Anthropogenic and biogenic emission modeling: implementation of meteorology dependent emissions in emission models and analysis of their impact on concentrations in chemistry transport models.
The successful candidate will join the development team responsible for the FUME emission model (www.fume-ep.org). FUME is an open source software intended primarily for the preparation of emissions for chemical transport models. As such, FUME is responsible for preprocessing the input files and the spatial distribution, chemical speciation, and time disaggregation of the primary emission inputs. The contribution of the PhD student to FUME will be the development and implementation of meteorology dependent emission modules and their testing. These will include improvements in the biogenic emission module (currently MEGAN), improvements in the module for calculating ammonia emission from live-stock and different agricultural activities, implementation of temperature dependent domestic heating module and module for wind -induced dust emissions. The implementation of module for defining sector/species based emission scenarios and improvements in overall model performance (speed) will be also part of his tasks. Finally, the candidate will focus on the assessment of the response of these emissions within a state-of-the-art chemistry transport model.
Outcome of a successful research will be advanced emission model extended with different modules for meteorology-dependent emission calculation and a detailed knowledge on how these emissions influence the final pollutant concentrations in chemistry transport model, especially during heavy air pollution events.
Modeling the contribution of primary emissions from different sources and regions to secondary pollutant concentrations: focus on secondary aerosol formation.
The numerical model representation of the formation of secondary aerosol are burdened with still high uncertainty, especially in case of the secondary organic aerosol with complicated nucleation pathways from low-volatile precursors. The successful candidate will focus on the model representation of formation of aerosol from gas-phase precursors and analyze the sensitivity of their concentrations on emission from different sectors and regions, on meteorological conditions as well as on different model parameterization of their formation from primary precursors. Apart from aerosol, the candidate will focus also on modeling benzo-α-pyrene (BaP) and identifying the contribution of different regional and local sources. Extensive comparison of model data to observations will be a crucial part of the candidate’s duties and a close cooperation with the Czech Hydrometeorological Institute and with the Institute of Chemical Process Fundamentals of the Czech Academy of Sciences is expected.
Outcome of a successful research will be and comprehensive assessment of the sources of aerosol and BaP pollution for the region of Central Europe.
will be fulfilled within the project of the Czech Technological Agency No: SS02030031 – Integrated system of research, evaluation and control of air quality. The successful candidates will join a young and ambitious research team at the Charles University and, within the project, will collaborate with other Czech research institutes (Czech Hydrometeorological Institute, Czech Academy of Sciences etc.). The Ph.D. study of the candidates will be fully funded, partly from the mentioned project and partly as a regular monthly stipendium with about net 1000 EUR/month income
(the stipendium is gradually increasing during the study – for details about the phd studies, please visit https://kfa.mff.cuni.cz/phd
1) Master-of-Science-equivalent degree in meteorology and/or environmental physics with fulfilled courses of atmospheric chemistry and physics.
2) The candidate should have good to very good experience in Unix / Linux working environments and programming skills in Python, SQL or Fortran.
3) Strong communication in English language (spoken and written)
4) Willingness to interact with an interdisciplinary science community
5) A creative mind-set for scientific research
1) Previous experience in modeling anthropogenic/biogenic emissions and air pollution transport using chemistry transport model is considered as a great advantage
2) Experience in contribution to scientific software development (preferably in Python)