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FUME 2.0 – Flexible Universal processor for Modeling Emissions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00585895" target="_blank" >RIV/67985807:_____/24:00585895 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11320/24:10489285

  • Result on the web

    <a href="https://doi.org/10.5194/gmd-17-3867-2024" target="_blank" >https://doi.org/10.5194/gmd-17-3867-2024</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5194/gmd-17-3867-2024" target="_blank" >10.5194/gmd-17-3867-2024</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    FUME 2.0 – Flexible Universal processor for Modeling Emissions

  • Original language description

    This paper introduces FUME 2.0, an open-source emission processor for air quality modeling, and documents the software structure, capabilities, and sample usage. FUME provides a customizable framework for emission preparation tailored to user needs. It is designed to work with heterogeneous emission inventory data, unify them into a common structure, and generate model-ready emissions for various chemical transport models (CTMs). Key features include flexibility in input data formats, support for spatial and temporal disaggregation, chemical speciation, and integration of external models like MEGAN. FUME employs a modular Python interface and PostgreSQL/PostGIS backend for efficient data handling. The workflow comprises data import, geographical transformation, chemical and temporal disaggregation, and output generation steps. Outputs for mesoscale CTMs CMAQ, CAMx, and WRF-Chem and the large-eddy-simulation model PALM are implemented along with a generic NetCDF format. Benchmark runs are discussed on a typical configuration with cascading domains, with import and preprocessing times scaling near-linearly with grid size. FUME facilitates air quality modeling from continental to regional and urban scales by enabling effective processing of diverse inventory datasets.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10509 - Meteorology and atmospheric sciences

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Geoscientific Model Development

  • ISSN

    1991-959X

  • e-ISSN

    1991-9603

  • Volume of the periodical

    17

  • Issue of the periodical within the volume

    9

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    12

  • Pages from-to

    3867-3878

  • UT code for WoS article

    001222533900001

  • EID of the result in the Scopus database

    2-s2.0-85193542888