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The Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISHTO) campaign took place in autumn 2021 at the NCSR Demokritos background high-altitude Helmos Hellenic Atmospheric Aerosol and Climate Change station (HAC) 2 to study the interactions between aerosols and clouds. The current study presents the chemical characterization of the non-refractory (NR) PM 1 aerosol fraction using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM). A comparative offline aerosol filter analysis by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) showed consistent results regarding the species determined. Source apportionment applied on both datasets (ACSM-ToF and offline AMS analysis on filter extracts) yielded the same factors for the organic aerosol (one primary and two secondary factors). Additionally, the positive matrix factorization (PMF) model was applied on the total PM 1 fraction by the ToF-ACSM (including both organic and inorganic ions). Five different types were identified, including a primary organic factor; ammonium nitrate; ammonium sulfate; and two secondary organic aerosols, one more oxidized and one less oxidized. The prevailing atmospheric conditions at the station, i.e., cloud presence, influence of emissions from the planetary boundary layer (PBL), and air mass origin, were also incorporated in the study. The segregation between PBL and free-troposphere (FT) conditions was made by combining data from remote sensing and in situ measurement techniques. The types of air masses arriving at the site were grouped as continental, marine, dust, and marine–dust based on back-trajectory data. Significant temporal variability in the aerosol characteristics was observed throughout the campaign; in September, air masses from within the PBL were sampled most of the time, resulting in much higher mass concentrations compared to October and November when concentrations were reduced by a factor of 5. Both in-cloud and FT measurement periods resulted in much lower concentration levels, while a similar composition was observed in PBL and FT conditions. We take advantage of using a recently developed "virtual-filtering" technique to separate interstitial from activated aerosol sampled from a PM 10 inlet during cloudy periods. This allows the determination of the chemical composition of the interstitial aerosol during in-cloud periods. Ammonium sulfate, the dominant PMF factor in all conditions, contributed more when air masses were arriving at (HAC) 2 during dust events, while a higher secondary organic aerosol contribution was observed when air masses arrived from continental Europe. [ABSTRACT FROM AUTHOR]

This paper addresses the challenges of calibrating low-cost electrochemical sensor systems for air quality monitoring. The proliferation of pollutants in the atmosphere necessitates efficient monitoring systems, and low-cost sensors offer a promising solution. However, issues such as drift, cross-sensitivity, and inter-unit consistency have raised concerns about their accuracy and reliability. The study explores the following three calibration methods for converting sensor signals to concentration measurements: utilizing manufacturer-provided equations, incorporating machine learning (ML) algorithms, and directly applying ML to voltage signals. Experiments were performed in three urban sites in Greece. High-end instrumentation provided the reference concentrations for training and evaluation of the model. The results reveal that utilizing voltage signals instead of the manufacturer's calibration equations diminishes variability among identical sensors. Moreover, the latter approach enhances calibration efficiency for CO, NO, NO2, and O3 sensors while incorporating voltage signals from all sensors in the ML algorithm, taking advantage of cross-sensitivity to improve calibration performance. The Random Forest ML algorithm is a promising solution for calibrating similar devices for use in urban areas. [ABSTRACT FROM AUTHOR]

Secondary organic aerosols (SOA) are a large source of uncertainty in our current understanding of climate change and air pollution. The phase state of SOA is important for quantifying their effects on climate and air quality, but its global distribution is poorly characterized. We developed a method to estimate glass transition temperatures based on the molar mass and molecular O:C ratio of SOA components, and we used the global chemistry climate model EMAC with the organic aerosol module ORACLE to predict the phase state of atmospheric SOA. For the planetary boundary layer, global simulations indicate that SOA are mostly liquid in tropical and polar air with high relative humidity, semi-solid in the mid-latitudes and solid over dry lands. We find that in the middle and upper troposphere SOA should be mostly in a glassy solid phase state. Thus, slow diffusion of water, oxidants and organic molecules could kinetically limit gas-particle interactions of SOA in the free and upper troposphere, promote ice nucleation and facilitate long-range transport of reactive and toxic organic pollutants embedded in SOA.

Measuring the mass concentration (PM0.1) of ultrafine particles (UFPs; diameter less than 100 nm) continuously, automatically, and accurately poses a considerable challenge because of the typically low PM0.1 concentration levels and susceptibility to interference from larger particles during the measurement processes. Previous work has shown that PM0.1 has a strong and stable correlation with the number concentration of particles with diameter above 50 nm (N50). This suggests that the indirect measurement of PM0.1 might be possible by measuring N50. In this work, the feasibility of using a Condensation Particle Counter (CPC) that measures PM0.1 by measuring N50 is examined. A water-based CPC was modified to measure N50 (CPC50). The CPC50's ability to measure PM0.1 was then evaluated by comparing its measurements with the PM0.1 measurements of a Scanning Mobility Particle Sizer (SMPS) in a suburban area. PM0.1 measured by the CPC50 was in good agreement with PM0.1 measured by the SMPS with a fractional bias (FBIAS) of 4% and a fractional error (FERROR) of 21% for hourly measurements. These findings indicate that a CPC50 could serve as a cheaper alternative to the SMPS, allowing for continuous and real-time measurement of PM0.1. Copyright © 2024 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

A dual chamber system was deployed in two different environments to study the potential of ambient air, that was directly injected into the chambers, to form secondary organic and inorganic aerosol. A total of 16 experiments took place during March 2022 in a polluted environment in the Po Valley, Italy which is dominated by anthropogenic emissions. Another experiments were conducted in the Pertouli forest, Greece which is dominated by biogenic emissions. In both campaigns, ambient air containing highly oxidized (average O:C 0.7-0.8) aerosol was the starting point of the experiments and its chemical evolution under the presence of OH radicals was followed. In the Po Valley SOA formation was observed in all experiments but one and the formed SOA ranged from 0.1 to 10 µg m-3. Experiments conducted under more polluted conditions (usually at night and early morning) had significantly higher SOA formation, with the concentration of the organic aerosol at the end being about four times higher than the initial. Also, production of 4-230 µg m-3 of ammonium nitrate was observed in all experiments due to the high levels of ammonia in this area. The produced SOA increased as the ambient relative humidity increased, but there was not a clear relationship between the SOA and temperature. Higher SOA production was observed when the PM1 levels in Po Valley were high. Contrary to the Po Valley, only one experiment in the Pertouli forest resulted in the formation of detectable SOA (about 1 µg m-3). This experiment was characterized by higher ambient concentrations of both monoterpenes and isoprene. In two experiments, some SOA was formed, but its concentration dropped below detection levels after 30 min. This behavior is consistent with local formation in a chamber that was not well mixed. Although both environments have OA with O:C in the range of 0.7-0.8, the atmosphere of the two sites had very different potentials of forming SOA. In the Po Valley, the system reacts rapidly forming large amounts of SOA, while in Pertouli the corresponding SOA formation chemistry appears to have been practically terminated before the beginning of most experiments, so there is little additional SOA formation potential left. [ABSTRACT FROM AUTHOR]

The purpose of this study is to understand the drivers of cloud droplet formation in orographic clouds. We used a combination of modeling, in-situ and remote sensing measurements at the high-altitude Helmos Hellenic Atmospheric Aerosol and Climate Change station ((HAC)2), which is located at the top of Mt. Helmos (1314 metres above sea level), Greece during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISTHO) campaign in Fall 2021 (https://calishto.panacea-ri.gr/) to examine the origins of the aerosols (i.e., local aerosol from the Planetary Boundary Layer (PBL), or long-range transported aerosol from the Free Tropospheric Layer (FTL) contributing to the Cloud Condensation Nuclei (CCN), their characteristics (hygroscopicity, size distribution and mixing state), as well as the vertical velocities distributions and resulting supersaturations. We found that the characteristics of the PBL aerosol were considerably different from FTL aerosol and use the aerosol particle number and equivalent mass concentration of the black carbon (eBC) in order to determine when the (HAC)2 was within the FTL or PBL based on timeseries of the height of the PBL. During the (HAC)2 cloud events we sample a mixture of interstitial aerosol and droplet residues, which we characterize using a new approach that utilizes the in-situ droplet measurements to determine time periods where the aerosol sample is purely interstitial. From the dataset we determine the properties (size distribution and hygroscopicity) of the pre-cloud, activated and interstitial aerosol. The hygroscopicity of activated aerosol is found to be higher than that of the interstitial or pre-cloud aerosol. A series of closure studies with the droplet parameterization shows that cloud droplet concentration (N d) and supersaturation can be predicted to within 25 % of observations when the aerosol size distributions correspond to pre-cloud conditions. Analysis of the characteristic supersaturation of each aerosol population indicates that droplet formation in clouds is aerosol-limited when formed in FTL airmasses – hence droplet formation is driven by aerosol variations, while clouds formed in the PBL tend to be velocity limited and droplet variations are driven by fluctuations in vertical velocity. Given that the cloud dynamics do not vary significantly between airmasses, the variation in aerosol concentration and type is mostly responsible for these shifts in cloud microphysical state and sensitivity to aerosol. With these insights, remote sensing of cloud droplets in such clouds can be used to infer either CCN spectra (when in the FTL) or vertical velocity (when in the PBL). In conclusion, we show that a coordinated measurement of aerosol and cloud properties, together with the novel analysis approaches presented here allow for the determination of the drivers of droplet formation in orographic clouds and their sensitivity to aerosol and vertical velocity variations. [ABSTRACT FROM AUTHOR]

This study explores the differences in performance and results by various versions of the ISORROPIA thermodynamic module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Three different versions of the module were used, ISORROPIA II v1, ISORROPIA II v2.3, and ISORROPIA-lite. First, ISORROPIA II v2.3 replaced ISORROPIA II v1 in EMAC to improve pH predictions close to neutral conditions. The newly developed ISORROPIA-lite has been added to EMAC alongside ISORROPIA II v2.3. ISORROPIA-lite is more computationally efficient and assumes that atmospheric aerosols exist always as supersaturated aqueous (metastable) solutions, while ISORROPIA II includes the option to allow for the formation of solid salts at low RH conditions (stable state). The predictions of EMAC by employing all three aerosol thermodynamic models were compared to each other and evaluated against surface measurements from three regional observational networks in the polluted Northern Hemisphere (Interagency Monitoring of Protected Visual Environments (IMPROVE), European Monitoring and Evaluation Programme (EMEP), and Acid Deposition Monitoring Network of East Asia (EANET)). The differences between ISORROPIA II v2.3 and ISORROPIA-lite were minimal in all comparisons with the normalized mean absolute difference for the concentrations of all major aerosol components being less than 11 % even when different phase state assumptions were used. The most notable differences were lower aerosol concentrations predicted by ISORROPIA-lite in regions with relative humidity in the range of 20 % to 60 % compared to the predictions of ISORROPIA II v2.3 in stable mode. The comparison against observations yielded satisfactory agreement especially over the USA and Europe but higher deviations over East Asia, where the overprediction of EMAC for nitrate was as high as 4 µ g m -3 (∼20%). The mean annual aerosol pH predicted by ISORROPIA-lite was on average less than a unit lower than ISORROPIA II v2.3 in stable mode, mainly for coarse-mode aerosols over the Middle East. The use of ISORROPIA-lite accelerated EMAC by nearly 5 % compared to the use of ISORROPIA II v2.3 even if the aerosol thermodynamic calculations consume a relatively small fraction of the EMAC computational time. ISORROPIA-lite can therefore be a reliable and computationally efficient alternative to the previous thermodynamic module in EMAC. [ABSTRACT FROM AUTHOR]

While the number and types of indoor air pollutants is rising, much is suspected but little is known about the impact of their potentially synergistic interactions, upon human health. Gases, particulate matter, organic compounds but also allergens and viruses, fall within the 'pollutant' definition. Distinct populations, such as children and allergy and asthma sufferers are highly susceptible, while a low socioeconomic background is a further susceptibility factor; however, no specific guidance is available. We spend most of our time indoors; for children, the school environment is of paramount importance and potentially amenable to intervention. The interactions between some pollutant classes have been studied. However, a lot is missing with respect to understanding interactions between specific pollutants of different classes in terms of concentrations, timing and sequence, to improve targeting and upgrade standards. SynAir‐G is a European Commission‐funded project aiming to reveal and quantify synergistic interactions between different pollutants affecting health, from mechanisms to real life, focusing on the school setting. It will develop a comprehensive and responsive multipollutant monitoring system, advance environmentally friendly interventions, and disseminate the generated knowledge to relevant stakeholders in accessible and actionable formats. The aim of this article it to put forward the SynAir‐G hypothesis, and describe its background and objectives. [ABSTRACT FROM AUTHOR]

The SmartAQ (Smart Air Quality) forecasting system produces high-resolution (1 × 1 km2) air quality predictions in an urban area for the next three days using advanced chemical transport modeling. In this study, we evaluated the SmartAQ performance for the urban area of Patras, Greece, for four months (July 2021, September 2021, December 2021, and March 2022), covering all seasons. In this work, we assess the system's ability to forecast PM2.5 levels and the major gas-phase pollutants during periods with different meteorological conditions and local emissions, but also in areas of the city with different characteristics (urban, suburban, and background sites). We take advantage of this SmartAQ application to also quantify the main sources of the pollutants at each site. During the summertime, PM2.5 model performance was excellent (Fbias < 15%, Ferror < 30%) for all sites both in the city center and suburbs. For the city center, the model reproduced well (MB = −0.9 μg m−3, ME = 2.5 μg m−3) the overall measured PM2.5 behavior and the high nighttime peaks due to cooking activity, as well as the transported PM pollution in the suburbs. During the fall, the SmartAQ PM2.5 performance was good (Fbias < 42%, Ferror < 45%) for the city center and the suburban core, while it was average (Fbias < 50%, Ferror < 54%, MB, ME < 3.3 μg m−3) for the suburbs because the model overpredicted the long-range transport of pollution. For wintertime, the system reproduced well (MB = −2 μg m−3, ME = 6.5 μg m−3) the PM2.5 concentration in the high-biomass-burning emission area with an excellent model performance (Fbias = −4%, Ferror = 33%) and reproduced well (MB < 1.1 μg m−3, ME < 3 μg m−3) the background PM2.5 levels. SmartAQ reproduced well the PM2.5 concentrations in the urban and suburban core during the spring (Fbias < 40%, Ferror < 50%, MB < 8.5 μg m−3, ME < 10 μg m−3), while it tended to slightly overestimate the regional pollution. The main local source of fine PM during summer and autumn was cooking, but most of the PM was transported to the city. Residential biomass burning was the dominant particle source of pollution during winter and early spring. For gas-phase pollutants, the system reproduced well the daily nitrogen oxides (NOx) concentrations during the summertime. Predicted NOx concentrations during the winter were consistent with measurements at night but underestimated the observations during the rest of the day. SmartAQ achieved the US EPA modeling goals for hourly O3 concentrations indicating good model performance. [ABSTRACT FROM AUTHOR]

Extensive continuous particle number size distribution measurements took place during two summers (2020 and 2021) at 11 sites in Greece for the investigation of the frequency and the spatial extent of new particle formation (NPF). The study area is characterized by high solar intensity and fast photochemistry and has moderate to low fine particulate matter levels during the summer. The average PM 2.5 levels were relatively uniform across the examined sites. The NPF frequency during summer varied from close to zero in the southwestern parts of Greece to more than 60 % in the northern, central, and eastern regions. The mean particle growth rate for each station varied between 3.4 and 8 nm h -1 , with an average rate of 5.7 nm h -1. At most of the sites there was no statistical difference in the condensation sink between NPF event and non-event days, while lower relative humidity was observed during the events. The high-NPF-frequency sites in the north and northeast were in close proximity to both coal-fired power plants (high emissions of SO 2) and agricultural areas with some of the highest ammonia emissions in the country. The southern and western parts of Greece, where NPF was infrequent, were characterized by low ammonia emissions, while moderate levels of sulfuric acid were estimated (10 7 molec. cm -3) in the west. Although the emissions of biogenic volatile organic compounds were higher in western and southern sectors, they did not appear to lead to enhanced frequency of NPF. The infrequent events at these sites occurred when the air masses had spent a few hours over areas with agricultural activities and thus elevated ammonia emissions. Air masses arriving at the sites directly from the sea were not connected with atmospheric NPF. These results support the hypothesis that ammonia and/or amines limit new particle formation in the study area. [ABSTRACT FROM AUTHOR]