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Chemistry and Aerosol","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"PartMC: Particle-resolved Monte Carlo code for atmospheric aerosol simulation\n======\n![PartMC](https://raw.githubusercontent.com/wiki/compdyn/partmc/logo.svg)\n\n[![Latest version](https://img.shields.io/github/tag/compdyn/partmc.svg?label=version)](https://github.com/compdyn/partmc/blob/master/ChangeLog.md) [![Documentation](https://img.shields.io/badge/docs-GitHub%20Pages-blue)](https://compdyn.github.io/partmc/) [![Docker build status](https://img.shields.io/docker/automated/compdyn/partmc.svg)](https://hub.docker.com/r/compdyn/partmc/builds/) [![Github Actions Status](https://github.com/compdyn/partmc/actions/workflows/main.yml/badge.svg?branch=master)](https://github.com/compdyn/partmc/actions/workflows/main.yml) [![License](https://img.shields.io/github/license/compdyn/partmc.svg)](https://github.com/compdyn/partmc/blob/master/COPYING) [![DOI](https://zenodo.org/badge/24058992.svg)](https://zenodo.org/badge/latestdoi/24058992) [![Coverage Status](https://codecov.io/gh/compdyn/partmc/branch/master/graph/badge.svg)](https://app.codecov.io/gh/compdyn/partmc)\n\nVersion 2.8.0  \nReleased 2024-02-23\n\n**Repository:** \u003chttps://github.com/compdyn/partmc\u003e\n\n**Documentation:**:\n- [Homepage](https://compdyn.github.io/partmc);\n- [Input file format description](https://compdyn.github.io/partmc/input_format.html);\n- [Output file format description](https://compdyn.github.io/partmc/output_format.html);\n- [Diagram of modules and dependencies](https://compdyn.github.io/partmc/module_diagram.html);\n- [Description of code conventions and style](https://compdyn.github.io/partmc/coding_style.html);\n- [Publications about PartMC](https://compdyn.github.io/partmc/publications.html).\n\n**Cite as:** M. West, N. Riemer, J. Curtis, M. Michelotti, and J. Tian (2024) PartMC, [![version](https://img.shields.io/github/release/compdyn/partmc.svg?label=version)](https://github.com/compdyn/partmc), [![DOI](https://zenodo.org/badge/24058992.svg)](https://zenodo.org/badge/latestdoi/24058992)\n\nCopyright (C) 2005-2024 Nicole Riemer and Matthew West  \nPortions copyright (C) Andreas Bott, Richard Easter, Jeffrey Curtis,\nMatthew Michelotti, and Jian Tian  \nLicensed under the GNU General Public License version 2 or (at your\noption) any later version.  \nFor details see the file COPYING or\n\u003chttp://www.gnu.org/licenses/old-licenses/gpl-2.0.html\u003e.\n\n**Selected references:**\n\n   * N. Riemer, M. West, R. A. Zaveri, and R. C. Easter (2009)\n     Simulating the evolution of soot mixing state with a\n     particle-resolved aerosol model, _J. Geophys. Res._ 114(D09202),\n     \u003chttp://dx.doi.org/10.1029/2008JD011073\u003e.\n   * N. Riemer, M. West, R. A. Zaveri, and R. C. Easter (2010)\n     Estimating black carbon aging time-scales with a\n     particle-resolved aerosol model, _J. Aerosol Sci._ 41(1),\n     143-158, \u003chttp://dx.doi.org/10.1016/j.jaerosci.2009.08.009\u003e.\n   * R. A. Zaveri, J. C. Barnard, R. C. Easter, N. Riemer, and M. West\n     (2010) Particle-resolved simulation of aerosol size, composition,\n     mixing state, and the associated optical and cloud condensation\n     nuclei activation properties in an evolving urban plume,\n     _J. Geophys. Res._ 115(D17210),\n     \u003chttp://dx.doi.org/10.1029/2009JD013616\u003e.\n   * R. E. L. DeVille, N. Riemer, and M. West (2011) Weighted Flow\n     Algorithms (WFA) for stochastic particle coagulation,\n     _J. Comp. Phys._ 230(23), 8427-8451,\n     \u003chttp://dx.doi.org/10.1016/j.jcp.2011.07.027\u003e\n   * J. Ching, N. Riemer, and M. West (2012) Impacts of black carbon\n     mixing state on black carbon nucleation scavenging: Insights from\n     a particle-resolved model, _J. Geophys. Res._ 117(D23209),\n     \u003chttp://dx.doi.org/10.1029/2012JD018269\u003e\n   * M. D. Michelotti, M. T. Heath, and M. West (2013) Binning for\n     efficient stochastic multiscale particle simulations, _Multiscale\n     Model. Simul._ 11(4), 1071-1096,\n     \u003chttp://dx.doi.org/10.1137/130908038\u003e\n   * N. Riemer and M. West (2013) Quantifying aerosol mixing state\n     with entropy and diversity measures, _Atmos. Chem. Phys._ 13,\n     11423-11439, \u003chttp://dx.doi.org/10.5194/acp-13-11423-2013\u003e\n   * J. Tian, N. Riemer, M. West, L. Pfaffenberger, H. Schlager, and\n     A. Petzold (2014) Modeling the evolution of aerosol particles in\n     a ship plume using PartMC-MOSAIC, _Atmos. Chem. Phys._ 14,\n     5327-5347, \u003chttp://dx.doi.org/10.5194/acp-14-5327-2014\u003e\n   * R. M. Healy, N. Riemer, J. C. Wenger, M. Murphy, M. West,\n     L. Poulain, A. Wiedensohler, I. P. O'Connor, E. McGillicuddy,\n     J. R. Sodeau, and G. J. Evans (2014) Single particle diversity\n     and mixing state measurements, _Atmos. Chem. and Phys._ 14,\n     6289-6299, \u003chttp://dx.doi.org/10.5194/acp-14-6289-2014\u003e\n   * J. H. Curtis, M. D. Michelotti, N. Riemer, M. Heath, and M. West\n     (2016) Accelerated simulation of stochastic particle removal\n     processes in particle-resolved aerosol models, _J. Comp. Phys._\n     322, 21-32, \u003chttp://dx.doi.org/10.1016/j.jcp.2016.06.029\u003e\n   * J. Ching, N. Riemer, and M. West (2016) Black carbon mixing state\n     impacts on cloud microphysical properties: Effects of aerosol\n     plume and environmental conditions, _J. Geophys. Res._ 121(10),\n     5990-6013, \u003chttp://dx.doi.org/10.1002/2016JD024851\u003e\n   * J. Ching, J. Fast, M. West, and N. Riemer (2017) Metrics to\n     quantify the importance of mixing state for CCN activity, _Atmos.\n     Chem. and Phys._ 17, 7445-7458,\n     \u003chttp://dx.doi.org/10.5194/acp-17-7445-2017\u003e\n   * J. Tian, B. T. Brem, M. West, T. C. Bond, M. J. Rood, and\n     N. Riemer (2017) Simulating aerosol chamber experiments with the\n     particle-resolved aerosol model PartMC, _Aerosol Sci. Technol._\n     51(7), 856-867, \u003chttp://dx.doi.org/10.1080/02786826.2017.1311988\u003e\n   * J. H. Curtis, N. Riemer, and M. West (2017) A single-column\n     particle-resolved model for simulating the vertical distribution\n     of aerosol mixing state: WRF-PartMC-MOSAIC-SCM v1.0,\n     _Geosci. Model Dev._ 10, 4057-4079,\n     \u003chttp://dx.doi.org/10.5194/gmd-10-4057-2017\u003e\n   * J. Ching, M. West, and N. Riemer (2018) Quantifying impacts of\n     aerosol mixing state on nucleation-scavenging of black carbon\n     aerosol particles, _Atmosphere_ 9(1), 17,\n     \u003chttp://dx.doi.org/10.3390/atmos9010017\u003e\n   * M. Hughes, J. K. Kodros, J. R. Pierce, M. West, and N. Riemer\n     (2018) Machine learning to predict the global distribution of\n     aerosol mixing state metrics, _Atmosphere_ 9(1), 15,\n     \u003chttp://dx.doi.org/10.3390/atmos9010015\u003e\n   * R. E. L. DeVille, N. Riemer, and M. West (2019) Convergence of a\n     generalized Weighted Flow Algorithm for stochastic particle\n     coagulation, _Journal of Computational Dynamics_ 6(1), 69-94,\n     \u003chttp://dx.doi.org/10.3934/jcd.2019003\u003e\n   * N. Riemer, A. P. Ault, M. West, R. L. Craig, and J. H. Curtis\n     (2019) Aerosol mixing state: Measurements, modeling, and impacts,\n     _Reviews of Geophysics_ 57(2), 187-249,\n     \u003chttp://dx.doi.org/10.1029/2018RG000615\u003e\n   * C. Shou, N. Riemer, T. B. Onasch, A. J. Sedlacek, A. T. Lambe,\n     E. R. Lewis, P. Davidovits, and M. West (2019) Mixing state\n     evolution of agglomerating particles in an aerosol chamber:\n     Comparison of measurements and particle-resolved simulations,\n     _Aerosol Science and Technology_ 53(11), 1229-1243,\n     \u003chttp://dx.doi.org/10.1080/02786826.2019.1661959\u003e\n   * J. T. Gasparik, Q. Ye, J. H. Curtis, A. A. Presto, N. M. Donahue,\n     R. C. Sullivan, M. West, and N. Riemer (2020) Quantifying errors\n     in the aerosol mixing-state index based on limited particle\n     sample size, _Aerosol Science and Technology_ 54(12), 1527-1541,\n     \u003chttp://dx.doi.org/10.1080/02786826.2020.1804523\u003e\n   * Z. Zheng, J. H. Curtis, Y. Yao, J. T. Gasparik, V. G. Anantharaj,\n     L. Zhao, M. West, and N. Riemer (2021) Estimating submicron\n     aerosol mixing state at the global scale with machine learning\n     and earth system modeling, _Earth and Space Science_ 8(2),\n     e2020EA001500, \u003chttp://dx.doi.org/10.1029/2020EA001500\u003e\n\n\nRunning PartMC with Docker\n==========================\n\nThis is the fastest way to get running.\n\n* **_Step 1:_** Install [Docker Community Edition](https://www.docker.com/community-edition).\n    * On Linux and MacOS this is straightforward. [Download from here](https://store.docker.com/search?type=edition\u0026offering=community).\n    * On Windows the best version is [Docker Community Edition for Windows](https://store.docker.com/editions/community/docker-ce-desktop-windows), which requires Windows 10 Pro/Edu.\n\n* **_Step 2:_** (Optional) Run the PartMC test suite with:\n\n        docker run -it --rm compdyn/partmc bash -c 'cd /build; make test'\n\n* **_Step 3:_** Run a scenario like the following. This example uses `partmc/scenarios/4_chamber`. This mounts the current directory (`$PWD`, replace with `%cd%` on Windows) into `/run` inside the container, changes into that directory, and then runs PartMC.\n\n        cd partmc/scenarios/4_chamber\n        docker run -it --rm -v $PWD:/run compdyn/partmc bash -c 'cd /run; /build/partmc chamber.spec'\n\nIn the above `docker run` command the arguments are:\n\n- `-it`: activates \"interactive\" mode so Ctrl-C works to kill the command\n- `--rm`: remove temporary docker container files after running\n- `-v LOCAL:REMOTE`: mount the `LOCAL` directory to the `REMOTE` directory inside the container\n- `compdyn/partmc`: the docker image to run\n- `bash -c 'COMMAND'`: run `COMMAND` inside the docker container\n\nThe directory structure inside the docker container is:\n\n    /partmc           # a copy of the partmc git source code repository\n    /build            # the diretory in which partmc was compiled\n    /build/partmc     # the compiled partmc executable\n    /run              # the default diretory to run in\n\n\nDependencies\n============\n\nRequired dependencies:\n\n   * Fortran 2003 compiler - \u003chttps://gcc.gnu.org/fortran/\u003e or similar\n   * CMake version 2.6.4 or higher - \u003chttp://www.cmake.org/\u003e\n   * NetCDF version 4.2 or higher -\n     \u003chttp://www.unidata.ucar.edu/software/netcdf/\u003e\n\nOptional dependencies:\n\n   * CAMP chemistry code - \u003chttps://github.com/open-atmos/camp\u003e\n   * MOSAIC chemistry code version 2012-01-25 - Available from Rahul\n     Zaveri - \u003cRahul.Zaveri@pnl.gov\u003e\n   * MPI parallel support - \u003chttp://www.open-mpi.org/\u003e\n   * GSL for random number generators -\n     \u003chttp://www.gnu.org/software/gsl/\u003e\n   * SUNDIALS ODE solver for condensation support -\n     \u003chttp://www.llnl.gov/casc/sundials/\u003e\n   * gnuplot for testcase plotting - \u003chttp://www.gnuplot.info/\u003e\n\n\nInstallation\n============\n\n1. Install cmake and NetCDF (see above). The NetCDF libraries are\n   required to compile PartMC. The `netcdf.mod` Fortran 90 module file\n   is required, and it must be produced by the same compiler being\n   used to compile PartMC.\n\n2. Unpack PartMC:\n\n        tar xzvf partmc-2.8.0.tar.gz\n\n3. Change into the main PartMC directory (where this README file is\n   located):\n\n        cd partmc-2.8.0\n\n4. Make a directory called `build` and change into it:\n\n        mkdir build\n        cd build\n\n5. If desired, set environment variables to indicate the install\n   locations of supporting libraries. If running `echo $SHELL`\n   indicates that you are running `bash`, then you can do something\n   like:\n\n        export NETCDF_HOME=/\n        export MOSAIC_HOME=${HOME}/mosaic-2012-01-25\n        export SUNDIALS_HOME=${HOME}/opt\n        export GSL_HOME=${HOME}/opt\n\n   Of course the exact directories will depend on where the libraries\n   are installed. You only need to set variables for libraries\n   installed in non-default locations, and only for those libraries\n   you want to use. Everything except NetCDF is optional.\n\n   If `echo $SHELL` instead is `tcsh` or similar, then the environment\n   variables can be set like `setenv NETCDF_HOME /` and similarly.\n\n6. Run cmake with the main PartMC directory as an argument (note the\n   double-c):\n\n        ccmake ..\n\n7. Inside ccmake press `c` to configure, edit the values as needed,\n   press `c` again, then `g` to generate. Optional libraries can be\n   activated by setting the `ENABLE` variable to `ON`. For a parallel\n   build, toggle advanced mode with `t` and set the\n   `CMAKE_Fortran_COMPILER` to `mpif90`, then reconfigure.\n\n8. Optionally, enable compiler warnings by pressing `t` inside ccmake\n   to enable advanced options and then setting `CMAKE_Fortran_FLAGS`\n   to:\n\n        -O2 -g -fimplicit-none -W -Wall -Wconversion -Wunderflow -Wimplicit-interface -Wno-compare-reals -Wno-unused -Wno-unused-parameter -Wno-unused-dummy-argument -fbounds-check\n\n8. Compile PartMC and test it as follows.\n\n        make\n        make test\n\n9. To run just a single test do something like:\n\n        ctest -R bidisperse   # argument is a regexp for test names\n\n10. To see what make is doing run it like:\n\n        VERBOSE=1 make\n\n11. To run tests with visible output or to make some plots from the\n    tests run them as follows. Note that tests often rely on earlier\n    tests in the same directory, so always run `test_1`, then\n    `test_2`, etc. Tests occasionally fail due to random sampling, so\n    re-run the entire sequence after failures. For example:\n\n        cd test_run/emission\n        ./test_emission_1.sh\n        ./test_emission_2.sh\n        ./test_emission_3.sh            # similarly for other tests\n        gnuplot -persist plot_species.gnuplot # etc...\n\n12. To run full scenarios, do, for example:\n\n        cd ../scenarios/1_urban_plume\n        ./1_run.sh\n\n\nUsage\n=====\n\nThe main `partmc` command reads `.spec` files and does the run\nspecified therein. Either particle-resolved runs, sectional-code runs,\nor exact solutions can be generated. A run produces one NetCDF file\nper output timestep, containing per-particle data (from\nparticle-resolved runs) or binned data (from sectional or exact\nruns). The `extract_*` programs can read these per-timestep NetCDF\nfiles and output ASCII data (the `extract_sectional_*` programs are\nused for sectional and exact model output).\n\nPython bindings\n===============\n\nThe [PyPartMC](https://github.com/open-atmos/PyPartMC) project offers\npip-installable Python bindings to PartMC. Both source and binary\npackages are available and ship with all PartMC dependencies included.\nPyPartMC exposes internal components of PartMC (utility routines and \nderived types) which then can serve as building blocks to develop PartMC \nsimulations in Python. Time stepping can be performed either using the\ninternal PartMC time-stepper or externally within a Python loop. The\nlatter allows to couple the simulation with external Python components\nin each timestep. PyPartMC features examples developed as Jupyter notebooks.\nSnippets of code provided in the README file depict how to use PyPartMC \nfrom Julia (using PyCall.jl) and Matlab (using Matlab's built-in Python bridge).\n","funding_links":[],"readme_doi_urls":["http://dx.doi.org/10.1029/2008JD011073","http://dx.doi.org/10.1016/j.jaerosci.2009.08.009","http://dx.doi.org/10.1029/2009JD013616","http://dx.doi.org/10.1016/j.jcp.2011.07.027","http://dx.doi.org/10.1029/2012JD018269","http://dx.doi.org/10.1137/130908038","http://dx.doi.org/10.5194/acp-13-11423-2013","http://dx.doi.org/10.5194/acp-14-5327-2014","http://dx.doi.org/10.5194/acp-14-6289-2014","http://dx.doi.org/10.1016/j.jcp.2016.06.029","http://dx.doi.org/10.1002/2016JD024851","http://dx.doi.org/10.5194/acp-17-7445-2017","http://dx.doi.org/10.1080/02786826.2017.1311988","http://dx.doi.org/10.5194/gmd-10-4057-2017","http://dx.doi.org/10.3390/atmos9010017","http://dx.doi.org/10.3390/atmos9010015","http://dx.doi.org/10.3934/jcd.2019003","http://dx.doi.org/10.1029/2018RG000615","http://dx.doi.org/10.1080/02786826.2019.1661959","http://dx.doi.org/10.1080/02786826.2020.1804523","http://dx.doi.org/10.1029/2020EA001500"],"works":{"http://dx.doi.org/10.1029/2008JD011073":{"id":"https://openalex.org/W3102231179","doi":"https://doi.org/10.1029/2008jd011073","title":"Simulating the evolution of soot mixing state with a particle‐resolved aerosol model","display_name":"Simulating the evolution of soot mixing state with a particle‐resolved aerosol model","publication_year":2009,"publication_date":"2009-05-05","ids":{"openalex":"https://openalex.org/W3102231179","doi":"https://doi.org/10.1029/2008jd011073","mag":"3102231179"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1029/2008jd011073","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2008JD011073","source":{"id":"https://openalex.org/S207178839","display_name":"Journal of Geophysical Research","issn_l":"0148-0227","issn":["2156-2202","0148-0227","0272-7528"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310315809","host_organization_name":"American Geophysical Union","host_organization_lineage":["https://openalex.org/P4310315809"],"host_organization_lineage_names":["American Geophysical Union"],"type":"journal"},"license":null,"version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2008JD011073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022554777","display_name":"Nicole Riemer","orcid":"https://orcid.org/0000-0002-3220-3457"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225","https://openalex.org/I2801919071"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"N. 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