Relating high ozone, ultrafine particles, and new particle formation episodes using cluster analysis

We studied the simultaneity of tropospheric ozone (O3) episodes, high ultrafine particle (UFP; diameter < 100 nm) concentrations, and the occurrence of new particle formation at a regional background station in the Western Mediterranean (northeast Spain), which is affected considerably by the transport of pollutants emitted in the Barcelona metropolitan area and nearby populated and industrial areas. Using cluster analysis, we categorized summer and spring days between 2014 and 2018 according to their daily cycles of O3 concentrations, and then studied the evolution of the particle number size distribution, meteorological variables, and black carbon and sulfur dioxide concentrations. The analysis revealed that, in spring and summer, the highest UFP concentrations coincided with the highest O3 episodes, but new particle formation was largely inhibited during these episodes, probably due to the high aerosol pollution load transported from the Barcelona metropolitan area to the station. In contrast, new particle formation episodes were concurrent with the lowest concentrations of O3 and UFPs, including the number of particles in the 9–25 nm size range. Measurements carried out in an intensive field study, using an air ion spectrometer and a particle size magnifier, support these results. In addition, measurements obtained onboard tethered balloons revealed that sea and land breezes transported regional pollutants vertically up to about 400 m above ground level. This coincided with episodes of vertical recirculation of air masses that lasted for several days, which resulted in high O3 and high UFP episodes, while new particle formation was inhibited.Peer reviewe

Long-term measurement of sub-3 nm particles and their precursor gases in the boreal forest

The knowledge of the dynamics of sub-3 nm particles in the atmosphere is crucial for our understanding of the first steps of atmospheric new particle formation. Therefore, accurate and stable long-term measurements of the smallest atmospheric particles are needed. In this study, we analyzed over 5 years of particle concentrations in size classes 1.1-1.7 and 1.7-2.5 nm obtained with the particle size magnifier (PSM) and 3 years of precursor vapor concentrations measured with the chemical ionization atmospheric pressure interface time-of-flight mass spectrometer (CI-APi-ToF) at the SMEAR II station in Hyytiala, Finland. The results show that there are significant seasonal differences in median concentrations of sub-3 nm particles, but the two size classes behave partly differently. The 1.1-1.7 nm particle concentrations are highest in summer, while the 1.7-2.5 nm particle concentrations are highest in springtime. The 1.7-2.5 nm particles exhibit a daytime maximum in all seasons, while the 1.1-1.7 nm particles have an additional evening maximum during spring and summer. Aerosol precursor vapors have notable diurnal and seasonal differences as well. Sulfuric acid and highly oxygenated organic molecule (HOM) monomer concentrations have clear daytime maxima, while HOM dimers have their maxima during the night. HOM concentrations for both monomers and dimers are the highest during summer and the lowest during winter following the biogenic activity in the surrounding forest. Sulfuric acid concentrations are the highest during spring and summer, with autumn and winter concentrations being 2 to 3 times lower. A correlation analysis between the sub-3 nm concentrations and aerosol precursor vapor concentrations indicates that both HOMs (particularly their dimers) and sulfuric acid play a significant role in new particle formation in the boreal forest. Our analysis also suggests that there might be seasonal differences in new particle formation pathways that need to be investigated further.Peer reviewe

Laboratory verification of a new high flow differential mobility particle sizer, and field measurements in Hyytiälä

Measurement of atmospheric sub-10 nm nanoparticle number concentrations has been of substantial interest recently, which, however, is subject to considerable uncertainty. We report a laboratory characterization of a high flow differential mobility particle sizer (HFDMPS), which is based on the Half-mini type differential mobility analyzer (DMA) and nano condensation nuclei counter (A11), and show the first results from atmospheric observations. The HFDMPS utilizes the state-of-the-art aerosol technology, and is optimized for sub-10 nm particle size distribution measurements by a moderate resolution DMA, optimized and characterized low-loss particle sampling line and minimal dilution in the detector. We present an exhaustive laboratory calibration to the HFDMPS and compare the measured size data to the Hyytiala long-term DMPS and Neutral cluster and ion spectrometer. The HFDMPS detects about two times higher 3-10 nm particle concentrations than the long-term DMPS, and the counting uncertainties are halved as compared to the long-term DMPS. The HFDMPS did not observe any sub-2.5 nm particles in Hyytiala, and the reason for that was shown to be the inability of diethylene glycol to condense on such small biogenic particles. Last, we discuss the general implications of our results to the sub-10 nm DMPS based measurements.Peer reviewe

The standard operating procedure for Airmodus Particle Size Magnifier and nano-Condensation Nucleus Counter

Measurements of aerosol particles and clusters smaller than 3 nm in diameter are performed by many groups in order to detect recently formed or emitted nanoparticles and for studying the formation and early growth processes of aerosol particles. The Airmodus nano-Condensation Nucleus Counter (nCNC), consisting of a Particle Size Magnifier (PSM) and a Condensation Particle Counter (CPC) is a versatile tool to detect aerosol particles and clusters as small as ca. 1 nm in mobility diameter. It offers several different operation modes: fixed mode to measure the total particle number concentration with a fixed, but adjustable lower cut-off size and stepping and scanning modes for retrieving size-resolved information of ca. 1–4 nm particles. The size analysis is based on changing the supersaturation of the working fluid (diethylene glycol) inside the instrument, which changes the lowest detectable size. Here we present a standard operating procedure (SOP) for setting up, calibrating and operating the instrument for atmospheric field measurements. We will also present recommendations for data monitoring and analysis, and discuss some of the uncertainties related to the measurements. This procedure is the first step in harmonizing the use of the PSM/nCNC for atmospheric field measurements of sub-3 nm clusters and particles.Measurements of aerosol particles and clusters smaller than 3 nm in diameter are performed by many groups in order to detect recently formed or emitted nanoparticles and for studying the formation and early growth processes of aerosol particles. The Airmodus nano-Condensation Nucleus Counter (nCNC), consisting of a Particle Size Magnifier (PSM) and a Condensation Particle Counter (CPC) is a versatile tool to detect aerosol particles and clusters as small as ca. 1 nm in mobility diameter. It offers several different operation modes: fixed mode to measure the total particle number concentration with a fixed, but adjustable lower cut-off size and stepping and scanning modes for retrieving size-resolved information of ca. 1–4 nm particles. The size analysis is based on changing the supersaturation of the working fluid (diethylene glycol) inside the instrument, which changes the lowest detectable size. Here we present a standard operating procedure (SOP) for setting up, calibrating and operating the instrument for atmospheric field measurements. We will also present recommendations for data monitoring and analysis, and discuss some of the uncertainties related to the measurements. This procedure is the first step in harmonizing the use of the PSM/nCNC for atmospheric field measurements of sub-3 nm clusters and particles.Peer reviewe

Automated identification of local contamination in remote atmospheric composition time series

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).Peer reviewe

Overview of the MOSAiC expedition-Atmosphere INTRODUCTION

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 crosscutting 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.Peer reviewe

A central arctic extreme aerosol event triggered by a warm air-mass intrusion

Warm and moist air-mass intrusions into the Arctic are more frequent than the past decades. Here, the authors show that warm air mass intrusions from northern Eurasia inject record amounts of aerosols into the central Arctic Ocean strongly impacting atmospheric chemistry and cloud properties. 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.Peer reviewe

Year-round trace gas measurements in the central Arctic during the MOSAiC expedition

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.Peer reviewe

Characteristics and sources of fluorescent aerosols in the central Arctic Ocean

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, &amp;gt;−9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.</jats:p