Aqpet — An R package for air quality policy evaluation

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. •'aqpet' is a toolkit that integrates auto-machine learning and augmented synthetic control method for air quality policy evaluation.•This open-source R package enables an efficient data handling, data presentation and visualisation.•'aqpet' offers user-friendly functions for non-specialists for rapid assessment.•It also provides advanced functions for data interpretation and expert analysis.•'aqpet' greatly streamlines the policy evaluation process, offering a time-efficient alternative to traditional process-based models.