Jing-Kai Xue

Physics-Regularized Operator Learning for Hourly Mapping of Near-Surface Air Pollution under Sparse Observations

Hourly air-pollution fields are needed for exposure assessment and air-quality management; however, ground monitors are sparse, and satellite observations are intermittent. Data-driven models may reproduce station observations while leaving unmonitored regions poorly constrained. This mismatch raises a central concer...