| 13 Jul 2026
Land-use-specific soil NOx emissions in eastern China derived from TROPOMI observations
Abstract. Quantifying soil nitrogen oxide (NOx) emissions is essential for constraining the nitrogen cycle and understanding its impacts on atmospheric chemistry and regional air quality. This study presents the first land-use-specific estimate of soil NOx emissions across eastern China derived from TROPOMI satellite observations at a spatial resolution of 0.2° × 0.2°, covering forest, cropland, grassland/shrubland and bare land. We derive the emission intensity factor β for these land use types as functions of soil temperature (Ts) and soil volumetric water content (θv). Total soil NOx emissions from eastern China in 2019 are estimated to be 1305 ± 368 Gg N, with largest contributions from cropland (623 ± 267 Gg N, ~ 48 %) and forest (486 ± 124 Gg N, ~ 37 %). High-emission areas (> 4 kg N ha-1 yr-1) are concentrated in the North China Plain, and all land use types show summer-peak seasonal patterns. Soil NOx emissions exhibit land-use-specific responses to temperature and moisture. Most land use types show a clear optimum temperature and high-temperature inhibition effect, which are captured by a Gaussian response function. We find that existing global emission inventories may underestimate soil NOx emissions from forests in China. The comparison with other emission inventories and soil emission observations demonstrates that the proposed method provides a reliable basis for estimating soil NOx emissions by capturing land-use-specific responses to environmental drivers. This satellite-based approach can provide input to the formulation of emission reduction strategies and support ecosystem management under climate change.
The authors presented a satellite-based analysis of land-use-specific soil NOx emissions in eastern China using DECSO NOx emissions, anthropogenic emission inventories, land-use information, and meteorological data. This is an interesting study and the approach has the potential to provide new constraints on soil NOx emissions from different land-use types. However, I have several major concerns regarding the attribution of the emissions. These issues need to be addressed before the quantitative results and conclusions can be considered robust.
Major comments:
1. The anthropogenic emission inventory plays a critical role in the derived soil NOx emissions. It is directly subtracted from DECSO emissions to estimate soil emissions. Anthropogenic inventories have substantial uncertainties in both their magnitude and spatial and temporal distributions, which is 35% said by the paper. Any bias in the inventory could therefore be directly attributed to soil emissions. This issue may be particularly important when soil emissions are small relative to anthropogenic emissions. The treatment of negative residuals as zero may introduce an additional positive bias. The authors should better evaluate how uncertainties and biases in the anthropogenic inventory affect the derived soil NOx emissions.
2. I have concerns about using land-use fractions to separate emissions from different soil sources. Land-use fractions represent source area, while important drivers such as fertilizer N input and irrigation are not included. The land-use fractions may be correlated, making it difficult to independently estimate the emission factors in the regression. In addition, the choice of LUR > 0.2 and at least 20 grid cells appears arbitrary. The authors should justify these assumptions and provide sensitivity tests and regression diagnostics.
3. I am not fully convinced that the fitted β–temperature relationships represent the response of soil NOx emissions to temperature. The β values in different temperature bins are derived from different locations and months, and they would reflect regional and seasonal differences in fertilizer application, vegetation, soil properties, or other factors. The authors should better demonstrate that the effects from these confounding factors. The sensitivity to the soil moisture threshold should also be evaluated.
4. The performance of the attribution framework is not sufficiently evaluated. The authors should provide model performance and diagnostics for Eq. (1) and evaluate how well the reconstructed emissions from Eq. (3) reproduce the satellite-derived emissions.
5. The final soil NOx estimates are capped by the DECSO total emissions when the calculated soil emissions exceed DECSO. It is unclear how this adjustment affects the final estimates.
6. The Monte Carlo analysis needs more explanation. The authors state that each input is randomly sampled within its uncertainty range, but the probability distributions used for the sampling are not specified. Several thresholds used in the method are fixed and their effects are not included in the uncertainty analysis. The authors should clarify the sampling procedure and evaluate the sensitivity of the results to the major methodological thresholds.