An enormous amount of air pollution data is collected worldwide and the amount of data collected continues to increase. In Europe, for example, there are thousands of measurement sites. The large bulk of this information is analysed in basic ways – often to check compliance with air quality standards and guidelines.
This situation represents a considerable missed opportunity because more insightful analysis of air pollution data can yield a much richer source of information concerning the nature of air pollution such as source identification and attribution. Improved information concerning the sources and nature of air pollution will help lead to the development of better policies for controlling air pollution.
The analysis of air pollution data can however be difficult. Often there is a lack of knowledge concerning what types of technique are available (there are many), the tools required to carry out analyses can be spread across many different types of software, or are expensive. In general, a consistent set of tools for air quality data analysis does not exist.
The openair project aims to address these issues by:
- Providing a free, open-source set of tools available to everyone
- Making available a range of existing techniques and developing new ones for the analysis of air pollution data
- Using the statistical/data analysis software R as a platform – a powerful, open-source programming language ideal for insightful data analysis
- Making it easy to carry out sophisticated analyses quickly, in an interactive and reproducible way
- Encourage the air quality community to use and help further develop these tools
The project is available as a package for the R project for statistical computing. It is led by the Environmental Research Group at King’s College London and supported by the University of Leeds.