1 - 5 of 5
rss atomLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
  • Grundström, Maria
    et al.
    SMHI, Samhällsplanering.
    Asker, Christian
    SMHI, Research Department, Meteorology.
    Segersson, David
    SMHI, Research Department, Meteorology.
    Alpfjord Wylde, Helene
    SMHI, Samhällsplanering.
    van Dongen, Eef
    SMHI, Samhällsplanering.
    Jakobsson, Mattias
    SMHI, Samhällsplanering.
    Windmark, Fredrik
    SMHI, Samhällsplanering.
    High resolution air quality modelling of NO2, PM10 and PM2.5 for Sweden: A national study for 2019 based on dispersion modelling from regional down to street canyon level2023Report (Other academic)
    Abstract [en]

    In this development project, concentrations of NO2, PM10 and PM2.5 have been calculated for the whole of Sweden for the year 2019. Simulations have been made with a new methodology that enables an almost completely seamless combination of dispersion modelling on three scales; regional, urban and street scale, without double counting emissions. Pollution levels have been calculated at 50x50 m2 resolution, which provides a complete and detailed dataset at a national level. The spatial resolution of 50 m captures concentration gradients important for high-resolution exposure calculations. A strength of using dispersion models to calculate pollutant levels is the direct connection to emission inventories and projections.New functionality, parameterizations and inputs have been developed with the goal of increasing the performance of model calculations while preserving storage capacity. This is crucial to be able to carry out a comprehensive national modelling with a high geographical resolution. Parameterizations and detailed input data have been developed to better represent the real dispersion conditions, the physical environment and the size of emissions from, for example, traffic.For NO2, high levels are seen in urban environments near roads with high traffic load, and exceedances of the air quality limit values are seen in several locations. The number of exceedances of current air quality standards are relatively low for PM10. Levels of PM2.5 are often low and no exceedances of current standards occur at all. In a future perspective with stricter requirements for clean air, the situation will likely be different. With potentially stricter limit values there is a risk for exceedances in the several Swedish municipalities, especially for PM10.The validation of the modelling results compared to measurements has shown that modelling quality objectives are achieved for PM2.5 at both urban and local traffic stations. For NO2 and PM10, the modelling quality objectives are not met. The model underperforms at a number of stations and the 90 % requirement is thus not achieved. The RDE indicator is however fulfilled for several stations except for NO2 at traffic stations where the margin to fulfilment was very close. Further investigation of these sites is required and should be prioritized to understand the causes and improve modelled concentrations. Model performance, memory and storage capacity remain a major challenge for performing high-resolution calculations efficiently. Work on this also needs to be prioritised in future projects.The national modelling results constitute a national description of the current state of air quality in which all of Sweden's municipalities are included. The dataset facilitates the identification of locations where air pollution levels are at risk of exceeding threshold values for air quality standards and environmental quality objectives. This can be of great help to municipalities that lack measurements and modelling of air pollution and supports the work with Swedish air pollution assessment and mitigation. A comprehensive national assessment is especially important to have available when the updated EU Ambient Air Quality Directive, with stricter requirements for clean air, is implemented in the coming years. The dataset can also support the design of measurement networks, selection of measurement site locations and provide valuable information to experts and researchers as well as an interested public. The results will be made freely available on the SMHI web portal “Luftwebb” by the turn of the year 2023/2024.

    Download full text (pdf)
    High resolution air quality modelling of NO2, PM10 and PM2.5 for Sweden
  • Yazgi, Daniel
    et al.
    SMHI, Research Department, Meteorology.
    Olenius, Tinja
    SMHI, Research Department, Meteorology.
    J-GAIN v1.1: a flexible tool to incorporate aerosol formation rates obtained by molecular models into large-scale models2023In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 16, no 17, p. 5237-5249Article in journal (Refereed)
    Download full text (pdf)
    J-GAIN v1.1: a flexible tool to incorporate aerosol formation rates obtained by molecular models into large-scale models
  • Dieterich, Christian
    et al.
    SMHI, Research Department, Oceanography.
    Radtke, Hagen
    Higher quantiles of sea levels rise faster in Baltic Sea Climate projections2024In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894Article in journal (Refereed)
    Download full text (pdf)
    Higher quantiles of sea levels rise faster in Baltic Sea Climate projections
  • Raza, Auriba
    et al.
    Partonen, Timo
    Hanson, Linda Magnusson
    Asp, Magnus
    SMHI, Samhällsplanering.
    Engström, Erik
    SMHI, Samhällsplanering.
    Westerlund, Hugo
    Halonen, Jaana, I
    Daylight during winters and symptoms of depression and sleep problems: A within-individual analysis2024In: Environment International, ISSN 0160-4120, E-ISSN 1873-6750, Vol. 183, article id 108413Article in journal (Refereed)
    Download full text (pdf)
    Daylight during winters and symptoms of depression and sleep problems: A within-individual analysis
  • Nielsen, J. M.
    et al.
    Van de Beek, Remco
    SMHI, Research Department, Hydrology.
    Thorndahl, S.
    Olsson, Jonas
    SMHI, Research Department, Hydrology.
    Andersen, C. B.
    Andersson, Jafet
    SMHI, Research Department, Hydrology.
    Rasmussen, M. R.
    Nielsen, J. E.
    Merging weather radar data and opportunistic rainfall sensor data to enhance rainfall estimates2024In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 300, article id 107228Article in journal (Refereed)
    Download full text (pdf)
    Merging weather radar data and opportunistic rainfall sensor data to enhance rainfall estimates