Environmental Insights: Democratizing access to ambient air pollution data and predictive analytics with an open-source Python package - Berrisford, Liam J.; Menezes, Ronaldo (Environmental modelling & software : with environment data news, 2024)
Ambient air pollution is a pervasive issue with wide-ranging effects on human health, ecosystem vitality, and economic structures. Utilizing data on ambient air pollution concentrations, researchers can perform comprehensive analyses to uncover the multifaceted impacts of air pollution across society. To this end, we introduce Environmental Insights, an open-source Python package designed to democratize access to air pollution concentration data. This tool enables users to easily retrieve historical air pollution data and employ a Machine Learning model for forecasting potential future conditions. Moreover, Environmental Insights includes a suite of tools aimed at facilitating the dissemination of analytical findings and enhancing user engagement through dynamic visualizations. This comprehensive approach ensures that the package caters to the diverse needs of individuals looking to explore and understand air pollution trends and their implications. Environmental Insights Github Home Page. •Machine Learning allows for a novel lightweight air pollution model to be developed to democratize predictive analytics.•Comprehensive analysis and visualization tools within the package enhance stakeholder engagement and public understanding of air pollution concentrations.•Demonstrates applications of the Environmental Insights python package in designing soft and hard interven-tions for air pollution management, emphasizing public health and policy implications.•Highlights the way forward for a community-driven platform for feedback and ongoing development, ensuring the tool meets the evolving needs of researchers, policymakers, and the public.