Aqpet — An R package for air quality policy evaluation

Yuqing Dai, Bowen Liu, Chengxu Tong, Zongbo Shi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Evaluating the effectiveness of clean air policies is important in the cycle of air quality management, ensuring policy accountability and informing future policy-making processes. However, such evaluations are challenging due to complex confounding factors such as varying weather conditions or seasonal or annual changes in air quality unrelated to the policy implementation. To address this challenge, we developed 'aqpet', a R package designed to streamline the quantification of policy effects on air quality using observational data. The package 'aqpet' includes: (1) automated-machine learning to predict air pollutants under average weather conditions – a process term as "weather normalisation"; (2) augmented synthetic control method (ASCM) to quantify the actual policy impact on air pollution. 'aqpet' offers functions for data collection and preparation, building auto-machine learning models, conducting weather normalisation, model performance evaluation and explanation, and causal impact analysis using ASCM. 'aqpet' enables fast, efficient, and interactive policy analysis for air quality management.

Original languageEnglish
Article number106052
Number of pages12
JournalEnvironmental Modelling and Software
Volume177
Early online date20 Apr 2024
DOIs
Publication statusPublished - Jun 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Keywords

  • Air quality policy evaluation
  • Augmented synthetic control
  • Machine learning
  • Observational data analysis
  • Weather normalisation

ASJC Scopus subject areas

  • Software
  • Environmental Engineering
  • Ecological Modelling

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