Fant 9760 publikasjoner. Viser side 175 av 391:
Indoor air quality assessment in the Baroque Hall of the National Library (Prague, Czech Republic). NILU F
2010
Indoor air quality at Life Technologies AS. Measurement of particulate matter. NILU OR
NILU - Norsk institutt for luftforskning har utført malinger av partikler på Life Technologies AS (tidligere Invitrogen Dynal AS) i Lillestrøm. Prøvetaking foregikk ved tre steder i produksjonsdelen av firmaet i perioden 31. januar til 28. februar 2012. Tidligere studier av lignende art ble gjennomført i 2007 og 2010.
Resultatene fra denne undersøkelsen viste at alle målte partikkelkonsentrasjoner var godt under normene fra Arbeidstilsynet. Den høyeste observerte PM2.5-konsentrasjonen var 14,5 µg/m3 under dagtid i NIT-280 (50 l reaktor), som er klart under normen anbefalt av Folkehelseinstituttet. Ingen av PM-prøvene tatt hos Life Technologies AS viste en verdi som overstiger selskapets eksponeringsgrense (OEL) for Dynabeads.
2012
2015
Indoor air quality in the Baroque Hall of the National Library in Prague - preliminary results. NILU PP
2010
2010
Indoor air quality investigation sector E3-02. NILU OR
Abu Dhabi Municipality has chosen the Norwegian Institute for Air Research (NILU) to perform indoor air quality investigation for six buildings in sector E3-02 (one School, one Mosque, one commercial building and three Residential building).
The main goal of this task is to define the main pollutants that could be found in the buildings and to define the status of existing buildings with respect to indoor air quality.
The results of measurements that were conducted at different locations have shown that there was a wide mold growth in the duct of ventilation system due to poor maintenance in all studied buildings, also that carbon dioxide (CO2) and voltaic organic compound (VOC) are considered the main pollutants that could found and affect the indoor air quality in these buildings.
In most of tested locations, the CO2 concentration has exceeded the standard limit, the readings were very high in the school, mosque, and to a lesser extent in commercial building.
2012
Indoor air quality study for the Norwegian Embassy in Abu Dhabi. NILU OR
NILU has been asked by the Norwegian Embassy in Abu Dhabi to carry out an indoor air quality(IAQ) study. The results have shown that there is a big variation in the temperatures ( ¿10 C) between the monitored locations in the office. Data analysis from employees survey about indoor air have shown that employees do not feel comfortable with the temperature conditions. In addition mould growth was detected in Ambassador¿s office.
CO2 concentration exceeded the acceptable limit in two locations, because the ventilation system is not capable to provide sufficient amount of fresh air to the number of occupants. The conclusion was that the main problem was related to the unbalanced ventilation system creating improper air circulation leading to high CO2 concentrations and large differences in temperatures.
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2010
Inferring surface energy fluxes using drone data assimilation in large eddy simulations
Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.
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