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Monitoring Soil Moisture Drought over Northern High Latitudes from Space
Mapping drought from space using, e.g., surface soil moisture (SSM), has become viable in the last decade. However, state of the art SSM retrieval products suffer from very poor coverage over northern latitudes. In this study, we propose an innovative drought indicator with a wider spatial and temporal coverage than that obtained from satellite SSM retrievals. We evaluate passive microwave brightness temperature observations from the Soil Moisture and Ocean Salinity (SMOS) satellite as a surrogate drought metric, and introduce a Standardized Brightness Temperature Index (STBI). We compute the STBI by fitting a Gaussian distribution using monthly brightness temperature data from SMOS; the normal assumption is tested using the Shapior-Wilk test. Our results indicate that the assumption of normally distributed brightness temperature data is valid at the 0.05 significance level. The STBI is validated against drought indices from a land surface data assimilation system (LDAS-Monde), two satellite derived SSM indices, one from SMOS and one from the ESA CCI soil moisture project and a standardized precipitation index based on in situ data from the European Climate Assessment & Dataset (ECA&D) project. When comparing the temporal dynamics of the STBI to the LDAS-Monde drought index we find that it has equal correlation skill to that of the ESA CCI soil moisture product ( 0.71 ). However, in addition the STBI provides improved spatial coverage because no masking has been applied over regions with dense boreal forest. Finally, we evaluate the STBI in a case study of the 2018 Nordic drought. The STBI is found to provide improved spatial and temporal coverage when compared to the drought index created from satellite derived SSM over the Nordic region. Our results indicate that when compared to drought indices from precipitation data and a land data assimilation system, the STBI is qualitatively able to capture the 2018 drought onset, severity and spatial extent. We did see that the STBI was unable to detect the 2018 drought recovery for some areas in the Nordic countries. This false drought detection is likely linked to the recovery of vegetation after the drought, which causes an increase in the passive microwave brightness temperature, hence the STBI shows a dry anomaly instead of normal conditions, as seen for the other drought indices. We argue that the STBI could provide additional information for drought monitoring in regions where the SSM retrieval problem is not well defined. However, it then needs to be accompanied by a vegetation index to account for the recovery of the vegetation which could cause false drought detection.
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Monitoring of the atmospheric ozone layer and natural ultraviolet radiation. Annual Report 2018.
This report summarizes the results from the Norwegian monitoring programme on stratospheric ozone and UV radiation
measurements. The ozone layer has been measured at three locations since 1979: in Oslo, Tromsø/Andøya and Ny-Ålesund.
The UV measurements started in 1995. The results show that there was a significant decrease in stratospheric ozone above
Norway between 1979 and 1997. After that the ozone layer stabilized at a level ~2% below pre-1980 level. 2018 was
characterized by low summer ozone values in Oslo and a record high annual integrated UV-dose.
NILU
2019
Public Health Institute of Belgrade
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In the present study, concentrations of legacy and emerging contaminants were determined in three non-destructive matrices (plasma, preen oil and body feathers) of northern goshawk (Accipiter gentilis) nestlings. Persistent organic pollutants (POPs), including polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polybrominated diphenyl ethers (PBDEs), together with emerging pollutants, including per- and polyfluorinated alkyl substances (PFASs), novel brominated flame retardants (NBFRs), phosphorus flame retardants (PFRs) and Dechlorane Plus isomers (DPs) were targeted. Plasma, preen oil and feather samples were collected from 61 goshawk nestlings in Norway (Trøndelag and Troms) in 2015 and 2016, and pollutant concentrations were compared between the three matrices. In plasma, PFASs were detected in the highest concentrations, ranging between 1.37 and 36.0 ng/mL, which suggests that the nestlings were recently and continuously exposed to these emerging contaminants, likely through dietary input. In preen oil, OCPs (169–3560 ng/g) showed the highest concentrations among the investigated compounds, consistent with their high lipophilicity. PFRs (2.60–314 ng/g) were the dominant compounds in feathers and are thought to originate mainly from external deposition, as they were not detected in the other two matrices. NBFRs and DPs were generally not detected in the nestlings, suggesting low presence of these emerging contaminants in their environment and/or low absorption. Strong and significant correlations between matrices were found for all POPs (rs = 0.46–0.95, p < 0.001), except for hexachlorobenzene (HCB, rs = 0.20, p = 0.13). Correlations for PFASs were less conclusive: linear perfluorooctane sulfonate (PFOS), perfluoroundecanoate (PFUnA), perfluorododecanoate (PFDoA) and perfluorotetradecanoate (PFTeA) showed strong and significant correlations between plasma and feathers (rs = 0.42–0.72, p < 0.02), however no correlation was found for perfluorohexane sulfonate (PFHxS), perfluorononanoate (PFNA) and perfluorotridecanoate (PFTriA) (rs = 0.05–0.33, p = 0.09–0.85). A lack of consistency between the PFAS compounds (contrary to POPs), and between studies, prevents concluding on the suitability of the investigated matrices for PFAS biomonitoring.
2019
Untargeted analysis of a composite house dust sample has been performed as part of a collaborative effort to evaluate the progress in the field of suspect and nontarget screening and build an extensive database of organic indoor environment contaminants. Twenty-one participants reported results that were curated by the organizers of the collaborative trial. In total, nearly 2350 compounds were identified (18%) or tentatively identified (25% at confidence level 2 and 58% at confidence level 3), making the collaborative trial a success. However, a relatively small share (37%) of all compounds were reported by more than one participant, which shows that there is plenty of room for improvement in the field of suspect and nontarget screening. An even a smaller share (5%) of the total number of compounds were detected using both liquid chromatography–mass spectrometry (LC-MS) and gas chromatography–mass spectrometry (GC-MS). Thus, the two MS techniques are highly complementary. Most of the compounds were detected using LC with electrospray ionization (ESI) MS and comprehensive 2D GC (GC×GC) with atmospheric pressure chemical ionization (APCI) and electron ionization (EI), respectively. Collectively, the three techniques accounted for more than 75% of the reported compounds. Glycols, pharmaceuticals, pesticides, and various biogenic compounds dominated among the compounds reported by LC-MS participants, while hydrocarbons, hydrocarbon derivatives, and chlorinated paraffins and chlorinated biphenyls were primarily reported by GC-MS participants. Plastics additives, flavor and fragrances, and personal care products were reported by both LC-MS and GC-MS participants. It was concluded that the use of multiple analytical techniques was required for a comprehensive characterization of house dust contaminants. Further, several recommendations are given for improved suspect and nontarget screening of house dust and other indoor environment samples, including the use of open-source data processing tools. One of the tools allowed provisional identification of almost 500 compounds that had not been reported by participants.
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