Skip to content
  • Submit

  • Category

  • Sort by

  • Per page

Found 10000 publications. Showing page 43 of 400:

Publication  
Year  
Category

The MetVed model: development and evaluation of emissions from residential wood combustion at high spatio-temporal resolution in Norway

Grythe, Henrik; Lopez-Aparicio, Susana; Vogt, Matthias; Vo, Dam Thanh; Hak, Claudia; Halse, Anne Karine; Hamer, Paul David; Santos, Gabriela Sousa

We present here emissions estimated from a newly developed emission model for residential wood combustion (RWC) at high spatial and temporal resolution, which we name the MetVed model. The model estimates hourly emissions resolved on a 250 m grid resolution for several compounds, including particulate matter (PM), black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) in Norway for a 12-year period. The model uses novel input data and calculation methods that combine databases built with an unprecedented high level of detail and near-national coverage. The model establishes wood burning potential at the grid based on the dependencies between variables that influence emissions: i.e. outdoor temperature, number of and type and size of dwellings, type of available heating technologies, distribution of wood-based heating installations and their associated emission factors. RWC activity with a 1 h temporal profile was produced by combining heating degree day and hourly and weekday activity profiles reported by wood consumers in official statistics. This approach results in an improved characterisation of the spatio-temporal distribution of wood use, and subsequently of emissions, required for urban air quality assessments. Whereas most variables are calculated based on bottom-up approaches on a 250 m spatial grid, the MetVed model is set up to use official wood consumption at the county level and then distributes consumption to individual grids proportional to the physical traits of the residences within it. MetVed combines consumption with official emission factors that makes the emissions also upward scalable from the 250 m grid to the national level.

The MetVed spatial distribution obtained was compared at the urban scale to other existing emissions at the same scale. The annual urban emissions, developed according to different spatial proxies, were found to have differences up to an order of magnitude. The MetVed total annual PM2.5 emissions in the urban domains compare well to emissions adjusted based on concentration measurements. In addition, hourly PM2.5 concentrations estimated by an Eulerian dispersion model using MetVed emissions were compared to measurements at air quality stations. Both hourly daily profiles and the seasonality of PM2.5 show a slight overestimation of PM2.5 levels. However, a comparison with black carbon from biomass burning and benzo(a)pyrene measurements indicates higher emissions during winter than that obtained by MetVed. The accuracy of urban emissions from RWC relies on the accuracy of the wood consumption (activity data), emission factors and the spatio-temporal distribution. While there are still knowledge gaps regarding emissions, MetVed represents a vast improvement in the spatial and temporal distribution of RWC.

2019

The MEMORI technology for movable cultural assets.

Dahlin, E.; Grøntoft, T.; Lopez-Aparicio, S.; Bellendorf, P.; Schieweck, A.; Drda-Kühn, K.; Colombini, M.P.; Bonaduce, I.; Vandenabeele, P.; Larsen, R.; Potthast, A.; Marincas, O.; Thickett, D.; Odlyha, M.; Andrade, G.; Hackney, S.; McDonagh, C.; Ackerman, J.J.

2011

The MEMORI technology - an innovative tool for the protection of movable cultural assets. Lecture Notes in Computer Science, 7616

Grøntoft, T.; Dahlin, E.

2012

The MEMORI dosimeter for indoor environment. NILU PP

Dahlin, E.; Grøntoft, T.; Lopez-Aparicio, S.; Bellendorf, P.; Wittstadt, Schieweck, A.; Drda-Kühn, K.; Perla Colombini, M.; Bonaduce, I.; Vandenabeele, P.; Larsen, R.; Poulsen Sommer, D.V.; Potthast, A.; Marincas, O.; Thickett, D.; Andrade, G.; Tabuenca, A.; Odlyha, M.; Hackney, S.; Laurenson, P.; McDonagh, C.; Ackerman, J.J.

2012

The MEMORI dosimeter for indoor environment.

Dahlin, E.; Grøntoft, T.; Lopez-Aparicio, S.; Bellendorf, P.; Wittstadt, Schieweck, A.; Drda-Kühn, K.; Perla Colombini, M.; Bonaduce, I.; Vandenabeele, P.; Larsen, R.; Poulsen Sommer, D.V.; Potthast, A.; Marincas, O.; Thickett, D.; Andrade, G.; Tabuenca, A.; Odlyha, M.; Hackney, S.; Laurenson, P.; McDonagh, C.; Ackerman, J.J.

2012

The MEMORI dosimeter - a user friendly tool for evaluation of indoor air quality for cultural heritage. NILU OR

Grøntoft, T.; Wittstadt, K.; Bellendorf, P.; Dahlin, E.; Håland, S.; Bernardo, C.; Ødegård, R.; Røen, H.V.; Heltne, T.

2012

The MEMORI dosimeter - a user friendly tool for evaluation of indoor air quality for cultural heritage. NILU F

Grøntoft, T.; Wittstadt, K.; Bellendorf, P.; Dahlin, E.; Håland, S.; Bernardo, C.; Ødegård, R.; Røen, H.V.; Heltne, T.

2012

The mass flow and proposed management of bisphenol A in selected Norwegian waste streams.

Arp, H. P. H.; Morin, N. A. O.; Hale, S. E.; Okkenhaug, G.; Breivik, K.; Sparrevik, M.

2017

The magnitude, trend and drivers of the global nitrous oxide budget: a new assessment

Tian, Hanqin; Thompson, Rona Louise; Xu, Rongting; Canadell, Josep G.; Davidson, Eric A.; Ciais, Philippe; Jackson, Robert B.; Winiwarter, Wilfried; Suntharalingam, Parvadha; Regnier, Pierre; Zhou, Feng; Janssens-Maenhout, Greet; Arneth, Almut; Li, Wei; Pan, Naiqing; Pan, Shufen; Prather, Michael J.; Raymond, Peter A.; Shi, Hao; Team, * GCP/INI Synthesis

2019

The link between springtime total ozone and summer UV radiation in Northern Hemisphere extratropics.

Karpechko, A.Yu.; Backman, L.; Thölix, L.; Ialongo, I.; Andersson, M.; Fioletov, V.; Heikkilä, A.; Johnsen, B.; Koskela, T.; Kyrölä, E.; Lakkala, K.; Myhre, C.L.; Rex, M.; Sofieva, V.F.; Tamminen, J.; Wohltmann, I.

2013

The libRadtran software package for radiative transfer calculations (version 2.0.1).

Emde, C.; Buras-Schnell, R.; Kylling, A.; Mayer, B.; Gasteiger, J.; Hamann, U.; Kylling, J.; Richter, B.; Pause, C.; Dowling, T.; Bugliaro, L.

2016

The Lagrangian particle dispersion model FLEXPART-WRF version 3.1.

Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, D.; Seibert, P.; Angevine, W.; Evan, S.; Dingwell, A.; Fast, J. D.; Easter, R. C.; Pisso, I.; Burkhart, J.; Wotawa, G.

2013

The Lagrangian particle dispersion model FLEXPART version 10.4

Pisso, Ignacio; Sollum, Espen; Grythe, Henrik; Kristiansen, Nina Iren; Cassiani, Massimo; Eckhardt, Sabine; Arnold, Delia; Morton, Don; Thompson, Rona Louise; Zwaaftink, Christine Groot; Evangeliou, Nikolaos; Sodemann, Harald; Haimberger, Leopold; Henne, Stephan; Brunner, Dominik; Burkhart, John; Fouilloux, Anne Claire; Brioude, Jerome; Philipp, Anne; Seibert, Petra; Stohl, Andreas

2020

The Lagrangian particle dispersion model FLEXPART version 10.4

Pisso, Ignacio; Sollum, Espen; Grythe, Henrik; Kristiansen, Nina Iren; Cassiani, Massimo; Eckhardt, Sabine; Arnold, Delia; Morton, Don; Thompson, Rona Louise; Zwaaftink, Christine Groot; Evangeliou, Nikolaos; Sodemann, Harald; Haimberger, Leopold; Henne, Stephan; Brunner, Dominik; Burkhart, John; Fouilloux, Anne Claire; Brioude, Jerome; Philipp, Anne; Seibert, Petra; Stohl, Andreas

The Lagrangian particle dispersion model FLEXPART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as those released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to global. In particular, inverse modeling based on source–receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, the temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing for more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing FLEXPART output data, and we briefly report on alternative FLEXPART versions.

2019

The Lagrangian particle dispersion model FLEXPART version 10.

Pisso, I.; Sollum, E.; Grythe, H.; Kristiansen, N.; Cassiani, M.; Eckhardt, S.; Thompson, R.; Zwaaftnik, C. G.; Evangeliou, N.; Hamburger, T.; Sodemann, H.; Haimberger, L.; Henne, S.; Brunner, D.; Burkhart, J.; Fouilloux, A.; Fang, X.; Phillip, A.; Seibert, P.; Stohl, A.

2017

The Kyoto Protocol: climate change.

Reimann, S.; Stordal, F. with contrib. from Ciais, P.; Goede, A.; Lazaridis, M.; Mazière, M. De, Zander, R.

2004

The Kongsfjorden system - a flagship programme for Ny-Ålesund. A concluding document from Workshop 28-31 March, 2008. Kortrapport 11/2009

Gabrielsen, G.W.; Hop, H.; Hübner, C.; Kallenborn, R.; Weslawski, J.M.; Wiencke, C. (eds.)

2009

The ISLAS2020 field campaign: studying the near-surface exchange process of stable water isotopes during the arctic wintertime

Seidl, Andrew W.; Johannessen, Aina; Dekhtyareva, Alena; Huss, Jannis M.; Jonassen, Marius Opsanger; Schulz, Alexander; Hermansen, Ove; Thomas, Christoph K.; Sodemann, Harald

The ISLAS2020 field campaign during February and March 2020 set out to obtain a unique dataset describing the Arctic water cycle using stable water isotope (SWI) observations. Our observation strategy focused on measuring evaporation, deposition, and precipitation, all of which are commonly sub-grid scale processes in numerical weather and climate models. Uncertain parameterizations for these processes can lead to compensating errors, which can go unnoticed; however, evaporation and precipitation can also be investigated with SWIs, as they are an integrated tracer for processes that atmospheric moisture has undergone. The campaign can be divided into two efforts: a localised field experiment in Ny-Ålesund focused on evaporation and deposition, and a larger precipitation collection network distributed around the Nordic Seas. The Ny-Ålesund field experiment lasted three weeks, from 23 February to 15 March 2020, with temperatures reaching below −30 °C. During these weeks, we obtained near-surface, high-resolution (approx. 20 cm) SWI profiles at two deployment sites. Using a newly developed profiling system, we measured SWI gradients in the lowermost 5 and 2 m over fjord water and snow-covered tundra, respectively. These profiles are complemented by fiber-optic distributed sensing (FODS) columns and ambient conditions from nearby meteorological stations. The FODS columns supply continuous, high-resolution (2 cm or finer) temperature profiles above both locations, whereas the meteorological stations provide information on wind speed and direction. We also made a short deployment to the Zeppelin mountain observatory (472 ma.s.l.) for measurements of the isotopic signal in the free-troposphere. Additionally, numerous water samples from the snowpack in and around Ny-Ålesund were taken, in addition to daily fjord water samples from Kongsfjorden. These samples provide the context for the surface conditions under which profiles were collected. Isotopic connections on the synoptic scale are achieved by linking Ny-Ålesund observations with precipitation sampling at locations across the European Arctic, namely Longyearbyen, Tromsø, Andenes, Ålesund, and Bergen. The resulting dataset provides comprehensive insight into the Arctic hydrological cycle and can facilitate the study of phase change processes and transport of water vapour into and out of the Svalbard region. Datasets from the field campaign are publicly available at the PANGAEA data repository (https://doi.org/10.1594/PANGAEA.971241, Seidl et al., 2024).

2026

Publication
Year
Category