This session brings together researchers working on urban air quality, greenhouse gases, and the indoor–outdoor air pollution interface. We invite contributions on urban air pollution, heat stress, urban carbon budgets, indoor and outdoor emission sources, indoor–outdoor exchange processes, and air pollution impacts on health. Topics include sensor networks, personal monitoring, airborne observations, high-resolution modelling and downscaling, source apportionment and isotopic attribution, ambient and indoor atmospheric chemical processes, biogenic and anthropogenic precursors to secondary pollution formation, community and personal exposure quantification, allergens, and air pollution and climate-related health effects.
Cities are at the heart of the climate challenge – and of the climate solutions. Responsible for a large share of fossil-fuel emissions, but also hubs of innovation and community engagement, they hold a unique position to accelerate the transition to climate neutrality.
While most cities recognize the need for climate action, effective policy implementation is often hampered by a lack of timely, reliable, and spatially detailed greenhouse gas (GHG) emission data. Traditional, statistic-based inventories frequently suffer from inconsistency, time lags, and missing local detail.
The ICOS Cities project (PAUL – Pilot Applications in Urban Landscapes), running from 2021 to 2025, was co-designed by scientists, policymakers, and local stakeholders to explore how techniques to quantify and partition CO2 emissions and emission reductions based of direct observations can improve informed climate action.
In three pilot cities, Paris, Munich, and Zurich, ICOS Cities brought together and evaluated the most innovative measurement approaches of greenhouse gas emissions in densely populated urban areas. State-of-the-art instrumentations were deployed and innovative combinations of measurements, modelling and inventories further developed.
The most important insight from the ICOS Cities project is that direct observations of GHG fluxes and concentrations combined with inverse modelling can severely support and improve inventories and general knowledge on greenhouse gas emissions from cities.
The presentation will present the key results of the project and give an outline how future services can be developed based on the project results.
How to cite: Kutsch, W. L. and the ICOS Cities Team: Observing urban greenhouse gas emissions – key results of the ICOS Cities project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10633, https://doi.org/10.5194/egusphere-egu26-10633, 2026.
Cities contribute substantially to anthropogenic greenhouse gas emissions and are increasingly implementing mitigation policies. Robust, sector-resolved emission estimates are needed to assess the effectiveness of these policies. We analyse the capabilities of an inversion framework with a 10m resolution transport model to provide sector-specific emission estimates for the city of Paris.
We use the atmospheric transport model GRAMM/GRAL to compute hourly steady-state wind fields and concentration maps covering central Paris with a horizontal resolution of 10 m. The high resolution makes it possible to simulate street channelling and building effects in densely populated urban areas.
We use two different prior inventories of anthropogenic CO2 fluxes – TNO GHGco_v4 and Origins.earth – and the Vegetation Photosynthesis and Respiration Model (VPRM) for the biogenic fluxes at high spatial and temporal resolution. We then evaluate the spatial and temporal patterns of the simulated concentrations with in-situ measurements from the ICOS Cities project’s network of mid- and high-cost instruments in Paris and discuss shortcomings and uncertainties induced by the model.
Finally, we conduct a Bayesian inversion for an optimized emission estimate based on the available CO2 data for 2023 and 2024. We assess the robustness of the inversion by testing the sensitivity of posterior fluxes on key methodological choices and input data sets, and we discuss the implications of our findings for the city of Paris.
How to cite: Maiwald, R., Utard, H., Chariot, M., Denier van der Gon, H., Ramonet, M., Laurent, O., and Vardag, S. N.: Urban CO2 inversions for Paris using ICOS Cities observations and GRAMM/GRAL, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19544, https://doi.org/10.5194/egusphere-egu26-19544, 2026.
Carbon dioxide (CO2) emissions from urban areas constitute the largest share of total anthropogenic emissions. At the same time, cities have positioned themselves as frontrunners in the implementation of emission reduction measures, driven by ambitious goals to achieve carbon neutrality within short timeframes. To design and evaluate such measures, localized CO2 measurement and modelling techniques are under development and demonstration deployments are underway in urban environments to estimate emissions, as well as their temporal evolution and trends, at high spatial and temporal resolution.
In the Rhine–Neckar region, encompassing the cities of Heidelberg and Mannheim in southwest Germany, we have established the UNICORN (UnIversity Network for CO2 in the Rhine–Neckar metropolitan area). The network consists of more than a dozen in-situ mid-cost CO2 sensors, a Fourier Transform Spectrometer (FTS) and a Dual Comb laser Spectrometer (DCS) for horizontal path measurements, a sun-viewing FTS with vertical column sensitivity and a CO2 camera for snapshot images of the local power plant. The in-situ nodes are based on the design developed by the University of California, Berkeley, for the BEACO2N (Berkeley Environmental Air-quality & CO2 Network) and equipped with ancillary air quality sensors measuring carbon monoxide, nitrogen oxides, ozone, and particulate matter. For estimating emission distributions from the observed concentration gradients, we employ the GRAMM–GRAL atmospheric model, which operates at a horizontal resolution of 10 m across the study domain.
Key challenges in establishing the UNICORN include optimal sensor placement, calibration of sensors under resource constraints, combining the various techniques under consideration of their sensitivity characteristics, effective use of ancillary meteorological and air quality data, robust estimation of background concentrations and their variability, and the derivation of emission distributions taking into account atmospheric transport and its uncertainties. Here, we report on our progress in addressing these challenges, showcasing the current UNICORN configuration and discussing lessons learned across the employed measurement and modelling techniques.
How to cite: Butz, A., von Buenau, K., Dermendzhiev, M., Herrenknecht, T., Kleinschek, R., Knapp, M., Leyer, S., Löw, B., Lüken-Winkels, C., Maiwald, R., Sindram, M., Schmitt, T., Voss, T., and Vardag, S. N.: UNICORN – UnIversity Network for CO2 in the Rhine–Neckar metropolitan area: implementation and first insights, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10583, https://doi.org/10.5194/egusphere-egu26-10583, 2026.
To quantitatively assess the impact of climate mitigation actions and support sustainable urban planning, the eddy covariance (EC) method serves as a potentially powerful tool for independent monitoring, reporting, and verification. However, interpreting EC fluxes in urban environments is challenging due to the spatial-temporal heterogeneity of urban surfaces and human activities, coupled with the complex coexistence of anthropogenic and biogenic fluxes. Furthermore, the EC footprint varies significantly with meteorological conditions, which can lead to biased flux estimates if the spatial representativeness is not properly accounted for.
This study presents a framework to resolve the monthly spatial distribution of CO2 sources and sinks at 10-meters resolution by integrating tall tower EC measurements (at heights up to 112 m) with bottom-up modelling and satellite imagery. The study site is a suburban area in Gladsaxe Municipality, northwest of Copenhagen, Denmark. A 12-months dataset collected throughout 2025 was analysed. Five major activities were considered: transportation, residential heating, human respiration, industrial emissions, and vegetation exchange. By coupling a footprint model with land-use and activity data, we performed a source apportionment to optimize spatially unbiased emission estimates.
Preliminary results indicate that transportation is a major contributor to the net CO2 emission at this suburban site, while residential heating shows an apparent elevation during the winter months. Notably, the CO2 exchange from vegetated areas displays an identifiable seasonal pattern, shifting between a potential weak source in winter and an appreciable sink during the peak growing season. These findings highlight the utility of tall tower EC in partitioning sectoral emissions, providing critical observation-based constraints for local CO2 inventories and urban climate action plans.
We acknowledge the financial support from the Independent Research Fund Denmark (DFF, Grant No. 1127-00308B) and the sponsorship provided by CIBICOM A/S (Ballerup, Denmark).
How to cite: Wang, Z., Sachsenmaier, P., Wiesner, S., Kissas, K., Scheutz, C., and Ibrom, A.: Temporal Variability and Spatial Distribution of CO2 Fluxes in a Danish Suburban Environment: Insights from Tall Tower Eddy Covariance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11815, https://doi.org/10.5194/egusphere-egu26-11815, 2026.
This study presents a comprehensive 2022 dataset of continuous in-situ measurements of δCO2 and CH4, δ¹³CO2 and δ¹³CH4 in Houston, Texas, USA complemented by targeted canister sampling to characterize key anthropogenic and biogenic emission sources. It also integrates ground-based in-situ measurements with satellite observations to characterize CO₂ and CH₄ emission hotspots in Houston, Texas.
Seasonal background variability reflects distinct biogeochemical processes: CO₂ declines from ~435 ppm in winter to ~410 ppm in summer due to photosynthetic uptake, while CH₄ decreases from ~2.02 to ~1.88 ppm primarily through OH oxidation. Regional contrasts are evident, with lower marine-influenced backgrounds (~410 ppm CO₂, ~1.85 ppm CH₄) compared to continental sectors (>435 ppm CO₂, >2.05 ppm CH₄).
Boundary-layer-height (BLH)-corrected enhancements reveal strong seasonal patterns in anthropogenic emissions. ΔCO₂ peaks in winter-fall (up to ~138 ppm hourly; ~20.6 ppm monthly) and drops to ~8.96 ppm in summer, while ΔCH₄ shows maxima in winter-spring (~5.45 ppm hourly; ~0.10 ppm monthly) and a summer minimum (~0.08 ppm). The 2022 mean ΔCH₄/ ΔCO₂ ratio (8.8 ppb/ppm) is ~14% higher than Philadelphia's in-situ winter value and ~35-40% above EDGAR v8.1 and EPA inventories, but broadly consistent with recent satellite-based estimates across U.S. cities.
Bivariate ΔCH₄/ ΔCO₂ mapping identifies major hotspots at McCarty, Blue Ridge, and Coastal Plains landfills (>40-60 ppb/ppm), which are underestimated or absent in inventories. Sharp enhancements at the Ship Channel and McCarty landfill align with satellite NO₂ and HCHO peaks, confirming these as multi-source hotspots. The BLH-corrected in-situ approach captures rapid emission events and diurnal variability, providing finer-scale source attribution and plume detection within the satellite sub-pixel domain that are missed by single overpasses.
Temporal analysis revealed distinct seasonal variability: δ¹³CO2 was most depleted in winter, reflecting enhanced combustion-related CO2, whereas δ¹³ CO2 showed the most negative values in summer and fall, consistent with intensified microbial methanogenesis under warm, humid conditions. Background δ¹³CO2 ranged from –11.8‰ to –13.2‰ depending on air mass origin, while δ¹³CH4 varied between –47.2‰ and –50.7‰, reflecting marine–continental transitions. Spatially, bivariate plots and isotopic mapping identified strong CH₄ enhancements (>0.5 ppm) and highly depleted δ¹³ CH4 (−50.5‰ to −51‰) over the McCarty landfill, indicating dominant microbial methane generation, further confirmed by canister measurements δ¹³CH4 ≈ −60.3‰. Estimated emissions from the McCarty Landfill, based on our isotopic mass-balance analysis, were ~2,100 kg CH₄ h⁻¹ ±55%, exceeding the EPA GHGRP inventory value (~857 kg CH₄ h⁻¹) and moderately higher than the Carbon Mapper satellite-derived flux but within combined uncertainties (~1,427 kg CH₄ h⁻¹ ±91%). highlighting that bottom-up inventories underestimate methane emissions from large urban landfills such as McCarty. Overall, the isotopic evidence demonstrates that integrating δ¹³C analyses data provides critical insights into source attribution and the relative roles of combustion, industrial, and microbial processes shaping Houston’s CO2 and CH4 emission landscape.
How to cite: Rappenglück, B. and Karim, I.: Characterizing Anthropogenic and Biogenic Sources of CO2 and CH4 in Houston, Texas, USA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11301, https://doi.org/10.5194/egusphere-egu26-11301, 2026.
Urban areas dominate anthropogenic CO2 emissions and play a key role in climate change mitigation. Efficient emissions reduction requires improved knowledge of the attribution of carbon emissions. Measuring the 14C (radiocarbon) content of atmospheric CO2 is the most direct method to distinguish fossil CO2 emissions (ffCO2) from biogenic and natural fluxes, due to their lack of 14CO2 content. Hence, CO2 produced from the combustion of fossil fuels causes a measurable decrease in the atmospheric 14CO2/CO2 isotope ratio. Results from flask sampling campaigns indicate the potential of high time resolution 14C measurements to attribute flux estimates using urban-scale inversions.
We present a novel analytical platform for autonomous and semi-continuous analysis of Δ14C-CO2 in atmospheric air samples with sub-hourly time resolution. The core of the analytics is based on a saturated-absorption cavity ring-down (C14-SCAR) spectrometer (ppqSense). This is coupled to a custom-developed compact quantum cascade laser absorption spectrometer (C13-QCLAS) to provide CO2 purity and δ13CO2. The C14-SCAR and C13-QCLAS share an automated pre-concentration device (NC Technologies), to purify CO2 from air applying a temperature-swing zeolite adsorbent trap and remove N2O interferences. We showcase performance characteristics of the coupled C14-SCAR / C13-QCLAS system for sensitive, i.e. ppm-level detection of fossil CO2 contributions in urban environments, and present first time series data for a monitoring site in the vicinity of Zürich (Dübendorf). Results will be discussed in conjunction with city-wide observations of CO2 and high-resolution simulations of ffCO2 variability.
This work is supported by the SNSF project RADIANCE (206021_220392) and part of the projects 24GRD03 MetHIR and 24GRD06 MetCTG.
How to cite: Mohn, J., Siegwolf, P., Whitehill, A. R., Henne, S., Hammer, S., Wacker, L., Emmenegger, L., and Tuzson, B.: High-temporal resolution measurements of radiocarbon in atmospheric CO2 for source sector attribution of urban emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1881, https://doi.org/10.5194/egusphere-egu26-1881, 2026.
Cities are major sources of anthropogenic carbon dioxide (CO2) emissions. Reducing these emissions is not enough to make urban areas carbon neutral without biogenic sinks offsetting a portion of the remaining emissions. Urban vegetation provides a CO2 sink that contributes to the net CO2 balance of a city. CO2 uptake of a neighborhood is strongly dependent on the number of trees, i.e. the canopy coverage. The current EU Nature Restoration Law recommends that each city should have a canopy coverage of 30% to get the multiple benefits of urban vegetation. However, this limit value is rarely reached at a neighborhood level, where most of the benefits take place.
In this study, we utilized urban land surface model SUEWS (the Surface Urban Energy and Water balance Scheme) in greater Paris area, France, to examine the variability of biogenic CO2 fluxes across the city with different canopy coverages. SUEWS simulates joint energy, water, and CO2 exchanges on local neighborhood scale with meteorological forcing and vegetation-specific parameterizations. The study period was from March 2024 to June 2025, corresponding to the availability of eddy covariance (EC) measurements from an urban forest Vincennes located in eastern Paris, which were used to evaluate the model. The meteorological input was from ERA5 data. First, we tested the effect of choosing different sets of biogenic CO2 parameters (Park trees, street trees, forest) for modelling CO2 and heat fluxes. We then upscaled the results by modelling CO2 in the greater Paris area with a 500 m x 500 m resolution. Results of CO2 uptake were also compared to canopy coverage of the grids to see the effect of urban vegetation offsetting the CO2 emissions on a neighborhood scale.
How to cite: Karvonen, A., Havu, M., Bignotti, L., Loubet, B., and Järvi, L.: Linking neighborhood canopy coverage to city-scale biogenic CO2 uptake in Paris, France , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16968, https://doi.org/10.5194/egusphere-egu26-16968, 2026.
Methane (CH4), a potent greenhouse gas, is emitted in large quantities from urban sources including landfills, wastewater treatment facilities, and natural gas distribution networks, and can make up a significant fraction of a city's total carbon budget. Reducing urban CH4 emissions is therefore an important part of anthropogenic climate change mitigation strategies. Toronto, Canada's largest city, has set significant carbon emission reduction goals, aiming to reach net-zero carbon emissions by 2040. The TAME (Toronto Atmospheric Monitoring of Emissions) Project has been established to help track the city's progress towards these goals using both observation networks and atmospheric modelling techniques. As part of TAME, we perform high-resolution (1km) simulations of atmospheric CH4 across the Greater Toronto Area (GTA) using the WRF-GEOS-Chem (WRF-GC) model coupled with two versions of the high-resolution (1km) FLAME-GTA urban methane emission inventory. We use the model to quantify the variability of CH4 across the city in terms of a correlation length scale. We also calculate spatial correlation footprints for multiple observation sites and use these footprints to assess the spatial coverage of different urban observation network configurations. We then compare the modelled CH4 with in-situ surface measurements and remote sensing retrievals at two urban sites and one rural background site. These comparisons show that urban landfill CH4 emissions were likely overestimated in the original FLAME-GTA inventory but have been significantly improved in the updated version. Measured versus modelled spatial gradients of CH4 suggest a possible overestimate of CH4 emissions in Downtown Toronto in both versions of FLAME-GTA. Low biases associated with specific wind directions may indicate regions of underestimated CH4 emissions in the model. These results demonstrate how high-resolution modelling can be combined with observations to assess and improve emission inventories in urban environments. Future work for the TAME project will extend this analysis to include other pollutants including CO2, CO, PM2.5, NOx, and O3.
How to cite: DiMaria, C., Demirci, C., Gillespie, L., Ars, S., Jacobs, N., Prates, L., Jones, D., and Wunch, D.: High-resolution modelling of atmospheric methane in the Greater Toronto Area using WRF-GEOS-Chem, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15301, https://doi.org/10.5194/egusphere-egu26-15301, 2026.
With the ever-increasing realisation that measures against climate change have to be local, many cities opted to become NetZero (i.e., CO2-Neutral, emissions compensated) in the near future. Especially within the EU, a large-scale project takes place driven in close collaboration between the EU and cities. The “EU Cities Mission” facilitates urban transition via supporting actions and strategies towards neutrality by offering official labelling to cities that create successful climate city contracts and commit to achieve CO2-Neutrality by 2030. The Horizon project CLMS-Cities targets to support cities with quantifying and trenching their CO2 emissions based on existing and freely available Copernicus Services, in particular within CLMS (Copernicus Land Monitoring Service Cities) and in-situ data such as GNSS based mobility data. Within CLMS-Cities a CO2 exchange model for local-scale scope 1 CO2 emissions is developed at 10m resolution at hourly scale for the five sectors: mobility, buildings, industrial sources, AFOLU (Agriculture, Forestry and other land uses), and human respiration following closely typical city inventories.
We here present first results and the background of the model for the case study city Vitoria-Gasteiz, Spain (Tier 1 city). The model is mainly based on the Urban Atlas and produces estimates of CO2 exchange by integrating relevant Copernicus services, satellite products and third-party mobility data. To ensure robustness, the model is paired with local-scale eddy covariance observations in the city centre of Vitoria-Gasteiz. Following this validation process, the model will be extended and rolled out to ten additional EU Mission cities to ensure that it accommodates a wide range of spatial, urban and environmental contexts, that is seen across the real cities in the EU. A co-design approach underpins this work, with continuous engagement with cities to ensure that their requirements are fully integrated in the design, development and operationalisation of the model.
How to cite: Spirig, R., Stagakis, S., Politakos, K., García-Moncó Piñeiro, B., Mitraka, Z., Panagiotakis, E., Karampour, K., Covato, E., Cranshaw, O., Benedito Bordonau, M., Gandini, A., Benito Moreno, M., Simon Moral, A., Monaco, C., Feliciotti, A., Kazemihatami, F., Monteiro, A., Khan, Z., Chrysoulakis, N., and Marconcini, M.: CLMS-Cities: Towards monitoring CO2 emissions on the neighbourhood scale in European cities based on Copernicus data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21412, https://doi.org/10.5194/egusphere-egu26-21412, 2026.
Orals: Tue, 5 May, 08:30–12:25 | Room M1
Urban air quality (AQ) is impacted by different emission sources (traffic, household heating, industry, energy production,...) and inhabitants are exposed to different pollutants that have impact on their health. Some pollutants, e.g. traffic-related ones (like UFP, BC & NOx), can show a very high spatial and temporal variability within a city or neighbourhood.
There is a need to better understand the spatio-temporal heterogeneity of AQ and at the same time understand levels of pollutants of emerging concern; this information is crucial for improved assessment of health effects and data-driven policy.
The new AQD (2024/2881) sets stricter requirements for regulated pollutants and requires the monitoring of emerging pollutants at so-called supersites (in urban areas). The purpose is to collect data on pollutants of emerging concern to improve understanding of health and environmental impacts. On the other hand, new (low-cost) monitoring devices can complement regulatory Air Quality Monitoring Stations (AQMS) and can collect data at multiple locations in urban areas (via stationary networks or mobile deployment). Whereas new monitoring approaches can result in insights on spatial variability across the city, there are still some issues related data quality of low-cost sensors or representativity of mobile mapping.
The recently finished RI-URBANS project (https://riurbans.eu/), provides data on emerging pollutants in different cities in Europe and introduced new methods e.g. to collect fine-grained pollution maps. Within the on-going Net4Cities project (https://www.net4cities.eu/), datasets of emerging pollutants at multiple locations in 11 cities (including UFP, LDSA, ammonia, VOCs) will become available.
In this presentation, challenges related to urban air quality monitoring in (European) cities will be discussed. New monitoring approaches to better understand urban AQ and levels of emerging pollutants will be discussed. Some examples will be given on how innovative monitoring can contribute to improved policy and cleaner cities.
How to cite: Van Poppel, M.: Urban Air Quality: Challenges and future directions , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12681, https://doi.org/10.5194/egusphere-egu26-12681, 2026.
This study employs a high-resolution modeling framework to quantify traffic-derived contributions to air pollution exposure in Augsburg, Germany, integrating a multi-scale model chain with agent-based population dynamics for exposure assessment. The microscale PALM4U model is driven by a customized WRF4PALM tool for a dynamic driver (meteorology, chemistry and aerosol) and utilizes a customized SALSA+SIMPLE mechanism with a source-tagging scheme. This enhancement explicitly isolates pollutants from road traffic, enabling direct attribution of NO₂, ultrafine particles (UFP), and trace metals within PM₂.₅ to vehicular emissions.
A novel aspect of the workflow is the integration of an agent-based model (ABM), which is informed by population mobility and activity data from the KORA (Kooperative Gesundheitsforschung in der Region Augsburg) cohort in Augsburg. The ABM simulates detailed spatiotemporal trajectories of individuals, providing dynamic urban emissions and enabling the reconstruction of personalized exposure profiles. The coupled PALM-ABM system overlays high-resolution, time-resolved exposure metrics such as inhaled dose and peak concentrations for traffic-attributable pollutants.
The model’s accuracy is rigorously evaluated through a multi-scale validation approach. First, simulated city-wide concentration fields are compared with the measurements from regulatory air quality stations in Augsburg and detailed pollutant speciation data from the Joint Environmental Exposure Center (JEEC) measurement station. Second, spatial patterns are assessed against satellite observations (e.g., TROPOMI NO₂ vertical columns) to ensure consistency at the urban-to-regional scale.
This integrated framework provides unprecedented, source-resolved insights into the contribution of traffic to personal air pollution exposure in a real urban environment. It quantifies the dominant influence of traffic on NO₂ and UFP concentrations at the street scale, while also explaining the trace metals in PM₂.₅. The robust multi-source validation spanning ground stations, specialized monitoring, and satellite data ensures the reliability of both the meteorological-chemistry model and the exposure reconstruction. This methodology establishes the health-oriented urban air quality management and for evaluating the effectiveness of traffic-related emission reduction strategies.
How to cite: Vaithiyanadhan, S. K. and Knote, C.: Urban scale modelling of NO2, ultrafine particles, metal components in particulate matter in Augsburg, Germany, for health applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21928, https://doi.org/10.5194/egusphere-egu26-21928, 2026.
The reduction of nitrogen oxides (NOx = NO + NO2) emissions is crucial for air pollution control. Since 2011, China has experienced its most intensive and effective period of reducing NOx emissions. Many previous studies have focused on emission trends, but they often lag by several years due to the lack of reliable and timely data. Leveraging the advantages of satellite-based NO2 observations, this study uses tropospheric NO2 vertical column densities (NO2 TVCD) at 0.05° × 0.05° horizontal resolution from POMINO-TROPOMI products and employs a top-down emission inversion method (PHLET). The PHLET is a two-dimensional model that describes the quantitative relationship between NOx emissions and NO2 TVCD over a period, influenced by horizontal transport and nonlinear chemical processes. Then we estimate annual anthropogenic NOx emissions at 0.05° × 0.05° for China from 2018 to 2025. First, it reveals that national anthropogenic NOx emissions exhibit a declining trend, with the rate of decline slowing after 2020. Specifically, this trend is reflected at the provincial level, with 12 out of 31 provincial-level administrative regions showing similar declining trends and meeting their reduction targets in 2025. Second, most cities meeting reduction targets are distributed in North China and East China, while South China, Southwest China, and Northwest China still hold significant reduction potential. Third, the derived NOx emissions show great consistency with ground-based surface NO2 concentration measurements in most cities. In a few cities, discrepancies between emissions and observed concentrations stem from insufficient spatial representativeness of monitoring stations. Moreover, we further validated this conclusion through an atmospheric chemistry transport model (GEOS-Chem) simulation against ground-based measurements.
How to cite: Wang, S., Lin, J., Kong, H., and Zhang, Y.: Mapping the Heterogeneity of NOx Emission Reductions across Chinese cities from 2018 to 2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3731, https://doi.org/10.5194/egusphere-egu26-3731, 2026.
Evaluating urban mobility scenarios typically relies on single-metric assessments—CO2 reductions, modal shares, or air quality indices—that fail to capture trade-offs between environmental effectiveness, social equity, and policy feasibility. A scenario delivering maximum emission cuts may exacerbate inequalities; one prioritising accessibility may underperform on climate targets. Decision-makers need multi-dimensional frameworks that make these trade-offs explicit and comparable across contexts.
We present the Key Performance Indicator (KPI) framework developed within IMTECC (Integrated Multimodal Traffic Emissions Climate and Cities), a Sino-European collaboration funded by ANR, Innovation Fund Denmark, and NSFC, involving LISA-CNRS, University of Copenhagen, Aarhus University, Zhejiang University, and the Municipality of Copenhagen. The framework structures scenario evaluation across six pillars and fourteen sub-dimensions:
• Climate & Pollution: emission reductions, net-zero pathway alignment, public health impacts
• Society & Lifestyles: behavioural shifts, inequality trends
• Mobility & Transport: pricing and incentives, multimodality, infrastructure upgrades
• Technology & Innovation: low-emission vehicle penetration, ITS optimisation
• Governance & Policy: master plan integration, low-emission zone implementation
• Territorial: urban typology coherence, innovation cluster development
This structure enables systematic cross-city comparison between Paris (OLYMPUS-CHIMERE platform), Copenhagen (COMPASS transport model), and Hangzhou, despite differences in modelling approaches and local policy contexts.
For the Paris metropolitan area, four scenarios at the 2035 horizon are evaluated against this KPI matrix:
• Scenario A (Reference): Baseline trajectory.
• Scenario B (Densification): 220,000 inhabitants and 140,000 jobs relocated within 800m of Grand Paris Express stations.
• Scenario C (LEZ + Electrification): 50% electric vehicle target with reinforced emission standards.
• Scenario E1 (Progressive LEZ + Equity): Gradual implementation with social support for vulnerable households.
The KPI matrix reveals differentiated scenario profiles. Scenario C scores highest on climate & pollution indicators (emission reductions, net-zero alignment) but neutral on inequality trends. Scenario B shows balanced performance across territorial coherence, multimodality, and master plan integration. Scenario E1 achieves the strongest score on inequality trends while maintaining moderate climate performance—demonstrating that equity need not be sacrificed for environmental ambition.
Cross-pillar analysis exposes synergies and tensions: scenarios combining electrification with densification (B+C hybrid) could maximise both climate and territorial scores, while pure technology-push approaches (C alone) leave behavioural and equity dimensions unaddressed. A composite sustainability index weighting GHG emissions, travel times, population exposure, exposure inequalities, and non-fossil energy share is proposed to support multi-criteria decision-making. This KPI-based approach, aligned with the Integrated Urban System framework promoted by the World Meteorological Organization, offers a replicable methodology for evidence-based urban climate governance.
How to cite: Elessa Etuman, A., Coll, I., Benoussaid, T., and Costes, M.: A multi-dimensional KPI framework for evaluating urban mobility scenarios: Integrating air quality, climate, and equity metrics across three metropolitan areas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23261, https://doi.org/10.5194/egusphere-egu26-23261, 2026.
Understanding the vertical structure of aerosols near the surface is crucial for enhancing exposure assessment, validating air quality models, and characterizing boundary layer processes at fine spatial scales, as pollutant level varies significantly due to complex interactions between emissions and local atmospheric conditions. However, most monitoring networks depend on surface stations that cannot detect altitude-related changes within the lowest tens of meters. This range is significant to human exposure and pollutant transformations. This study presents early results from a UAV-based vertical profiling system designed for high-resolution measurements of PM₂.₅ and key meteorological parameters. A multirotor drone equipped with a custom sensor module, including a NOVA-SD laser-scattering PM₂.₅ sensor, a Bosch BME280 sensor for measuring barometric pressure, temperature, and relative humidity, and an STM32 Microcontroller for onboard data logging, was used for two vertical profiling flights. The UAV ascended up to 35 m above ground level, collecting resolution measurements for all mentioned variables at each second. Over both flights, more than 1,500 data points were gathered. The profiles show expected thermodynamic behavior, that is, temperature and pressure decrease with altitude, while relative humidity increases in the upper part of the measured layer. PM₂.₅ levels were generally low but showed noticeable altitude-related variations. A mid-altitude increase appeared consistently in both flights, indicating a shallow aerosol layer rather than sensor noise. These initial findings highlight the potential of UAV-based sensing to detect fine-scale stratification that surface monitors miss. The expanded dataset will help create a validated UAV-based approach that complements traditional monitoring networks and provides better insight into urban boundary-layer air quality.
How to cite: Nawaz, U., Nagendra, S. M. S., and Muniraj, D.: Investigating Pollutant-Meteorology Interactions In Urban Surface Layer Through UAV-Based Vertical Profiling , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14827, https://doi.org/10.5194/egusphere-egu26-14827, 2026.
Air quality concerns persist in urban areas due to the density of pollutant releases and population. This leads to complexities in understanding air pollution impacts given the high spatiotemporal variability of ambient pollutant levels. Those complexities are exacerbated by the lack of integration among the research and management activities associated with the air quality issues of smog, acid deposition, trace contaminants, and air toxics. The Study of Winter Air Pollution in Toronto (SWAPIT) involves over 100 scientific and technical collaborators from government and academia working to characterize the composition and spatiotemporal variability of the whole urban air pollution mixture and to better understand urban air pollution sources and impacts. A six-week field campaign was carried out from January to March 2024 using a variety of measurement techniques at multiple locations in the Toronto area. Campaign timing allowed for a focus on the relatively understudied winter period when low temperature and light alter secondary pollutant formation, and seasonal pollutant sources such as roadway de-icing and residential wood combustion are active. Results will be presented to demonstrate the differences in spatial patterns between pollutants, the ongoing impacts of urban transportation sources, and the growing role of non-exhaust pollutants. Insights into human and wildlife health will also be presented along with improvements to satellite and chemical transport modelling tools that have been driven by measurements taken during the SWAPIT field campaign.
How to cite: Galarneau, E. and the Study of Winter Air Pollution in Toronto: The urban multi-pollutant mixture measured in the Study of Winter Air Pollution in Toronto (SWAPIT), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14614, https://doi.org/10.5194/egusphere-egu26-14614, 2026.
In 2021, the city of Toronto adopted a plan to reach net-zero emissions by 2040 that includes ambitious strategies to be implemented over the coming years. The purpose of the Toronto Atmospheric Monitoring of Emissions (TAME) project is to produce measurements of greenhouse gases and air pollutants in the urban area in order to quantify emissions during this period and study air quality co-benefits of emissions reduction strategies. Instrumentation operated as part of TAME includes ground-based column measurements and in situ measurements. Many of the in situ measurements are made with mid-cost sensor packages. One is the QuantAQ Modulair, which measures CO, NOX, O3, and particulate matter, and the other is a CO2 sensor built by Environment and Climate Change Canada. Since August 2024, these sensors have been evaluated against reference instrumentation and deployed at eight sites around the Greater Toronto Area. The pollutant concentrations are calculated using regression models based on colocation with reference instrumentation; we also employ one pair of sensors as a travel standard to assess changes in the sensors’ performance while they are deployed at their respective sites and revise the regression models as needed. We also maintain a set of QuantAQ sensors permanently colocated with our reference instruments throughout the deployment period. The advantages and disadvantages of these calibration approaches will be discussed and compared to other methodologies. A summary of pollutant trends among the sites will be presented with emphasis on what can be confidently quantified given both the spatial gradients and the performance limitations of these sensors.
How to cite: Panas, M., Ward, E., Corapi, A., Lao, I. R., Ars, S., Murphy, J. G., Vogel, F., Wunch, D., and Young, C. J.: Opportunities, Constraints, and Progress of a Mid-Cost Sensor Network for In Situ Greenhouse Gas and Air Quality Monitoring in the Greater Toronto Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15654, https://doi.org/10.5194/egusphere-egu26-15654, 2026.
Spatio-temporal variation analysis of PM2.5 in Lahore using Beta Attenuation Monitor and Low-cost sensors
Shahbaz A. 1, Nizami A.S1, Dillner A. M.2, Anwar M. N.1,2*
1Sustainable Development Study Center, Government College University, Lahore, Pakistan
2Air Quality Research Center, University of California, Davis, Davis, CA 95618, USA
*Corresponding author. Tel: 92-333-4881593;
E-mail address: naveedanwarenv@gcu.edu.pk
Air pollution (especially fine particulate matter PM2.5) is a major global issue causing 7 million premature deaths each year. It also reduces the atmospheric visibility and interacts with overall ecosystem. The Low and Middle-Income Countries (LMICs), home to 6.62 billion people, are at forefront to air pollution exposure. Despite grave impact (89% of the premature deaths), LMICs lack sufficient air quality monitoring. Pakistan, like other LMICs, is faced with severe air pollution as well. Lahore, one if its metropolitans, was among top 10 most polluted cities globally in 2022. In this study temporal and spatial variability of PM2.5 concentration in Lahore was investigated by using reference grade Beta Attenuation Monitor (BAM) and low-cost sensors based data from 2019 to 2025. Over the study period, daily PM2.5 concentration was measured by BAM ranged from 0.1 µgm⁻³ to 910.1 µgm⁻³, with an overall mean concentration of 125.5 µg m⁻³. A strong seasonal trend was observed with winter frequently exceeding 300µgm⁻³ (far surpassing WHO and EPA guidelines of 15 µgm⁻³ and 35 µgm⁻³ respectively), even higher than 600µgm⁻³ occasionally. Data from a city-wide network of low-cost sensors was used to examine the spatial variation of the PM2.5. Furthermore, this PM2.5 mass concentration data was validated against the reference grade BAM data and tailored calibrations, catering the potential bias of different factors, were developed. These calibrations can be readily applied in the future on the low cost sensors data to reduce the need for the deployment of expensive reference grade monitors paving the way for routine and dispersed monitoring – much needed towards the prevention of recurrence of smog episodes in Lahore. In addition, the role of the transboundary agricultural residue burning towards the higher PM2.5 mass concentrations was also investigated by using the satellite imageries and meteorological data. These findings underscore the urgent need to improve data integration approaches, strengthened air quality networks, and policy interventions that are evidence based to mitigate the increasing air pollution in urbanizing regions of LMICs.
How to cite: Shahbaz, A., Nizami, A.-S., Dillner, A. M., and Anwar, M. N.: Spatio-temporal variation analysis of PM2.5 in Lahore using Beta Attenuation Monitor and Low-cost sensors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17139, https://doi.org/10.5194/egusphere-egu26-17139, 2026.
Mobile measurements have emerged as a powerful tool for characterising air pollutant sources, providing high-resolution spatial and temporal information that complements fixed monitoring stations. In this study, we used mobile measurements to investigate air pollution across York, England. High time resolution measurements were made of nitrogen oxides (NOx), carbon dioxide (CO2), methane (CH4), fine particulate matter (PM2.5) and over 20 individual volatile organic compounds (VOCs). The measurements were made on a pre-defined route and repeated 19 times across different times of the day, days of the week, and seasons. The measurement route covered the densely populated city centre, characterised by heavy traffic and numerous commercial activities, such as restaurants and beauty salons, and extended to the outskirts dominated by agricultural land and green spaces. This spatial coverage allows the investigation of contrasting local emission sources, including poorly quantified source types such as restaurants and traffic-related emissions, as well as background pollutant concentrations affected by regional source contributions. Our study explores how best to partition the measurements into background and local increments to investigate the nature of the sources affecting measurements across the city. We also explore the potential of using information on individual source locations for sectors such as restaurants as a method to examine the relationship between source density and pollutant concentration. We derive the source factor through advanced Gaussian modelling of individual sources based on their location and local meteorology. The results demonstrate the applicability of mobile measurements combined with the source factor method for resolving fine-scale variability in urban air pollution.
How to cite: Tidmarsh, E., Budisulistiorini, S. H., Lee, J., Shaw, M., and Carslaw, D.: A Source Focused Approach Applied to Urban Mobile Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20168, https://doi.org/10.5194/egusphere-egu26-20168, 2026.
Indoor air quality (IAQ) has become a critical focus of research due to the substantial amount of time people spend indoors, where a significant proportion of air pollution exposure occurs. However, understanding how time and activity dependent sources, as well as built environment characteristics, influence pollutant emissions and distributions remains very limited.
This presentation will provide an overview of recent developments on indoor air quality modelling outlining the latest capabilities of the tools initially developed in the MetOffice/Strategic Priorities Fund (SPF) project "Indoor Air Quality Emissions & Modelling System (IAQ-EMS)". Specific focus will be the opportunities and challenges associated with contrasting modelling approaches such as ChemFlow3D (Liu et al., 2025; doi.org/10.1063/5.0270416) with high spatial and temporal resolution and multi-box flexible (MBM-Flex) modelling which allows the incorporation of a wide range of chemical schemes and tracking concentration gradients across complex buildings and at the indoor-outdoor interface while assuming well-mixed conditions in each box. Development opportunities and use cases will also be discussed.
We have also developed, InAPI — an Excel-based Indoor Air Pollution Inventory tool — using data synthesised from reviewing UK indoor air pollution research (Mazzeo et al., 2025; doi.org/10.5194/egusphere-2025-783). For the development of the InAPI tool, we have categorised existing literature by pollutant types, indoor environments, and activities, identifying significant knowledge gaps and offering an open-access database of typical pollutant concentrations and emission rates (Mazzeo et al., 2025; doi.org/10.1039/D4EA00121D). Despite the fragmented methodologies in historical IAQ research and the underrepresentation of key sources, pollutants, and environment-specific characteristics (in particular ventilation and occupant behaviour), InAPI consolidates this evidence into a practical and easy-to-use tool.
By providing a robust platform for understanding indoor air pollutant dynamics, our work aims to advance IAQ research in the UK and beyond given the transferability of the approach, and thus support efforts to mitigate indoor air pollution and inform policy initiatives nationally and globally.
How to cite: Pfrang, C.: Indoor Air Quality Modelling: Challenges and Opportunities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12587, https://doi.org/10.5194/egusphere-egu26-12587, 2026.
Formaldehyde remains one of the most critical indoor air pollutants due to its ubiquity, reactivity, and harmful health effects (Salthammer et al., 2010). In recent years, microplastics (MPs) have also been reported as a critical indoor air pollutant (Zhang et al., 2020). Although sorption processes of formaldehyde on indoor surfaces have a significant impact on their persistence and spatial distribution, quantitative data on material-specific adsorption behavior are currently scarce, especially for emerging pollutants like MPs. This study provides a systematic experimental investigation of formaldehyde sorption onto the surface of fresh and O3-aged MPs, such as Low-density polyethylene (LDPE), polyvinyl chloride (PVC), Polyether ether ketone (PEEK) (PlasticsEurope, 2018; Stober et al.,1984), and also common indoor materials: cement, gypsum, conventional paint, and depolluting paint. Uptake measurements were performed in a flow reactor coupled with selective ion flow tube mass spectrometry (SIFT-MS) to enable real-time monitoring of formaldehyde. Experiments were performed at room temperature across a wide range of formaldehyde concentrations (100–550 ppb), under both dry air and 50% relative humidity. The objective was to determine formaldehyde partition coefficients, Ke, on the surfaces of interest.
The partitioning coefficient (Ke) of formaldehyde to MPs was found to be very low, at least two orders of magnitude lower than that of common indoor materials. Ozone aging and relative humidity influenced formaldehyde uptake, with the extent of this effect varying depending on the type of MP studied. However, in all cases, Ke values for MPs remained significantly below those measured for typical indoor surfaces. Under humid conditions (50% RH), depolluting paint exhibited the highest partitioning capacity, followed by conventional paints, gypsum, and cement. These findings suggest that, despite their growing presence in indoor environments, MPs are unlikely to have a significant contribution in formaldehyde loss compared to conventional building materials.
To evaluate the impact of the experimentally derived Ke-values on indoor air quality and identify dominant loss processes, we implemented them in a modified 1D-box model (Fiorentino et al., 2021) representing a typical room, based on the IRINA (Harb et al., 2016) experimental facility. Simulations considered a pollution episode and included ventilation, gas-phase reactions with atmospheric oxidants, and heterogeneous uptake on room surfaces. Results show that heterogeneous loss dominates formaldehyde removal indoors, with rates over an order of magnitude higher than gas-phase processes. Depolluting paint under 50% RH led to the fastest concentration decline. These results highlight the key role of surface interactions in indoor air quality and the importance of material choice in controlling pollutant levels. The combined experimental–modelling approach facilitates improved predictions of pollutant behavior in indoor environments and promotes the development of more potent passive depollution strategies.
References:
Salthammer, T. et al (2010) Chem. Rev. 110, 2536–2572.
Zhang, Y. et al (2020) Earth-Sci. Rev. 203, 103118.
PlasticsEurope (2018) Plastics – the Facts 2018.
Stober, E. J. et al (1984) Polymer 25, 1845–1852.
Fiorentino, E. A. et al (2021) Geosci. Model Dev. 14, 2747-2780.
Harb, P. et al (2016) Chem. Eng. J. 306, 568-578.
How to cite: Nayak, S., Gandolfo, A., Thevenet, F., Romanias, M. N., and Tinel, L.: Sorption Dynamics of Formaldehyde on Microplastics and Indoor Materials: Experiments and 1D‑Box Modelling Insights, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19136, https://doi.org/10.5194/egusphere-egu26-19136, 2026.
Chemical species emitted in indoor environments by humans (skin emission and breath) and their activities (cooking, use of detergents and personal care products), or by building and furnishing materials, have a direct impact on air quality. In addition, these species exhibit an indirect impact through their gas phase reactions with atmospheric oxidants (e.g. hydroxyl radicals), leading to the formation of Oxygenated Volatile Organic Compounds (OVOCs) and Secondary Organic Aerosol (SOA), which can directly affect human health. They can also be transferred outside (through infiltration or ventilation), where they can further react to produce ozone and SOA, potentially having an additional impact on health and climate change. The COST action INDAIRPOLLNET aimed to identify and rank species emitted indoors, according to different criteria such as their health impact, or their reactivity with atmospheric oxidants (OH, O3, Cl and NO3). This work highlighted an important knowledge gap, as more than 800 compounds have been measured indoors, but only a limited number have relevant information to enable ranking. For instance, less than 65% of the molecules have a reported rate constant with OH. In this context, a FAGE (Fluorescence Assay by Gas Expansion) instrument, measuring the total OH reactivity (sum of OH loss rates due to reactions with trace gases), has been used to measure missing rate constants with OH, and to investigate oxidation mechanisms of species of interest that may impact human health, or react quickly with OH. The oxidation of furan, N,N-dimethylformamide and 1.2-diethoxyethane has been studied via two complementary approaches: laboratory experiments and modelling (using INCHEM-Py box model). The experiments were conducted in the DouAir simulation chamber, coupled with a Proton Transfer Reaction-Mass Spectrometer, -monitoring the primary VOCs and their oxidation products -, and with the FAGE instrument. In a second step, these experiments were simulated with INCHEM-Py. Experimental findings confirm the formation of butenedial, 5-hydroxyfuran-2(5H)-one, 4-oxobut-2-enoic acid, 2-hydroxy-5-carboxyfuran and maleic anhydride as the main oxidation products for the furan + OH reaction, and the formation of dimethylnitramine when N,N-dimethylformamide is oxidized by OH radicals. Oxidation products for the reaction of 1.2-diethoxyethane + OH are presented for the first time. In addition, the kinetic of this last reaction was studied using the FAGE technique, yielding a measured rate coefficient of (5.3 ± 0.4) × 10-11 cm3.mol-1.s-1, in good agreement with the value of (5.8 ± 0.6) × 10-11 cm3.mol-1.s-1 reported by Porter et al. 1997. The modelling of these experiments is ongoing to allow to derive and/or validate complete oxidation mechanisms for these three species.
How to cite: Chantraine, É., Jamar, M., Shaw, D., Lahccen, A., Fittschen, C., Dusanter, S., Carslaw, N., and Schoemaecker, C.: Oxidation mechanisms study of molecules of interest for indoor air and atmospheric chemistry , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12615, https://doi.org/10.5194/egusphere-egu26-12615, 2026.
Deterministic application of computational simulations of PM2.5 mass concentration in residences, informed by occupant diaries, allows evaluation of the uncertainty from emission rates and activity character. Uncertainty is generated by emission rates through varying methods to quantify rates of a given activity, whilst uncertainty is generated by activity character by the fact that participant surveys typically only ask for what activity is occurring, thereby omitting information on how it is occurring. Using the PyCHAM (CHemistry with Aerosol Microphysics in Python) box model alongside measurements for contrasting case studies from inhabited family homes in Bradford (UK), we show that these uncertainties are sufficiently great to undermine apportionment of key sources of PM2.5 in residences, motivating future work to reduce uncertainty.
How to cite: O'Meara, S. P., Shaw, D. R., Chatzidiakou, L., Shao, Y., Thomas, M., Cheung, R. W., Constantine, R., Yang, T. C., McEachan, R. R. C., Hamilton, J. F., McFiggans, G., and Carslaw, N.: Emission and activity uncertainty limits source apportionment for PM2.5 mass in residences, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10276, https://doi.org/10.5194/egusphere-egu26-10276, 2026.
While consumer-grade natural gas leaks contribute to methane-induced climate change, they can also degrade air quality both indoors and outdoors. However, limited leakage and gas composition data exist outside of North America. Here, we chemically characterized 78 unburned gas samples from residential stoves and measured stove-off natural gas leakage in 35 homes across seven cities in the United Kingdom, Netherlands, and Italy. Benzene, a known human carcinogen, was substantially elevated in unburned gas compared to North America (9 to 73 times higher on average), while sulfur-based odorants, which are added to natural gas to warn against explosivity, were lower. Stove-off methane leakage rates had a highly skewed, long-tailed distribution with an average of 46 mg/hr and a range from no detectable leak to 651 mg/hr. Modeling of indoor kitchen benzene enhancements from gas stove leaks showed potential for hazardous benzene exposure, often undetectable by odor. Eight percent of homes exhibited a stove-off leak that, combined with city-median benzene concentrations in gas, resulted in modeled benzene enhancements above the European Union’s annual limit value of 1.6 ppbv. Modeling of an outdoor distribution pipeline leak resulted in benzene concentrations over four times the European Union’s 200 ppbv occupational hazard limit and showed benzene enhancements up to 10 km away. These modeled indoor and outdoor enhancements are in addition to other sources of benzene exposure from cooking, smoking, gasoline, and leaks from other gas appliances or pipelines. The combination of high benzene and relatively low odorization in natural gas suggests that hazardous leaks are likely underreported in Europe. Natural gas leaks are not just a climate or explosion risk—they are an underrecognized public health issue.
How to cite: Sparks, T., Kashtan, Y., Rowland, S., Lebel, E., Goldman, J., Finnegan, C., Huang, G., Lucha, N., Shankute, A., Heath, N., Bisogno, S., Bilsback, K., Garg, A., Hill, L. A., Jackson, R., Shonkoff, S., and Michanowicz, D.: Benzene and Other Hazardous Air Pollutants in Consumer-Grade Natural Gas in the United Kingdom, Italy, and the Netherlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14792, https://doi.org/10.5194/egusphere-egu26-14792, 2026.
Air pollution is the leading Global Burden of Disease risk factor [1]. People spend most of the time indoors and especially children are estimated to spend 90% of their day in indoor environments [2] where they are exposed to indoor air pollution. Children are particularly susceptible to the effects of air pollution, as their faster breathing rate and immature bodies make them more prone to accumulating higher concentrations of pollutants in their bodies [3]. As part of the Horizon Europe project LEARN, we measured indoor air pollution in four elementary schools in Denmark. Our measurements comprised several air-quality parameters such as particulate matter (PM) mass focusing on PM2.5, particle number (PN), and black carbon (BC). The study followed a single blinded crossover design with measurements carried out in two classrooms in parallel. One classroom had an air-purification device with particulate filter in operation (intervention) and the other had an air-purification device without a filter installed (sham) in a randomized manner. The researchers were aware of the presence/absence of the intervention, while children and teachers were blinded. Each measurement campaign lasted five to six weeks including a baseline, intervention, wash-out period, and sham. Fig. 1 shows diurnal variation in PM2.5 levels in two different classrooms with and without intervention. Interestingly, between 8:00-14:00 on weekdays when the classrooms were occupied, measurements showed an increase in PM2.5 indicating high exposure during their school hours. The effects of air-purification device are clearly visible as PM2.5 levels are lower at times when classrooms had the intervention. The absolute mass concentrations are not final as no sensor calibration factors have yet been applied to data shown here. During the next step of the study, we will investigate the factors leading to high PM2.5 concentrations indoors during the classroom hours and suggest mitigation strategies for air pollutants improving indoor air quality in schools. We will also investigate the effects of PM2.5 on children’s cognitive functions during school hours. First results on the efficiency of air purification systems within our studies suggest that such set-ups can improve air quality in classrooms to a significant extent. However, more detailed analysis needs to be conducted before final assessment of this effect can be made.
Fig. 1: Comparison of diurnal variation in PM2.5 for individual classes i.e., a.) classroom 1 and b.) classroom 2 with intervention periods and sham intervention periods.
References:
1. Murray, C. J. L. et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet 396, 1223–1249 (2020).
2. de Gennaro, G. et al. Indoor air quality in schools. Environ. Chem. Lett. 12, 467–482 (2014).
3. Bennett, W. D., Zeman, K. L. & Jarabek, A. M. Nasal Contribution to Breathing and Fine Particle Deposition in Children Versus Adults. J. Toxicol. Environ. Health A 71, 227–237 (2008).
How to cite: Kumar, V., Hildebrand, F., Jensen, B., Christoffersen, C., Omar, A. H., Madsen, H. W., Nielsen, C. B., Frederickson, L. B., Gutzke, V. H., Gabel, C., Laursen, K. R., Sigsgaard, T., Sørensen, M. O. B., Sørensen, L. L., Nøjgaard, J. K., and Massling, A.: Overview of indoor air pollution measurements in elementary schools in Denmark and impacts of air-purification devices: a case study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21732, https://doi.org/10.5194/egusphere-egu26-21732, 2026.
Air pollution is a significant driver of adverse health outcomes, contributing to an estimated 6–7 million premature deaths in 2019. According to the World Health Organization (WHO), nearly half of these fatalities are attributed by indoor air pollution, including particulate matter (PM), a critical concern as populations spend the majority of their time indoors. Exposure to PM2.5 is positively associated with cardiovascular diseases, lung cancer, neurodegenerative conditions, and elevated oxidative stress in cells. Despite growing recognition of its health relevance, characterizing indoor air quality (IAQ) remains challenging due to building designs, ventilation systems, and human activity. Large-scale residential IAQ monitoring is limited, as indoor data are difficult to collect at scale. While low-cost sensors (LCS) offer a promising approach for improving spatial and temporal coverage, they face challenges related to inter-model variability and limited accuracy for gaseous pollutants such as NO, NO2 and O3.
Singapore is a complex urban city located at the southern tip of the Malay Peninsula. It is characterized by high population density, a major petrochemical complex, and one of the world’s busiest shipping ports and airports. Several previous studies have reported seasonal and spatial variability of black carbon (BC), brown carbon (BrC) and organic aerosols (OA). Our previous work using drone-based light absorption measurements reported elevated outdoor BC and BrC, near the 10th and 20th floors, respectively, compared to ground level. Notably, 77% of Singaporeans live in Housing and Development Board units. Of these buildings, 82% exceed 10 floors and 11% exceed 20 floors. As a result, vertical gradients in air pollution may have important implications for indoor exposure.
In this study, we explore feasibility of collecting IAQ data in the SG100K cohort. The cohort includes 100,000 participants with detailed clinical assessments and linkage to health records, allowing for a direct link between environmental exposure and health outcomes to be examined. This feasibility study consists of 200 participants, informing protocols for scaling up measurements in the SG100K cohort over 5 years. Each participant undergoes three months of continuous indoor measurements in their living room and bedroom. Our low-cost sensor system collects PM2.5, CO2, temperature, and humidity data remote. Data are supported by a proprietary remote data acquisition and quality-control pipeline. A subgroup of participants will also measure particle number concentration to explore the impacts of cooking and traffic emissions.
Preliminary indoor measurements indicate significant vertical variation in PM2.5 concentrations within the same building. Higher concentrations were consistently observed on the 11th floor (12.1±3.9 µg/m3) compared with the 5th and 7th floors (6.3±2.5 and 8.0±3.3 µg/m3, respectively). In addition, indoor PM concentrations do not always follow outdoor ground-level diurnal patterns, suggesting that indoor PM is influenced by indoor human activity, indoor–outdoor air exchange, filtration systems, transport, and secondary processes. Initial cross-sensor comparisons demonstrate consistent performance among individual devices. Further analysis will include a wider range of room types, locations, and floor heights. Data collected from RAHES will be synthesized with longitudinal health records to elucidate how the residential environment influences human behaviours and health outcomes.
How to cite: Ma, M., Fu, X., Gonzales, T., Falk, M.-R., Lee, J. K. W., Mastorakos, E., Bardhan, R., Li, M., and Brage, S.: RAHES: Remote Assessment of Health Exposures and Environment in SG100K Study Using a Low-Cost Indoor Air Quality Monitoring System, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8943, https://doi.org/10.5194/egusphere-egu26-8943, 2026.
Indoor concentrations of volatile organic compounds (VOCs), such as aromatic hydrocarbons, alkanes, and formaldehyde, are higher than outdoor levels. Exposure to these pollutants has raised ongoing concerns about their long-term health impacts. Assessing indoor air quality and associated health risks requires an in-depth understanding of human lifestyles and comprehensive analysis of VOCs. Key to this is identifying critical pollutants and establishing population exposure scenarios across different indoor environments. Hong Kong serves as a representative urban case study, with a population density of approximately 50,000 residents per square kilometer. This study collected air samples from various microenvironments in Hong Kong, including residences, activity centers, transportation settings, and outdoor areas. The concentrated VOCs were re-volatilized and injected into three gas chromatography systems for analysis, detecting 90 VOCs along with concentrations of carbon monoxide and carbon dioxide. The results revealed significant differences in VOC profiles across different environments: the main components of alkenes were isobutene, propene, isoprene, and ethylene; alkanes primarily consisted of ethane, isobutane, propane, and n-butane, with indoor concentrations of propane significantly higher than outdoor levels. This study conducted a risk assessment of indoor pollutants. The results showed that the cumulative carcinogenic risks for both children and adults exceeded acceptable limits. The cumulative hazard quotient for adults also surpassed safety thresholds in multiple exposure scenarios. These findings indicate that future VOC risk assessments must incorporate predicted compounds and scenario-specific exposure evaluation systems.
How to cite: Xu, Z. and Gu, D.: The Assessment of VOCs Health Risks for Various Indoor Living Scenarios in Hong Kong, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10018, https://doi.org/10.5194/egusphere-egu26-10018, 2026.
A key challenge in modern epidemiology is understanding the source-related effects of air pollution on health. Large-scale studies traditionally use measurements of outdoor reference monitoring stations as metrics of exposure. However, these measurements are often poorly correlated with personal exposure levels due to varying local sources, microenvironmental settings, attenuation effects of the building envelops and individual behavioural patterns. My research expands the capabilities of low-cost sensors by developing analytical techniques to maximise extracted information:
- A time-activity model to classify major exposure-related microenvironments using as input readily gathered parameters from smartphone technologies. to provide a comprehensive picture of environmental health risks during daily life.
- A novel source apportionment method to characterise local and regional emission sources, and review how the low-cost sensor measurements can be used as proxies for more detailed measurements.
This integrated technological and analytical framework can revolutionise the fields of indoor exposure, building science and epidemiology. Health models using improved exposure metrics indicate the strong influence of source-related exposure on health.
How to cite: Chatzidiakou, L.: Integrated technological and computational tools to capture detailed personal exposure for improved health models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22310, https://doi.org/10.5194/egusphere-egu26-22310, 2026.
Posters on site: Tue, 5 May, 14:00–15:45 | Hall X5
Cities are significant contributors to global greenhouse gases. Accurately quantifying urban CO2 emissions from atmospheric observations requires fine-scale modelling and rigorous inverse optimization of the emissions. Within the ICOS Cities project, we developed a high-resolution urban CO2 emission estimation framework for Munich, coupling a detailed emission inventory with the computational fluid dynamics (CFD) based GRAMM-SCI/GRAL-ST-ROG model and with a novel inversion algorithm based on a Markov Chain Monte Carlo and Gaussian Process (MCMC-GP) approach.
The framework utilizes GRAMM-SCI to simulate mesoscale wind fields, which are subsequently refined by the GRAL-ST-ROG model. By integrating high-resolution datasets—including land cover, 3D building, and a self-developed tree cover dataset—with surface meteorological observations and Doppler wind lidar vertical profiles, the model generates wind fields at a 10-meter spatial resolution. The resulting wind fields are then combined with high-resolution emission inventories to drive the CO2 dispersion simulation.
The simulated CO2 concentrations were validated against Munich's mid-cost observation network. Furthermore, a new MCMC-GP algorithm was developed to facilitate spatio-temporal inversion across multiple emission sectors. This approach offers high flexibility, the capability to perform inversions under data-sparse conditions, and the ability to refine prior knowledge—such as spatial correlations and uncertainties—to ensure the method’s robustness.
This study presents a high-fidelity tool for quantifying urban emissions, supporting evidence-based policymaking to achieve climate targets.
How to cite: Li, J., Chen, J., Brunner, D., Öttl, D., Holst, C. C., and Tang, H.: Urban CO2 Emission Assessment based on High-Resolution Dispersion Simulations and MCMC based Inversion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17218, https://doi.org/10.5194/egusphere-egu26-17218, 2026.
In this study, long-term data from two flux eddy-covariance flux towers (since 2004 and 2009, respectively) in the city centre of Basel, Switzerland, which are only 1.6 km apart from each other, are analysed with focus on the source strengths of CO2 emissions in the flux footprints of the towers. The wind field in the city of Basel is predominated by a valley wind system due to its location in the Rhine valley with a clear diurnal pattern of the wind flow, if not superimposed by a macroscale synoptic weather situation. For a detailed interpretation of the mean seasonal diurnal courses of CO2 fluxes, a distinct flux footprint analysis, combined with a detailed land cover map of the city, is applied. Land cover classes like “buildings” and “roads” are extended with attributes characterizing the source strength of CO2, i.e. the type of heating (oil, gas, district heating, etc.) and the traffic volumes, respectively, and these source strengths are weighted by the flux footprint. This framework allows a distinct interpretation of the observed seasonal and annual trends of the two flux towers. The long-term time series show different but, in both cases, declining trends in CO2 emissions. These trends can be mainly attributed to the extension of the district heating network by the city administration during the last 15 years. Traffic volume changes have also strong impact on the total amount of CO2 emissions, but, despite great efforts of the city administration to reduce the traffic in the city center, these measures have only minor impacts on the CO2 flux.
How to cite: Feigenwinter, C., Sigmund, A., Spirig, R., Stagakis, S., Vogt, R., and Kalberer, M.: Impact of transition of heating types and traffic on urban CO2 emissions – long-term interannual and seasonal analysis of two flux towers in the city of Basel, Switzerland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6781, https://doi.org/10.5194/egusphere-egu26-6781, 2026.
Urban areas are hotspots for CO2 emissions. Therefore, accurately estimating sources and sinks in these areas is important for studying the urban carbon budget. Due to the heterogeneous land cover of urban areas, modeling in high resolution is essential for accurate estimates of CO2 fluxes and concentrations in urban domains. Being a major sink for CO2, the urban biosphere plays a crucial role in the urban carbon budget, and accurately estimating the biogenic fluxes is key to our understanding of the urban carbon cycle. We model CO2 concentrations in the Greater Toronto Area (GTA), the largest metropolitan area in Canada, using the Weather Research and Forecasting Model coupled with GEOS-Chem (WRF-GC), which makes it possible for us to run high resolution simulations in our region of interest, with a resolution of 1 km x 1 km. For our biogenic fluxes, we use two regional biogenic models, the Solar Induced Fluorescence for Modelling Urban biogenic Fluxes (SMUrF) and the Urban Vegetation Photosynthesis and Respiration Model (UrbanVPRM), in addition to the global biogenic fluxes from the Más Informada Carnegie-Ames-Stanford-Approach (MiCASA) model, to assess the effects of different vegetation models on CO2 concentrations over the GTA. Using the regional biogenic models with 500m x 500m resolution and global emissions with 0.1 x 0.1 degrees resolution, we investigate the effects of including different high resolution fluxes in our model, and how modifications in these vegetation models can affect the CO2 concentrations around our model domain.
How to cite: Demirci, C., DiMaria, C., Madsen-Colford, S., Weir, B., Wunch, D., and Jones, D.: Effects of vegetation models on urban CO2 simulations over the Greater Toronto Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13487, https://doi.org/10.5194/egusphere-egu26-13487, 2026.
Urban environments represent major hotspots of atmospheric CO2 emissions; however, the availability of measurements resolving fine spatial and temporal variability remains limited. This limitation is largely due to the high cost and sparse deployment of reference-grade monitoring systems in complex urban settings. In recent years, sensor-based approaches have shown that dense networks of low- to mid-cost CO2 sensors can substantially enhance spatial coverage in complex urban settings. Urban sensor networks, such as the Zurich CO2 Sensor (ZiCOS) network (Grange et al., 2025) and the BErkeley Atmospheric CO2 Observation Network (BEACO2N) in California (Shusterman et al., 2016), have shown that such deployments can improve the characterization of the urban CO2 spatial patterns and temporal dynamics. These developments highlight how sensor-based networks can enable denser spatial coverage and provide an effective pathway toward a high-resolved description of urban CO2 variability.
The current study outlines a recently initiated project on urban CO2 budgeting in the Po Valley, a densely populated area in southern Europe, combining atmospheric monitoring by reference equipment and mid-cost sensors, with atmospheric modelling by urban-scale Lagrangian particle dispersion modelling. We assessed the field comparability of two identical mid-cost CO2 sensors GMP343 (Vaisala Oy). The instruments were deployed between May–November 2025 at the rooftop of the Geophysical Observatory of the University of Modena and Reggio Emilia, a 40 m high tower located in the city centre of Modena, Italy. The sensors were laboratory calibrated prior to deployment, and measured CO2 concentrations were corrected for temperature and pressure using the built-in firmware algorithm, followed by the application of sensor-specific calibration offsets.
To assess the inter-sensor agreement and operational stability, we processed the six months of continuous measurement data. Sensor performance was evaluated using correlation analysis, error statistics, and Deming regression, demonstrating strong agreement between the sensors and good stability. The two mid-cost sensors exhibited a high linear correlation (Pearson’s r = 0.965) and a mean bias of 2.47 ppm during the intercomparison. The results achieved so far showed their suitability for high-resolution urban monitoring and for an integration with reference-grade eddy covariance (EC) observations in urban CO2 assessment studies.
Since January 2026, a 2 m pole on the rooftop of the Observatory has been equipped with a reference-grade EC measurement setup consisting of a LI-COR 7200RS gas analyzer (LI-COR Biosciences) and a 3D Gill WindMaster anemometer (Gill Instruments), and provides continuous measurements of urban CO2 fluxes. Concurrently since December 2025 the mid-cost sensors were moved at two urban air quality regulatory monitoring stations under urban background and urban traffic conditions, where several regulatory atmospheric pollution monitors are already in place. Study outlooks include the maintenance of the CO2 network for at least 12 months and the setup of an urban scale CO2 dispersion model combining both biogenic and anthropogenic fluxes within a lagrangian particle dispersion model.
How to cite: Bigi, A. and Binoy, A.: Field Intercomparison of Mid-Cost CO2 Sensors for Urban Atmospheric Monitoring, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16450, https://doi.org/10.5194/egusphere-egu26-16450, 2026.
Urban areas are global hotspots of anthropogenic greenhouse gas emissions; however, distinguishing between fossil fuel combustion and biogenic fluxes remains challenging due to the complexity of the urban environment. High-precision atmospheric observations are essential for validating "bottom-up" emission inventories and guiding local green strategies. This study presents a comprehensive comparative analysis examining atmospheric CO2 and CH4 mole fractions, as well as atmospheric radiocarbon (14C) signals, from May 2025 in Debrecen (an urban environment) and two elevations at the regional background station in Hegyhátsál (ICOS HUN).
During the research campaign, Picarro Cavity Ring-Down Spectroscopy (CRDS) analyzers were employed at both sites for continuous, high-resolution measurement of CO2 and CH4 concentrations. These measurements were complemented by a two-week integrated 14CO2 sampling, followed by Accelerator Mass Spectrometry (LEA-AMS) analysis. This dual-tracer approach enables the separation of the Debrecen CO2excess into fossil and biogenic components.
Our results highlight that the urban-derived excess varies dynamically relative to the regional background. The continuous mole fraction data reveal characteristic diurnal and seasonal patterns, with wintertime enrichment of CO2 and CH4, driven by reduced boundary layer mixing and increased heating demand. Analysis of CH4:CO2 correlations provides further insight into sector-specific emissions, distinguishing between traffic-dominated and heating-dominated periods. By combining high-frequency concentration measurements with isotopic constraints, our study provides a more precise understanding of the urban carbon cycle in a mid-sized city in Hungary, highlighting the importance of parallel urban-rural monitoring networks in verifying climate protection measures.
How to cite: Baráth, B. Á., Bán, S., Varga, T., Barcza, Z., Haszpra, L., and Molnár, M.: Comparative analysis of atmospheric CO₂, CH₄, and ¹⁴CO₂ between a Hungarian urban site and an ICOS regional background station, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16895, https://doi.org/10.5194/egusphere-egu26-16895, 2026.
Major metropolitan areas are critical carbon emission hotspots, and understanding their carbon dynamics is essential for developing targeted climate mitigation strategies. Remote background stations often capture spatially smoothed anthropogenic signals, failing to resolve distinct urban source–sink processes. Here, we leveraged the unique 632-m Shanghai Tower (121.51°E, 31.23°N) to conduct a nearly 2-yr field campaign (April 2021–March 2023), aiming to investigate CO2 and CO dynamic from the top of urban canopy layer (UCL) via stationary, continuous, single-level, high-precision, in-situ measurements with a cavity ringdown laser spectrometer. Campaign-averaged mole fractions substantially exceeded global and regional backgrounds, confirming a pronounced urban carbon burden. Through a multi-stage filtering framework targeting nocturnal measurements, we derived robust regional background values. Component analysis of CO2 excess, using CO as a reliable regional combustion tracer, revealed burning of fossil fuels as the dominant contributor (avg. 85%), alongside biogenic processes that enhanced this atmospheric excess, especially in winter under respiratory predominance, but less so in summer when partially offset by net photosynthetic uptake and cleaner airmass dilution. The 2022 Shanghai lockdown provided a natural experiment that underscored the pronounced sensitivity of UCL-top observations to metropolitan-scale anthropogenic perturbations, as reflected in synchronized decline and rapid rebound of CO2 and CO, along with a marked reversal of their emission ratio compared to 2021. Overall, these findings affirm that UCL-top observations effectively capture integrated metropolitan carbon signals, supporting refined emission tracking and top-down carbon neutrality strategies.
How to cite: Fu, S. and Fang, S.: Observational Insights into Atmospheric CO2 and CO at the Urban Canopy Layer Top in Metropolitan Shanghai, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2658, https://doi.org/10.5194/egusphere-egu26-2658, 2026.
Cities are major sources of both air pollutants and greenhouse gases due to dense energy consumption, traffic, industry, and residential heating. Fossil fuel carbon dioxide (CO2) is frequently co-emitted with nitrogen oxides (NOx), linking urban air quality degradation with climate forcing. However, monitoring urban CO2 emissions remains challenging because fixed ground stations provide sparse coverage, while bottom-up inventories often lack the temporal responsiveness needed to capture rapid socioeconomic and policy-driven changes. These limitations are particularly critical for cities, where emission patterns are highly heterogeneous in space and time.
Here we present a satellite-based framework to constrain urban and regional fossil fuel CO2 emissions across China from 2019 to 2024 by exploiting the co-emission relationship between NOx and CO2. The approach integrates tropospheric NO2 vertical column densities observed by the TROPOspheric Monitoring Instrument (TROPOMI) with simulations from the GEOS-Chem chemical transport model. Anthropogenic NOx emissions are first optimized using a finite-difference mass balance inversion, which links observed NO2 enhancements to emission perturbations at high spatial resolution. The optimized NOx fields are then translated into fossil fuel CO2 emissions using dynamically derived CO2/NOx ratios from bottom-up inventories, allowing indirect yet spatially explicit constraints on urban CO2 emissions.
Our results reveal that China’s fossil fuel CO2 emissions remained broadly stable over 2019–2024, with pronounced spatial contrasts between urban agglomerations and less developed regions. Persistent emission hotspots are identified over major metropolitan clusters, including the Beijing–Tianjin–Hebei region, the Yangtze River Delta, the Pearl River Delta, and the Fenwei Plain, underscoring the dominant role of cities in national carbon budgets. Despite overall stability at the national scale, many large urban regions exhibit discernible declines in emissions, consistent with strengthened air pollution control policies and structural energy transitions. In contrast, energy-intensive provinces outside the major city clusters continue to show increasing trends, highlighting emerging risks of regional “high-carbon lock-in”. Comparisons with widely used inventories such as EDGAR, MEIC, and Carbon Monitor indicate that the satellite-constrained estimates more effectively capture abrupt emission changes associated with events such as the COVID-19 pandemic and subsequent economic recovery.
Overall, this study demonstrates that satellite-derived NO2 observations provide a powerful, observation-driven pathway to monitor urban fossil fuel CO2 emissions at high spatial and temporal resolution. By bridging air quality and greenhouse gas perspectives, the framework offers new opportunities to evaluate the climate co-benefits of urban air pollution policies, support city-scale carbon budgeting, and improve the transparency of emission monitoring in rapidly evolving urban environments.
How to cite: Mao, Y. and Jiang, F.: Urban-scale constraints on fossil fuel CO2 emissions from satellite-inferred NO2: implications for air quality–climate co-benefits in Chinese cities (2019–2024), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2761, https://doi.org/10.5194/egusphere-egu26-2761, 2026.
Our current understanding of the carbon cycle relies on a limited network of direct and remote sensing systems for measuring atmospheric greenhouse gases (GHGs). While this has provided a general understanding of natural and anthropogenic GHG sources and sinks, it is insufficient for monitoring subtle emission changes caused by climate change, mitigation efforts, and interventions. To address this, a new network, integrating existing and emerging technologies, will be necessary. This network, enhanced through public-private partnerships, will enable verification of GHG emissions and uptake from global to local scales.
A prime example of these expanding private sector collaborations is the recent partnership between NOAA and United Airlines. This collaboration leverages commercial aircraft to provide up to eight daily atmospheric profiles at a fraction (1%) of the cost of comparable research aircraft. The benefits of these observations are magnified by their low cost, increased frequency, and the ability to frequently sample large metropolitan areas, which are often served by mid-size aircraft like the Boeing 737. These profiles are crucial for bridging the gap between ground-based direct measurements and satellite-based remote measurements, thereby facilitating GHG emission monitoring across all scales.
This presentation will offer an overview and update on a global initiative that utilizes a unique platform to enhance our capacity for GHG observation. Specifically, NOAA's agreement with United Airlines to carry a GHG analyzer in the EE-bay of their 737-900ER short-haul aircraft is expected to significantly expand measurements of CO2, CH4, CO, and water vapor in and out of major metropolitan areas worldwide. With 50 aircraft distributed among 10 different airlines, we anticipate sampling 200 metropolitan areas globally with a frequency of better than every 3 days. This will lead to a substantial reduction in the uncertainty of urban methane emissions, as well as providing critical constraints on regional GHG emissions and satellite retrievals through the unique characteristics of aircraft profiles.
How to cite: Sweeney, C. and Peichle, J.: Using Commercial Aircraft to Monitor Urban Carbon Reservoirs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15478, https://doi.org/10.5194/egusphere-egu26-15478, 2026.
Urban areas globally are the major source regions of anthropogenic greenhouse gases [1]. To reduce city-scale uncertainties associated with bottom-up inventory-based emission estimates and to design and evaluate emission reduction measures, top-down emission estimates based on concentration measurements and transport modeling are necessary. Inferring these emissions from a number of in-situ concentration measurements comes with the challenge of limited measurement representativeness, uncertain knowledge of prior emissions, and uncertainties in transport modelling on very local scales. Path-integrated concentration measurements are representative of areas on the kilometer scale, and thus, they are less sensitive to very local processes and more representative of model grid scales. They therefore have the potential to improve measurement-based urban emission quantification in the future.
We measure path-integrated concentrations by sending light along kilometer-long air paths above the city of Heidelberg, Germany, to reflectors and spectroscopically analyze the returning signal. By fitting an absorption model to the spectra, we infer the CO2 concentrations along the respective paths. Our spectroscopic method of choice is Dual-Comb Spectroscopy (DCS) based on two interfering laser frequency combs. It allows measuring broadband spectra with high spectral resolution and signal-to-noise ratio.
We present the first nine months of concentration measurements of greenhouse gases along one path above the city of Heidelberg. We show first results from this deployment period and compare them to a co-deployed Fourier-transform spectrometer (FTIR) that has been continuously running since 2023 [2] and different in-situ sensors. We also report our current progress in expanding our setup into a network consisting of multiple light paths above the city, including modelling of expected concentration gradients, with the aim of inferring urban emissions.
References:
[1] Intergovernmental Panel on Climate Change (IPCC). (2021). Climate Change 2021: The Physical Science Basis. Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, et al.]. Cambridge University Press. https://doi.org/10.1017/9781009157896
[2] Schmitt, T. D., et al. (2023). An open-path observatory for greenhouse gases based on near-infrared Fourier transform spectroscopy. Atmos. Meas. Tech., 16(24), 6097–6110. https://doi.org/10.5194/amt-16-6097-2023
How to cite: Sindram, M., Schmitt, T. D., Dubroeucq, R., Mukherjee, S., Pilz, L., Pfeifer, T., Oberthaler, M. K., and Butz, A.: Towards an Urban Network of Path Integrated Greenhouse Gas Measurements Using Dual-Comb Spectroscopy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9995, https://doi.org/10.5194/egusphere-egu26-9995, 2026.
Urban air pollution and greenhouse gas (GHG) emissions stem from diverse sources, including transportation, heating, buildings, waste management, industrial and agricultural activities, and natural events like forest fires. Simultaneous monitoring of air pollutants and GHGs with high selectivity and sensitivity is essential for resolving the complex chemical interactions and source–sink dynamics that characterize urban atmospheres. Accurate measurements across various spatial and temporal scales are essential for modeling and validating emission inventories or satellite observations.
Traditionally, solutions for monitoring air pollutants or GHGs with high precision and temporal resolution have been "one-gas-one-instrument", resulting in large, stationary setups with high energy consumption. MIRO Analytical’s compact laser absorption spectrometer that integrates multiple mid-IR lasers enables simultaneous high-precision measurements of greenhouse gases (CO2, N2O, H2O, CH4, C2H6), pollutants (CO, NO, NO2, O3, SO2, NH3), and trace gases (OCS, HONO, CH2O) within a single instrument. With a time-resolution of up to 10Hz, it is well-suited for detecting the relationships between co-emitted pollutants and GHGs as well as eddy-covariance flux studies.
In this contribution, we showcase the broad variety of MIRO’s MGA analyzers for urban applications.
Thanks to their versatility, the same instrument can be used for: (I) Ambient air monitoring, demonstrated through a comparison campaign at a Zurich air-quality monitoring station, (II) urban eddy-covariance measurements, linking GHG fluxes to reactive gas emissions and improving the identification of emission sources and (III) airborne and van-based mobile measurements, enabling flexible deployment across urban environments. This unique multi-purpose approach provides insights that go beyond standard monitoring techniques and contributes to a deeper and more comprehensive understanding of the complex urban atmosphere.
Key words: eddy covariance, multi-compound gas analyzer, mobile monitoring, GHG fluxes, air pollutants
How to cite: Espic, C., Smith, E., and Bruckhuisen, J.: From stationary Eddy covariance systems to mobile gas analyzer platforms: monitoring urban GHGs and air pollutants, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18400, https://doi.org/10.5194/egusphere-egu26-18400, 2026.
Urban areas account for approximately two-thirds of global anthropogenic carbon dioxide (CO₂) emissions. Direct greenhouse gas flux measurements provide the basis for quantifying city emissions and developing effective mitigation strategies. Eddy covariance (EC) is a direct, continuous monitoring method for capturing net surface fluxes of CO2 (and other greenhouse gases) at a high temporal resolution (30 min). Despite the methodological potential, only a few urban locations worldwide currently estimate greenhouse gas fluxes with the EC method.
In this study we established two EC systems in the city of Münster in northwest Germany. Münster is a midsized city (about 300,000 in habitants), known for its extensive cycling culture and green urban character. Often called the bicycle capital of Germany, Münster combines urban life with abundant parks, green spaces, and a high modal share of bicycle traffic. Since May 2025, continuous 30-min observations of CO2 and energy fluxes are being collected in two locations, combining a rooftop (33m above the ground) EC system sampling a heterogeneous urban footprint with complementary near-surface (2.4m above the ground) measurements over unmanaged urban grassland and impervious surfaces. This coordinated observational design enables investigation of how different urban surface types contribute to the integrated city-scale CO2 exchange and provides a robust basis for long-term carbon-cycle monitoring.
In addition, the observational framework is complemented by process-based urban land-surface modeling using the Surface Urban Energy and Water Balance Scheme (SUEWS), which enables a bottom-up representation of urban energy and CO2 exchange. In combination with the multi-site EC measurements, SUEWS will support interpretation of seasonal and diurnal variability and provide a first-order partitioning of biogenic and anthropogenic contributions at the neighborhood scale.
How to cite: Aslan, T. and Gharun, M.: Direct quantification of greenhouse gas emissions in a mid-sized German city , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5654, https://doi.org/10.5194/egusphere-egu26-5654, 2026.
How to cite: Oliveira Makowski, M., Tang, H., Brase, R., Klappenbach, F., Luther, A., Stauber, J., Grasberger, T., Zhao, X., and Chen, J.: RETRO: City-Scale High-Resolution Footprint Modeling Using LPDMs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17311, https://doi.org/10.5194/egusphere-egu26-17311, 2026.
How to cite: Jin, X.: Impact of urban space on PM2.5 distribution: A multiscale and seasonal study in the Yangtze River Delta urban agglomeration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5508, https://doi.org/10.5194/egusphere-egu26-5508, 2026.
Wintertime aerosol loading is a prevalent public health issue in Asian megacities. A combination of meteorological effects, local emissions, and biomass burning contributes to high aerosol loading in some of the most densely populated regions of the globe. Local controls of this pollution have been effective at reducing urban aerosol loading, but the effectiveness of controls of nitrogen oxides (NOx) versus ammonia (NH3) remains to be seen. Ammonium nitrate (AN) formation is especially relevant during the cold season due to increased thermodynamic favorability at lower temperatures. Understanding these chemical controls remains difficult due to a lack of comprehensive measurements that incorporate the precursors and products of aerosol formation spatially in both vertical and horizontal transport. Using in-situ measurements from the NASA DC-8 taken during the 2024 ASIA-AQ campaign, the relative contributions of NH3 and NOx to inorganic AN formation is explored over and near Asian megacities in the Philippines, South Korea, Taiwan, and Thailand. Missed approaches at airports in and near these cities provide insight into the vertical distribution of the relevant gas-phase precursors and their corresponding aerosol products across both tropical and wintertime urban environments.
By quantifying the thermodynamic AN dissociation constant, we calculate that over Taiwan 25% of vertical profiles near urban centers have conditions where NH3 and nitric acid (HNO3) are abundant enough for thermodynamically favorable AN formation. Preliminary results show this is generally NOx limited and more favorable aloft at or above the boundary layer due to lower temperatures. This estimation will be further constrained against the ISORROPIA-II aerosol thermodynamic model and expanded across missed approaches over all the sampled countries. To further understand the impact of urban emissions on this aerosol formation, tracers such as carbon monoxide, methane, and nitrous oxide are used to determine the relevant contributions of urban versus agricultural emissions to the relevant precursors. Results will be compared to relevant policy on emissions regulations to evaluate the effectiveness of currently implemented controls.
How to cite: Boyd, R., Choi, Y., Yi, H., Sevostianov, V., Moore, D., Symonds, G., Kim, D., Campuzano-Jost, P., Jimenez, J.-L., Ball, K., Crounse, J., Lee, Y. R., Wennberg, P., Lee, M., Dibb, J., Digangi, J., Choi, Y., Diskin, G., and Zondlo, M.: Investigating Urban Ammonium Nitrate Aerosol Formation over Asian Cities with In-Situ Measurements and Thermodynamic Modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14425, https://doi.org/10.5194/egusphere-egu26-14425, 2026.
We have interfaced an off-line chemistry-transport model (https://silam.fmi.fi) to the wind velocity fields obtained from PALM large-eddy simulation (LES) model. With the resulting setup the dispersion simulations with a deca-meter resolution become feasible with very moderate compute resources. As a proof of concept we demonstrate a few examples of the LES-driven dispersion simulations made with an ordinary PC.
In the presentation we discuss the difference between the assumptions in the LES and regional air-quality models and indicate several approaches
to cope with them and to reduce the storage and IO requirements for such a setup. We show a comparison of a simulated tracer dispersion in an urban environment made with native PALM transport scheme and with SILAM model driven by the same wind fields and discuss the differences between the transport schemes used in the models.
How to cite: Kouznetsov, R., Sofiev, M., Keskinen, J.-P., and Auvinen, M.: Driving a chemistry transport model with a large-eddy simulation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16692, https://doi.org/10.5194/egusphere-egu26-16692, 2026.
An air quality (AQ) network consisting of roughly 100 low-cost sensors and 12 high-quality AQ instruments is currently being set up in Enschede, the Netherlands. The network is part of Infrastructure Twente for Environmental Monitoring (ITEM), based at the University of Twente, which integrates climate, meteorological and hydrological observations in the region. By introducing AQ sensors in in an area with low sensor coverage, the ITEM-AQ network has the potential to improve local air quality estimates, enable enhanced monitoring, model evaluation, early-warning systems, and source apportionment.
The network will support a wide range of scientific investigations, including the interaction between air pollution and extreme temperatures in affecting human health, and the extent to which air quality exposure varies with socio-economic status. At the same time, ITEM-AQ will serve as a test bed to improve instrumentation, data handling, storage and sharing, leveraging both new and existing platforms (e.g., samenmeten.nl). Measurements from static AQ stations will be complemented by observations from instruments mounted on Uncrewed Aerial Vehicles that can provide atmospheric profiles in addition to near-surface “nose level” observations.
The ITEM-AQ infrastructure offers substantial opportunities for integration into university education and training. Stakeholders will be engaged from an early stage to co-create relevant and actionable outputs. At a later stage, data gathered by the AQ network will be integrated into an urban digital twin to aid policy development and evaluation.
How to cite: Penning de Vries, M., Dadrass Javan, F., Flacke, J., Ostermann, F., and Timmermans, W.: An urban air quality sensor network in Enschede, the Netherlands: Opportunities for science, technology, education, and policy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21198, https://doi.org/10.5194/egusphere-egu26-21198, 2026.
Understanding particulate pollution in Eastern Mediterranean (EM) cities is challenging due to the combined influence of local urban emissions, marine aerosols, and long-range transported desert dust. Conventional surface-based measurements often fail to detect lofted dust layers, while satellite-derived Aerosol Optical Depth (AOD) provides only column-integrated information, limiting its ability to represent near-surface PM2.5 (fine particulate matter 2.5 micrometres or less in diameter) concentrations. Here, we combine five years of ground-based lidar observations with high resolution satellite AOD retrievals, PM2.5 measurements and meteorological data over the EM to investigate aerosol layering, source contributions, and column-to-surface relationships across three contrasting urban environments: regional background, urban traffic and semi-indoor sites located along highway/railroad. Lidar profiling identifies ten distinct aerosol layering types, from shallow anthropogenic layers to deep mixed structures composed of desert dust, marine aerosols, and urban pollution. We find that the AOD-PM2.5 relationship is strongly regime-dependent, and the degree of column-surface coupling varies sharply across the three urban environments. Machine-learning models that incorporate vertical lidar features significantly improve PM2.5 predictions across all sites, outperforming models without vertical information. Overall, our results demonstrate that reliable urban PM2.5 assessment requires explicit consideration of vertical aerosol structure. Integrating lidar-derived features enhances the interpretation of satellite AOD and improves urban exposure estimates in complex EM atmospheres.
How to cite: Rogozovsky, I., Ansmann, A., Baars, H., Hofer, J., and Chudnovsky, A.: Vertical Structure Matters: Improving Urban PM2.5 Assessment Using Lidar at Background and Traffic-Influenced Sites, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-854, https://doi.org/10.5194/egusphere-egu26-854, 2026.
Dense urban areas experience poor air quality due to increased anthropogenic emissions and complex urban morphology that restricts ventilation. While our general understanding of urban air pollution has improved considerably through advances in numerical modeling and sensor platforms, our insights into neighborhood-to-building-scale pollution remain insufficient. Most current forecasting models do not account for urban climate processes, and traditional in-situ observations do not capture street-level variability in primary pollutants. Here, we investigate the street- and neighborhood-scale dynamics of air pollution in New York City, using both mobile and in situ observations. We used a backpack fitted with research-grade instruments to monitor particulate matter (PM2.5) and ozone. In-situ observations from multiple public air quality networks were also included in our analysis. Our results show a high degree of uniformity in street-level ozone concentrations in NYC, whereas particulate matter concentrations varied significantly. On days impacted by synoptic disturbances, both ozone and particulate matter concentrations were nearly uniform throughout the city. The fixed ground stations adequately captured the median PM2.5 concentration. However, they missed the extremes, which were, in some cases, two to five times the median value. The observations were also used to validate an urbanized WRF-Chem model and satellite-derived measurements. The numerical simulations conducted at 4km X 4km resolution performed better than the current forecast model in predicting both PM2.5 and ozone concentration. The model accounted for the impacts of the urban heat island effect and local sea breeze flows on air pollutants. The model particularly captured the ozone dynamics accurately.
How to cite: Ramamurthy, P., Hosannah, N., Ni-Meister, W., and Devineni, N.: Multiscale Analysis of Air Quality in New York City, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2213, https://doi.org/10.5194/egusphere-egu26-2213, 2026.
This study explored the inter-transport of PM2.5 between the Kaohsiung Harbor and the neighboring Metro Kaohsiung. PM2.5 was sampled at four sites for analyzing its chemical composition including water-soluble ions, metallic elements, carbons, anhydrosugars, and organic acids to characterize PM2.5’s chemical fingerprints. Furthermore, an air dispersion model, CALPUFF, was applied to simulate the spatiotemporal distribution of PM2.5 in the Kaohsiung Harbor and neighboring urban areas. Additionally, PM2.5 concentrations at nighttime were commonly higher than those in the daytime in winter, spring, and fall, while an opposite trend was observed in summer. High correlation of PM2.5 at the port and urban areas at nighttime implied the inter-transport phenomena of PM2.5 between these two areas. Sea salt spray, ship emissions, secondary aerosols, and heavy fuel-oil boilers were higher in the port area than those in the urban area. Mobile sources, fugitive dust, and waste incinerators were the major sources in the Metro Kaohsiung. Moreover, sea breeze significantly influenced the dispersion of PM2.5 from the Kaohsiung Harbor to the Metro Kaohsiung, particularly in the afternoon. The average contribution of PM2.5 from main engines of ships in the Kaohsiung Harbor was 2.9-5.3%, while the auxiliary engines contributed 3.8-8.3% of PM2.5 to the Metro Kaohsiung.
How to cite: Tseng, Y.-L.: Influences of Ship Emissions from an Asian Seaport on Ambient PM2.5 of Nearby Metropolitan Area: Field Sampling and Model Simulation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12067, https://doi.org/10.5194/egusphere-egu26-12067, 2026.
This study investigates how urban morphology and pollutant emissions influence near-surface meteorology and the spatial distributions of CO, NO2, O3, and PM2.5 in Songdo, Incheon, Republic of Korea. We use a fine-scale air quality modeling framework that couples computational fluid dynamics with atmospheric chemistry, driven by mesoscale meteorological and chemical fields and high-resolution emissions developed using a top-down approach. Model performance is evaluated against meteorological observations and multi-site air quality measurements within the study area. To examine the determinants of spatial variability, the domain is divided into subzones and statistical analyses are applied to relate simulated surface concentrations to emissions and building morphology parameters, including building surface fraction and occlusivity. Surface concentrations show the strongest associations with emissions for CO, NO2, and O3, whereas occlusivity exhibits the strongest association with PM2.5. Notably, systematic concentration differences are observed even under comparable emission levels, highlighting the influence of morphology on ventilation and near-surface pollutant accumulation. The findings suggest that preserving wind corridors and allocating open spaces, particularly in high-rise districts, can enhance ventilation and reduce pollutant buildup. This work supports urban planning and air quality management and provides a basis for future exposure and environmental health analyses.
How to cite: Kang, J.-E., Kim, D.-J., Kim, M. J., Lee, S.-H., Choi, W., and Kim, J.: Evaluating the effects of urban morphology and emissions on urban air quality using a CFD model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3677, https://doi.org/10.5194/egusphere-egu26-3677, 2026.
Ultrafine particles (UFP; diameter < 100 nm) in urban environments are emitted from fossil-fuel combustion, particularly vehicular emissions, whereas indoor emissions from cooking activities remain insufficiently characterized. This study examined indoor UFP exposure in 13 restaurants representing diverse cooking methods by measuring particle number concentrations (PNC) and mean particle diameter. On average, indoor PNC were 16.1 and 7.0 times higher than those in background and adjacent outdoor areas, respectively, while mean particle sizes were correspondingly smaller. The indoor-to-outdoor (I/O) ratio of mean PNC was 7.2 (±7.3), whereas that of mean particle size was 0.93 (±0.24), indicating direct emissions of smaller particles from cooking activities. Indoor PNC often approached or exceeded levels observed along major roadways with high heavy-duty diesel traffic. Variations in indoor PNC were governed not only by cooking characteristics but also by ventilation and microenvironmental factors, including room volume, cooking-source location, and the distance between cooking sources and seating areas. Closing windows or doors increased the indoor–outdoor PNC difference by a factor of 2.6 and the I/O ratio by 2.7, highlighting the importance of adequate ventilation.
A simplified respiratory deposition model estimated that 54.8% of inhaled indoor UFPs are deposited in the human respiratory tract, exceeding the factions estimated for background (45.2%) and adjacent outdoor (50.3%) environments. The alveolar deposition fraction averaged 39.4%, comparable to that in major roadways (42.8%). These findings suggest that long-term exposure to cooking-related UFPs in poorly ventilated environments may pose significant health risks and underscore the need for further characterization of their physical and chemical properties.
How to cite: Seo, S. and Choi, W.: Characterization of Indoor Ultrafine Particles from Various Cooking Activities and Their Respiratory Deposition Potential, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8821, https://doi.org/10.5194/egusphere-egu26-8821, 2026.
Indoor air pollution is a critical public health concern, with fine and ultrafine particulate matter inducing oxidative stress, inflammation, and xenobiotic responses in the respiratory system. The Optimizing Air Safety in Indoor Spaces (OASIS) project applies an innovative integrated framework combining biotag-based droplet mapping, real-time monitoring of indoor air pollutants and environmental parameters, with the direct exposure of air–liquid interface-grown human bronchial epithelial cells (BEAS-2B) using the portable Cultex®-RFS system. This multidisciplinary approach links aerosol dynamics, spatial dispersion, and event-driven air quality variations with pathway-specific cellular responses in a complex indoor environment selected for the campaign at Rome Fiumicino International Airport.
Aerosol characterization includes gravimetric mass concentration of airborne Particulate Matter (PM10, PM2.5 and PM1), particle number size distribution, and black carbon (BC), measured using PM samplers, Optical Particle Counters, and multi-wavelength aethalometer, respectively. Indoor micro-meteorological parameters including temperature, pressure and humidity, were measured using reliable off-the-shelf sensors integrated into a cloud- and edge-based IoT platform, enabling identification of event-related indoor air quality degradation and assessment of the impacts of routine actions, such as opening/closing a door or window.
To track the movement and dispersion of droplets within the indoor space, an advanced technique based on identifiable genomic sequences (Biotag) was applied to the monitored indoor space. This revealed localized hotspots of droplet persistence and concentration near the Cultex exposure module, aerosol instruments, heating, ventilation and air conditioning (HVAC) outlets, indicating that airflow patterns and instrument-induced turbulence strongly influence inhalation exposure.
The toxicological response was characterised in BEAS-2B cells undergoing 24h exposure to the monitored indoor environment (for a total of 15 exposures over the period May-December 2025), and assessed by quantitative real-time PCR of genes involved in oxidative stress (HMOX1, NQO1, SOD1, SOD2, NFE2L2), xenobiotic response (AHR, CYP1A1, CYP1B1) and inflammation (IL-1β, IL-6, IL-8, IL-18, TNF-α, NLRP3). Pathway-specific biological indices were calculated as the mean standardized fold-change of genes within each pathway. Correlation analyses revealed PM size- and composition-dependent responses, with the xenobiotic response index positively associating with 0.25–0.50 µm particle number (Spearman ρ = 0.59, p = 0.024), PM2.5 mass (ρ = 0.66, p = 0.009), PM₁ mass (ρ = 0.61, p = 0.017), and black carbon (ρ = 0.57, p = 0.030). Oxidative stress and inflammatory indices exhibited more variable associations, suggesting preferential activation of xenobiotic pathways by fine, combustion-derived particles.
Overall, the OASIS project provides a comprehensive mechanistic understanding of indoor aerosol behaviour and related cellular responses, integrating aerosol dynamics, spatial dispersion and pathway-specific biological effects. The results show that indoor exposure patterns and biological responses are shaped not only by indoor sources and airflow regimes, but also by outdoor air pollution infiltrating the indoor environment, particularly fine and combustion-derived particles. These findings underscore the importance of integrated indoor–outdoor air quality monitoring and targeted mitigation strategies to protect occupational and public health in complex indoor environments, supporting timely, evidence-based interventions to promote healthier indoor conditions.
How to cite: Santoro, M., Pierdomenico, M., Caiazzo, L., De Silvestri, L., Scamarcia, A., Messeri, C., Dobriakova, L., Cuscito, F., Stracquadanio, M., La Torretta, T. M. G., Petralia, E., D’Elia, I., Pace, G., Spaziani, F., Proposito, M., Grollino, M. G., Piersanti, A., and Benassi, B.: Indoor aerosol dynamics, composition, and pathway-specific biological responses in human bronchial epithelial cells (BEAS-2B) at Rome Fiumicino International Airport (OASIS Project), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11284, https://doi.org/10.5194/egusphere-egu26-11284, 2026.
Indoor concentrations are consistently higher than outdoors for most VOCs due to indoor sources and limited ventilation. In Finland, outdoor VOC concentrations are low even in urban areas. However, sometimes outdoor air can be impacted by long-range transported (LRT) pollution and concentration levels of VOCs increase. Some of these VOCs also impact the indoor air. In this study we compared indoor-outdoor ratios of VOCs in different kind of environments in Finland (Vantaa and Tampere) Czech Republic (Prague) and Germany (Düsseldorf).
Carbopack B tubes were collected at five different locations, both indoors and outdoors; two daycare centers in Tampere, office in Vantaa, office in Düsseldorf and a high school in Prague. In Vantaa, an online thermal desorption–gas chromatography–mass spectrometry (TD-GC-MS) system was additionally employed to measure indoor and outdoor air with a time resolution of 2 hours over the two-week period.
During the Vantaa campaign with more intensive online VOC measurements a LRT event occurred providing an opportunity to investigate its impact on indoor air quality. For certain compounds, such as benzene, which is not effectively removed by building ventilation, a clear correlation was observed: as outdoor concentrations increased, indoor concentrations rose accordingly, closely matching the outdoor levels. Up to four times higher concentrations were measured both indoors and outdoors during the event. Benzene is a known carcinogenic and regulated by the EU. Similar levels in indoor and outdoor air were also observed in passive samples in all locations for benzene and tetrachloromethane indicating that the main source is in outdoor air. For most other compounds higher indoor air levels were detected. Especially for monoterpenes (α-pinene, 3Δ-carene and limonene) and octane clearly higher concentrations were measured in indoor air indicating strong indoor sources.
How to cite: Tykkä, T., Barreira, L., Li, D., Harni, S., Salo, L., Silvonen, V., Elsayed, M., Säämänen, A., Rönkkö, T., Timonen, H., and Hellén, H.: Outdoor–Indoor VOC Dynamics: Insights from multi-site measurements and impacts of long-range transport on indoor air quality, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11905, https://doi.org/10.5194/egusphere-egu26-11905, 2026.
In a rapidly changing world characterized by increasing urbanization and climate change, urban air quality monitoring is essential for advancing fundamental process understanding, assessing environmental impacts, understanding human exposure to air pollution, and supporting evidence-based mitigation strategies in densely populated areas.
The TROPOS Institute has a long-standing track record in developing and applying mobile measurement systems for the comprehensive characterization of aerosol particle properties, including particulate matter (PM), particle number size distributions, and black carbon (BC), which are key indicators of urban air quality. The institute’s expertise spans from hardware design and sensor integration to laboratory-based calibration and long-term quality assurance. Building on these mobile “backpack” platforms and leveraging state-of-the-art low-cost sensor technology, further miniaturized sensor packages have been developed for different indoor and outdoor applications in scientific, as well as engagement and educational projects.
These activities represent a continuous and iterative development process, with systems being regularly adapted to emerging scientific needs and technological advances. A major emphasis is placed on the development of scalable data infrastructures aligned with Internet-of-Things (IoT) concepts. This includes the implementation of MQTT-based communication protocols and the integration of SQL-based database solutions for reliable data storage, management, and analysis. As a result, these developments enable real-time data analysis and facilitate deployment in sensor networks as key improvements.
The developed instruments are applied across a wide range of interdisciplinary scientific contexts, including local and regional atmospheric studies, large-scale European research projects, but also education and knowledge transfer activities. They support high-resolution, spatiotemporal observations of particulate air quality in diverse urban and indoor environments, providing robust tools for both scientific research and practical applications. As an example, modular low-cost instruments combined with an innovative interactive online platform were successfully applied in the collaborative educational project EngageMINT, in which more than 150 young participants measured air quality parameters and were engaged for environmental topics together with scientists. Furthermore, 15 innovative and very user-friendly devices, named AQBIE (Air Quality Beacon and Immission Evaluator), were developed and applied for several months in a different study exploring indoor air quality to capture seasonal effects of air pollution, mainly the impact of winter biomass burning.
How to cite: Voigtländer, J., Förster, J.-D., Cuesta, A., Düsing, S., Wiesner, A., and Pöhlker, M.: Mobile and Low-Cost Measurement Systems for Indoor and Outdoor Urban Air Quality Characterization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18406, https://doi.org/10.5194/egusphere-egu26-18406, 2026.
Assessing the impact of indoor volatile organic compound (VOC) sources on outdoor concentrations remains challenging due to their variability, rapid dispersion, and chemical reactions in the atmosphere. Mobile monitoring can address these challenges by providing spatial and temporal resolution of localized emission sources. In this study, we developed a new approach to characterize the impact of indoor emissions on outdoor air quality using mobile measurements. We used geographic information to identify the locations of hundreds of individual source types in Bradford, England, including restaurants, beauty salons, and automobile repair shops. For each source type, we modeled the potential hourly contribution using an advanced Gaussian plume modeling system across approximately 57 hours of mobile measurements. The outcome is a single source factor for each latitude-longitude coordinate at each hour of the measurement campaign, representing the influential level of each source type. We then applied K-means clustering to group source factors based on their spatial distributions and influence levels, and analyzed their relationship with the incremental concentrations of VOCs and NOx using a generalized additive model. Several previously identified key tracer compounds showed strong correlations with specific source factors. These include m/z 102 (tentatively assigned as butanone) with auto repair source factor, m/z 88 (acetone) with beauty salon source factor, and m/z 68 (isobaric compounds: isoprene and furan) with restaurant source factor. By clustering the source factor metric, we linked these emission sources to VOC concentrations at different locations along the mobile measurement route. Our method offers a new perspective on air quality monitoring by using source location information to inform the analysis of mobile VOC measurements, complementing existing source characterization approaches.
How to cite: Budisulistiorini, S. H., Moore, T., Shaw, M., Drysdale, W., Lee, J., and Carslaw, D.: Linking Indoor Commercial Source Emissions to Outdoor Volatile Organic Compounds Using Mobile Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20306, https://doi.org/10.5194/egusphere-egu26-20306, 2026.
Posters virtual: Mon, 4 May, 14:00–18:00 | vPoster spot 5
EGU26-18929 | ECS | Posters virtual | VPS2
Black crust as a passive sampler of urban pollution on the heritage buildings in Delhi, India: An analytical and modelling approachMon, 04 May, 14:51–14:54 (CEST) vPoster spot 5
Delhi is one of the most polluted megacities in the world. Since the ancient era, Delhi has been known for its rich heritage sites like the Red Fort, Humayun’s Tomb, and Qutub Minar, which are UNESCO World Heritage Sites. In this study, we investigate urban pollution-linked alterations at the heritage buildings (HBs) of Delhi, India, through a comparative characterization of deposited black crust (BC) and the underlying red sandstone (RS) collected from the exposed surfaces of the HBs. The BC on HBs can act as an integrative passive sampler of urban pollution, recording particulate matter, reactive gases (SOx/NOx), and associated heavy metal deposition. To achieve this objective, we applied a multi-analytical workflow combining X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDX), Fourier transform infrared spectroscopy (FTIR), carbonaceous analysis, and inductively coupled plasma mass spectrometry (ICP-MS) resolved phase assemblages, morphology, major-elemental composition profiles, and signatures of trace elements. The outcome suggests that the urban pollution sources, including vehicular emissions, road/construction/soil dust, industrial activity, and biomass burning, were identified as fingerprints of calcium (Ca) and sulfur (S) in the formed BC at the RS substrate. In this scenario, BC was enriched with Ca and S, which may cause sulfation phenomena to occur at the RS substrate as it contains low intrinsic Ca. Therefore, gypsum was identified as a dominant deteriorating agent, along with weddellite, bassanite, while carbon and heavy metals were also embedded in BC relative to the RS substrate. Additionally, in this work, a modeling approach is also utilized to assess the pollution dispersion impacts on the built HBs and linkage with BC deposition, which was employed using coupled WRF (Weather Research and Forecasting) and AERMOD (the American Meteorological Society/Environmental Protection Agency Regulatory Model) technique. Hence, considering these analytical and modelling approaches contributes to applying the site-specific conservation and preservation interventions in similar urban polluted environments.
How to cite: Kumar, G., Gurjar, B. R., Sharma, M., and Ojha, C. S. P.: Black crust as a passive sampler of urban pollution on the heritage buildings in Delhi, India: An analytical and modelling approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18929, https://doi.org/10.5194/egusphere-egu26-18929, 2026.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 5
EGU26-13522 | ECS | Posters virtual | VPS3
Influence of Vegetation Cover on Atmospheric CO2 Mixing Ratios in the São Paulo Metropolitan AreaTue, 05 May, 15:00–15:03 (CEST) vPoster spot 5
Urban vegetation plays a key role in modulating atmospheric carbon dioxide (CO2) in megacities. However, studies that explicitly quantify the effect of urban vegetation on CO2 remain scarce. This study investigates how vegetation cover affects CO2 mixing ratios in the Metropolitan Area of São Paulo (MASP) during 2020–2022, using four monitoring sites with contrasting vegetation fractions: Pico do Jaraguá (PJ; 59.75%), IAG (36.38%), ICESP (22.42%), and UNICID (10.42%). Vegetation cover was derived from Sentinel-2 Level-2A imagery using NDVI-based pixel classification, while CO2 observations were obtained from the METROCLIMA network and analyzed together with concurrent meteorological variables (temperature, humidity, and wind). The analysis comprised characterizing temporal variability and quantifying vegetation effects using regression models and probability distribution functions (PDFs). Clear seasonal and diurnal patterns were observed, with lower CO2 concentrations during summer and afternoon hours (420-414 ppm), and higher values during winter and nighttime periods (447-425 ppm). The greener and less urban site, PJ, exhibited the lowest and most stable CO2 levels, whereas the highly urban UNICID site showed the highest average mixing ratios. Elevated CO2 values at IAG (428.30 ppm in summer and 435.49 ppm in winter), despite substantial vegetation cover, suggest the influence of local emissions and boundary-layer dynamics, while relatively low CO2 values at ICESP (422.10 ppm in summer and 428.03 ppm in winter) likely reflect the elevated measurement height (~100 m a.g.l.), which favors regional-scale mixing and reduces sensitivity to local emission sources. NDVI revealed a bimodal phenological cycle (April–May and October–November), which was mirrored by CO2 variability at PJ. Among 132 fitted PDFs, the Normal Inverse Gaussian distribution best captured CO₂ variability, with greener sites showing flatter and more symmetric distributions and urban sites showing increased skewness and peakedness. Regression results indicate a significant vegetation signal: a 0.1 increase in NDVI was associated with CO2 reductions of ~3.92 ppm (PJ), 2.81 ppm (IAG), and 7.66 ppm (ICESP; likely conditional on site features), while no significant effect was detected at UNICID. Overall, urban vegetation influences both mean CO2 levels and their distributional characteristics, supporting the role of green infrastructure and phenology in urban carbon management.
Keywords: carbon dioxide, vegetation cover, linear regression, Metropolitan Area of São Paulo.
How to cite: Piscoya, J., Franco, M. A., and Andrade, M. D. F.: Influence of Vegetation Cover on Atmospheric CO2 Mixing Ratios in the São Paulo Metropolitan Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13522, https://doi.org/10.5194/egusphere-egu26-13522, 2026.
EGU26-2329 | ECS | Posters virtual | VPS3
Quantifying Urban Biogenic CO2 Fluxes in Greenhouse Gas Budgets: A Scalable Framework and Case StudyTue, 05 May, 15:27–15:30 (CEST) vPoster spot 5
To advance urban sustainability and achieve climate neutrality, cities are proposing various decarbonization strategies through nature-based solutions, including the implementation of green infrastructures (GI). Accurately quantifying urban biogenic CO2 exchange is essential for developing robust greenhouse gas budgets and for distinguishing biogenic from anthropogenic contributions to atmospheric CO2 in urban environments.
This study systematically reviews current approaches for estimating urban biogenic CO2 fluxes from both measurement- and model-based perspectives, evaluating their advantages, limitations, and applicability in urban contexts. Building on this review, we present an optimized framework to quantify urban biospheric CO2 fluxes using the Vegetation Photosynthesis and Respiration Model (VPRM) driven by a high-resolution land cover map and sentinel-2 satellite data. The framework is applied to the Metropolitan Area of Barcelona for April and December 2023 at a 10 m spatial resolution. Results show that evergreen needleleaf forests and croplands act as significant carbon sinks in April, with biogenic CO2 uptake offsetting approximately 10% of anthropogenic CO2 emissions in April and 4% in December. A cross-city comparison of urban vegetation cover, climatic conditions, and the biogenic offset effects indicates that increased vegetation cover does not necessarily translate into a proportionally stronger carbon sink. Nevertheless, this study proposes that a standardized framework for accounting for biogenic CO2 fluxes and uptake should be established to provide critical support for GI-based mitigation strategies in urban planning.
How to cite: Luo, Q., Segura-Barrero, R., Badia, A., Lauvaux, T., Li, J., Chen, J., and Villalba, G.: Quantifying Urban Biogenic CO2 Fluxes in Greenhouse Gas Budgets: A Scalable Framework and Case Study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2329, https://doi.org/10.5194/egusphere-egu26-2329, 2026.
