CALPUFF
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Overview
- CALPUFF is a Lagrangian puff and elongated-puff (slug) model for pollutant transport & dispersion.
- CALPUFF is a multi-layer, multi-species non-steady-state puff
dispersion model that simulates the effects of time- and space-varying
meteorological conditions on pollution transport, transformation and
removal.
- CALPUFF can be applied on scales of tens to hundreds of kilometers.
- It includes algorithms for subgrid scale effects (such as terrain
impingement), as well as, longer range effects (such as pollutant
removal due to wet scavenging and dry deposition, chemical
transformation, and visibility effects of particulate matter
concentrations).
- It is one of the EPA's Preferred regulatory models
- The CALPUFF system has many major components, of which we will use four:
- CALWRF to translate WRF netCDF files into the right format for CALMET (get from version 7)
- CALMET to extract the meteorology needed to run CALPUFF (get from version 5)
- CALPUFF to do the Lagrangian puff dispersion (get from version 5)
- CALPOST to produce postprocessing graphics and statistics (get from version 6).
- And there are many more minor pre- and post-processing systems.
Used For*
- Atmospheric dispersion modeling both near (10 m) and far (many 100 km) from the pollutant-emissions source, for
- non-steady meteorology and complex topography,
- with non-steady point and area sources.
- It can handle passive tracers as well as those that react, fallout, washout, etc.
- The model produces output for averaging times of seconds to one year.
* from Wikipedia
Links for the 2024 course:
How to install CALPUFF on the UBC computer - version 2 . (written by Tim Chui)
Flow-chart diagram on selecting the best building-downwash algorithm. (created by Rei Bertoldi)
Links for the 2021 course:
Calpuff installation tips updated in 2021 by our TA Tim Chui.
Outdated installation tips from 2018.
Outdated tips from 2016: Model installation Tips, from our TA Matt.
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http://www.eos.ubc.ca/courses/atsc507/ADM/
Last updated 4 May 2024
Copyright (c) 2016, 2018, 2021, 2024 by Roland Stull.