Found 9890 publications. Showing page 108 of 396:
2018
Equinors miljøovervåkingsprogram for Snøhvit. Overvåking av vegetasjon og jord – reanalyser i 2018
Petroleumsanlegget på Melkøya utenfor Hammerfest ble startet opp i 2007 og slipper ut karbon-dioksid (CO2), nitrogenoksider (NOx), metan (CH4), flyktige organiske forbindelser utenom metan (nmVOC), svoveldioksid (SO2) og hydrogensulfid (H2S) fra energiproduksjon og prosessanlegg. Utslipp av nitrogen og svovelholdige gasser kan generelt påvirke terrestriske økosystemer ved forsuring og gjødsling av jordsmonn og vegetasjon. Petroleumsanlegget på Melkøya tar imot naturgass fra feltene Snøhvit og Albatross i Barentshavet. Her prosesseres og nedkjøles natur-gassen til flytende gass (LNG) for videre distribuering. Utslippene fra LNG-anlegget er beregnet til å ligge under gjeldene kritiske tålegrenseverdier for terrestriske naturtyper, men tålegrense-verdiene i arktisk/alpine naturtyper er imidlertid usikre. For å kunne dokumentere eventuelle ef-fekter av utslipp til luft, ble det i 2006 (før utslipp) etablert et overvåkingsprogram for vegetasjon og jord i influensområdet fra LNG-anlegget på Melkøya. Grunnlagsundersøkelsen ble utført samme år, og det ble utført analyser i 2008, 2013 og 2018 etter samme metodikk som i 2006.
To overvåkingsområder ble opprettet i 2006, ett med estimert relativt høy avsetning av nitrogen, nordøst på Kvaløya ved Forsøl og ett område med relativt lav avsetning sør på Kvaløya ved Stangnes. Områdene er samkjørt med Norsk institutt for luftforskning (NILU) sine overvåkings-stasjoner for luft- og nedbørskvalitet. Innen hvert område utføres det en integrert overvåking av vegetasjonens artssammensetning og kjemisk innhold av planter og jord i to atskilte naturtyper (næringsfattig kreklinghei og litt kalkfattig og svakt intermediær jordvannsmyr).
Vegetasjonen overvåkes i permanent oppmerkede ruter (1m × 1m i arktisk hei og 0,5m × 0,5m på myr). I hver rute registreres mengde av karplanter, moser og lav, samt vegetasjonssjiktenes høyde og dekning. Lys reinlav/fjellreinlav (reinlav) og rusttorvmose analyseres for kjemisk inn-hold, Kjeldahl-nitrogen, tungmetallene bly (Pb), nikkel (Ni) og sink (Zn) og polyaromatiske hydro-karboner (PAH). Jordprøver fra hver av naturtypene analyseres for pH, Kjeldahl-nitrogen, ekstraherbare kationer, utbyttingskapasitet, basemetning, Pb, Ni, Zn og PAH. De kjemiske analysene av planter og jord utføres av Norsk institutt for bioøkonomi og NILU.
Analysene av vegetasjonens artssammensetning viste få endringer i mengdeforhold mellom artene fra 2006 til 2018. De små endringene vi fant skyldes trolig årlige variasjoner. Det ble funnet noen få endringer av arter som normalt responderer positivt på nitrogengjødsling, slik som gress. Lav har gått noe tilbake mest sannsynlig pga. økt beitepress fra rein. Det er således ingen indikasjon på at en eventuell forurensing fra LNG-anlegget på Melkøya har påvirket vegetasjonens artssammensetning og mengdeforholdet mellom arter.
NØKKELORD : Hammerfest, Melkøya, Kvaløya, LNG-anlegg, forurensing, forsuring, gjødsling, nitrogen, arktisk/ alpin vegetasjon, kreklinghei, myr, plantekjemi, jordkjemi, polyaromatiske hydrokarboner,
KEY WORDS : Hammerfest, Melkøya, Kvaløya, LNG plant, pollution, acidification, fertilization, nitrogen, arctic/ alpine vegetation, mire, plant chemistry, soil chemistry, polynuclear aromatic hydrocarbons
Norsk institutt for naturforskning
2018
Interdecadal change in the relationship between the East Asian winter monsoon (EAWM) and the Arctic Oscillation (AO) has been documented by many studies. This study, utilizing the model outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), evaluates the ability of the coupled models in CMIP5 to capture the intensified relationship between the EAWM and winter AO since the 1980s, and further projects the evolution of the EAWM–AO relationship during the 21st century. It is found that the observed evolution of the EAWM–AO relationship can be reproduced well by some coupled models (e.g., GFDL-ESM2M, GISS-E2-H, and MPI-ESM-MR). The coupled models’ simulations indicate that the impact of winter AO on the EAWM-related circulation and East Asian winter temperature has strengthened since the 1980s. Such interdecadal change in the EAWM–AO relationship is attributed to the intensified propagation of stationary planetary waves associated with winter AO. Projections under the RCP4.5 and RCP8.5 scenarios suggest that the EAWM–AO relationship is significant before the 2030s and after the early 2070s, and insignificant during the 2060s, but uncertain from the 2030s to the 2050s.
Science Press
2018
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Interim Annual Assessment Report for 2017. European air quality in 2017.
Copernicus Atmosphere Monitoring Service
2018
This paper presents the light-scattering properties of atmospheric aerosol particles measured over the past decade at 28 ACTRIS observatories, which are located mainly in Europe. The data include particle light scattering (σsp) and hemispheric backscattering (σbsp) coefficients, scattering Ångström exponent (SAE), backscatter fraction (BF) and asymmetry parameter (g). An increasing gradient of σsp is observed when moving from remote environments (arctic/mountain) to regional and to urban environments. At a regional level in Europe, σsp also increases when moving from Nordic and Baltic countries and from western Europe to central/eastern Europe, whereas no clear spatial gradient is observed for other station environments. The SAE does not show a clear gradient as a function of the placement of the station. However, a west-to-east-increasing gradient is observed for both regional and mountain placements, suggesting a lower fraction of fine-mode particle in western/south-western Europe compared to central and eastern Europe, where the fine-mode particles dominate the scattering. The g does not show any clear gradient by station placement or geographical location reflecting the complex relationship of this parameter with the physical properties of the aerosol particles. Both the station placement and the geographical location are important factors affecting the intra-annual variability. At mountain sites, higher σsp and SAE values are measured in the summer due to the enhanced boundary layer influence and/or new particle-formation episodes. Conversely, the lower horizontal and vertical dispersion during winter leads to higher σsp values at all low-altitude sites in central and eastern Europe compared to summer. These sites also show SAE maxima in the summer (with corresponding g minima). At all sites, both SAE and g show a strong variation with aerosol particle loading. The lowest values of g are always observed together with low σsp values, indicating a larger contribution from particles in the smaller accumulation mode. During periods of high σsp values, the variation of g is less pronounced, whereas the SAE increases or decreases, suggesting changes mostly in the coarse aerosol particle mode rather than in the fine mode. Statistically significant decreasing trends of σsp are observed at 5 out of the 13 stations included in the trend analyses. The total reductions of σsp are consistent with those reported for PM2.5 and PM10 mass concentrations over similar periods across Europe.
2018
We present the organization, instrumentation, datasets, data interpretation, modeling, and accomplishments of the multinational global atmospheric measurement program AGAGE (Advanced Global Atmospheric Gases Experiment). AGAGE is distinguished by its capability to measure globally, at high frequency, and at multiple sites all the important species in the Montreal Protocol and all the important non-carbon-dioxide (non-CO2) gases assessed by the Intergovernmental Panel on Climate Change (CO2 is also measured at several sites). The scientific objectives of AGAGE are important in furthering our understanding of global chemical and climatic phenomena. They are the following: (1) to accurately measure the temporal and spatial distributions of anthropogenic gases that contribute the majority of reactive halogen to the stratosphere and/or are strong infrared absorbers (chlorocarbons, chlorofluorocarbons – CFCs, bromocarbons, hydrochlorofluorocarbons – HCFCs, hydrofluorocarbons – HFCs and polyfluorinated compounds (perfluorocarbons – PFCs), nitrogen trifluoride – NF3, sulfuryl fluoride – SO2F2, and sulfur hexafluoride – SF6) and use these measurements to determine the global rates of their emission and/or destruction (i.e., lifetimes); (2) to accurately measure the global distributions and temporal behaviors and determine the sources and sinks of non-CO2 biogenic–anthropogenic gases important to climate change and/or ozone depletion (methane – CH4, nitrous oxide – N2O, carbon monoxide – CO, molecular hydrogen – H2, methyl chloride – CH3Cl, and methyl bromide – CH3Br); (3) to identify new long-lived greenhouse and ozone-depleting gases (e.g., SO2F2, NF3, heavy PFCs (C4F10, C5F12, C6F14, C7F16, and C8F18) and hydrofluoroolefins (HFOs; e.g., CH2 = CFCF3) have been identified in AGAGE), initiate the real-time monitoring of these new gases, and reconstruct their past histories from AGAGE, air archive, and firn air measurements; (4) to determine the average concentrations and trends of tropospheric hydroxyl radicals (OH) from the rates of destruction of atmospheric trichloroethane (CH3CCl3), HFCs, and HCFCs and estimates of their emissions; (5) to determine from atmospheric observations and estimates of their destruction rates the magnitudes and distributions by region of surface sources and sinks of all measured gases; (6) to provide accurate data on the global accumulation of many of these trace gases that are used to test the synoptic-, regional-, and global-scale circulations predicted by three-dimensional models; and (7) to provide global and regional measurements of methane, carbon monoxide, and molecular hydrogen and estimates of hydroxyl levels to test primary atmospheric oxidation pathways at midlatitudes and the tropics. Network Information and Data Repository: http://agage.mit.edu/data or http://cdiac.ess-dive.lbl.gov/ndps/alegage.html (https://doi.org/10.3334/CDIAC/atg.db1001).
2018
Background: This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.
Results: Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of < 40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (= above-average) or low (= below-average) correlation coefficients.
Conclusions: LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites.
Springer
2018
Atmospheric monitoring and inverse modelling for verification of greenhouse gas inventories
The Paris Agreement requires accurate accounting of greenhouse gases (GHGs) by all countries. Complementary to bottom-up emission inventories, global, regional and national GHG emissions can be estimated using atmospheric measurements and atmospheric models (the "top-down" approach). This report provides an overview of current capabilities, potential, and further perspectives to use the "top-down" approach to evaluate and improve estimates of greenhouse gas emissions in support of the Paris Agreement.
Publications Office of the European Union
2018
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ThermoFisher Scientific
2018
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