the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Apr 2026
Characterization and applications of multi-decadal black carbon observations at a Mediterranean mountain site
Abstract. Long-term observations of black carbon (BC) are essential for assessing the effectiveness of air-quality and climate policies and for understanding the potential feedback of climate change. We present an 18-year dataset (2007–2024) of equivalent black carbon (eBC) mass concentration derived from the aerosol absorption coefficient measured at the Monte Cimone WMO/GAW Global Station (CMN, 2165 m a.s.l.), a key high-altitude observatory in the Mediterranean climate-change hotspot. The dataset is accompanied by detailed description of: i) the infrastructural evolution, including instrumentation and sampling system; ii) the definition of quality assurance protocol and data treatment; iii) the definition of the uncertainties. This documentation provides a comprehensive description and quantification of the data reliability over 18 years of measurements, necessary for the scientific valorisation of the dataset. Applications of the dataset demonstrate: i) a statistically significant decline in eBC concentrations over the last two decades ii) a strong linkage between eBC variability and boundary-layer dynamics when combined with ERA5 reanalysis; iii) a variable agreement with FLEXPART simulations across temporal scales, supporting its use for model evaluation. The dataset, openly available through the ITINERIS HUB, provides one of the longest continuous eBC records in the Mediterranean troposphere and represents a valuable resource for climate studies, trend assessments, and multi-station integration within ACTRIS and GAW.
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Status: open (until 29 Jul 2026)
- RC1: 'Comment on essd-2026-211', Pramod Kumar, 16 Jun 2026 reply
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RC2: 'Comment on essd-2026-211', Anonymous Referee #2, 26 Jun 2026
reply
Review of: “Characterization and application of multi-decadal black carbon observations at a Mediterranean mountain site” by Zanatta and coauthors.
This manuscript presents 18 years of eBC mass concentration data obtained from multiangle absorption photometer (MAAP). eBC data were integrated with ERA5 reanalysis and FLEXPART/CAMS regional and global transport models. Measurements were performed at CMN WMO/GAW global station (Italy).
The manuscript is well written and present a rather unique dataset of eBC data. The sources of uncertainties are properly discussed and the manuscript can be published in ESSD after some minor correction.
Below my comments:
- The authors should mention in the Introduction section the inclusion of eBC in the new Air Quality Directive to further reinforce the usefulness of this work.
- The results of the trend analysis could be compared with the trend analyses reported for eBC by Savadkoohi et al. (2023) for Europe (https://doi.org/10.1016/j.envint.2023.108081). Moreover, given that the trend analysis reported here is for the absorption coefficient divided by a constant, the reported trends could also be compared (in %/year) with those for absorption reported by Rovira et al. (2025), at least in a qualitative sense, as the total absorption in Rovira et al., 2025 is that at 370 nm.
- In relation to the comment above, it should be noted that eBC cannot be directly measured; therefore, the trends reported in the manuscript are based on absorption, since eBC is calculated using a constant MAC value of 10 m²/g over the entire period. Any change in MAC would therefore directly affect the derived eBC values. Unfortunately, EC data are not available at CMN, and the local MAC cannot be determined. While it is acknowledged that trends based on absorption normalized by a constant (i.e. eBC) are commonly reported in the literature, this limitation should be explicitly discussed in the manuscript.
- Line 97: I would use the term “pseudo-reference” for the MAAP instrument, as it cannot be a reference method.
- I do not understand what use is made of the nephelometer data in this manuscript. In Table 1, “sensor” is associated with the different nephelometer models used at CMN. Does this mean that the P, T, and RH data are taken from the nephelometer? If this is the case, only the pressure measured by the nephelometer corresponds to ambient conditions. The temperature and RH do not correspond to ambient conditions. The authors should clarify this point more clearly, as later in the manuscript it is stated that meteorological data were recorded in the sampling line.
- Lines 178–186: Rolling hourly negative values were flagged as invalid, which I agree with, even though the absorption measured at CMN is very low and negative values can therefore be expected. What is the percentage of invalid negative hourly values? How was the 1 mg/m³ threshold (defined as the difference between the 95th and 5th percentiles) selected? In my view, Level 0 data should include invalid data and calibration periods. However, I understand that these data were removed from Level 0.
- Table 2: It is indicated a MAC for dust of 16 m2/g. Please, correct.
- Line 200: raw eBC with a MAC of 6.6 m²/g is classified as Level 0, whereas eBC calculated using a MAC of 10 m²/g is classified as Level 3. This point should be clarified more clearly.
- For the period 2020-2024 AE33 data were also available. Using the simple AE source apportionment method (as e.g. Sandradewi), the authors could estimate the fossil and non-fossil contributions to BC and compare the trends calculated for this short period with the trend of eBC reported in the manuscript.
- Line 250: The pc1 of AAE calculated from fits 370-950 nm with R2>0.99 has been suggested as good indicator of AAEBC. WHich is the pc1 in your dataset?
- Line 252: Is the contribution of BrC to absorption in winter due to long-range transport? I assume that in winter CMN is mostly well above the PBL. Ori t is just due to les BrC emissions in summer?
- Line 267: How have you estimated PMdust?, as PM10-PM1?
- Line 293: How were the different cloud types distinguished?
- Line 327: The winter eBC trend shows no significant variation. What could be the reason for this? Could this be due to free-tropospheric conditions in winter, or to high noise levels in the eBC measurements in winter?
- Line 393: Please also quantify the offsets between FLEXPART and the measurements in relative terms (%), since eBC values at CMN are very low.
Citation: https://doi.org/10.5194/essd-2026-211-RC2
Data sets
Equivalent black carbon product dataset collection over Monte Cimone, Italy 2007-2024 M. Zanatta et al. https://doi.org/10.71763/itineris-hub/nfy7-yz86
Dust event identification product dataset collection over Monte Cimone, Italy 2003-2023 F. Vogel et al. https://doi.org/10.71763/xdza-fa77
ICOS ATC Meteo Release from Monte Cimone (8.0 m) P. Cristofanelli et al. https://meta.icos-cp.eu/objects/-23mwxRlF7b_gqqmw3KyhAfi
FLEXPART model tools for black carbon observed in Monte Cimone, Italy S. Eckhardt and N. Evangeliou https://doi.org/10.82160/2cgx-5f94
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- 1
This kind of work we needed for policy makers:
Characterization and applications of multi‑decadal black carbon observations at a Mediterranean mountain site” is fundamentally about turning a rare, high‑quality, long‑term BC record into a reference dataset for trends, process understanding, and model evaluation in a sensitive regional climate system.
This makes this work more specific.
I am accepting this work with some major comments, which to be addressed and incorporated in the revised version.
Abstract:
Conceptual and novelty comments on Abstract
Authors state that the dataset is “one of the longest continuous eBC records in the Mediterranean troposphere,” but you never clearly articulate what this enables that was not possible before. For a broader reader, it would help to say explicitly what new capability this record unlocks (let me make it more specific e.g., first multi‑decadal BC trend at a Mediterranean free‑tropospheric site with fully documented uncertainty).
The phrase ‘understanding the potential feedback of climate change’ is imprecise. Do you mean BC–snow/ice albedo feedback, BC–circulation interactions, or changes in transport patterns affecting BC? Either specify or drop ‘feedback’ and say ‘impacts’ or ‘responses.’
Technical and small suggestions on Abstract
Authors are mentioning an 18‑year dataset (2007–2024), but then speak of a ‘statistically significant decline … over the last two decades.’ Strictly speaking, your observation period is under 20 years. Either justify ‘two decades’ (e.g., 2005–2024 with earlier ancillary data) or rephrase to ‘over the last 18 years’ or ‘since 2007.’
‘One of the longest continuous eBC records in the Mediterranean troposphere’ is a strong claim. If Authors mean ‘Mediterranean free troposphere at high altitude’ or central Mediterranean region, it might be safer to soften that, unless you explicitly benchmark against all other Mediterranean BC time series in the paper.
As written, ‘variable agreement across temporal scales’ could be interpreted as anything from ‘acceptable’ to ‘poor.’ Consider clarifying whether this means, for example, ‘good agreement for seasonal and inter‑annual variability but weaker at daily scales,’ or similar. So authors can rephrase it for better clarity.
Authors used “i), ii), iii)” twice. It reads clearly but feels a bit heavy. Author might compress the first list (infrastructure, and uncertainties) into a single sentence to save words and give more room to applications part. This will make abstract more precise and beautiful.
Introduction:
This is too absolute. Current assessments attribute net positive effective radiative forcing to BC, while many other aerosol species (sulfate, nitrate, organic aerosol) are net cooling; however, some near‑source absorbing organic aerosol (brown carbon) also contributes to warming, and IPCC language is more nuanced.
Author can use this one instead: ‘BC is the dominant aerosol species with a positive effective radiative forcing.’
The phrasing is awkward and over‑general. PM as a whole is major; BC is a key component.
I would suggest it in this fashion: ‘BC is a key component of particulate matter linked to adverse health outcomes.’
The paragraph correctly notes that BC has generally decreased, while other species show mixed trends regionally. This is good context, but you might explicitly state why BC in the Mediterranean is particularly interesting (climate hotspot, mixture of European, North African, and shipping sources).
As in the abstract, ‘feedback’ is vague here. If Authors don’t analyse feedback mechanisms explicitly, better to say ‘climate impacts’ or ‘climate responses.’
The first three sentences are strong, but the introduction then moves quickly into ‘total aerosol’ and general aerosol processes (circulation, precipitation, heat waves, economic growth). These are relevant, yet they dilute the focus on BC and Mediterranean mountain context. Authors can add this statement for better and comprehensive
‘deviations from common trends reflect interactions of emissions and meteorology.’
Then moving faster to the role of ACTRIS/GAW and why a mountain GAW site is strategic.
The ACTRIS and GAW paragraph is excellent, but you could more explicitly position CMN as part of these global networks and one of the few long‑term BC sites in the Mediterranean.
Author mentioned ‘CAMs and FLEXPART’ only once at the end. Since they are central to your applications, consider one more clause indicating what kind of model–data questions you address (e.g., transport pathways, background levels, seasonal cycles).
As noted earlier, calling CMN ‘one of the longest continuous records of eBC in the Mediterranean troposphere’ is a strong claim. It may be safer to specify ‘at a Mediterranean high‑altitude site’ unless authors benchmark against other long records in the paper.
III. ERA5 land data is better than ERA5, Authors should have been used it, just clarify why have not gone with more fine resolution and quality meteorological reanalysis data.
3.1 Multi angle absorption photometer
Whether the inlet changes could introduce artificial shifts in the time series?
Author should mention it.
Minor language and style comments
A few phrases should be revised for clarity:
‘Thanks to its design and built-in data correction algorithm’ make it like this ‘Owing to its design and built-in correction algorithm.’
‘the instrument was object of several intercomparison’ make it to this ‘the instrument has been the subject of several intercomparison studies.’
‘fully verified’ replace with this ‘extensively evaluated’ or ‘well documented’.
‘various model of nephelometers’ replace with this ‘various models of nephelometers.’
‘temperature, relative humidity and pressure at the end of the sampling line’ better rephase with this one ‘at the downstream end of the sampling line.’
‘maintaining the total WAI at 150 LPM’ replace with this one ‘maintaining the total WAI flow at 150 L min⁻¹.’
‘after which, pressure, temperature and relative were measured’ should be ‘after which pressure, temperature, and relative humidity were measured.’
‘through the various inlet systems’ should be ‘through different inlet systems’ or ‘through the inlet systems listed in Table 1’.
The text needs substantial polishing for grammar, terminology, and internal consistency.
If available, Authors should also mention these:
Next sub-section:
Figure 1: Add one study area map as subplot in figure 1. This will make your title stronger and more easer to follow for the reader.
Increase the font size for better readability of the figures.
Section 4.3.1 Assumption of mass absorption cross-section:
A few notes
Change “assumed a constant value” to sound more formal and precise.
Replace “in turns” with “in turn”.
Replace “as function of the season” with “with the season” / “seasonal changes”.
Change “background station as CMN” to “a remote mountain station such as CMN”.
If Authors should make this section a bit more cautious, which could be slightly soften the last part:
With this one:
‘The geometric standard deviation (1.33) associated with the European MAC value suggests an uncertainty of approximately +30% and −25% in the derived eBC mass concentration.’
Section 4.3.2
Authors can cite this article as well;
https://acp.copernicus.org/articles/24/11585/2024/
Section 4.3.3
Define the dust-day screening more clearly,
Explain the MAC choice,
State the wavelength of the absorption estimate, and frame the dust contribution as an approximate attribution rather than a definitive separation.
Comments on supporting materials:
Figure S1: If possible, Authors can add radiation data for the more comprehensive outcomes.
Figure S5: In Figure S5c Y-axis should be (eBC) rather than Planetary boundary layer height [m asl]. Correct it.
Figure S6: In the winter FLEXPART result is over-estimates while in the summer its under-estimates. why? Discuss the limitation of the model.
Note: Added comments in the additional pdf-MS hilighted. (please follow pdf as well)