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2023
Trends in polar ozone loss since 1989: potential sign of recovery in the Arctic ozone column
Ozone depletion over the polar regions is monitored each year by satellite- and ground-based instruments. In this study, the vortex-averaged ozone loss over the last 3 decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from Système d'Analyse par Observation Zénithale (SAOZ) ground-based instruments and Multi-Sensor Reanalysis (MSR2). The passive-tracer method allows us to determine the evolution of the daily rate of column ozone destruction and the magnitude of the cumulative column loss at the end of the winter. Three metrics are used in trend analyses that aim to assess the ozone recovery rate over both polar regions: (1) the maximum ozone loss at the end of the winter, (2) the onset day of ozone loss at a specific threshold, and (3) the ozone loss residuals computed from the differences between annual ozone loss and ozone loss values regressed with respect to sunlit volume of polar stratospheric clouds (VPSCs). This latter metric is based on linear and parabolic regressions for ozone loss in the Northern Hemisphere and Southern Hemisphere, respectively. In the Antarctic, metrics 1 and 3 yield trends of −2.3 % and −2.2 % per decade for the 2000–2021 period, significant at 1 and 2 standard deviations (σ), respectively. For metric 2, various thresholds were considered at the total ozone loss values of 20 %, 25 %, 30 %, 35 %, and 40 %, all of them showing a time delay as a function of year in terms of when the threshold is reached. The trends are significant at the 2σ level and vary from 3.5 to 4.2 d per decade between the various thresholds. In the Arctic, metric 1 exhibits large interannual variability, and no significant trend is detected; this result is highly influenced by the record ozone losses in 2011 and 2020. Metric 2 is not applied in the Northern Hemisphere due to the difficulty in finding a threshold value in enough of the winters. Metric 3 provides a negative trend in Arctic ozone loss residuals with respect to the sunlit VPSC fit of −2.00 ± 0.97 (1σ) % per decade, with limited significance at the 2σ level. With such a metric, a potential quantitative detection of ozone recovery in the Arctic springtime lower stratosphere can be made.
2023
2023
Troll observing network – for useful new data about Antarctica
What do Antarctic petrels in Svarthamaren, soil structure movements at Troll research station and ocean chemistry in the Håkon VII Sea have in common? They will all be studied at the Troll observing network currently being established at Troll research station in Dronning Maud Land in Antarctica.
2023
Phthalate contamination in marine mammals off the Norwegian coast
Phthalates are used in plastics, found throughout the marine environment and have the potential to cause adverse health effects. In the present study, we quantified blubber concentrations of 11 phthalates in 16 samples from stranded and/or free-living marine mammals from the Norwegian coast: the killer whale (Orcinus orca), sperm whale (Physeter macrocephalus), long-finned pilot whale (Globicephala melas), white-beaked dolphin (Lagenorhynchus albirostris), harbour porpoise (Phocoena phocoena), and harbour seal (Phoca vitulina). Five compounds were detected across all samples: benzyl butyl phthalate (BBP; in 50 % of samples), bis(2-ethylhexyl) phthalate (DEHP; 33 %), diisononyl phthalate (DiNP; 33 %), diisobutyl phthalate (DiBP; 19 %), and dioctyl phthalate (DOP; 13 %). Overall, the most contaminated individual was the white-beaked dolphin, whilst the lowest concentrations were measured in the killer whale, sperm whale and long-finned pilot whale. We found no phthalates in the neonate killer whale. The present study is important for future monitoring and management of these toxic compounds.
Elsevier
2023
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IOP Publishing
2023
American Meteorological Society
2023
Quality-assured aerosol optical properties (AOP) with high spatiotemporal resolution are vital for the accurate estimation of direct aerosol radiative forcing and solar irradiance under clear skies. In this study, the sky information from an all-sky imager (ASI) is used with machine learning (ML) synergy to estimate aerosol optical depth (AOD) and the Ångström Exponent (AE). The retrieved AODs (AE) revealed good accuracy, with a dispersion error lower than 0.07 (0.15). The retrieved ML AOPs are used to estimate the DNI by applying radiative transfer modeling. The estimated ML DNI calculations revealed adequate accuracy to reproduce reference measurements with relatively low uncertainties.
2023
PM2.5 Retrieval Using Aerosol Optical Depth, Meteorological Variables, and Artificial Intelligence
Particulate matter (PM) is one of the major air pollutants that has adverse impacts on human health. The aim of this study is to present an alternative approach for retrieving fine PM (particles with an aerodynamic diameter less than 2.5 μm, PM2.5) using artificial intelligence. Ground-based instruments, including a hand-held Microtops II sun photometer (for aerosol optical depth), a PurpleAir sensor (for PM2.5), and Rotronic sensors (for temperature and relative humidity), are used for the machine learning algorithm training. The retrieved PM2.5 reveals an adequate performance with an error of 0.08 μg m−3 and a Pearson correlation coefficient of 0.84.
2023
Radiative transfer modeling is used to investigate the effect of aerosol optical properties and water vapor on cloud-free sky radiances at various atmospheric conditions. Simulations are generated by changing the most critical aerosol optical properties, namely aerosol optical depth, Ångström exponent, the single-scattering albedo, the precipitable water, and the solar zenith angle (SZA) in three different spectral ranges: ultraviolet A, visible, and near-infrared.
2023
2023