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Satellite-derived aerosol optical depth (AOD) has been increasingly employedfor the estimation of ground-level PM2.5, which is often achieved by modelingthe relationship between AOD and PM2.5. To evaluate the accuracy of PM2.5estimation, the cross-validation (CV) technique has been widely used. Therehave been several CV-based validation approaches applied for the AOD-PM2.5models. However, the applicable conditions of these validation approaches stillremain unclear. Additionally, is there space to develop better validationapproaches for the AOD-PM2.5 models? The contributions of this study can besummarized as two aspects. Firstly, we comprehensively analyze and assess theexisting validation approaches, and give the suggestions for applicableconditions of them. Then, the existing validation approaches do not take thedistance to monitoring station into consideration. A new validation approachconsidering the distance to monitoring station is proposed in this study. Amongthe existing validation approaches, the sample-based CV is used to reflect theoverall prediction ability; the site-based CV and the region-based CV have thepotentials to evaluate spatial prediction performance; the time-based CV andthe historical validation are capable of evaluating temporal predictionaccuracy. In addition, the validation results indicate that the proposedvalidation approach has shown great potentials to better evaluate the accuracyof PM2.5 estimation. This study provides application implications and newperspectives for the validation of AOD-PM2.5 models.

Validation approaches for satellite-based PM2.5 estimation: Assessment and a new approach