Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants

We present an updated mechanism for tropospheric halogen (Cl&thinsp;+&thinsp;Br&thinsp;+&thinsp;I) chemistry in the GEOS-Chem global atmospheric chemical transport model and apply it to investigate halogen radical cycling and implications for tropospheric oxidants. Improved representation of HOBr heterogeneous chemistry and its pH dependence in our simulation leads to less efficient recycling and mobilization of bromine radicals and enables the model to include mechanistic sea salt aerosol debromination without generating excessive BrO. The resulting global mean tropospheric BrO mixing ratio is 0.19&thinsp;ppt (parts per trillion), lower than previous versions of GEOS-Chem. Model BrO shows variable consistency and biases in comparison to surface and aircraft observations in marine air, which are often near or below the detection limit. The model underestimates the daytime measurements of Cl2 and BrCl from the ATom aircraft campaign over the Pacific and Atlantic, which if correct would imply a very large missing primary source of chlorine radicals. Model IO is highest in the marine boundary layer and uniform in the free troposphere, with a global mean tropospheric mixing ratio of 0.08&thinsp;ppt, and shows consistency with surface and aircraft observations. The modeled global mean tropospheric concentration of Cl atoms is 630&thinsp;cm&minus;3, contributing 0.8&thinsp;% of the global oxidation of methane, 14&thinsp;% of ethane, 8&thinsp;% of propane, and 7&thinsp;% of higher alkanes. Halogen chemistry decreases the global tropospheric burden of ozone by 11&thinsp;%, NOx by 6&thinsp;%, and OH by 4&thinsp;%. Most of the ozone decrease is driven by iodine-catalyzed loss. The resulting GEOS-Chem ozone simulation is unbiased in the Southern Hemisphere but too low in the Northern Hemisphere. &nbsp; Full List of Authors: Xuan Wang1,2, Daniel J. Jacob3, William Downs3, Shuting Zhai4, Lei Zhu5, Viral Shah3, Christopher D. Holmes6, Tom&aacute;s Sherwen7,8, Becky Alexander4, Mathew J. Evans7,8, Sebastian D. Eastham9, J. Andrew Neuman10,11, Patrick R. Veres10, Theodore K. Koenig11,12, Rainer Volkamer11,12, L. Gregory Huey13, Thomas J. Bannan14, Carl J. Percival14,a, Ben H. Lee4, and Joel A. Thornton4 1School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China 2City University of Hong Kong Shenzhen Research Institute, Shenzhen, China 3School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA 4Department of Atmospheric Sciences, University of Washington, Seattle, Washington, USA 5School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China 6Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, Florida, USA 7Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, UK 8National Centre for Atmospheric Science, University of York, York, UK 9Laboratory for Aviation and the Environment, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 10NOAA Chemical Sciences Laboratory (CSL), Boulder, Colorado, USA 11Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA 12Department of Chemistry, University of Colorado, Boulder, Colorado, USA 13School of Earth and Atmospheric Science, Georgia Institute of Technology, Atlanta, Georgia, USA 14School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, UK anow at: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA &nbsp;</p

Inter-comparison of MAX-DOAS measurements of tropospheric HONO slant column densities and vertical profiles during the CINDI-2 campaign

We present the inter-comparison of delta slant column densities (SCDs) and vertical profiles of nitrous acid (HONO) derived from measurements of different multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments and using different inversion algorithms during the Second Cabauw Inter-comparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) in September&nbsp;2016 at Cabauw, the Netherlands (51.97∘&thinsp;N, 4.93∘&thinsp;E). The HONO vertical profiles, vertical column densities (VCDs), and near-surface volume mixing ratios are compared between different MAX-DOAS instruments and profile inversion algorithms for the first time. Systematic and random discrepancies of the HONO results are derived from the comparisons of all data sets against their median values. Systematic discrepancies of HONO delta SCDs are observed in the range of &plusmn;0.3&times;1015&thinsp;molec.&thinsp;cm&minus;2, which is half of the typical random discrepancy of 0.6&times;1015&thinsp;molec.&thinsp;cm&minus;2. For a typical high HONO delta SCD of 2&times;1015&thinsp;molec.&thinsp;cm&minus;2, the relative systematic and random discrepancies are about 15&thinsp;% and 30&thinsp;%, respectively. The inter-comparison of HONO profiles shows that both systematic and random discrepancies of HONO VCDs and near-surface volume mixing ratios (VMRs) are mostly in the range of &sim;&plusmn;0.5&times;1014&thinsp;molec.&thinsp;cm&minus;2 and &sim;&plusmn;0.1&thinsp;ppb (typically &sim;20&thinsp;%). Further we find that the discrepancies of the retrieved HONO profiles are dominated by discrepancies of the HONO delta SCDs. The profile retrievals only contribute to the discrepancies of the HONO profiles by &sim;5&thinsp;%. However, some data sets with substantially larger discrepancies than the typical values indicate that inappropriate implementations of profile inversion algorithms and configurations of radiative transfer models in the profile retrievals can also be an important uncertainty source. In addition, estimations of measurement uncertainties of HONO dSCDs, which can significantly impact profile retrievals using the optimal estimation method, need to consider not only DOAS fit errors, but also atmospheric variability, especially for an instrument with a DOAS fit error lower than &sim;3&times;1014&thinsp;molec.&thinsp;cm&minus;2. The MAX-DOAS results during the CINDI-2 campaign indicate that the peak HONO levels (e.g. near-surface VMRs of &sim;0.4&thinsp;ppb) often appeared in the early morning and below 0.2&thinsp;km. The near-surface VMRs retrieved from the MAX-DOAS observations are compared with those measured using a co-located long-path DOAS instrument. The systematic differences are smaller than 0.15 and 0.07&thinsp;ppb during early morning and around noon, respectively. Since true HONO values at high altitudes are not known in the absence of real measurements, in order to evaluate the abilities of profile inversion algorithms to respond to different HONO profile shapes, we performed sensitivity studies using synthetic HONO delta SCDs simulated by a radiative transfer model with assumed HONO profiles. The tests indicate that the profile inversion algorithms based on the optimal estimation method with proper configurations can reproduce the different HONO profile shapes well. Therefore we conclude that the features of HONO accumulated near the surface derived from MAX-DOAS measurements are expected to represent the ambient HONO profiles well. Full List of Authors: Yang Wang1, Arnoud Apituley2, Alkiviadis Bais3, Steffen Beirle1, Nuria Benavent4, Alexander Borovski5, Ilya Bruchkouski6, Ka Lok Chan7,8, Sebastian Donner1, Theano Drosoglou3, Henning Finkenzeller9,10, Martina M. Friedrich11, Udo Frie&szlig;12, David Garcia-Nieto4, Laura G&oacute;mez-Mart&iacute;n13, Fran&ccedil;ois Hendrick11, Andreas Hilboll14, Junli Jin15, Paul Johnston16, Theodore K. Koenig9,10, Karin Kreher17, Vinod Kumar1, Aleksandra Kyuberis18, Johannes Lampel12,19, Cheng Liu20, Haoran Liu20, Jianzhong Ma21, Oleg L. Polyansky18,22, Oleg Postylyakov5, Richard Querel16, Alfonso Saiz-Lopez4, Stefan Schmitt12, Xin Tian23,24, Jan-Lukas Tirpitz12, Michel Van Roozendael11, Rainer Volkamer9,10, Zhuoru Wang8, Pinhua Xie24, Chengzhi Xing25, Jin Xu24, Margarita Yela13, Chengxin Zhang25, and Thomas Wagner11Max Planck Institute for Chemistry, Mainz, Germany 2Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands 3Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece 4Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano (CSIC), Madrid, Spain 5A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia 6National Ozone Monitoring Research and Education Center BSU (NOMREC BSU), Belarusian State University, Minsk, Belarus 7Meteorologisches Institut, Ludwig-Maximilians-Universit&auml;t M&uuml;nchen, Munich, Germany 8Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany 9Department of Chemistry, University of Colorado Boulder, Boulder, CO, USA 10Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA 11Royal Belgian Institute for Space Aeronomy, Brussels, Belgium 12Institute of Environmental Physics, University of Heidelberg, Heidelberg, Germany 13National Institute of Aerospatial Technology, Madrid, Spain 14Institute of Environmental Physics, University of Bremen, Bremen, Germany 15Meteorological Observation Center, China Meteorological Administration, Beijing, China 16National Institute of Water &amp; Atmospheric Research (NIWA), Lauder, New Zealand 17BK Scientific, Mainz, Germany 18Institute of Applied Physics, Russian Academy of Sciences, Nizhny Novgorod, Russia 19Airyx GmbH, Justus-von-Liebig-Str. 14, 69214 Eppelheim, Germany 20Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, China 21Chinese Academy of Meteorology Science, China Meteorological Administration, Beijing, China 22Department of Physics and Astronomy, University College London, Gower St, London, WC1E 6BT, UK 23Institutes of Physical Science and Information Technology, Anhui University, Hefei, 230601, China 24Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China 25School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui, China </ul

Anopheles gambiae Trehalase Inhibitors for Malaria Vector Control: A Molecular Docking and Molecular Dynamics Study.

Trehalase inhibitors are considered safe alternatives for insecticides and fungicides. However, there are no studies testing these compounds on Anopheles gambiae, a major vector of human malaria. This study predicted the three-dimensional structure of Anopheles gambiae trehalase (AgTre) and identified potential inhibitors using molecular docking and molecular dynamics methods. Robetta server, C-I-TASSER, and I-TASSER were used to predict the protein structure, while the structural assessment was carried out using SWISS-MODEL, ERRAT, and VERIFY3D. Molecular docking and screening of 3022 compounds was carried out using AutoDock Vina in PyRx, and MD simulation was carried out using NAMD. The Robetta model outperformed all other models and was used for docking and simulation studies. After a post-screening analysis and ADMET studies, uniflorine, 67837201, 10406567, and Compound 2 were considered the best hits with binding energies of -6.9, -8.9, -9, and -8.4 kcal/mol, respectively, better than validamycin A standard (-5.4 kcal/mol). These four compounds were predicted to have no eco-toxicity, Brenk, or PAINS alerts. Similarly, they were predicted to be non-mutagenic, carcinogenic, or hepatoxic. 67837201, 10406567, and Compound 2 showed excellent stability during simulation. The study highlights uniflorine, 67837201, 10406567, and Compound 2 as good inhibitors of AgTre and possible compounds for malaria vector control

Help-seeking attitudes and behaviours for mental health problems in adolescents before and during the first COVID-19 school closures in Germany.

AIM Comparing measures of psychological wellbeing and help-seeking in youths before and within the first school closures due to the coronavirus disease 2019 (COVID-19) pandemic enables a better understanding of the effects the pandemic has for those seeking professional help for mental health problems. METHODS Data were obtained from the Germany-based ProHEAD school study. Pre-lockdown and lockdown samples (n = 648) were compared regarding pupils' psychological wellbeing, help-seeking attitudes and help-seeking behaviour. RESULTS Participants from the lockdown sample showed greater positive attitudes towards seeking professional help, whereas psychological wellbeing and help-seeking behaviour remained stable. CONCLUSIONS Possible explanations may include an increased public discourse on mental health or self-selection bias for participation during lockdown

Iodine chemistry in the chemistry-climate model SOCOL-AERv2-I

In this paper, we present a new version of the chemistry-climate model SOCOL-AERv2 supplemented by an iodine chemistry module. We perform three 20-year ensemble experiments to assess the validity of the modeled iodine and to quantify the effects of iodine on ozone. The iodine distributions obtained with SOCOL-AERv2-I agree well with AMAX-DOAS observations and with CAM-chem model simulations. For the present-day atmosphere, the model suggests that the iodine-induced chemistry leads to a 3ĝ€¯%-4ĝ€¯% reduction in the ozone column, which is greatest at high latitudes. The model indicates the strongest influence of iodine in the lower stratosphere with 30ĝ€¯ppbv less ozone at low latitudes and up to 100ĝ€¯ppbv less at high latitudes. In the troposphere, the account of the iodine chemistry reduces the tropospheric ozone concentration by 5ĝ€¯%-10ĝ€¯% depending on geographical location. In the lower troposphere, 75ĝ€¯% of the modeled ozone reduction originates from inorganic sources of iodine, 25ĝ€¯% from organic sources of iodine. At 50ĝ€¯hPa, the results show that the impacts of iodine from both sources are comparable. Finally, we determine the sensitivity of ozone to iodine by applying a 2-fold increase in iodine emissions, as it might be representative for iodine by the end of this century. This reduces the ozone column globally by an additional 1.5ĝ€¯%-2.5ĝ€¯%. Our results demonstrate the sensitivity of atmospheric ozone to iodine chemistry for present and future conditions, but uncertainties remain high due to the paucity of observational data of iodine species.Fil: Karagodin Doyennel, Arseniy. The Institute for Atmospheric and Climate Science; Suiza. Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center; SuizaFil: Rozanov, Eugene. The Institute for Atmospheric and Climate Science; Suiza. Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center; Suiza. Saint Petersburg State University; RusiaFil: Sukhodolov, Timofei. Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center; Suiza. Saint Petersburg State University; Rusia. University of Natural Resources and Life Sciences; AustriaFil: Egorova, Tatiana. Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center; SuizaFil: Saiz López, Alfonso. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Cuevas, Carlos A.. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Fernandez, Rafael Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Interdisciplinario de Ciencias Básicas. - Universidad Nacional de Cuyo. Instituto Interdisciplinario de Ciencias Básicas; Argentina. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Sherwen, Tomás. University of York; Reino UnidoFil: Volkamer, Rainer. The Institute for Atmospheric and Climate Science ; Suiza. State University of Colorado at Boulder; Estados Unidos. Cooperative Institute for Research in Environmental Sciences; Estados Unidos. Paul Scherrer Institute; SuizaFil: Koenig, Theodore K.. State University of Colorado at Boulder; Estados Unidos. Cooperative Institute for Research in Environmental Sciences; Estados UnidosFil: Giroud, Tanguy. The Institute for Atmospheric and Climate Science; SuizaFil: Peter, Thomas. The Institute for Atmospheric and Climate Science; Suiz

Observed in-plume gaseous elemental mercury depletion suggests significant mercury scavenging by volcanic aerosols

Terrestrial volcanism is known to emit mercury (Hg) into the atmosphere. However, despite many years of investigation, its net impact on the atmospheric Hg budget remains insufficiently constrained, in part because the transformations of Hg in volcanic plumes as they age and mix with background air are poorly understood. Here we report the observation of complete gaseous elemental mercury (GEM) depletion events in dilute and moderately aged (&amp; SIM;3-7 hours) volcanic plumes from Piton de la Fournaise on Reunion Island. While it has been suggested that co-emitted bromine could, once photochemically activated, deplete GEM in a volcanic plume, we measured low bromine concentrations in both the gas- and particle-phase and observed complete GEM depletion even before sunrise, ruling out a leading role of bromine chemistry here. Instead, we hypothesize that the GEM depletions were mainly caused by gas-particle interactions with sulfate-rich volcanic particles (mostly of submicron size), abundantly present in the dilute plume. We consider heterogeneous GEM oxidation and GEM uptake by particles as plausible manifestations of such a process and derive empirical rate constants. By extrapolation, we estimate that volcanic aerosols may scavenge 210 Mg y(-1) (67-480 Mg y(-1)) of Hg from the atmosphere globally, acting effectively as atmospheric mercury sink. While this estimate is subject to large uncertainties, it highlights that Hg transformations in aging volcanic plumes must be better understood to determine the net impact of volcanism on the atmospheric Hg budget and Hg deposition pathways