3619 research outputs found

    Total ozone trends at three northern high-latitude stations

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    After the decrease of ozone-depleting substances (ODSs) as a consequence of the Montreal Protocol, it is still challenging to detect a recovery in the total column amount of ozone (total ozone) at northern high latitudes. To assess regional total ozone changes in the “ozone-recovery” period (2000–2020) at northern high latitudes, this study investigates trends from ground-based total ozone measurements at three stations in Norway (Oslo, Andøya, and Ny-Ålesund). For this purpose, we combine measurements from Brewer spectrophotometers, ground-based UV filter radiometers (GUVs), and a SAOZ (Système d'Analyse par Observation Zénithale) instrument. The Brewer measurements have been extended to work under cloudy conditions using the global irradiance (GI) technique, which is also presented in this study. We derive trends from the combined ground-based time series with the multiple linear regression model from the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) project. We evaluate various predictors in the regression model and found that tropopause pressure and lower-stratospheric temperature contribute most to ozone variability at the three stations. We report significantly positive annual trends at Andøya (0.9±0.7 % per decade) and Ny-Ålesund (1.5±0.1 % per decade) and no significant annual trend at Oslo (0.1±0.5 % per decade) but significantly positive trends in autumn at all stations. Finally we found positive but insignificant trends of around 3 % per decade in March at all three stations, which may be an indication of Arctic springtime ozone recovery. Our results contribute to a better understanding of regional total ozone trends at northern high latitudes, which is essential to assess how Arctic ozone responds to changes in ODSs and to climate change.publishedVersio

    Modelling of the deterioration and conservation costs of polychrome painted wood in two Norwegian medieval stone churches

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    EnvCul (https://envcul.nilu.no/) modelling was performed of condition changes of painted wooden panels and related conservation cost in indoor climate and object response scenarios in two Norwegian Medieval stone churches: Kinn (mean relative humidity = 79%) on the humid west coast, and Ringsaker (mean RH = 49%) in the drier eastern part of the country. It was found that, hypothetical, building measures in Kinn, and conservation heating measures in Ringsaker, to approach an indoor RH of about 65% in the two churches, could probably increase conservation intervals with 20–100%, and correspondingly reduce conservation costs between 10% and 50%. This is in reasonable agreement with an available report of observed conservation requirements in differently heated Norwegian churches. A situation between a linear and accelerating development of the deterioration of the painted wood on approaching a new conservation intervention gave the best correspondence to the observed values. The large modelling uncertainty was mainly due to lacking observations of the deterioration development, but also lacking understanding of the complex mechanisms and phases of the environmental dose-deterioration response of painting conservation treatments.publishedVersio

    Health impacts of PM2.5 originating from residential wood combustion in four nordic cities

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    Residential wood combustion (RWC) is one of the largest sources of fine particles (PM2.5) in the Nordic cities. The current study aims to calculate the related health effects in four studied city areas in Sweden, Finland, Norway, and Denmark.publishedVersio

    Bioaccumulation of Per and Polyfluoroalkyl Substances in Antarctic Breeding South Polar Skuas (Catharacta maccormicki) and Their Prey

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    Per and polyfluoroalkyl substances (PFASs) are found in Antarctic wildlife, with high levels in the avian top predator south polar skua (Catharacta maccormicki). As increasing PFAS concentrations were found in the south polar skua during the breeding season in Antarctica, we hypothesised that available prey during the breeding period contributes significantly to the PFAS contamination in skuas. To test this, we compared PFAS in south polar skuas and their main prey from two breeding sites on opposite sides of the Antarctic continent: Antarctic petrel (Thalassoica antarctica) stomach content, eggs, chicks, and adults from Svarthamaren in Dronning Maud Land and Adélie penguin chicks (Pygoscelis adeliae) from Dumont d’Urville in Adélie Land. Of the 22 PFAS analysed, seven were present in the majority of samples, except petrel stomach content [only perfluoroundecanoate (PFUnA) present] and Adélie penguins (only four compounds present), with increasing concentrations from the prey to the skuas. The biomagnification factors (BMFs) were higher at Dumont d’Urville than Svarthamaren. When adjusted to reflect one trophic level difference, the BMFs at Svarthamaren remained the same, whereas the ones at Dumont d’Urville doubled. At both the colonies, the skua PFAS pattern was dominated by perfluorooctanesulfonic acid (PFOS), followed by PFUnA, but differed with the presence of branched PFOS and perfluorotetradecanoate (PFTeA) and lack of perfluorononanoate (PFNA) and perfluorodecanoate (PFDA) at Dumont d’Urville. At Svarthamaren, the pattern in the prey was comparable to the skuas, but with a higher relative contribution of PFTeA in prey. At Dumont d’Urville, the pattern in the prey differed from the skuas, with the domination of PFUnA and the general lack of PFOS in prey. Even though the PFAS levels are low in Antarctic year-round resident prey, the three lines of evidence (pattern, BMF difference, and BMF adjusted to one trophic level) suggest that the Antarctic petrel are the significant source of PFAS in the Svarthamaren skuas, whereas the skuas in Dumont d’Urville have other important sources to PFAS than Adélie penguin, either in the continent or external on the inter-breeding foraging grounds far from Antarctica.publishedVersio

    Siberian Arctic black carbon: gas flaring and wildfire impact

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    As explained in the latest Arctic Monitoring and Assessment Programme (AMAP) report released in early 2021, the Arctic has warmed 3 times more quickly than the planet as a whole, as well as faster than previously thought. The Siberian Arctic is of great interest mainly because observations are sparse or largely lacking. A research aerosol station has been developed on Bely Island (Kara Sea) in western Siberia. Measurements of equivalent black carbon (EBC) concentrations were carried out at the “Island Bely” station continuously from August 2019 to November 2020. The source origin of the measured EBC and the main contributing sources were assessed using atmospheric transport modeling coupled with the most updated emission inventories for anthropogenic and biomass burning sources of BC. The obtained climatology for BC during the period of measurements showed an apparent seasonal variation with the highest concentrations between December and April (60 ± 92 ng m−3) and the lowest between June and September (18 ± 72 ng m−3), typical of the Arctic haze seasonality reported elsewhere. When air masses arrived at the station through the biggest oil and gas extraction regions of Kazakhstan, Volga-Ural, Komi, Nenets and western Siberia, BC contribution from gas flaring dominated over domestic, industrial and traffic sectors, ranging from 47 % to 68 %, with a maximum contribution in January. When air was transported from Europe during the cold season, emissions from transportation were more important. Accordingly, shipping emissions increased due to the touristic cruise activities and the ice retreat in summertime. Biomass burning (BB) played the biggest role between April and October, contributing 81 % at maximum in July. Long-range transport of BB aerosols appeared to induce large variability to the absorption Ångström exponent (AAE) with values > 1.0 (excluding outliers). As regards the continental contribution to surface BC at the Island Bely station, Russian emissions dominated during the whole year, while European and Asian ones contributed up to 20 % in the cold period. Quantification of several pollution episodes showed an increasing trend in surface concentrations and frequency during the cold period as the station is directly in the Siberian gateway of the highest anthropogenic pollution sources to the Russian Arctic.Siberian Arctic black carbon: gas flaring and wildfire impactpublishedVersio

    Evaluation and Global-Scale Observation of Nitrous Oxide from IASI on Metop-A

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    Nitrous oxide (N2O) is a greenhouse gas difficult to estimate by satellite because of its weak spectral signature in the infra-red band and its low variability in the troposphere. Nevertheless, this study presents the evaluation of new tropospheric N2O observations from the Infrared Atmospheric Sounder Interferometer (IASI) on Metop-A using the Toulouse N2O Retrieval Version 2.0 tool. This tool is based on the Radiative Transfer for Tiros Operational Vertical sounder (RTTOV) model version 12.3 coupled to the Levenberg-Marquardt optimal estimation method enabling the simultaneous retrieval of methane, water vapour, temperature profiles together with surface temperature and emissivity within the 1240–1350 cm−1 window. In this study, we focused on the upper troposphere (300 hPa) where the sensitivity of IASI is significant. The IASI N2O data has been evaluated using aircraft N2O observations from the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO) campaigns in 2009, 2010, and 2011 and from the National Oceanic and Atmospheric Administration’s (NOAA) Global Greenhouse Gas Reference Network (GGGRN) in 2011. In addition, we evaluated the IASI N2O using ground-based N2O measurements from 9 stations belonging to the Network for the Detection of Atmospheric Composition Change (NDACC). We found a total random error of ∼2 ppbv (0.6%) for one single retrieval at 300 hPa. Under favorable conditions, this error is also found in the vertical level pressure range 300–500 hPa. It decreases rapidly to ∼0.4 ppbv (0.1%) when we average on a 1° × 1° box. In addition, independent observations allows the estimation of bias with the IASI TN2OR v2.0 N2O. The bias between IASI and aircraft N2O data at 300 hPa is ∼1.0 ppbv (∼0.3%). We found an estimated random error of ∼2.3 ppbv (∼0.75%). This study also shows relatively high correlations between IASI data and aircraft in situ profiles but more varying correlations over the year 2011 depending on the location between IASI and NDACC remote sensing data. Finally, we present daily, monthly, and seasonal IASI N2O horizontal distributions in the upper troposphere as well as cross sections for different seasons that exhibit maxima in the Tropical band especially over Africa and South America.publishedVersio

    European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

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    Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models.publishedVersio

    Inferring surface energy fluxes using drone data assimilation in large eddy simulations

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    Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.publishedVersio

    An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry

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    Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS

    Plastic ingestion and associated additives in Faroe Islands chicks of the Northern Fulmar Fulmarus glacialis

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    Northern Fulmars (Fulmarus glacialis) are a pelagic seabird species distributed at northern and polar latitudes. They are often used as an indicator of plastic pollution in the North Sea region, but data are lacking from higher latitudes, especially when it comes to chicks. Here, we investigated amounts of ingested plastic and their characteristics in fulmar chicks from the Faroe Islands. Plastic particles (≥1 ​mm) in chicks of two age classes were searched using a digestion method with KOH. In addition, to evaluate if additive tissue burden reflects plastic ingestion, we measured liver tissue concentrations of two pollutant classes associated with plastic materials: polybrominated diphenyl ethers (PBDEs) and several dechloranes, using gas chromatography with high-resolution mass spectrometry. The most common shape was hard fragment (81%) and the most common polymer was polyethylene (73%). Plastic contamination did not differ between either age class, and we found no correlation between neither the amount and mass of plastic particles and the concentration of additives. After comparison with previous studies on adult fulmars, we do not recommend using chicks for biomonitoring adults because chicks seem to ingest more plastics than adults.publishedVersio

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