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Open research questions in Atmospheric and Environmental Gas Dynamics

62 unresolved questions extracted from the limitations and future-work sections of 409 Atmospheric and Environmental Gas Dynamics papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Wetland methane (CH 4 ) emission seasonality is a major yet uncertain component of the global CH 4 seasonal cycle, with its quantification primarily limited by the challenges in accurately characterizing wetland dynamics and emission processes.

    Unveiling cascading lag effects of wetland methane emissions: Evidence from Lake Chad in Africa · 2026 · DOI

  • In the coming years, our aim is to expand the scope of the TundraFlux Database beyond Reco by incorporating methane and nitrous oxide fluxes, net ecosystem exchange (NEE), and gross primary productivity (GPP). We also plan to ex- pand the scope of warming manipulations represented in the database by including additional climate change treatments, such as the use of snow fences to manipulate snow depth. This will enable us to distinguish between the effects of sum- mer (OTC) and winter (snow fences) warming on Reco, as well as the combined effects of these treatments (Hermes- https://doi.org/10.5194/essd-18-4965-2026 Earth Syst. Sci. Data, 18, 4965–4982, 2026 4974 S. Schwieger et al.: TundraFlux: a database of ecosystem respiration with biotic and abiotic metadata Figure 4. Monthly Reco availability aggregated across all years. White/light grey/light blue cells = 0 observations. Color intensity based on Log10(Number of Observations + 1) due to strong bias of ALA_1. Growing season = June–September in the Northern Hemisphere, December–March in the Southern Hemisphere. Except for AUS_1, shaded areas indicate winter months (light blue) and shoulder months (light grey). dorf et al., 2024). It will also allow us to account for cross- seasonal carry-over and the effects of coupled air-soil warm- ing, whereby winter soil warming persists into summer and summer air warming can indirectly modify winter soil con- ditions via changes to vegetation (Kropp et al., 2020). In recent years, remote sensing using unmanned aerial vehicles (UAVs) and satellites has advanced significantly, providing an opportunity to quantify landscape heterogene- ity in the tundra biome at high spatio-temporal resolutions (Assmann et al., 2020; Myers-Smith et al., 2020). With this Earth Syst. Sci. Data, 18, 4965–4982, 2026 https://doi.org/10.5194/essd-18-4965-2026 S. Schwieger et al.: TundraFlux: a database of ecosystem respiration with biotic and abiotic metadata 4975 data, it is possible to bridge the gap between the TundraFlux plot-scale field measurements and large-scale remote sensing mapping products. In addition, we will incorporate remote sensing-derived metadata, such as tundra type and landform classification (e.g., peatlands, thaw slumps and coastal sys- tems), as well as other derived products (Niittynen, 2026; Virkkala et al., 2024; Wagner and Hugelius, 2026), into future syntheses. Finally, we aim to link the TundraFlux Database with other available databases on terrestrial carbon fluxes (Table S1 in the Supplement), including the Tundra Trait Team database (Bjorkman et al., 2018), the Manipu- lation Experiments Synthesis Initiative (MESI; Van Sundert et al., 2023), COSORE (Bond-Lamberty et al., 2020), and the ABCflux database (Leffler et al., 2025; Virkkala et al., 2022). Although integration remains challenging due to differences in data formats, identifiers, and metadata standards, estab- lishing common protocols will be crucial to advance synthe- ses across databases. To follow updates on ongoing and future projects re- lated to our Tundra flux Database, please visit our website https://arcticflux.org/ (last access: 13 July 2026). To con- tribute new datasets, please contact us via our mail tun- drafl[email protected].

    TundraFlux: a database of ecosystem respiration with biotic and abiotic metadata from Arctic and alpine tundra warming experiments · 2026 · DOI

  • The development of TRACE has occurred in parallel to and in some cases dependent on related ocean chemistry software. This includes other property estimation routines (Carter et al., 2021a, b; Dias and Carter, 2025; Carter et al., 2017), inorganic carbon equilibrium and air-sea flux calculations (Humphreys et al., 2022; Sharp et al., 2020; Orr et al., 2015; Gregor and Humphreys, 2021; Lewis and Wallace, 1998) and seawater thermodynamic toolboxes (Firing et al., 2021). Further development of this suite of open-source software tools should seek to incorporate new findings and techniques, maintain dependency and interoperability, and respond to the needs of users in order to pursue high-quality and accessible ocean chemistry data practices. It is anticipated that TRACE will continue to be developed without fundamentally altering its core approach, while continuing to reliably offer results with well-documented assumptions and consistency across implementations. Potential directions for further development include integrating future GLODAP releases in its training data, exploring the impact of other reanalysis products on estimates, including updated atmospheric CO2 trajectories, and refining TTD shape and surface transient tracer and Canth disequilibrium assumptions. As methods for estimating Canth continue use and development, a more comprehensive understanding of their differences, assumptions, and uncertainties should be formed. This need gains currency in light of the present need to understand the effects of climate change mitigation and marine carbon dioxide removal on the ocean carbon cycle. Future work in pursuit of these needs should seek to advance the practice of Canth estimation from scientific and applied perspectives. Appendix A: Gridded product comparison The distribution of the differences, or residuals, of the TRACEv1 and TRACE-Python gridded data products indicated close agreement for results in 2020 (Fig. 2). The same analysis produced for other years illustrates that this agreement holds for other periods as well (Figs. A1–A6). Figure A1. Histogram plot of the residuals of TRACEv1 and TRACE-Python point estimates of Canth against TRACE-Python point estimates of Canth performed on the GLODAPv2.2016b gridded product for the year 1850 given the historical CO2 trajectory. The ordinate axis, in units of pmol kg−1, was limited to include 99 % of point estimates. https://doi.org/10.5194/gmd-19-5961-2026 Geosci. Model Dev., 19, 5961–5978, 2026 5972 D. E. Sandborn et al.: TRACE-Python Figure A2. Histogram plot of the residuals of TRACEv1 and TRACE-Python point estimates of Canth against TRACE-Python point estimates of Canth performed on the GLODAPv2.2016b gridded product for the year 1900 given the historical CO2 trajectory. The ordinate axis was scaled as in Fig. 2. Figure A4.

    TRACE-Python: tracer-based rapid anthropogenic carbon estimation implemented in Python (version 1.0) · 2026 · DOI

  • Although the Global Atmosphere Watch (GAW) programme provides a network of worldwide measurements, continuous atmospheric measurements across Africa remain scarce.

    Long-term trace gas and black carbon measurements at the high-altitude station Mount Kenya: tropical atmospheric variability and the influence of African emissions · 2026 · DOI

  • While this study contributes knowledge that elevated [CH4] in New England homes served by fracked gas is common, there are a number of study limitations: we did not measure fluxes of methane, concentrations of co-pollutants such as benzene, nor assess odorant detectability by residents. We did not sample comprehensively nor randomly across all housing stock and household types (including renters), household ventilation types or degree of insulation, and did not undertake a comprehensive survey of service line conditions. These limitations raise further questions for follow-on stud- ies that are conducted in as large or larger sample sizes than the 195 homes studied here.

    Indoor methane consistently above outdoor levels in homes with natural gas service · 2026 · DOI

  • The snow fraction calculation (Eq. A16) uses ERA5 snow depth with a maximum threshold (SDmax) dependent on LAI, but the paper does not validate how this simplified approach represents methanol deposition over snow-covered surfaces or discuss whether snow-specific methanol uptake coefficients differ from those for other surfaces.

    Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data · 2026 · DOI

  • Soil pH distribution for SO2 ground resistance calculation (Eq. A15) is obtained from Hengl et al. (2017), but the applicability of this global soil pH map to regional methanol deposition modeling and the impact of soil pH uncertainty on the inversion results are not quantified.

    Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data · 2026 · DOI

  • The dew presence threshold (Eq. A14) depends on specific humidity and cloud cover from ERA5, but the paper does not discuss how uncertainties or biases in ERA5 cloud cover and precipitation fields propagate into the calculated wet/dry resistance fractions and ultimately affect top-down methanol emission estimates.

    Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data · 2026 · DOI

  • The cuticular and soil uptake resistances for SO2 and O3 (Eqs. A11-A15) employ empirical parameterizations with fixed reference values (Rcutd0, Rcutw0) from Table S7, but the paper does not specify whether these values have been validated for methanol or if methanol-specific cuticular resistance coefficients need to be determined experimentally.

    Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data · 2026 · DOI

  • The stomatal resistance parameterization for methanol uses diffusivity ratios derived from water (Eq. A9), but this assumes similar physiological regulation mechanisms between H2O and CH3OH across all plant functional types. Direct measurements of stomatal resistance specifically for methanol across different vegetation types and environmental conditions are needed to validate this assumption.

    Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data · 2026 · DOI

  • The paper uses ERA5 reanalysis at 0.3° × 0.3° spatial and 1 h temporal resolution for primary simulations, but only compares output against coarser ERA5 configurations (1° × 1° at 6 h resolution) in the appendix; systematic sensitivity analysis of how ERA5 resolution affects CLaMS tracer distribution accuracy for volcanic aerosol transport is not provided.

    Transport of volcanic aerosol from the Raikoke eruption in 2019 through the Northern Hemisphere · 2026 · DOI

  • The mechanisms driving dilution of volcanic aerosol peaks in the ASMA through upwelling from lower potential temperature levels and dispersion with lateral mixing are identified qualitatively but lack quantitative analysis of the relative contributions of each process to the observed smoothing of enhanced BSR455 signals.

    Transport of volcanic aerosol from the Raikoke eruption in 2019 through the Northern Hemisphere · 2026 · DOI

  • The study validates CLaMS simulations against balloon-borne measurements at only two specific locations (Lhasa and Boulder); the model's ability to reproduce enhanced BSR455 signals and dilution processes driven by upwelling and lateral mixing needs validation across additional geographic regions and multiple eruption events beyond the 2019 Raikoke case.

    Transport of volcanic aerosol from the Raikoke eruption in 2019 through the Northern Hemisphere · 2026 · DOI

  • The CLaMS SO2-based tracer simulations show sensitivity to mixing frequency (6 h vs 24 h), but the paper does not systematically investigate how other parameterizations of turbulent mixing affect the reconstruction of volcanic aerosol vertical structure and horizontal transport into the ASMA during stratospheric plume evolution.

    Transport of volcanic aerosol from the Raikoke eruption in 2019 through the Northern Hemisphere · 2026 · DOI

  • The small fossil component in Paris is surprising and not yet fully understood. Since the footprint model does not account for the explicit height of the point emissions (chimney of ∼ 30 m) nor plume rise due to hot emissions, and since CO2 spikes observed in the continuous concentration measurements indicate an in- fluence from the point source, we assume that these three measurements could nevertheless have been influenced by the district heating plant.

    <sup>14</sup> C-based separation of fossil and non-fossil CO <sub>2</sub> fluxes in cities using relaxed eddy accumulation: results from tall-tower measurements in Zurich, Paris, and Munich · 2026 · DOI

  • Future studies are needed to improve isotopic discrimination schemes and seasonal phenology in biosphere models, particularly to reduce per- sistent overestimation of seasonal amplitudes in NH and enhance spatial attribution of δ13C signals in global-scale carbon assessments.

    Growth rates, seasonal cycles, and meridional gradients of atmospheric CO2 and δ13C using an atmospheric transport model for the period 1948–2021 · 2026 · DOI

  • While XAI techniques (Grad-CAM and Integrated Gradients) are applied, the paper does not validate whether physically meaningful spectral features learned by the model align with theoretical CH4 absorption characteristics across all architectures tested.

    Beyond localized methane plume detection: a dual-path deep learning framework for sensor-agnostic global hyperspectral methane plume monitoring · 2026 · DOI

  • Cross-sensor generalization was evaluated only between EMIT and Tanager-1 sensors; evaluation on additional hyperspectral sensor platforms would strengthen claims of sensor-agnostic capability.

    Beyond localized methane plume detection: a dual-path deep learning framework for sensor-agnostic global hyperspectral methane plume monitoring · 2026 · DOI

  • While the paper evaluates performance across ESA WorldCover V2 2021 land cover classes, it does not explicitly discuss limitations in performance across extremely spectrally complex or novel surface types not well-represented in training data.

    Beyond localized methane plume detection: a dual-path deep learning framework for sensor-agnostic global hyperspectral methane plume monitoring · 2026 · DOI

  • The Tversky loss parameters (α = 0.3, β = 0.7) were chosen to penalize false positives, but no ablation study or sensitivity analysis is provided to justify these specific weighting values.

    Beyond localized methane plume detection: a dual-path deep learning framework for sensor-agnostic global hyperspectral methane plume monitoring · 2026 · DOI

  • Batch size (8–64) and learning rate (0.001–0.00001) were tuned empirically, but the hyperparameter search space and justification for the final configuration selection process could be more systematically documented.

    Beyond localized methane plume detection: a dual-path deep learning framework for sensor-agnostic global hyperspectral methane plume monitoring · 2026 · DOI

  • Ground-based measurements and remote sensing data are urgently needed to validate existing inventories and choose the most accurate emission inventory product to improve prediction precision.

    Recent and future CO2 emission trajectories and nature-based carbon neutrality potential in China under different SSP scenarios · 2026 · DOI

  • Atmospheric inversion methods rely on observed atmospheric CO2 concentrations, making their applicability for future emission projections impossible due to the inherent inability to directly measure future CO2 concentrations.

    Recent and future CO2 emission trajectories and nature-based carbon neutrality potential in China under different SSP scenarios · 2026 · DOI

  • There is not a single emission inventory that has been verified and improved by observation across China, necessitating the use of multiple emission inventories (CEADs, MEIC, ODIAC, and EDGAR) to quantify potential CO2 emission ranges and uncertainties.

    Recent and future CO2 emission trajectories and nature-based carbon neutrality potential in China under different SSP scenarios · 2026 · DOI

  • The integration of satellite and isotopic constraints to improve estimates of the global methane budget and its uncertainties is an ongoing effort within the SMART-CH4 project (2024–2026).

    Satellite and isotopic constraints on global methane source attribution · 2026 · DOI

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62 open questions have been extracted from the limitations and future-work passages of 409 Atmospheric and Environmental Gas Dynamics papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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