| 18 Aug 2025
Global biogenic isoprene emissions 2013–2020 inferred from satellite isoprene observations
Abstract. Isoprene, the most emitted biogenic volatile organic compound, exerts a remarkable influence on atmospheric oxidation capacity, air quality, and climate. Most existing top-down atmospheric estimates of isoprene emissions rely on observational formaldehyde (HCHO) as an indirect proxy, introducing substantial uncertainties due to complex and nonlinear chemical pathways. Recent advances in satellite retrievals of isoprene concentrations from the Cross-track Infrared Sounder (CrIS) enable a direct constraint on isoprene emission inversions. Yet global, multi-year isoprene-based atmospheric inversions are still lacking. Here, we present global, monthly biogenic isoprene emission maps spanning 2013–2020, derived from a mass-balance inversion framework that assimilates CrIS-retrieved isoprene columns into the LMDZ-INCA chemistry–transport model. The global biogenic isoprene emissions average is of 456 ± 200 TgC yr-1 over 2013–2020, which is broadly consistent with existing inventories and HCHO-based inversion estimates. The LMDZ-INCA simulations using this estimate of the emissions exhibit improved spatial agreement and reduced biases relative to two independent satellite HCHO retrieval products and to surface observations, confirming the robustness of this inversion framework. The seasonal cycle of emissions is dominated by the Northern Hemisphere, driven by the strong seasonality in temperature and vegetation biomes. Interannually, emissions vary by on average 14 TgC yr-1 (1-sigma standard deviation). Two major emission peaks are found in 2015–2016 (456 TgC yr-1) and 2019–2020 (478 TgC yr-1), coinciding with El Niño and widespread extreme heat-wave events, underscoring the dominant influence of temperature anomalies that increase biogenic emissions. Regional analyses identify the Amazon as the largest contributor to the interannual variability, accounting for 22.3 % of the global interannual variance in isoprene emissions. Temperature emerges as the primary driver of regional interannual emissions, with its influence modulated by leaf area index, precipitation, and radiation to varying degrees across regions. As one of the earliest attempts at a global, multi-year inversion based on isoprene observations, this dataset provides input for air quality and climate-chemistry models. The isoprene emission dataset is available at https://doi.org/10.5281/zenodo.16214776 (Hui et al., 2025).
Competing interests: At least one of the (co-)authors is a member of the editorial board of Earth System Science Data.
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This study established a mass-balance inversion framework that integrates CrIS-retrieved isoprene columns into the LMDZ-INCA chemistry-transport model to constrain global, monthly biogenic isoprene emission maps spanning 2013–2020. This represents a significant scientific contribution. Overall, I find the methodology generally sound, and particularly acknowledge the author’ thorough justification of key assumptions and parameter selections. The manuscript is well-organized and clearly written. However, there are major concerns that must be addressed before I can recommend publication.
Major Concern
The validity of inversion critically depends on demonstrating whether posterior results converge when using different prior emissions inventories. The manuscript exclusively employs LMDZ-INCA land module simulations as the prior inventory. It is imperative to conduct additional inversions using an alternative emissions inventory—ideally one mechanistically distinct from LMDZ-INCA, with differing total magnitude, spatial distribution, and seasonal variation in isoprene emissions. This test would reveal whether the inferred total isoprene emissions align with those derived using LMDZ-INCA as prior, or quantify the extent to which discrepancies between the two prior inventories are reduced.
This validation using independent prior emissions is particularly crucial because the study finds that the posterior isoprene emission seasonal cycle using LMDZ−INCA as prior is entirely reversed compared to inventories such as MEGAN (Figure3). This is a new and important conclusion but has to be addressed carefully. What seasonal cycle does the prior LMDZ-INCA itself exhibit? Would using MEGAN as prior similarly yield a reversed seasonal pattern in the inversion? Without addressing these points, the scientific robustness of the posterior emissions—especially their seasonal cycle—remains limited. Given computational constraints, this sensitivity test could be restricted to a single representative year.
Other Comments
The authors analyze the β+25%/β-40% value, with a global mean value of 0.9, to argue that the method is not sensitive to the perturbation magnitude and that the relationship between isoprene emissions and concentrations can be assumed linear. However, as seen in Figure S2, β+25%/β-40% ratios reveal substantial spatial heterogeneity. The manuscript should: