the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 May 2026
A Revised Framework for Classifying Organic Aerosols using Wavelength-dependent Absorption Properties
Abstract. The representation of organic aerosols (OA) in global climate models fails to account for the wide range of species found in the atmosphere. Previous studies have observed that the optical parameters of OA species vary depending on the source from which they are emitted, as well as on their physical and chemical characteristics. However, accounting for all OA species in climate models is not practical. Hence, we have grouped OA species according to their optical parameters and physico-chemical characteristics. We classified OA as strongly absorbing brown carbon (S-BrC), moderately absorbing brown carbon (M-BrC), weakly absorbing brown carbon (W-BrC) and very weakly absorbing brown carbon (VW-BrC). We defined thresholds based on the imaginary refractive index (IRI) for a broad wavelength range from 300 to 550 nm. The classification demonstrates clear optical separation at 350–500 nm, with mass absorption coefficient (MAC) values spanning two orders of magnitude from VW-BrC (0.004 m2/g) to S-BrC (1 m2/g) at 400 nm. Representative species from each category were suggested as surrogates. This choice of species includes both absorbing and scattering OA and enables more accurate representation of OA in climate models and satellite retrievals, improving aerosol radiative forcing estimates.
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- RC1: 'Comment on egusphere-2026-1917', Anonymous Referee #1, 15 Jun 2026 reply
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CC1: 'Comment on egusphere-2026-1917', Jing Li, 17 Jul 2026
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This manuscript presents a timely and scientifically valuable framework that addresses a long-standing deficiency in global climate models: the oversimplification of organic aerosol optical properties. By synthesizing literature data across the 300 to 550 nm shortwave spectral region, the authors categorize OA into four distinct brown carbon (BrC) classes based on imaginary refractive index (IRI) thresholds: strongly absorbing (S-BrC), moderately absorbing (M-BrC), weakly absorbing (W-BrC), and very weakly absorbing (VW-BrC). The translation of these IRI thresholds into mass absorption coefficient (MAC) and single scattering albedo (SSA) spaces using Mie theory, along with the identification of specific surrogate species (e.g., tarballs, SRFA, toluene- and limonene-derived SOAs) for the upcoming Table of Aerosol Optics (TAO) database, provides a practical roadmap for modelers. The manuscript is logically structured and clearly highlights the severe limitations of legacy databases like OPAC. However, to maximize the scientific rigor and atmospheric applicability of this framework, the authors should address several methodological and conceptual issues before publication.
Major Comments
- The authors define specific IRI and MAC thresholds to separate the four BrC classes across different wavelengths (e.g., S-BrC defined as IRI > 0.03 at 550 nm). However, the manuscript lacks a quantitative explanation of how these precise numerical boundaries were established.
- Please clarify whether these cutoffs were derived from statistical clustering (e.g., k-means or quantile distributions) of the compiled literature data or if they correspond to specific physicochemical transitions (e.g., changes in volatility, O:C ratios, or aromaticity).
- At 300 nm, the MAC classification boundaries converge tightly (0.8–1.84 m²/g for W-BrC, 1.84–2.38 m²/g for M-BrC, and 2.38–3.5 m²/g for S-BrC), which the authors rightly note limits discriminating power. A sensitivity analysis demonstrating how slight shifts in these boundary thresholds impact top-of-atmosphere direct radiative forcing calculations would significantly strengthen the justification for these specific groupings.
- The introduction and methodology correctly acknowledge that OA optical properties evolve due to atmospheric processing and oxidation. In the real atmosphere, BrC undergoes rapid photochemical aging, where strong absorbers can photobleach into weak absorbers over hours to days, or where secondary chromophores form via NOx-facilitated pathways (as noted for toluene SOA).
- The current framework classifies discrete, static surrogates into fixed categories. How do the authors envision 3D Eulerian climate models implementing dynamic transitions between these classes during atmospheric transport?
- Providing a conceptual discussion or a recommended parameterization timescale for how an S-BrC or M-BrC particle might chemically transition into a W-BrC or VW-BrC particle during aging would greatly enhance the framework's utility for chemical transport modeling.
Minor and Technical Comments
- In Section 3.3, the authors note that while IRI values show four distinct categories at 300 nm, the computed MAC values converge and show minimal separation. Because MAC depends explicitly on the lognormal size distribution parameters and particle density applied in Equations (1) through (6), please clarify how much of this MAC convergence at 300 nm is driven by the intrinsic optical properties versus variations in the adopted median radii and geometric standard deviations listed in Table 1.
- The observation in Section 3.3 that OPAC systematically underestimates absorption for water-soluble and water-insoluble organics (S-BrC and M-BrC) while overestimating absorption for biogenic SOA (VW-BrC) is a critical finding. It would be beneficial to add a brief discussion on how these competing biases might interact in global models. For example, in biomass-burning plumes where S-BrC dominates, legacy OPAC assumptions likely cause severe underestimations of shortwave atmospheric heating rates, whereas in pristine biogenic environments, OPAC may artificially inflate aerosol absorption.
- In Section 4.1, the authors rightly note that the IRI of VW-BrC above 400 nm and W-BrC above 500 nm falls below the AERONET detection limit shown in Figure 1. To increase the practical impact of this observation, briefly discuss how remote sensing retrieval algorithms might handle these low-absorption regimes without defaulting to pure scattering assumptions, which currently propagate systematic biases in aerosol radiative forcing estimates.
- In Table 6, surrogate species are assigned specific complex refractive indices at discrete 50 nm intervals. Please clarify in the text whether the upcoming TAO database will provide continuous spectral parameterizations (e.g., polynomial fits or dispersion models across the wavelength continuum) or if climate models will be expected to linearly interpolate between these discrete 50 nm wavelength steps.
This revised framework represents a substantial step forward in organizing the optical complexity of organic aerosols for the climate modeling community. By tightening the quantitative justification for the classification thresholds and explicitly addressing how models should handle atmospheric aging, this work will serve as an indispensable reference for both modelers and observationalists. To help me tailor any further recommendations for the revised manuscript, could you clarify whether your primary target audience for the TAO database implementation is global climate modelers running coarse-grid radiative transfer codes, or regional chemical transport modelers attempting to resolve high-resolution aerosol aging dynamics?
Citation: https://doi.org/10.5194/egusphere-2026-1917-CC1 - The authors define specific IRI and MAC thresholds to separate the four BrC classes across different wavelengths (e.g., S-BrC defined as IRI > 0.03 at 550 nm). However, the manuscript lacks a quantitative explanation of how these precise numerical boundaries were established.
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The manuscript presents a revised framework for classifying organic aerosols based on wavelength-dependent absorption properties. By compiling refractive index data from previous studies and translating the proposed IRI thresholds into MAC and SSA space, the authors attempt to provide a practical optical classification scheme for organic aerosols and brown carbon. The topic is relevant to aerosol-radiation interactions, climate-model parameterization, and satellite retrieval applications. The manuscript is generally well structured, and the effort to extend previous BrC classification concepts from a single reference wavelength to a broader spectral range is valuable. However, several issues need to be addressed before the manuscript can be considered for publication.