Abstract
The current environmental legal system primarily focuses on environmental pollution and ecological damage, yet it does not adequately address climate change as an environmental risk issue. Consequently, environmental law struggles to directly respond to air pollution and climate change. Due to the complexity of air pollution regulation, there is a need for legal frameworks that extend beyond conventional environmental pollution controls. The advent of "AI + Big Data" has provided new momentum and opportunities for predicting and improving air quality. This paper, viewed through the lens of environmental law and based on the policy of the National Big Data Comprehensive Experimental Zone, combined with the Difference-in-Differences (DID) model, outlines the impact mechanisms of Big Data and Artificial Intelligence in empowering air quality prediction and improvement. It also explores the path choices for achieving the objectives of accuracy and effectiveness in air quality prediction from the perspective of environmental law.
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