| 30 Apr 2026
A simplified isoprene oxidation mechanism for fast global chemistry transport modeling and emission inversion
Abstract. We introduce the Simplified Isoprene Chemistry for MAGRITTE (SICMA), a compact chemical mechanism designed for computationally efficient global chemistry transport modeling and adjoint-based emission inversions. The scheme reduces the isoprene oxidation network of the MAGRITTEv1.2 model from 93 organic species and 243 reactions to four organic species and five lumped reactions. The SICMA parameters (rate coefficients and product yields) are optimized using box-model simulations across multiple NOx regimes to reproduce cumulative formaldehyde (HCHO) production and HOx concentrations from the full mechanism. The simplified scheme successfully captures the NOx-dependent branching of isoprene oxidation and reproduces HCHO production and oxidant recycling with high fidelity. Implemented in the global MAGRITTE model, SICMA reproduces the monthly HCHO vertical columns from the full chemistry run within 10 % over most continental regions. Larger discrepancies occur over boreal forests and remote oceans, mainly due to the simplified treatment of monoterpene oxidation and organic nitrate chemistry. Despite these simplifications, the seasonal cycle and spatial distribution of HCHO columns remain in close agreement with both the full chemistry simulation and TROPOMI observations. Inversions of isoprene emissions constrained by TROPOMI HCHO columns yield nearly identical global totals when using SICMA or the full chemistry (568.0 and 568.4 Tg yr-1, respectively). SICMA therefore provides a robust and computationally efficient alternative to detailed isoprene mechanisms for large-scale modeling and emission inversion applications.
Review of Oomen et al. 2026
This is an interesting and well written evaluation paper of the SIMCA reduced chemical complexity mechanism for the degradation of isoprene. Oomen et al. first detail the development of the reduced chemical mechanism from the MAGRITTE v1.2 mechanism including the box model experiments used to derive the key parameters. They then compare the performance of the SIMCA mechanism in a full CTM simulation to that of a corresponding simulation using the MAGRITTE v1.2 mechanism. Finally, they use inversion techniques and TROPOMI observations of formaldehyde columns to derive new spatial estimates for isoprene emissions.
Overall, this is a good study but before it is considered for publication several key areas need to be addressed and I detail these below.
Please note that as emission inversions are not my area of expertise, I have not evaluated the inversion setup (Section 3.3) in detail.
Major Comments
Parameter optimisation – a fixed temperature of 298 K is used in all box model simulations. While this is a sensible daily mean value for the tropics, the 1,6-H shift of the isoprene is highly temperature dependent (as you capture with your large exponent for R4). How did you derive this temperature dependence if you weren’t changing the temperature in the box model?
Please explain how you forced the concentration of isoprene to follow a diurnal profile in the box modelling. Does this run this risk that, as there is a fixed source of isoprene, that any feedbacks between oxidants and isoprene, which could be different between the mechanisms, are suppressed?
The role of monoterpene chemistry is an important feature of the SIMCA chemistry and needs greater explanation. As I interpret it, while the SIMCA mechanism has no explicit monoterpene chemistry, it implicitly includes a 10:1 ratio of isoprene to monoterpene emissions and this is captured in the fitted parameters. Therefore, its parameters (Table 3) are not describing an isoprene-only situation, but an isoprene + monoterpene situation where the monoterpene concentration is ~10% of the isoprene concentration. If this is correct, this needs to be made much clearer in the abstract and throughout the main text.
Further on this topic, in the CTM evaluation in Section 5 the MAGRITTE v1.2 simulation uses 439 Tg yr-1 of isoprene emissions and the 108 Tg yr-1 of monoterpene emissions. However, SIMCA has no monoterpene chemistry so only uses the 439 Tg yr-1 of isoprene emissions with remaining 108 Tg yr-1 “accounted for” by SIMCA’s chemistry. Is that correct? If so, this needs to be made clear.
When looking at the boreal OH high bias in SIMCA (relative to MAGRITTE), would it be better correct to saying that SIMCA is effectively underestimating monoterpenes in this region (since, as you say, monoterpene/isoprene emissions >> 0.1 here)? I am surprised that the higher local NOx, due to lack of isoprene and monoterpene nitrate formation in SIMCA, doesn’t lead to higher O3 in the region since there should be plentiful isoprene. Could you explain this?
While I broadly agree with the framework for parameter optimisation, the one major omission is the lack of an isoprene nitrate or PAN-type species to act as a surrogate for NOx-reservoir species. To their credit, the authors highlight in several places the problems this omission causes. I will not ask the authors to redo the optimisation, but it is imperative that they mention in their concluding statements that a high priority for further SIMCA development is the inclusion of a nitrate term.
The choice to optimise for HCHO production makes sense given that one of the aims of the SIMCA mechanisms is to be used to generate new isoprene emission estimates. However, there are other important species whose performance needs to be evaluated in more detail if the second aim of the SIMCA mechanism, that of being a feasible alternative mechanism to MAGRITTE v1.2 for chemical transport modelling, is to be met. Specifically, the following evaluation should be done as a minimum and included in the revised manuscript’s main text.
In addition, most researchers would expect the production of ozone or ozone burden to the most useful constraint metric, not formaldehyde production. I am not saying your choice is wrong but please explain in more detail the decision not to use ozone burden/production as a target.
While you note that the inversion-derived emissions are very similar using the SIMCA and MAGRITTE v1.2 scheme and that they are 30% higher than the MEGAN emissions, there is no further analysis on the reason for this difference. Given that it is very large, I would like to see some explanation for why both mechanisms need a lot more isoprene to optimise HCHO column performance. Could it potentially be a bias in the NOx emissions being used?
I also think more explanation should be given to the spatial differences in the estimated emissions using the SIMCA and MAGRITTE mechanisms. While the global totals are very similar, the spatial differences are substantial in fractional, and in some places like the Congo or western Amazonia, in absolute terms.
Minor Comments
Line 21 - please make it clear to what “its” corresponds. I suspect it is isoprene but the preceding sentence references biogenic VOCs.
Figure 6 - I think there is a standard from term (e.g. x 1015) missing on the y axis.
Please add the equivalent of Figure 7 for the SIMCA inversion, i.e. specifically 7(b) and 7(c) so that a side by side comparison can be made. Also make clear the bwr colourbar has a logarithmic scale and consider if you can “zoom” in (i.e. I don’t think it is necessary to go from 0.1 to 10) so that the magnitude of changes are easier to identify.
Please give an indication of the decreases to model runtime and compute on switching from MAGRITTE v1.2 to SIMCA.
On line 228 you reference Fig 2c for OH but OH is Fig 2d. I note also that Fig 2d, as it is right now doesn’t present evidence for lower nighttime OH as all OH lines are ~ zero. You will need a log plot to make this argument.