| 08 Apr 2026
ORACLE-lite (v3.0): A reduced-complexity module for simulating organic aerosol formation and evolution in long term chemistry-climate simulations
Abstract. The representation of organic aerosol (OA) in global chemistry–climate models remains computationally challenging due to the large number of volatility-resolved tracers required to simulate gas–particle partitioning and aging. We present ORACLE-lite (v3.0), a reduced-complexity version of the ORACLE module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model, specifically designed for multi-decadal simulations. ORACLE-lite preserves the core mechanisms governing OA formation while employing the minimum number of surrogate tracers required to represent organic compounds across the principal volatility classes, including low-volatility (LVOC), semi-volatile (SVOC), intermediate-volatility (IVOC), and volatile organic compounds (VOC). This structured reduction lowers the computational cost per model time step by a statistically robust speed-up of 13.9 ± 1.1 %, enabling efficient multi-decadal simulations while maintaining a dynamic representation of volatility evolution. ORACLE-lite is evaluated in a 21-year global simulation (2000–2020) and compared against the standard ORACLE configuration. The simplified volatility basis set modifies gas–particle partitioning, leading to enhanced primary organic aerosol (POA) concentrations of up to 5 µg m-3 over major biomass-burning and industrial regions, while secondary organic aerosol (SOA) concentrations decrease over biomass-burning regions and increase over anthropogenic source regions due to differences in precursor allocation among volatility bins. Model performance is assessed against long-term aerosol mass spectrometer (AMS) and aerosol chemical speciation monitor (ACSM) observations across North America, Europe, and Eastern Asia. Simulated total OA agrees well with observations over North America (normalized mean bias, NMB = −4 %) and Eastern Asia (NMB = −29 %), while larger seasonal biases occur in Europe, particularly in winter. Over tropical and subtropical regions, the model shows an overall underestimation (NMB ≈ −39 %) with substantial regional variability. Across all regions, the model reproduces the observed spatial distribution and seasonal variability of OA mass and its primary and secondary components within a factor of two for the majority of sites. These results demonstrate that ORACLE-lite provides a computationally efficient and physically grounded framework capable of reproducing the key features of global OA variability, making it suitable for long-term chemistry–climate simulations.
This work documents a newly-developed model (ORACLE-lite) for organic aerosol with simplified representation of organic aerosol volatility and aging chemistry and embedded as a module in the global model ECHAM/MESSy, and further demonstrates the model’s ability to improve computational efficiency (in comparison to a previous version of the ORACLE model) and to capture observed OA/POA/SOA concentrations across the globe. Several model deficiencies demanding further strengthening are identified (e.g., aqueous SOA formation). Overall, this works represents a concrete step of advancement of the ECHAM/MESSy-ORACLE modeling system, which has continuously progressed over the past decade. There is no major issue from this reviewer and publication is recommended if the following comments can be addressed.
1. In Figure 1, change “Sort Term” to “Short Term”
2. In Figure 2, the meaning of SOA-sv/SOA-iv/SOA-v are not immediately clear; would be helpful to add a legend.
3. In Line 190-191, the authors used the term “emission factor”, which is confusing, because what the authors really mean is the emission ratio of I/S/LVOCs to the traditional emission factor of POA. Please revise the text here.
4. In Line 235, it is stated that “only homogeneous gas-phase aging is included”. Since the ECHEM-MESSy-ORACLE system is intended for long-term global simulations, wouldn’t heterogeneous oxidation have a substantial impact on this spatial and temporal scale (Hodzic et al., 2016)? If the authors agree, please acknowledge this as an issue for future improvement in the Conclusions Section.
5. In Figure 4a, there seems to be some hotspots of OA in Canada. Are there any justifications for these hotspots? There seems to be no discussion of it in the current text.
6. In Figure 4b, the OA prediction from ORACLE-lite differs significantly from the prediction from ORACLE-base, mainly due to a change of volatility bins used to represent POA. Since it is not definite which representation (ORACLE-lite or ORACLE-base) is better, which results should be trusted more? Please elaborate and add to the text.
7. In Section 3.2.1, there lacks a description of the modeling configuration; that is, what emission inventories and meteorological fields (if any) are used. Are the emission inventories up-to-date?
8. In Section 3.2.1, it is stated that “Overall, the model reproduces the large-scale spatial variability of OA across regions, with most locations showing agreement within a factor of two”, which is not substantiated by the data shown in Figure 6 alone. Therefore, the reviewer suggests that Figure 6 and Figure 7 be combined to form a single Figure, so that the scatter plots can be visible alongside the relevant text.
9. In Section 3.2.1, it is not clear whether the model-measurement comparison is on basis of annual average or 20-year average. Please clarify early in this section.
10. In Line 523, “key missing SOA formation pathways” is mentioned; thus, a comprehensive discussion of the missing pathways should include auto-oxidation of larger molecules (e.g., monoterpenes) to rapidly form extremely low volatility organic compounds (Bianchi et al., 2019).
11. In Line 99, the ORACLE-lite model is described as “standalone”. If so, would it be valuable for the OA model to be configured as a 0-dimension box model to simulate laboratory experiments in the literature to further validate model predictions in an isolated setting? Please consider this possibility and discuss it in the Conclusions Section.
References:
Bianchi, F., Kurtén, T., Riva, M., Mohr, C., Rissanen, M. P., Roldin, P., Berndt, T., Crounse, J. D., Wennberg, P. O., Mentel, T. F., Wildt, J., Junninen, H., Jokinen, T., Kulmala, M., Worsnop, D. R., Thornton, J. A., Donahue, N., Kjaergaard, H. G., and Ehn, M.: Highly Oxygenated Organic Molecules (HOM) from Gas-Phase Autoxidation Involving Peroxy Radicals: A Key Contributor to Atmospheric Aerosol, Chem. Rev., 119, 3472–3509, https://doi.org/10.1021/acs.chemrev.8b00395, 2019.
Hodzic, A., Kasibhatla, P. S., Jo, D. S., Cappa, C. D., Jimenez, J. L., Madronich, S., and Park, R. J.: Rethinking the global secondary organic aerosol (SOA) budget: stronger production, faster removal, shorter lifetime, Atmos. Chem. Phys., 16, 7917–7941, https://doi.org/10.5194/acp-16-7917-2016, 2016.