Atmospheric ice nucleating substances (INSs) play a crucial role in ice cloud formation above -35°C, impacting cloud radiative properties, cloud lifetime, and the hydrological cycle. Characterizing inorganic (e.g., mineral dusts, volcanic ash, metals) and organic (e.g., bacterial cells, fungal spores, pollen, and various biomacromolecules) INSs has typically involved: 1) single-particle analyses, which offer high resolution but require specialized equipment, and 2) bulk sample treatment (e.g., heat, H₂O₂, (NH₄)₂SO₄) analyses, which are more accessible but may overestimate or underestimate INS concentrations due to non-target effects. There is a need for additional methods to quantify inorganic and organic INSs concentrations in the atmosphere to test and improve climate models.

Here we show a new density gradient centrifugation method to differentiate and quantify inorganic (densities ≥ 2.1 g cm^-3) and organic INSs (densities ≤ 1.6 g cm^-3). Density gradient centrifugation was used to separate the INSs suspension into their respective density isolate. This was followed by a wash procedure consisting of sequential differential centrifugation and ultrafiltration. Lastly, the INSs were quantified using a droplet freezing assay.

Our method successfully recovered organic water-soluble INSs (lignin, birch pollen washing water and filtered Fusarium acuminatum) and organic water-insoluble INSs (Snomax and Pseudomonas syringae) in the low-density isolate. We recovered inorganic water-insoluble INSs (K-feldspar) in the high-density isolate. In an INS mixed suspension, we recovered K-feldspar in the high-density isolate and lignin in the low-density isolate both at concentrations similar to the isolated K-feldspar or lignin tests. 

This work demonstrates the broad applicability of density gradient centrifugation for characterizing a wide range of inorganic and organic atmospheric INSs.

How to cite: Uppal, G. K., Worthy, S. E., Chen, L., Yeung, C., McConville, O., and Bertram, A. K.: SeParation of Ice Nuclei via Density Layers (SPINDL): A new method for characterizing ice nuclei using density gradient centrifugation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3841, https://doi.org/10.5194/egusphere-egu25-3841, 2025.

EGU25-3841

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The atmosphere is a critical reservoir for and transporter of microplastics (MPs) but little is known about the nature and drivers of their regional and climatic variability. In this study, dry deposition of MPs is quantified simultaneously over a seven-day period in nine Iranian cities encompassing different populations and climates and relationships with meteorological conditions and gaseous and particulate air quality parameters investigated. Overall, deposition ranged from < 5 to > 100 MP m^-2 h^-1 and was dominated by fibres of various sizes and constructed of different polymers (mainly polyethylene, polyethylene terephthalate, polypropylene, polystyrene and nylon), and there were clear and significant differences in mean values between the different cities that were not a simple function of climate or population. On a local scale, both positive and negative relationships between MP deposition and various meteorological and air quality parameters were observed among the cities. However, the pooled depositional data for MPs and various shapes and sizes thereof exhibited significant inverse relationships with wind speed and specific measures of airborne particulate matter (e.g., dust, PM-2.5, PM-10). The results suggest that there is a broadly consistent, fibre-dominated regional population of MPs whose deposition (and presumably resuspension) is influenced by variations in wind speed, but additional location-specific factors and sources contribute to temporal variations within the different cities. Despite the relationships between deposition and some gaseous and particulate air quality parameters identified at specific locations, it may be difficult to introduce a sharp parameter that can be used as a regional proxy for MP deposition.

Acknowledgements

We thank Shiraz University and Klaipeda University for technical support. This project has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-PD-24-51.

How to cite: Abbasi, S., Dzingelevičienė, R., and Turner, A.: Regional and climatic variations in atmospheric microplastic deposition, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16376, https://doi.org/10.5194/egusphere-egu25-16376, 2025.

EGU25-16376

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Microplastics, particularly microplastic fibers, are an emerging pollutant of growing concern, frequently detected in the atmosphere. However, recent studies emphasized the predominance of artificial and natural microfibers over microplastic fibers. Despite this, research focusing on all types of microfibers, commonly grouped as anthropogenic microfibers (MFs) remains limited, especially in residential indoor environments. Therefore, this study explored the indoor atmospheric deposition of microfibers, in the residential homes of Chennai, India, marking the first such study in the country. Additionally, workplaces, including offices, laboratories, and hostel rooms, were examined. Bedrooms (16,736±7,263 MFs/m²/day) and student hostels (5,572±2,898 MFs/m²/day) recorded the highest contamination in respective categories, and this could be attributed to the abundance of textile products, such as bedsheets, carpets, quilts, towels, and curtains in the indoors of both the rooms. MFs shorter than 500 µm dominated the samples, comprising 78.8 and 65.9 % of total MFs in residential and workplace categories, respectively. The diameter of MFs ranged from 2.02–23 µm in residential spaces and 2.04–36.4 µm in workplaces, indicating their potential to penetrate human lungs. µ-FTIR analysis revealed the predominance of semi-synthetic MFs (48.2 %), followed by natural (29.3%) and synthetic (22.5 %) MFs, underscoring the need to consider all categories of MFs. Further classification revealed rayon (94.5±6.40 %), cotton (68.1±6.12 %), and polyethylene terephthalate (PET) (48.1±11.5 %) as major MFs, indicating textiles as a significant contamination source. The detection of black rubber/latex MFs indicates additional contributions from road dust. Surface morphological analysis, correlations with environmental and meteorological factors, and backward trajectory analysis further highlighted the primary role of indoor/local sources in MFs contamination. Overall, the study emphasizes the need to monitor all categories of MFs and calls for comprehensive investigations into the impact of indoor textile products and road dust on indoor atmospheric contamination in future research.

How to cite: Jessieleena, A., Kambapalli Ezhilan, I., Chandel, A. S., D'sa, S. V., Mohamed, N., and Nambi, I.: Atmospheric deposition of anthropogenic microfibers in different indoor environments of Chennai, India , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7978, https://doi.org/10.5194/egusphere-egu25-7978, 2025.

EGU25-7978

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Tropical deep convective clouds (DCCs) play a pivotal role in Earth's hydrological cycle, with their dynamics strongly influenced by aerosols. Depending on their properties, aerosols can either invigorate or suppress cloud formation and development. Previous observational studies and cloud-resolving model simulations have shown that aerosols such as black carbon (BC) and sulfates modify cloud microphysics, affecting droplet size distribution, latent heat release, and precipitation patterns. However, the use of global climate models (GCMs) to study these aerosol-cloud interactions remain limited, despite their ability to capture large-scale circulation patterns and associated non-linear feedback. This study investigates the sensitivity of aerosol-induced cloud invigoration and suppression (AIVe) to major aerosol species during the Indian summer monsoon (ISM) season using the Community Earth System Model, specifically its atmospheric component, the Community Atmosphere Model version 5 (CESM-CAM5). The analysis focuses on DCCs over central India during the monsoon months of June–September (JJAS) for the period 2005–2008. Aerosol and cloud parameters from CESM-CAM5 simulations, conducted at 0.5-degree horizontal resolution, are compared with satellite observations. Five Atmospheric Model Intercomparison Project (AMIP)-style simulations were performed: one with aerosols at pre-industrial level (PI) levels, another at present-day (PD) levels, and three additional simulations perturbing specific aerosol species (dust, BC, and sulfate) under PD conditions to isolate their individual effects on AIVe. The findings highlight that aerosol physico-chemical properties critically influence DCC behavior. Black carbon near the boundary layer increases cloud condensation nuclei (CCN) concentrations, delaying precipitation, enhancing warm-phase invigoration, and strengthening updrafts. In the upper troposphere, BC absorbs solar radiation, causing atmospheric warming that promotes cloud deepening and cold-phase processes. Additionally, BC intensifies both shortwave and longwave heating, prolonging cloud lifetimes and supporting deeper convection. Sulfate aerosols primarily enhance warm-phase invigoration through increased CCN concentrations at lower altitudes. However, their weaker vertical transport limits their impact on cold phase processes and deep convection compared to BC and dust. Dust aerosols with high concentrations in the mid-troposphere, act as efficient ice-nucleating particles (INPs), enhancing cold phase invigoration. However, suppressed updrafts in the upper troposphere reduce their overall effect on deep convective systems, emphasizing the importance of aerosol size, number concentration, and properties in shaping AIVe. This study underscores the complex interplay between aerosol characteristics and their vertical distribution in influencing cloud dynamics during the ISM. Detailed results and further implications will be presented.

How to cite: Sharma, P., Ganguly, D., and Kant, S.: Sensitivity of Cloud Invigoration and Suppression Effects to Major Aerosol species During the Indian Summer Monsoon in a Global Climate Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-886, https://doi.org/10.5194/egusphere-egu25-886, 2025.

EGU25-886

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During winter, dense fog occurrences in the Indo-Gangetic Plain pose severe risks to visibility, air quality, and public health, emphasizing the need for improved fog forecasting in India. This study employs a high-resolution WRF-Chem model (2 km × 2 km) to identify optimal configurations for simulating fog in the region and investigate the impact of urbanization-induced UHI/UDI (Urban Heat Island/Urban Dry Island) and elevated emissions on the fog life cycle in and around the megacity of Delhi.

A comprehensive sensitivity analysis explores model configurations across microphysics, planetary boundary layer (PBL), land surface models (LSM), radiation schemes, chemistry, and emission inputs. Simulations of surface and vertical meteorology are evaluated against data from weather stations and radiosonde profiles, while modeled chemistry is compared with ground-based measurements. Results demonstrate that specific combinations of microphysics, PBL, and LSM schemes coupled with chemistry effectively simulate Liquid Water Content (LWC), a critical fog proxy. Modeled relative humidity, particulate matter concentrations, and fog life cycles show strong agreement with observations. We then utilize this optimized model configuration to quantitatively analyze individual and combined effects of urbanization and aerosols on fog formation.

How to cite: K Lal, A., Kunchala, R. K., and Mohan, M.: Evaluating WRF-Chem for simulating fog episodes: A Case Study from The National Capital Region Delhi, India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1370, https://doi.org/10.5194/egusphere-egu25-1370, 2025.

EGU25-1370

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Wildfires and dust storms significantly contribute to air pollution, causing adverse health impacts and intensifying various aerosol-meteorology feedbacks in the atmosphere through direct and indirect aerosol effects. These effects, however, are highly variable and depend on prevailing synoptic conditions. In April 2020, Ukraine experienced one of its most severe air pollution episodes, which had a profoundly negative impact on the Kyiv metropolitan area. This event was triggered by wildfires in the abandoned exclusion zone around the Chornobyl Nuclear Power Plant (northern Ukraine) and a dust storm that swept across the entire territory of Ukraine from the west to the east. Despite similar aerosol emissions – characterized by elevated levels of dust, organic carbon (OC), and black carbon (BC) – the atmospheric effects varied significantly under different synoptic processes during April 2020. This study presents seamless modeling results that analyze the meteorological response to direct (DAE) and indirect aerosol effects (IDAE) under varying synoptic conditions during this pollution episode in Ukraine.

Using the Environment – HIgh-Resolution Limited Area Model (Enviro-HIRLAM) at a 1.5 km horizontal resolution, four simulations/runs were conducted to investigate the role of aerosols: DAE run, IDAE run, combined aerosol effects (COMB run), and a reference (REF run) representing a standard Numerical Weather Prediction configuration without aerosol effects. The uniform and continuous effects of biomass burning and dust aerosols were primarily observed in radiation parameters, leading to a reduction in downwelling global and net short-wave radiation by 25-40 W/m². A clear correspondence between aerosol distribution and changes in the spatial patterns of other meteorological parameters was evident during the atmospheric fronts and the dust storm episode. Notably, the movement of a warm front caused near-surface air temperature to decrease and specific humidity to increase ahead of the front, with the opposite effects observed behind it. Compared to the REF run, these parameters exhibited local variations ranging from -2.6°C to +1.0°C for air temperature and from -1.5 g/kg to +1.0 g/kg for specific humidity. Aerosol effects during the stationary cold front led to an increase in air temperature and cloud liquid water content. However, transported sulfur aerosols significantly influenced these effects against the background of OC and BC emissions. In contrast, the subsequent dust storm and cold front had the opposite effect on air temperature, also impacting changes in turbulent kinetic energy. Most of these effects were associated with areas in model domain affected by elevated concentrations of dust, BC, and OC in their coarse and accumulation modes.

We acknowledge support through the grant HPC-Europa3 Transnational Access Programme for projects “Integrated modelling for assessment of potential pollution regional atmospheric transport as result of accidental wildfires”; projects Horizon Europe programme under Grant Agreement No 101137680 CERTAINTY (Cloud-aERosol inTeractions & their impActs IN The earth sYstem); project No 101036245 RI-URBANS (Research Infrastructures Services Reinforcing Air Quality Monitoring Capacities in European Urban & Industrial AreaS) and No 101056783 European Union via FOCI-project (Non-CO2 Forcers And Their Climate, Weather, Air Quality And Health Impacts).

How to cite: Savenets, M., Mahura, A., Nuterman, R., and Petäjä, T.: Direct and indirect effects of biomass burning and dust aerosols under various synoptic processes during the April 2020 pollution case in Ukraine, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4697, https://doi.org/10.5194/egusphere-egu25-4697, 2025.

EGU25-4697

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Cloud droplet size distribution is essential for quantifying the role of clouds in earth system, including cloud albedo, precipitation formation, and cloud lifetime. The response of cloud droplet spectral relative dispersion (ε) to aerosol number concentration (N_a) is highly uncertain, and the role of turbulence in ε–N_a relationships is yet puzzling. This study uses large eddy simulation to examine the ε–N_a relationship and derives an expression for ε from a minimal model to elucidate this relationship. Our findings indicate that as N_a increases, ε initially decreases due to the aerosol’s effect on weakening the intensity of turbulence-induced broadening greater than its effect on weakening the intensity of condensational narrowing. However, as N_a continues to increase, ε increases due to the aerosol’s effect on weakening the intensity of condensational narrowing more significant than its effect on weakening the intensity of turbulence-induced broadening. These findings improve the understanding of the aerosol effects on cloud droplet size distribution and address the challenge of quantifying aerosol indirect effects considering turbulence, potentially leading to new cloud microphysics parameterizations.

How to cite: Chen, Y., Chen, J., and Lu, C.: Turbulence-induced Non-Monotonic Influence of Aerosols on Cloud Droplet Size Distribution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5362, https://doi.org/10.5194/egusphere-egu25-5362, 2025.

EGU25-5362

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Air quality and climate over the western Indian region have been shown to be strongly influenced by trans-regional anthropogenic emissions originated from the Indo-Gangetic Plain (IGP) and central India, besides the local and regional processes. Nevertheless, the relative roles of local versus remote anthropogenic processes in changing precipitation over western India have remained unclear. In this regard, numerical simulations have been conducted using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to quantify regional versus trans-regional anthropogenic effects on cloud droplet number concentration (CDNC) and precipitation during monsoon (August 2019). WRF-Chem simulations show a good agreement with the ERA5 reanalysis for cloud fraction (CF) (r = 0.88, MB = 0.08 mm/day) and accumulated monthly precipitation (AMP) (r = 0.84, MB = -0.14 mm/day). Sensitivity simulations reveal that regional plus trans-regional anthropogenic emissions enhance CDNC by up to 5.1×10⁶ number/cm² (~121% of the average CDNC over WI) but significantly reduce the precipitation by up to 45 mm (~15% of the average precipitation). The findings also revealed that the impact of trans-regional emissions in perturbing CDNC and precipitation is higher than that of regional emissions. Our results suggest that anthropogenic emissions can substantially lower water resources in this already stressed arid region in India. The study also highlights that policies need to aim emission reductions ubiquitously and not only over western India for mitigating pollution impacts on regional precipitation.

How to cite: Dhaka, S., Lakshmi, S., Vaishya, A., Ojha, N., Pozzer, A., Ansari, T., and Sharma, A.: Impacts of anthropogenic emissions on monsoon precipitation over western India: Insights from high-resolution regional modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14891, https://doi.org/10.5194/egusphere-egu25-14891, 2025.

EGU25-14891

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Black carbon (BC) aerosols, strong absorbers of solar radiation, induce atmospheric heating, altering vertical profiles of temperature, water vapor, and clouds. These impacts can lead to localized precipitation changes, and may also initiate changes to atmospheric circulation, with potentially far-reaching impacts on precipitation patterns.

While prior studies suggest BC's significant influence on precipitation, its role in both local and remote precipitation change remains insufficiently quantified. To address this gap, we explore the extent to which historical BC emissions have shaped regional precipitation. Specifically, we ask: how much could future BC changes influence regional precipitation, based on insights from the historical period?

Using the Community Earth System Model version 2 (CESM2), we have generated a 20-member ensemble of simulations of 1950–2014 with anthropogenic BC emissions fixed at 1950 levels. By comparing these to standard historical simulations with evolving emissions, we isolate the impacts of BC emission trends from 1950 to 2014 on global and regional climates.

Our results reveal that BC emissions have caused localized drying in regions of high emissions, notably over Europe during the 1980s–1990s and Eastern China in the early 21st century. Furthermore, we find indications that BC exerts a dampening effect on the most extreme precipitation events, highlighting its historical role in modulating climate extremes.

How to cite: Stjern, C. W., Samset, B. H., Alterskjaer, K., and Johansen, A. N.: Tracing Black Carbon's Historical Impact on Regional Precipitation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15895, https://doi.org/10.5194/egusphere-egu25-15895, 2025.

EGU25-15895

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Aerosol-cloud interactions contribute to 75–80% of the total radiative effect of aerosols and remain a major source of uncertainty in predicting future climate. Aerosols significantly influence the warm cloud properties by serving as cloud condensation nuclei (CCN). An increase in CCN leads to the formation of more numerous and smaller cloud droplets, suppresses warm rain by reducing the efficiency of collision and coalescence processes, and extends the cloud lifetime, and liquid water path (LWP) and/or cloud fraction (CF). The activation of a CCN into a cloud droplet is strongly influenced by its size and chemical composition, which subsequently affects the size distribution of cloud droplets and other cloud properties. Although the physical processes of nucleation are well documented for individual particles, the impact of aerosol size on cloud properties is often underestimated because both fine and coarse aerosols co-exist together. To bridge this gap, this study aims to address the impact of size-differentiated aerosols on warm cloud properties over the Northern Indian Ocean (NIO) by utilizing ~20 years of multi-satellite observation data.

The Arabian Sea (AS) and the Bay of Bengal (BoB) in the NIO were chosen in this study as these regions experience a continuous load of aerosols from natural and anthropogenic sources with high seasonal variations. Comparative analysis of size-segregated aerosol optical depth (AOD) revealed the dominance of coarse mode particles (c-AOD) over AS, and fine mode (f-AOD) over BoB. However, a significant increasing trend in the mean f-AOD, particularly during the post-monsoon (ON) and winter (DJF) seasons, is observed over both the AS (0.05/decade) and BoB (0.045/decade) from 2000 to 2021, primarily driven by rising anthropogenic emissions. Further, a climatological analysis of warm cloud CF during these seasons reveals a corresponding increasing trend over the AS (0.07/decade) and BoB (0.05/decade). A correlation analysis of c-AOD and f-AOD with warm CF was conducted, which revealed a stronger annual positive correlation of warm CF with c-AOD (AS: r = 0.56, BOB: r = 0.41) compared to f-AOD (AS: r = 0.37, BOB: r = 0.27). To further investigate the impact of f-AOD and c-AOD on cloud effective radius (CER) for a fixed LWP, an additional correlation analysis was performed. For low LWP (up to 70 gm^-2), an increase in CER was observed with both c-AOD and f-AOD, with a more pronounced increase in CER associated with c-AOD over both the AS and BoB regions. However, as LWP increased, f-AOD exhibited a faster decrease in CER over the BoB compared to the AS. In contrast, c-AOD consistently showed an increasing CER with rising LWP, indicating a contrasting effect relative to f-AOD. These results indicate the dominant radiative effect of fine mode aerosols on cloud formation against the classical microphysical effect of coarse mode aerosols.  Further analysis, incorporating meteorological parameters such as relative humidity and atmospheric stability, is essential to better understand these relationships and enhance the robustness of this study.

How to cite: Bangar, V. and Mishra, A. K.: Satellite-Based Analysis of Size-Segregated Aerosols and Their Effects on Warm Cloud Properties over the Northern Indian Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16951, https://doi.org/10.5194/egusphere-egu25-16951, 2025.

EGU25-16951

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Extreme weather events, such as extreme temperatures, water vapor transport, and the resulting extreme precipitation, have been occurring with increasing frequency and are projected to intensify further in a warming climate. Understanding how these events respond to climate change is critically important. Numerical models serve as essential tools for uncovering the mechanisms behind these phenomena, with spatial resolution being one of the key challenges. Leveraging advanced supercomputing resources, we have recently made significant advancements in developing high-resolution Earth system models based on the Community Earth System Model (CESM), featuring a 25 km atmospheric resolution and a 10 km oceanic resolution. Compared to the commonly used CMIP5 and CMIP6 models, the high-resolution Earth system model demonstrates substantial improvements in reproducing extreme weather events, thereby greatly enhancing the confidence in future projections.

How to cite: Gao, Y.: Enhancing the Simulation and Prediction of Extreme Temperature and Water Vapor in a Warming Climate Using a High-Resolution Earth System Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11612, https://doi.org/10.5194/egusphere-egu25-11612, 2025.

EGU25-11612

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The Southern Hemisphere (SH) stratosphere circulation can be organized around the development of the low-latitude jet (LLJ) in the upper stratosphere during winter months. The LLJ is associated with weak planetary wave activity, reduced residual circulation, and connections to westerly anomalies of the middle and upper stratosphere during early and mid-winter. The 2022 Hunga eruption coinciding with an anomalously strong LLJ year. Additionally, the LLJ is linked to a persistent, strong polar vortex in the lower stratosphere during October–December. This strong vortex, primarily driven by dynamical processes in winter, is further associated with enhanced ozone losses in spring, with ozone feedback reinforcing the vortex as sunlight returns in October.

How to cite: Wang, X., Yu, W., Randel, W., and Garcia, R.: Stratospheric Circulation in the Southern Hemisphere: links to tropical winds, ozone and Hunga Eruption, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15068, https://doi.org/10.5194/egusphere-egu25-15068, 2025.

EGU25-15068

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How to cite: Vaittinen, A., Sarnela, N., Sipilä, M., Brasseur, Z., Boyer, M., Righi, C., Thakur, R., Mazzola, M., and Quéléver, L.: New Particle Formation and Condensable Vapours in an Arctic Site: Ny-Ålesund, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18095, https://doi.org/10.5194/egusphere-egu25-18095, 2025.

EGU25-18095

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Active and passive sensors onboard satellites and suborbital measurements have shown frequent aerosol-cloud overlapping situations over several regions worldwide on a monthly to seasonal scale. However, retrieving the optical properties of aerosols lofted over clouds poses challenges. Primarily, the assumption of aerosol single-scattering albedo (SSA) in the satellite-based algorithms is known to be one of the largest sources of uncertainty in quantifying the above-cloud aerosol optical depth (ACAOD). On the radiative forcing aspect, the sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the aerosol loading, the absorption capacity of aerosols (SSA), and the brightness of the underlying cloud cover.

We contribute to addressing the uncertainties surrounding the absorbing aerosols-cloud radiative interactions by offering a novel, NASA’s A-train-centric, one-and-half decade long (2006-2022) global retrieval product of aerosols above cloud that delivers 1) spectral ACAOD, 2) spectral SSA of light-absorbing aerosols lofted over the clouds, and 3) aerosol-corrected cloud optical depth (COD). The synergy algorithm combines lidar retrievals of ACAOD derived from the ‘De-polarization Ratio’ method applied to CALIOP and the top-of-atmosphere (TOA) spectral reflectance from OMI (354-388 nm) and MODIS (470-860 nm) sensors to deduce the joint aerosol-cloud product. The availability of accurate ACAOD accompanied by a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD allow retrieval of SSA for above-cloud aerosols scenes using the ‘color ratio’ algorithm applied to UV and VIS sensors.

We will present multiyear (2006-2022), regional retrievals of UV-VIS spectral aerosol SSA above clouds, and it’s a comparison against ORACLES airborne in situ and remote sensing measurements and ground-based AERONET inversions. A preliminary uncertainty analysis suggests that an uncertainty of 20% in ACAOD can result in an error of ~0.02 at 388 nm and ~0.01 at 470 nm in the retrieved SSA from OMI and MODIS, respectively. Furthermore, the presented aerosol-cloud remote sensing algorithm assumes implications for the recently launched EarthCARE and PACE missions with potential synergy of ATLID lidar and OCI imager. The availability of the global aerosol-cloud joint product will reenergize the community by offering 1) an improved representation of aerosol extinction and absorption properties over clouds and 2) much-needed observational estimates of the radiative effects of aerosols in cloudy regions for constraining the climate models.

How to cite: Jethva, H., Torres, O., Kayetha, V., and Hu, Y.: One-and-half Decade Long Global Retrieval Dataset of UV-VIS Spectral Optical Depth and Single-scattering Albedo of Absorbing Aerosols above Clouds from A-train Active-Passive Synergy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14363, https://doi.org/10.5194/egusphere-egu25-14363, 2025.

EGU25-14363

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The EM27/SUN instrument is a FTIR spectrometer allowing to retrieve total atmospheric column abundance of CO2, CH4, CO and H2O. LSCE is currently developing a tropical network in the framework of the OBS4CLIM French project.

OBS4CLIM aims at deploying five EM27 at observatories located in tropical (Bolivia, French Guiana, Morocco, Ivory Coast) and background regions (Amsterdam Island, Indian Ocean) for long-term observations and satellite validation purposes (TROPOMI, OCO-2/3, GOSAT, MicroCarb). The chosen stations are also part of French National Observation Service and benefit from in situ greenhouse gas measurements.

The rapid growth of this EM27/SUN network requires developing tools to ensure data quality and availability. Therefore, LSCE has developed:

- An automatic data treatment chain based on PROFFAST (developed and maintained at KIT). Two models are used as a priori profiles (GGG2020, and CAMS) allowing to retrieve daily data in near real-time (NUBICOS project).

- Automatic enclosure systems to protect the instrument from a rough environment. This system allows increasing drastically the daily observations and data availability.

Four of the five stations are fully operational. We will present in details the network construction and the first measurement results.

How to cite: Lopez, M., Cassagne, M., Leuridan, H., Ticona, L., Burban, B., Mellouki, W., Hazan, L., and Ramonet, M.: A tropical EM27/SUN network for satellite validation and long term observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18600, https://doi.org/10.5194/egusphere-egu25-18600, 2025.

EGU25-18600

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Increasing concentrations of greenhouse gases (GHGs) in the atmosphere are the primary driver of the observed rise in global surface temperatures, meanwhile exceeding 1°C above pre-industrial levels. Addressing this challenge requires linking GHG concentrations to specific anthropogenic and natural sources as part of the global carbon budget. This study investigates the relationship between GHG concentrations measured in Thessaloniki, Greece, and potential long-range transport sources using a clustering approach.

The GHG data were obtained from the EM27/SUN Fourier Transform Infrared (FTIR) spectrometer, a ground-based low-resolution infrared spectrometer operated in the framework of the Collaborative Carbon Column Observing Network (COCCON) at a mid-latitude urban site. The instrument provides column-averaged dry air molar fractions of CH₄, CO₂, CO, and H₂O. Meteorological data for trajectory simulations were derived from the Global Data Assimilation System (GDAS) with a spatial resolution of 1° × 1°.

Clustering analysis was performed using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Seven-day kinematic back trajectories were calculated for the period 2019–2024 at two arrival heights, 1500 m and 3000 m above mean sea level. The findings aim to specify the influence of long-range transport on GHG concentrations over Thessaloniki, contributing to a more complete understanding of regional GHG source-receptor relationships and transport patterns.

How to cite: Panou, T., Mermigkas, M., Topaloglou, C., Balis, D., Dubravica, D., and Hase, F.: "Investigating Regional and Long-Range Transport Contributions to GHG Concentrations of a Mid-Latitude Urban Site" , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15708, https://doi.org/10.5194/egusphere-egu25-15708, 2025.

EGU25-15708

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NASA’s Atmospheric Science Data Center (ASDC) at Langley Research Center will present an overview of the Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission, focusing on the cutting-edge tools and services available to users for air quality research and environmental monitoring. TEMPO is a pioneering geostationary satellite that provides day light hourly observations of pollutants over North America, including measurements of ozone, nitrogen dioxide, and other critical pollutants.This presentation will highlight the ASDC’s role in archiving, distributing, and providing user support for TEMPO data. Attendees will be introduced to data access tools, visualization platforms, and analysis services designed to facilitate the use of TEMPO observations for scientific research and decision-making. Key resources, such as NASA Earthdata Search, Earth GIS, OPeNDAP, Worldview, Github Tutorials and Harmony services on the cloud, will be showcased, demonstrating how researchers can efficiently explore and download high-resolution data products.Additionally, the presentation will cover the application of TEMPO data in studying air quality trends, emission sources, and the impacts of pollution on public health and climate. Attendees will also gain insights into ASDC's open science initiatives, which encourage collaboration and data sharing to enhance the impact of TEMPO and NASA’s broader Earth science mission.Through this presentation, the ASDC aims to empower the scientific community with the tools and knowledge needed to harness the full potential of TEMPO data in addressing pressing environmental challenges.

How to cite: Mahmoud, H. and Radkevich, A.: Leveraging TEMPO Data: Tools and Services for Air Quality Monitoring and Research from the Atmospheric Science Data Center, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7314, https://doi.org/10.5194/egusphere-egu25-7314, 2025.

EGU25-7314

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Nitrous acid (HONO) is known to be the significant source of hydroxyl radicals (OH), impacting air quality and climate as a major oxidant in the atmosphere. Many studies have highlighted that the photolysis of HONO can produce substantial amounts of OH throughout the day. Despite the crucial role of HONO in tropospheric chemistry, more research is needed to improve understanding of global HONO budgets. To address this, we developed a prototype HONO retrieval algorithm from the Geostationary Environment Monitoring Spectrometer (GEMS). The retrieval algorithm comprises two major processes, commencing with the spectral fitting of UV spectral range (343-371 nm) using the direct fitting method to obtain the slant columns. Subsequently, the conversion of slant columns into vertical columns is achieved by applying the air mass factor. The last step involves background correction, wherein the slant column amounts of HONO included in the radiance reference spectrum are added to the differential slant columns. Enhancements of HONO resulting from wildfire events in Asia were detected using GEMS. Refining the GEMS HONO retrieval algorithm is expected to enhance our understanding of the diurnal cycle of HONO, along with tropospheric chemistry in Asia.

How to cite: Cha, H., Kim, J., Chong, H., González Abad, G., Park, S. S., and Lee, W.: Nitrous Acid (HONO) Retrievals from wildfire events by using Geostationary Environment Monitoring Spectrometer (GEMS) ultraviolet spectra, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15191, https://doi.org/10.5194/egusphere-egu25-15191, 2025.

EGU25-15191

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We present the status of the Level 0-1 processor for the Tropospheric Emissions: Monitoring of Pollution (TEMPO), with a primary focus on radiometric calibration. Multiple version updates have significantly improved the TEMPO Level 1 products, enhancing the quality of Level 2 products and enabling the detection of city lights, nightglow, and aurora signals during twilight hours. However, assessments of TEMPO Level 1 data (versions 1 to 3) indicated overestimations of Sun-normalized radiances when compared to radiative transfer calculations. To investigate these biases, we compared TEMPO solar irradiance measurements to those from multiple independent instruments and a high-resolution reference solar spectrum. For Earth radiance assessments, we conducted intercomparisons with spaceborne measurements from the Advanced Baseline Imager (ABI) instruments onboard the Geostationary Operational Environmental Satellite (GOES)-16 and -19. Located at the checkout position of 89.5°W for post-launch testing, GOES-19 ABI has provided comparable viewing geometries with TEMPO (at 91.0°W) over North America. On the other hand, comparisons with GOES-16 ABI (located at 75.2°W) may require corrections for viewing angles and bidirectional reflectance distribution function (BRDF) effects due to larger differences in geometries. Additionally, we compared TEMPO Sun-normalized radiances with radiative transfer simulations over Railroad Valley, which use ground-based surface reflectance measurements as input. In this work, we present the intercomparison results and propose potential approaches to mitigate the radiometric biases.

How to cite: Chong, H., Liu, X., Houck, J., Flittner, D. E., Carr, J., and Hou, W. and the TEMPO instrument calibration team: The Tropospheric Emissions: Monitoring of Pollution (TEMPO) Level 0-1 Processor – Radiometric calibration and intercomparison, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14596, https://doi.org/10.5194/egusphere-egu25-14596, 2025.

EGU25-14596

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In this study, we conducted the estimation of shortwave aerosol radiative forcing using the aerosol optical depth (AOD) and supplementary information from the Geostationary Environment Monitoring Spectrometer (GEMS) dataset. We used the libRadtran package for the radiative transfer modeling (RTM), and used the radiative forcing values provided from the Aerosol Robotic Network (AERONET) system for the input value of RTM and the validation task. Total 6 sites in the Korean peninsula are target regions, such as Seoul (Yonsei University and Seoul National university), Anmyeon, Gwangju, Gangneung, and Ulsan. In detail, we used the climatological mean of surface albedo and asymmetry parameter at 4 shortwave channels (440, 675, 870, and 1020 nm), and used daily representative single scattering albedo provided from the GEMS dataset in order to consider the different aerosol type (dust, non-absorbing, and black carbon types). These set-up conditions were finally decided after a number of sensitivity tests. As a result, our estimation of direct aerosol radiative forcing (DARF) at the surface and top of the atmosphere (TOA) shows high correlations with the DARF from the AERONET (correlation coefficient is 0.65 to 0.85 in all 6 sites). Our estimated DARF is a little underestimated compared to the DARF of AERONET, and it seems natural due to the spatial resolution difference. With this high performance, we can provide the daytime hourly variation of DARF over the whole Korean peninsula, which can be useful information to a number of application in the future.

How to cite: Koo, J.-H., Lee, J., and Yoo, J.-A.: Estimation and validation of direct aerosol radiative forcing in the Korean peninsula using the GEMS dataset, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19628, https://doi.org/10.5194/egusphere-egu25-19628, 2025.

EGU25-19628

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Black carbon (BC), the primary light-absorbing aerosol, has significant implications for atmospheric heating and climate change, with far-reaching effects on regional air quality and public health. In Iran, BC concentrations, primarily resulting from combustion processes such as industrial emissions, vehicular exhaust, and biomass burning, constitute a significant air quality challenge, particularly in urban regions with high levels of anthropogenic activity. However, there is a lack of studies on the long-term trends of BC in Iran, particularly regarding the effects of urban growth and land use changes on air quality and human health. This study systematically analyzes trends in BC concentrations from 1980 to 2023, both on a national and regional scales, using high-resolution data from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2).  The analysis includes temporal and spatial variations to evaluate the impact of anthropogenic and natural factors on BC levels over this period. A substantial increase in BC concentrations was observed from 1980 to 2023, followed by a decline after 2010. Regional analysis revealed higher BC levels in western Iran, driven by concentrated anthropogenic and industrial activities, compared to the sparsely populated, desert-dominated eastern regions, characterized by arid landscapes. Seasonal variations in BC concentrations were observed nationwide, with peak levels occurring in Tehran and Ahvaz during the winter. Trend analysis across various land use and land cover (LULC) types indicated that urban and agricultural expansion were the primarily drivers of increasing BC concentrations. Positive correlations were observed between the aforementioned factors and aerosol emissions, while water and grassland coverage were associated with reduced emissions in most regions. These findings underscore the necessity of expanding natural land use, such as forest coverage, and promoting sustainable urbanization as strategies to mitigate BC emissions.

How to cite: Shaheen, A., Yousefi, R., Wang, F., Kaveh-Firouz, A., and Ge, Q.: Assessing black carbon dynamics in Iran: the role of urban growth and land use changes in long-term trends (1980–2023), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5323, https://doi.org/10.5194/egusphere-egu25-5323, 2025.

EGU25-5323

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Nitrogen dioxide (NO₂), an atmospheric pollutant produced by fossil fuel combustion in vehicles and industrial processes, is harmful to human health, worsening respiratory and cardiovascular diseases. The main effects of NO₂ pollution on human health are respiratory infections, airway inflammation, asthma, and low birth weight, among others. Vehicle traffic in cities is one of the main sources of NO₂, affecting the health of the population living near highways. The highest NO₂ concentration occurs at distances between 200 and 500 meters from high-traffic highways. The study area, the metropolitan region of Campinas (MRC), Brazil, is a technological, industrial and economic hub with 3.3 million inhabitants and busy transport corridors that connect the southeast and central-west regions of the country. It is composed of 20 municipalities and is located in São Paulo state, the most developed and populated Brazilian state. The aims of this work are to map atmospheric NO₂ pollution and estimate NO₂ concentrations near the highways in the MRC using average daily vehicle flow (DVF) and NO₂ concentrations estimated from satellite images. Data on the tropospheric vertical column of nitrogen dioxide (in mol/cm²) values from 32 daily images from the Sentinel 5P satellite TROPOMI spectrometer that were collected from April 15 to May 20, 2024, were used. During that period, there was no rain, and the sky remained clear and cloudless. The images were processed to produce NO₂ median images during the study period. The NO₂ pollution map was produced by the spline interpolation algorithm method. To estimate the concentration of NO₂ near the MRC highways, a road map was used, and a 500 m buffer was drawn around the highways. The NO₂ pollution map was combined with the buffer map, and the median NO₂ concentration within the 500 m buffer around the highways was estimated. Pearson regression analysis was performed between the average DVF and the NO₂ concentration. The results revealed a positive and significant correlation (r=0.692; p= 0.004) between the DVF and NO₂ concentration near the highways estimated from satellite data. The highest NO₂ concentrations were observed near highways SP-083 (1.5591 mol/cm²; 45,000 vehicles/day), SP-330 (1.521 mol/cm²; 38,815 vehicles/day), and SP-075 (1.485 mol/cm²; 37,813 vehicles/day). The results of this study can be used in epidemiological research to identify neighborhoods and populations that live near high NO₂ concentration highways and are exposed to respiratory and cardiovascular disease risks. In the next step of this research, the NO₂ concentration values ​​estimated from Sentinel 5P images in mol/cm² units will be converted to µg/m³ units using data from ground-based measurement stations located in the MRC. In the future, this methodology can be used to produce highway NO₂ pollution maps for areas in which ground measurement station data are unavailable.

How to cite: Ferreira, M.: Using Sentinel 5P satellite and vehicle flow data to map NO2 air pollution near highways in the Metropolitan Region of Campinas, Brazil, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9328, https://doi.org/10.5194/egusphere-egu25-9328, 2025.

EGU25-9328

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The aim of this study is to investigate Particulate Matter (PM) sources and mechanisms of formations over the city of Naples (Italy) and their seasonal and day-to-day variations.

We have sampled fine particles with diameter < 2.5 μm (PM_2.5) and < 10 μm (PM₁₀) daily on pre-cleaned (700 °C for 2 h) quartz filters, during the months of May and November 2016-January 2017, on top of the historical building complex in Largo San Marcellino, Naples. We have measured the concentrations of total N/C together with their isotopic composition (δ¹⁵N and δ¹³C). We have also measured the concentration of major ions and interpreted the results with data of gaseous compounds, as well as consideration of the meteorology, using data and state of the art models of atmospheric circulation (Hysplit). Our point was to show that the uncertainty associated with quantification of sources contribution with an apportionment model decreases when the model is constrained with information derived from different methods.

Seasonal differences: the results show that the concentrations of total PM₁₀/PM_2.5, N/C measured in autumn are more variable than those measured in spring. This is related to a different wind regime, whereby in spring air masses mostly originated from West and South (the “clean” Mediterranean sea), whereas in autumn the wind blew air from North (over the highly urbanized and “dirty” European continent). This interpretation is supported by the concentration of major ions showing more scattered values in autumn for species typically originating from land (K⁺, NH₄⁺, NO₃^-), with high values on the 9^th and the 26-27^th of December and the 2^nd of January 2017. However, neither the monthly mean δ¹⁵N and δ¹³C, nor the daily values corresponding to the spikes show significant changes, suggesting that the isotopic composition of total N/C has limited power in identifying changes of mean monthly sources or for the spikes. 

Day-to-day variations: a significant change of the main species measured is found around the middle of May. This event is associated with a change in weather pattern going from a typical land-sea breeze wind regime (typically causing poor air circulation and stagnation of air masses) to an intense synoptic with winds originating mostly from South/South-West (the sea). Correspondingly, there is a peak in the concentration of major ions originating mostly from land (NO₃^-, SO₄^2-, Ca₂⁺, C₂O₄^2-, K⁺) towards the end of the land-sea breeze regime (9-11^th May), followed (10-15^th May) by an increase of the concentration of major ions originating mostly from the sea (Na⁺, Mg²⁺, Cl^-). The entire period (9-14^th) is characterized by a concurrent variation of total N, C, δ¹⁵N and δ¹³C. While the changes of δ¹⁵N are caused mainly by isotope fractionations, associated with the dissociation of NH₄Cl producing NH₃ and HCl, the changes of δ¹³C are caused mostly by a change of the source of total C, associated with carbonate (CO₃^2-) apportion.

We conclude that the concentrations and isotopic compositions of N/C in PM are useful tools only when coupled with other tools like the analysis of the meteorology and the concentration of major ions.

How to cite: Rubino, M., Sirignano, C., Chianese, E., Hernández-Ceballos, M. Á., Angyal, A., Marzaioli, F., Di Rosa, D., Caso, G., and Riccio, A.: Multiple lines of evidence help identify the sources and formation mechanisms of Nitrogen and Carbon in Particulate Matter sampled in the historical center of Naples (Italy), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13295, https://doi.org/10.5194/egusphere-egu25-13295, 2025.

EGU25-13295

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Dhaka, the capital of Bangladesh, is currently experiencing critically alarming levels of air pollution, with its Air Quality Index (AQI) exceeding 200, indicating hazardous conditions. This study investigates the factors contributing to Dhaka's deteriorating air quality over the past two decades by integrating AQI data with Land Use and Land Cover (LULC) analyses. Particular attention is given to the impacts of major development projects, including the Metro Rail, Elevated Expressway, and International Airport Terminal 3, on the city’s air quality. Comparative assessments of AQI before and after the completion of these projects reveal a significant worsening of air quality, attributed to increased construction activity and subsequent urbanization. The rapid expansion of impervious surfaces is identified as another critical factor exacerbating the AQI. The findings emphasize the urgent need for sustainable urban planning and air quality management strategies to mitigate the adverse effects of development on public health and the environment in Dhaka.

How to cite: Akhter, J. and Rayhan, M.: Assessing the Impact of Urban Development and Land Use Changes on Dhaka's Hazardous Air Quality, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14892, https://doi.org/10.5194/egusphere-egu25-14892, 2025.

EGU25-14892

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Monitoring emissions of nitrogen dioxide is crucial for understanding the atmospheric composition and its impacts on air quality and climate. This study aims to evaluate the accuracy of retrievals of nitrogen dioxide tropospheric column by the Tropospheric Emissions: Monitoring of Pollution (TEMPO) by comparing them against retrievals of the ground-based Pandora instruments.

The TEMPO is a visible and ultraviolet spectrometer flying aboard of a commercial telecommunications satellite, Intelsat 40e, in geostationary orbit over 91˚ W longitude, thus maintaining a continuous view of North America. High resolution measurements of radiance reflected by the Earth's back to the instrument's detectors enable retrievals of columns of nitrogen dioxide involved in the chemical dynamics of Earth’s atmosphere. TEMPO V03 Level 1, 2, and 3 data were recently made available from the Atmospheric Science Data Center (ASDC) via NASA EarthData Search.

Direct-Sun Pandora spectrometer is used to retrieve columnar amounts of trace gases in the atmosphere by the means of differential optical absorption spectroscopy at numerous locations around the globe.

ASDC has developed a set of Jupyter notebooks dedicated to TEMPO vs. Pandora comparisons of the columns of individual trace gases including one dealing with NO₂ tropospheric column. The notebooks allow a user to select a specific Pandora station and a timeframe of interest. The code downloads all relevant TEMPO L2 granules as well as the Pandora dataset. The latter is sub-set to the selected timeframe. Time series of the gas column retrievals along with their uncertainties are then derived with accounting for the quality flags from both datasets. Since Pandora measurements are significantly more frequent, a procedure computing weighted averages of them at the times of TEMPO retrievals was incorporated to the notebooks allowing direct comparison of gaseous columns from two sensors against each other.

The results derived by the ASDC tool show only qualitative agreement between the TEMPO and Pandora retrievals of nitrogen dioxide tropospheric column. it was also found that the discrepancies between the two are site dependent which may point to a potential problem with Pandora quality flags. Two attempts were made to improve comparison. Since TEMPO algorithm allows for negative NO₂ tropospheric columns, such retrievals were removed from consideration. There are also multiple TEMPO retrievals accompanied by uncertainty greater that the retrieved column. Removal of such retrievals constitutes another approach to improve comparison.

The findings of this study will contribute to the understanding of the reliability and applicability of space-based trace gases monitoring for air quality applications. The results will enhance our understanding of atmospheric processes related to tropospheric NO₂.

How to cite: Radkevich, A., Mahmoud, H., and Kaufman, D.: Comparison of nitrogen dioxide tropospheric columns retrieved by TEMPO and Pandora, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4493, https://doi.org/10.5194/egusphere-egu25-4493, 2025.

EGU25-4493

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Satellite remote sensing has the advantage of wide spatial coverage and high data consistency, which is an important technology for global atmospheric environment monitoring. However, due to the influence of cloud cover, satellite remote sensing faces the problem of data missing; moreover, the direct object of hyperspectral satellite remote sensing is the total amount of pollution gases in the atmosphere, which is different from the near-ground concentration that directly affects human health. To solve these problems, this research developed a remote sensing technology combining satellite spectral analysis and artificial intelligence. We use artificial intelligence to increase the spatial coverage of satellite and ground-based remote sensing, and make future short term predictions and their applications. Preliminary results show that the reconstruction of satellite remote sensing data supported by artificial intelligence is of great significance for environmental pollution monitoring and control.

How to cite: Liu, C., Hu, Q., Li, Q., and Zhang, C.: Spatiotemporal reconstruction of gas pollutants with high resolution and coverage using hyperspectral remote sensing and artificial intelligence, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1923, https://doi.org/10.5194/egusphere-egu25-1923, 2025.

EGU25-1923

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Volcano eruption is one of the most destructive natural disasters, and its direct release of toxic gases and volcanic ash can lead to atmospheric pollution, posing significant threats to human health and ecological balance. To investigate the environmental impact of volcanic emissions, we retrieved the vertical column densities (VCDs) of sulfur dioxide (SO₂) and bromine monoxide (BrO) using the Chinese highest-resolution atmospheric trace gas remote sensing satellite payloads: the Environmental Trace Gas Monitoring Instrument (EMI) series on-board the GaoFen (GF5-02) and DaQi (DQ-1) satellites.

Here, we present our study on two significant volcanic emission events. On January 15, 2022, a violent eruption occurred near the South Pacific Island nation of Tonga, which is a typical submarine volcano. During this eruption, the volcanic plume ascended directly into the stratosphere (above 20 km), releasing a substantial amount of SO₂ and spreading rapidly westward (~30 m/s). In contrast, the majority of the BrO dispersed southeastward slowly (~10 m/s) within the altitude range of 8–15 km on January 16. The differences in eruption height and timing resulted in the transport of SO₂ and BrO in distinct directions in the Southern Hemisphere.

Another case is the Sundhnukagigar volcano on Iceland's Reykjanes Peninsula, which is a typical fissure volcano. A significant eruption began at 21:00 on August 22nd, following an earthquake swarm; this was the largest eruption in the region since December 2023. Satellite data indicated that the volcanic eruption released high concentrations of SO₂, with the maximum SO₂ VCD exceeding 15 Dobson Units (DU). By the morning of the 26th, part of the air mass had been transported northward to the Arctic Svalbard region. Simultaneously, ground observations from Ny-Ålesund revealed that an unprecedented Arctic haze event occurred, with the SO₂ VCD reaching approximately 40 times the usual level. It is also important to note that, in the context of global warming, the ongoing activity of Iceland's volcanoes will further exacerbate the melting of local glaciers and permafrost. This, in turn, disrupts the gravitational balance of the overlying crust, leading to an intensification of volcanic activity. Therefore, it is essential to employ multi-instrument, multi-scale, and high-resolution observations to monitor volcanic activity and assess its impact on both regional and global climate and the environment.

How to cite: Luo, Y., Li, Q., Wu, K., Qian, Y., Zhou, H., and Si, F.: Two Typical Case Studies of Volcanic Eruption Trace Gases Based on EMI Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2443, https://doi.org/10.5194/egusphere-egu25-2443, 2025.

EGU25-2443

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Anthropogenic aerosols significantly deteriorate the urban air quality and climate of the western Indian region, nevertheless, the contributions from different sources (power, residential, transport and industries) to ambient particulate pollution has been uncertain. In this regard, high-resolution simulations have been conducted employing the WRF-Chem (v3.9.1) model to comprehensively assess contribution from major anthropogenic sources in post-monsoon (November 2019), when air quality is typically poor in the region. Model evaluation is conducted by comparing simulated near-surface aerosol concentrations (PM_2.5 and PM₁₀) and aerosol optical depth (AOD) against ground-based measurements (CPCB), satellite data (MODIS), and the reanalysis dataset (MERRA-2). The results show that the model captures the spatial distribution of AOD satisfactorily, with WRF-Chem simulated AOD (0.38 ± 0.10) aligning well with MERRA-2 AOD (0.54 ± 0.10) and MODIS AOD (0.50 ± 0.20). Surface PM_2.5 and PM₁₀ concentrations also meet performance metrics of Fractional Bias ≤ 60% and Fractional Error ≤ 75%, with FAC2 values of 0.9 and 0.7, respectively. Sensitivity analysis reveals spatial heterogeneity in dominant sector that contributes to PM_2.5 concentration over western India. The power sector dominates in most areas with an average contribution of ~14% from regional power sources, followed by regional industries (~12%), regional residential emissions (~9%), and regional transport (~5%). In the trans-regional emissions from the Indo-Gangetic Plain (IGP) and central India also, the power sector remains the largest contributor (~15%), followed by industry (10.5%). Our findings underscore the need for targeted emission reductions in high-impact sectors to improve air quality over western India.

How to cite: Shekhar, S., Dhaka, S., Vaishya, A., Ojha, N., Pozzer, A., and Sharma, A.: Quantifying the sources of anthropogenic aerosols over western India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14890, https://doi.org/10.5194/egusphere-egu25-14890, 2025.

EGU25-14890

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The Cerrado biome, a globally significant biodiversity hotspot, is undergoing rapid degradation primarily due to anthropogenic activities. Large-scale conversion of native vegetation for agriculture, particularly soybean and cattle ranching, and strong urbanization rates are the main drivers of the biome losses. Additionally, unsustainable water use, infrastructure development, and recurrent fires exacerbate ecosystem degradation, leading to significant biodiversity decline and ecosystem service impairment. A direct consequence of this change in land use is the generation of substantial quantities of air pollutants, mainly particulate matter of 2.5 and 10 𝜇m (PM2.5 and PM10, respectively). These particles, emitted from biomass burning, soil erosion, and dust storms, can penetrate the respiratory tract, leading to various health issues, including respiratory infections, cardiovascular disease, and increased mortality rates. Using measurements of meteorological variables and air pollutants from CETESB (Environmental Company of the State of São Paulo) from 2017 to 2023 in an important urbanized region of the Brazilian Cerrado, we characterized the seasonal distribution of PM2.5 and PM10, together with other pollutants, such as nitrogen oxides (NOx), carbon monoxide (CO) and ozone (O3). In addition, using different combinations of meteorological and air pollution variables, we trained machine learning models to predict the concentration of PM2.5 and PM10. We list Random Forest, XGBoost, and Artificial Neural Networks (ANN) among these models. Our results show that a lower concentration of air pollutants (PM10, PM2.5, CO, and NOx) is observed during summer, while, in contrast, the peak occurs during winter. This is directly related to the seasons with higher and lower precipitation rates. Curiously, O3 peaks in spring and is minimal in autumn, likely related to cloud occurrence. During the whole analyzed period, NOx, PM10, and PM2.5 exceeded the daily average limits of the World Health Organization by about 15, 22 and 35%, respectively. Regarding the predictive models, the random forest better predicted PM10 and PM2.5 concentrations. For PM10, the statistical results for the train (80% of the data)/test (20% of the data) set were R² = 0.79/ 0.92 (p-value < 0.05), with RMSE of 10.7 and 6.5 𝜇g m-3. For PM2.5, the model returned R² = 0.74/0.91, with RMSE of 4.3 and 2.6 𝜇g m-3 for the train/test set, respectively. Although not the best, the ANN also worked relatively well after proper tuning. Future investigations will extend and validate the predictions obtained in this study to other stations in the Cerrado biome with multiple models to spatialize the PM prediction and obtain the regions in which the most air pollutants are emitted. 

How to cite: Franco, M. A. and Teixeira, M.: Characterization and machine learning prediction of atmospheric pollutants in an urban region of the Cerrado biome, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20571, https://doi.org/10.5194/egusphere-egu25-20571, 2025.

EGU25-20571

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In Indian metropolitan cities, two-wheelers (2W) constitute 60–70% of traffic, making their emissions a significant contributor to urban air pollution. This study measured 2W exhaust emissions and driver exposure under real-world traffic conditions in the Chennai metropolitan area. Emission factors for CO, HC, and NO were 1.1, 0.02, and 0.03 g/km, respectively. However, limited studies on 2W are available due to the complexity of real-world measurements in Indian traffic conditions. The gaseous emissions from the measured vehicles are lower than their respective Bharat Stage (BS) standards except for CO. Personal exposure levels for PM₁₀, PM_2.5, and PM₁ were 212.5, 78.1, and 58.9 µg/m³, with the highest exposures occurring during idling and driving behind heavy-duty vehicles. The Multiple Particle Path Dosimetry (MPPD) model was used to estimate the deposition fractions in the human respiratory tract (HRT). Results indicated that PM_2.5 and PM₁ deposition fractions are higher in the pulmonary region, whereas PM₁₀ deposition is higher in the head region. 2W drivers are exposed to higher concentrations than any other motor vehicle driver. Since there is no substantiation of a tolerable limit of PM₁ exposure or a threshold beyond which no detrimental health implications occur, cautious planning is needed when developing the roads.

How to cite: Ranjan, S., K. Kuppili, S., and Nagendra SM, S.: Exploring the Nexus of Two-Wheeler Gaseous Contributions and Driver Exposure in a Million-Plus Population City, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2082, https://doi.org/10.5194/egusphere-egu25-2082, 2025.

EGU25-2082

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Delhi is one of the most polluted cities in the world with a rapidly growing population. Huge amount of VOCs is released into the atmosphere from both anthropogenic and biogenic emissions. Various types of VOCs are released from anthropogenic sources such as disinfectants and cleansers, paints and varnishes, wood preservatives, aerosol sprays, room fresheners, dry cleaners and organic solvents. Another important anthropogenic source is burning of fossil fuels in motor vehicles, which also releases VOCs. Various plants species also release VOCs like isoprene (biogenic VOCs) which upon oxidation with atmospheric oxidants like ozone (O₃), nitrate (NO₃) and hydroxyl radicals (OH) forms less volatile products which on further reaction forms secondary organic aerosols (SOA). VOCs are also responsible for formation of tropospheric ozone which is one of the major criterion air pollutants and causes various health issues.

Around 32 samples of VOCs have been collected in the NCT of Delhi using charcoal tubes from the selected sites, VIZ., Okhla Phase 2 (OKHL, Industrial site), Sri Aurobindo Marg (SAM, traffic intervention site), Income tax office (ITO, traffic intervention site), Jawaharlal Nehru University (JNU, Institutional site). Sample preparation has been done following the protocol given by NIOSH 1501 method for xylene analysis, which is widely accepted as a “golden standard” for Industrial Hygiene sampling. Collected samples were run on GC-FID and concentration of VOCs is determined. The average concentration of Total VOCs at SAM is found to be 382.07µg/m³ while it is 200.14, 242.63 and 452.62 µg/m³ at JNU, OKHL and ITO, respectively. Out of all the VOCS, benzene and toluene represents the highest percentage with benzene representing a percentage of 17%  and 18% at SAM, JNU, Okhla and ITO, respectively and Toluene  contributing to a percentage concentration of 15% , 13%, 16% and 15% respectively at SAM , JNU, Okhla and  ITO thus owing to high vehicular emissions in Delhi. Individual average concentration at evening is higher than individual average concentration at morning at all chosen sites.  Also individual concentration of benzene and toluene is higher than other VOCs being 64.14 µg/m³ and 59.13 µg/m³ respectively at SAM, 35.64 µg/m³ and 25.83 µg/m³ at JNU, 79.6 µg/m³ and 69.9 µg/m³ at ITO and 41.92 µg/m³ and 37.80 µg/m³ at Okhla. It has planned to evaluate both the carcinogenic and non-carcinogenic risk associated with the chosen VOCs. This research will help us to get knowledge of sources of emission of VOCs. Further we will get a knowledge of the carcinogenic and non-carcinogenic impacts of VOCs and the percentage of population in Delhi which is getting directly or indirectly exposed to the carcinogenic VOCs. Hence it would help us in determining the health risk associated with VOC emission which would help in formulating effective strategies for controlling VOC emission. This would further aid us in reducing tropospheric ozone which is also a pollutant of concern. This study can also be used further in understanding atmospheric chemical reactions, photochemical smog pollution, assessment and forecast of possible change in atmospheric environment on the regional/global scale.

How to cite: Sharma, R.: Volatile organic compounds in ambient air of Delhi, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5764, https://doi.org/10.5194/egusphere-egu25-5764, 2025.

EGU25-5764

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In 2018, international shipping accounted for significant anthropogenic greenhouse gas emissions, contributing approximately 740 million tons of CO₂ according to the voyage-based method of the Fourth International Maritime Organization (IMO) Greenhouse Gases Study [1] and 880 million tons based on the CEDS and EDGAR inventories [2]. Recognizing this impact, the IMO adopted a long-term strategy in 2023 to achieve decarbonisation of global shipping by mid-century. However, concrete measures remain under development. A recent assessment of the 2018–2022 period suggests emissions are once again approaching 2008 levels, attributed to stagnation in improving energy efficiency [3]. This highlights the urgency of evaluating the potential of operational measures to mitigate emissions.

Voyage optimization, or ship weather routing, is an operational strategy leveraging meteo-oceanographic data to minimize energy consumption. This reduction can be achieved through spatial diversions, speed variations, or a combination of both. VISIR-2 [4], an open-source Python-based model, computes least-CO₂ routes by optimizing spatial diversions. Using a validated graph-search algorithm, the model integrates ocean currents and avoids adverse sea conditions [5].

In this study, we apply VISIR-2 to an ocean-going vessel operating on the Shanghai–Los Angeles/Long Beach route, identified as one of the first green corridors of shipping [6]. Simulations are conducted for both eastbound and westbound voyages over an entire calendar year, with and without the influence of ocean currents. We evaluate the resulting CO₂ savings, analysing their dependence on engine load and environmental conditions.

These results demonstrate the potential of operational measures like voyage optimization to contribute to shipping decarbonisation. The VISIR-2 model is currently employed within the EDITO-Model Lab project [7], contributing to developing a digital twin of the ocean. This work underscores the importance of open-source tools in fostering sustainable maritime practices and achieving the IMO's decarbonisation goals.

References
[1] https://www.imo.org/en/ourwork/Environment/Pages/Fourth-IMO-Greenhouse-Gas-Study-2020.aspx
[2] Deng, S., Mi, Z. A review on carbon emissions of global shipping. Mar Dev 1, 4 (2023). https://doi.org/10.1007/s44312-023-00001-2
[3] https://www.shippingandoceans.com/post/international-shipping-emissions-return-to-peak-2008-levels-due-to-insufficient-energy-efficiency-im
[4] https://doi.org/10.5281/zenodo.8305526
[5] Mannarini, G., Salinas, M. L., Carelli, L., Petacco, N., and Orović, J.: VISIR-2: ship weather routing in Python, Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, 2024
[6] https://www.c40.org/news/la-shanghai-implementation-plan-outline-green-shipping-corridor/
[7] https://www.edito-modellab.eu/

How to cite: Salinas, M. L. and Mannarini, G.: Voyage Optimization with the VISIR-2 Model on the Shanghai–Los Angeles Green Corridor of shipping, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16374, https://doi.org/10.5194/egusphere-egu25-16374, 2025.

EGU25-16374

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Shipping is a high-energy-consuming sector and a significant source of climate-related and harmful pollutant emissions. In response to growing environmental concerns, the maritime sector has been subject to stringent regulations aimed at reducing emissions, achieved through the adoption of alternative fuels and emission control technologies. Accurate and diverse emission factors (EFs) are critical for quantifying shipping’s contribution to current emission inventories and projecting future trends under various policy scenarios. This study presents advancements in the development of emission factors for ships, incorporating alternative fuels, biofuels and emission control technologies. The methodology integrates statistical analysis of emission data from an extensive literature review with newly acquired on-board emission measurements. To ensure high resolution and applicability across diverse operational conditions, the emission factors are formulated as functions of engine load and categorized by engine type and fuel used. The results provide insights into the emission performance of ships and intend to support the development of robust, up-to-date emission models and inventories, contributing to the broader goal of sustainable maritime transport.

How to cite: Grigoriadis, A., Chountalas, T., Fragkou, E., Chountalas, D., and Ntziachristos, L.: Advancing load-dependent emission factors for ships: Integrating alternative fuels, biofuels, and control technologies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15097, https://doi.org/10.5194/egusphere-egu25-15097, 2025.

EGU25-15097

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As a major air pollutant and precursor of ozone (O₃), anthropogenic nitrogen oxides (NO_X = NO + NO₂) have been effectively controlled in China since peaking around 2012. However, the evolving contrast of emissions across cities and its impacts on secondary pollutants such as O₃ remain poorly understood, primarily due to the limitations of existing emission inventories. Here we track the historical high-resolution (5 km) NO_X emissions based on POMINO-OMI and POMINO-TROPOMI NO₂ VCDs, adopting our previously developed inversion, PHLET. The results demonstrate significantly weaker NO_X emission declines in economically small cities where environmental pollution received much less attentions, leading to a shift of emission burdens toward western and non-capital cities. Moreover, simulations based on GEOS-Chem indicate that such disparities in NO_X emission trends have inhibited the mitigation of O₃ mainly in the western China, and even added up to the O₃ increase in some areas of the North China Plain. Our study points to the value of satellite-based inversion to access historical environmental regulations, and emphasizes the importance of collaborative pollution control across regions for comprehensive pollution control in China and other Global South countries undergoing rapid emission changes.

How to cite: Kong, H., Lin, J., Chen, L., Zhang, Y., and Wang, S.: City-level Disparities in NOX Emission Trends and Their Inhibitory Effects on O3 Mitigation in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3222, https://doi.org/10.5194/egusphere-egu25-3222, 2025.

EGU25-3222

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The Indo-Gangetic Plain (IGP) is a globally recognized hotspot for high aerosol loading, necessitating precise modelling to understand its spatial and temporal dynamics. This study evaluates the performance of differently parameterized Seasonal Autoregressive Integrated Moving Average (SARIMA) models in forecasting the Aerosol Optical Depth (AOD) at 550 nm retrieved from the CERES (Clouds and the Earth's Radiant Energy System) satellite platform across eight  locations: Delhi, Dhaka, Jaipur, Kanpur, Karachi, Kolkata, Lahore, and Varanasi in the IGP. Using long-term AOD datasets from CERES during the period of 2005 to 2020, we tested various SARIMA configurations to capture seasonal trends and irregular variations specific to urban environments. The SARIMA configurations tested include configure_1: (1,0,1)(1,0,1)₁₂, configure_2: (1,1,1)(1,1,1)₁₂, configure_3: (2,0,1)(2,0,1)₁₂, and configure_4: (2,1,1)(2,1,1)₁₂ These configure models were compared with CERES-derived observations for AOD at the study sites for the next two years, that is, Jan, 2021 to Dec, 2022. Each configuration was assessed for data stationarity using the Augmented Dickey-Fuller (ADF) test and if not follows, then the differentiation method has been used to stationaries the series. The Model performance was evaluated using multiple statistical metrics, including normalized Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Squared Error (RMSE), Mean Bias Error (MBE), and Mean Absolute Percentage Error (MAPE) for every configuration showed the low metric values. The result indicates high correlation coefficients, ranging from 0.54 to 0.91, and R-squared values, varying between 0.31 and 0.81 for all configurations that significantly determined the best-suited models for each location. Every modelled configuration has been checked with 95% and 99% confidence interval (with alpha=0.05 and 0.01, respectively) showing the p-value <0.001. These results emphasize the models' ability to replicate observed AOD patterns effectively. It reveal that parameter sensitivity plays a critical role in predictive accuracy, with optimal configurations varying across locations due to heterogeneity in aerosol sources and meteorological conditions. The present study underlines the importance of site-specific model tuning for reliable aerosol forecasting in densely populated and pollution-prone regions. These insights provide a foundation to enhance air quality prediction studies and address health, and climate impacts associated with aerosols in the IGP.

How to cite: Mall, A. and Singh, S.: Comparison of Differently Parameterized SARIMA Models using CERES-Derived Aerosol Optical Depth over Indo-Gangetic Plain, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12277, https://doi.org/10.5194/egusphere-egu25-12277, 2025.

EGU25-12277

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Over the past 15 years, imaging spectrometers developed at the NASA Jet Propulsion Laboratory have significantly advanced the field of remote sensing of methane (CH4) and carbon dioxide (CO2) point source emissions. This began in 2008 with airborne observations from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), 2013 with the next generation AVIRIS-NG instrument, and has culminated with the launch of NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) in 2022.

These instruments have identified thousands of CH4 and CO2 point source emissions across the oil and gas, waste, and energy sectors, contributing in some cases to emission mitigation efforts. As part of an extended mission, EMIT coverage will expand beyond the arid regions of Earth to cover terrestrial surfaces between +51.6° and −51.6° latitude, enabling direct attribution of anthropogenic emissions on a global scale. EMIT's measurements and greenhouse gas data products are accessible through NASA’s Land Processing DAAC and the U.S. GHG Center, with all associated code available as open source. These data are already being utilized by public, private, and non-profit organizations, including UNEP IMEO and the Carbon Mapper Coalition. Additionally, new airborne instruments, such as AVIRIS-3 (2023) and the planned AVIRIS-5, promise enhanced sensitivity to CH4 and CO2 point sources, offering the potential for direct comparisons with satellite-based EMIT observations.

The Carbon Investigation (Carbon-I), a proposed mission for the NASA Earth System Explorer Program, reflects a dramatic advancement in greenhouse gas mapping capability. It provides a unique combination of coverage, high spatial sampling, and very high sensitivity, to permit quantification of emissions that cannot be observed with current technology. With contiguous global observations of CH4, CO2, and CO at 300 m sampling every 28 days with targeted observations at 30 m sampling, Carbon-I will permit emission quantification at the global to regional scales as well as for localized point sources. Consistent with NASA’s Open Source Science Initiative, all Carbon-I data and code will be publicly accessible, empowering Earth Action initiatives worldwide.

How to cite: Thorpe, A., Green, R., Frankenberg, C., Michalak, A., Thompson, D., Brodrick, P., Chadwick, D., Eastwood, M., Scott, V., Frazier, W., Fahlen, J., Coleman, R. W., Xiang, C., Jensen, D., Villanueva-Weeks, C., Lopez, A., Vinckier, Q., Bender, H., Chlus, A., and Chapman, J.: Advancing Greenhouse Gas Mapping with JPL Imaging Spectrometers: AVIRIS, EMIT, and Carbon-I, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14903, https://doi.org/10.5194/egusphere-egu25-14903, 2025.

EGU25-14903

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Background aims: Life cycle assessment (LCA) is widely used to evaluate the carbon footprint (CF) of milk production. Changes in soil organic carbon (SOC) stock play a vital role in agricultural greenhouse gas emissions. However, no consensus has been reached to incorporate SOC changes into agricultural LCA. This study aims to evaluate the CF of milk production using LCA methodology with integrating  SOC balance based on data from Viikki Research Farm at Helsinki. Methods: The CF of milk production was analyzed for 2022 and 2023 using the Solagro Carbon Calculator. Furthermore, the study explored the soil carbon and nitrogen balances using the DNDC model, for a comparison with IPCC Tier 1 & Tier 2 methods and the real measurements. Results and conclusions: Real measurements demonstrated substantial SOC loss from grassland and subsequent annual cropland, which was 607 and 3939 kg C ha^-1 in 2022 and 2023, respectively. Incorporation of those results increased the CF of milk production. Estimated based on DNDC modeling, the SOC loss exceeded the measured results in 2022 and was underestimated in 2023, while the IPCC method showed SOC sequestration in 2022. The observed emissions fluctuation between the two years was related to the rotation between perennial grass and annual crop, and harsh wintertime conditions affecting crop growth. This study underscores the importance of SOC change in agricultural LCAs. While direct measurements may have limitations, a more profound understanding of SOC dynamics and better calculation is crucial to minimize bias in CF estimations.

How to cite: Gao, Y., Hu, T., Roitto, M., Jokiniemi, T., Sandell, M., Pihlatie, M., and Tuomisto, H.: Life cycle assessment of milk production: integrating changes in soil carbon stock with eddy covariance and DNDC modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20229, https://doi.org/10.5194/egusphere-egu25-20229, 2025.

EGU25-20229

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The effects of major greenhouse gas (GHG) emissions in West Africa remain insufficiently documented. Over two consecutive years, we monitored soil GHG emissions using a chamber-based experimental setup across four contrasting land management conditions in the Sudanian savanna. The environmental drivers of the emissions were assessed through stepwise linear regression and ANOVA statistical tests. Our results show that, regardless of land management conditions, N₂O release occurs at the highest rate in rice fields (4.29±2.9 µg N m^-2 h^-1). The soil acts as a sink for CH₄ in the forest reserve (-1.09±7.67 µg C m^-2 h^-1), whereas degraded lands, such as cropland and rainfed rice farms, exhibit CH₄ release at rates of 1.03±13.1 µg C m^-2 h^-1 and 5.93±12.28 µg C m^-2 h^-1, respectively. Livestock breeding contributes significantly to CH₄ emissions in grasslands, where the annual mean CH₄ flux is the highest (16.79±6.69 µg C m^-2 h^-1). The statistical analysis indicates that 53.8% and 50.2% variability in the CH₄ flux is explained by soil moisture and soil temperature respectively in the grassland and rice field. Soil moisture is negatively correlated with N₂O release, while the relationship with CH₄ is positive in grassland and rice fields, where higher CH₄ emissions are observed. N₂O flux shows a positive correlation with soil temperature. These findings suggest that land degradation exacerbates CH₄ emissions, and the effect of fertilizer use on biomass during the growing season increases CH₄ release in rice fields by approximately threefold. At the peak of the raining season, the forest CH₄ sink reaches the highest -6.08±14.7 µg C m^-2 h^-1 while the rainfed rice field releases 9.14±29.57 µg C m^-2 h^-1. Overall, there is intra annual variability of GHG fluxes with dry and wet years showing different magnitude of N₂O and CH₄ emissions. The patterns of GHG flux dynamics in this data-scarce region is better clarified through our investigation. We conclude that GHG emissions in response to land cover degradation and agricultural practices, such as fertilizer use, are significant in the Sudanian savanna and urgent decisions are needed to mitigate these effects.

How to cite: Oussou, F. E., Sy, S., Bliefernicht, J., Spangenberg, I., Guug, S. S., Steinbrecher, R., Schäffler-Schmidt, A., Kiese, R., Ayamba, M., Yalo, N., Asiwaju-Bello, A. Y., Sawadogo, W., Olusegun, C. F., Amekudzi, L. K., and Kunstmann, H.: Evaluation of Chamber-based soil greenhouse gas emissions in contrasted land use of the Sudanian savanna, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19307, https://doi.org/10.5194/egusphere-egu25-19307, 2025.

EGU25-19307

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 Providing sufficient and nutritious food while reducing climate emissions footprints from food systems is a Grand Engineering Challenge for India. The increasing dietary emissions pose a serious threat to achieving the national net-zero goal by 2070, yet such emissions are not yet accounted for in India’s Climate Action Plans. Since the 1990s, India’s dietary transitions have been largely propelled by economic development and intensive urbanization, yet such transitions have occurred unequally between urban and rural regions across India.

The regional and temporal heterogeneity in dietary consumption patterns across different populations and the corresponding GHG emissions is not well known. Here, we apply a life-cycle approach to quantify the regional, demographical, and food commodity-specific GHG emissions (CO₂, N₂O, and CH₄) based on detailed household-expenditure data across three national-scale censuses (1999, 2011, 2022). We differentiate such emissions across twelve major food groups that are typically consumed in 88 distinct NSSO regions with demographics (rural and urban) differentiated by income. Our findings suggest that between 1999-2022, the per capita consumption of animal-based products has increased by ~20% respectively, and a ~15% decrease in wholegrain intake. Emissions from dairy (34%), wholegrain (31%), and meat (18%) food groups contributed more than 80% of total dietary emissions for 2011.

The demographical analysis suggested that household expenditure directly influences GHG emissions. For example, the highest expenditure decile of the population was 2.2 kgCO₂eq cap^-1 day^-1  with 0.7 kgCO₂eq cap^-1 day^-1  for the lowest decile in 2011Both rural and urban regions have per capita GHG emissions similarly, but the total emissions and share of food groups varied extremely with the household expenditure. The disparities in total emissions remain as high as 65% among poor and rich households, with poor houses having wholegrain-dominated emissions and rich households having dairy-dominated emissions. The spatial examination further showed the high heterogeneity in emissions among and within Indian states. Our findings highlight the opportunities and challenges in using food consumption as a lever for climate change while also reducing food inequality by shifting to healthier diets. Such findings can help strengthen State Climate Action Plans to help towards green agriculture and sustainable consumption.

How to cite: Yadav, S. and Balasubramanian, S.: Quantifying regional and temporal heterogeneity in greenhouse gas emissions from Indian diets, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19539, https://doi.org/10.5194/egusphere-egu25-19539, 2025.

EGU25-19539

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Hydrogen could play a crucial role in achieving climate neutrality by serving as an energy carrier for renewable sources, offering an alternative to traditional fossil fuels. However, researchers are investigating the impact of hydrogen emissions, as its leakage into the atmosphere poses a concern due to its potential to indirectly influence methane’s atmospheric lifetime and thereby extending its greenhouse effect. Therefore, minimising hydrogen emissions would reduce any potential environmental impact while enhancing safety and efficiency throughout the hydrogen value chain. Thus far, the literature lacks a verified data inventory on the amount of hydrogen emitted from the value chain. Little to no standardized data are present for many elements of the value chain. Otherwise, when present, efforts are still needed for their collection and validation in a unique inventory. The research community needs to address this by improving the capability to quantify small and large emissions and delivering validated methodologies and techniques for measuring or calculating them. An open-access and comprehensible user-friendly tool is urgently needed to better quantify the emissions from the whole hydrogen value chain. The pre-normative research on hydrogen release assessment (NHyRA) project is specifically designed to address these urgent needs. As a first step in this process, the project defined the hydrogen value chain, identifying its main components’ typical operative conditions and recognizing the potential sources of hydrogen emissions.  The next step, the project is working to update an open-access first version of the hydrogen emissions inventory to serve as a reference for the scientific and industrial community. Therefore, by welcoming and validating any contribution of new data, including from outside the NHyRA Consortium, subsequent versions of the inventory will include a more significant amount of data for some of the archetypes (i.e. processes or equipment) in the hydrogen value chain section, to ensure consistent scenario analysis and provide mitigation action recommendations. Furthermore, the NHyRA Consortium experts have identified hydrogen detection and quantification techniques and instruments, covering those which are commercially available and emerging. In this regard, partners of the Consortium have identified three monitoring categories: Detection of emissions at the component level, Detection and quantification of emissions at the component level, and detection and quantification of emissions at the area/site level. Additionally, new or adequately adapted experimental, theoretical, and simulation methodologies will be validated to perform laboratory or in-field measurements to achieve the ambitious goal. Experimental tests will also be performed on the most critical elements of the hydrogen value chains by the partners of the Consortium. A complete picture of the hydrogen emission scenarios, applied on the middle (2030) and long (2050) term European hydrogen economy, will be developed to enable decision-makers to quantify the impact of hydrogen emissions in the energy system transition, identifying  and prioritizing effective risk mitigation actions. Finally, the project will formulate recommendations for Standards and Technical Specifications.

How to cite: Connor, A., Guzzini, A., Holewa-Rataj, J., Piras, P., Claveul, J., Robino, M., and Kostereva, A.: Pre-normative research on hydrogen release assessment, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19010, https://doi.org/10.5194/egusphere-egu25-19010, 2025.

EGU25-19010

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Oxygenated volatile organic compounds (OVOCs) significantly contribute to the radical formation in the troposphere, enhancing atmospheric oxidation capacity and driving secondary pollutant production. However, uncertainties in OVOC emissions hinder accurate assessments of their regional impacts. This study updates OVOC emission profiles for the Yangtze River Delta (YRD) region and integrates them into the Community Multiscale Air Quality (CMAQ) model to refine OVOC estimations. The updated model effectively captures the diurnal variations of most OVOCs, significantly reducing biases compared to simulations based on previous inventories. OVOCs, particularly formaldehyde (HCHO), are key precursors of hydroperoxyl radicals (HO₂), which play a dominant role in ozone production across the YRD. Anthropogenic emissions, primarily from industrial activities and vehicular sources, account for 40−60% of total OVOCs. Sensitivity simulations reveal that reducing emissions of reactive OVOCs, such as HCHO and glyoxal, effectively lowers regional ozone levels. These findings underscore the pivotal role of OVOCs in radical chemistry and ozone formation, providing insights for mitigating ozone pollution in rapidly urbanizing regions like the YRD.

How to cite: Li, J.: Photooxidation of Oxygenated Volatile Organic Compounds as a Major Source of Hydroperoxyl Radicals Driving Ozone Formation in the Yangtze River Delta Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21194, https://doi.org/10.5194/egusphere-egu25-21194, 2025.

EGU25-21194

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Monoterpenes, the second most abundant biogenic volatile organic compounds globally, are crucial in forming secondary organic aerosols, making their oxidation mechanisms vital for addressing climate change and air pollution. This study utilized cyclohexene as a surrogate to explore first-generation products from its ozonolysis through laboratory experiments and mechanistic modeling. We employed proton transfer reaction mass spectrometry with NH₄⁺ ion sources (NH₄⁺-CIMS) and a custom-built OH calibration source to quantify organic peroxy radicals (RO₂) and closed-shell species. Under near-real atmospheric conditions in a Potential Aerosol Mass-Oxidation Flow Reactor, we identified 30 ozonolysis products, expanding previous data sets of low-oxygen compounds. Combined with simulations based on the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere and relevant literature, our results revealed that OH dominates over ozone in cyclohexene oxidation at typical atmospheric oxidant levels with H-abstraction contributing 30% of initial RO₂ radicals. Highly oxidized molecules primarily arise from RO₂ autoxidation initiated by ozone, and at least 15% of ozone oxidation products follow the overlooked nonvinyl hydroperoxides pathway. Gaps remain especially in understanding RO₂ cross-reactions, and the structural complexity of monoterpenes further complicates research. As emissions decrease and afforestation increases, understanding these mechanisms becomes increasingly critical.

How to cite: Li, Y., Ma, X., Lu, K., and Zhang, Y.: Investigation of the Cyclohexene Oxidation Mechanism Through the Direct Measurement of Organic Peroxy Radical, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14804, https://doi.org/10.5194/egusphere-egu25-14804, 2025.

EGU25-14804

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