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vein - Vehicular Emissions Inventories

Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.

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atmoschematmospheric-chemistryatmospheric-scienceatmospheric-sciencesemissionsemissions-modelvehicular-emissions-inventoriesveinopenmp

8.74 score 51 stars 138 scripts 629 downloads

eixport - Export Emissions to Atmospheric Models

Emissions are the mass of pollutants released into the atmosphere. Air quality models need emissions data, with spatial and temporal distribution, to represent air pollutant concentrations. This package, eixport, creates inputs for the air quality models 'WRF-Chem' Grell et al (2005) <doi:10.1016/j.atmosenv.2005.04.027>, 'MUNICH' Kim et al (2018) <doi:10.5194/gmd-11-611-2018> , 'BRAMS-SPM' Freitas et al (2005) <doi:10.1016/j.atmosenv.2005.07.017> and 'RLINE' Snyder et al (2013) <doi:10.1016/j.atmosenv.2013.05.074>. See the 'eixport' website (<https://atmoschem.github.io/eixport/>) for more information, documentations and examples. More details in Ibarra-Espinosa et al (2018) <doi:10.21105/joss.00607>.

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atmospheric-modelsatmospheric-scienceemissionsexporting-emissionswrf

5.81 score 29 stars 90 scripts 292 downloads

pega - Pollutants Emissions and Gaseous of the Atmosphere

Elaboration of fix emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in <doi:>. Before using PEGA you need to know the industrial composition of your study area, in other words, the combination of industrial type, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.

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5.43 score 3 stars 395 scripts

EmissV - Tools for Create Emissions for Air Quality Models

Processing tools to create emissions for use in numerical air quality models. Emissions can be calculated both using emission factors and activity data (Schuch et al 2018) <doi:10.21105/joss.00662> or using pollutant inventories (Schuch et al., 2018) <doi:10.30564/jasr.v1i1.347>. Functions to process individual point emissions, line emissions and area emissions of pollutants are available as well as methods to incorporate alternative data for Spatial distribution of emissions such as satellite images (Gavidia-Calderon et. al, 2018) <doi:10.1016/j.atmosenv.2018.09.026> or openstreetmap data (Andrade et al, 2015) <doi:10.3389/fenvs.2015.00009>.

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atmosatmospheric-chemistryatmospheric-modellingatmospheric-modelsatmospheric-scienceemissionswrf-chem

5.34 score 46 stars 12 scripts 292 downloads

rtorf - Observations, Footprints and Receptors ('rtorf') and HYSPLIT Configuration Tools

Ingest, process, and visualize atmospheric observation data, specifically tailored for the NOAA Global Monitoring Laboratory (GML) ObsPack GLOBALView+ products <https://gml.noaa.gov/ccgg/obspack/index.html>. Includes specialized routines for filtering trace gas time-series data based on meteorological and quality control parameters. Additionally, streamlines the generation of configuration files for the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model <https://www.ready.noaa.gov/HYSPLIT.php>, supporting high-throughput parallel processing of trajectory simulations.

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glibcopenmp

5.17 score

respeciate - Speciation profiles for gases and aerosols

Access to the air pollutant emission profiles in US EPA SPECIATE (v5.2) and EU JRC SPECIEUROPE archives. More details in Simon et al (2010) doi:10.5094/APR.2010.026 and Pernigotti et al (2016) doi:10.1016/j.apr.2015.10.007, respectively.

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2.18 score 3 stars 2 scripts