Fant 10278 publikasjoner. Viser side 309 av 412:
2019
2019
NORDUST : Nordic Road Dust Project
Road dust is an important contributor to airborne particle pollution, especially in the Nordic countries where high road surface wear, due to studded tyre use as well as winter maintenance and operations including sanding and salting are important contributors. Even though the road dust problems are similar, the countries have tackled different parts of the problem with different research approaches, resulting in a complex knowledgebase in need of compilation. A former project, NORTRIP, started this work and implemented the knowledge into an emission model with a specially elaborated road dust focus. The model work has been used to identify knowledge gaps, intended to be filled within the NorDust project.Laboratory tests and controlled and uncontrolled field measurements as well as parametrisation and modelling have been used as tools to find, describe and implement issues concerning road dust formation, suspension and dynamics and road operation effects on emissions in facilities and sites in finland and Sweden. The NORTRIP model has been implemented and evaluated in Iceland, not previously involved in the model development, to identify input data needs.The project has resulted in an array of findings, of which some have been possible to implement in new parametrisations in the NORTRIP model. In the complex research area of road dust dynamics, the project has also resulted in a lot of practical experiences concerning experimental and measurement designs and evaluation possibilities that future research will be able to benefit from.
NordFoU
2019
2019
2019
2019
2019
A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error–covariance in the EnOI is sampled in two ways: (i) by using the stochastic spread from an ensemble open-loop run, and (ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore, the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in situ observations at a 95% significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in situ data at the same significance level; however this improvement is dependent on which in situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95% significance level. The study also suggests that assimilation of satellite derived surface soil moisture using the EnOI can correct random errors in the atmospheric forcing and give an analysed surface soil moisture close to that of an open-loop run using observation derived precipitation. Importantly, this shows that estimates of soil moisture could be improved using a combination of assimilating SMAP using the computationally cheap EnOI while using model derived precipitation as forcing. Finally, we assimilate three different Level-2 satellite derived soil moisture products from the European Space Agency Climate Change Initiative (ESA CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.
2019
2019
2019
2019
2019
Spredningsberegninger for ammoniakkutslipp. Leangen idrettsanlegg i Trondheim.
NILU har gjennomført spredningsberegninger for utslipp av ammoniakk (NH3) ved Leangen idrettsanlegg I Trondheim. Beregningene er utført for å undersøke hvilke konsentrasjoner av ammoniakk som kan forekomme i bakkenivå for ulike høyder av avkast for ammoniakkdamp. Beregningene viser at avkastet bør være 21 m over bakkenivå for å overholde grenseverdi for arbeidsatmosfære. Så lenge utslippet pågår vil det forekomme timemiddelkonsentrasjoner av ammoniakk over luktegrensen nedvinds for utslippet.
NILU
2019
Skogens helsetilstand i Norge. Resultater fra skogskadeovervåkingen i 2018
Skogens helsetilstand påvirkes i stor grad av klima og værforhold, enten direkte ved tørke, frost og vind, eller indirekte ved at klimaet påvirker omfanget av soppsykdommer og insektangrep. Klimaendringene og den forventede økningen i klimarelaterte skogskader gir store utfordringer for forvaltningen av framtidas skogressurser. Det samme gjør invaderende skadegjørere, både allerede etablerte arter og nye som kan komme til Norge i nær framtid. I denne rapporten presenteres resultater fra skogskadeovervåkingen i Norge i 2018 og trender over tid for følgende temaer: (i) Landsrepresentativ skogovervåking; (ii) Skogøkologiske analyser og målinger av luftkjemi på de intensive overvåkingsflatene; (iii) Overvåking av bjørkemålere i Troms og Finnmark; (iv) Granbarkbilleovervåking – utvikling av barkbillepopulasjonene i 2018;
(v) Ny barkbille på vei – vil den like klimaet?; (vi) Phytophthora i importert jord på prydplanter og faren det utgjør for skog; (vii) Overvåking av askeskuddsyke; (viii) Skog- og utmarksbranner i 2018; (ix) Andre spesielle skogskader i 2018...….
NIBIO
2019
2019
Using meteor wind data from the Super Dual Auroral Radar Network (SuperDARN) in the Northern Hemisphere, we (1) demonstrate that the migrating (Sun‐synchronous) tides can be separated from the nonmigrating components in the mesosphere and lower thermosphere (MLT) region and (2) use this to determine the response of the different components of the semidiurnal tide (SDT) to sudden stratospheric warming (SSW) conditions. The radars span a limited range of latitudes around 60°N and are located over nearly 180° of longitude. The migrating tide is extracted from the nonmigrating components observed in the meridional wind recorded from meteor ablation drift velocities around 95‐km altitude, and a 20‐year climatology of the different components is presented. The well‐documented late summer and wintertime maxima in the semidiurnal winds are shown to be due primarily to the migrating SDT, whereas during late autumn and spring the nonmigrating components are at least as strong as the migrating SDT. The robust behavior of the SDT components during SSWs is then examined by compositing 13 SSW events associated with an elevated stratopause recorded between 1995 and 2013. The migrating SDT is seen to reduce in amplitude immediately after SSW onset and then return anomalously strongly around 10–17 days after the SSW onset. We conclude that changes in the underlying wind direction play a role in modulating the tidal amplitude during the evolution of SSWs and that the enhancement in the midlatitude migrating SDT (previously reported in modeling studies) is observed in the MLT at least up to 60°N.
2019