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2020
Thyroid hormone disrupting chemicals (THDCs) are of major concern in ecotoxicology. With the increased number of emerging chemicals on the market there is a need to screen for potential THDCs in a cost-efficient way, and in silico modeling is an alternative to address this issue. In this study homology modeling and docking was used to screen a list of 626 compounds for potential thyroid hormone disrupting properties in two gull species. The tested compounds were known contaminants or emerging contaminants predicted to have the potential to reach the Arctic. Models of transthyretin (TTR) and thyroid hormone receptor α and β (TRα and TRβ) from the Arctic top predator glaucous gull (Larus hyperboreus) and temperate predator herring gull (Larus argentatus) were constructed and used to predict the binding affinity of the compounds to the thyroid hormone (TH) binding sites. The modeling predicted that 28, 4 and 330 of the contaminants would bind to TRα, TRβ and TTR respectively. These compounds were in general halogenated, aromatic and had polar functional groups, like that of THs. However, the predicted binders did not necessarily have all these properties, such as the per- and polyfluoroalkyl substances that are not aromatic and still bind to the proteins.
Elsevier
2020
Investigating the presence and persistence of volatile methylsiloxanes in Arctic sediments
Royal Society of Chemistry (RSC)
2020
2020
FLEXPART v10.1 simulation of source contributions to Arctic black carbon
The Arctic environment is undergoing rapid changes such as faster warming than the global average and exceptional melting of glaciers in Greenland. Black carbon (BC) particles, which are a short-lived climate pollutant, are one cause of Arctic warming and glacier melting. However, the sources of BC particles are still uncertain. We simulated the potential emission sensitivity of atmospheric BC present over the Arctic (north of 66∘ N) using the FLEXPART (FLEXible PARTicle) Lagrangian transport model (version 10.1). This version includes a new aerosol wet removal scheme, which better represents particle-scavenging processes than older versions did. Arctic BC at the surface (0–500 m) and high altitudes (4750–5250 m) is sensitive to emissions in high latitude (north of 60∘ N) and mid-latitude (30–60∘ N) regions, respectively. Geospatial sources of Arctic BC were quantified, with a focus on emissions from anthropogenic activities (including domestic biofuel burning) and open biomass burning (including agricultural burning in the open field) in 2010. We found that anthropogenic sources contributed 82 % and 83 % of annual Arctic BC at the surface and high altitudes, respectively. Arctic surface BC comes predominantly from anthropogenic emissions in Russia (56 %), with gas flaring from the Yamalo-Nenets Autonomous Okrug and Komi Republic being the main source (31 % of Arctic surface BC). These results highlight the need for regulations to control BC emissions from gas flaring to mitigate the rapid changes in the Arctic environment. In summer, combined open biomass burning in Siberia, Alaska, and Canada contributes 56 %–85 % (75 % on average) and 40 %–72 % (57 %) of Arctic BC at the surface and high altitudes, respectively. A large fraction (40 %) of BC in the Arctic at high altitudes comes from anthropogenic emissions in East Asia, which suggests that the rapidly growing economies of developing countries could have a non-negligible effect on the Arctic. To our knowledge, this is the first year-round evaluation of Arctic BC sources that has been performed using the new wet deposition scheme in FLEXPART. The study provides a scientific basis for actions to mitigate the rapidly changing Arctic environment.
2020
We present an observing simulated system experiment (OSSE) dedicated to evaluate the potential added value from the Sentinel-4 and the Sentinel-5P observations on tropospheric ozone composition. For this purpose, the ozone data of Sentinel-4 (Ultraviolet Visible Near-infrared) and Sentinel-5P (TROPOspheric Monitoring Instrument) on board a geostationary (GEO) and a low-Earth-orbit (LEO) platform, respectively, have been simulated using the DISAMAR inversion package for the summer 2003. To ensure the robustness of the results, the OSSE has been configured with conservative assumptions. We simulate the reality by combining two chemistry transport models (CTMs): the LOng Term Ozone Simulation - EURopean Operational Smog (LOTOS-EUROS) and the Transport Model version 5 (TM5). The assimilation system is based on a different CTM, the MOdele de Chimie Atmospherique a Grande Echelle (MOCAGE), combined with the 3-D variational technique. The background error covariance matrix does not evolve in time and its variance is proportional to the field values. The simulated data are formed of six eigenvectors to minimize the size of the dataset by removing the noise-dominated part of the observations. The results show that the satellite data clearly bring direct added value around 200 hPa for the whole assimilation period and for the whole European domain, while a likely indirect added value is identified but not for the whole period and domain at 500 hPa, and to a lower extent at 700 hPa. In addition, the ozone added value from Sentinel-5P (LEO) appears close to that from Sentinel-4 (GEO) in the free troposphere (200-500 hPa) in our OSSE. The outcome of our study is a result of the OSSE design and the choice within each of the components of the system.
2020
Even though production and open use of polychlorinated biphenyls (PCBs) have been phased out in Western industrialised countries since the 1980s, PCBs were still present in waste collected from different waste handling facilities in Norway in 2013. Sums of seven indicator-PCBs (I-PCB7: PCB-28, -52, -101, -118, -138, -153 and -180) were highest in plastic waste (3700 ±1800 μg/kg, n=15), waste electrical and electronic equipment (WEEE) (1300 ± 400 μg/kg, n=12) and fine vehicle fluff (1800 ± 1400 μg/kg, n=4) and lowest in glass waste, combustibles, bottom ash and fly ash (0.3 to 65 μg/kg). Concentrations in leachate water varied from 1.7 to 2900 ng/L, with higher concentrations found at vehicle and WEEE handling facilities. Particles in leachate water exhibited similar PCB sorption properties as solid waste collected on site, with waste-water partitioning coefficients ranging from 105 to 107. I-PCB7 in air samples collected at the sites were mostly in the gas phase (100–24000 pg/m3), compared to those associated with particles (9–1900 pg/m3). In contrast brominated flame retardants (BFRs) in the same samples were predominantly found associated with particles (e.g. sum of 10 brominated diethyl ethers, ΣBDE10, associated with particles 77–194,000 pg/m3) compared to the gas phase (ΣBDE10 6–473 pg/m3). Measured gas-phase I-PCB7 concentrations are less than predicted, assuming waste-air partitioning in equilibrium with predominant waste on site. However, the gas-particle partitioning behavior of PCBs and BFRs could be predicted using an established partitioning model for ambient aerosols. PCB emissions from Norwegian waste handling facilities occurred primarily in the form of atmospheric vapor or leachate particles.
Elsevier
2020
Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and presents a general framework to evaluate them, based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those where it is expected that the techniques will perform well, and those for which some complexity about the site may provide a more severe test. Overall all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small/large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as Optimal Estimation the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potential mixed land/water surfaces, or aerosol optical properties outside of the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for refinement of these techniques.
2020
It is unclear whether the Eurasian snow plays a role in the tropospheric driving of sudden stratospheric warming (SSW). The major SSW event of February 2018 is analyzed using reanalysis datasets. Characterized by predominant planetary waves of zonal wave 2, the SSW developed into a vortex split via wave–mean flow interaction. In the following two weeks, the downward migration of zonal-mean zonal wind anomalies was accompanied by a significant transition to the negative phase of the North Atlantic Oscillation, leading to extensive cold extremes across Europe. Here, we demonstrate that anomalous Siberian snow accumulation could have played an important role in the 2018 SSW occurrence. In the 2017/18 winter, snow depths over Siberia were much higher than normal. A lead–lag correlation analysis shows that the positive fluctuating snow depth anomalies, leading to intensified “cold domes” over eastern Siberia (i.e., in a region where the climatological upward planetary waves maximize), precede enhanced wave-2 pulses of meridional heat fluxes (100 hPa) by 7–8 days. The snow–SSW linkage over 2003–19 is further investigated, and some common traits among three split events are found. These include a time lag of about one week between the maximum anomalies of snow depth and wave-2 pulses (100 hPa), high sea level pressure favored by anomalous snowpack, and a ridge anchoring over Siberia as precursor of the splits. The role of tropospheric ridges over Alaska and the Urals in the wave-2 enhancement and the role of Arctic sea ice loss in Siberian snow accumulation are also discussed.
American Meteorological Society (AMS)
2020
Combining information from several channels of the Norwegian Institute for Air Research (NILU-UV) irradiance meter, one may determine the total ozone column (TOC) amount. A NILU-UV instrument has been deployed and operated on two locations at Troll research station in Jutulsessen, Queen Maud Land, Antarctica, for several years. The method used to determine the TOC amount is presented, and the derived TOC values are compared with those obtained from the Ozone Monitoring Instrument (OMI) located on NASA’s AURA satellite. The findings show that the NILU-UV TOC amounts correlate well with the results of the OMI and that the NILU-UV instruments are suitable for monitoring the long-term change and development of the ozone hole. Because of the large footprint of OMI, NILU-UV is a more suitable instrument for local measurements.
2020