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 normalization"; (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 normalization, model performance evaluation and explanation, and causal impact analysis using ASCM. 'aqpet' enables fast, efficient, and interactive policy analysis for air quality management.