Reducing the radioactive doses of liquid samples taken from reprocessing plant vessels by volume reduction

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Audio vs. Video: Does Viewing Support Learning? A Comparision of an Audio-Visual with an Auditory Virtual Lecture

Häufig wird behauptet, dass audiovisuelle Informationen gegenüber auditiven lernwirksamer sind. Dies wird meist mit der kognitiv-anregenden Funktion begründet, die der audiovisuellen Darstellung zugeschrieben wird. Bisherige empirische Arbeiten konnten das auch tendenziell bestätigen; allerdings beziehen sich diese Befunde überwiegend auf das video- oder fernsehgestützte Lernen, bei dem den Lernenden keine zusätzlichen textbasierten Informationen zur Verfügung stehen. Für den Bereich der virtuellen Vorlesung wurde noch nicht untersucht, ob sich eine audiovisuelle Präsentation des Vortragenden gegenüber einer rein auditiven Präsentation positiv auf den Lernerfolg auswirkt. In einer empirischen Studie mit 61 Versuchspersonen wurde daher Lernenden ein Ausschnitt aus einer Online-Vorlesung in zwei Variationen präsentiert. Während die eine Gruppe eine Lerneinheit bearbeitete, in der sie neben textbasierten Informationen eine Videosequenz (Aufnahme des Dozenten) präsentiert bekam, bearbeitete die zweite Gruppe die gleiche Lerneinheit; hier war jedoch nur die Stimme des Dozenten hörbar. In einem direkt anschließenden Wissens- und späteren Behaltenstest zeigten sich keine signifikanten Leistungsunterschiede zwischen den beiden Gruppen. Jedoch berichtete die Mehrheit der Versuchspersonen, dass sie die Videovariante für affektiv-unterstützender hält als die Tonvariante. (ZPID

Trend analysis from 1970 to 2008 and model evaluation of EDGARv4 global gridded anthropogenic mercury emissions

The Emission Database for Global Atmospheric Research (EDGAR) provides a time-series of man-made emissions of greenhouse gases and short-lived atmospheric pollutants from 1970 to 2008. Mercury is included in EDGARv4.tox1, thereby enriching the spectrum of multi-pollutant sources in the database. With an average annual growth rate of 1.3% since 1970, EDGARv4 estimates that the global mercury emissions reached 1287 tonnes in 2008. Specifically, gaseous elemental mercury (GEM) (Hg[superscript 0]) accounted for 72% of the global total emissions, while gaseous oxidised mercury (GOM) (Hg[superscript 2 +]) and particle bound mercury (PBM) (Hg-P) accounted for only 22% and 6%, respectively. The less reactive form, i.e., Hg[superscript 0], has a long atmospheric residence time and can be transported long distances from the emission sources. The artisanal and small-scale gold production, accounted for approximately half of the global Hg[superscript 0] emissions in 2008 followed by combustion (29%), cement production (12%) and other metal industry (10%). Given the local-scale impacts of mercury, special attention was given to the spatial distribution showing the emission hot-spots on gridded 0.1° × 0.1° resolution maps using detailed proxy data. The comprehensive ex-post analysis of the mitigation of mercury emissions by end-of-pipe abatement measures in the power generation sector and technology changes in the chlor-alkali industry over four decades indicates reductions of 46% and 93%, respectively. Combined, the improved technologies and mitigation measures in these sectors accounted for 401.7 tonnes of avoided mercury emissions in 2008. A comparison shows that EDGARv4 anthropogenic emissions are nearly equivalent to the lower estimates of the United Nations Environment Programme (UNEP)'s mercury emissions inventory for 2005 for most sectors. An evaluation of the EDGARv4 global mercury emission inventory, including mercury speciation, was performed using the GEOS-Chem global 3-D mercury model. The model can generally reproduce both spatial variations and long-term trends in total gaseous mercury concentrations and wet deposition fluxes.National Science Foundation (U.S.) (Atmospheric Chemistry Program Grant 1053648

Exploring synergies between climate and air quality policies using long-term global and regional emission scenarios

In this paper, we present ten scenarios developed using the IMAGE framework (Integrated Model to Assess the Global Environment) to explore how different assumptions on future climate and air pollution policies influence emissions of greenhouse gases and air pollutants. These scenarios describe emission developments in 26 world regions for the 21st century, using a matrix of climate and air pollution policies. For climate policy, the study uses a baseline resulting in forcing levels slightly above RCP6.0 and an ambitious climate policy scenario similar to RCP2.6. For air pollution, the study explores increasingly tight emission standards, ranging from no improvement, current legislation and three variants assuming further improvements. For all pollutants, the results show that more stringent control policies are needed after 2030 to prevent a rise in emissions due to increased activities and further reduce emissions. The results also show that climate mitigation policies have the highest impact on SO2 and NOX emissions, while their impact on BC and OC emissions is relatively low, determined by the overlap between greenhouse gas and air pollutant emission sources. Climate policy can have important co-benefits; a 10% decrease in global CO2 emissions by 2100 leads to a decrease of SO2 and NOX emissions by about 10% and 5%, respectively compared to 2005 levels. In most regions, low levels of air pollutant emissions can also be achieved by solely implementing stringent air pollution policies. The largest differences across the scenarios are found in Asia and other developing regions, where a combination of climate and air pollution policy is needed to bring air pollution levels below those of today

Uncertainties in emissions estimates of greenhouse gases and air pollutants in India and their impacts on regional air quality

Greenhouse gas and air pollutant precursor emissions have been increasing rapidly in India. Large uncertainties exist in emissions inventories and quantification of their uncertainties is essential for better understanding of the linkages among emissions and air quality, climate, and health. We use Monte Carlo methods to assess the uncertainties of the existing carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission estimates from four source sectors for India. We also assess differences in the existing emissions estimates within the nine subnational regions. We find large uncertainties, higher than the current estimates for all species other than CO, when all the existing emissions estimates are combined. We further assess the impact of these differences in emissions on air quality using a chemical transport model. More efforts are needed to constrain emissions, especially in the Indo-Gangetic Plain, where not only the emissions differences are high but also the simulated concentrations using different inventories. Our study highlights the importance of constraining SO2, NOx, and NH3 emissions for secondary PM concentrations

Data-driven estimates of global nitrous oxide emissions from croplands

Croplands are the single largest anthropogenic source of nitrous oxide (N2O) globally, yet their estimates remain difficult to verify when using Tier 1 and 3 methods of the Intergovernmental Panel on Climate Change (IPCC). Here, we re-evaluate global cropland-N2O emissions in 1961–2014, using N-rate-dependent emission factors (EFs) upscaled from 1206 field observations in 180 global distributed sites and high-resolution N inputs disaggregated from sub-national surveys covering 15593 administrative units. Our results confirm IPCC Tier 1 default EFs for upland crops in 1990–2014, but give a ∼15% lower EF in 1961–1989 and a ∼67% larger EF for paddy rice over the full period. Associated emissions (0.82 ± 0.34 Tg N yr–1) are probably one-quarter lower than IPCC Tier 1 global inventories but close to Tier 3 estimates. The use of survey-based gridded N-input data contributes 58% of this emission reduction, the rest being explained by the use of observation-based non-linear EFs. We conclude that upscaling N2O emissions from site-level observations to global croplands provides a new benchmark for constraining IPCC Tier 1 and 3 methods. The detailed spatial distribution of emission data is expected to inform advancement towards more realistic and effective mitigation pathways