pollucheck v1.0, A package to explore open-source air pollution data

Summary

Air pollution impacts human health, quality of living, climate, and the economy. To assess its impact and facilitate mitigation actions, quantification of air pollution is vital. Measurements are the most accurate way of quantifying air pollution. Many countries conduct regulatory measurements of various air pollutants (e.g., fine and respirable particulate matter, nitrogen dioxide, sulfur dioxide, and surface ozone) and make the data available publicly.

Air pollution data sets typically span several seasons or years and real-time data are recorded typically every hour or at a higher frequency. With the ever increasing amount of data and number of data providers, there is a clear need for tools to handle, analyze, and visualize large data sets. The current Shiny app pollucheck aims at a simple workflow to generate a suite of statistical plots and summary statistics. Users do not need any programming background to analyze time series data and generate a variety of plots.

pollucheck can handle real-time pollution and co-located meteorological data (if available) from the three most popular open-source air pollution databases: OpenAQ, AirNow, and Indian Central Pollution Control Board (CPCB) dashboard. While CPCB data are specific to Indian regulatory monitoring stations, OpenAQ hosts the global open-source pollution databases and AirNow hosts the global PM~2.5~ (mass concentration of particulate matter with an aerodynamic diameter less than or equal to 2.5 microns) data, collected under the United States Embassy and Consulates' air quality monitoring programmes.

The output of pollucheck is displayed in seven tabs. Different packages used for building pollucheck include tidyverse, openair, shiny, bslib, forecast, biwavelet, readxl, DT, data.table, nortest, and zoo.