Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 5
Accurate retrieval of the dry-air mole fraction of CO₂ (XCO₂) is essential for tracking emissions and supporting mitigation. However, aerosols significantly alter photon path lengths through scattering and absorption, making them the largest variable error source in XCO₂ retrieval. Current efforts to improve aerosol treatment in XCO₂ retrievals, such as the Atmospheric CO₂ Observations from Space (ACOS) algorithm for the Orbiting Carbon Observatory-2 (OCO-2), primarily focus on enhancing prior estimates of aerosol optical depth (AOD), vertical distribution, and optical properties. Yet, aerosol particle size distribution (PSD) parameters—a critical microphysical factor contributing to nonlinear variations in aerosol optical properties—are held fixed and excluded from the ACOS retrieval, thereby introducing additional biases into the XCO₂ results.
To address this challenge, we developed a Boosted Aerosol-Size-Integrated XCO₂ (BASIC) retrieval algorithm that concurrently retrieves XCO₂ and aerosol PSD parameters from OCO-2 observations. Validation at five Total Carbon Column Observing Network (TCCON) sites in East Asia shows that BASIC reduces the root-mean-square error (RMSE) by 30% and 13% compared to the standard and bias-corrected OCO-2 products, respectively. The improvement primarily stems from BASIC’s ability to generate forward-modeled spectra that more closely match observations than those from ACOS, particularly in the O₂ A-band, which is highly sensitive to aerosols. These results highlight the importance of incorporating variable aerosol PSD in retrievals and demonstrate that BASIC more accurately represents aerosol effects on radiative transfer. Our findings suggest that PSD-aware retrievals can significantly improve the accuracy of satellite-derived XCO₂ estimates under highly variable aerosol loading conditions, such as those in East Asia.
How to cite: Li, Z. and Li, S.: BASIC: A Boosted Aerosol-Size-Integrated XCO2 Retrieval Algorithm, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1603, https://doi.org/10.5194/egusphere-egu26-1603, 2026.
Abstract. This work presents the incorporation of a tropospheric isoprene oxidation scheme into an Earth System Model to enhance the simulation of tropospheric ozone levels. Numerical experiments were performed using two distinct model setups: one accounting for isoprene oxidation and another in which this chemical pathway was not considered.
Keywords: Isoprene, tropospheric ozone, atmospheric chemistry, MIM1 mechanism
Understanding the processes of tropospheric ozone formation is of key importance both for the development of air quality control measures and for climate prediction, especially under conditions of changing anthropogenic and biogenic emissions. While on the global scale the production of tropospheric ozone is primarily governed by the oxidation of carbon monoxide and methane, in densely populated and industrial regions non-methane volatile organic compounds (NMVOCs) become the dominant contributors. Among these NMVOCs, isoprene plays a particularly important role, with the majority of its atmospheric emissions originating from vegetation.
The aim of this study is to further develop the INM RAS–RSHU chemical–climate model [1], which is a component of the Earth System Model (ESM), with an emphasis on a more accurate representation of tropospheric chemical processes. The primary focus is on the implementation of an improved chemical mechanism designed to enhance the accuracy of simulated concentrations of key atmospheric gaseous components. One of the main criteria in selecting the mechanism is achieving an optimal balance between the level of chemical detail and the computational efficiency of the model.
As part of the model development, a comparative analysis of several widely used chemical mechanisms was performed, including the Mainz Isoprene Mechanism (MIM1) [2], comprising 16 species and 44 reactions; MIM2, with 69 species and 178 reactions [3]; the Model for Ozone and Related Chemical Tracers (MOZART), including 151 species and 287 reactions [4]; and the Regional Atmospheric Chemistry Mechanism (RACM), which includes more than 100 species and 363 reactions [5]. Based on the results of this analysis, the MIM1 mechanism was considered the most appropriate for initial implementation in the ESM, as it was decided to begin with the most compact option while still providing sufficient accuracy in representing key tropospheric chemical processes.
To assess the impact of the MIM1 mechanism, two numerical experiments were conducted using identical model settings and boundary conditions. In the control simulation, a basic tropospheric chemistry scheme without isoprene was applied, whereas the MIM1 experiment implemented the full isoprene oxidation mechanism, including 44 chemical reactions.
The study and the set of numerical experiments are aimed at optimizing the chemical component of the INM RAS–RSHU chemical–climate model in order to improve the accuracy of representing tropospheric processes while maintaining high computational efficiency. The obtained results provide a solid basis for further investigation of the interactions between chemical and dynamical processes in the atmosphere and will contribute to the development of approaches for forecasting atmospheric composition and its impact on regional and global climate change.
How to cite: Okulicheva, A., Tkachenko, M., and Smyshlyaev, S.: Numerical modeling of tropospheric chemistry in an Earth System Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17672, https://doi.org/10.5194/egusphere-egu26-17672, 2026.
Phenolic compounds are key precursors and intermediates in the formation and aging of secondary organic aerosols (SOA), particularly in biomass-burning plumes and urban atmospheres. However, their detection typically requires laboratory-based chromatographic or mass-spectrometric techniques, limiting rapid or on-site characterization. The current research present a fully 3D-printed electrode (3D-PE) platform produced via hybrid material extrusion additive manufacturing, providing a compact, low-cost, and field-deployable tool for electrochemical quantification of atmospheric phenolics. The device integrates PLA-based structural components with graphene and silver conductive layers deposited in a single manufacturing step. Cyclic voltammetry measurements demonstrate clear and distinct redox signatures for representative phenolic structures, with oxidation potentials of 0.48–0.68 V and well-resolved reduction peaks. These redox behaviors correspond to functional groups commonly found in lignin-derived and anthropogenically emitted aromatic species.
The 3D-PE operates with sample volumes as low as 50 µL, suitable for extracts from aerosol filters, cloud water, or fog samples. Its electroactive surface area (5.8–6.7 mm²) and high electron-transfer efficiency from the graphene electrode enable sensitive detection of trace phenolic compounds. The platform’s portability and rapid response offer new opportunities for quantifying oxidation intermediates during field campaigns, studying heterogeneous oxidation pathways, and investigating Secondary Organic Aerosol (SOA) formation dynamics.
This work demonstrates that additive manufacturing provides a promising route for developing next-generation, customizable atmospheric chemistry sensors. The 3D-printed electrochemical platform can complement established mass-spectrometric techniques by enabling low-cost, high-frequency measurements of reactive organic compounds that play central roles in SOA formation and atmospheric oxidative chemistry.
How to cite: Raj, A., Yadav, P., Sahai, A., and Sharma, R. S.: 3D-Printed Electrochemical Sensor for Rapid Detection of Phenolic Oxidation Products Relevant to Organic Aerosol Formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-186, https://doi.org/10.5194/egusphere-egu26-186, 2026.
The Indo-Gangetic Plain (IGP) experiences strong seasonal and spatial heterogeneity in aerosol composition, driven by variations in emissions, meteorology, and regional transport. Capturing these variations requires measurement approaches that extend beyond conventional fixed-site monitoring. In this study, we deployed a mobile lab platform equipped with aerosol instrumentation, including a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), to investigate seasonal variability in organic aerosol (OA) sources during the post-monsoon and spring seasons across distinct urban environments in Lucknow, located in the central Indo-Gangetic Plain.
Field campaigns were conducted during the post-monsoon and spring seasons at Babasaheb Bhimrao Ambedkar University (BBAU), a site influenced by traffic near major highways, and at the Council of Scientific & Industrial Research–Central Institute of Medicinal and Aromatic Plants (CSIR-CIMAP), located adjacent to a forested area. Additional measurements were conducted during the spring season at the Uttar Pradesh Pollution Control Board (UPPCB) site, which represents a residential–commercial environment.
At each location, the mobile laboratory was operated for approximately 10–15 days, enabling continuous, near real-time characterization of fine particulate matter and associated co-pollutants. Measurements of non-refractory PM2.5 (NR-PM2.5) chemical composition (measured using HR-ToF-AMS) were supported by simultaneous observations of trace elements, black carbon, gaseous species, total PM2.5 mass, and meteorological parameters. This integrated, multi-instrument framework allowed for a consistent comparison of aerosol chemical signatures across sites and seasons, while capturing short-term variability linked to local emissions, atmospheric processing, and regional transport.
Organic aerosol dominated the mass of NR-PM2.5 across all sites and seasons, contributing more than 50% of the total NR-PM2.5. Source apportionment using Positive Matrix Factorization (PMF) with the multilinear engine (ME-2) resolved hydrocarbon-like OA (HOA), biomass-burning OA (BBOA), oxidized biomass-burning OA (O-BBOA), and secondary oxygenated OA components (SVOOA and LVOOA). During the post-monsoon period, BBOA accounted for approximately 28–40% of total OA across the sites, indicating a strong combustion influence under shallow boundary-layer conditions. Traffic-related HOA contributed about 8–13% of OA, with enhanced fractions at the highway-influenced BBAU site, reflecting local vehicular emissions. In contrast, springtime conditions showed enhanced secondary OA contributions (70-60%), with trajectory-based analyses highlighting the role of long-range transport in shaping aerosol composition.
The use of a mobile laboratory enabled rapid deployment across diverse land-use environments while maintaining consistent instrumentation and methodology, allowing robust inter-site and inter-seasonal comparisons. This approach emphasises the significance of high-resolution mobile observations for elucidating the fine-scale spatial variability and seasonal evolution of organic aerosol sources in the complex urban regions of the IGP.
How to cite: Lakra, A., Tripathi, S. N., Sethi, D., Kumar, A., Bhowmik, H. S., and Shukla, A. K.: Seasonal variation of organic sources during the post-monsoon and spring seasons across multiple urban sites of the Indo-Gangetic Plain using a mobile lab platform, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8822, https://doi.org/10.5194/egusphere-egu26-8822, 2026.
Abstract
The densely populated monsoon region of Pakistan, influenced by a diverse mix of natural and anthropogenic aerosols, provides a natural laboratory to investigate aerosol impacts on cloud properties. Using a decade-long (2015–2024) dataset from MODIS, MERRA-2, and ERA5, we examine the response of non-precipitating warm clouds to fine-mode and coarse-mode aerosols. We find positive correlations between aerosol optical depth (AOD) and cloud effective radius (CER), with stronger sensitivity to fine-mode AOD. The relationships of AOD with cloud optical thickness (COT) and liquid water path (LWP) are generally negative, but more pronounced for coarse-mode AOD. These aerosol-cloud relationships are strongly modulated by meteorological conditions: low relative humidity and low lower-tropospheric stability enhance the negative AOD–COT and AOD–LWP responses. Additionally, the sensitivity of aerosol-cloud relationships to meteorology is greater for fine-mode AOD than coarse-mode. These results highlight the importance of aerosol size and ambient meteorology in determining cloud microphysical responses, providing insight into aerosol cloud interactions in a region critical for South Asian climate.
How to cite: Anwar, K., Liu, Y., Labban, A., and Zeydan, Ö.: Aerosol-cloud interactions under fine-mode and coarse-mode aerosol conditions over the monsoon region of Pakistan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-323, https://doi.org/10.5194/egusphere-egu26-323, 2026.
A closed to open-celled transition of mixed-phase clouds within a marine cold air outbreak (MCAO), driven by an occluded cyclone over the Nordic Seas, is interrogated with data acquired during the Cold Air Outbreak Experiment in the Sub-Arctic Region (CAESAR) field campaign on 29 February 2024. The understanding of these transitions is a challenge for numerical prediction models due to their small scale but important for weather and climate prediction, as open celled conditions have stronger updrafts supporting locally high precipitation rates along with a lower cloud fraction (lower albedo) than closed celled conditions. Measurements indicate that a stratiform (closed cell convective) cloud deck with cloud top heights of ~1230 m and liquid water paths (LWP) of ~130 gm-2, within a boundary layer with aerosol number/CCN surpassing 600 cm-3, deepen to heights of ~1520 m with LWPs of ~270 gm-2 over 250 km of fetch, before transitioning into an open-celled convective structure with cloud tops reaching up to 2220 m. Cooling free tropospheric temperatures with fetch, which reduce the inversion strength thereby enhancing growth by entrainment may encourage boundary layer growth. Open-cells are more glaciated than closed-cells with mean LWPs falling from 270 gm-2 to 80 gm-2 across the transition, however isolated peaks of LWP within updrafts of open cells occasionally surpass 500 gm-2. Minimal secondary ice production (SIP) is observed in closed cells with ice nucleating particle and ice number concentrations ~2 L-1 with cloud temperatures between -20oC and -15oC. In open cellular convection (cloud temperatures between -22oC and -15oC), ice number concentrations reach ~10 L-1 indicating SIP. High aerosol concentrations are hypothesized to support the maintenance of closed-celled convection, with 80% of drops smaller than 10 μm reducing the riming efficiency. Small droplets also limit the production of freezing drizzle, which is hypothesized to limit the potential of SIP due to freezing/fragmentation within closed cell convection. Only after aerosol concentrations are depleted through scavenging and/or entrainment are SIP processes able to become more effective and precipitation particles able to grow large and dense enough to reach the surface and form cold pools breaking up the cloud deck. Plumes of warm moist air lifting off the ocean surface, juxtaposed with cold pools and entrainment events penetrating to the surface are documented using the Multi-function Airborne Raman Lidar (MARLi) in the first observations of its kind.
How to cite: Ephraim, S., Zuidema, P., Bansemer, A., Cai, L., Cruikshank, O., Evengeliou, N., French, J., Geerts, B., Grasmick, C., Massling, A., McFarquhar, G., Noel, G., Petters, M., Rosky, E., Skov, H., Snider, J., Tatro, T., Wang, Z., Woods, S., and Zhang, L.: Closed to Open-Celled Mixed-Phase Cloud Transition Over the Nordic Seas Under High Aerosol Loading, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12630, https://doi.org/10.5194/egusphere-egu26-12630, 2026.
This work evaluates EarthCARE cloud products against ground-based Cloudnet retrievals at multiple sites in Europe. We focus on the comparison between the EarthCARE synergetic target classification product (AC-TC), with the Cloudnet target classification product, both derived from the synergy of lidar/radar measurements. As the two classifications have different aerosol/cloud types, a new common classification with the following classes is defined and used for direct comparison: Unknown, Clear, Liquid (Droplets T>0°C), Supercooled Liquid (Droplets T<0°C), Drizzle or rain, Drizzle & droplets, Ice, Ice & droplets, Melting ice possibly coexisting with droplets, Insects, Aerosol. Each AC-TC or Cloudnet target is assigned with a new class. Spatiotemporal collocation criteria are considered, along with visual inspection of the collocated scenes, to limit the dataset in homogenous scenes where the satellite and suborbital platform has detected similar clouds. Additionally, retrieved ice and liquid water cloud contents from Cloudnet and EarthCARE are compared to evaluate cloud microphysical properties. Τhe geographical diversity of the Cloudnet network, provides the advantage of investigating different atmospheric conditions in terms of clouds and aerosols, with abundant ice cloud occurrences in the northern sites and frequent liquid water clouds at the southern sites. This analysis aims to assess the consistency of cloud categorization and microphysical retrievals between the satellite and suborbital measurements, and to investigate the strengths and limitations of both approaches.
How to cite: Tsikoudi, I., Marinou, E., Pfeitzenmaier, L., Mashon, S., O'Connor, E., Karkani, D., Karipis, A., Voudouri, K. A., Kollias, P., Treserras, B. P., and Battaglia, A.: Cloud typing and microphysics: An EarthCARE-Cloudnet Comparison, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21851, https://doi.org/10.5194/egusphere-egu26-21851, 2026.
We present an automated procedure that combines lidar measurements, ADS-B flight tracks and ECMWF ERA5 meteorological data to detect and characterise nighttime aircraft contrails. Measurements have been carried out at the Observatory of Haute-Provence (OHP) in France. Lidar scattering-ratio profiles were processed with a sensitivity-driven spatio-temporal discrimination algorithm to identify contrail “spots” and aggregate them into contrail signatures. A parameter score identifies an optimal discrimination threshold set that balances sensitivity and false positives. In our case, these thresholds took these values: scattering ratio SR ≈ 2.1; temporal aggregation ≈ 7.2 min; vertical separation ≈ 0.3 km. Applied to five nighttime events, the method yields mean contrail altitudes of 8.7–10.3 km, geometrical thicknesses of 0.1–1.1 km, horizontal widths 2–3 km, and optical depths (COD) of ≈0.05–0.40. Persistent contrails are associated with ice-supersaturated layers and temperatures below −41 °C. Contrail optical depth resulted well correlated with both vertical thickness and horizontal extent. We have demonstrated that combining lidar with ADS-B and ERA5 substantially improves detection and discriminates contrails from natural cirrus at night, a regime where passive satellite retrievals are limited. This approach is automatic, transferable and reproducible, offering robust validation data for satellite algorithms and improved contrail parameterizations in climate models.
How to cite: Mandija, F., Keckhut, P., Alraddawi, D., Irbah, A., Sarkissian, A., Khaykin, S., Peyrin, F., and Baray, J.-L.: Automated nighttime contrail detection using spatio-temporal clustering of Raman lidar measurements , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5443, https://doi.org/10.5194/egusphere-egu26-5443, 2026.
Remote sensing of aerosol variability over the Central Himalayas remains challenging because of complex terrain, strong elevation gradients in surface reflectance, and frequent cloud and snow contamination, which can bias passive aerosol optical depth (AOD) retrievals. In this study, we examine an apparent MODIS-derived AOD enhancement in 2011 over the Central Himalayas that deviates from the expected seasonal pattern of reduced aerosol loading during the monsoon and post-monsoon periods. The central objective is to determine whether this apparent anomaly represents a physically meaningful aerosol enhancement or is influenced by retrieval limitations in high-relief environments. We evaluate the MODIS anomaly using collocated CALIPSO observations, including vertically resolved aerosol extinction profiles and aerosol-layer optical depths. CALIPSO measurements show no evidence of persistently elevated aerosol layers corresponding to the MODIS enhancement, and aerosol extinction remains vertically shallow, indicating that the observed AOD anomaly is not associated with strong free-tropospheric aerosol intrusion. These results suggest that the apparent MODIS “spike” likely reflects a column-integrated enhancement dominated by near-surface aerosol and/or terrain–cloud–snow-related retrieval effects rather than a sustained elevated aerosol event. This study highlights the importance of integrating active lidar profiling with passive satellite retrievals to improve the interpretation of aerosol anomalies over mountainous regions and strengthens the basis for aerosol–cloud interaction assessments in the Himalayas.
How to cite: Bello, A., Bhardwaj, A., and Sam, L.: CALIPSO validation of an apparent MODIS AOD spike over the Central Himalayas (2011), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23052, https://doi.org/10.5194/egusphere-egu26-23052, 2026.
Smoke aerosols constitute a critical component of atmospheric pollutants and radiative forcing agents. Northeast China is frequently afflicted by smoke episodes. Driven by the combined impacts of anthropogenic emissions, residential heating, agricultural biomass burning, and other factors, this region exhibits complex aerosol characteristics with pronounced seasonal variations. This study systematically evaluates the spatiotemporal evolution of smoke aerosols from 2015 to 2023 using GEOS-Chem global simulations (2°×2.5°), along with ground-based PM2.5 measurements, sun photometer AOD measurements in Harbin, MODIS, and VIIRS fire data. We classified the region into six distinct sub-regions based on smoke concentration characteristics: four urban zones (Dalian, Shenyang, Changchun, Harbin) and two rural zones (Eastern Coastal and Western Inland). Observational and simulation data demonstrates that the model captures regional seasonal variability and annual trends. Employing the HYSPLIT model and Concentration Weighted Trajectory (CWT) analysis, we identified potential external source regions and initially assessed the relative contribution of cross-regional transport (e.g., from Siberia or North China) to smoke episodes across different seasons. This comprehensive analysis provides a scientific basis for understanding the climatic effects of aerosols and formulating refined regional air quality management strategies in Northeast China.
How to cite: Gao, X. and Miatselskaya, N.: Long-term spatiotemporal evolution and source attribution of smoke aerosols in Northeast China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8607, https://doi.org/10.5194/egusphere-egu26-8607, 2026.
The new satellite missions including active sensors (e.g. EarthCare), passive multi-angular polarimeters (e.g. PACE/SPEXone, PACE/HARP-2) and single-viewing instruments (e.g. OLCI), together with synergies among existing sensors, are foreseen to characterize aerosols and clouds with high accuracy. However, robust validation activities are essential to ensure the quality of the new satellite products.
In this study, we focus on the evaluation of the aerosol optical properties synergistically retrieved from three sensors, i.e., TROPOMI, OLCI-A, and OLCI-B, within the framework of the AIRSENSE ESA project (https://www.grasp-earth.com/portfolio/airsense/). The derived optical properties include the aerosol optical depth (AOD), Ångström exponent (AE), coarse- and fine-mode AOD, and single-scattering albedo (SSA). Validation is performed against ground-based sun-photometer observations from five ACTRIS/AERONET stations across Europe (https://aeronet.gsfc.nasa.gov/). The results show good agreement for AOD with root-mean-square errors (RMSE) ranging from 0.006 to 0.09. In contrast, AE and SSA show lower agreement, with RMSE values of 0.27 and 0.02, respectively, at the Limassol station, even when quality flags are applied.
Moreover, we evaluate the aerosol properties retrieved using PACE/SPEXone observations. PACE (Plankton, Aerosol, Cloud, and ocean Ecosystem) mission was launched in February 2024 and employs advanced passive polarimetric observations to enhance the aerosol characterization. In addition to aerosol optical properties (e.g., AOD, AE) the PACE/SPEXone products generated within the framework of AIRSENSE, include the aerosol layer height (ALH), a parameter that is critical for quantifying aerosol-cloud interactions. Since EarthCARE/ATLID provides vertically resolved aerosol profiles, it offers an independent reference for the assessment of ALH. Here, we present first comparison results of the PACE/SPEXone ALH product over the ocean, produced with two algorithms, RemoTAP and FastMAPOL, compared to EarthCARE/ATLID weighted backscatter heights. Overall, RemoTAP ALH products are systematically lower than those derived from EarthCARE/ATLID, whereas FastMAPOL retrieves a larger number of ALH estimates but exhibits lower overall agreement with the EarthCARE/ATLID reference. As a next step, we intend to expand the area of interest and increase the number of collocations.
Acknowledgements:
This research is financially supported by the PANGEA4CalVal project (Grant Agreement 101079201) funded by the European Union and the AIRSENSE (Aerosol and aerosol cloud Interaction from Remote SENSing Enhancement) project, funded by the European Space Agency under Contract No. 4000142902/23/I-NS.
How to cite: Voudouri, K. A., Tsekeri, A., Karipis, A., Litvinov, P., Lopatin, A., Dubovik, O., Hasekamp, O., and Amiridis, V.: Evaluation of new polarimetric products, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21713, https://doi.org/10.5194/egusphere-egu26-21713, 2026.
Past aerial hyperspectral mapping campaigns and pilot studies have demonstrated that highly concentrated plumes are a significant portion of California’s total methane emissions, including many unintentional leaks that can be fixed quickly when operators are notified. Satellite plume imagers such as Planet’s Tanager offer the capacity for repeated observations of known methane infrastructure, with enough spatial resolution and sensitivity to address a significant fraction of these leaks by identifying source facilities and contacting operators. Here we present system design and first results from the California Satellite Methane Project (CalSMP), a comprehensive multi-sector effort to notify individual operators of plumes within days of detection and ensure prompt mitigation when possible through a mix of direct regulation and voluntary dialogue with operators.
In May 2025, CARB began retrieving low-latency Tanager plume detections purchased from Carbon Mapper. Using a cloud-based system developed in-house, CARB employees oversee a semi-automated process to assign plumes to a source and facilitate information exchange with operators. The system generates a notification email with instructions and response forms tailored to the specific facility type (e.g. landfill, oil and gas, dairy biogas). These responses allow us to categorize emissions across sectors by emission type (e.g. unintentional, temporary, process) as well as identify sector-specific components or infrastructure (landfill gas collection system, gas well stuffing box) and details of any repairs.
CARB plans to expand its spatiotemporal coverage through additional satellites, with increased automation as we scale up. While the project’s initial focus is direct repair of unintentional leaks, operator responses also effectively survey underlying causes of point-source emissions and can inform future efforts to improve industry operational practices. CARB has dedicated community outreach funds to ensure methane observations are accessible, understandable, and useful to communities, and is committed to sharing technical details, project design, and lessons learned with other jurisdictions to maximize global mitigation efforts.
How to cite: Phillips, D., Yang, E., Schroeder, J., Zelinka, S., Frausto-Vicencio, I., Fibiger, D., and Herner, J.: From Detection to Mitigation: The California Satellite Methane Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14127, https://doi.org/10.5194/egusphere-egu26-14127, 2026.
We quantify climate effects of Tambora-scale eruptions under current and future warming using the SOCOL-MPIOM coupled atmosphere-chemistry-ocean model for 2020, SSP2-4.5, and SSP3-7.0 (2080) scenarios.
Global cooling amplifies counterintuitively with background warming: SSP3-7.0 shows 44% stronger cooling than present-day due to polar vortex intensification increasing from 5.5% to 44.5%. Regional responses reveal complex patterns: winter exhibits Arctic warming (+0.4-0.6°C) simultaneous with tropical cooling (up to -8°C) and continental extremes (up to +15°C). Summer brings widespread continental cooling (-2 to -4°C). Monsoon systems weaken by 20-35% while mid-latitude winter precipitation intensifies by 20-40%.
Results demonstrate that volcanic impacts under anthropogenic warming generate spatially heterogeneous extremes rather than uniform cooling, critical for agricultural and water resource risk assessment.
How to cite: Tkachenko, M. and Eugene, R.: Climate Response to Tambora-Scale Volcanic Eruptions Under Present and Future Climate Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14645, https://doi.org/10.5194/egusphere-egu26-14645, 2026.
The impact of increasing anthropogenic hydrogen (H2) emissions on Earth’s radiative balance depends on the soil microbial H2 sink—the largest and most uncertain term in the global H2 budget. Soil moisture is a primary but poorly quantified control regulating the soil sink. Here, we assess the sensitivity of microbial H2 oxidation to soil moisture in laboratory experiments with temperate and arid soils spanning distinct textures. H2 oxidizer activity is observed down to –70 to –100 MPa water potentials across soils, which are among the driest conditions reported for microbial activity and are much drier than assumed in global simulations of H2. Using genome-resolved meta-omics, we link H2 oxidation dynamics in temperate soils to specific desiccation-adapted microbial taxa that contribute differentially to H2 uptake along the moisture gradient. Through global simulations, we show that our observationally constrained drier moisture threshold increases the contribution of arid and semi-arid regions for soil H2 uptake by 4-7 percentage points (pp), while decreasing the contribution of temperate and continental regions (−7 pp). Our results highlight the importance of H2 uptake under extreme hydrological conditions, particularly the roles of desertification, dryland expansion, and H2-oxidizer ecophysiology in modulating long-term changes in H2 uptake.
How to cite: Reji, L., Bertagni, M., Paulot, F., Qin, Q., and Zhang, X.: Global Implications of a Low Soil Moisture Threshold for Microbial Hydrogen Uptake , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11855, https://doi.org/10.5194/egusphere-egu26-11855, 2026.
As growing environmental pressures challenge urban resilience, sustainability, and human well-being, the lack of high-resolution geospatial information at the urban or intra-urban scale remains a critical limitation for effective and targeted decision-making. In the context of air quality and associated health impacts, this study addresses this gap by developing the Atmospheric SpatioTemporal Emissions Model (AtmoSTEM), a high-resolution spatiotemporal framework for representing atmospheric emissions, pollutant concentrations, and population exposure at 1 km2 resolution. The application focuses on the Ioannina basin in Greece, where residential biomass burning (BB) constitutes a dominant emission source, especially during the cold season, frequently leading to pollution levels exceeding the World Health Organization (WHO) Air Quality Guidelines (AQG) and EU thresholds and underscoring the need for targeted interventions.
For this purpose, a high spatiotemporal emission inventory for Residential Heating is developed. The Copernicus Atmosphere Monitoring Service (CAMS) regional emission inventory, structured according to the GNFR classification and provided at a spatial resolution of 0.05° × 0.1°, serves as the baseline dataset. The downscaling process is based on publicly available, open-access, GNFR-dependent high-resolution spatial proxies, including the Coordination of Information on population density data from Global Human Settlement (GHSL), land-use classifications from the Copernicus Land Monitoring Service (CLC 2018), the OpenStreetMap (OSM) road network, and, where applicable in coastal and maritime domains, marine traffic density from the European Marine Observation and Data Network (EMODNet). Particular emphasis is placed on refining pollutant fields that are more relevant to BB activities, thereby improving the spatial representativeness of BB emissions within urban and peri-urban environments.
To capture the temporal variability of the emissions, CAMS is combined with CAMS temporal Regional Profiles (CAMS-TEMPO), enabling the generation of analytically resolved, hourly emission estimates. Pollutant concentrations are then estimated using a Random Forest machine learning model that integrates AtmoSTEM’s high-resolution emissions, with meteorological, satellite-derived, and spatial data, as well as in-situ air quality measurements provided by the University of Ioannina. The resulting high-resolution concentration fields are evaluated against independent in-situ measurements. Additionally, BB-related PM2.5 fields are derived and analyzed, enabling improved source-specific characterization of residential heating contributions and providing a physically consistent basis for air-quality and exposure assessments.
How to cite: Kakouri, A., Filippis, G., Korras-Carassa, M.-B., Kuenen, J., Hatzianastassiou, N., Matsoukas, C., and Kontos, T.: AtmoSTEM: A high-resolution spatiotemporal emission model for urban air quality applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5251, https://doi.org/10.5194/egusphere-egu26-5251, 2026.
Simulations of aviation's air quality impacts near airports are critical for enhancing our understanding of how aviation impacts air quality regionally, and the potential effects of sustainable alternatives. In order to better understand such impacts, a research to investigate the effects of the resolution of the simulation grid and of the meteorology inputs on the air quality impact estimates due to aircraft emissions, specifically in the context of stretched gnomonic cubed-sphere grids for the simulation of a specific area was conducted. Such grids allow for the possibility of having a region with finer grid elements while coarsening the grid outside a specified area.
The research questions that the present research effort aims to address are: which parameter (grid resolution or meteorology resolution) impacts most the simulations, how grid and meteorology resolution impact air quality estimates, and whether stretched grids can be used for regional simulations.
To address the matter, we use the distributed-memory, high-performance version of the GEOS-Chem atmospheric chemistry-transport model to simulate the evolution of aviation attributable to Landing and Take-Off operations (LTO) emissions throughout the year of 2019. The LTO emissions were obtained from the OpenAVEM emissions inventory, whereas the remaining non-aviation emissions were taken from the default GCHP databases.
Three different grid resolutions were chosen to evaluate the impact of the horizontal grid resolution: C24, C36, and C48, with grid cell lengths ranging between 40 km, 30 km, and 20 km, respectively. All grids use the same stretch parameters, i.e., target latitude, target longitude, and stretch factor. These parameters were set so as to have a finer resolution around Europe. For the meteorology sensitivity, two resolutions were used, 2 ° ×2.25 ° and 0.5 ° ×0.625 ° from MERRA2 for the three grid resolutions aforementioned.
A comparison between the area weighted concentrations for NO2, PM2.5, and O3 showed that the resolution of the meteorology plays a more important role than the horizontal grid resolutions, for the resolutions tested. For the human health impacts, the deaths attributable to each component have also been estimated and compared for each grid resolution.
How to cite: Kavabata, L., Quadros, F., Meijer, V., Snellen, M., and Dedoussi, I.: Horizontal grid and meteorology resolution impacts on aviation’s air quality impacts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15593, https://doi.org/10.5194/egusphere-egu26-15593, 2026.
Tropospheric Emissions: Monitoring of Pollution (TEMPO) is observing air quality and
atmospheric composition over North America from a geostationary orbit since its operations
started in August 2023. TEMPO observes the continent every 40 to 60 minutes at a spatial
resolution on the order of ~ 2 x 4.5 km 2 . Together with the Geostationary Environment
Monitoring Spectrometer (GEMS, launch 2020) monitoring Asia and the Sentinel-4/UVN
(launch 2025) monitoring Europe, TEMPO is part of the current global constellation of
geostationary sensors devoted to the observation of air quality. Like GEMS and Sentinel-4/UVN,
TEMPO uses backscattered ultraviolet and visible solar radiation to retrieve atmospheric
amounts of key trace gases and aerosols associated with air quality and atmospheric chemistry.
Among the species retrieved from TEMPO observations of nitrogen dioxide and formaldehyde
are important to understand emissions and atmospheric chemistry, including the formation and
destruction of tropospheric ozone.
After multiple version updates over the first two years of the mission, the TEMPO Level 2 NO 2
and HCHO products have undergone significant enhancements to improve the performance and
accuracy of the slant column retrievals, air mass factor calculations and post-processing
corrections including destriping for NO 2 and background for HCHO. We illustrate the
performance of both retrievals (version 3 & 4), evaluating their fitting uncertainty and showing
comparisons with independent correlative measurements and other satellite products showcasing
small noise levels and remarkable accuracy with well quantified biases. We continue by
illustrating the capacity of TEMPO products focusing on different case studies showing
TEMPO’s high temporal and spatial resolution. We finalize discussing aspects of the retrieval
subject to improvement and our plans to address them.
How to cite: Gonzalez Abad, G., Nowlan, C. R., Chance, K., Liu, X., Chong, H., Fasnacht, Z., Flittner, D. E., Ghahremanloo, M., Henderson, B., Hou, W., Houck, J., Judd, L., Knowland, K. E., Shah, V., Wales, P., Qin, W., Valin, L., and Wang, H.: First two years of TEMPO nitrogen dioxide and formaldehyde observations:algorithm status and highlights, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23274, https://doi.org/10.5194/egusphere-egu26-23274, 2026.
The Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission is part of a global constellation of geostationary satellites, along with GEMS and Sentinel-4, dedicated to monitoring air quality across the Northern Hemisphere. TEMPO is the first geostationary satellite instrument to monitor air pollutants over North America on an hourly basis at nearly neighborhood-scale resolution, covering an area from Mexico City to the Canadian oil sands and from the Atlantic to the Pacific Ocean.TEMPO measures backscattered ultraviolet and visible radiation to observe several trace gases important to air quality, including ozone, nitrogen dioxide, and formaldehyde, with observations every 40–60 minutes and at a high spatial resolution of approximately 2 × 4.75 km². TEMPO was successfully launched in April 2023 and began nominal operations in October 2023. Since then, it has been continuously monitoring atmospheric pollutants across its observation domain.
This presentation summarizes the Version 4 (V04) updates and improvements to the TEMPO total-ozone (O3TOT) and ozone-profile (O3PROF) retrieval algorithms. This presentation also presents the evaluation of the upcoming V04 TEMPO O3TOT product through comparisons of total ozone columns (TOCs) with measurements from other satellite instruments (e.g., OMPS and TROPOMI) and ground-based instruments, including Pandora, Brewer, and Dobson spectrometers. The V04 TEMPO O3PROF algorithm, which is UV-only, is validated through comparisons of ozone profiles, tropospheric ozone, and 0–2 km ozone columns with those from the Tropospheric Ozone Lidar Network (TOLNet) and aircraft observations, as well as through validation with MLS, EPIC, TROPOMI, and OMI observations.
How to cite: Park, J., Liu, X., Bak, J., Chong, H., Chance, K., Hou, W., Houck, J., Abad, G. G., Nowlan, C. R., Wang, H., Yang, K., Flynn, L. E., Haffner, D. P., Flittner, D. E., Knowland, K. E., Johnson, M., Demetillo, M. A. G., Spurr, R., Li, C., and Zhao, X. and the TEMPO Validation Team and NASA's GMAO Team: The Status of the TEMPO Total-Ozone and Ozone-Profile Algorithm: V04 Updates and Comprehensive Evaluations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23276, https://doi.org/10.5194/egusphere-egu26-23276, 2026.
Urban vegetation plays a key role in modulating atmospheric carbon dioxide (CO2) in megacities. However, studies that explicitly quantify the effect of urban vegetation on CO2 remain scarce. This study investigates how vegetation cover affects CO2 mixing ratios in the Metropolitan Area of São Paulo (MASP) during 2020–2022, using four monitoring sites with contrasting vegetation fractions: Pico do Jaraguá (PJ; 59.75%), IAG (36.38%), ICESP (22.42%), and UNICID (10.42%). Vegetation cover was derived from Sentinel-2 Level-2A imagery using NDVI-based pixel classification, while CO2 observations were obtained from the METROCLIMA network and analyzed together with concurrent meteorological variables (temperature, humidity, and wind). The analysis comprised characterizing temporal variability and quantifying vegetation effects using regression models and probability distribution functions (PDFs). Clear seasonal and diurnal patterns were observed, with lower CO2 concentrations during summer and afternoon hours (420-414 ppm), and higher values during winter and nighttime periods (447-425 ppm). The greener and less urban site, PJ, exhibited the lowest and most stable CO2 levels, whereas the highly urban UNICID site showed the highest average mixing ratios. Elevated CO2 values at IAG (428.30 ppm in summer and 435.49 ppm in winter), despite substantial vegetation cover, suggest the influence of local emissions and boundary-layer dynamics, while relatively low CO2 values at ICESP (422.10 ppm in summer and 428.03 ppm in winter) likely reflect the elevated measurement height (~100 m a.g.l.), which favors regional-scale mixing and reduces sensitivity to local emission sources. NDVI revealed a bimodal phenological cycle (April–May and October–November), which was mirrored by CO2 variability at PJ. Among 132 fitted PDFs, the Normal Inverse Gaussian distribution best captured CO₂ variability, with greener sites showing flatter and more symmetric distributions and urban sites showing increased skewness and peakedness. Regression results indicate a significant vegetation signal: a 0.1 increase in NDVI was associated with CO2 reductions of ~3.92 ppm (PJ), 2.81 ppm (IAG), and 7.66 ppm (ICESP; likely conditional on site features), while no significant effect was detected at UNICID. Overall, urban vegetation influences both mean CO2 levels and their distributional characteristics, supporting the role of green infrastructure and phenology in urban carbon management.
Keywords: carbon dioxide, vegetation cover, linear regression, Metropolitan Area of São Paulo.
How to cite: Piscoya, J., Franco, M. A., and Andrade, M. D. F.: Influence of Vegetation Cover on Atmospheric CO2 Mixing Ratios in the São Paulo Metropolitan Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13522, https://doi.org/10.5194/egusphere-egu26-13522, 2026.
Field-based observations of Carbon dioxide (CO₂) exchange between soils and atmosphere are critical to accurately account for terrestrial carbon cycling in data-scarce West African savanna ecosystems. This study quantified soil CO₂ fluxes over two consecutive years (2023–2024) using a static chamber approach across four contrasting land-use systems namely forest, grassland, cropland, and rice fields. Measurements were conducted on weekly basis using replicated chambers to assess both spatial heterogeneity and interannual variability. Soil CO₂ fluxes were analysed in relation to key environmental drivers, including water-filled pore space (WFPS) and soil temperature, using mixed-effects statistical models to account for repeated chamber measurements. Across all land uses, CO₂ emissions increased markedly in 2024 compared to 2023. Median seasonal CO₂ fluxes ranged from 0.59 to 1.46 t C ha⁻¹ season⁻¹ in forest systems, 1.91 to 5.07 t C ha⁻¹ season⁻¹ in grasslands, 1.75 to 5.09 t C ha⁻¹ season⁻¹ in croplands, and 1.84 to 2.61 t C ha⁻¹ season⁻¹ in rice fields. Grasslands and croplands consistently exhibited the highest CO₂ emissions, with maximum values reaching 7.18 and 5.38 t C ha⁻¹ season⁻¹, respectively, highlighting the strong influence of land management and disturbance intensity. Forest soils showed comparatively lower CO₂ fluxes, reflecting reduced soil disturbance and more stable microclimatic conditions. Statistical analyses revealed that soil temperature was a dominant driver of CO₂ emissions across all ecosystems, while soil moisture exerted a secondary but significant control, particularly in managed systems. Higher WFPS and elevated soil temperatures during the wet season were associated with enhanced CO₂ release, indicating intensified microbial respiration and root activity. Interannual contrasts suggest that wetter and warmer conditions in 2024 amplified soil respiration across all land uses. Overall, our results demonstrate pronounced spatial and temporal variability in soil CO₂ fluxes in the Sudanian savanna and underscore the sensitivity of carbon emissions to land-use change and hydro-climatic variability. These findings provide critical baseline data for improving regional carbon budgets and for informing mitigation strategies in data-scarce tropical savanna regions.
How to cite: Oussou, F. E. and the WASCAL CONCERT Team: Assessing Spatial and temporal heterogeneity of Soil Carbon emissions across anthropized land use Gradient in the Sudanian savanna, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21511, https://doi.org/10.5194/egusphere-egu26-21511, 2026.
Anthropogenic fires linked to the burning of agricultural biomass residues represent a recurring environmental disturbance in the province of Tucumán, northwest Argentina. These events are predominantly associated with land clearing and post-harvest burning in sugarcane fields concentrated in the region’s lowland plains, where agro-industrial activity is most intense. Such practices contribute significantly to greenhouse gas (GHG) emissions, vegetation degradation, and a range of socio-economic impacts. This study integrates satellite-derived fire indices with environmental economic tools to quantify the spatial and temporal effects of fire over the past five years (2021–2025) and assess their implications for climate change mitigation and policy.
Multispectral data from Sentinel‑2 and atmospheric composition products from Sentinel‑5P were processed via Google Earth Engine to calculate vegetation and fire severity indices including NDVI, dNBR, and BAI. Additionally, tropospheric CO and CO₂ concentrations were used to evaluate atmospheric impacts. The spatial distribution of fire activity—primarily in the eastern and southern lowlands—was cross-referenced with the Global Fire Emissions Database (GFED) and IPCC Tier 1 emission factors to estimate fire-related GHG emissions. Preliminary analyses indicate an average of 45,000 ha affected annually, mainly in sugarcane-dominated landscapes, resulting in estimated emissions of approximately 382,500 t CO₂-equivalent per year.
To evaluate broader socio-environmental impacts, economic losses were estimated across multiple dimensions: reduced land productivity, costs of ecosystem restoration, loss of ecosystem services (e.g. carbon sequestration, water retention), and public health expenses related to degraded air quality. Additional indirect impacts include traffic accidents due to smoke-induced low visibility and recurring property damage reported in local media. These preliminary estimates suggest combined annual damages of approximately USD 46.5 million, underscoring the considerable burden imposed by current fire management practices.
It is important to note that this work presents ongoing research, and all results are preliminary. The estimates provided will be further refined through continued integration of field data, emission modeling, and economic valuation methods.
This integrative approach demonstrates the value of combining Earth observation technologies with environmental economics to support climate-oriented decision-making. By quantifying the environmental and economic impacts of anthropogenic fires, this study provides critical evidence for the development of cross-sectoral policies aimed at regulating biomass burning, improving land management practices, and strengthening resilience to climate risks. The case of Tucumán underscores the urgent need for sustainable alternatives to current residue management practices and for aligning agricultural production with mitigation goals.
How to cite: Reynoso Posse, F., Zbrun Luoni, J. P., and Aguilera Sammaritano, M.: Greenhouse gas emissions and socio-environmental costs of anthropogenic fires in Tucumán (Argentina): A remote sensing and environmental economics approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21709, https://doi.org/10.5194/egusphere-egu26-21709, 2026.
This study presents a comprehensive climatological analysis of aerosol optical and microphysical properties over the Eastern Mediterranean, utilizing long-term AERONET measurements from Mersin/Erdemli (IMS-METU) site. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm was used to retrieve key parameters, including Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and Volume Size Distribution, offering robust separation of surface and aerosol properties.
Results revealed a distinct seasonal cycle in aerosol loading, with AOD peaking in summer (July-August) due to fine-mode pollution and exhibiting a secondary peak in spring (April) driven by mineral dust transport from desert regions. The annual mean SSA displays a negative spectral slope, decreasing from ~0.93 at 440 nm to ~0.90 at 1020 nm, indicating a background atmosphere dominated by fine-mode urban-industrial aerosols. Although winter months exhibit the lowest total aerosol load due to wet scavenging, they display the strongest absorption characteristics. The imaginary refractive index significantly exceeds 0.015, and SSA values drop sharply during winter, attributed to Black Carbon emissions from domestic heating. The volume size distribution maintains a bimodal structure year-round; while the coarse mode dominates during spring dust events, the fine mode contribution remains substantial across all seasons. The aerosol population over the Eastern Mediterranean is characterized as a heterogeneous mixture where the anthropogenic fine-mode background is periodically modulated by natural mineral dust intrusions and local carbonaceous emissions.
How to cite: Çetiner, A. S. and Aslanoğlu, S. Y.: Long Term Analysis of Aerosol Properties Over the Eastern Mediterranean Using Grasp Retrieved AERONET Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3325, https://doi.org/10.5194/egusphere-egu26-3325, 2026.
Aerosol optical depth (τ) is routinely reported at wavelengths that are not directly measured by ground-based sun photometers, in particular at 550 nm for satellite validation and at longer wavelengths for short-wave infrared applications. These values are typically obtained by spectral interpolation or extrapolation, most often using linear or quadratic regressions in logarithmic space. However, the uncertainty structure of such regressions is frequently treated incorrectly, because measurement uncertainties in τ are absolute and approximately wavelength-independent in linear space, and therefore become wavelength-dependent in logarithmic space. As a result, the measurement covariance matrix must be explicitly accounted for in log–log regression, although this is rarely done in practice. This study provides both a formal and a practical framework for estimating τ at non-measured wavelengths together with its associated uncertainty. A rigorous formulation is presented for linear and quadratic regression in logarithmic space, including the propagation of random and systematic (bias-related) errors from the original spectral measurements to the interpolated or extrapolated wavelength.
Sensitivity analyses based on synthetic aerosol optical depth spectra generated with the GRASP forward model are used to compare six different approaches for deriving τ(550) and τ(2000), including linear and quadratic regressions over different spectral ranges as well as the GRASP-AOD method. When the covariance matrix is treated correctly, quadratic log–log regression is found to be the most robust method for estimating τ(550), and its results become essentially independent of the chosen spectral range. In contrast, when the covariance matrix is neglected, the same regression becomes highly sensitive to the selected wavelengths, and artificially improved performance is obtained when restricting the fit to the central AERONET channels. These findings are confirmed using real AERONET observations. When the full covariance treatment is applied, differences between estimates obtained using different spectral ranges remain below 0.002 at all sites analysed. When it is ignored, root-mean-square differences exceeding 0.01 are observed at sites dominated by fine-mode aerosols.
Finally, the uncertainty propagation framework is applied to real data and shows that the uncertainty of interpolated τ follows the expected Beer–Lambert law governing sun-photometer measurements, scaling with optical air mass. This provides an independent validation of the formal error model. Overall, this work establishes a consistent methodology for spectral interpolation and extrapolation of τ, ensuring both accurate values and physically meaningful uncertainties for satellite validation and related applications.
How to cite: Torres, B., Dubovik, O., Toledano, C., Fuertes, D., Momoi, M., Kazadzis, S., Marbach, T., Lind, E., Roman, R., Veloso Varela, M., and Barreto, A.: Inferring aerosol optical depth at unmeasured wavelengths from ground-based spectral photometer data: uncertainty-consistent regression, sensitivity tests, and application to real data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13698, https://doi.org/10.5194/egusphere-egu26-13698, 2026.
Meteorological normalization of surface ozone typically relies on air temperature to proxy both photochemical activity and boundary-layer dynamics. However, this approach implicitly assumes that the thermal state adequately represents radiative energy input—an assumption that remains untested in high-elevation environments where strong solar forcing and a thin atmosphere may decouple temperature from the surface energy balance. Here, we examine how surface energy forcing modulates ozone variability independently of air temperature using continuous station-level measurements in Lhasa (3650 m a.s.l.), Tibetan Plateau. By stratifying days based on net radiative input while explicitly constraining thermal conditions through a counterfactual matched-pair analysis, we isolate energy-driven processes without invoking reanalysis-based boundary-layer estimates. Results demonstrate that high-energy states consistently exhibit enhanced morning ozone growth (median +4.3 ppb h-1) and elevated daytime concentrations relative to temperature-matched low-energy states. These enhancements are accompanied by coherent multi-tracer responses, including moisture drying and the dilution of primary pollutants, which provide observational constraints on energy-driven vertical coupling that are distinct from temperature-dependent photochemistry. Furthermore, a rate-based robustness analysis confirms that these signals persist across varying stratification thresholds. We conclude that surface energy forcing represents a previously under-constrained structural factor in conventional ozone attribution frameworks, particularly in complex terrain where thermal and radiative states frequently decouple.
How to cite: Zhao, C., Wang, Y., Liu, Y., Li, W., Gongga, D., Quzhen, D., Ao, Y., Yue, J., Zhong, X., and Du, X.: Surface energy forcing modulates ozone variability independently of air temperature over the Tibetan Plateau, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4386, https://doi.org/10.5194/egusphere-egu26-4386, 2026.
Cloud detection over snow- or ice-covered (S/IC) surfaces remains a critical challenge in satellite remote sensing. The cloud-like high surface albedo and ice-cloud-like brightness temperatures of these surfaces often lead to systematic misclassification in visible- and infrared-based algorithms, including the threshold-based cloud detection applied to Sentinel-5P atmospheric composition retrievals. Misclassified clear-sky scenes can introduce biases in the retrieved total columns of ozone, sulfur dioxide, and nitrogen dioxide, while misclassified cloudy scenes reduce the spatial coverage of satellite products.
To address this challenge, we develop a global cloud detection algorithm based on absorption images derived from Sentinel-5P oxygen A-band observations. The algorithm exploits the reduction of oxygen absorption in cloudy pixels, as cloud layers reflect solar radiation before it reaches the underlying surface, thereby shortening the radiative transfer path in the atmosphere and reducing absorption along the path. In addition, spatial texture information extracted from oxygen absorption images is incorporated to enhance sensitivity to optically thin and broken clouds, enabling more robust discrimination between clouds and bright underlying surfaces. This physical mechanism makes the algorithm insensitive to surface type, rendering it particularly suitable for global cloud detection, including over S/IC surfaces.
Validation against CALIPSO demonstrates a marked improvement in cloud detection performance across diverse surface and cloud conditions. The proposed algorithm achieves an overall accuracy of 91%, compared with 85% for the Suomi-NPP product and 48% for the operational Sentinel-5P product. Improvements are particularly pronounced over S/IC surfaces, where detection accuracy increases by 15% relative to Suomi-NPP. Additionally, detection accuracy for optically thin clouds improves by 20% globally, with the largest gains (up to 52%) observed over S/IC surfaces. These results demonstrate the value of oxygen absorption and spatial texture features for cloud detection, especially over S/IC surfaces, and support improved quality and consistency of satellite-based atmospheric observations over polar and other bright-surface regions.
How to cite: Liu, H. and Li, S.: Cloud Detection over Snow- or Ice-covered Surfaces Using Oxygen A-Band Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15531, https://doi.org/10.5194/egusphere-egu26-15531, 2026.
The influx of anthropogenic metals into the atmosphere is expected to increase substantially due to the rapid growth of the space industry. More than 20 elements from re-entering spacecraft have been identified in sulphuric acid droplets in the Junge layer, with several estimated to surpass the background level from cosmic dust. While the atmospheric impact of these particles is uncertain, they have been widely hypothesised, including ozone destruction, increased polar stratospheric cloud formation, harmful surface deposition, a perturbed radiative balance and in turn, changes to global circulation.
The spacecraft ablation process and subsequent formation of space debris particles (SDPs) are not well defined. The dominant constituent of spacecraft is aluminium. If vaporised, aluminium is expected to undergo a series of reactions to form aluminium hydroxide (Al(OH)3). The initial form and size of the particles will strongly influence the coagulation, global transport, and atmospheric lifetime of the particles. Constraining these factors is vital to accurately assessing the impact SDPs have on the atmosphere.
This work provides an update on the work presented at EGU2025 (Egan et al., Modelling impacts of ablated space debris on atmospheric aerosols, EGU25-4460), using the Whole Atmosphere Community Climate Model with the Community Aerosol and Radiation Model for Atmospheres (WACCM-CARMA) to simulate the production and transport of SDPs. This work investigates the sensitivity of the initial particle radius to the transport, lifetime and surface deposition of particles.
How to cite: Hawkins, S., Egan, J., Plane, J., Marsh, D., and Feng, W.: Modelling the transport of ablated space debris particles in the atmosphere, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19003, https://doi.org/10.5194/egusphere-egu26-19003, 2026.
Solid fuels such as fuelwood (FW), coal balls (CB), dung cake (DC), and agricultural residue (AR) are widely used for domestic heating and cooking in developing countries, particularly in rural and peri-urban regions. Combustion of these fuels is a major source of carbon-based gaseous emissions, notably carbon monoxide (CO) and carbon dioxide (CO2), contributing to indoor air pollution, adverse health effects, and climate change. The emission characteristics of these gases are strongly influenced by fuel moisture content, elemental composition, and inorganic constituents. This study presents the development of emission factors (EFs) for CO and CO2 from commonly used solid fuels and evaluates materials-based mitigation strategies using a laboratory-designed fixed-bed reactor system with a combustion chamber simulating real-world burning conditions.
Fuel samples were collected from representative domestic sources, air-dried, pulverized, and homogenized prior to analysis. Moisture content was determined gravimetrically by oven drying at 105 °C. Ultimate analysis of carbon (C), hydrogen (H), nitrogen (N), sulfur (S), and oxygen (O) was performed using a CHNS/O elemental analyzer, while anionic and cationic species were quantified using ion chromatography. Combustion experiments for emission factor development were conducted in a custom-designed fixed-bed reactor equipped with a controlled burning chamber to simulate domestic heating conditions. The reactor enabled stable combustion, controlled airflow, and downstream integration of mitigation materials for post-combustion treatment of exhaust gases. It also includes real-gas cylinders to generate the gas mixture representing smoke.
The results revealed notable variability in fuel composition and emission behavior. FW exhibited relatively efficient combustion with lower CO emissions, while DC, with higher moisture and lower carbon content, produced higher CO levels. CB showed high CO emissions despite its carbon content, whereas AR displayed intermediate emission characteristics. Elevated levels of alkali metals and anions, particularly in DC, were associated with reduced combustion efficiency and increased CO formation.
The hazards of these gases demands for removal. In this study, removal experiments were carried out by integrating advanced functional materials into the exhaust section of the fixed-bed reactor. Porous and nanostructured materials such as graphene-based materials, biochar, graphitic carbon nitride (g-C3N4), zeolites, metal–organic frameworks (MOFs), covalent organic frameworks (COFs), and silica-based materials were evaluated for CO oxidation and CO2 capture. Material characterization using Brunauer–Emmett–Teller (BET) surface area analysis, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) confirmed high specific surface area, well-developed porous structures, and the presence of reactive surface functional groups, which directly enhance adsorption and catalytic conversion of carbonaceous gases.
Overall, the study demonstrates that fuel chemical composition and combustion conditions strongly influence CO and CO2 emission factors from domestic heating activities. The integration of a designed fixed-bed reactor with a burning chamber and advanced materials-based mitigation strategies provides a robust experimental framework for reducing carbon-based emissions and improving air quality in regions dependent on traditional solid fuels.
How to cite: Sahu, D. and Pervez, S.: Emission of Carbon Monoxide (CO) and Carbon Dioxide (CO2) from Household Solid Fuels Burning Practices: Development of Real World Emission Factor and Removal Methods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20738, https://doi.org/10.5194/egusphere-egu26-20738, 2026.
To advance urban sustainability and achieve climate neutrality, cities are proposing various decarbonization strategies through nature-based solutions, including the implementation of green infrastructures (GI). Accurately quantifying urban biogenic CO2 exchange is essential for developing robust greenhouse gas budgets and for distinguishing biogenic from anthropogenic contributions to atmospheric CO2 in urban environments.
This study systematically reviews current approaches for estimating urban biogenic CO2 fluxes from both measurement- and model-based perspectives, evaluating their advantages, limitations, and applicability in urban contexts. Building on this review, we present an optimized framework to quantify urban biospheric CO2 fluxes using the Vegetation Photosynthesis and Respiration Model (VPRM) driven by a high-resolution land cover map and sentinel-2 satellite data. The framework is applied to the Metropolitan Area of Barcelona for April and December 2023 at a 10 m spatial resolution. Results show that evergreen needleleaf forests and croplands act as significant carbon sinks in April, with biogenic CO2 uptake offsetting approximately 10% of anthropogenic CO2 emissions in April and 4% in December. A cross-city comparison of urban vegetation cover, climatic conditions, and the biogenic offset effects indicates that increased vegetation cover does not necessarily translate into a proportionally stronger carbon sink. Nevertheless, this study proposes that a standardized framework for accounting for biogenic CO2 fluxes and uptake should be established to provide critical support for GI-based mitigation strategies in urban planning.
How to cite: Luo, Q., Segura-Barrero, R., Badia, A., Lauvaux, T., Li, J., Chen, J., and Villalba, G.: Quantifying Urban Biogenic CO2 Fluxes in Greenhouse Gas Budgets: A Scalable Framework and Case Study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2329, https://doi.org/10.5194/egusphere-egu26-2329, 2026.
