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  • SDSN - Greece
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: V. A. Flood; K. Strong; C. H. Whaley; K. A. Walker; +30 Authors

    This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Chalmers Researcharrow_drop_down
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    Chalmers Research
    Article . 2024
    Data sources: Chalmers Research
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Atmospheric Chemistry and Physics
    Article . 2024
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Chalmers Researcharrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Chalmers Research
      Article . 2024
      Data sources: Chalmers Research
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2024 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Atmospheric Chemistry and Physics
      Article . 2024
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: S. Atabakhsh; L. Poulain; G. Chen; G. Chen; +6 Authors

    Atmospheric aerosol particles are a complex combination of primary emitted sources (biogenic and anthropogenic) and secondary aerosol resulting from aging processes such as condensation, coagulation, and cloud processing. To better understand their sources, investigations have been focused on urban areas in the past, whereas rural-background stations are normally less impacted by surrounding anthropogenic sources. Therefore, they are predisposed for studying the impact of long-range transport of anthropogenic aerosols. Here, the chemical composition and organic aerosol (OA) sources of submicron aerosol particles measured by an aerosol chemical speciation monitor (ACSM) and a multi-angle absorption photometer (MAAP) were investigated at Melpitz from September 2016 to August 2017. The location of the station at the frontier between western and eastern Europe makes it the ideal place to investigate the impact of long-range transport over Europe. Indeed, the station is under the influence of less polluted air masses from westerly directions and more polluted continental air masses from eastern Europe. The OA dominated the submicron particle mass concentration and showed strong seasonal variability ranging from 39 % (in winter) to 58 % (in summer). It was followed by sulfate (15 % and 20 %) and nitrate (24 % and 11 %). The OA source identification was performed using the rolling positive matrix factorization (PMF) approach to account for the potential temporal changes in the source profile. It was possible to split OA into five factors with a distinct temporal variability and mass spectral signature. Three were associated with anthropogenic primary OA (POA) sources: hydrocarbon-like OA (HOA; 5.2 % of OA mass in winter and 6.8 % in summer), biomass burning OA (BBOA; 10.6 % and 6.1 %) and coal combustion OA (CCOA; 23 % and 8.7 %). Another two are secondary and processed oxygenated OA (OOA) sources: less oxidized OOA (LO-OOA; 28.4 % and 36.7 %) and more oxidized OOA (MO-OOA; 32.8 % and 41.8 %). Since equivalent black carbon (eBC) was clearly associated with the identified POA factors (sum of HOA, BBOA, and CCOA; R2= 0. 87), eBC's contribution to each of the POA factors was achieved using a multilinear regression model. Consequently, CCOA represented the main anthropogenic sources of carbonaceous aerosol (sum of OA and eBC) not only during winter (56 % of POA in winter) but also in summer (13 % of POA in summer), followed by BBOA (29 % and 69 % of POA in winter and summer, respectively) and HOA (15 % and 18 % of POA in winter and summer, respectively). A seasonal air mass cluster analysis was used to understand the geographical origins of the different aerosol types and showed that during both winter and summer time, PM1 (PM with an aerodynamic diameter smaller than 1 µm) air masses with eastern influence were always associated with the highest mass concentration and the highest coal combustion fraction. Since during wintertime CCOA is a combination of domestic heating and power plant emissions, the summer contribution of CCOA emphasizes the critical importance of coal power plant emissions to rural-background aerosols and its impact on air quality, through long-range transportation.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Atmospheric Chemistr...arrow_drop_down
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Atmospheric Chemistry and Physics
    Article . 2023
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Atmospheric Chemistr...arrow_drop_down
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Atmospheric Chemistry and Physics
      Article . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: E. Ioannidis; E. Ioannidis; K. S. Law; J.-C. Raut; +12 Authors

    Anthropogenic and natural emissions contribute to enhanced concentrations of aerosols in the Arctic winter and early spring, with most attention being paid to anthropogenic aerosols that contribute to so-called Arctic haze. Less-well-studied wintertime sea-spray aerosols (SSAs) under Arctic haze conditions are the focus of this study, since they can make an important contribution to wintertime Arctic aerosol abundances. Analysis of field campaign data shows evidence for enhanced local sources of SSAs, including marine organics at Utqiaġvik (formerly known as Barrow) in northern Alaska, United States, during winter 2014. Models tend to underestimate sub-micron SSAs and overestimate super-micron SSAs in the Arctic during winter, including the base version of the Weather Research Forecast coupled with Chemistry (WRF-Chem) model used here, which includes a widely used SSA source function based on Gong et al. (1997). Quasi-hemispheric simulations for winter 2014 including updated wind speed and sea-surface temperature (SST) SSA emission dependencies and sources of marine sea-salt organics and sea-salt sulfate lead to significantly improved model performance compared to observations at remote Arctic sites, notably for coarse-mode sodium and chloride, which are reduced. The improved model also simulates more realistic contributions of SSAs to inorganic aerosols at different sites, ranging from 20 %–93 % in the observations. Two-thirds of the improved model performance is from the inclusion of the dependence on SSTs. The simulation of nitrate aerosols is also improved due to less heterogeneous uptake of nitric acid on SSAs in the coarse mode and related increases in fine-mode nitrate. This highlights the importance of interactions between natural SSAs and inorganic anthropogenic aerosols that contribute to Arctic haze. Simulation of organic aerosols and the fraction of sea-salt sulfate are also improved compared to observations. However, the model underestimates episodes with elevated observed concentrations of SSA components and sub-micron non-sea-salt sulfate at some Arctic sites, notably at Utqiaġvik. Possible reasons are explored in higher-resolution runs over northern Alaska for periods corresponding to the Utqiaġvik field campaign in January and February 2014. The addition of a local source of sea-salt marine organics, based on the campaign data, increases modelled organic aerosols over northern Alaska. However, comparison with previous available data suggests that local natural sources from open leads, as well as local anthropogenic sources, are underestimated in the model. Missing local anthropogenic sources may also explain the low modelled (sub-micron) non-sea-salt sulfate at Utqiaġvik. The introduction of a higher wind speed dependence for sub-micron SSA emissions, also based on Arctic data, reduces biases in modelled sub-micron SSAs, while sea-ice fractions, including open leads, are shown to be an important factor controlling modelled super-micron, rather than sub-micron, SSAs over the north coast of Alaska. The regional results presented here show that modelled SSAs are more sensitive to wind speed dependence but that realistic modelling of sea-ice distributions is needed for the simulation of local SSAs, including marine organics. This study supports findings from the Utqiaġvik field campaign that open leads are the primary source of fresh and aged SSAs, including marine organic aerosols, during wintertime at Utqiaġvik; these findings do not suggest an influence from blowing snow and frost flowers. To improve model simulations of Arctic wintertime aerosols, new field data on processes that influence wintertime SSA production, in particular for fine-mode aerosols, are needed as is improved understanding about possible local anthropogenic sources.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PURE Aarhus Universi...arrow_drop_down
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    Authors: M. Mytilinaios; S. Basart; S. Basart; S. Ciamprone; +12 Authors

    Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

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    Atmospheric Chemistry and Physics
    Article . 2023
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      Atmospheric Chemistry and Physics
      Article . 2023
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    Authors: M. Okuljar; O. Garmash; O. Garmash; M. Olin; +18 Authors

    Condensable vapors, including highly oxygenated organic molecules (HOMs), govern secondary organic aerosol formation and thereby impact the quantity, composition, and properties (e.g., toxicity) of aerosol particles. These vapors are mainly formed in the atmosphere through the oxidation of volatile organic compounds (VOCs). Urban environments contain a variety of VOCs from both anthropogenic and biogenic sources, as well as other species, for instance nitrogen oxides (NOx), that can greatly influence the formation pathways of condensable vapors like HOMs. During the last decade, our understanding of HOM composition and formation has increased dramatically, with most experiments performed in forests or in heavily polluted urban areas. However, studies on the main sources for condensable vapors and secondary organic aerosols (SOAs) in biogenically influenced urban areas, such as suburbs or small cities, have been limited. Here, we studied the HOM composition, measured with two nitrate-based chemical ionization mass spectrometers and analyzed using positive matrix factorization (PMF), during late spring at two locations in Helsinki, Finland. Comparing the measured concentrations at a street canyon site and a nearby urban background station, we found a strong influence of NOx on the HOM formation at both stations, in agreement with previous studies conducted in urban areas. Even though both stations are dominated by anthropogenic VOCs, most of the identified condensable vapors originated from biogenic precursors. This implies that in Helsinki anthropogenic activities mainly influence HOM formation by the effect of NOx on the biogenic VOC oxidation. At the urban background station, we found condensable vapors formed from two biogenic VOC groups (monoterpenes and sesquiterpenes), while at the street canyon, the only identified biogenic HOM precursor was monoterpenes. At the street canyon, we also observed oxidation products of aliphatic VOCs, which were not observed at the urban background station. The only factors that clearly correlate (temporally and composition-wise) between the two stations contained monoterpene-derived dimers. This suggests that HOM composition and formation mechanisms are strongly dependent on localized emissions and the oxidative environment in these biogenically influenced urban areas, and they can also change considerably within distances of 1 km within the urban environment. This further suggests that studies should be careful when extrapolating single-point measurements in an urban setting to be representative of district or city scales.

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    https://doi.org/10.5194/egusph...
    Preprint . 2023 . Peer-reviewed
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    Copernicus Publications
    Other literature type . 2023
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    Atmospheric Chemistry and Physics
    Article . 2023
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2023 . Peer-reviewed
    License: CC BY
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      https://doi.org/10.5194/egusph...
      Preprint . 2023 . Peer-reviewed
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      Copernicus Publications
      Other literature type . 2023
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      Atmospheric Chemistry and Physics
      Article . 2023
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2023 . Peer-reviewed
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    Authors: W. F. Swanson; C. D. Holmes; W. R. Simpson; K. Confer; +10 Authors

    ReactivehalogensplayaprominentroleintheatmosphericchemistryoftheArcticduringspringtime. Field measurements and modeling studies suggest that halogens are emitted into the atmosphere from snowpack and reactions on wind-blown snow-sourced aerosols. The relative importance of snowpack and blowing snow sources is still debated, both at local scales and regionally throughout the Arctic. To understand the implications of these halogen sources on a pan-Arctic scale, we simulate Arctic reactive bromine chemistry in the atmospheric chemical transport model GEOS-Chem. Two mechanisms are included: (1) a blowing snow sea salt aerosol formation mechanism and (2) a snowpack mechanism assuming uniform molecular bromine production from all snow surfaces. We compare simulations including neither mechanism, each mechanism individually, and both mechanisms to examine conditions where one process may dominate or the mechanisms may interact. We compare the models using these mechanisms to observations of bromine monoxide (BrO) derived from multiple- axis differential optical absorption spectroscopy (MAX-DOAS) instruments on O-Buoy platforms on the sea ice and at a coastal site in Utqiag ̇vik, Alaska, during spring 2015. Model estimations of hourly and monthly average BrO are improved by assuming a constant yield of 0.1 % molecular bromine from all snowpack surfaces on ozone deposition. The blowing snow aerosol mechanism increases modeled BrO by providing more bromide-rich aerosol surface area for reactive bromine recycling. The snowpack mechanism led to increased model BrO across the Arctic Ocean with maximum production in coastal regions, whereas the blowing snow aerosol mechanism increases BrO in specific areas due to high surface wind speeds. Our uniform snowpack source has a greater impact on BrO mixing ratios than the blowing snow source. Model results best replicate several features of BrO observations during spring 2015 when using both mechanisms in conjunction, adding evidence that these mechanisms are both active during the Arctic spring. Extending our transport model throughout the entire year leads to predictions of enhanced fall BrO that are not supported by observations. International audience

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    Atmospheric Chemistry and Physics
    Article . 2022
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2022 . Peer-reviewed
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      Article . 2022
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      Atmospheric Chemistry and Physics (ACP)
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    Authors: Michail Mytilinaios; Sara Basart; Sergio Ciamprone; Juan Cuesta; +9 Authors

    Abstract. Aerosol reanalysis datasets are model-based observationally constrained continuous 3D aerosol fields with relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects and impacts upon socio–economic sectors, such as health. Here we compare and assess the recently published MONARCH high resolution regional desert dust reanalysis over Northern Africa, the Middle East and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS, MISR and IASI space-borne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows for at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products, are factors that bias the reanalysis assessment. We, therefore, also used ground-based DOD observations provided by 238 stations of the AERONET network located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking into consideration these results, the MONARCH reanalysis assessment showed that total and coarse DOD simulations are consistent with satellite and ground-based data, capturing qualitatively the major dust sources in the area as well as the dust transport patterns. Moreover, the reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases were found over the Sahara Desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low as the low relative bias in the Sahara Desert (< 0.5) and over the adjacent maritime regions (< 1), certifies. Similarly, over areas with intense dust activity the linear correlation coefficient between the reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean and the Arabian Sea, and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions where large amounts of observations are available, allowing for robust model assessment.

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    https://doi.org/10.5194/acp-20...
    Preprint . 2022 . Peer-reviewed
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      https://doi.org/10.5194/acp-20...
      Preprint . 2022 . Peer-reviewed
      License: CC BY
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    Authors: Yueling Ma; Carsten Montzka; Bibi S Naz; Stefan Kollet;

    Abstract The main challenge of pan-European groundwater (GW) monitoring is the sparsity of collated water table depth (wtd) observations. The wtd anomaly (wtda ) is a measure of the increased wtd due to droughts. Combining long short-term memory (LSTM) networks and transfer learning (TL), we propose an AI-based methodology LSTM-TL to produce reliable wtda estimates at the European scale in the absence of consistent wtd observational data sets. The core idea of LSTM-TL is to transfer the modeled relationship between wtda and input hydrometeorological forcings to the observation-based estimation, in order to provide reliable wtda estimates for regions with no or sparse wtd observations. With substantially reduced computational cost compared to physically-based numerical models, LSTM-TL obtained wtda estimates in good agreement with in-situ wtda measurements from 2569 European GW monitoring wells, showing r ⩾ 0.5, root-mean-square error ⩽1.0 and Kling-Gupta efficiency ⩾0.3 at about or more than half of the pixels. Based on the reconstructed long-term European monthly wtda data from the early 1980s to the near present, we provide the first estimate of seasonal wtda trends in different European regions, that is, significant drying trends in central and eastern Europe, which facilitates the understanding of historical GW dynamics in Europe. The success of LSTM-TL in estimating wtda also highlights the advantage of combining AI techniques with knowledge contained in physically-based numerical models in hydrological studies.

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    Environmental Research Letters
    Article . 2022 . Peer-reviewed
    License: CC BY
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    Environmental Research Letters
    Article . 2022
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      Environmental Research Letters
      Article . 2022 . Peer-reviewed
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      Environmental Research Letters
      Article . 2022
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    Authors: A. M. Koenig; O. Magand; B. Verreyken; B. Verreyken; +13 Authors

    Atmospheric mercury (Hg) observations in the lower free troposphere (LFT) can give important insights into Hg redox chemistry and can help constrain Hg background concentrations on a regional level. Relatively continuous sampling of LFT air, inaccessible to most ground-based stations, can be achieved at highaltitude observatories. However, such high-altitude observatories are rare, especially in the Southern Hemisphere (SH), and atmospheric Hg in the SH LFT is unconstrained. To fill this gap, we continuously measured gaseous elemental mercury (GEM; hourly) and reactive mercury (RM; integrated over ∼ 6-14 d) for 9 months at Maïdo mountain observatory (2160 m a.s.l.) on remote Réunion Island (21.1 • S, 55.5 • E) in the tropical Indian Ocean. GEM exhibits a marked diurnal variation characterized by a midday peak (mean: 0.95 ng m −3 ; SD: 0.08 ng m −3) and a nighttime low (mean: 0.78 ng m −3 ; SD: 0.11 ng m −3). We find that this diurnal variation is likely driven by the interplay of important GEM photo-reemission from the islands' vegetated surfaces (i.e. vegetation + soil) during daylight hours (8-22 ng m −2 h −1), boundary layer influences during the day, and predominant LFT influences at night. We estimate GEM in the LFT based on nighttime observations in particularly dry air masses and find a notable seasonal variation, with LFT GEM being lowest from December to March (mean 0.66 ng m −3 ; SD: 0.07 ng m −3) and highest from September to November (mean: 0.79 ng m −3 ; SD: 0.09 ng m −3). Such a clear GEM seasonality contrasts with the weak seasonal variation reported for the SH marine boundary layer but is in line with modeling results, highlighting the added value of continuous Hg observations in the LFT. Maïdo RM is 10.6 pg m −3 (SD: 5.9 pg m −3) on average, but RM in the cloud-free LFT might be about twice as high, International audience

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    Atmospheric Chemistry and Physics
    Article . 2023
    Data sources: DOAJ
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    https://doi.org/10.5194/egusph...
    Preprint . 2022 . Peer-reviewed
    License: CC BY
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    Copernicus Publications
    Other literature type . 2023
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      Atmospheric Chemistry and Physics
      Article . 2023
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      https://doi.org/10.5194/egusph...
      Preprint . 2022 . Peer-reviewed
      License: CC BY
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      Copernicus Publications
      Other literature type . 2023
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    Authors: Glaubitz, Lina; Stumme, Johanna; Lucht, Sarah; Moebus, Susanne; +4 Authors

    BACKGROUND: Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown. OBJECTIVE: This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks. METHODS: Data from 574 participants (44.1% female, 56-85 years of age) in the German 1000BRAINS study (2011-2015) were analyzed. Exposure to particulate matter (formula presented , and formula presented absorbance), accumulation mode particle number (formula presented ), and nitrogen dioxide (formula presented ) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h (formula presented ) and nighttime (formula presented ) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables. RESULTS: Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, formula presented (95% CI: formula presented , 0.009) per 0.3 formula presented increase in formula presented absorbance and formula presented (95% CI: formula presented ) per 1-y age increase]. CONCLUSION: High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: V. A. Flood; K. Strong; C. H. Whaley; K. A. Walker; +30 Authors

    This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

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    Chalmers Research
    Article . 2024
    Data sources: Chalmers Research
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2024 . Peer-reviewed
    License: CC BY
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    Atmospheric Chemistry and Physics
    Article . 2024
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      Chalmers Research
      Article . 2024
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2024 . Peer-reviewed
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      Atmospheric Chemistry and Physics
      Article . 2024
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    Authors: S. Atabakhsh; L. Poulain; G. Chen; G. Chen; +6 Authors

    Atmospheric aerosol particles are a complex combination of primary emitted sources (biogenic and anthropogenic) and secondary aerosol resulting from aging processes such as condensation, coagulation, and cloud processing. To better understand their sources, investigations have been focused on urban areas in the past, whereas rural-background stations are normally less impacted by surrounding anthropogenic sources. Therefore, they are predisposed for studying the impact of long-range transport of anthropogenic aerosols. Here, the chemical composition and organic aerosol (OA) sources of submicron aerosol particles measured by an aerosol chemical speciation monitor (ACSM) and a multi-angle absorption photometer (MAAP) were investigated at Melpitz from September 2016 to August 2017. The location of the station at the frontier between western and eastern Europe makes it the ideal place to investigate the impact of long-range transport over Europe. Indeed, the station is under the influence of less polluted air masses from westerly directions and more polluted continental air masses from eastern Europe. The OA dominated the submicron particle mass concentration and showed strong seasonal variability ranging from 39 % (in winter) to 58 % (in summer). It was followed by sulfate (15 % and 20 %) and nitrate (24 % and 11 %). The OA source identification was performed using the rolling positive matrix factorization (PMF) approach to account for the potential temporal changes in the source profile. It was possible to split OA into five factors with a distinct temporal variability and mass spectral signature. Three were associated with anthropogenic primary OA (POA) sources: hydrocarbon-like OA (HOA; 5.2 % of OA mass in winter and 6.8 % in summer), biomass burning OA (BBOA; 10.6 % and 6.1 %) and coal combustion OA (CCOA; 23 % and 8.7 %). Another two are secondary and processed oxygenated OA (OOA) sources: less oxidized OOA (LO-OOA; 28.4 % and 36.7 %) and more oxidized OOA (MO-OOA; 32.8 % and 41.8 %). Since equivalent black carbon (eBC) was clearly associated with the identified POA factors (sum of HOA, BBOA, and CCOA; R2= 0. 87), eBC's contribution to each of the POA factors was achieved using a multilinear regression model. Consequently, CCOA represented the main anthropogenic sources of carbonaceous aerosol (sum of OA and eBC) not only during winter (56 % of POA in winter) but also in summer (13 % of POA in summer), followed by BBOA (29 % and 69 % of POA in winter and summer, respectively) and HOA (15 % and 18 % of POA in winter and summer, respectively). A seasonal air mass cluster analysis was used to understand the geographical origins of the different aerosol types and showed that during both winter and summer time, PM1 (PM with an aerodynamic diameter smaller than 1 µm) air masses with eastern influence were always associated with the highest mass concentration and the highest coal combustion fraction. Since during wintertime CCOA is a combination of domestic heating and power plant emissions, the summer contribution of CCOA emphasizes the critical importance of coal power plant emissions to rural-background aerosols and its impact on air quality, through long-range transportation.

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    Atmospheric Chemistry and Physics (ACP)
    Article . 2023 . Peer-reviewed
    License: CC BY
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    Atmospheric Chemistry and Physics
    Article . 2023
    Data sources: DOAJ
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      Atmospheric Chemistry and Physics (ACP)
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      Atmospheric Chemistry and Physics
      Article . 2023
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    Authors: E. Ioannidis; E. Ioannidis; K. S. Law; J.-C. Raut; +12 Authors

    Anthropogenic and natural emissions contribute to enhanced concentrations of aerosols in the Arctic winter and early spring, with most attention being paid to anthropogenic aerosols that contribute to so-called Arctic haze. Less-well-studied wintertime sea-spray aerosols (SSAs) under Arctic haze conditions are the focus of this study, since they can make an important contribution to wintertime Arctic aerosol abundances. Analysis of field campaign data shows evidence for enhanced local sources of SSAs, including marine organics at Utqiaġvik (formerly known as Barrow) in northern Alaska, United States, during winter 2014. Models tend to underestimate sub-micron SSAs and overestimate super-micron SSAs in the Arctic during winter, including the base version of the Weather Research Forecast coupled with Chemistry (WRF-Chem) model used here, which includes a widely used SSA source function based on Gong et al. (1997). Quasi-hemispheric simulations for winter 2014 including updated wind speed and sea-surface temperature (SST) SSA emission dependencies and sources of marine sea-salt organics and sea-salt sulfate lead to significantly improved model performance compared to observations at remote Arctic sites, notably for coarse-mode sodium and chloride, which are reduced. The improved model also simulates more realistic contributions of SSAs to inorganic aerosols at different sites, ranging from 20 %–93 % in the observations. Two-thirds of the improved model performance is from the inclusion of the dependence on SSTs. The simulation of nitrate aerosols is also improved due to less heterogeneous uptake of nitric acid on SSAs in the coarse mode and related increases in fine-mode nitrate. This highlights the importance of interactions between natural SSAs and inorganic anthropogenic aerosols that contribute to Arctic haze. Simulation of organic aerosols and the fraction of sea-salt sulfate are also improved compared to observations. However, the model underestimates episodes with elevated observed concentrations of SSA components and sub-micron non-sea-salt sulfate at some Arctic sites, notably at Utqiaġvik. Possible reasons are explored in higher-resolution runs over northern Alaska for periods corresponding to the Utqiaġvik field campaign in January and February 2014. The addition of a local source of sea-salt marine organics, based on the campaign data, increases modelled organic aerosols over northern Alaska. However, comparison with previous available data suggests that local natural sources from open leads, as well as local anthropogenic sources, are underestimated in the model. Missing local anthropogenic sources may also explain the low modelled (sub-micron) non-sea-salt sulfate at Utqiaġvik. The introduction of a higher wind speed dependence for sub-micron SSA emissions, also based on Arctic data, reduces biases in modelled sub-micron SSAs, while sea-ice fractions, including open leads, are shown to be an important factor controlling modelled super-micron, rather than sub-micron, SSAs over the north coast of Alaska. The regional results presented here show that modelled SSAs are more sensitive to wind speed dependence but that realistic modelling of sea-ice distributions is needed for the simulation of local SSAs, including marine organics. This study supports findings from the Utqiaġvik field campaign that open leads are the primary source of fresh and aged SSAs, including marine organic aerosols, during wintertime at Utqiaġvik; these findings do not suggest an influence from blowing snow and frost flowers. To improve model simulations of Arctic wintertime aerosols, new field data on processes that influence wintertime SSA production, in particular for fine-mode aerosols, are needed as is improved understanding about possible local anthropogenic sources.

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    NARCIS
    Article . 2023
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    Atmospheric Chemistry and Physics
    Article . 2023
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    Article . 2023
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      Atmospheric Chemistry and Physics
      Article . 2023
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    Authors: M. Mytilinaios; S. Basart; S. Basart; S. Ciamprone; +12 Authors

    Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

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    Atmospheric Chemistry and Physics
    Article . 2023
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      Atmospheric Chemistry and Physics
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    Authors: M. Okuljar; O. Garmash; O. Garmash; M. Olin; +18 Authors

    Condensable vapors, including highly oxygenated organic molecules (HOMs), govern secondary organic aerosol formation and thereby impact the quantity, composition, and properties (e.g., toxicity) of aerosol particles. These vapors are mainly formed in the atmosphere through the oxidation of volatile organic compounds (VOCs). Urban environments contain a variety of VOCs from both anthropogenic and biogenic sources, as well as other species, for instance nitrogen oxides (NOx), that can greatly influence the formation pathways of condensable vapors like HOMs. During the last decade, our understanding of HOM composition and formation has increased dramatically, with most experiments performed in forests or in heavily polluted urban areas. However, studies on the main sources for condensable vapors and secondary organic aerosols (SOAs) in biogenically influenced urban areas, such as suburbs or small cities, have been limited. Here, we studied the HOM composition, measured with two nitrate-based chemical ionization mass spectrometers and analyzed using positive matrix factorization (PMF), during late spring at two locations in Helsinki, Finland. Comparing the measured concentrations at a street canyon site and a nearby urban background station, we found a strong influence of NOx on the HOM formation at both stations, in agreement with previous studies conducted in urban areas. Even though both stations are dominated by anthropogenic VOCs, most of the identified condensable vapors originated from biogenic precursors. This implies that in Helsinki anthropogenic activities mainly influence HOM formation by the effect of NOx on the biogenic VOC oxidation. At the urban background station, we found condensable vapors formed from two biogenic VOC groups (monoterpenes and sesquiterpenes), while at the street canyon, the only identified biogenic HOM precursor was monoterpenes. At the street canyon, we also observed oxidation products of aliphatic VOCs, which were not observed at the urban background station. The only factors that clearly correlate (temporally and composition-wise) between the two stations contained monoterpene-derived dimers. This suggests that HOM composition and formation mechanisms are strongly dependent on localized emissions and the oxidative environment in these biogenically influenced urban areas, and they can also change considerably within distances of 1 km within the urban environment. This further suggests that studies should be careful when extrapolating single-point measurements in an urban setting to be representative of district or city scales.

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    https://doi.org/10.5194/egusph...
    Preprint . 2023 . Peer-reviewed
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    Other literature type . 2023
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    Atmospheric Chemistry and Physics
    Article . 2023
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    Atmospheric Chemistry and Physics (ACP)
    Article . 2023 . Peer-reviewed
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      Atmospheric Chemistry and Physics
      Article . 2023
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      Atmospheric Chemistry and Physics (ACP)
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    Authors: W. F. Swanson; C. D. Holmes; W. R. Simpson; K. Confer; +10 Authors

    ReactivehalogensplayaprominentroleintheatmosphericchemistryoftheArcticduringspringtime. Field measurements and modeling studies suggest that halogens are emitted into the atmosphere from snowpack and reactions on wind-blown snow-sourced aerosols. The relative importance of snowpack and blowing snow sources is still debated, both at local scales and regionally throughout the Arctic. To understand the implications of these halogen sources on a pan-Arctic scale, we simulate Arctic reactive bromine chemistry in the atmospheric chemical transport model GEOS-Chem. Two mechanisms are included: (1) a blowing snow sea salt aerosol formation mechanism and (2) a snowpack mechanism assuming uniform molecular bromine production from all snow surfaces. We compare simulations including neither mechanism, each mechanism individually, and both mechanisms to examine conditions where one process may dominate or the mechanisms may interact. We compare the models using these mechanisms to observations of bromine monoxide (BrO) derived from multiple- axis differential optical absorption spectroscopy (MAX-DOAS) instruments on O-Buoy platforms on the sea ice and at a coastal site in Utqiag ̇vik, Alaska, during spring 2015. Model estimations of hourly and monthly average BrO are improved by assuming a constant yield of 0.1 % molecular bromine from all snowpack surfaces on ozone deposition. The blowing snow aerosol mechanism increases modeled BrO by providing more bromide-rich aerosol surface area for reactive bromine recycling. The snowpack mechanism led to increased model BrO across the Arctic Ocean with maximum production in coastal regions, whereas the blowing snow aerosol mechanism increases BrO in specific areas due to high surface wind speeds. Our uniform snowpack source has a greater impact on BrO mixing ratios than the blowing snow source. Model results best replicate several features of BrO observations during spring 2015 when using both mechanisms in conjunction, adding evidence that these mechanisms are both active during the Arctic spring. Extending our transport model throughout the entire year leads to predictions of enhanced fall BrO that are not supported by observations. International audience

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    Atmospheric Chemistry and Physics
    Article . 2022
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    Atmospheric Chemistry and Physics (ACP)
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    Authors: Michail Mytilinaios; Sara Basart; Sergio Ciamprone; Juan Cuesta; +9 Authors

    Abstract. Aerosol reanalysis datasets are model-based observationally constrained continuous 3D aerosol fields with relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects and impacts upon socio–economic sectors, such as health. Here we compare and assess the recently published MONARCH high resolution regional desert dust reanalysis over Northern Africa, the Middle East and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS, MISR and IASI space-borne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows for at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products, are factors that bias the reanalysis assessment. We, therefore, also used ground-based DOD observations provided by 238 stations of the AERONET network located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking into consideration these results, the MONARCH reanalysis assessment showed that total and coarse DOD simulations are consistent with satellite and ground-based data, capturing qualitatively the major dust sources in the area as well as the dust transport patterns. Moreover, the reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases were found over the Sahara Desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low as the low relative bias in the Sahara Desert (< 0.5) and over the adjacent maritime regions (< 1), certifies. Similarly, over areas with intense dust activity the linear correlation coefficient between the reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean and the Arabian Sea, and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions where large amounts of observations are available, allowing for robust model assessment.

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    https://doi.org/10.5194/acp-20...
    Preprint . 2022 . Peer-reviewed
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      https://doi.org/10.5194/acp-20...
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    Authors: Yueling Ma; Carsten Montzka; Bibi S Naz; Stefan Kollet;

    Abstract The main challenge of pan-European groundwater (GW) monitoring is the sparsity of collated water table depth (wtd) observations. The wtd anomaly (wtda ) is a measure of the increased wtd due to droughts. Combining long short-term memory (LSTM) networks and transfer learning (TL), we propose an AI-based methodology LSTM-TL to produce reliable wtda estimates at the European scale in the absence of consistent wtd observational data sets. The core idea of LSTM-TL is to transfer the modeled relationship between wtda and input hydrometeorological forcings to the observation-based estimation, in order to provide reliable wtda estimates for regions with no or sparse wtd observations. With substantially reduced computational cost compared to physically-based numerical models, LSTM-TL obtained wtda estimates in good agreement with in-situ wtda measurements from 2569 European GW monitoring wells, showing r ⩾ 0.5, root-mean-square error ⩽1.0 and Kling-Gupta efficiency ⩾0.3 at about or more than half of the pixels. Based on the reconstructed long-term European monthly wtda data from the early 1980s to the near present, we provide the first estimate of seasonal wtda trends in different European regions, that is, significant drying trends in central and eastern Europe, which facilitates the understanding of historical GW dynamics in Europe. The success of LSTM-TL in estimating wtda also highlights the advantage of combining AI techniques with knowledge contained in physically-based numerical models in hydrological studies.

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    Environmental Research Letters
    Article . 2022 . Peer-reviewed
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    Environmental Research Letters
    Article . 2022
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      Environmental Research Letters
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    Authors: A. M. Koenig; O. Magand; B. Verreyken; B. Verreyken; +13 Authors

    Atmospheric mercury (Hg) observations in the lower free troposphere (LFT) can give important insights into Hg redox chemistry and can help constrain Hg background concentrations on a regional level. Relatively continuous sampling of LFT air, inaccessible to most ground-based stations, can be achieved at highaltitude observatories. However, such high-altitude observatories are rare, especially in the Southern Hemisphere (SH), and atmospheric Hg in the SH LFT is unconstrained. To fill this gap, we continuously measured gaseous elemental mercury (GEM; hourly) and reactive mercury (RM; integrated over ∼ 6-14 d) for 9 months at Maïdo mountain observatory (2160 m a.s.l.) on remote Réunion Island (21.1 • S, 55.5 • E) in the tropical Indian Ocean. GEM exhibits a marked diurnal variation characterized by a midday peak (mean: 0.95 ng m −3 ; SD: 0.08 ng m −3) and a nighttime low (mean: 0.78 ng m −3 ; SD: 0.11 ng m −3). We find that this diurnal variation is likely driven by the interplay of important GEM photo-reemission from the islands' vegetated surfaces (i.e. vegetation + soil) during daylight hours (8-22 ng m −2 h −1), boundary layer influences during the day, and predominant LFT influences at night. We estimate GEM in the LFT based on nighttime observations in particularly dry air masses and find a notable seasonal variation, with LFT GEM being lowest from December to March (mean 0.66 ng m −3 ; SD: 0.07 ng m −3) and highest from September to November (mean: 0.79 ng m −3 ; SD: 0.09 ng m −3). Such a clear GEM seasonality contrasts with the weak seasonal variation reported for the SH marine boundary layer but is in line with modeling results, highlighting the added value of continuous Hg observations in the LFT. Maïdo RM is 10.6 pg m −3 (SD: 5.9 pg m −3) on average, but RM in the cloud-free LFT might be about twice as high, International audience

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    Atmospheric Chemistry and Physics
    Article . 2023
    Data sources: DOAJ
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    https://doi.org/10.5194/egusph...
    Preprint . 2022 . Peer-reviewed
    License: CC BY
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    Copernicus Publications
    Other literature type . 2023
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      Atmospheric Chemistry and Physics
      Article . 2023
      Data sources: DOAJ
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      https://doi.org/10.5194/egusph...
      Preprint . 2022 . Peer-reviewed
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      Copernicus Publications
      Other literature type . 2023
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    Authors: Glaubitz, Lina; Stumme, Johanna; Lucht, Sarah; Moebus, Susanne; +4 Authors

    BACKGROUND: Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown. OBJECTIVE: This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks. METHODS: Data from 574 participants (44.1% female, 56-85 years of age) in the German 1000BRAINS study (2011-2015) were analyzed. Exposure to particulate matter (formula presented , and formula presented absorbance), accumulation mode particle number (formula presented ), and nitrogen dioxide (formula presented ) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h (formula presented ) and nighttime (formula presented ) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables. RESULTS: Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, formula presented (95% CI: formula presented , 0.009) per 0.3 formula presented increase in formula presented absorbance and formula presented (95% CI: formula presented ) per 1-y age increase]. CONCLUSION: High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737.

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