman, Heath Powers, Kerri A. Pratt, Andrea Preusser, Lauriane L. J. Quéléver, Martin Radenz, Benjamin Rabe, Annette Rinke, Torsten Sachs, A. Schulz, Holger Siebert, Tércio Pessoa Tabosa e Silva, Amy Solomon, Anja Sommerfeld, Gunnar Spreen, Mark P. Stephens, Andreas Stohl, Gunilla Svensson, Janek Uin, Juarez Viegas, Christiane Voigt, Peter von der Gathen, Birgit Wehner, Jeffrey M. Welker, Manfred Wendisch, Martin Werner, Zhouqing Xie, Fan Ming yue 
01 Jan 2022-Elementa
TL;DR: The MOSAiC program as mentioned in this paper was organized into four subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets, using a variety of approaches, and across multiple scales.
Abstract: With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

111 citations


Journal ArticleDOI
TL;DR: In this paper , the authors present coordinated measurements of oxygenated organic molecules in the three most urbanized regions of China and determine their likely precursors, enabling them to connect secondary organic aerosol formation to various volatile organic compounds.
Abstract: Secondary organic aerosol contributes a significant fraction to aerosol mass and toxicity. Low-volatility organic vapours are critical intermediates connecting the oxidation of volatile organic compounds to secondary organic aerosol formation. However, the direct measurement of intermediate vapours poses a great challenge. Here we present coordinated measurements of oxygenated organic molecules in the three most urbanized regions of China and determine their likely precursors, enabling us to connect secondary organic aerosol formation to various volatile organic compounds. We show that the oxidation of anthropogenic volatile organic compounds dominates oxygenated organic molecule formation, with an approximately 40% contribution from aromatics and a 40% contribution from aliphatic hydrocarbons (predominantly alkanes), a previously under-accounted class of volatile organic compounds. The irreversible condensation of these anthropogenic oxygenated organic molecules increases significantly in highly polluted conditions, accounting for a major fraction of the production of secondary organic aerosol. We find that the distribution of oxygenated organic molecules and their formation pathways are largely the same across the urbanized regions. This suggests that uniform mitigation strategies could be effective in solving air pollution issues across these highly populated city clusters. The formation of secondary organic aerosol in Chinese megacities is dominated by the condensation of anthropogenic organic vapours, according to measurements across three urbanized regions.

46 citations


Journal ArticleDOI
TL;DR: In this article , the authors used data from eight observatories that represent the entire Arctic to reveal the annual cycles in anthropogenic and biogenic sources of organic aerosol, mainly from Eurasia, which consist of both direct combustion emissions and long-range transported, aged pollution.
Abstract: Aerosols play an important yet uncertain role in modulating the radiation balance of the sensitive Arctic atmosphere. Organic aerosol is one of the most abundant, yet least understood, fractions of the Arctic aerosol mass. Here we use data from eight observatories that represent the entire Arctic to reveal the annual cycles in anthropogenic and biogenic sources of organic aerosol. We show that during winter, the organic aerosol in the Arctic is dominated by anthropogenic emissions, mainly from Eurasia, which consist of both direct combustion emissions and long-range transported, aged pollution. In summer, the decreasing anthropogenic pollution is replaced by natural emissions. These include marine secondary, biogenic secondary and primary biological emissions, which have the potential to be important to Arctic climate by modifying the cloud condensation nuclei properties and acting as ice-nucleating particles. Their source strength or atmospheric processing is sensitive to nutrient availability, solar radiation, temperature and snow cover. Our results provide a comprehensive understanding of the current pan-Arctic organic aerosol, which can be used to support modelling efforts that aim to quantify the climate impacts of emissions in this sensitive region.

28 citations


Journal ArticleDOI
TL;DR: In this paper , it was shown that ammonium and ammonium nitrate can be efficiently convected aloft during the Asian monsoon, driving rapid, multi-acid HNO3-H2SO4-NH3 nucleation in the upper troposphere and producing ice nucleating particles that spread across the mid-latitude Northern Hemisphere.
Abstract: New particle formation in the upper free troposphere is a major global source of cloud condensation nuclei (CCN)1-4. However, the precursor vapours that drive the process are not well understood. With experiments performed under upper tropospheric conditions in the CERN CLOUD chamber, we show that nitric acid, sulfuric acid and ammonia form particles synergistically, at rates that are orders of magnitude faster than those from any two of the three components. The importance of this mechanism depends on the availability of ammonia, which was previously thought to be efficiently scavenged by cloud droplets during convection. However, surprisingly high concentrations of ammonia and ammonium nitrate have recently been observed in the upper troposphere over the Asian monsoon region5,6. Once particles have formed, co-condensation of ammonia and abundant nitric acid alone is sufficient to drive rapid growth to CCN sizes with only trace sulfate. Moreover, our measurements show that these CCN are also highly efficient ice nucleating particles-comparable to desert dust. Our model simulations confirm that ammonia is efficiently convected aloft during the Asian monsoon, driving rapid, multi-acid HNO3-H2SO4-NH3 nucleation in the upper troposphere and producing ice nucleating particles that spread across the mid-latitude Northern Hemisphere.

16 citations


Journal ArticleDOI
TL;DR: In this article , a year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia.
Abstract: Frequency and intensity of warm and moist air-mass intrusions into the Arctic have increased over the past decades and have been related to sea ice melt. During our year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia. The two-day intrusion, caused drastic changes in the aerosol size distribution, chemical composition and particle hygroscopicity. Here we show how the intrusion transformed the Arctic from a remote low-particle environment to an area comparable to a central-European urban setting. Additionally, the intrusion resulted in an explosive increase in cloud condensation nuclei, which can have direct effects on Arctic clouds' radiation, their precipitation patterns, and their lifetime. Thus, unless prompt actions to significantly reduce emissions in the source regions are taken, such intrusion events are expected to continue to affect the Arctic climate.

16 citations


Journal ArticleDOI
TL;DR: In this paper , the size-resolved molecular composition of nanoparticles using the thermal desorption chemical ionization mass spectrometer and the gas precursors using the nitrate CI-APi-ToF was analyzed.
Abstract: Atmospheric new particle formation significantly affects global climate and air quality after newly formed particles grow above ∼50 nm. In polluted urban atmospheres with 1-3 orders of magnitude higher new particle formation rates than those in clean atmospheres, particle growth rates are comparable or even lower for reasons that were previously unclear. Here, we address the slow growth in urban Beijing with advanced measurements of the size-resolved molecular composition of nanoparticles using the thermal desorption chemical ionization mass spectrometer and the gas precursors using the nitrate CI-APi-ToF. A particle growth model combining condensational growth and particle-phase acid-base chemistry was developed to explore the growth mechanisms. The composition of 8-40 nm particles during new particle formation events in urban Beijing is dominated by organics (∼80%) and sulfate (∼13%), and the remainder is from base compounds, nitrate, and chloride. With the increase in particle sizes, the fraction of sulfate decreases, while that of the slow-desorbed organics, organic acids, and nitrate increases. The simulated size-resolved composition and growth rates are consistent with the measured results in most cases, and they both indicate that the condensational growth of organic vapors and H2SO4 is the major growth pathway and the particle-phase acid-base reactions play a minor role. In comparison to the high concentrations of gaseous sulfuric acid and amines that cause high formation rates, the concentration of condensable organic vapors is comparably lower under the high NOx levels, while those of the relatively high-volatility nitrogen-containing oxidation products are higher. The insufficient condensable organic vapors lead to slow growth, which further causes low survival of the newly formed particles in urban environments. Thus, the low growth rates, to some extent, counteract the impact of the high formation rates on air quality and global climate in urban environments.

14 citations


Journal ArticleDOI
TL;DR: In this article , strong evidence for the existence of base molecules such as amines in the smallest atmospheric sulfuric acid clusters prior to their detection by mass spectrometers was presented.
Abstract: Abstract Transformation of low-volatility gaseous precursors to new particles affects aerosol number concentration, cloud formation and hence the climate. The clustering of acid and base molecules is a major mechanism driving fast nucleation and initial growth of new particles in the atmosphere. However, the acid–base cluster composition, measured using state-of-the-art mass spectrometers, cannot explain the measured high formation rate of new particles. Here we present strong evidence for the existence of base molecules such as amines in the smallest atmospheric sulfuric acid clusters prior to their detection by mass spectrometers. We demonstrate that forming (H2SO4)1(amine)1 is the rate-limiting step in atmospheric H2SO4-amine nucleation and the uptake of (H2SO4)1(amine)1 is a major pathway for the initial growth of H2SO4 clusters. The proposed mechanism is very consistent with measured new particle formation in urban Beijing, in which dimethylamine is the key base for H2SO4 nucleation while other bases such as ammonia may contribute to the growth of larger clusters. Our findings further underline the fact that strong amines, even at low concentrations and when undetected in the smallest clusters, can be crucial to particle formation in the planetary boundary layer.

13 citations


Journal ArticleDOI
22 Mar 2022
TL;DR: In this paper , the authors investigated the contribution of atmospheric new particle formation (NPF) and subsequent growth of the newly formed particles, characterized by high concentrations of fine particulate matter (PM2.5).
Abstract: We investigated the contribution of atmospheric new particle formation (NPF) and subsequent growth of the newly formed particles, characterized by high concentrations of fine particulate matter (PM2.5). In addition to having adverse effects on visibility and human health, these haze particles may act as cloud condensation nuclei, having potentially large influences on clouds and precipitation. Using atmospheric observations performed in 2019 in Beijing, a polluted megacity in China, we showed that the variability of growth rates (GR) of particles originating from NPF depend only weakly on low-volatile vapor – highly oxidated organic molecules (HOMs) and sulphuric acid – concentrations and have no apparent connection with the strength of NPF or the level of background pollution. We then constrained aerosol dynamic model simulations with these observations. We showed that under conditions typical for the Beijing atmosphere, NPF is capable of contributing with more than 100 μg m−3 to the PM2.5 mass concentration and simultaneously >103 cm−3 to the haze particle (diameter > 100 nm) number concentration. Our simulations reveal that the PM2.5 mass concentration originating from NPF, strength of NPF, particle growth rate and pre-existing background particle population are all connected with each other. Concerning the PM pollution control, our results indicate that reducing primary particle emissions might not result in an effective enough decrease in total PM2.5 mass concentrations until a reduction in emissions of precursor compounds for NPF and subsequent particle growth is imposed.

12 citations


Journal ArticleDOI
01 Feb 2022-Arctic
TL;DR: In this paper , a roadmap for Arctic observing and data systems (ROADS) is proposed to address the current lack of a systematic planning mechanism to develop and link observing requirements and implementation strategies in the Arctic region.
Abstract: Arctic observing and data systems have been widely recognized as critical infrastructures to support decision making and understanding across sectors in the Arctic and globally. Yet due to broad and persistent issues related to coordination, deployment infrastructure and technology gaps, the Arctic remains among the most poorly observed regions on the planet from the standpoint of conventional observing systems. Sustaining Arctic Observing Networks (SAON) was initiated in 2011 to address the persistent shortcomings in the coordination of Arctic observations that are maintained by its many national and organizational partners. SAON set forth a bold vision in its 2018 – 28 strategic plan to develop a roadmap for Arctic observing and data systems (ROADS) to specifically address a key gap in coordination efforts—the current lack of a systematic planning mechanism to develop and link observing and data system requirements and implementation strategies in the Arctic region. This coordination gap has hampered partnership development and investments toward improved observing and data systems. ROADS seeks to address this shortcoming through generating a systems-level view of observing requirements and implementation strategies across SAON’s many partners through its roadmap. A critical success factor for ROADS is equitable participation of Arctic Indigenous Peoples in the design and development process, starting at the process design stage to build needed equity. ROADS is both a comprehensive concept, building from a societal benefit assessment approach, and one that can proceed step-wise so that the most imperative Arctic observations—here described as shared Arctic variables (SAVs)—can be rapidly improved. SAVs will be identified through rigorous assessment at the beginning of the ROADS process, with an emphasis in that assessment on increasing shared benefit of proposed system improvements across a range of partnerships from local to global scales. The success of the ROADS process will ultimately be measured by the realization of concrete investments in and well-structured partnerships for the improved sustainment of Arctic observing and data systems in support of societal benefit.

11 citations


Journal ArticleDOI
TL;DR: In this paper , the authors present a dataset on the overall chemical composition and seasonal variability of the Arctic total particulate matter (with a size cut at 10 μm, PM10, or without any size cut) at eight observatories representing all Arctic sectors.
Abstract: The Arctic is warming two to three times faster than the global average, and the role of aerosols is not well constrained. Aerosol number concentrations can be very low in remote environments, rendering local cloud radiative properties highly sensitive to available aerosol. The composition and sources of the climate-relevant aerosols, affecting Arctic cloud formation and altering their microphysics, remain largely elusive due to a lack of harmonized concurrent multi-component, multi-site, and multi-season observations. Here, we present a dataset on the overall chemical composition and seasonal variability of the Arctic total particulate matter (with a size cut at 10 μm, PM10, or without any size cut) at eight observatories representing all Arctic sectors. Our holistic observational approach includes the Russian Arctic, a significant emission source area with less dedicated aerosol monitoring, and extends beyond the more traditionally studied summer period and black carbon/sulfate or fine-mode pollutants. The major airborne Arctic PM components in terms of dry mass are sea salt, secondary (non-sea-salt, nss) sulfate, and organic aerosol (OA), with minor contributions from elemental carbon (EC) and ammonium. We observe substantial spatiotemporal variability in component ratios, such as EC/OA, ammonium/nss-sulfate and OA/nss-sulfate, and fractional contributions to PM. When combined with component-specific back-trajectory analysis to identify marine or terrestrial origins, as well as the companion study by Moschos et al 2022 Nat. Geosci. focusing on OA, the composition analysis provides policy-guiding observational insights into sector-based differences in natural and anthropogenic Arctic aerosol sources. In this regard, we first reveal major source regions of inner-Arctic sea salt, biogenic sulfate, and natural organics, and highlight an underappreciated wintertime source of primary carbonaceous aerosols (EC and OA) in West Siberia, potentially associated with the oil and gas sector. The presented dataset can assist in reducing uncertainties in modelling pan-Arctic aerosol-climate interactions, as the major contributors to yearly aerosol mass can be constrained. These models can then be used to predict the future evolution of individual inner-Arctic atmospheric PM components in light of current and emerging pollution mitigation measures and improved region-specific emission inventories.

11 citations


Journal ArticleDOI
TL;DR: In this paper , a deep learning model called Mask R-CNN is applied to localize the spatial layouts of new particle formation (NPF) events in their surface plots, which can determine the growth rates, start times, and end times for NPF events automatically.
Abstract: Abstract. 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 (Hyytiälä, 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.

Journal ArticleDOI
TL;DR: In this article , a year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia.
Abstract: Frequency and intensity of warm and moist air-mass intrusions into the Arctic have increased over the past decades and have been related to sea ice melt. During our year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia. The two-day intrusion, caused drastic changes in the aerosol size distribution, chemical composition and particle hygroscopicity. Here we show how the intrusion transformed the Arctic from a remote low-particle environment to an area comparable to a central-European urban setting. Additionally, the intrusion resulted in an explosive increase in cloud condensation nuclei, which can have direct effects on Arctic clouds' radiation, their precipitation patterns, and their lifetime. Thus, unless prompt actions to significantly reduce emissions in the source regions are taken, such intrusion events are expected to continue to affect the Arctic climate.

Journal ArticleDOI
TL;DR: Beck et al. as mentioned in this paper presented a method to identify primary pollution in remote atmospheric datasets, e.g., from ship campaigns or stations with a low background signal compared to the contaminated signal.
Abstract: Abstract. Atmospheric observations in remote locations offer a possibility of exploring trace gas and particle concentrations in pristine environments. However, data from remote areas are often contaminated by pollution from local sources. Detecting this contamination is thus a central and frequently encountered issue. Consequently, many different methods exist today to identify local contamination in atmospheric composition measurement time series, but no single method has been widely accepted. In this study, we present a new method to identify primary pollution in remote atmospheric datasets, e.g., from ship campaigns or stations with a low background signal compared to the contaminated signal. The pollution detection algorithm (PDA) identifies and flags periods of polluted data in five steps. The first and most important step identifies polluted periods based on the derivative (time derivative) of a concentration over time. If this derivative exceeds a given threshold, data are flagged as polluted. Further pollution identification steps are a simple concentration threshold filter, a neighboring points filter (optional), a median, and a sparse data filter (optional). The PDA only relies on the target dataset itself and is independent of ancillary datasets such as meteorological variables. All parameters of each step are adjustable so that the PDA can be “tuned” to be more or less stringent (e.g., flag more or fewer data points as contaminated). The PDA was developed and tested with a particle number concentration dataset collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic. Using strict settings, we identified 62 % of the data as influenced by local contamination. Using a second independent particle number concentration dataset also collected during MOSAiC, we evaluated the performance of the PDA against the same dataset cleaned by visual inspection. The two methods agreed in 94 % of the cases. Additionally, the PDA was successfully applied to a trace gas dataset (CO2), also collected during MOSAiC, and to another particle number concentration dataset, collected at the high-altitude background station Jungfraujoch, Switzerland. Thus, the PDA proves to be a useful and flexible tool to identify periods affected by local contamination in atmospheric composition datasets without the need for ancillary measurements. It is best applied to data representing primary pollution. The user-friendly and open-access code enables reproducible application to a wide suite of different datasets. It is available at https://doi.org/10.5281/zenodo.5761101 (Beck et al., 2021).

Posted ContentDOI
TL;DR: In this article , the response of atmospheric new particle formation to changes in the atmospheric chemical cocktail was examined and the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered.
Abstract: Abstract. During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5–3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3–7 nm and 7–15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.

Journal ArticleDOI
25 Mar 2022-Tellus B
TL;DR: In this paper , the authors present how the boreal and the tropical forests affect the atmosphere, its chemical composition, its function, and further how that affects the climate and, in return, the ecosystems through feedback processes.
Abstract: This review presents how the boreal and the tropical forests affect the atmosphere, its chemical composition, its function, and further how that affects the climate and, in return, the ecosystems through feedback processes. Observations from key tower sites standing out due to their long-term comprehensive observations: The Amazon Tall Tower Observatory in Central Amazonia, the Zotino Tall Tower Observatory in Siberia, and the Station to Measure Ecosystem-Atmosphere Relations at Hyytiäla in Finland. The review is complemented by short-term observations from networks and large experiments. The review discusses atmospheric chemistry observations, aerosol formation and processing, physiochemical aerosol, and cloud condensation nuclei properties and finds surprising similarities and important differences in the two ecosystems. The aerosol concentrations and chemistry are similar, particularly concerning the main chemical components, both dominated by an organic fraction, while the boreal ecosystem has generally higher concentrations of inorganics, due to higher influence of long-range transported air pollution. The emissions of biogenic volatile organic compounds are dominated by isoprene and monoterpene in the tropical and boreal regions, respectively, being the main precursors of the organic aerosol fraction. Observations and modeling studies show that climate change and deforestation affect the ecosystems such that the carbon and hydrological cycles in Amazonia are changing to carbon neutrality and affect precipitation downwind. In Africa, the tropical forests are so far maintaining their carbon sink. It is urgent to better understand the interaction between these major ecosystems, the atmosphere, and climate, which calls for more observation sites, providing long-term data on water, carbon, and other biogeochemical cycles. This is essential in finding a sustainable balance between forest preservation and reforestation versus a potential increase in food production and biofuels, which are critical in maintaining ecosystem services and global climate stability. Reducing global warming and deforestation is vital for tropical forests.

Journal ArticleDOI
TL;DR: The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed the need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region as mentioned in this paper .
Abstract: Abstract. The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.

Journal ArticleDOI
TL;DR: In this article , the authors used measurement data from several locations (Hyytiälä, Järvselja, and near-city background and city center of Budapest) and found that during such days, particle formation rates at 6 nm were about 2-20% of those observed during the traditional NPF event days.
Abstract: Atmospheric new particle formation (NPF) has been observed to take place in practice all around the world. In continental locations, typically about 10–40% of the days are so-called NPF event days characterized by a clear particle formation and growth that continue for several hours, occurring mostly during daytime. The other days are either non-event days, or days for which it is difficult to decide whether NPF had occurred or not. Using measurement data from several locations (Hyytiälä, Järvselja, and near-city background and city center of Budapest), we were able to show that NPF tends to occur also on the days traditionally characterized as non-event days. One explanation is the instrument sensitivity towards low number concentrations in the sub-10 nm range, which usually limits our capability to detect such NPF events. We found that during such days, particle formation rates at 6 nm were about 2–20% of those observed during the traditional NPF event days. Growth rates of the newly formed particles were very similar between the traditional NPF event and non-event days. This previously overlooked phenomenon, termed as quiet NPF, contributes significantly to the production of secondary particles in the atmosphere.


Journal ArticleDOI
TL;DR: In this paper , the authors investigate Hg isotope variability of Arctic atmospheric, marine, and terrestrial Hg and observe highly characteristic Hg- isotope signatures during the summertime peak that reflect re-emission of Hg deposited to the cryosphere during spring.
Abstract: Abstract During Arctic springtime, halogen radicals oxidize atmospheric elemental mercury (Hg 0 ), which deposits to the cryosphere. This is followed by a summertime atmospheric Hg 0 peak that is thought to result mostly from terrestrial Hg inputs to the Arctic Ocean, followed by photoreduction and emission to air. The large terrestrial Hg contribution to the Arctic Ocean and global atmosphere has raised concern over the potential release of permafrost Hg, via rivers and coastal erosion, with Arctic warming. Here we investigate Hg isotope variability of Arctic atmospheric, marine, and terrestrial Hg. We observe highly characteristic Hg isotope signatures during the summertime peak that reflect re-emission of Hg deposited to the cryosphere during spring. Air mass back trajectories support a cryospheric Hg emission source but no major terrestrial source. This implies that terrestrial Hg inputs to the Arctic Ocean remain in the marine ecosystem, without substantial loss to the global atmosphere, but with possible effects on food webs.

Journal ArticleDOI
TL;DR: In this article , an overview of the trace gas measurements conducted during MOSAiC and highlights the high quality of the monitoring activities is provided and in the case of redundant measurements, merged datasets are provided and recommended for further use by the scientific community.
Abstract: Despite the key role of the Arctic in the global Earth system, year-round in-situ atmospheric composition observations within the Arctic are sparse and mostly rely on measurements at ground-based coastal stations. Measurements of a suite of in-situ trace gases were performed in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These observations give a comprehensive picture of year-round near-surface atmospheric abundances of key greenhouse and trace gases, i.e., carbon dioxide, methane, nitrous oxide, ozone, carbon monoxide, dimethylsulfide, sulfur dioxide, elemental mercury, and selected volatile organic compounds (VOCs). Redundancy in certain measurements supported continuity and permitted cross-evaluation and validation of the data. This paper gives an overview of the trace gas measurements conducted during MOSAiC and highlights the high quality of the monitoring activities. In addition, in the case of redundant measurements, merged datasets are provided and recommended for further use by the scientific community.

Journal ArticleDOI
TL;DR: In this article , the authors suggest the current AQI should be revised in a way that new air pollution indicators would be considered so that it would better represent the health effects caused by local combustion processes from traffic and residential burning.

Journal ArticleDOI
TL;DR: In this article , the authors investigated the role of wetlands in aerosol formation and found that terpenes initiate stronger atmospheric new particle formation than is typically observed over boreal forests and that new wetlands produced by melting permafrost need to be taken into consideration as sources of secondary aerosol particles.
Abstract: Abstract Aerosols and their interaction with clouds constitute the largest uncertainty in estimating the radiative forcing affecting the climate system. Secondary aerosol formation is responsible for a large fraction of the cloud condensation nuclei in the global atmosphere. Wetlands are important to the budgets of methane and carbon dioxide, but the potential role of wetlands in aerosol formation has not been investigated. Here we use direct atmospheric sampling at the Siikaneva wetland in Finland to investigate the emission of methane and volatile organic compounds, and subsequently formed atmospheric clusters and aerosols. We find that terpenes initiate stronger atmospheric new particle formation than is typically observed over boreal forests and that, in addition to large emissions of methane which cause a warming effect, wetlands also have a cooling effect through emissions of these terpenes. We suggest that new wetlands produced by melting permafrost need to be taken into consideration as sources of secondary aerosol particles when estimating the role of increasing wetland extent in future climate change.

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TL;DR: In this article , a mixture of anthropogenic vapours, under condensation sinks typical of haze conditions, up to 0.1 s−1 was observed in the cloud chamber at CERN.
Abstract: Intense new particle formation events are regularly observed under highly polluted conditions, despite the high loss rates of nucleated clusters. Higher than expected cluster survival probability implies either ineffective scavenging by pre-existing particles or missing growth mechanisms. Here we present experiments performed in the CLOUD chamber at CERN showing particle formation from a mixture of anthropogenic vapours, under condensation sinks typical of haze conditions, up to 0.1 s−1. We find that new particle formation rates substantially decrease at higher concentrations of pre-existing particles, demonstrating experimentally for the first time that molecular clusters are efficiently scavenged by larger sized particles. Additionally, we demonstrate that in the presence of supersaturated gas-phase nitric acid (HNO3) and ammonia (NH3), freshly nucleated particles can grow extremely rapidly, maintaining a high particle number concentration, even in the presence of a high condensation sink. Such high growth rates may explain the high survival probability of freshly formed particles under haze conditions. We identify under what typical urban conditions HNO3 and NH3 can be expected to contribute to particle survival during haze.

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TL;DR: The binned positive matrix factorization method (binPMF) was applied to the measured spectra. as mentioned in this paper investigated the occurrence of new particle formation (NPF) events detected in a coastal agricultural site, at Qvidja, in Southwestern Finland, using the data measured with a nitrate ion-based chemical ionization atmospheric-pressure-interface time-of-flight (CI-APi-TOF) mass spectrometer.
Abstract: Abstract. The occurrence of new particle formation (NPF) events detected in a coastal agricultural site, at Qvidja, in Southwestern Finland, was investigated using the data measured with a nitrate ion-based chemical-ionization atmospheric-pressure-interface time-of-flight (CI-APi-TOF) mass spectrometer. The binned positive matrix factorization method (binPMF) was applied to the measured spectra. It resulted in eight factors describing the time series of ambient gas and cluster composition at Qvidja during spring 2019. The most interesting factors related to the observed NPF events were the two factors with the highest mass-to-charge ratios, numbered 7 and 8, both having profiles with patterns of highly oxygenated organic molecules with one nitrogen atom. It was observed that factor 7 had elevated intensities during the NPF events. A variable with an even better connection to the observed NPF events is fF7, which denotes the fraction of the total spectra within the studied mass-to-charge ratio range between 169 and 450 Th being in a form of factor 7. Values of fF7 higher than 0.50±0.05 were observed during the NPF events, of which durations also correlated with the duration of fF7 exceeding this critical value. It was also observed that factor 8 acts like a precursor for factor 7 with solar radiation and that the formation of factor 8 is associated with ozone levels.

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TL;DR: In this article , the authors show that decreasing the temperature from +25 to −10 °C enhances the gas-phase MSA production by an order of magnitude from OH-initiated DMS oxidation, while H2SO4 production is modestly affected.
Abstract: Dimethyl sulfide (DMS) influences climate via cloud condensation nuclei (CCN) formation resulting from its oxidation products (mainly methanesulfonic acid, MSA, and sulfuric acid, H2SO4). Despite their importance, accurate prediction of MSA and H2SO4 from DMS oxidation remains challenging. With comprehensive experiments carried out in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at CERN, we show that decreasing the temperature from +25 to −10 °C enhances the gas-phase MSA production by an order of magnitude from OH-initiated DMS oxidation, while H2SO4 production is modestly affected. This leads to a gas-phase H2SO4-to-MSA ratio (H2SO4/MSA) smaller than one at low temperatures, consistent with field observations in polar regions. With an updated DMS oxidation mechanism, we find that methanesulfinic acid, CH3S(O)OH, MSIA, forms large amounts of MSA. Overall, our results reveal that MSA yields are a factor of 2–10 higher than those predicted by the widely used Master Chemical Mechanism (MCMv3.3.1), and the NOx effect is less significant than that of temperature. Our updated mechanism explains the high MSA production rates observed in field observations, especially at low temperatures, thus, substantiating the greater importance of MSA in the natural sulfur cycle and natural CCN formation. Our mechanism will improve the interpretation of present-day and historical gas-phase H2SO4/MSA measurements.


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TL;DR: Zhang et al. as discussed by the authors found that ammonium nitrate-rich (NH4NO3-rich) fine particles acting as condensation sink are more effective in removing gaseous H2SO4 (effectiveness of the CS) driving NPF.
Abstract: Relatively high concentrations of preexisting particles, acting as a condensation sink (CS) of gaseous precursors, have been thought to suppress the occurrence of new particle formation (NPF) in urban environments, yet NPF still occurs frequently. Here, we aim to understand the factors promoting and inhibiting NPF events in urban Beijing by combining one-year-long measurements of particle number size distributions and PM2.5 chemical composition. Our results show that indeed the CS is an important factor controlling the occurrence of NPF events, with its chemical composition affecting the efficiency of the background particles in removing gaseous H2SO4 (effectiveness of the CS) driving NPF. During our observation period, the CS was found to be more effective for ammonium nitrate-rich (NH4NO3-rich) fine particles. On non-NPF event days, particles acting as CS contained a larger fraction of NH4NO3 compared to NPF event days under comparable CS levels. In particular, in the CS range from 0.02 to 0.03 s–1, the nitrate fraction was 17% on NPF event days and 26% on non-NPF event days. Overall, our results highlight the importance of considering the chemical composition of preexisting particles when estimating the CS and their role in inhibiting NPF events, especially in urban environments.

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TL;DR: In this article , an eleven-month time series of the ambient concentration of organic carbon (OC) and elemental carbon (EC) between May 2018-March 2019 in Amman, Jordan was collected.
Abstract: The Mediterranean region is an important area for air pollution as it is the crossroads between three continents; therefore, the concentrations of atmospheric aerosol particles are influenced by emissions from Africa, Asia, and Europe. Here we concentrate on an eleven-month time series of the ambient concentration of organic carbon (OC) and elemental carbon (EC) between May 2018–March 2019 in Amman, Jordan. Such a dataset is unique in Jordan. The results show that the OC and EC annual mean concentrations in PM2.5 samples were 5.9 ± 2.8 µg m–3 and 1.7 ± 1.1 µg m–3, respectively. It was found that the majority of OC and EC concentrations were within the fine particle fraction (PM2.5). During sand and dust storm (SDS) episodes OC and EC concentrations were higher than the annual means; the mean values during these periods were about 9.6 ± 3.5 µg m–3 and 2.5 ± 1.2 µg m–3 in the PM2.5 samples. Based on this, the SDS episodes were identified to be responsible for an increased carbonaceous aerosol content as well as PM2.5 and PM10 content, which may have direct implications on human health. This study encourages us to perform more extensive measurements during a longer time period and to include an advanced chemical and physical characterization for urban aerosols in the urban atmosphere of Amman, which can be representative of other urban areas in the region.

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TL;DR: In this article , a machine learning approach is proposed to develop a BC proxy using air pollution datasets as an input, based on two machine learning models, support vector regression (SVR) and random forest (RF), using observations of particle mass and number concentrations (N), gaseous pollutants and meteorological variables as the input.
Abstract: Black carbon (BC) is a product of incomplete combustion, present in urban aerosols and sourcing mainly from road traffic. Epidemiological evidence reports positive associations between BC and cardiovascular and respiratory disease. Despite this, BC is currently not regulated by the EU Air Quality Directive, and as a result BC data are not available in urban areas from reference air quality monitoring networks in many countries. To fill this gap, a machine learning approach is proposed to develop a BC proxy using air pollution datasets as an input. The proposed BC proxy is based on two machine learning models, support vector regression (SVR) and random forest (RF), using observations of particle mass and number concentrations (N), gaseous pollutants and meteorological variables as the input. Experimental data were collected from a reference station in Barcelona (Spain) over a 2-year period (2018–2019). Two months of additional data were available from a second urban site in Barcelona, for model validation. BC concentrations estimated by SVR showed a high degree of correlation with the measured BC concentrations (R2 = 0.828) with a relatively low error (RMSE = 0.48 μg/m3). Model performance was dependent on seasonality and time of the day, due to the influence of new particle formation events. When validated at the second station, performance indicators decreased (R2 = 0.633; RMSE = 1.19 μg/m3) due to the lack of N data and PM2.5 and the smaller size of the dataset (2 months). New particle formation events critically impacted model performance, suggesting that its application would be optimal in environments where traffic is the main source of ultrafine particles. Due to its flexibility, it is concluded that the model can act as a BC proxy, even based on EU-regulatory air quality parameters only, to complement experimental measurements for exposure assessment in urban areas.

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TL;DR: In this article , it was shown that Iodine is a reactive trace element in atmospheric chemistry that destroys ozone and nucleates particles, but its gas-phase formation mechanism remains unresolved.
Abstract: Abstract Iodine is a reactive trace element in atmospheric chemistry that destroys ozone and nucleates particles. Iodine emissions have tripled since 1950 and are projected to keep increasing with rising O 3 surface concentrations. Although iodic acid (HIO 3 ) is widespread and forms particles more efficiently than sulfuric acid, its gas-phase formation mechanism remains unresolved. Here, in CLOUD atmospheric simulation chamber experiments that generate iodine radicals at atmospherically relevant rates, we show that iodooxy hypoiodite, IOIO, is efficiently converted into HIO 3 via reactions (R1) IOIO + O 3 → IOIO 4 and (R2) IOIO 4 + H 2 O → HIO 3 + HOI + (1) O 2 . The laboratory-derived reaction rate coefficients are corroborated by theory and shown to explain field observations of daytime HIO 3 in the remote lower free troposphere. The mechanism provides a missing link between iodine sources and particle formation. Because particulate iodate is readily reduced, recycling iodine back into the gas phase, our results suggest a catalytic role of iodine in aerosol formation.