Fant 10007 publikasjoner. Viser side 124 av 401:
Comparison of dust-layer heights from active and passive satellite sensors
Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5–0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).
2018
A multi-model comparison of meteorological drivers of surface ozone over Europe
The implementation of European emission abatement strategies has led to a significant reduction in the emissions of ozone precursors during the last decade. Ground-level ozone is also influenced by meteorological factors such as temperature, which exhibit interannual variability and are expected to change in the future. The impacts of climate change on air quality are usually investigated through air-quality models that simulate interactions between emissions, meteorology and chemistry. Within a multi-model assessment, this study aims to better understand how air-quality models represent the relationship between meteorological variables and surface ozone concentrations over Europe. A multiple linear regression (MLR) approach is applied to observed and modelled time series across 10 European regions in springtime and summertime for the period of 2000–2010 for both models and observations. Overall, the air-quality models are in better agreement with observations in summertime than in springtime and particularly in certain regions, such as France, central Europe or eastern Europe, where local meteorological variables show a strong influence on surface ozone concentrations. Larger discrepancies are found for the southern regions, such as the Balkans, the Iberian Peninsula and the Mediterranean basin, especially in springtime. We show that the air-quality models do not properly reproduce the sensitivity of surface ozone to some of the main meteorological drivers, such as maximum temperature, relative humidity and surface solar radiation. Specifically, all air-quality models show more limitations in capturing the strength of the ozone–relative-humidity relationship detected in the observed time series in most of the regions, for both seasons. Here, we speculate that dry-deposition schemes in the air-quality models might play an essential role in capturing this relationship. We further quantify the relationship between ozone and maximum temperature (mo3 − T, climate penalty) in observations and air-quality models. In summertime, most of the air-quality models are able to reproduce the observed climate penalty reasonably well in certain regions such as France, central Europe and northern Italy. However, larger discrepancies are found in springtime, where air-quality models tend to overestimate the magnitude of the observed climate penalty.
2018
2018
Curating scientific information in knowledge infrastructures
Interpreting observational data is a fundamental task in the sciences, specifically in earth and environmental science where observational data are increasingly acquired, curated, and published systematically by environmental research infrastructures. Typically subject to substantial processing, observational data are used by research communities, their research groups and individual scientists, who interpret such primary data for their meaning in the context of research investigations. The result of interpretation is information—meaningful secondary or derived data—about the observed environment. Research infrastructures and research communities are thus essential to evolving uninterpreted observational data to information. In digital form, the classical bearer of information are the commonly known “(elaborated) data products,” for instance maps. In such form, meaning is generally implicit e.g., in map colour coding, and thus largely inaccessible to machines. The systematic acquisition, curation, possible publishing and further processing of information gained in observational data interpretation—as machine readable data and their machine readable meaning—is not common practice among environmental research infrastructures. For a use case in aerosol science, we elucidate these problems and present a Jupyter based prototype infrastructure that exploits a machine learning approach to interpretation and could support a research community in interpreting observational data and, more importantly, in curating and further using resulting information about a studied natural phenomenon.
2018
2018
2018
Atlantic multidecadal oscillation modulates the impacts of Arctic sea ice decline
The Arctic sea ice cover has been rapidly declining in the last two decades, concurrent with a shift in the Atlantic Multidecadal Oscillation (AMO) to its warm phase around 1996/1997. Here we use both observations and model simulations to investigate the modulation of the atmospheric impacts of the decreased sea ice cover in the Atlantic sector of the Arctic (AASIC) by the AMO. We find that the AASIC loss during a cold AMO phase induces increased Ural blocking activity, a southeastward‐extended snowpack, and a cold continent anomaly over Eurasia in December through northerly cold air advection and moisture transport from the Arctic. The increased Ural blocking activity and more extended Eurasian snowpack strengthen the upward propagation of planetary waves over the Siberian‐Pacific sector in the lower stratosphere and hence lead to a weakened stratospheric polar vortex and a negative Arctic Oscillation (AO) phase at the surface in February. However, corresponding to the AASIC loss during a warm AMO phase, one finds more widespread warming over the Arctic and a reduced snowpack over Northern Eurasia in December. The stratosphere‐troposphere coupling is suppressed in early winter and no negative AO anomaly is found in February. We suggest that the cold AMO phase is important to regulate the atmospheric response to AASIC decline, and our study provides insight to the ongoing debate on the connection between the Arctic sea ice and the AO.
2018
Assessing, quantifying and valuing the ecosystem services of coastal lagoons
The natural conservation of coastal lagoons is important not only for their ecological importance, but also because of the valuable ecosystem services they provide for human welfare and wellbeing. Coastal lagoons are shallow semi-enclosed systems that support important habitats such as wetlands, mangroves, salt-marshes and seagrass meadows, as well as a rich biodiversity. Coastal lagoons are also complex social-ecological systems and the ecosystem services that lagoons deliver provide livelihoods, benefits wellbeing and welfare to humans. This study assessed, quantified and valued the ecosystem services of 32 coastal lagoons. The main findings of the study were: (i) the definitions of ecosystem services are still not generally accepted; (ii) the quantification of ecosystem services is made in many different ways, using different units; (iii) the evaluation in monetary terms of some ecosystem service is problematic, often relying on non-monetary evaluation methods; (iv) when ecosystem services are valued in monetary terms, this may represent very different human benefits; and, (v) different aspects of climate change, including increasing temperature (SST), sea-level rise (SLR) and changes in rainfall patterns threaten the valuable ecosystem services of coastal lagoons.
2018
I prosjektet ble det utført målinger av kvikksølv (Hg) i luft ved en stasjon og prøvetaking og analyse av Hg i nedbør ved to stasjoner, samt analyse av Hg i 14 storfisk fra Pasvikvassdraget. Måleresultatene for Hg i luft i Karpdalen viser bakgrunnsnivåer rundt 1,3 - 1,4 ng/m3. Forhøyede konsentrasjoner av Hg samsvarer med forhøyede konsentrasjoner av SO2 (episoder). Det er derfor sannsynliggjort at episodene skyldes utslipp fra samme kilde eller kildeområder på russisk side. Konsentrasjoner av Hg i nedbør og avsetning er høyere på Svanvik enn i Karpdalen, men lavere enn bakgrunnsstasjoner i Sør-Norge. Analyser av Hg i fisk viser at de største fiskene (gjedde, ørret, abbor) har verdier over grenseverdi på 0,5 mg/kg. Sik viste lave verdier.
NILU
2018
The Zeppelin Observatory is an atmospheric monitoring station located on the northwest coast of Spitzbergen island, in the Svalbard archipelago. The station provides background air composition, meteorological and climatological data for numerous research projects. The observatory is located on a mountain ridge in a region with complex topography that affects local atmospheric circulation processes. Research question: How the seasonal data collected at the Zeppelin observatory and Ny-Ålesund station (Fig. 2b), a temporarily station in the settlement, is affected by: 1) micrometeorological conditions 2) mesoscale dynamics 3) local air pollution
2018
CITI-SENSE Citizens' Observatories Architecture
This paper introduces the architecture of the CITI-SENSE Citizens’ Observatories based on the ISO 19119 reference model. It describes the various parts of the architecture including boundary services with sensors and apps and data management services with the CITI-SENSE data model. It also describes the Web Feature Service (WFS) storage support and the reusable visualisation widgets used for both apps and web portals in various Citizens’ Observatories.
2018
2018
2018
Rapporten viser overskridelser av tålegrenser for forsuring av vann og jord, samt overgjødslingseffekter på vegetasjon, med
avsetningsverdier for perioden 2012–2016. Det er kun en liten reduksjon i areal med overskridelse siden forrige periode: For
vann, ved bruk av SSWCoaa-modellen er 7% av Norges areal overskredet (8% i forrige periode). Bruk av FABoaa-modellen, som
forutsetter et mye større forsuringsbidrag fra nitrogen, gir en overskridelse på 19% av Norges areal (20% i forrige periode).
Overskredet areal for overgjødslingseffekter på vegetasjon er 20% (21% i forrige periode). Tålegrensene for forsuring av
skogsjord er ikke overskredet. Noen oppdateringer av tålegrensene har blitt gjort, primært for overgjødsling av vegetasjon. Det
er også benyttet en ny metode for beregning av avsetninger. Ingen av endringene gav store forskjeller i totalt overskredet areal,
men noen forskjeller i hvor man finner overskridelser og størrelsen på overskridelsene.
Norsk institutt for vannforskning (NIVA)
2018
Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO2 cameras is commonly used to monitor SO2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows the gas velocities in the plume to be retrieved directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constrained OF motion vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion fields. The new method is applied to two example data sets recorded at Mt Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO2 emission rates. We further show that our proposed correction can account for this and that it significantly improves the reliability of optical-flow-based gas velocity retrievals.
In the case of Mt Etna, the SO2 emissions of the north-eastern crater are investigated. The corrected SO2 emission rates range between 4.8 and 10.7 kg s−1 (average of 7.1 ± 1.3 kg s−1) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO2 emission rates are between 0.5 and 2.9 kg s−1 (average of 1.3 ± 0.5 kg s−1) and provide the first report of SO2 emissions from this remotely located and inaccessible volcano.
2018
Uptake and effects of 2, 4, 6 - trinitrotoluene (TNT) in juvenile Atlantic salmon (Salmo salar)
Elsevier
2018
2017
2017
2017