Skip to content
  • Submit

  • Category

  • Sort by

  • Per page

Found 9849 publications. Showing page 336 of 394:

Publication  
Year  
Category

Biological activity of plant extract isolated from Papaver rhoeas on human lymfoblastoid cell line.

Hasplova, K.; Hudecova, A.; Miadokova, E.; Magdolenova, Z.; Galova, E.; Vaculcikova, L.; Gregan, F.; Dusinska, M.

2011

Bioindication and modelling of atmospheric deposition in forests enable exposure and effect monitoring at high spatial density across scales.

Schröder, W.; Nickel, S.; Schönrock, S.; Schmalfuß, R.; Wosniok, W.; Meyer, M.; Harmens, H.; Frontasyeva, M. V.; Alber, R.; Aleksiayenak, J.; Barandovski, L.; Blum, O.; Carballeira, A.; Dam, M.; Danielsson, H.; De Temmermann, L.; Dunaev, A. M.; Godzik, B.; Hoydal, K.; Jeran, Z.; Karlsson, G. P.; Lazo, P.; Leblond, S.; Lindroos, J.; Liiv, S.; Magnússon, S. H.; Mankovska, B.; Núñez-Olivera, E.; Piispanen, J.; Poikolainen, J.; Popescu, I. V.; Qarri, F.; Santamaria, J. M.; Skudnik, M.; Špiric, Z.; Stafilov, T.; Steinnes, E.; Stihi, C.; Suchara, I.; Thöni, L.; Uggerud, H. T.; Zechmeister, H. G.

2017

Bioakkumulering, økotoksikologi og biomarkørresponser i marine næringskjeder. NILU F

Nygård, T.; Berge, J.A.; Berger, U.; Brevik, E.; Herzke, D.; Melbøe, A.; Jenssen, B.M.; Kallenborn, R.; Røv, N.; Schlabach, M.; Vetter, W.; Aarnes, J.B.

2005

Bioaccumulation of synthetic musks in different aquatic species. Poster presentation. NILU F

Gatermann, R.; Rimkus, G.; Hecker, M.; Biselli, S.; Hühnerfuss, H.

1999

Bioaccumulation of polybrominated diphenyl ethers in fish from the Norwegian lake Mjøsa.

Mariussen, E.; Fjeld, E.; Strand-Andersen, M.; Hjerpset, M.; Schlabach, M.

2003

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

Alfaro Garcia, Laura Andrea; Descamps, Sebastien; Herzke, Dorte; Chastel, Olivier; Carravieri, Alice; Cherel, Yves; Labadie, Pierre; Budzinski, Helene; Munoz, Gabriel; Bustamante, Paco; Polder, Anuschka; Gabrielsen, Geir Wing; Bustnes, Jan Ove; Borgå, Katrine

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.

Frontiers Media S.A.

2022

Bioaccumulation of nickel by E. sativa and role of plant growth promoting rhizobacteria (PGPRs) under nickel stress.

Kamran, M.A.; Eqani, S.A.M.A.S.; Bibi, S.; Xu, R.-k.; Amna, Monis, M.F.H.; Katsoyiannis, A.; Bokhari, H.; Chaudhary, H.J.

2016

Bioaccumulation of brominated flame retardants. The Handbook of Environmental Chemistry, vol. 16

Dominguez, A.A.; Law, R.J.; Herzke, D.; de Boer, J.

2011

Big data processing and apps for citizens' observatories - the CITI-SENSE approach.

Berre, A.J.; Fredriksen, M.; Rombouts, R.; Liu, H.-Y.; Ferry, N.

2015

Bias determination and precision validation of ozone profiles from MIPAS-Envisat retrieved with the IMK-IAA processor.

Steck, T.; von Clarmann, T.; Fischer, H.; Funke, B.; Glatthor, N.; Grabowski, U.; Höpfner, M.; Kellmann, S.; Kiefer, M.; Linden, A.; Milz, M.; Stiller, G.P.; Wang, D.Y.; Allaart, M.; Blumenstock, Th.; von der Gathen, P.; Hansen, G.; Hase, F.; Hochschild, G.; Kopp, G.; Kyrö, E.; Oelhaf, H.; Raffalski, U.; Redondas Marrero, A.; Remsberg, E.; Russell III, J.; Stebel, K.; Steinbrecht, W.; Wetzel, G.; Yela, M.; Zhang, G.

2007

BHT in cosmetic products. NILU OR

Schlabach, M.; Dye, C.; Gundersen, H.; Enge, E.-K.; Mariussen, E.

2005

Bhas 42 cell transformation assay for genotoxic and non-genotoxic carcinogens. Methods in Pharmacology and Toxicology

Sasaki, K.; Huk, A.; El Yamani, N.; Tanaka, N.; Dusinska, M.

2014

BFR-governmental testing programme.

Kemmlein, S.; Herzke, D.; Law, R.L.

2003

Beyond target chemicals: updating the NORMAN prioritisation scheme to support the EU chemicals strategy with semi-quantitative suspect/non-target screening data

Dulio, Valeria; Alygizakis, Nikiforos; Ng, Kelsey; Schymanski, Emma L.; Andres, Sandrine; Vorkamp, Katrin; Hollender, Juliane; Finckh, Saskia; Aalizadeh, Reza; Ahrens, Lutz; Bouhoulle, Elodie; Čirka, Ľuboš; Derksen, Anja; Deviller, Genevieve; Duffek, Anja; Esperanza, Mar; Fischer, Stellan; Fu, Qiuguo; Gago-Ferrero, Pablo; Haglund, Peter; Junghans, Marion; Kools, Stefan A. E.; Koschorreck, Jan; Lopez, Benjamin; de Alda, Miren Lopez; Mascolo, Giuseppe; Miège, Cécile; Oste, Leonard; O'Toole, Simon; Rostkowski, Pawel; Schulze, Tobias; Sims, Kerry; Six, Laetitia; Slobodnik, Jaroslav; Staub, Pierre-François; Stroomberg, Gerard; Thomaidis, Nikolaos S.; Togola, Anne; Tomasi, Giorgio; von der Ohe, Peter C.

Background

Prioritisation of chemical pollutants is a major challenge for environmental managers and decision-makers alike, which is essential to help focus the limited resources available for monitoring and mitigation actions on the most relevant chemicals. This study extends the original NORMAN prioritisation scheme beyond target chemicals, presenting the integration of semi-quantitative data from retrospective suspect screening and expansion of existing exposure and risk indicators. The scheme utilises data retrieved automatically from the NORMAN Database System (NDS), including candidate substances for prioritisation, target and suspect screening data, ecotoxicological effect data, physico-chemical data and other properties. Two complementary workflows using target and suspect screening monitoring data are applied to first group the substances into six action categories and then rank the substances using exposure, hazard and risk indicators. The results from the ‘target’ and ‘suspect screening’ workflows can then be combined as multiple lines of evidence to support decision-making on regulatory and research actions.

Results

As a proof-of-concept, the new scheme was applied to a combined dataset of target and suspect screening data. To this end, > 65,000 substances on the NDS, of which 2579 substances supported by target wastewater monitoring data, were retrospectively screened in 84 effluent wastewater samples, totalling > 11 million data points. The final prioritisation results identified 677 substances as high priority for further actions, 7455 as medium priority and 326 with potentially lower priority for actions. Among the remaining substances, ca. 37,000 substances should be considered of medium priority with uncertainty, while it was not possible to conclude for 19,000 substances due to insufficient information from target monitoring and uncertainty in the identification from suspect screening. A high degree of agreement was observed between the categories assigned via target analysis and suspect screening-based prioritisation. Suspect screening was a valuable complementary approach to target analysis, helping to prioritise thousands of substances that are insufficiently investigated in current monitoring programmes.

Conclusions

This updated prioritisation workflow responds to the increasing use of suspect screening techniques. It can be adapted to different environmental compartments and can support regulatory obligations, including the identification of specific pollutants in river basins and the marine environments, as well as the confirmation of environmental occurrence levels predicted by modelling tools.

Springer

2024

Between man and technology: adressing IAQ in Norwegian schools

Bartonova, Alena; Fredriksen, Mirjam; Høiskar, Britt Ann Kåstad

2023

Publication
Year
Category