Found 9887 publications. Showing page 332 of 396:
2007
2009
Svalbard is a near pristine Arctic environment, where long-range transport from mid-latitudes is an
important air pollution source. Thus, several previous studies investigated the background
nitrogen oxides (NO x ) and tropospheric ozone (O 3 ) springtime chemistry in the region. However,
there are also local anthropogenic emission sources on the archipelago such as coal power plants,
ships and snowmobiles, which may significantly alter in situ atmospheric composition.
Measurement results from three independent research projects were combined to identify the
effect of emissions from various local sources on the background concentration of NO x and O 3 in
Svalbard. The hourly meteorological and chemical data from the ground-based stations in
Adventdalen, Ny-Ålesund and Barentsburg were analysed along with daily radiosonde soundings
and weekly data from O 3 sondes. The data from the ERA5 reanalysis were used to evaluate the
prevailing synoptic conditions during the fieldwork. Although the correlation between the NO x
concentrations in the three settlements was low due to dominant influence of the local
atmospheric circulation, cases with common large-scale meteorological conditions increasing the
local pollutant concentration at all sites were identified. In colder and calmer days and days with
temperature inversions, the concentrations of NO x were higher. In contrast to NO x values, O 3
concentrations in Barentsburg and at the Zeppelin station in Ny-Ålesund correlated strongly, and
hence the prevailing synoptic situation and long-range transport of air masses were controlling
factors for them. The Lagrangian models HYSPLIT and FLEXPART have been used to investigate air
mass transport and transformations during the large scale O 3 depletion and enrichment events.
The factors affecting Arctic springtime photochemistry of O 3 have been investigated thoroughly
using Lagrangian and Eulerian numerical weather prediction model data and Metop GOME-2
satellite observations.
2021
Svalbard is a remote and scarcely populated Arctic archipelago and is considered to be mostly influenced by long-range-transported air pollution. However, there are also local emission sources such as coal and diesel power plants, snowmobiles and ships, but their influence on the background concentrations of trace gases has not been thoroughly assessed. This study is based on data of tropospheric ozone (O3) and nitrogen oxides (NOx) collected in three main Svalbard settlements in spring 2017. In addition to these ground-based observations and radiosonde and O3 sonde soundings, ERA5 reanalysis and BrO satellite data have been applied in order to distinguish the impact of local and synoptic-scale conditions on the NOx and O3 chemistry. The measurement campaign was divided into several sub-periods based on the prevailing large-scale weather regimes. The local wind direction at the stations depended on the large-scale conditions but was modified due to complex topography. The NOx concentration showed weak correlation for the different stations and depended strongly on the wind direction and atmospheric stability. Conversely, the O3 concentration was highly correlated among the different measurement sites and was controlled by the long-range atmospheric transport to Svalbard. Lagrangian backward trajectories have been used to examine the origin and path of the air masses during the campaign.
2022
2017
2015
2016
2021
American Meteorological Society (AMS)
2023
State of the Climate in 2021: 5. The Arctic
American Meteorological Society
2022
State of the Climate in 2021: The Arctic
American Meteorological Society (AMS)
2022
State of the Climate in 2022: The Arctic
American Meteorological Society (AMS)
2023
State of the Climate in 2023 : Global Climate
American Meteorological Society (AMS)
2024
State of the Climate in 2023: The Arctic
American Meteorological Society (AMS)
2024
State of the environment in the Norwegian, Finnish and Russian border area. The Finnish environment 6/2007
2007
2017
2006
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
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
Statoil's environmental monitoring program for Snøhvit. Monitoring of vegetation and soil - reanalyses in 2013. NINA Rapport, 1017
2014