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Fant 10351 publikasjoner. Viser side 123 av 415:

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Highlights from the latest research and monitoring activities at the Trollhaugen Observatory

Aas, Wenche; Eckhardt, Sabine; Evangeliou, Nikolaos; Fiebig, Markus; Hansen, Georg Heinrich; Lunder, Chris Rene

2018

Small-scale spatial variability of flame retardants in indoor dust and implications for dust sampling

Jilkova, Simona; Melymuk, Lisa; Vojta, Šimon; Vykoukalová, Martina; Bohlin-Nizzetto, Pernilla; Klánova, Jana

2018

Net ecosystem exchange estimates for Europe using a Bayesian atmospheric inversion

Thompson, Rona Louise; Broquet, Grégoire; Karstens, Ute; Scholze, Marko

2018

Unequivocal determination of fluorine on the surface of cross country skis prepared for competition by WD-XRF

Schlabach, Martin; Fiedler, D.; Myhre, Gunnar; Gruber, L.; Vik, Aasmund Fahre; Schlummer, M.; Myhre, Cathrine Lund; Rostkowski, Pawel

2018

Methane emission estimates for Ireland using a Bayesian Atmospheric Inversion

Arnold, Delia; O'Dowd, Colin; Martin, Damien; Thompson, Rona Louise

2018

Analyses of selected organic contaminants and metals in coffee cups. Technical report.

Rostkowski, Pawel; Uggerud, Hilde Thelle; Harju, Mikael; Nikiforov, Vladimir; Borgen, Anders; Kringstad, Alfhild; Bjørklund, Morten; Thomassen, Silje Eltvik; Vadset, Marit; Ghebremeskel, Mebrat; Eikenes, Heidi; Reid, Malcolm James

On behalf of Norwegian Consumer Council, NILU has conducted analyses of organic contaminants and metals in the leachate from selected coffee-cups. The simulation of the leakage is conducted based on a compilation of the methods described within NS-EN-1186-9 and NS-EN-13130-1. The instrumental analytical methods used were already established at NILU and NIVA. A number of different organic contaminants and metals have been found in trace amounts in the different products.

NILU

2018

The Global N2O model Intercomparison Project (NMIP): Objectives, simulation protocol and expected products

Tian, Hanqin; Yang, Jia; Lu, Chaoqun; Xu, Rongting; Canadell, Josep G.; Jackson, Robert; Arneth, Almut; Chang, Jinfeng; Chen, Guangsheng; Ciais, Philippe; Gerber, Stefan; Ito, Akihiko; Huang, Yuanyuan; Joos, Fortunat; Lienert, Sebastian; Messina, Palmira; Olin, Stefan; Pan, Shufen; Peng, Changhui; Saikawa, Eri; Thompson, Rona Louise; Vuichard, Nicolas; Winiwarter, Wilfried; Zaehle, Sönke; Zhang, Bowen; Zhang, Kerou; Zhu, Qiuan

2018

World Data Centre for Aerosol: Status & News 2018

Fiebig, Markus; Fjæraa, Ann Mari; Tørseth, Kjetil; Aas, Wenche

2018

Miljøgifter i innemiljøer

Bohlin-Nizzetto, Pernilla

2018

Hva skjer innendørs

Bohlin-Nizzetto, Pernilla

2018

Impacts of the autumn Arctic sea ice on the intraseasonal reversal of the winter Siberian high

Lü, Zhuozhuo; He, Shengping; Li, Fei; Wang, Huijun

During 1979–2015, the intensity of the Siberian high (SH) in November and December–January (DJ) is frequently shown to have an out-of-phase relationship, which is accompanied by opposite surface air temperature and circulation anomalies. Further analyses indicate that the autumn Arctic sea ice is important for the phase reversal of the SH. There is a significantly positive (negative) correlation between the November (DJ) SH and the September sea ice area (SIA) anomalies. It is suggested that the reduction of autumn SIA induces anomalous upward surface turbulent heat flux (SHF), which can persist into November, especially over the Barents Sea. Consequently, the enhanced eddy energy and wave activity flux are transported to mid and high latitudes. This will then benefit the development of the storm track in northeastern Europe. Conversely, when downward SHF anomalies prevail in DJ, the decreased heat flux and suppressed eddy energy hinder the growth of the storm track during DJ over the Barents Sea and Europe. Through the eddy–mean flow interaction, the strengthened (weakened) storm track activities induce decreased (increased) Ural blockings and accelerated (decelerated) westerlies, which makes the cold air from the Arctic inhibited (transported) over the Siberian area. Therefore, a weaker (stronger) SH in November (DJ) occurs downstream. Moreover, anomalously large snowfall may intensify the SH in DJ rather than in November. The ensemble-mean results from the CMIP5 historical simulations further confirm these connections. The different responses to Arctic sea ice anomalies in early and middle winter set this study apart from earlier ones.

2018

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