Comment to “In-Tandem Multi-Waveband Particulate Absorption and Size Observations Yield Substantial Increase in Radiative Forcing over Industrial Central China”

This study combined optical particle size and multi-band in-situ BC mass and column aerosol optical depth, with MIE modeling to simulate optical properties per particle and over the atmospheric column for absorbing aerosols, providing a realistic probabilistic framework to quantify BC aging and mixing induced optical properties in industrial regions. Valuable results have been shown. In principle, I would suggest its acceptance with necessary revisions.

Line 25-26, In addition to relatively old studies, recent studies could also be cited as supporting material, such as Chen et al., (2024, doi: 10.1038/s41467-024-52255-z) for direct climate effect.  

Line 31-34, Regarding the solar radiation absorption of BC along with its impact on atmospheric thermal structure has also been examined by a recent study of Pei et al. (2025, doi: 10.5194/acp-25-10443-2025), which is also worthy to mention here.

Line 35-36, Actually, BC is not only from industrial regions, but also from natural sources such as biomass burning.

Line 39-41, The sentence could be rephrased to make it easier to follow.

Line 41-42, “properties” and “varies” cannot be used together.

Line 47-50, Gamma distribution is often used by previous studies.

Line 72, “quantification” and “estimates” cannot be used together.

Line 90, I wonder if there are many industrial areas in part countries of Global South.

Line 116, I am curious if it is right that the BC absorption is strong across various wavebands.

Line 124, Note that the Beer-Lambert law is an approximate solution to AOD, without considering multiple scattering, which might be worthy to mention?

Line 129-131, I wonder if the 2 times standard deviation threshold value is too small. I remember many studies use 3 times standard deviation threshold value. In other words, how do this threshold value affect the analysis results?

Line 137-139, please rephrase the sentence. It is currently weird with “in order to” at the end.

Line 139-140, To me, this sentence is also weird with grammar issue.

Line 160, TOA should be put behind the “top of atmosphere”

Line 170-174, How large uncertainties could this assumption introduce?

Line 187 along with other places, please check reference format to make them suitable.

Line 202, “sources” and “is” – grammar error.

Line 207, TOA has already been defined earlier in this study.

Line 211-213, Description writing issues! It seems that there are still many writing issues, with some of them pointed out here and earlier. I would suggest that the authors make a careful writing revision.

Line 215-219, Why do the authors select these three statistics?

Figure 2, I would change “orange” color to others so that it could be more clear.

Line 295-297, I understand the logic and agree the assumption, but still wonder how would this assumption affect the results?

Line 323, “can presents”?

This manuscript presents a novel and valuable integration of in-situ, multi-band, and multi-size aerosol observations with Mie modeling and radiative transfer simulations to improve constraints on BC radiative forcing over industrial Central China. The study framework is scientifically strong and the results are potentially impactful. However, several aspects require clarification and strengthening before the manuscript can be considered for publication. In particular, the authors should: (i) clearly define and justify the mixing-state assumptions used in the modeling, (ii) better situate the findings within the context of existing literature, (iii) discuss the representativeness and limitations of the study region and period, (iv) more explicitly link the theoretical framework to its practical implementation in the radiative transfer model, and (v) improve the manuscript’s structure and readability for a broader scientific audience. Additionally, a more transparent treatment of uncertainties and generalizability would further enhance the robustness of the conclusions. Addressing these points will strengthen the clarity, rigor, and interpretability of the manuscript and improve its suitability for publication.



Major comments:



1. Introduction: The introduction provides an overview of regional and global issues related to black carbon (BC) emissions, aerosol optical properties, and radiative forcing in industrial areas. The discussion of uncertainties in BC size, mixing, and optical properties is critical and well-motivated. However, the dense citation style and intermittent sentence structure reduce overall readability. Several sentences combine multiple issues and references, making it challenging to track the key point being made. So, I suggest the authors reorganize to separate conceptual motivations (i.e., why size and mixing matter) from the current limitations of models and observations, summarize the challenges in tabular or bulleted form for clarity before outlining the study aims, and clearly state the main hypothesis or focus questions at the end of the introduction.



2. Methods:



(i) Within the 'Site and Instrumentation', the data collection site is well-chosen to represent typical industrial settings with BC aerosol heterogeneity. Instrument details (Aethalometer AE-31, GRIMM-180, Microtops II) are described with relevant specifications and data cleaning protocols, which is a strength of the section. Although the temporal and spatial representativeness is asserted, but quantitative evidence is not provided (e.g., discussion of site variability or representativeness of campaign duration). The method for excluding outlier data, which uses standard deviations in five-point windows, may miss sustained measurement drifts or biases—it would be helpful to report how many data points were excluded and statistical justifications used.

(ii) Coming to the aspect of 'Mixing and Size Parameterization', the adoption of both uniform and non-uniform BC mixing state assumptions is justified and provides a valuable bracket around real-world conditions. However, the manuscript could better clarify why these two extremes are sufficient to span possible states and whether any empirical evidence supports favoring one over the other in this region. I suggest the authors to include a schematic summarizing the two mixing-state approaches for non-expert readers. Also, discuss the implications of possible intermediate mixing states, and whether the assumption of complete internal/external mixing might oversimplify actual atmospheric processes.

(iii) Mie Model and Radiative Transfer: The use of the Mie model is standard for BC optical properties. The selection of refractive indices and the matching of AOD and BC wavelengths is clear. However, the use of the Santa Barbara DISORT model (SBDART) is only briefly described, and the role of ERA-5 data for ancillary parameters is not thoroughly justified. Please provide references or validation for SBDART in similar BC-rich, high-pollution regions, and explain the implications of using spherical particle assumptions for fresh/aged BC, and discuss any associated uncertainties.

(iv) Statistical Analysis: The description of statistical metrics (RMSE, R², pointwise t-tests) is adequate. However, the direct relevance of each metric to the main questions (especially TOA radiative forcing uncertainty) could be emphasized further. Provide a table or schematic linking each metric to its interpretive role in the conclusions.



3. Results: 

(i) Physical and Optical Properties: The tri-modal size distribution finding is a significant result, offering insight into industrial area aerosol complexity. The connection drawn between combustion sources and specific size modes is plausible.​ There are some clarity issues, namely, the methods for associating emissions sources to each mode are only briefly mentioned. Is this based solely on size, or also on temporal patterns, source apportionment, or supporting chemical data? Also, the use of the term "SSA bias" is confusing in some parts; clarify whether this is bias relative to true values, model assumptions, or other studies.

(ii) Radiative Forcing Calculations: The section demonstrates a nuanced examination of size and mixing state choices on column number loading and derived radiative forcing. The sensitivity analysis using different size distributions (ISSIZE, Log123, Log1) is a highlight.​ There is an apparent contradiction between the statements about minor bias being unavoidable in any parameterization, and the claim that their trimodal framework "substantially" increases accuracy—quantifying the difference and its implications for climate modeling would clarify this issue. Also, the interpretation of SSA values and their physical meaning needs more explanation. I suggest the authors to explicitly compare results to literature or standard models (AERONET, OPAC) in a summary table. Also, discuss limitations in separating lensing effects from actual size distribution impacts.

(iii) The regression-based rapid fitting approach is interesting and potentially useful for global models. However, the generalizability of the results beyond the specific region is not tested or discussed in any detail. So, clearly state the limitations and caveats of these generalized corrections when applied to other industrial or mixed-source regions. Also, consider including an error propagation analysis.



4. Discussion and Conclusions: The discussion covers the main findings and implications for climate models and remote sensing products. Limitations of the observational period and site dependence are acknowledged, which lends credibility to the work.​ The text would greatly benefit from a graphic summary or conceptual diagram showing how the new findings could change radiative forcing estimates in global or regional models. Also, clarify to what extent the proposed framework is ready to be assimilated by existing global models, or what further validation is required.



General Recommendation:

The technical content and the novel combined observational–modeling approach are strong. However, the overall readability and logical flow of the manuscript are impeded by dense writing, long sentences, and the use of specialized terminology without immediate explanation. To improve accessibility, especially for a cross-disciplinary audience, the authors are encouraged to:

(i) Break up long paragraphs and reorganize dense sections into clearer subsections or bullet points where appropriate.

(ii) Ensure that all figures referenced in the main text are clear, interpretable, and directly support the associated discussion. In several cases, references to supplementary figures interrupt the narrative and may confuse readers; these should be streamlined.

(iii) Provide a transparent and comprehensive discussion of all potential sources of bias or uncertainty, including measurement limitations, modeling assumptions, and representativeness of the study region and period.

Addressing these issues will significantly enhance the clarity, coherence, and scientific impact of the manuscript.