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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.
2022
2023
Plastic pollution (including microplastics) has been reported in a variety of biotic and abiotic compartments across the circumpolar Arctic. Due to their environmental ubiquity, there is a need to understand not only the fate and transport of physical plastic particles, but also the fate and transport of additive chemicals associated with plastic pollution. Further, there is a fundamental research gap in understanding long-range transport of chemical additives to the Arctic via plastics as well as their behavior under environmentally relevant Arctic conditions. Here, we comment on the state of the science of plastic as carriers of chemical additives to the Arctic, and highlight research priorities going forward. We suggest further research on the transport pathways of chemical additives via plastics from both distant and local sources and laboratory experiments to investigate chemical behavior of plastic additives under Arctic conditions, including leaching, uptake, and bioaccumulation. Ultimately, chemical additives need to be included in strategic monitoring efforts to fully understand the contaminant burden of plastic pollution in Arctic ecosystems.
2023
2022
2017
2009
2000
2019
Norsk institutt for luftforskning (NILU) har gjennomført en studie av bidrag fra utslipp av vedfyring til PM-forurensning i luft i Norge.
Fase 1 av studien omfattet et måleprogram i Oslo vinteren/våren 2004 på to målestasjoner, Kirkeveien og Sofienbergparken, samt bakgrunnsstasjonen Glittre i Hakadal.
I denne fase 2B rapporteres en studie av vedfyringsbidraget i Trondheim, basert på målinger på 2 stasjoner 2005/06. Det ble tidvis målt høye PM-konsentrasjoner i Trondheim denne vinteren, opp mot og over 100 µg/m3 for PM10. På dager med sannsynlig vesentlig bidrag fra vedfyring kunne PM2,5 og PM10 komme over 50 µg/m3. På grunn av problemer med analyse av sporstoffet for vedfyring (en uforklarlig interferens-topp) kunne ikke vedfyringsbidraget bestemmes kvantitativt.
2008
2014
PM10/PM2.5 comparison exercise in Oslo, Norway. Study in 2015-2016 and 2018.
Formålet med sammenligningen var å ekvivalensteste og etablere kalibreringsfaktorer for de vanligste automatiske PM-målere som er i bruk i Norge. For å etablere faktorene utførte Referanselaboratoriet en feltstudie på tre steder i Oslo under sommer- og vinterforhold i periodene september 2015 til juli 2016 og februar til mars 2018. Måleinstrumentene som deltok var Palas Fidas 200, Grimm EDM 180, TEI TEOM 1405 DF, TEI FH 62 I-R, og R&P TEOM 1400AB.
Rapporten beskriver et mulig system for kontinuerlig verifikasjon av kalibreringsfaktorene i de norske målenettene og hvordan analysedata skal kalibreres.
NILU
2021
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
2009
2009