Found 9889 publications. Showing page 64 of 396:
Status of current activities on emissions inventories for organic and inorganic toxic compounds in Europe. WMO Global Atmosphere Watch, 136
2000
Status of current activities on emissions inventories for organic and inorganic toxic compounds in Europe. WMO Global Atmosphere Watch, 136
1999
Status for miljøet i norske havområder - Rapport fra Overvåkingsgruppen 2023
I denne rapporten gir Overvåkingsgruppen, for første gang, en felles vurdering av miljøtilstanden i Barentshavet og havområdene utenfor Lofoten, Norskehavet og Nordsjøen med Skagerrak. Det er også første rapport som bruker resultater fra det nylig utviklede fagsystemet for vurdering av økologisk tilstand. I denne rapporten dekkes to hovedtemaer: (1) Dominerende trekk i status og utvikling i økosystemet i alle tre havområdene, basert på vurderingene av økologisk tilstand, Overvåkingsgruppens rapport om forurensning fra 2022, indikatorer fra Overvåkingsgruppen som ikke er dekket under vurdering av økologisk tilstand, samt rapporter og annen relevant informasjon fra forskning, og (2) en vurdering av karbonbinding i marint plankton, marine vegetasjonstyper og marine sedimenter. I tillegg er det gitt en oppsummering for endringer i ytre påvirkning, vurdering av kunnskapsbehov samt en vurdering av indikatorverdier i forhold til referanseverdier og tiltaksgrenser. Vurderingen av dominerende trekk i utvikling og tilstand av miljøet som er gitt i kapittel 2, utgjør Overvåkingsgruppens bidrag til Faglig forums samlerapport om det faglige grunnlaget for revisjon og oppdatering av de helhetlige forvaltningsplanene for norske havområder.
Havforskningsinstituttet
2023
Status for miljøet i Barentshavet og ytre påvirkning - rapport fra Overvåkingsgruppen 2017. Fisken og Havet, særnummer 1b-2017
2017
Status and trends of NO2 ambient concentrations in Europe. ETC/ACC Technical paper, 2010/19
2011
2012
2012
Statoil's environmental monitoring program for Snøhvit. Monitoring of vegetation and soil - reanalyses in 2013. NINA Rapport, 1017
2014
Statoil refinery Mongstad. Monitoring program air and precipitation 2011 - 2013. NILU OR
NILU has conducted a monitoring for Statoil in the vicinity of Mongstad refinery. There were two stations, Sande and Sundsbø. Mean concentrations of NOx at Sande and Sundsbø were 3,43 og 1,42 µg/m3 respectively, i.e. low values. Maximum hourly mean concentrations of NO2 were 49,9 µg/m3 and 36,4 µg/m3 (Sande and Sundsbø). Concerning O3 annual mean concentration in 2012 at Sande was 64,6 µg/m3, maximum hourly mean was 145,4 µg/m3. SO2 showed very low values (maximum hourly mean 7,24 µg/m3). For PM10 annual mean values were 16,8 µg/m3 and 7,4 µg/m3 respectively (Sande and Sundsbø), maximum daily mean values in 2012 were 60,9 µg/m3 and 29,1 µg/m3. BTEX (benzene, toluene, etylbenzene and xylene) showed low values. Sampling of PAH in air was performed every 6. day. Maximum concentration of 16 EPA PAH was 6,96 ng/m3, maximum benzo(a)pyren (BaP) was 0,050 ng/m3. PAH in precipitation showed maximum value of 42,7 ng/L, maksimum BaP in prcipitation was 0,679 ng/L.
2013
The current report provides a short overview of previous years’ studies on long-term trends in O3, NO2 and PM and the role of meteorological variability for the concentration of these pollutants. The previous studies on the link between trends and meteorology has shown that these links could be estimated by a careful design of model setups using CTMs (chemical transport models). The conclusions from this work is that CTMs are certainly useful tools for explaining pollutant trends in terms of the separate impact of individual physio-chemical drivers such as emissions and meteorology although computationally demanding. The statistical GAM model that have been developed as part of the recent ETC/ACM and ETC/ATNI tasks could be considered as complementary to the use of CTMs for separating the influence of meteorological variability from other processes. The main limitation of the statistical model is that it contains no parameterisation of the real physio-chemical processes and secondly, that it relies on a local assumption, i.e. that the observed daily concentrations could be estimated based on the local meteorological data. We found clear differences in model performance both with respect to geographical area and atmospheric species. In general, the best performance was found for O3 (although not for peak levels) with gradually lower performance for NO2, PM10 and PM2.5 in that order. With respect to area, the model produced the best predictions for Central Europe (Germany, Netherlands, Belgium, France, Austria, Czech Republic) and poorer agreement with observations in southern Europe. Although the GAM model did not detect many meteorology induced long-term trends in the data, the model is well suited for separating the influence of meteorology from the other driving forces, such as emissions and boundary conditions. The GAM model thus provides robust and smooth long-term trend functions corrected for meteorology as well as the perturbations from year to year, reflecting the variability in weather conditions. One could consider to define a set of performance criteria to decide if the GAM model is applicable for a specific station and parameter.
ETC/ATNI
2020
2006
2017
State of the environment in the Norwegian, Finnish and Russian border area. The Finnish environment 6/2007
2007
State of the Climate in 2023: The Arctic
American Meteorological Society (AMS)
2024
State of the Climate in 2023 : Global Climate
American Meteorological Society (AMS)
2024
State of the Climate in 2022: The Arctic
American Meteorological Society (AMS)
2023
State of the Climate in 2021: The Arctic
American Meteorological Society (AMS)
2022
State of the Climate in 2021: 5. The Arctic
American Meteorological Society
2022