The manuscript deals with an important and often discussed topic, the multiple scattering correction factor “C” and related size effects reported for aethalometers. The authors present new data from laboratory and field experiments. The data analysis is well-founded and reproducible. The results are discussed in detail and the relevant literature is well reviewed.

The results are important for the community to compare light absorption or equivalent soot content across measurement networks and also as a basis for calibrating the Aethalometer AE33.

General comment:

MWAA and MAAP are used as references. As this is crucial to the work, further information is needed to justify the suitability of these instruments as references, since they are filter-based techniques. Specifically, has it been demonstrated that the size dependence is negligible for their use as references? Please comment on this.

Specific comments:

Section 2.1. Experimental setup

The manuscript focuses primarily on observation rather than a detailed discussion of the reasons for size dependence. According to Moteki et al. (2010) and Nakayama et al. (2010), the reason for size dependence is the penetration depth of the particles, which is a function of sampling face velocity. The datasets collected at CMN and CESAM use data from AEE collected at different flow rates (see Table 2). Could the differences in flow rate influence the C factors of CMN and CESAM?

3.1.1 Loading correction, lines 310 to 319  

Since the DUAL spot correction factors require some time to adapt to new aerosol types, it is advantageous when changing aerosols to first load one spot and then analyze only the following spots. Another different approach used in this study is data post-processing. In addition to the existing compensation methods for single spot instruments, the dual spot aethalometer method could be used with a constant compensation factor determined by an adjustment procedure. This would have the advantage of not requiring the introduction of a new correction function. The best-fitting compensation parameter should also be given, as it could be helpful for future studies on the dependence of the compensation parameter on the aerosol type.

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A single scattering albedo of equal to 1.0 is probably due to measurement noise. Values below the lower limit of babs for C determination should be removed.

Figure 5 and related text: Is the geometric mean diameter of the number size distribution the best indicator of “size”? Are there other moments of the size distribution that better capture the proportion of soot in the total aerosol? These could possibly be more consistent with the laboratory results. 

This manuscript addresses an important and timely topic regarding filter absorption photometers, which is of considerable interest to the atmospheric science community. The study is well contextualized, and the authors justify their results with relevant literature. The focus on the influence of particle size on the multiple scattering correction factor (C factor) is valuable. However, as mentioned in the conclusions, the study explores the broader role of aerosol properties on C variability, and not only particle size. If the intention were to limit the scope exclusively to particle size, the manuscript would require significant restructuring to address this aspect in more detail.

Specific comments:

Abstract: The statement that C characterization is “poorly understood” is not entirely accurate. As the authors themselves note, there is a growing body of recent literature on this topic. The recent study by Yus-Díez et al. (2025), which provides a comprehensive analysis of C factor, should be considered for the interpretation of the present results.

Use of MAAP as a reference instrument: The reliance on MAAP as a reference instrument is questionable. Yus-Díez et al. (2025) demonstrated that MAAP can overestimate absorption coefficients by ~47%, which directly affects the estimation of eBC and MAC. The authors should explicitly discuss this limitation and justify their approach, considering these known biases.

Lines 231–236: This section is currently confusing for the reader. It should be rewritten with improved clarity to better explain the intended message.

The study presents a detailed analysis of C factor characterization, but the conclusions could be clearer in showing why these findings matter. In particular, the authors should expand on the broader relevance of their work:

Since Aethalometers are widely used in monitoring networks, what do these results mean for improving data quality and ensuring comparability across sites?

Do the results provide recommendations to narrow the variability in C factor estimates, and how generalizable are they across instruments and locations?

The discussion could better balance the value of controlled chamber experiments with the ambient measurements, which include complex, mixed-source aerosols. Since monitoring is done under ambient conditions, it would be important to highlight how representative and applicable the results are in these real-world settings.