Environmental Insights: Democratizing Access to Ambient Air Pollution Data and Predictive Analytics with an Open-Source Python Package

Extensive research has been conducted on predicting air pollution concentrations using various modelling frameworks [1, 2, 3, 4, 5, 6, 7, 8, 9]. However, leveraging air pollution concentration data should not be seen as a unilateral process where predictions are simply delivered to stakeholders without further engagement. Instead, an iterative approach that considers the practical use and outcomes of these predictions is crucial for refining and directing future research concerning air pollution. In response to this need, our work introduces Environmental Insights, an open-source Python package designed to facilitate active engagement with air pollution issues. This package enables stakeholders to download, analyse, and visualise air pollution concentration data, thereby offering a unified platform for exploring potential air pollution futures. Environmental Insights aims to disseminate and democratise access to air pollution data, breaking down barriers for individuals and communities without extensive resources or technical expertise. By empowering a broader audience to engage with air pollution data, the package also seeks to amplify public pressure on policymakers for meaningful air quality improvements in areas of significant concern to the community.