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Found 9941 publications. Showing page 283 of 398:

Publication  
Year  
Category

Effect of nanosilver and TiO2 on MAPK activation: role of ROS and implicaton of DNA damage.

Rinna, A.; Magdolenova, Z.; Hudecová, A.; Hasplová, K.; Fjellsbø, L.; Dusinska, M.

2010

Effect of nanosilver and TiO2 on MAPK activation: role of ROS and implicaton of DNA damage. NILU PP

Rinna, A.; Magdolenova, Z.; Hudecová, A.; Hasplová, K.; Fjellsbø, L.; Dusinska, M.

2010

Effect of Long-Range Transported Fire Aerosols on Cloud Condensation Nuclei Concentrations and Cloud Properties at High Latitudes

Kommula, Snehitha M.; Buchholz, Angela; Gramlich, Yvette; Mielonen, Tero; Hao, L.; Pullinen, Iida; Vettikkat, Lejish; Ylisirniö, A.; Joutsensaari, J.; Schobesberger, Siegfried; Tiitta, P; Leskinen, Ari; Heslin-Rees, Dominic; Haslett, S. L.; Siegel, Karolina; Lunder, Chris Rene; Zieger, Paul; Krejci, Radovan; Romakkaniemi, Sami; Mohr, C.; Virtanen, Annele

Active vegetation fires in south-eastern (SE) Europe resulted in a notable increase in the number concentration of aerosols and cloud condensation nuclei (CCN) particles at two high latitude locations—the SMEAR IV station in Kuopio, Finland, and the Zeppelin Observatory in Svalbard, high Arctic. During the fire episode aerosol hygroscopicity κ slightly increased at SMEAR IV and at the Zeppelin Observatory κ decreased. Despite increased κ in high CCN conditions at SMEAR IV, the aerosol activation diameter increased due to the decreased supersaturation with an increase in aerosol loading. In addition, at SMEAR IV during the fire episode, in situ measured cloud droplet number concentration (CDNC) increased by a factor of ∼7 as compared to non-fire periods which was in good agreement with the satellite observations (MODIS, Terra). Results from this study show the importance of SE European fires for cloud properties and radiative forcing in high latitudes.

American Geophysical Union (AGU)

2024

Effect of filter type in ventilation systems on NO2 concentrations in classrooms

Yang, Aileen; Nikolaisen, Kristian Fredrik; Holøs, Sverre Bjørn; Thunshelle, Kari; Dauge, Franck Rene; Mysen, Mads

2018

Effect of filter type in ventilation systems on NO2 concentrations in classrooms

Yang, Aileen; Nikolaisen, Kristian Fredrik; Holøs, Sverre Bjørn; Thunshelle, Kari; Dauge, Franck Rene; Mysen, Mads

2019

Effect of demand-controlled ventilation strategies on indoor air pollutants in a classroom: A Norwegian case study

Yang, Aileen; Andersen, Kamilla Heimar; Hak, Claudia; Mikoviny, Tomas; Wisthaler, Armin; Holøs, Sverre Bjørn

IOP Publishing

2023

Effect of climate change on flux of N and C: air-land-freshwater-marine links: synthesis.

Stuanes, A.O.; de Wit, H.; Hole, L.R.; Kaste, Ø.; Mulder, J.; Riise, G.; Wright, R.F.

2008

EEA-33 Industrial Emissions Country Profiles. Methodology report. Updated July 2020.

Weydahl, Torleif; Young, Katrina; Hampshire, Kathryn; Goodwin, Justin; Granger, Marthe; Zeiger, Bastian

The industrial emissions country profiles summarise key data related to industry: its relevance with respect to economic contributions, energy and water consumption, as well as air and water emissions and waste generation. The country profiles are developed for the EEA-33 countries which includes the 28 EU Member States together with Iceland, Lichtenstein, Norway, Switzerland and Turkey.

The present revision (v. 3.0) of this report includes data available at date of release. This year, a new reporting, the so-called EU-Registry and thematic data reporting, is introduced in order to gather the former E-PRTR, LCP and IED reportings and finally replace them. The 2018 data are not yet readily available. Nevertheless, more quality checks have been performed on the latest E-PRTR database in order to have the cleanest final E-PRTR dataset possible. Hence, the industrial emissions country profiles are enriched with the most up-to-date data sources while still only covering the years up to 2017.

This report describes the underlying methodology to the industrial emissions country profiles that are presented as a Tableau story on the EEA webpages ([1]).

The scope of industry in this respect includes in short all industrial activities reported under the European Pollutant Release and Transfer Register (E-PRTR) excluding agriculture (activity code 7.(a) and 7.(b)). The data sources include Eurostat, the E-PRTR, greenhouse gas (GHG) emissions reported under the Monitoring Mechanism Regulation (MMR) and air pollutant emission inventories reported under the Convention on Long-range Transboundary Air Pollution (CLRTAP), each of which have their own data categories. A recently developed EEA-mapping which align these different categories is used ([2]). The data sources and industry scope is presented in full detail in the Annexes following this report.

The water and air pollutants including greenhouse gases are selected based on criteria related to their relative impact. Emissions of heavy metals to air and water have been combined by weighted averages using both eco toxicology and human toxicology characterisation factors ([3]). The amounts of hazardous and non-hazardous waste reported under Eurostat is presented, but excluding the major mineral waste that dominates the mining and construction sectors.

The data quality is evaluated and gap filling of Eurostat data is performed when needed. A method for E-PRTR outlier handling is proposed and applied where appropriate.

The significance of industry, given by gross value added (GVA), energy consumption and water use, as well as generation of waste are presented in the Tableau story as a sector percentage of EEA-33 gross total as well as percentage of country total. The trend in air and water pollution is presented as totals per pollutants relative to the latest year (2017). For the latest year the emissions are also given as percentage per sector relative to country total. The details on how the presented data is processed and aggregated is described in Annex 2.

The report is to a large extent based on previous methodology reports for “Industrial pollution country profiles”, but is also further developed to reflect feedback received through Eionet review and general requests from EEA and the European Commission.

ETC/ATNI

2020

EEA air quality web dissemination solution - recommendations for further development. ETC/ACC Technical Paper 2006/9

Endregard, G.; Karatzas, K.; Carlsen, K.H.; Fløisand, I.; Skaanes, B.I.; Larssen, S.

2007

EE-avfall under lupen

Abbasi, Golnoush; Uggerud, Hilde Thelle (interview subjects); Eide, Lise H. (journalist)

2021

EDUCE - European database for ultraviolet radiation climatology and evaluation. Abstract. NILU F

Seckmeyer, G.; Kjeldstad, B.; Putz, E.; Taalas, P.; Gardiner, B.; Bais, A.; Slaper, H.; Kylling, A.; Webb, A.; Weihs, P.; Engelsen, O.; Blumthaler, M.; Lenoble, J.; Janouch, M.; Krzyscin, J.; Eerme, K.; Litynska, Z.; Gillotay, D.; di Sarra, A.G.; Feister, U.; Steinmetz, M.; Gröbner, J.; Siani, A.-M.; Henriques, D.; van Weele, M.; Brogniez, C.; Koskel, T.

2003

Editorial: Environmental impacts and risks of car tire and styrene-butadiene rubber: microplastic pollution and contaminant transport

Halsband, Claudia; Sørensen, Lisbet; Khan, Farhan R.; Herzke, Dorte; Wagner, Stephan

Frontiers Media S.A.

2023

Editorial for the Special Issue From Nanoinformatics to Nanomaterials Risk Assessment and Governance

Lynch, Iseult; Afantitis, Antreas; Greco, Dario; Dusinska, Maria; Banares, Miguel A.; Melagraki, Georgia

MDPI

2021

Editoral: The COST 723 Action.

Lahoz, W.A.; Geer, A.J.; Orsolini, Y.J.

2007

Ecosystem specific accumulation of organohalogenated compounds: A comparison between adjacent freshwater and terrestrial avian predators

Bustnes, Jan Ove; Bårdsen, Bård-Jørgen; Herzke, Dorte; Bangjord, Georg; Bourgeon, Sophie; Fritsch, Clémentine; Eulaers, Igor

Insight into processes determining the exposure of organohalogenated contaminants (OHCs) in wildlife might be gained from comparing predators in different ecosystems. This study compared two avian predator species with similar food chain lengths: the goldeneye duck (Bucephala clangula) and the tawny owl (Strix aluco) breeding in adjacent freshwater- and terrestrial ecosystems in central Norway. We measured lipophilic organochlorines (OCs) and protein-bound perfluorinated substances (PFASs) in eggs of the two species over 21 years (1999–2019). Across years, the proportional distribution of OCs (∼90% of the ΣOHC load) relative to PFASs (∼10%) was similar in the two species. Moreover, ΣOC concentrations were similar between the species, but PFAS compounds were 2–12 times higher in the goldeneyes than in tawny owls. OC-pesticides dominated in tawny owls (∼60% of ΣOC), whereas persistent polychlorinated biphenyl (PCBs) congeners were the main OC components in goldeneyes (∼70% of ΣOC). The lipid-normalized concentrations of most OC-pesticides and the less persistent PCB101 declined significantly in both species. Hexachlorobenzene (HCB), p,p’-dichlorodiphenyldichloroethylene (p,p’-DDE), and more persistent PCBs decreased in tawny owls, while they tended to increase in goldeneyes. The increase in HCB was particulary robust. Among the PFASs, contrasted temporal trends were found across the species for four out of 11 compounds: PFOS declined while most perfluorocarboxylic acids (PFCAs) increased in tawny owls. In contrast, most PFASs were stable in goldeneyes. Moreover, there was no annual covariance between the OHC exposure in the two species: i.e., high concentrations in one species in a given year did not translate into high concentrations in the other. Hence, the two avian predators in adjacent ecosystems seem to be subject to different processes determining the OHC exposure, probably related to variation in diet and climate, long-range transport of different contaminants, and emissions of pollution locally.

Elsevier

2022

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