Hamer et al. applied the land surface model and satellite products to reconstruct the BVOC emission across Europe. Overall, the study is very interesting. However, the manuscript still suffers from some weaknesses. I recommend the manuscript for publication on ESSD after the following comments have been well addressed.

1. The manuscript clearly presents two new BVOC emission datasets, but it did not state how these datasets advance beyond existing ones (e.g., CAMS-GLOB-BIO, MEGAN-MACC) in terms of process representation, especially regarding dynamic vegetation and soil moisture effects. A more direct comparison of methodological improvements and their impacts on emission estimates would strengthen the introduction or conclusions.
2. While the evaluation using ambient isoprene concentrations is valuable, the lack of direct comparison with eddy covariance or other flux measurements of BVOCs is a limitation. The authors should acknowledge this and discuss plans or possibilities for such evaluations in future work.
3. Although LAI assimilation could improve LAI estimates to some extents, its impact on total isoprene emissions might be modest. The authors should elaborate on why this is the case and whether this suggests that LAI assimilation is more critical for certain regions or compounds.
4. The manuscript mentions using MEGAN EFP with updated land cover but does not fully address potential biases from emission factors, especially given their significant contribution to uncertainty. The authors should discuss on how emission factors were validated or constrained for the European domain.
5. The study shows many limitations. The authors should add more descriptions about the limitations in the discussions or conclusions.

Hamer et al. present two new databases of BVOC emission inventories covering the CAMS European domain. They focus on some key aspects like the importance of using a land surface model that takes into account the humidity of soil and plant phenology modelling. The authors compare the results obtained with observations and previous databases, providing some explanations for the discrepancies found. The manuscript is well written and clear, and I recommend it for publication after the main comments have been addressed, and the minor comments integrated.

Main comments

1. From the introduction, I recommend clearly identifying which processes driving biogenic emissions are already well represented in models (such as temperature dependence, LAI, and water stress) and which have been recognized but are still poorly represented (such as plant defenses and signaling via attractor molecules).
2. The authors used the ECMWF HRES operational forecast; however, employing meteorological variables from a reanalysis dataset might have led to more robust results. The authors are kindly invited to comment on this methodological choice.
3. In Section 3.1 (Performance of the SURFEX land surface model), could the authors please provide more details on the LAI/SIF comparison? For instance, what is the temporal resolution of the two datasets? Additionally, why is only Saint-Félix-de-Lauragais shown in the soil moisture comparison? Were other sites compared as well, and if so, did the comparisons yield similar results?
4. In Section 3.3.2 (Evaluation using other emission datasets), could the authors please provide some explanation for the large differences observed between SURFEX-MEGAN3.0 and the MEGAN-MACC database? Are these differences mainly due to variations in the meteorological parameters, the emission factors, or both?
5. The differences between SURFEX-MEGAN3.0 and CAMS-GLOB-BIOv3.1 are only partially explained by variations in LAI. This is particularly noteworthy since, although there is a difference in LAI between the SURFEX-MEGAN3.0 analysis and the SURFEX-MEGAN3.0 OL datasets, this difference does not appear to result in any noticeable change in emissions, at least none that are evident in Figure 16. I would therefore ask the authors to suggest plausible explanations for the discrepancies observed between these two datasets (SURFEX-MEGAN3.0 and CAMS-GLOB-BIOv3.1).
6. In Section 3.3.2 ('Evaluation using other emission datasets'), it is mentioned that the differences in seasonality observed among the various emission datasets are mainly driven by LAI. The authors also note that “LAI datasets (based on Yuan et al., 2011) used to calculate the monthly emission factors in the CAMS-GLOB-BIOv3.1 emissions tend to peak later in summer than the LAI calculated by SURFEX.” Could the authors please provide additional details on this comparison, perhaps by including a figure or table to illustrate it more clearly?
7. I suggest paying attention to the use of the term “dynamic vegetation”. This could be confusing for readers, as it may be interpreted as referring to “Dynamic Vegetation Models (DVMs)”. Such models represent the biosphere and are capable of simulating vegetation dynamics, that is, the transient development of vegetation composition and structure. This aspect is not addressed in your paper, where you primarily refer to plant phenology.

 Minor comments

Line 208: The reference should be to Sect. 2.2.2 and not Sect. 2.1.2

Line 365: In the sentence “with LAI having a more significant and beneficial effect for the estimation of root zone soil moisture”: do the authors really mean that LAI have a beneficial effect for the estimation of root zone soil moisture? 

Line 432: In the sentence the authors say that “We perform this evaluation using three approaches:”, but in the list after there are 4 points.

Line 434: Please add a reference to TROPOMI satellite observations of solar induced fluorescence (SIF).

Line 454: Please add a reference to SMOSMANIA in situ measurements.

From line 471 to 479: The authors come back speaking about LAI. It is a little bit misleading. I’ll move these lines before in the paragraph where the authors introduce the comparison with LAI.

Page 19: Please increase the size of Figure 5.

Line 553: Is the standard deviation calculated for isoprene average annual emitted mass over the 5 years?

Line 510: Could you please detailed more what do you mean with “gamma parameters for soil moisture, LAI, and radiation-temperature”. Do you mean the different activity factors (g)?

Page 22: Figure 8, as far as I understood, shows the R2 that is calculated on a yearly basis. This means that the times series of variables have only 5 elements. A correlation calculated like this is not very strong. It should be discussed a little in the text. 

Page 27: Please add country contours in Figure 12.

Page 27: In Figure 12 (plot on the right). Could you please give some explanation on why there are still some areas where correlation is negative (especially in Portugal)?

Line 688: Please correct “Figure 15Figure 15”.

Line 759: In the sentence “such as wind, turbulence, boundary layer height, and isoprene lifetime are implicitly ignored in this comparison.” I would remove “isoprene lifetime”, as you mentioned just before.

Page 36: Figure 16 could be more readable with a legend.

Line 824: Please add reference to “SUMO emission inventories”.

Lines 809 and 813: “Analysis” should be written in lowercase letters.