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New GRAL 24.11 version

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   The new GRAL version 24.11 has been released, bringing important bug fixes, enhanced visualisations, and new features that improve the overall user experience. This update addresses issues in odour percentile calculations and source group management, introduces expanded export options, and changes the installation process to offer greater flexibility. The software remains open source, with its full code available on GitHub for those interested in exploring it further.

   The release of GRAL 24.11 has sparked considerable interest among users of this atmospheric dispersion model. This version not only fixes bugs that previously affected the stability of certain functions but also adds visual and technical improvements that could transform how the tool is used in scientific and professional contexts. For those relying on GRAL, the update presents an opportunity to explore new capabilities and enhance their analyses.

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New guideline on assessment of odour exposure by using dispersion modelling is looking for volunteers and contributors.

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odour dispersion guideline   A new development on the first worldwide guideline on the assessment of odour exposure by using dispersion modelling will take its first steps. At this stage, there are many initiatives related to dispersion modelling worldwide but there is no specific guideline for odour modelling to our knowledge. This is an initiative promoted by several experts in the area of modelling that will be led by Mr. Günther Schauberger and Ms. Jennifer Barclay. First meeting will take place the 27th of August.

  Modelling odours is complex and many of the guidelines on modelling published around the world fall short in treating this vector. Modelling odours often requires to forget about traditional dispersion modelling operating modes and to focus on exposure. Odours are perceived in seconds or minutes, not hours and this is key in calculating its impact on ambient air. Most odour incidents are generated during calm or very low wind speeds which do not facilitate the dispersion of an odour and that makes modelling challenging. Last, but not least, there is a need to investigate the role of Instrumental Odour Monitoring Systems (IOMS) on the evaluation of model performance.

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New Visualization and Analytical Capabilities for Emission Assessment in Scentroid SIMS3

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   Scentroid has introduced several improvements to its SIMS3 platform, enhancing the accuracy of emission plume visualization, integrating new monitoring hardware, and refining analytical tools for more robust odour event assessment. These updates aim to provide more reliable representations of atmospheric dispersion patterns and improve data interpretation in environmental monitoring applications.

   Recent developments in the Scentroid SIMS3 system focus on upgrading how emission plumes are modelled and displayed. The standard heatmap representation has been replaced by a custom visualization engine that ensures higher spatial resolution and stability at all zoom levels. This modification eliminates clustering effects common in dense measurement networks and provides better definition near emission sources, particularly under variable meteorological conditions. The result is a more consistent and realistic depiction of dispersion dynamics, improving the interpretation of odour and pollutant transport in complex environments.

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