CITATION.cff

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cff-version: 1.2.0
title: Environmental Insights
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Liam
    family-names: Berrisford
    email: liberrisford@gmail.com
    affiliation: University of Exeter
    orcid: 'https://orcid.org/0000-0001-6578-3497'
identifiers:
  - type: doi
    value: 10.1016/j.envsoft.2024.106131
repository-code: 'https://github.com/berrli/Environmental-Insights'
abstract: >-
  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.
keywords:
  - Air Pollution
  - 'Machine Learning '
  - Predictive Analytics