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2021
DNA damage and repair activity are often assessed in blood samples from humans in different types of molecular epidemiology studies. However, it is not always feasible to analyse the s#38les on the day of collection without any type of storage. For instance, certain studies use repeated sampling of cells from the same subject or samples from different subjects collected at different time-points, and it is desirable to analyse all these samples in the same comet assay experiment. In addition, flawless comet assay analyses on frozen samples opens up for the possibility of using this technique on biobank material. In this article we discuss the use of cryopreserved peripheral blood mononuclear cells (PBMCs), buffy coat (BC) and whole blood (WB) for analysis of DNA damage and repair using the comet assay. The published literature and the authors’ experiences indicate that various types of blood samples can be cryopreserved with only minor effect on the basal level of DNA damage. There is evidence to suggest that WB and PBMCs can be cryopreserved for several years without much effect on the level of DNA damage. However, care should be taken when cryopreserving WB and BCs. It is possible to use either fresh or frozen samples of blood cells, but results from fresh and frozen cells should not be used in the same dataset. The article outlines detailed protocols for the cryopreservation of PBMCs, BCs and WB samples.
Oxford University Press
2021
The long-term time trends of atmospheric pollutants at eight Arctic monitoring stations are reported. The work was conducted under the Arctic Monitoring and Assessment Programme (AMAP) of the Arctic Council. The monitoring stations were: Alert, Canada; Zeppelin, Svalbard; Stórhöfði, Iceland; Pallas, Finland; Andøya, Norway; Villum Research Station, Greenland; Tiksi and Amderma, Russia. Persistent organic pollutants (POPs) such as α- and γ-hexachlorocyclohexane (HCH), polychlorinated biphenyls (PCBs), α-endosulfan, chlordane, dichlorodiphenyltrichloroethane (DDT) and polybrominated diphenyl ethers (PBDEs) showed declining trends in air at all stations. However, hexachlorobenzene (HCB), one of the initial twelve POPs listed in the Stockholm Convention in 2004, showed either increasing or non-changing trends at the stations. Many POPs demonstrated seasonality but the patterns were not consistent among the chemicals and stations. Some chemicals showed winter minimum and summer maximum concentrations at one station but not another, and vice versa. The ratios of chlordane isomers and DDT species showed that they were aged residues. Time trends of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) were showing decreasing concentrations at Alert, Zeppelin and Andøya. The Chemicals of Emerging Arctic Concern (CEAC) were either showing stable or increasing trends. These include methoxychlor, perfluorohexane sulfonic acid (PFHxS), 6:2 fluorotelomer alcohol, and C9-C11 perfluorocarboxylic acids (PFCAs). We have demonstrated the importance of monitoring CEAC before they are being regulated because model calculations to predict their transport mechanisms and fate cannot be made due to the lack of emission inventories. We should maintain long-term monitoring programmes with consistent data quality in order to evaluate the effectiveness of chemical control efforts taken by countries worldwide.
Elsevier
2021
American Meteorological Society (AMS)
2021
Implementing Citizen Science in Primary Schools: Engaging Young Children in Monitoring Air Pollution
Most European cities have air pollution levels that exceed the threshold for human health protection. Children are sensitive to air pollution and thus it is important to ensure they are not exposed to high concentrations of air pollutants. In order to make a positive change toward cleaner air, a joint effort is needed, involving all civil society actors. Schools and local communities have a decisive role, and can, for example, become engaged in citizen science initiatives and knowledge coproduction. In 2019, with the aim of raising awareness for air quality, NILU developed a citizen science toolbox to engage primary schools in monitoring air quality using a simple and affordable measuring method based on paper and petroleum jelly. This is a very visual method, where the students can clearly see differences from polluted and non-polluted places by looking at “how dirty” is the paper. In addition to the qualitative analysis, we have developed an air meter scale making possible for the students to obtain an indicative measurement of the air pollution level. The comparison between the paper and petroleum jelly method against reference PM10 data collected at two official air quality stations showed a good agreement. The method is a strong candidate for dust monitoring in citizen science projects, making participation possible and empowering people with simple tools at hand. The toolbox is targeted at primary schools and children aged 6–12 years, although it can easily be adapted to other age groups. The main objective of the toolbox is to involve young children who are usually not targeted in air quality citizen science activities, to develop research skills and critical thinking, as well as increase their awareness about the air they breathe. The toolbox is designed to engage students in hands-on activities, that challenge them to create hypotheses, design scientific experiments, draw conclusions and find creative solutions to the air pollution problem. The toolbox includes all the necessary material for the teachers, including guidance, background information and templates facilitating the incorporation in the school curricula. The toolbox was launched as part of the Oslo European Green Capital in March 2019 and was later included as part of the European Clean Air Day initiative coordinated by the European Citizen Science Association (ECSA) working group on air quality. A total of 30 schools and 60 4th grade classes (aged 8–9 years) participated in the Oslo campaign. The citizen science approach employed in the schools, combined the four key elements that promote knowledge integration: elicit ideas, add new ideas, distinguish among ideas and reflect and sort out ideas. Although the main goal of the study was to provide simple but robust tools for engaging young children in air quality monitoring, we also carried out ex-ante and ex-post evaluations in 12 of the participating classes using a 10-question multiple choice test to have an indication of the contribution of the activity to knowledge integration. The results show that there is an increase in the number of correct answers, as well as a reduction in the misconceptions after conducting the activity. These results indicate that applying a citizen science approach improved science instruction and helped knowledge integration by including students' views and taking advantage of the diverse ideas students generated. Citizen science gives learners an insight into the ways that scientists generate solutions for societal problems. But more important, citizen science provides a way to differ from the classic view of the learner as an absorber of information, by considering the social context of instruction and making the topic personally relevant.
Frontiers Media S.A.
2021
Instead of a flag valid/non-valid usually proposed in the quality control (QC) processes of air quality (AQ), we proposed a method that predicts the p-value of each observation as a value between 0 and 1. We based our error predictions on three approaches: the one proposed by the Working Group on Guidance for the Demonstration of Equivalence (European Commission (2010)), the one proposed by Wager (Journal of Machine Learning Research, 15, 1625–1651 (2014)) and the one proposed by Lu (Journal of Machine Learning Research, 22, 1–41 (2021)). Total Error framework enables to differentiate the different errors: input, output, structural modeling and remnant. We thus theoretically described a one-site AQ prediction based on a multi-site network using Random Forest for regression in a Total Error framework. We demonstrated the methodology with a dataset of hourly nitrogen dioxide measured by a network of monitoring stations located in Oslo, Norway and implemented the error predictions for the three approaches. The results indicate that a simple one-site AQ prediction based on a multi-site network using Random Forest for regression provides moderate metrics for fixed stations. According to the diagnostic based on predictive qq-plot and among the three approaches used in this study, the approach proposed by Lu provides better error predictions. Furthermore, ensuring a high precision of the error prediction requires efforts on getting accurate input, output and prediction model and limiting our lack of knowledge about the “true” AQ phenomena. We put effort in quantifying each type of error involved in the error prediction to assess the error prediction model and further improving it in terms of performance and precision.
MDPI
2021
2021
Low concentrations of 106Ru were detected across Europe at the turn of September and October 2017. The origin of 106Ru has still not been confirmed; however, current studies agree that the release occurred probably near Mayak in the southern Urals. The source reconstructions are mostly based on an analysis of concentration measurements coupled with an atmospheric transport model. Since reasonable temporal resolution of concentration measurements is crucial for proper source term reconstruction, the standard 1-week sampling interval could be limiting. In this paper, we present an investigation of the usability of the newly developed AMARA (Autonomous Monitor of Atmospheric Radioactive Aerosol) and CEGAM (carousel gamma spectrometry) real-time monitoring systems, which are based on the gamma-ray counting of aerosol filters and allow for determining the moment when 106Ru arrived at the monitoring site within approx. 1 h and detecting activity concentrations as low as several mBq m−3 in 4 h intervals. These high-resolution data were used for inverse modeling of the 106Ru release. We perform backward runs of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) atmospheric transport model driven with meteorological data from the Global Forecast System (GFS), and we construct a source–receptor sensitivity (SRS) matrix for each grid cell of our domain. Then, we use our least squares with adaptive prior covariance (LS-APC) method to estimate possible locations of the release and the source term of the release. With Czech monitoring data, the use of concentration measurements from the standard regime and from the real-time regime is compared, and a better source reconstruction for the real-time data is demonstrated in the sense of the location of the source and also the temporal resolution of the source. The estimated release location, Mayak, and the total estimated source term, 237±107 TBq, are in agreement with previous studies. Finally, the results based on the Czech monitoring data are validated with the IAEA-reported (International Atomic Energy Agency) dataset with a much better spatial resolution, and the agreement between the IAEA dataset and our reconstruction is demonstrated. In addition, we validated our findings also using the FLEXPART (FLEXible PARTicle dispersion) model coupled with meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF).
2021
This study investigated concentrations of phthalates (diesters of phthalic acids) in blubber/adipose tissue of blue whales (Balaenoptera musculus), fin whales (Balaenoptera physalus), bowhead whales (Balaena mysticetus) and polar bears (Ursus maritimus) sampled in the Svalbard Archipelago (extending westward in the case of bowhead whales). Additionally, total concentrations (free and conjugated forms) of eight phthalate monoester metabolites were analysed in plasma of polar bears. Bis(2-ethylhexyl) phthalate (DEHP) was the only phthalate quantified among the 12 phthalates investigated. This compound was present in 6/7 fin whale samples, 4/7 blue whale samples, 2/5 bowhead whale samples and 1/12 polar bear samples. DEHP concentrations ranged from <20–398 ng/g wet weight. Phthalate metabolites, mono-n-butyl phthalate and monoisobutyl phthalate, were found in low concentrations (<1.2 ng/mL) in some of the polar bear samples. In vitro reporter gene assays were used to assess transcriptional activity of fin whale peroxisome proliferator-activated receptor gamma (PPARG), glucocorticoid receptor (GR) and the thyroid hormone receptor beta (THRB) by DEHP and diisononyl phthalate (DiNP). Due to the high degree of similarity of the ligand binding domain in the THRB and PPARG among whales, polar bears and humans, the transactivation results also apply for these species. DEHP showed both agonistic and antagonistic effects towards whale THRB at considerably higher concentrations than measured in the study animals; DiNP was a weak agonist of whale THRB. No significant agonistic or antagonistic effects were detected for DEHP or DiNP for whale PPARG, whereas DEHP and DiNP decreased basal luciferase activity mediated by whale GR at several test concentrations. In conclusion, DEHP was detected in the blubber of marine mammals from the Norwegian Arctic and it appears to have potential to modulate the transcriptional activity of whale THRB, but current DEHP concentrations do not modulate the function of the studied nuclear receptors in adipose tissue of blue whales, fin whales, bowhead whales or polar bears sampled from the Norwegian Arctic.
Elsevier
2021
This paper presents the validation results of Aerosol Optical Depth (AOD) retrieved from the Spinning Enhanced Visible Infrared Radiometer (SEVIRI) data using the near-real-time algorithm further developed in the frame of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project. The SEVIRI AOD was compared against multiple data sources: six stations of the Aerosol Robotic Network (AERONET) in Romania and Poland, three stations of the Aerosol Research Network in Poland (Poland–AOD) and Moderate Resolution Imaging Spectroradiometer (MODIS) data overlapping Romania, Czech Republic and Poland. The correlation values between a four-month dataset (June–September 2014) from SEVIRI and the closest temporally available data for both ground-based and satellite products were identified. The comparison of the SEVIRI AOD with the AERONET AOD observations generally shows a good correlation (r = 0.48–0.83). The mean bias is 0.10–0.14 and the root mean square error RMSE is between 0.11 and 0.15 for all six stations cases. For the comparison with Poland–AOD correlation values are 0.55 to 0.71. The mean bias is 0.04–0.13 and RMSE is between 0.10 and 0.14. As for the intercomparison to MODIS AOD, correlations values were generally lower (r = 0.33–0.39). Biases of −0.06 to 0.24 and RMSE of 0.04 to 0.28 were in good agreement with the ground–stations retrievals. The validation of SEVIRI AOD with AERONET results in the best correlations followed by the Poland–AOD network and MODIS retrievals. The average uncertainty estimates are evaluated resulting in most of the AOD values falling above the expected error range. A revised uncertainty estimate is proposed by including the observed bias form the AERONET validation efforts.
MDPI
2021