With the ever-increasing global measurements of air pollutants (through stationary, mobile, low-cost, and satellite monitoring), the amount of data being collected is huge and necessitates the use of management platforms. In an effort to address this issue, we developed two Shiny applications to analyse and visualise air-pollution data.
‘mmaqshiny’, now on CRAN, is aimed at handling, calibrating, integrating, and visualising spatially and temporally acquired air-pollution data from mobile monitoring campaigns. Currently, the application caters to data collected using specific instruments. With just the click of a button, even non-programmers can generate summary statistics, time series, and spatial maps. The application is capable of handling high-resolution data from multiple instruments and formats. Moreover, it also allows users to visualize data at near-real time and helps in keeping a tab on data quality and instrument health.
Our second Shiny application (currently in the development phase) is specific to India, and allows users to handle open-source air-quality datasets available from OpenAQ (https://openaq.org/#/countries/IN?_k=5ecycz), CPCB (https://app.cpcbccr.com/ccr/#/caaqm-dashboard-all/caaqm-landing), and AirNow (https://www.airnow.gov/international/us-embassies-and-consulates/#India). Users can visualize data, perform basic statistical operations, and generate a variety of publication-ready plots. It also provides outlier detection and replacement of fill/negative values. We have also integrated the popular openair package in this application.
Adithi is a Geospatial Analyst at ILK Labs Bangalore, India. She loves automating things and making a code, simple to use. Developer and maintainer of mmaqshiny. She is also a co-founder and co-organiser of R-Ladies Bangalore and a peer reviewer for the Journal of Open Source Software.