Found 2260 publications. Showing page 76 of 226:
Satellite-based measurements of volcanic ash give the total amount of volcanic ash per area, typically in units of grams of volcanic ash per square meter. To convert this to concentration the vertical thickness of the ash cloud is needed. The ash cloud thickness is not available from passive remote sensors, e.g. IR-sensors, but may be obtained from ground- and space-based lidars. Dispersion models will also provide information of the ash thickness.
This report gives an overview of volcanic ash cloud thickness as observed by space, aircraft and ground-based lidars. Also, ash cloud thickness as simulated by the Flexpart particle dispersion model is analysed. The impact of varying cloud thickness on the signal measured by IR-sensor in space is investigated. Focus is on the Eyjafjallajokull 2010 eruption for which a unique wealth of data are available.
2013
Measurement of volcanic ash in Norwegian air space. WP 1.4.2 Improved detection of ash clouds. NILU OR
Water and ice clouds and temperature conditions may often influence the detection of volcanic ash affected pixels in infrared satellite images. Several methods are available for the detection of ash clouds in SEVIRI images. Manual adjustments to the methods are often needed for a given ash situation. The report describes various methods for detection of ash affected pixels. A quantitative comparison of the methods is made based on synthetic SEVIRI images from the 2010 Eyafjallajokull eruption.
2013
Modellering av vulkanaske i norsk luftfrom. Pkt. 1.3 Enkle forbedringer av utslippsestimat. NILU OR
The report describes how a transport model is used to simulate the emission of ash from volcanic eruptions and how the ash emissions can be described in the model. A number of methods for calculating ash emissions are presented and the development of improved ash emissions by manual analysis of satellite data is presented.
2013
Atmospheric supply of nitrogen, lead, cadmium, mercury and dioxines/furans to the Baltic Sea in 2011. Summary Report for HELCOM. EMEP/MSC-W Technical report, 2/2013
2013
Deposition of air pollutants around the North Sea and the North-East Atlantic in 2011. OSPAR monitoring and assessment, 597/2013
2013
Air quality near E6 at Jessheim. NILU OR
NILU has assesed air quality at a proposed site for a hospital close to E6 at Jessheim. Based upon traffic volume, emission factors and local meteorology, concentrations of NO2 and PM10 have been modelled. The results have been compared to 'Guidelines for air quality in area planning' and the 'Red' and 'Yellow' air quality areas have been presented on a map.
2013
The nikkel smelters in NW Russia close to the Norwegian border emits large quantities of sulphur dioxide (SO2) and heavy metals. These emissions lead to enhanced concentrations of environmental pollutants in the border areas, also at the Norwegian side of the border. This report is part of the national environmental monitoring program and includes air quality monitoring, precipitation chemistry and meteorology.
2013
The Bangladesh Air Pollution Management (BAPMAN) project is an institutional-building project where NILU lends the necessary Air Quality Management (AQM) tools and associated training to the Clean Air and Sustainable Environment (CASE) program at the Department of Environment (DoE). Mission 9 of the BAPMAN project occurred in Dhaka from 19-24 October 2013 where the target of the mission was to finalize Task 2 training (CAMS QA/QC), continue Task 1 training (AirQUIS emission inventory), and to upgrade the data retrieval interface for the AirQUIS server (Task 3).
2013
Background concentrations in Norway - Temporal averaging and uncertainty assessment. NILU OR
A system for providing approximate spatial and temporal estimates of the surface background concentrations of PM10 , PM2.5, NO2 , and O3 for a typical year in Norway has been established at NILU in recent years. In 2013, the system was further improved and expanded by carrying out two main tasks: Firstly the spatial component of the system was extended from previously a single year to a 3-year average, thus decreasing the impact of inter-annual variability. Secondly, a preliminary validation of the background estimates was carried out and an approximate uncertainty was calculated for four species in the dataset and is now communicated to the user on the project website. The validation results indicate that overall the average estimated concentrations follow the average observed concentration fairly well. This is particularly true for PM10 and PM2.5. The averaged estimates for O3 and NO2 also follow the averaged observations relatively closely, although NO2 is clearly underestimated at all four validation stations. In terms of quantitative uncertainty estimates for the hourly estimates at the level of individual species, O3 is the parameter which was found to have the lowest uncertainty of all four species. While the median absolute uncertainty for hourly O3 estimates was found to be 18.7 ¿g m-3, the median relative uncertainty was only 33.8 %. Both PM10 and PM2.5 had significantly higher uncertainties, with a median relative uncertainty for the hourly estimates of 90 % and 88 %, respectively. Finally, the hourly estimates for NO2 also showed quite high relative uncertainties with a value of 73 %.
2013