Skip to contents

AirVeg

AirVeg is a set of tools to import, analyse and validate air quality and meteorological data, both from numerical simulations and observations. The package has been developed in the framework of the VEG-GAP project and all the initial development choices have been taken by taking into account the needs of the participant to the project.

AirVeg is currently maintained by Simularia and it is free open source software.

Credits

This packages has been partially developed with the financial contribution of ENEA within the framework of VEG-GAP Project - LIFE18 PRE IT 003. For further information visit the VEG-GAP project website.

Installation

AirVeg is currently not on CRAN, therefore you have to install it from the repository on GitLab:

install.packages("remotes")
remotes::install_gitlab(repo="simularia/veg-gap/airveg", dependencies = TRUE)

Alternatively, you can download the zip archive of the sources and install them like that:

remotes::install_local(path="airveg-master.zip", dependencies = TRUE)

To install the development version:

remotes::install_gitlab(repo="simularia/veg-gap/airveg@develop", dependencies = TRUE)

All dependencies are automatically installed from CRAN.

Brief description

AirVeg is a collection of tools to pre and post process data from air quality models, meteorological models and measurements.

A full description of each function included in the package is provided in the integrated help. For example, type:

? nc_get_variable

to see the corresponding documentation, with full details, arguments description and examples.

The whole set of included functions is logically organized in five main groups.

  1. Read and import data from NetCDF binary archives

This group of functions are included in the netcdfutils.R file:

nc_deadlines()
nc_dimensions()
nc_extract()
nc_get_CRS()
nc_get_variable()
nc_summary()
nc_variables()

All the functions are compatible with input files in Climate and Forecast (CF) convention and with I/O API used by CMAQ.

  1. Read and import data and metadata from measurements and point-like dataset.

Two subsets of functions are provided. In the observations.R file, functions are provided to deal with measurements:

import_EEA()
import_data_EEA()
import_data_arpameteo()
import_data_brace()
import_metadata_EEA()
import_metadata_arpameteo()
import_metadata_brace()
download_data_EEA()
download_metadata_EEA()

In the models.R source file, functions are provided to read data from the postbin tool used in the VEG-GAP project:

import_data_postbin()
import_metadata_postbin()
import_postbin()
  1. Data processing and other utilities

The following functions are included in the time_series.R file:

timeAggregation()
check_validity()
check_aggregation_validity()

The following utilities are included in the utils.R file:

ppb2ugm3()
projectCoordinates()
season()
windDir()
  1. Statistical scores and other statistical functions

The following functions are included in the stats.R file:

aot40f()
aot40v()
bias()
computeMode()
corr()
countComplete()
fac2()
fb()
ioa()
mage()
mange()
maxRunningValue()
mfb()
mfe()
mqi()
mqi_year()
nmse()
rmse()
rmsu()
runningEightHoursMean 
unc_year()
  1. Graphical output

The following functions are included in the graphics.R file:

boxPlot()
buglePlot()
contourPlot()
scatterPlot()

Contributing

All contributions, in any form, are welcome!

To submit new features just open a pull request in the main repo on gitlab. For any other reason, bug report, feature request, etc. file an issue.