: Data fusion is now an integral component of air pollution exposure assessment, enabling spatially and temporally resolved concentration estimates that enhance epidemiologic research, policy evaluation, and environmental justice assessments. By integrating ground observations, satellite data, and model simulations, these approaches improve exposure characterization beyond the limitations of individual data sources. Ongoing advances in model transparency, interpretability, and uncertainty characterization will be essential to increase the reliability and applicability of fused products. When applied appropriately, data fusion can support more robust, evidence-based decision-making and contribute to improved public health protection.
Liu et al. (Wed,) studied this question.