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Fant 9759 publikasjoner. Viser side 97 av 391:

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Reply to: The environmental footprint of fisheries

Halpern, Benjamin S.; Frazier, Melanie; Rayner, Paul-Eric; Clawson, Gage; Blanchard, Julia L.; Cottrell, Richard S.; Froehlich, Halley E.; Gephart, Jessica A.; Jacobsen, Nis Sand; Kuempel, Caitlin D.; Moran, Daniel; Nash, Kirsty L.; Williams, David R.

2023

Reply to Bawa and Liu: Want sustainable food? Embrace complexity

Hoang, Nguyen Tien; Taherzadeh, Oliver; Ohashi, Haruka; Yonekura, Yusuke; Nishijima, Shota; Yamabe, Masaki; Matsui, Tetsuya; Matsuda, Hiroyuki; Moran, Daniel; Kanemoto, Keiichiro

2023

Repeatability and reproducibility of data from different groups and locations in Ny-Ålesund during the Hg-Campaign 2003.

Temme, C.; Aspmo, K.; Bahlmann, E.; Banic, C.; Berg, T.; Dommergue, A.; Ebinghaus, R.; Ferrari, C.; Gauchard, P.-A.; Magand, O.; Pirrone, N.; Planchon, F.; Sprovieri, F.; Steffen, A.

2004

Renere luft i Longyearbyen

Grythe, Henrik (intervjuobjekt); Krüger, Louise (journalist)

2023

Ren luft. Helse og miljø i et bistandsperspektiv. NILU F

Sivertsen, B.; Bartonova, A.

2001

Ren luft for alle. ExtraStiftelsen project 2019/HE1-263918.

Castell, Nuria; Grossberndt, Sonja; Gray, Laura; Fredriksen, Mirjam; Høiskar, Britt Ann Kåstad

In 2019, in the framework of Oslo being European Green Capital, NILU invited students from elementary schools to
measure air pollution in their neighbourhood, using simple and affordable measuring methods based on paper and
Vaseline. The students prepared the measuring devices and selected the places where they wanted to monitor. After one
week, they retrieved the devices and used a scale to compare the amount of dust fastened to the Vaseline. All of the data
gathered by the students was uploaded by the teachers to a website (https://luftaforalle.nilu.no/), where a map showed all the results from the participating schools. The school campaign has helped researchers to get data on particulate matter from many places where data was not available, and has increased awareness among the children about the sustainability challenges cities are facing.

NILU

2021

Remote sensing of volcanic SO2 emissions using UV camera systems.

Gliss, J.; Stebel, K.; Kylling, A.; Sudbø, A.

2017

Remote sensing of gas emissions from volcanoes. Springer Praxis Books

Prata, F.; Bluth, G.; Werner, C.; Realmuto, V.; Carn, S.; Watson, M.

2015

Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations. NILU F

Glantz, P.; Bourassa, A.; Herber, A.; Iversen, T.; Karlsson, J.; Kirkevåg, A.; Maturilli, M.; Seland, Ø.; Stebel, K.; Struthers, H.; Tesche, M.; Thomason, L.

2014

Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations.

Glantz, P.; Bourassa, A.; Herber, A.; Iversen, T.; Karlsson, J.; Kirkevåg, A.; Maturilli, M.; Seland, Ø.; Stebel, K.; Struthers, H.; Tesche, M.; Thomason, L.

2014

Remote sensing and inverse transport modeling of the Kasatochi eruption sulfur dioxide cloud.

Kristiansen, N.; Stohl, A.; Prata, F.; Rischter, A.; Eckhard, S.; Seibert, P.; Hoffmann, A.; Ritter, C.; Bitar, L.; Duck, T.J.; Stebel, K.

2010

Relative impacts of sea ice loss and atmospheric internal variability on winter Arctic to East Asian surface air temperature based on large-ensemble simulations with NorESM2

He, Shengping; Drange, Helge; Furevik, Tore; Wang, Huijun; Fan, Ke; Graff, Lise Seland; Orsolini, Yvan Joseph Georges Emile G.

2023

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

He, Shengping; Drange, Helge; Furevik, Tore; Wang, Hui-Jun; Fan, Ke; Graff, Lise Seland; Orsolini, Yvan Joseph Georges Emile G.

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia” (WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) to the Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Science Press

2024

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