In this study, a comprehensive analysis of how different aerosol types (MOD04, MOD09, and Urban Clean) affect the accuracy of atmospheric correction (AC) is conducted using Landsat 8 data acquired at 100 Aerosol Robotic Network (AERONET) sites for the first time，and some meaningful results are obtained as well.

The authors give proper credit to related work and clearly indicate their own new contribution.

The findings of the study emphasize the critical importance of aerosol-type assumptions in AC workflow. And also, a mixed strategic implementation framework that can serve as a novel concept or idea is proposed.

The description of experiments and calculations is sufficiently complete to allow their reproduction by fellow scientists since the datasets used in this work are publicly available remote sensing and ground-based observation products, and also further information about the datasets used in this study can be provided by the authors upon reasonable request.

This manuscript sits between a methods paper and an application or survey paper. Overall, the manuscript was well written, however, some of the issues (as stated below) need to be solved/ clarified:

1. As shown in Line 20 of the Abstract, “The results indicated that, in terms of aerosol optical depth (AOD), the MOD04 aerosol type exhibited the highest accuracy, with an R² of 0.762, Root Mean Square Error (RMSE) of 0.0437, and bias of 0.0876. The accuracy, precision, and uncertainty of the SR products corresponding to the three aerosol types were within the ranges of 0.00036–0.00043, 0.02382–0.02468, and 0.02337–0.02425, respectively.” These key data related to the research conclusions, such as R² of 0.762, RMSE) of 0.0437, bias of 0.0876, A(0.00036–0.00043), P(0.02382–0.02468), U(0.02337–0.02425), cannot be found in the main text (in line 439, “The total A, P, and U values for the four SR products are 0.00036–0.00377, 0.02382–0.02544, and 0.02337–440 0.2598, respectively”, Table 4 and 6?).
2. Line 156, “……after rigorous spatiotemporal matching (e.g., image selection based on site coordinates……)” Due to the significant impact of scene screening on evaluation results, please provide additional information on the spatiotemporal matching method between Landsat 8 scenes and AERONET sites in this study, as well as the quality control method for cloud detection (or explain which cloud detection product was used and how accurate it is?).
3. The Figure caption is inconsistent with the textual description in the main text.  e.g., Line 475, “Fig. 7 illustrates the results: the x-axis represents SR values within the 0-1 range, the left y-axis denotes the number of pixels (with tick marks at 10⁴, 10⁵, 10⁶, 10⁷, and 10⁸), and the right y-axis presents accuracy metrics.” Line 578, “Figure 7: A, P, and U (y left axis) and the number of pixels (y right axis) of the four surface reflectance products within the 0.1 Surface Reflectance Range.”
4. Line 476, “Gray bars denote pixel counts per interval, and the red, green, while red, green, and blue dashed lines represent A, P, and U, respectively.”   Delete “and the red, green,” ?
5. Line 584, “……as shown in Fig. 8–9…….. across different surface types.” Line 636, “Figure 8: Scatter Plot of Measured vs. 6S-Simulated SR over Building-Surface​”. Line 639, “Figure 9: Scatter Plot of Measured vs. 6S-Simulated SR over Snow-Surface​.”
6. Regarding geographical regions and land cover types, vegetation and snow cover exhibit significant seasonal and interannual variations. Will there be corresponding changes in the accuracy of aerosol types? How to conduct further evaluation?

The authors have carefully addressed all comments point by point. And there are also detailed clarifications and supplementary explanations in the revised manuscript. I am very satisfied with it.

Thank you!