Abstracts should investigate the efficacy of climate mitigation and air pollution controls by linking them to impacts on air quality, climate, public health, or environmental justice. Of particular interest is research examining both intended outcomes and potential unintended consequences of emission reduction strategies—including unexpected changes in atmospheric chemical composition such as ozone increases or unforeseen climate impacts. Submissions that consider interactions between air quality, climate, health, and environmental justice, connecting the environmental and social sciences, are especially valued.
Submissions may employ a wide range of techniques including remote sensing, statistical and Earth-system modeling, ground-based observations, machine learning, and policy analysis. Contributions examining historical, current, and projected future changes in anthropogenic emissions and their atmospheric responses are encouraged, particularly those investigating how effectively policies can address poor air quality, climate change, health impacts, and environmental injustices. Novel research that identifies areas of policy need through advances in atmospheric science is also sought, ultimately supporting more holistic and effective strategies that balance pollution reduction with comprehensive understanding of atmospheric system responses.
NOTE: The session AS3.25 - Atmospheric composition responses to historical, current, and future changes in anthropogenic emissions has merged with this one.
Climate change research relies heavily on scenarios to explore possible futures, yet they are still too often used as purely emissions or temperature trajectories. In this presentation, I showcase scenario-based studies and conceptual advances with scenario frameworks to argue that scenarios can and should be used for joint assessments of climate impacts and the evolving capacities of societies to adapt and mitigate, while placing equity, vulnerability, and feasibility at the center.
I will first discuss scenarios as representations of alternative socioeconomic development pathways, not just climate outcomes. By systematically varying progress in areas such education, health, poverty reduction, governance, scenario analysis can illuminate how different “worlds” of human development translate into very different levels of climate risk, even under similar global warming levels. This work shows that indicators of adaptive capacity (i.e., societies' or individuals' ability to implement adaptation actions, which depends on access to resources and decision-making power) are key for assessing future impacts.
A second focus will be on using scenarios to assess the capacity of societies to undertake mitigation. This strand of research highlights how scenario frameworks can incorporate multiple dimensions of feasibility—social, economic, technological, institutional, and political—rather than treating all mitigation pathways as equally implementable. This allows us to ask where and under what conditions rapid emissions reductions are more feasible, where feasibility constraints are most binding, and how these constraints interact with development and equity.
A particular focus will be on incorporating gender inequality into scenario design and assessment. Drawing on studies that link gender gaps in education, labor force participation, political representation, and access to resources with vulnerability to climate extremes and air quality impacts, I will discuss how gendered power structures shape both the exposure and the capacity to respond.
Finally, I will outline a research agenda for the next generation of scenarios: ones that place societal capacity, equity, and feasibility on equal footing with emissions and temperature, and that are explicitly designed to inform debates on loss and damage, just transitions, climate finance, and development planning in a warming world.
How to cite: Andrijevic, M.: Equity and societal capacity for action in climate change scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14261, https://doi.org/10.5194/egusphere-egu26-14261, 2026.
With increasing urgency to mitigate air pollution, climate change, and racialized exposure disparities, decision-makers in the United States (US) are faced with three distinct challenges that arise from the same sources but are often managed separately. This is in part because traditional environmental policies are generally designed based on a forward simulation approach: formulating an idea, estimating emission-changes, and modeling the resulting changes to air pollution, climate mitigation, and environmental justice. This process is computationally inefficient for testing multiple strategies and poorly suited for optimizing outcomes that address multiple objectives. Here, we reverse this pipeline to derive emission-reduction pathways that represent the optimal “triple win” strategy for mitigating air pollution exposure, climate change, and exposure inequity across the contiguous US.
To do this, we build upon our novel receptor-oriented, Bayesian optimization method by incorporating an additional cost function that reweights reductions for other priorities. Our approach begins from an atmospheric inverse modeling framework, whereby we set an idealized concentration surface — meeting the US National Ambient Air Quality Standard for particulate matter (PM2.5) everywhere — as the target variable. Using an alternating gradient descent algorithm, we perturb this optimal solution to find the co- or triple-benefits associated with advancing climate or equity goals. We consider four optimal emission reduction scenarios representing distinct combinations of policy goals: PM2.5 Exposure Alone, Climate Priority, Equity Priority, and Triple Win. Our solutions are discretized in space, by precursor pollutant, and by the economic sector of emission.
Although all scenarios meet the PM2.5 standard, preliminary results suggest that meeting different combinations of goals requires attention to diverse locations, chemical species, and sectors. While the difference in total aggregate emissions reduction is small when comparing the PM2.5 Exposure Alone case with the other priorities, incorporating additional priorities up front enables the direct identification of distinct mitigation pathways in space and by sector (e.g., marine vessels are important for climate mitigation). We demonstrate how a non-optimal emission reduction pathway results in lesser or neutral air quality and climate benefits; however, the non-optimal reduction pathway can also result in significant harms in terms of environmental injustices.
This framework could have strong implications for how we think about the challenge of how environmental policy can advance action against compounding risks. Our approach provides a data-driven and scalable strategy for simultaneously achieving a triple win across exposure, climate, and equity goals.
How to cite: Koolik, L., Manchanda, C., Ünal, A., Fung, I. Y., Marshall, J. D., Morello-Frosch, R., Turner, A. J., Harley, R. A., and Apte, J. S.: A Bayesian Inverse Modeling Approach to Achieving Triple Wins in Air Quality, Climate, and Equity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13354, https://doi.org/10.5194/egusphere-egu26-13354, 2026.
Economic and social development in the Association of Southeast Asian Nations (ASEAN) region has led to increased greenhouse gas (GHG) emissions and elevated levels of fine particulate matter (PM2.5), contributing to global warming and severe health impacts. More than 75 percent of population (about 500 million) is exposed to PM2.5 levels above WHO guidelines with over 17 percent of urban residents experiencing concentrations above 35 µg/m3. Despite national and regional commitments on emission reductions, their current and future impacts on air quality and health remain poorly understood.
Using the Greenhouse Gases - Air Pollution Interactions and Synergies (GAINS) modelling framework, we projected CO2 and PM2.5 precursor emissions (primary PM2.5, SO2, NOX, NH3 and VOC), PM2.5 population exposure and associated premature mortality from 2020 to 2040 under different policy scenarios. We also identified the contributing sectors with the largest mitigation potential.
We estimate CO2 emissions of around 1,685 Mt in 2020 in the ASEAN region, and ASEAN-wide mean PM2.5 exposure levels around 15 µg/m3, leading to 210,000 premature deaths. In a counterfactual scenario without further mitigation measures beyond those implemented in 2015, CO2 emissions are projected to double and PM2.5 levels increase by 33 percent by 2040 and doubling the number of urban residents exposed to PM2.5 levels above 35 µg/m3.
While committed climate policies in power and transportation sectors achieve substantial CO2 emission reductions (25 percent by 2040), they lead only to marginal improvements on PM2.5 exposure and health co-benefits. The effective implementation of current legislation on air pollution on top of the climate measures reduces 2040 PM2.5 exposure to about 2020 levels, however, premature mortality still exceeds current levels due to a higher share of exposure to very high levels especially in cities and to population aging.
Ample potential exists to reduce PM2.5 exposure with existing technologies. Our maximum emission control scenario suggests that tightening air pollution controls could reduce health impacts by over two-thirds across ASEAN region, with largest emission reduction potential identified in the transport, industry and agriculture sectors.
These findings show that significant co-benefits of climate policies for air pollution related health impacts are not achieved without stringent measures beyond existing policies in the ASEAN region. The assessment lays the basis for developing regional strategies integrating climate and air pollution policies.
How to cite: Dedring, S., Brito, T., Gomez Sanabria, A., Kaltenegger, K., Kiesewetter, G., Klimont, Z., Purohit, P., Rafaj, P., Sander, R., and Wagner, F.: Health benefits of climate and air pollution policies in the ASEAN region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20525, https://doi.org/10.5194/egusphere-egu26-20525, 2026.
Severe air pollution across the Indo-Gangetic Plain (IGP) remains a critical environmental governance challenge in South Asia, with ambient fine particulate matter (PM₂.₅) concentrations persistently exceeding national and international air quality standards. Uttar Pradesh (UP), India’s most populous state, lies at the center of this highly interconnected region and experiences chronically elevated PM₂.₅ exposure driven by a combination of local emissions and substantial transboundary pollution. In such settings, effective air quality management requires policy-relevant analytical tools that integrate emissions, atmospheric transport, population exposure, and mitigation costs across administrative boundaries. This study applies an integrated assessment modeling framework to evaluate cost-effective policy pathways for reducing PM₂.₅ exposure in UP from a regional perspective.
We employ the GAINS-IGP (Greenhouse gas–Air pollution Interactions and Synergies) model to develop a region-specific, multi-sectoral emissions inventory for UP and the wider IGP for the base year 2020 and to project air quality outcomes to 2035. The model represents emission sources across the residential, industrial, transport, agriculture, power generation, and waste sectors, accounting for both primary PM₂.₅ emissions and key gaseous precursors (SO₂, NOₓ, NH₃, and NMVOCs). Atmospheric transport and secondary aerosol formation are simulated using reduced-form source–receptor relationships derived from chemical transport modeling, enabling estimation of population-weighted PM₂.₅ exposure at high spatial resolution. The GAINS optimization module is used to rank more than 300 emission control measures according to their marginal cost per unit reduction in population exposure.
Three policy-relevant scenarios are evaluated for 2035. The Current Legislation scenario assumes full implementation of all national and state regulations in force as of 2020. Frozen Legislation counterfactually illustrates air quality outcomes in the absence of policy advances beyond 2015, thereby isolating the contribution of recent regulatory efforts. A Coordinated Action scenario assesses the effects of harmonized implementation of additional, widely applied mitigation measures across the IGP. This scenario framework enables a systematic comparison of the effectiveness and cost-efficiency of state-level interventions versus regionally coordinated strategies.
Results indicate that while existing regulations partially decouple emissions from economic growth, they remain insufficient to achieve either India’s National Ambient Air Quality Standards (40 µg m⁻³) or the WHO Interim Target-1 (35 µg m⁻³) in UP. Approximately 44% of PM₂.₅ exposure in the base year originates from sources outside the state and from natural dust, while secondary PM₂.₅ formation contributes about 40% of total exposure. These structural characteristics substantially limit the effectiveness of unilateral mitigation policies. Cost-effectiveness analysis identifies high-impact measures across multiple sectors, including clean cooking transitions, improved fertilizer management, control of road and construction dust, elimination of open burning, industrial emission controls, and stricter vehicle standards. Achieving WHO-aligned targets at a reasonable cost, however, requires coordinated implementation of these measures across neighboring IGP states to reduce regional background pollution.
From a policy perspective, the findings highlight the importance of complementing city- and state-level clean air action plans with formal mechanisms for inter-state coordination. Integrated assessment modeling provides a transparent, quantitative basis for prioritizing measures, sequencing policies, and sharing mitigation efforts and benefits across jurisdictions in highly interconnected regions.
How to cite: Srivastava, P., Purohit, P., Schöpp, W., Wagner, F., Klimont, Z., Kiesewetter, G., Dey, S., Nygard, J., Tiwari, A., Sharma, M., and Amann, M.: Integrated assessment of cost-effective air quality mitigation pathways for Uttar Pradesh, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6350, https://doi.org/10.5194/egusphere-egu26-6350, 2026.
In recent decades, substantial progress has been made in reducing emissions of major regulated air pollutants across Europe. Nevertheless, despite overall improvements in air quality, current EU standards are still not met, with approximately 96% of the urban population exposed to unsafe levels of fine particulate matter. In response to the World Health Organization’s more stringent air quality guidelines, the EU has adopted a revised Ambient Air Quality Directive with more ambitious standards, which is scheduled to enter into force in 2030 ((EU) 2024/2881).
Robust Air Quality Monitoring Stations (AQMSs) are essential for evaluating the effectiveness of air quality legislation. These stations provide reliable, real-time data needed to track pollution levels, support warning systems, identify long-term trends, and assess whether implemented policies achieve their intended objectives. On the island of Crete, a joint Action Plan for Addressing Air Pollution in the Region of Crete (ACAP-Crete) has been developed through close collaboration between academic institutions-the University of Crete (UOC) and the Technical University of Crete (TUC)-and regional authorities, namely the Region of Crete. A network of AQMSs has been established that currently comprises five AQMSs: two newly established urban/traffic stations in the major cities of Heraklion and Chania; two urban background stations (one newly established at Voutes-UOC and the Akrotiri station operated by TUC); and one regional background station (the Finokalia station operated by UOC). Three additional stations are planned to be established by 2026. The ACAP-Crete network is complemented by the development of low-cost sensor networks across the island.
In anticipation of the requirements of Directive (EU) 2024/2881, the ACAP-Crete network is preparing to monitor newly regulated pollutants, including Black Carbon (BC), Ultrafine Particles (UFP), ammonia (NH₃), as well as the chemical composition of PM₁. Meanwhile, the transport sector on the island is undergoing rapid transformation due to the construction of a new international airport and the island’s primary motorway. These developments are expected to substantially alter air pollutant emission patterns and their associated impacts, thereby increasing the need for comprehensive and adaptive air quality monitoring. ACAP-Crete contributes to transparency and public awareness by making air quality data accessible to both citizens and decision-makers. The official web platform (airquality.crete.gov.gr) was recently launched to support this objective.
Overall, the AQMS network on Crete represents a successful example of cooperation between academia and regional authorities, providing a distributed air quality monitoring infrastructure that addresses current challenges while proactively preparing for future regulatory and environmental requirements.
Financial support from Region of Crete through the project “Action Plan for Addressing Air Pollution in the Region of Crete” is greatly acknowledged. We acknowledge support by Horizon Europe project Net4Cities Contract No. 101138405
How to cite: Kalivitis, N., Kozonaki, P., Stergiou, E., Papoutsidaki, K., Tavernaraki, K., Tsagkaraki, M., Kouvarakis, G., Mihalopoulos, N., Chatoutsidou, S.-E., Chalvatzaki, E., Lazaridis, M., Kargaki, E., Kandilogiannaki, M., and Kanakidou, M.: Air Quality Management on the island of Crete: A Collaborative Initiative Between Academia and Regional Authorities , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10562, https://doi.org/10.5194/egusphere-egu26-10562, 2026.
Emission controls in Europe have substantially reduced SOx and NOx but left NH3 largely unchanged. This imbalance between acidic and basic species may shift aerosol acidity and its impacts, including toxicity, particulate matter (PM) composition, and the deposition of reactive nitrogen (Nr). The atmospheric deposition of Nr plays a critical role in ecosystem productivity and PM formation, with impacts that vary across spatial and temporal scales.
In this study, long-term observations (2008–2024) of atmospheric gases and aerosols from Swiss monitoring sites ware analyzed to assess changes under current emission reductions. Aerosol pH was estimated using the ISORROPIA-lite thermodynamic model1 and interpreted using SHapley Additive exPlanations (SHAP) to quantify key drivers. Annual mean aerosol pH shows a slight increasing trend, with consistently lower values in summer than in winter. SHAP results indicate that temperature controls seasonal pH variability at agricultural sites, whereas total ammonia (NH3T) dominates at the semi-alpine site.
Dry deposition regimes of HNO3 and NH3 were investigated in relation to aerosol liquid water content and acidity following the approach of Nenes et al. (2021).2 The findings indicate that NH3 deposition is rapid across both the lowland and Alpine regions, suggesting localized nitrogen burdens near emission sources. In contrast, PM has become increasingly insensitive to NH3 and more sensitive to HNO3, particularly in the agricultural sites. These results highlight that, although HNO3 precursor controls have effectively reduced PM pollution without the need for NH3 reductions, evermore significant ecological concerns remain from a lack of NH3 control. This underscores the need for coordinated reductions in both NOx and NH3 emissions.
References:
1 Kakavas, S., Pandis, S. N., and Nenes, A.: ISORROPIA-Lite: A Comprehensive Atmospheric Aerosol Thermodynamics Module for Earth System Models, Tellus B: Chemical and Physical Meteorology, 74, DOI: 10.16993/tellusb.33, 2022.
2 Nenes, A., Pandis, S. N., Kanakidou, M., Russell, A. G., Song, S., Vasilakos, P., and Weber, R. J.: Aerosol acidity and liquid water content regulate the dry deposition of inorganic reactive nitrogen, Atmospheric Chemistry and Physics, 21, 6023–6033 DOI:10.5194/acp-21-6023-2021, 2021.
How to cite: Zhang, J., Waseem, A., Baccarini, A., Kakavas, S., Hüglin, C., and Nenes, A.: Historical Changes and Drivers of Aerosol Acidity in Switzerland under emission reduction and its implication of regulation policies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18181, https://doi.org/10.5194/egusphere-egu26-18181, 2026.
Fine particulate matter (PM2.5) remains the UK's most harmful air pollutant, contributing to approximately 29,000 premature deaths annually. This study investigates the drivers of recent UK PM2.5 improvements, with particular focus on the role of European transboundary pollution and atmospheric chemistry controlling secondary inorganic aerosol formation.
Analysis of UK Automatic Urban and Rural Network (AURN) monitoring data from 2016-2024 demonstrates a 25% reduction in annual average PM2.5 concentrations, with a pronounced step-change across 2019 to 2020 that has been sustained through 2024. In 2024, 98.6% of monitoring sites achieved the UK's 2040 target of 10 μg/m³, compared to just 60.5% in 2019. Wind sector analysis demonstrates that the highest PM2.5 concentrations and largest reductions are associated with easterly and south-easterly air masses originating from continental Europe, with median concentrations under easterly flow declining by approximately 5 μg/m³ between the 2016-2019 and 2020-2024 periods.
To quantify regional source contributions, we employed Simplified Quantitative Transport Bias Analysis (SQTBA) using HYSPLIT 72-hour back-trajectories generated every 3 hours at 11 urban and rural background sites across the UK. This approach accounts for meteorological transport and dispersion effects on observed concentrations. Results indicate that the highest PM2.5 concentrations are associated with air masses from central and eastern Europe, particularly Germany, Belgium, Netherlands and Poland. Comparison between 2016-2019 and 2020-2024 periods reveals that the largest reductions in PM2.5 are associated with these same European source regions, particularly during winter and spring when secondary inorganic aerosol formation is most efficient. European contributions to UK PM2.5 declined from approximately 2 μg/m³ to 1 μg/m³ between the two periods, representing a 50% reduction in the transboundary component.
Measurements from UK rural monitoring networks (NAMN, AGANet) and high-temporal-resolution supersites demonstrate that ammonium nitrate concentrations have declined by 44-54% since 2016, closely tracking observed PM2.5 reductions. Thermodynamic modeling using ISORROPIA-II at two contrasting UK sites highlights that ammonium-nitrate formation throughout the study period is “NOx limited”, meaning ammonium-nitrate concentrations are more sensitive to changes in NOx than ammonia. This regime means that NOx emission reductions associated with COVID-19 and vehicle fleet turnover will have had a pronounced effect on ammonium-nitrate in the UK and Europe.
This work suggests that recent UK PM2.5 improvements result from both domestic emission controls and reductions in transboundary sources from Europe. Due to ammonium-nitrates sensitivity to NOx over ammonia, NOx controls emerge as the primary driver of the recent PM2.5 reductions observed in the UK. Overall, this highlights the benefits of NOx emissions reductions on human health.
How to cite: Bryant, D. J., Lewis, A., and Moller, S.: Recent reductions in UK PM2.5: The role of NO2 and transboundary sources, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3398, https://doi.org/10.5194/egusphere-egu26-3398, 2026.
Over the last two decades there have been diverse variabilities and trends in anthropogenic, pyrogenic, and biogenic emissions, resulting in varied responses of net ozone production rates (PO₃) to their precursors. A quantitative understanding of the underlying ozone precursor sources and the extent to which they influence PO₃ typically requires running computationally demanding chemical transport models, often constrained by satellite observations, under various modeling scenarios.
Instead, we provide a much more efficient approach to predicting PO₃ using a deep neural network trained on more than 6 million observationally constrained data points collected from suborbital atmospheric composition missions. The parameterization meaningfully captures the non-linear relationships between O₃-NOX-VOC, as well as photolysis rates and water vapor. The parameterization inputs are constrained by various datasets including reanalysis models, ground remote sensing, TROPOMI and OMI retrievals, enabling us to provide a long-term record of global net ozone production rates along with magnitude-dependent sensitivity maps that advance beyond the conventionally binary maps (i.e., NOX-sensitive or VOC-sensitive) obtained from ozone indicators such HCHO/NO₂.
We reveal predominantly positive trends in PO₃ over Asia and the Middle East (>30% relative to 2005) and negative trends across the eastern U.S., Europe, and parts of Africa during 2005-2019, based on stable long-term records from OMI. We demonstrate how rapid evolution of heat waves can substantially increase PO₃ and its sensitivity to NOₓ and VOC. Our high-resolution TROPOMI-based product reveals high locally-produced ozone in less-documented regions such as Johannesburg (South Africa), Rio de Janeiro (Brazil), São Paulo (Brazil), Santiago (Chile), Hanoi (Vietnam), Cairo (Egypt), and Tehran (Iran). This product, along with a comprehensive error budget, is freely available to our community (https://www.ozonerates.space)
How to cite: Souri, A., Gonzalez Abad, G., Duncan, B., and Oman, L.: Two Decades from Space: Satellite-Constrained Parameterization Delivers Computationally Efficient Global Ozone Production Rates and Sensitivity Records, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3172, https://doi.org/10.5194/egusphere-egu26-3172, 2026.
Nitrogen oxides (NOx) are key air pollutants that directly affect health and are precursors of health-harming fine particulate matter (PM2.5) and ozone. China has implemented stringent emission control measures over the past decades, leading to significant declines in air pollution. To further improve air quality and protect public health, more precise and timely tools are needed for pinpointing emission sources and assessing changes in emissions. While bottom-up emission inventories are essential, they often suffer from reporting lags, coarse resolutions, and potential systematic biases. Here we use satellite NO2 observations from the TROPOspheric Monitoring Instrument (TROPOMI), ERA5 meteorological reanalysis products and a divergence-flux method to derive high-resolution (0.025° × 0.025°) NOx emissions across China in 2019-2024. We independently evaluate bottom-up emission inventories, identify emission sources, and report on emission trends in China. Our top-down estimates show good spatial correlations (r ≥ 0.7) with widely-used national and global bottom-up inventories, but there is a systematic underestimation in bottom-up emissions (~60% at the city level and ~70% at the provincial level). Top-down emission estimates effectively pinpoint large point sources (e.g., industrial clusters and ports) that are either missing or underrepresented in bottom-up emission invntories. The 2019-2024 trend analysis shows a significant decline in NOx emissions across many of China's populated and industrialized regions, despite increases in some rapidly developing areas. Currently underway is the use of our top-down emission estimates to improve air pollution modeling and enable more accurate health burden assessments in China. Our results will also enhance the understanding of regional air quality and atmospheric chemistry.
How to cite: Lu, G., He, Y., Baldo, C., Li, Y., Dong, J., Zhang, Q., Chen, L., Chen, H., Chen, G., Li, J., Yang, Y., Zhao, J., Huang, Y., Wang, Z., Fang, L., Zhang, L., and Ma, P.: Estimating high-resolution top-down nitrogen oxides emissions for improving air quality and public health in China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1055, https://doi.org/10.5194/egusphere-egu26-1055, 2026.
The CAMS-GLOB-ANT global emissions inventory, developed within the Copernicus Atmosphere Monitoring Service (CAMS) framework, provides monthly emissions for 36 chemical species, including CO, NOx, SO₂, NMVOC, NH₃, black carbon (BC), organic carbon (OC), CO₂, CH₄, N2O, and several individual VOCs, at a spatial resolution of 0.1° × 0.1° for the period 2000–2026. Alongside the officially released v6.2 dataset, which is used in the CAMS global air pollution forecasting system, a so-called mosaic emissions inventory is constructed. This mosaic product integrates official regional emission datasets based on nationally reported data for Europe, the United States, and China with the CAMS-GLOB-ANT global inventory. The resulting M1.0 mosaic inventory is being further enhanced through the incorporation of the PAPILA dataset, which provides a regional inventory of reactive gases for selected countries in South America.
In this study, we first intercompare the CAMS-GLOB-ANT v6.2 and M1.0 inventories and highlight the importance of refining global datasets with locally derived information to improve the accuracy of emission estimates, their temporal trends, and ultimately the performance of air quality models. We then evaluate both inventories against other available global and regional emission datasets. Finally, we conduct an in-depth assessment by examining discrepancies among existing inventories in terms of emission magnitude, spatial distribution, and temporal evolution. This assessment aims to identify species, sectors, and regions where emissions are robustly characterized, as well as those where substantial uncertainties remain.
How to cite: Bouarar, I., Granier, C., Denier van der Gon, H., Doumbia, T., Guevara, M., Jalkanen, J.-P., Kuenen, J., Majamäki, E., Zilbermann, N., and Brasseur, G.: Refining the CAMS Global Anthropogenic Emissions Inventory with Regional Datasets: Advances in the Mosaic Approach and Remaining Uncertainties, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9863, https://doi.org/10.5194/egusphere-egu26-9863, 2026.
The EU’s CATALYSE project (Climate Action to Advance Healthy Societies in Europe) aims to close the knowledge-to-action gap concerning environmental hazards linked to climate change and their effects on human health in Europe. In doing so, CATALYSE will fortify the science-to-policy interface by providing actionable policy scenarios for Europe for the coming decades. Four such policy scenarios for Europe (spanning 2020 to 2050) have been developed under CATALYSE, each with differing assumptions concerning energy use, agricultural practices, and air quality controls and policies: [1] a business-as-usual Reference Scenario, [2] a Green Deal Scenario, which incorporates the climate targets of the EU's Green Deal, [3] a Beyond Green Deal Scenario, which adds behavioural change policies associated with buildings, transport, and food sectors, and [4] a Beyond Green Deal - 90% Optimization Scenario, which adds enhanced end-of-pipe air pollution control measures. Each of the four scenarios results in differing PM2.5 -precursor emissions between 2020 and 2050.
We have implemented the emissions output from the four CATALYSE scenarios as input in the EMAC atmospheric model (Jöckel et al. 2006), simulating the years 2020, 2030, 2040, and 2050, in order to evaluate each scenario’s impact on PM2.5 concentrations in Europe specifically. We estimate the European mortality burden from these PM2.5 concentrations in each scenario across the coming decades using a suite of exposure response functions. With the FUSION global exposure response function (Burnett et al. 2022), we find that compared to the Reference scenario, annual mortality due to PM2.5 in Europe in the Green Deal scenario is reduced by more than 20,000 deaths in 2030, 30,000 deaths in 2040, and almost 40,000 deaths in 2050. In the more ambitious policy scenarios, those numbers are enhanced by up to a factor of two. Using the European ELAPSE exposure response function (Strak et a. 2021), the Green Deal scenario saves over 50,000, 80,000, and 90,000 lives in 2030, 2040, and 2050, respectively, with the more ambitious policy scenarios once again enhancing those numbers by up to a factor of two.
We conclude that even modest, realistic pollution-mitigation approaches in Europe can significantly reduce the mortality burden due to PM2.5 in the coming decades.
How to cite: Steffens, B., Pozzer, A., Tonne, C., and Lelieveld, J.: Updated PM2.5 Mortality Estimates for Europe in Coming Decades via the CATALYSE Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18901, https://doi.org/10.5194/egusphere-egu26-18901, 2026.
The 2021 update to the World Health Organization (WHO) Global Air Quality Guidelines (AQGs) for Fine Particulate Matter (PM2.5) presents ambitious targets that may not be achievable worldwide by 2030 and beyond. Regions influenced by biogenic sources, hard-to-abate sectors, or unique orographic and meteorological conditions may face persistent challenges to meet healthy targets. This research aims to evaluate the feasibility of the WHO’s AQGs for PM2.5 on a global scale based on recent historical data, complementing evidence from simulations. Through a comprehensive review of the existing literature and analysis of recent data, we use a variety of methods to show that natural sources and background concentration levels of PM2.5 constitute a significant share of overall concentrations and a source of inequality in exposure. Our study includes reanalysis data, high-resolution empirical estimates, and measurements from ground-level monitoring stations around the world. Using 1-km data we analyze inequality in exposure to air pollution across age, gender and income. We find that the recommended AQGs are widely exceeded globally, and show substantial heterogeneity between regions. Exceedances are particularly pronounced in many parts of Asia and Africa, where populations are exposed to unhealthy PM2.5 levels for most of the year. In roughly a third of the analyzed areas, desert dust and sea salt aerosols alone cause exceedances of the guidelines, indicating that mitigation is not sufficient and adaptation is required. Globally, only a small share of the population currently breathes air within the recommended limits, yet we find that spatial resolution matters when assessing exposure. Income is the main source of inequality in exposure, while differences by age and gender are minimal when considering ambient air levels.
How to cite: Renna, S., Rodriguez-Pardo, C., and Aleluia Reis, L.: Is air pollution mitigation enough? When adaptation is needed to protect health, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1145, https://doi.org/10.5194/egusphere-egu26-1145, 2026.
Despite discernible improvements in ambient air quality across the European Union in recent years, income-based inequalities in exposure to fine particulate matter (PM2.5) have remained remarkably persistent. Populations residing in the most socioeconomically disadvantaged regions continue to experience disproportionately higher PM2.5 concentrations compared to those in the wealthiest areas. However, the spatial scales at which these disparities are generated and the structural mechanisms sustaining them remain insufficiently understood.
This study quantifies the PM2.5 exposure gap between the lowest and highest socioeconomic strata across Europe and decomposes this disparity across its constituent spatial scales. The analysis integrates satellite-derived annual mean PM2.5 concentrations from the Atmospheric Composition Analysis Group (V6.GL.02), high-resolution population distributions from the Global Human Settlement Layer (GHS-POP), and settlement typologies from the GHS Settlement Model (GHS-SMOD). These are combined with gridded GDP per capita adjusted for Purchasing Power Parity (PPP) to stratify the European population into socioeconomic quintiles. Europe-wide exposure disparities are then systematically partitioned using a sequential spatial decomposition framework.
This approach isolates three fundamental components of total inequality: (1) inter-country economic disparities, (2) the urban–rural divide, and (3) intra-urban socioeconomic segregation. By disentangling these spatial scales, the study identifies whether observed inequalities primarily arise from regional contrasts across Europe or from localized patterns of urban structure and socioeconomic segregation.
Quantitative results for the 2013–2022 period indicate that regional differences are the dominant contributor to PM2.5 exposure inequality across Europe. Mean concentrations in Southern Europe exceed those in Northern Europe by approximately 9 µgm-3 on avarage, while the lowest socioeconomic quintile experiences PM2.5 levels about 15–20% higher than the highest quintile. Urban–rural contrasts are comparatively smaller, on the order of 1–2 µgm-3.
The findings highlight the necessity of aligning air quality and equity-oriented policies with the spatial scales at which pollution-related inequalities are produced, providing a robust atmospheric science–based foundation for scale-appropriate policy design.
How to cite: Denizoğlu, M., Aydın, Y., and Ünal, A.: Spatial Decomposition of Socioeconomic Inequalities in PM2.5 Exposure Across Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14333, https://doi.org/10.5194/egusphere-egu26-14333, 2026.
Air pollution is a significant environmental risk for premature mortality and disease. Previous research has documented inequitable air pollution exposure and health outcomes among marginalized and biologically susceptible populations. Characterizing air pollution exposure levels is a key component of assessing public health risks to inform urban policies and planning decisions; however, traditional, residence-based approaches to exposure assessment can fail to capture real-world variability in exposure across space and time, and between households. In this work, we investigate the impact of considering mobility patterns and microenvironments on exposure variability across households.
In urban environments, air pollutant concentrations show strong spatial patterns with fine-scale heterogeneity across diverse microenvironments. For example, traffic-related air pollution (TRAP) often decays by approximately 50% within 150 meters of emission sources (e.g., major roads) and returns to the local background within 500 meters. Still, the decay is context-dependent, shaped by local meteorology and urban-modified flow. Indoor exposure differs further from outdoor concentrations, which are determined by factors such as indoor emissions, building characteristics, and air exchange rates. Individual routines also influence their exposure levels, as reflected in daily activity locations (origins/destinations), the travel trajectories between them, and mobility modes.
To better capture air pollution exposure and assess health risks by accounting for these sources of variability and uncertainty, our study utilizes hourly, 1-km resolution air pollution estimates (NO₂, PM₂.₅, and O₃) for Metro Vancouver, Canada, generated by the coupled WRF-CMAQ modelling system. The high temporal resolution allows us to assess health risks associated with both short- and long-term exposure to air pollution. Beyond assigning exposure based on residential location, the fine resolution enables us to characterize concentration variability across microenvironments and to link exposures with individuals’ daily time-activity patterns and commuting trajectories. There is a wide range of microenvironment types relevant to air pollution exposure. For example, the U.S. EPA’s Hazardous Air Pollutant Exposure Model defines 18 microenvironments within broader categories such as indoor, outdoor, and in-vehicle, including residences, offices, public transit, and transit-waiting areas. Air pollution exposure within these microenvironments can be estimated using inputs such as the penetration of outdoor pollutants indoors and proximity to emission sources.
As a next step to explore exposure disparities, we will estimate exposures using developed, narrative household archetypes that are grounded in residents' lived experiences. These archetypes are designed to capture intersecting marginalization and disadvantage, reflecting mobility inequities (e.g., barriers to travel, mode choice constraints, and differences in commuting routes).
Together, we will compare and discuss: (1) differences in exposure estimates and their associated uncertainties across modelling methods; and (2) exposure disparities across groups that may contribute to health inequities. We hypothesize that mobility-based approaches offer higher granularity and therefore better capture exposure variability across households and populations than residence-based approaches. We further expect larger exposure differences between households after explicitly accounting for time-activity patterns and travel modes. By evaluating exposures under alternative policy and planning scenarios, our findings can inform sustainable travel mode shift as well as land-use and transportation planning to reduce exposures and enhance environmental health benefits.
How to cite: Ren, S., Giang, A., Delbari, S. H., Bhalla, M., and Hosseini, V.: From residence-based to mobility-based exposure assessment: a comparison of urban air pollution exposure modelling approaches for environmental health equity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15281, https://doi.org/10.5194/egusphere-egu26-15281, 2026.
Poor air quality is one of the largest environmental threats to human health, with a broad range of pollutants contributing to air pollution. Of these, fine particulate matter, defined here as particles with an aerodynamic diameter of less than 2.5 micrometres (PM2.5), is especially important with respect to human health. Globally, exposure to ambient PM2.5 is estimated to cause 4.2 million early deaths a year (WHO, 2024) and in the UK 30,422-42,640 early deaths were attributable to ambient PM2.5 exposure in 2018 (Flower et al., 2025).
PM2.5 is emitted from a broad range of primary sources and secondary aerosol is formed in the atmosphere from gaseous precursors. In the UK wood smoke from domestic heating has been shown to be an important source of PM2.5 in urban areas, accounting for 20% of annual average PM2.5 mass and up to 50% of PM2.5 mass in the winter heating season (Srivastava et al., 2025). This has led to policy interventions designed to reduce the emission of PM2.5 from domestic combustion. To ensure policy is led by evidence, the source locations and communities exposed to PM2.5 from wood burning need to be better understood.
Here, the spatial distribution of PM2.5 from wood burning was investigated in the West Midlands, the third largest conurbation in the UK. Black carbon concentrations were determined using an aethalometer mounted in a car and the Aethalometer model (Sandradewi et al., 2008) was used to estimate PM2.5 from wood smoke in the winter heating season. Large spatial variations in PM2.5 from wood smoke were observed and combining these measurements with socio-economic data shows that deprived communities are exposed to the highest concentrations of PM2.5 from wood burning. However, once population density is considered the data suggest that emissions per household may be higher in less deprived areas.
References
Flower G, Schneider R., Exley K., Mitsakou C., Masselot P. and Gasparrini A.: Mortality impacts of long-term PM2.5 and NO2 exposure in Great Britain under national and international air quality limits. Atmospheric Pollution Research, https://doi.org/10.1016/j.apr.2025.102827
Sandradewi J., Prevot A.S.H., Szidat S., Perron N., Rami Alfarra M., Lanz V.A., Weingartner E., and Baltensperger U.: Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter, Environ. Sci. Technol., 42, 33163323, 2008
Srivastava D., Saksakulkrai S., Acton W.J.F., Rooney D.J., Hall J., Hou S., Wolstencroft M., Bartington S., Harrison R.M., Shi Z., Bloss W.J.: Comparative receptor modelling for the sources of fine particulate matter PM2.5 at urban sites in the UK, Atmos. Environ., 343, 2025
World Health Organisation (WHO): Ambient (Outdoor) Air Pollution, 2024. Available at: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health (Last accessed 18th Dec 2025)
How to cite: Acton, W. J., Srivastava, D., Hou, S., Wynn, T., Lalchandani, V., Dunn, L., Shi, Z., and Bloss, W.: Investigating inequalities in exposure to PM2.5 from wood burning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20384, https://doi.org/10.5194/egusphere-egu26-20384, 2026.
Air pollution, specifically PM2.5 (Particulate matter with a diameter ≤ 2.5 μm), is a leading environmental stressor, contributing to ~1.05 million premature deaths annually in India. Unlike other western regions of the world where higher population densities are concentrated in urban sprawls, India features a majority of its population (two-thirds) concentrated in non-urban (rural) regions. Studies have shown a comparable PM2.5-associated mortality in urban and rural regions at a national scale for India. The contributions of source sectors to regional mortality specifically in urban and non-urban regions, essential for effective policy interventions, are discussed here.
In this study, we performed district-level, source-sector specific PM2.5 attributable mortality analysis for urban and rural populations for India for the year 2019. We first performed a baseline (all-sector combined) and sectoral zero-out WRF-Chem simulations using the SMoG-India emission inventory, gap-filled with CEDS and GFED, for the year 2019 covering the South Asia Cordex Domain with a 27 km horizontal resolution. The sectoral runs were performed for agriculture, residential combustion, industry, energy, and transport sectors. For the mortality calculations, we utilized relative risk curves generated using Meta Regression Bayesian Regularized, trimmed (MR-BRT) splines cause-specific for 6 diseases, developed over baseline PM2.5 concentration; cause-specific baseline mortality rates (BMR) from IHME (https://ghdx.healthdata.org/); and gridded population from SEDAC, segregated into urban and rural grids using VIIRS nighttime light radiance datasets. We scaled the fraction of sectoral PM2.5 contributions with baseline mortality to determine the mortality of each source sector at the grid level.
Relying on a model simulated PM2.5, we estimate population-weighted mean PM2.5 exposure of 42.7 µg/m³ and related mortality of 1.08 million. Our findings suggest that total premature deaths from PM2.5 exposures in India’s rural population are approximately 2 times larger than those in the urban population (Figure 1), similar to previous work. However, contributing emission sectors in both geographies are significantly different. The residential combustion sector contributes the most, approximately 44% of total premature deaths, out of which ~29% are borne by the rural population. Much larger impacts from the residential and agricultural sectors are seen in rural populations. Interestingly, energy emissions (from thermal power plants) have more than twice the impact on rural than on urban populations, indicating a regional scale of impact from an interplay of sulphate chemistry and atmospheric transport. Industry and transport sector emissions have 1.2 times larger mortality in rural than urban populations, indicating their more local-scale impact in urban regions. Sectorally, interventions to reduce residential biomass fuel use can yield the largest health benefits in both the rural and urban populations across India. For energy and industry sectors, regulatory interventions are needed at central and state government levels, since these emissions too impact both rural and urban populations. There is an urgent need for air quality management beyond the city scales and for expansion of air quality monitoring to rural areas in India.
Figure 1. Source sector contribution to mortality in rural and urban population across India
How to cite: Tiwari, D., Balasubramanian, S., Maji, S., and Venkataraman, C.: Contrasting Sources of Air Pollution Exposure and Associated Mortality in Rural and Urban India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3168, https://doi.org/10.5194/egusphere-egu26-3168, 2026.
Post-combustion carbon capture and storage (CCS) can substantially reduce CO2 emissions from coal and natural gas combined cycle (NGCC) power plants before entering the atmosphere. Little is known about the maximum potential of CCS across U.S. thermoelectric power plants or the potential air pollution and resulting human health effects associated with its retrofit. Integrating CCS affects other air pollutant emissions as well. The flue gas must be adequately pretreated to remove air pollutants that react with solvents to cause losses, while solvents can break down and lead to ammonia (NH3) emissions. In this study, we explore the air pollution and CO2 emissions impacts of national-scale post-combustion CCS adoption at coal and NGCC plants in the U.S. using monoethanolamine (MEA) and CESAR1 as representative first- and second-generation solvents, respectively. We quantify the effects of CCS on human health using the InMAP Source-Receptor Matrix (ISRM), which transforms emissions of primary PM2.5 and precursors of secondary PM2.5 into total changes in concentrations. This analysis brings together four main components in an integrated assessment model: (1) power plant CCS retrofit scenarios for coal and NGCC plants, (2) grid mix and generation scenario modeling, (3) plant-level emissions changes, and (4) the quantification of human health and greenhouse gas (GHG) emissions impacts.
If CCS retrofits are only viable on newer facilities, 97% of NGCC plant emissions are addressable compared to only 27% of coal plant emissions. Potential human health benefits of CCS retrofits are concentrated at coal plants, where the net benefits of added flue gas pretreatment are substantial, regardless of solvent. NGCC plants, however, require NH3 emissions controls and/or modern solvents, as using MEA without NH3 emissions controls could increase net human health burdens fourfold. This study shows that post-combustion CCS using amine-based solvents can have human health co-benefits or co-burdens depending on the solvent choice, fuel type, existing flue gas concentration, and presence of NH3 emission controls. Further, we provide policy-relevant recommendations for achieving greenhouse gas reduction benefits while limiting air pollution-related human health effects.
How to cite: McNeil, W., Harley, R., Preble, C., and Scown, C.: Health Implications and Deployment Potential of Post-Combustion CCS in the U.S. Power Sector, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1765, https://doi.org/10.5194/egusphere-egu26-1765, 2026.
Heat–health risk assessment forms a cornerstone of climate-resilient urban planning and is essential for advancing the United Nations Sustainable Development Goals (SDGs 3, 11, 13, and 15). In this study, a hyperlocal, high-resolution analysis was carried out for Ahmedabad—one of India’s fastest-growing metropolitan regions with a population exceeding 8.2 million. Using the Weather Research and Forecasting (WRF) model, key meteorological variables including 2-m air temperature and relative humidity were simulated at an hourly timestep and 1 km × 1 km spatial resolution for an extreme-heat episode from 18 to 25 May 2024.
The Heat Index was computed for each grid cell and subsequently integrated with population density and vegetation scarcity (derived from satellite-based greenness indicators) to develop a Heat-Health Risk Index (HHRI). The HHRI was classified into five categories—very low (0–0.1), low (0.1–0.2), moderate (0.2–0.3), high (0.3–0.4), and very high (>0.4). A unique component of this study is the computation of occurrence frequency of each HHRI class at every grid cell across all heat-wave hours, generating the first spatially continuous temporal–risk map for the city at this granularity.
Results reveal that approximately 6% of Ahmedabad experienced very-high heat-health risk during 10–40% of all heat-wave hours, while about 17% of the city encountered high risk for 30–45% of the period. At the ward level, Khokhra, Khadia, Amraiwadi, and Bhaipura-Hatkeshwar emerged as persistent heat-stress hotspots, spending nearly 15% of the time in the very-high-risk category. Fifteen additional wards faced high or very-high risk for at least one-third of the event. In contrast, peri-urban wards such as Gota, Chandlodia, Chandkheda, Thaltej, and Bodakdev exhibited very-low risk for more than 90% of the period, attributed to lower population density and higher vegetation cover.
This hyperlocal heat-health risk framework provides actionable insights for strengthening Ahmedabad's Heat Action Plan. By revealing fine-scale spatial and temporal variations in vulnerability, the study offers a robust evidence base for targeted interventions, resource prioritisation, and long-term climate and public-health planning. The approach can be replicated for other Indian and global cities seeking data-driven strategies to build resilience against intensifying heatwaves.
keywords:Heat Health Risk Assessment, Urban Heat, Ahmedabad, WRF Model, Heat Action Plan, SDGs
How to cite: Patel, V., Kandya, A., Kela, S., Uphale, S., and Gadekar, K.: Urban Heat–Health Risk assessment over Ahmedabad city, India: A Hyperlocal approach using WRF Model and Satellite Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1203, https://doi.org/10.5194/egusphere-egu26-1203, 2026.
The combined impact of the urban heat island (UHI) and the urban pollutant island can increase the risk of respiratory and cardiovascular illness, in addition to heat stress, thereby elevating morbidity and mortality by intensifying vulnerability, particularly among population groups already facing social disadvantage.
This study develops a method to investigate co-exposure to summer heat and ultrafine particles (UFP, < 0.1 um) in Toronto using high-resolution datasets for temperature and air quality derived from spatially extensive monitoring campaigns conducted in 2022 and 2023. The temperature data is used to derive three indicators of thermal discomfort (Apparent Temperature, Discomfort Index, and a composite Hotspot Index), which are subsequently used to generate exposure surfaces using a Machine-Learning based land-use regression model. Similarly, the UFP data is used to generate a model and an exposure surface.
Heat and UFP exposure surfaces are combined and analyzed using a multivariate Local Indicators of Spatial Association (LISA) approach, to identify clusters where both burdens are simultaneously elevated. These co-exposure hotspots were then linked with four dimensions of the Ontario Marginalization Index to evaluate disparities across socioeconomic and ethnocultural population groups.
Results show that combined heat–pollution hotspots are concentrated in Toronto’s central and southern neighbourhoods, particularly along major traffic corridors, and exposure levels rise consistently from the least to the most marginalized areas. In the most marginalized areas, up to nearly 90% of residents live in High–High co-exposure zones. These findings show that areas with higher levels of social marginalization consistently have higher combined heat and air pollution exposure, meaning that residents of these neighbourhoods are more likely to experience multiple environmental stresses at the same time. The results provide actionable evidence to support climate and air-quality policy aimed at reducing environmental health inequities.
How to cite: Li, J., Ganji, A., Venuta, A., Llyod, M., Weichenthal, S., and Hatzopoulou, M.: Exploring inequalities in experiencing the double burden of thermal discomfort and ultrafine particle exposure across urban communities , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3196, https://doi.org/10.5194/egusphere-egu26-3196, 2026.
The ambient fine particle (PM2.5) pollution in China has declined over the past decade, as a consequence of stringent clean air actions from 2013 to 2023. The sustained policy interventions have not only reduced the magnitude of PM2.5 concentrations but also reshaped the source profile, i.e., the contribution from different emission sources. PM2.5 toxicity varies markedly across emission sources, complicating the identification of dominant contributors and the robust quantification of associated health risks. The existing health risk assessments tend to rely primarily on PM2.5 mass concentrations and therefore neglect toxicity differences by emission source. By contrast, oxidative potential (OP), which reflects the capacity of particles to induce oxidative stress, may provide a more mechanistically grounded metric for toxicity assessment. Here, we developed a method to estimate the OP of PM2.5 in China, integrating direct ambient sample measurements with the GEOS-Chem model simulations and satellite observations, enabling nationwide, long-term reconstruction of aerosol toxicity at high spatiotemporal resolution. Using population-weighted mean exposure estimate (i.e., PWM-PM2.5 concentrations and PWM-OP) as the exposure metric, we systematically track the evolution of PM2.5 toxicity across China under policy-driven changes in emission sources and air pollution situations. The preliminary results show that, PWM-PM2.5 between 2013 and 2023 declined from 62.8 to 33.9 μg m-3 (−46%). Over the same period, PWM-OP declined from 2.48 to 1.17 nmol min-1 m-3 (−53%). Reductions were primarily attributed to control of coal combustion, underscoring the importance of energy-structure transitions and pollution control in reducing population health risks. In contrast, meteorological variability exerted a comparatively minor influence on these improvements; over 2013-2023, meteorological changes increased PWM-PM2.5 by 0.4 μg m-3 and PWM-OP by 0.62 nmol min-1 m-3, only partially offsetting the benefits of emission reductions. Our findings suggest that air quality improvements cannot be understood solely through PM2.5 mass concentrations and that toxicity metrics can offer additional insights relevant to health. The future clean air policies need to shift from concentration-oriented targets to toxicity-oriented emission source control strategies, prioritizing the reduction of high-risk sources to achieve great health benefits.
Keywords: PM2.5; Oxidative potential; Policy-driven; Coal combustion; Health benefits
How to cite: Liu, J. and Zheng, B.: Oxidative potential of atmospheric fine particles in China from 2013 to 2023: trends, drivers, and mitigation implications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8796, https://doi.org/10.5194/egusphere-egu26-8796, 2026.
China is a global hotspot for reactive nitrogen (Nr) emissions driven by its large livestock sector, which contribute to air pollution, climate change, and biodiversity losses. Despite their importance, current emission inventory development efforts often address singular Nr species, lacking a comprehensive presentation of all Nr species together and their interconnected features. This may jeopardize China’s achievements of carbon neutrality and clean air. In this study, we developed a high-resolution (0.1° × 0.1°) inventory of monthly Nr emissions from livestock manure in China for 23 livestock typesfrom 2005 to 2022. Based on a unified dataset, our inventory provides detailed estimates of multiple emissions from livestock, including ammonia, nitrogen oxides, and nitrous oxide. The inventory can serve as a valuable resource for atmospheric modelling and support integrated nitrogen management strategies in response to China’s evolving agricultural landscape, facilitating future decision-making to tackle environmental challenges associated with the agriculture sector.
How to cite: Chen, Y., Zhao, Y., Zhang, L., Guo, Y., Zhou, M., Chen, L., Yan, Y., Li, T., Zhang, Y., Xu, Y., and Luo, B.: High-resolution inventories for Reactive Nitrogen Emissions fromChina’s livestock during 2005–2022, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-59, https://doi.org/10.5194/egusphere-egu26-59, 2026.
Volatile organic compounds (VOCs) are significant air pollutants emitted from both anthropogenic and biogenic sources, impacting atmospheric photochemical processes and human health. This study aimed to determine the variations and potential sources of VOCs concentration in ambient air across various land-use types, including urban, industrial, and background areas in Malaysia. It also evaluated the impact of VOCs on photochemical processes and assessed health risks. The concentrations of ∑30 VOCs were measured between January 2018 and December 2019 at ten continuous air quality monitoring (CAQM) stations operated by the Malaysian Department of Environment (DOE). The positive matrix factorisation (PMF) model was used to identify the VOCs source apportionment. The VOCs contributions to ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) were quantified. Non-carcinogenic and carcinogenic risks of specific VOCs species were assessed using the health risk assessments (HRA) for both children and adults. The results revealed the highest VOCs concentrations in urban areas (125 ± 116 µg m-3 at the S3 station), followed by industrial (112 ± 112 µg m-3 at the S4 station and 95.4 ± 87.1 µg m-3 at the S1 station), while the lowest concentrations were recorded at the background site (55.5 ± 65.4 µg m-3 at the S9 station). Fuel evaporation (28.5%) was the major contributor in both urban (S3 station) and industrial (S4 station) areas, whereas combustion and biogenic sources (29.7%) dominated in background areas (S9). For the VOCs photochemical reactivity, alkenes (182 µg m-3, 59.0%) and aromatics (79.8 µg m-3, 25.9%) had the highest mean contributions to ozone (O3)formation across all monitoring stations. Aromatic VOCs recorded the highest SOAFP levels at all stations, ranging from 351 µg m-3 (88.1%) to 2312 µg m-3 (96.7%). The hazard quotient (HQ) and hazard index (∑HI) for non-carcinogenic risk were below 1.00 for both children and adults. The excess lifetime cancer risk (ELCR) for adults was above the regulatory threshold of 1.00 × 10-⁶ at all monitoring stations, indicating potential carcinogenic risk due to benzene exposure. Given the limited research on VOCs in Malaysia, the outcomes of this study will be vital for informing nationwide policy and standards for ambient VOCs monitoring.
How to cite: Limi Hawari, N. S. S., Latif, M. T., Mohd Hanif, N., Othman, M., and Ashfold, M. J.: Linking Volatile Organic Compounds (VOCs) in the Ambient Air of Malaysia with its Sources, Environmental Impacts, and Potential Health Risks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1098, https://doi.org/10.5194/egusphere-egu26-1098, 2026.
Accurate assessment of HCFC-141b emission trends is critical for compliance with the Montreal Protocol and climate mitigation. However, substantial gaps persist between top-down and bottom-up estimates, and systematic methods for gridded emission calculation and validation remain lacking. To address these gaps, we refine the emission estimation methodology for polyurethane foams during the waste disposal stage and establish a framework for calculating and validating gridded HCFC-141b emissions based on emission factor method and NAME model. Using China as a case study, we develop and verify a gridded inventory during 2000-2024. Estimated cumulative emissions are 294.0 kt, 133.7 kt lower than the latest bottom-up estimate and align more closely with top-down emissions, narrowing the gap between the two methods to some extent. The refined method reduced the normalized maximum benefit between simulated and observed atmospheric concentrations, from -7.94% to -1.65%. China’s 2024 banks (560 kt) far exceed cumulative emission, indicating substantial future potential. Gridded results show emissions concentrated in eastern coastal regions. Under an accelerated phase-out scenario, cumulative HCFC-141b emissions during 2025-2060 could be reduced by 4,266.9 kt, equivalent to 469.4 kt CFC-11-eq and 3,336.7 Mt CO2-eq, underscoring the importance of early phase-out measures. This framework supports more accurate regional assessments of halogenated compound emissions and their environmental impacts.
How to cite: Wu, J., Wang, T., Zhang, D., Yao, B., Purohit, P., and Peng, L.: Improved bottom-up approach for estimating HCFC-141b emissions and reduction potential in China from 2000 to 2060, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2396, https://doi.org/10.5194/egusphere-egu26-2396, 2026.
Surface ozone has become a major air quality concern in Taiwan as particulate matter concentrations have declined, while climate warming is expected to intensify high-temperature and high-ozone compound events. These changes increase health risks and challenge the effectiveness of existing air pollution control strategies, highlighting the need for atmospheric science that directly informs climate adaptation planning.
This study integrates source-oriented ozone analyses and warming-scenario simulations to link ozone formation processes with policy-relevant adaptation needs in southern Taiwan, focusing on the Linyuan industrial region and surrounding townships. Source apportionment and ozone formation potential analyses indicate that highly reactive volatile organic compounds associated with petrochemical activities play a dominant role in ozone enhancement during high-temperature episodes, identifying clear targets for emission-oriented mitigation strategies.
To assess how climate change may alter air quality risks, ozone hazards were evaluated under baseline, +2 °C, and +4 °C warming scenarios. Results show a pronounced increase in the frequency and spatial extent of high-ozone hazard days under warming conditions, suggesting that climate change can amplify ozone exposure even under existing emission control frameworks.
Beyond hazard characterization, this study develops a spatially explicit ozone risk assessment framework that integrates hazard, exposure, and vulnerability components to support climate adaptation planning. Exposure indicators reflect local ventilation conditions, while vulnerability metrics incorporate demographic structure and healthcare accessibility. The analysis identifies emerging ozone risk hotspots, including Meinong and Yanpu townships, where elevated hazards coincide with higher exposure and limited adaptive capacity.
By translating atmospheric science results into both mitigation-oriented and adaptation-oriented policy options, this study demonstrates how integrated air quality and climate analyses can inform effective public health protection and climate adaptation strategies. The proposed framework provides a transferable approach for supporting evidence-based air quality adaptation planning in subtropical industrial regions.
How to cite: Hsieh, P.-Y., Shen, M.-H., and Tsai, I.-C.: From Surface Ozone Risk Assessment to Climate Adaptation-Oriented Air Quality Policy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2646, https://doi.org/10.5194/egusphere-egu26-2646, 2026.
We present a global assessment of excess mortality attributable to long-term exposure to fine particulate matter (PM2.5) over the period 2000–2021, using satellite-derived PM2.5 concentration estimates. Mortality burdens attributable to PM2.5 exposure are quantified for this period using the FUSION relative risk model for non-communicable diseases (NCDs) and lower respiratory infections (LRIs). We analyze global and regional trends in PM2.5 exposure and associated excess mortality and assess the contribution of key driving factors. By integrating population-based thresholds with gross domestic product (GDP) data, we examine disparities between rural and urban areas as well as between low- and high-income regions. Our findings reveal substantial cross-country heterogeneity in the mitigation of PM2.5-related health impacts and identify potential pathways for reducing pollution-induced mortality.
Funded by the European Union and the Swiss State Secretariat for Education, Research and Innovation (SERI). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, or the European Health and Digital Executive Agency (HADEA) or the SERI. Neither the European Union nor the granting authorities can be held responsible for them, MARKOPOLO project GA No:101156161.
How to cite: Georgoulias, A. K., Lelieveld, J., Pozzer, A., Steffens, B., Klingmüller, K., Akritidis, D., Alexandri, G., Zanis, P., and Sciare, J.: Particulate matter–related mortality in the 21st century: disparities between rural and urban areas and across income groups, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3054, https://doi.org/10.5194/egusphere-egu26-3054, 2026.
Exposure to fine particulate matter (PM2.5) is a major risk for human health. Over recent decades, air-quality standards have become progressively more stringent, reflecting growing evidence of PM2.5 as a public health concern. At the country level, differences in PM2.5 exposure experienced and caused by countries, combined with differences in economic and social characteristics, shape inequalities in exposure to air pollution. We exploit a set of roughly 180 global simulations with the ECHAM/MESSy2 Atmospheric Chemistry model (EMAC) for the period 2014–2019, in which anthropogenic emissions from each country are excluded to quantify country-to-country contributions to PM2.5 levels. Within this framework, we assess the role of domestic and transboundary anthropogenic pollution in shaping PM2.5 exposure at global and national scales under different air-quality standards. Combining the country-to-country air pollution exchanges with socioeconomic indicators, we aim to identify disparities in the way countries experience and shape exposure to PM2.5, thereby unraveling air pollution inequalities across nations
How to cite: Akritidis, D., Moellendorf, D., Georgoulias, A. K., and Pozzer, A.: Exposure to fine particulate matter and inequalities across countries , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4376, https://doi.org/10.5194/egusphere-egu26-4376, 2026.
Precipitation is an important mediator between the atmosphere and the Earth's surface. As a wet-only part of atmospheric deposition, it maintains transfer of water, nutrients and air pollutants into ecosystems. Precipitation chemistry reflects ongoing atmospheric processes (Seinfeld and Pandis, 2006), and given its importance, its composition is regularly observed and measured at global, regional and national scales.
This contribution presents long-term changes in precipitation chemistry observed within a nationwide monitoring network in the Czech Republic, which is run by the Czech Hydrometeorological Institute. Point-wise data from station measurements from 1990 to 2024 were analysed, and nationwide averages from stations with simultaneous major ion measurements were explored.
Our results clearly demonstrate significant changes over the past three decades, evident in the relative proportions of major pollutants such as sulphates, nitrates and ammonium ions. These changes (i) reveal substantial changes in atmospheric composition with respect to changing emission levels; (ii) suggest changes in atmospheric chemistry; and (iii) indicate potential impacts on ecosystems and the environment.
Changes in precipitation chemistry are driven by changes in the absolute amounts and relative proportions of pollutant emissions and ongoing climate change. Due to uneven reductions in SO₂ and NOx emissions, the relative proportions of SO₄²⁻, NO₃⁻ and NH₄⁺ in precipitation have changed. These changes are evident not only in the levels of individual pollutants, but also in the ratios of these pollutants over time.
Further detailed information can be found, for example, in Hůnová et al. (2024) and Hůnová and Škáchová (2025).
Hůnová, I., Brabec, M., Malý, M., 2024. Major ions in Central European precipitation: Insight into changes in NO3−/SO42−, NH4+/NO3− and NH4+/SO42− ratios over the last four decades. Chemosphere 349, 140986.
Hůnová, I., Škáchová, H., 2025. Chemické složení atmosférických srážek je indikátorem výrazných změn v našem ovzduší, Chemické listy, 119, 533–540.
Seinfeld, J.H., Pandis, S.N., 2006. Atmospheric Chemistry and Physics. From Air Pollution to Climate change. Second edition. John Wiley & Sons, Inc., Hoboken.
How to cite: Hunova, I.: Precipitation chemistry: Long-term Changes in Central Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4952, https://doi.org/10.5194/egusphere-egu26-4952, 2026.
Poor air quality (AQ) is one of the largest environmental stresses on human health. In the UK, poor AQ results in 28,000-36,000 premature deaths per year and annual socioeconomic costs of ~£20 billion. To help address this, the UK Met Office (UKMO) provides critical national daily AQ forecasts of key pollutants (e.g. ozone (O3), nitrogen dioxide (NO2) and aerosols) to provide the public and government bodies (e.g. Defra) with prior warning of hazardous AQ events.
To evaluate the skill of their forecast model (AQUM – Air Quality in the Unified Model), and to bias-correct the forecasts, the UKMO use AQ measurements from the UK Automated Urban and Rural Network (AURN) of surface sites. The AURN observations are used in the “Statistical Post Processing of Observations (SPPO)” step to correct the forecasts (known as “hybrid-forecasts”) before release. However, sparse surface monitoring sites are often unrepresentative of widespread pollution.
Satellite AQ data provides a powerful resource to help address this issue with daily UK spatial coverage, detection of pollution hotspots and transboundary pollution gradients. Therefore, this project described here (AIRSAT) aims to integrate key satellite AQ products (e.g. tropospheric NO2 & O3) into the UKMO’s SPPO framework to improve these “hybrid-forecasts”, thus benefiting the downstream users of this service.
Analysis of multiple satellite AQ products concludes that tropospheric column NO2 (TCNO2), total column ammonia (TCNH3) and lower (0-6 km) tropospheric column O3 (LTCO3) from the TROPOspheric Monitoring Instrument (TropOMI), the Cross-track Infrared Sounder (CrIS) and the Infrared Atmospheric Sounding Interferometer (IASI), respectively, are the most suitable datasets for UK AQ monitoring and for comparison with AQUM.
AQUM showed good agreement with TropOMI TCNO2 but has substantial (i.e. absolute model-satellite bias is greater than the satellite uncertainty) negative biases over London. Consistent with other studies, this indicates that the nitrogen oxide (NOx) emissions from the official bottom-up inventory (National Atmospheric Emissions Inventory – NAEI) are too low over London. Comparisons between AQUM and CrIS in summer indicate that the model substantially underestimates NH3 over broad rural regions of the UK. Primary NH3 emissions are linked to agricultural processes and the model biases co-locate with the regions, which is supported by surface model-observational comparisons. These findings are consistent with previous research but building on it taking account of key factors like satellite vertical sensitivities and errors.
Investigation of the 2-week air pollution episode (24th June – 7th July 2018) shows widespread enhancements in NO2 and O3 surface concentrations and satellite integrated columns. By using AQUM, O3 enhancements are detected throughout the lower-mid troposphere across the UK. This is a novel result as it confirms that IASI retrieved LTCO3 is detecting O3 originating from the surface / boundary layer (i.e. suitable for AQ applications) despite having peak measurement capabilities in the mid-troposphere.
Overall, I will present these results from the AIRSAT project (i.e. Work Package (WP) 1) and new developments in WP2 utilising TropOMI TCNO2 and AQUM to infer surface NO2 concentrations for evaluation of the modelled forecasts suitable for the SPPO approach.
How to cite: Pope, R. and Graham, A.: Integration of Earth Observation into the UK Met Office Air Quality Forecasting System, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5574, https://doi.org/10.5194/egusphere-egu26-5574, 2026.
Agricultural ammonia (NH3) emissions, primarily released from livestock waste and synthetic fertilizer application, are a major precursor of fine particulate matter (PM2.5), imposing considerable public health burdens worldwide. Although these emissions are strongly linked to socioeconomic factors and agricultural development pathways, a comprehensive mid-century assessment of air quality and health benefits under different agricultural futures has yet to be fully established. In this study, we scaled NH3 emissions from various crop and livestock species under three scenarios developed by the Food and Agriculture Organization: Business as Usual (BAU), Stratified Societies (SSS), and Toward Sustainability (TSS), using documented and projected agricultural data. PM2.5-attributable health outcomes were quantified via a hybrid approach integrating the GEOS-Chem High Performance (GCHP) model, machine learning bias correction, and the Global Exposure Mortality Model (GEMM). Results indicate that global NH3 emissions substantially increase under BAU and SSS (+50–51% relative to the 2012 baseline), but remain nearly stable under TSS, where growth in livestock emissions is offset by fertilizer phase-out. Global population-weighted PM2.5 concentrations are projected to rise by 1.2 μg m−3 under BAU and 1.3 μg m−3 under SSS, but decline by 1.0 μg m−3 under TSS. Under baseline conditions, PM2.5 is estimated to cause 4.3 million premature deaths annually. Projections suggest that premature deaths would rise by more than 80000 under BAU and SSS, affecting Europe, India, and East China in particular, where equitable development is essential to mitigate the future mortality. Although TSS – characterized by equal access to basic services, universal food availability, and widespread conservation – could reduce premature deaths by nearly 50000, increases are still expected in Sub-Saharan Africa due to elevated emissions and worsened PM2.5 air quality driven by population growth and economic development. Our findings underscore the need for further agricultural transformations – towards crops with higher nitrogen use efficiency, livestock with lower emission factors, and less meat-intensive diets – to prevent disproportionate public health burden. This scenario-based analysis highlights the benefits of sustainable agricultural pathways, demonstrating that strategies ensuring nutritious and sustainable food production can simultaneously improve air quality and reduce global mortality.
How to cite: Shek, S. Y. T., Tai, A. P. K., Chen, X., and Luo, B.: Mid-century Air Quality and Public Health Responses to Future Agricultural Ammonia Emission Pathways, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7495, https://doi.org/10.5194/egusphere-egu26-7495, 2026.
Atmospheric aerosols play a key role in air pollution and atmospheric chemistry, with important consequences for air quality and public health. Variations in aerosol loading influence heterogeneous chemistry by regulating the uptake of HO₂ radicals on particle surfaces; a reduction in aerosols weakens this sink, enhances NOx and OH concentrations, and consequently increases surface ozone. This study investigates the seasonal variability of PM₁₀ and aerosol surface area and their impact on surface ozone over India using the GEOS-Chem chemical transport model for 2018 and 2022, representing years with high and low simulated PM₁₀ concentrations, respectively. The results show pronounced seasonal variations in both PM₁₀ and aerosol surface area. During winter (DJF), elevated PM₁₀ and aerosol surface area are observed over the Indo-Gangetic Plain and western Central India, mainly driven by biomass burning and industrial activities, while coastal regions show relatively lower aerosol surface area. Aerosol surface area decreases during the pre-monsoon (MAM) and monsoon (JJAS) seasons, followed by an increase during the post-monsoon (ON) period. Enhanced aerosol surface area during winter and post-monsoon leads to stronger aerosol-induced HO₂ uptake, suppressing surface ozone by approximately 5–10 μg/m³ in 2022 compared to 2018. In contrast, during the monsoon season, the reduced aerosol surface area in 2022 results in an increase in surface ozone of about 5–7.5 μg/m³ relative to 2018. On average, this aerosol-driven enhancement in surface ozone can be mitigated by reducing anthropogenic NOx emissions by roughly 25–50%. These findings emphasise the importance of integrated air quality management strategies that jointly address aerosol levels, precursor emissions, and regional meteorological conditions to effectively control ozone pollution over India.
How to cite: Gopikrishnan, G. P., Westervelt, D. M., and Kuttippurath, J.: Regional Sensitivity of Ozone Formation to Emissions and Meteorology in India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8282, https://doi.org/10.5194/egusphere-egu26-8282, 2026.
Long‑lived halocarbons have been subject to progressive international regulation due to their significant impacts on stratospheric ozone depletion and climate forcing. Following the phase‑out of chlorofluorocarbons (CFCs) under the Montreal Protocol, hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs) were introduced as transitional and long‑term substitutes. While HCFCs are being phased out globally, legacy emissions still persist, and HFCs, despite their zero ozone‑depletion potential, have become a growing concern because of their high global warming potentials, prompting further controls under the Kigali Amendment.
Within this regulatory and scientific context, emissions of HFCs and HCFCs in East Asia have attracted substantial attention over the past decades. This region hosts some of the world’s most intensive production, consumption, and use of fluorinated refrigerants, with southeastern China in particular representing a major hotspot of anthropogenic activity. Previous studies have identified the Pearl River Delta (PRD) and Yangtze River Delta (YRD) as key source regions for multiple halocarbon species, making East Asia a focal area for evaluating emission trends, inventory accuracy, and policy effectiveness.
The Hong Kong University of Science and Technology (UST) atmospheric observatory plays a key role in monitoring halocarbon mole fractions across East Asia. Owing to its coastal location and favorable meteorological conditions, the site is sensitive to air masses originating from a broad swath of the region, including the highly developed areas of southeastern China such as the PRD and YRD. Leveraging continuous observations from the UST site together with background measurements, we applied a FLEXPART‑based Bayesian inversion framework to quantify emissions of HFC‑134a and HCFC‑142b over East Asia. This approach provides regional‑scale emission constraints that are directly relevant for assessing long‑lived halocarbon emissions under current control policies.
How to cite: Cao, X., Gu, D., and Chan, W. M.: Top-down Estimates of HFC-134a and HCFC-142b Emissions in East Asia in 2022 and 2023 Using a Bayesian Inversion Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8805, https://doi.org/10.5194/egusphere-egu26-8805, 2026.
To enable scientifically targeted reductions of atmospheric pollutant emissions, policymakers require robust quantification of the impacts of facility-specific emissions on air quality and associated health benefits. In this study, we couple the chemical transport model CMAQ with the atmospheric dispersion model CALPUFF to develop a grid-scale emission–concentration rapid response framework, termed the Air-quality Intervention for Source-Directed Emission Control Model (AISEC). Using this rapid response model, we conduct a comprehensive assessment of the health burdens attributable to point-source emissions from multiple sectors, such as power plants, across the North China Plain. The results reveal pronounced facility-level heterogeneity in air quality and health impacts in the region. This study provides a computationally efficient and policy-relevant tool for prioritizing emission control strategies based on facility-specific health or other benefits.
How to cite: Song, Q., Wang, S., and Zhao, B.: A Rapid-Response Model for Facility-Level Assessment of Air Pollution and Health Impacts , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16021, https://doi.org/10.5194/egusphere-egu26-16021, 2026.
Air pollution has become a serious problem in developing countries due to industrial growth, poor understanding of the atmospheric circulation, weakly planned land use, and weakly enforced air pollution regulation. As part of this, the location of industrial emission clusters frequently does not account for air mass transport, pollutant dispersion, and topographic considerations. This leads to increased regional air pollution; furthermore, regulation remains inadequately focused on urban planning challenges and environmental impact assessments to allow future emissions. Simpler regulatory methodologies usually do not consider regional atmospheric characteristics governed by meteorology, topography, and current pollution load. Ignoring the impact of complex meteorological and topographic features on industrial cluster location leads to an incomplete framework for air quality governance and management. There are two conceptual approaches to regional air pollution management from physical and regulatory / governance perspectives. First, the airshed is defined as a geographic area (also known as an air quality control region), where the air pollutant emissions impact a common group of receptors independent of the administrative / jurisdictional boundaries. Second, the air basin concept refers to a volume of atmosphere in a region within the boundary layer where an airflow phenomenon occurs with similar meteorological and topographic characteristics. The application of this concept in tropical regions is further complicated due to their unique characteristics: complex airflow dynamics, including ventilation, stagnation, recirculation, vertical mixing within the tropical atmospheric boundary layer (ABL), and deep moist convection phenomena. For this reasons, air basins are fundamentally dynamic, with spatial and seasonal variability that can be addressed using the assimilative capacity concept, i.e., the allowable pollutant load under acceptable ambient air concentrations (emissions limits). We argue that the air basin and airshed definitions are currently poorly founded on meteorological and physical region characteristics, particularly in the tropics. In addition, assimilative capacity daily and seasonal variations are usually ignored, and air ventilation maps are not considered as tools for environmental licensing and emissions permitting assessment. Framing air basins is essential to properly estimating assimilative capacity and environmental and land use policies, potentially applicable to tropics. Moreover, an integral definition of an air basin applied to the tropics would cement the basis for the development of appropriate air quality regulations, approval of emission permits, interjurisdictional coordination for mitigation of air pollutants in regions. These concepts will be discussed along with a case example in an inter-Andean in Colombia.
How to cite: Cely, J., González, C. M., Rueda-Saa, G., and Jimenez, R.: Revisiting the airshed concept in the tropics for assimilative capacity characterization. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16023, https://doi.org/10.5194/egusphere-egu26-16023, 2026.
Ambient PM2.5 exposure remains the most critical environmental risk to public health in India; however, exposure to PM2.5 species remains poorly quantified due to the absence of a systematic network for measuring PM2.5 composition. This has limited our understanding of the differential health impacts of PM2.5 species. Here, we developed a novel high-resolution (1-km x 1-km) dataset of concentrations of six aerosol species (BC, OC, sulfate, nitrate, ammonium, dust) and assessed exposure inequality by integrating sociodemographic data from the National Family Health Surveys (NFHS-4 and NFHS-5) across urban and rural India, focusing on gender and wealth.
We trained machine learning models to predict the mass fractions of six PM2.5 species derived from a chemical transport model (CTM), using four predictor variable types: (1) Multi-angle Imaging Spectro-Radiometer-retrieved size- and shape-segregated AODs, (2) sectoral emissions, (3) meteorology, and (4) geospatial variables. These predicted mass fractions were combined with satellite-derived PM2.5 data to estimate monthly mass concentrations across South Asia. The model shows robust performance against ground-based observations (R2 = 0.61; RMSE = 4.23 mg/m3).
Population-weighted exposure to BC, OC, sulfate, nitrate, ammonium, and dust in India for the NHFS-4 (NFHS-5) was estimated to be 4.22 (4.19), 10.51 (11.02), 5.99 (5.85), 6.97 (7.07), 5.65 (5.58), and 15.97 (16.40) mg/m3, respectively. Exposure was highest in low-SDI states (the Indo-Gangetic Plain and Central India), driven by persistent reliance on biomass and solid fuels. Middle-SDI states achieved the largest reductions in overall exposure from NHFS-4 to NHFS-5, likely due to high clean-fuel conversion rates. In these regions, the urban poor faced a disproportionate relative burden from OC exposure (Z-score of -1.001 in NFHS-5), suggesting that air quality improvements primarily benefited the wealthy. While relative disparities narrowed in urban clusters between the two survey rounds, they widened in rural clusters. Women in rural regions were consistently exposed to elevated levels of carbonaceous aerosols (BC and OC), highlighting the gendered impacts of residential air pollution. In high-SDI urban areas, the relative disparity shifted from positive to negative. This shows that vulnerability patterns change as states progress to higher levels of development. These results underscore the dynamic nature of human exposure throughout economic changes. The study further emphasises the essential need for gender- and wealth-stratified exposure tracking to ensure that national clean air programs do not neglect disadvantaged people as they progress.
How to cite: Srivastava, S. and Dey, S.: Disparity in exposure to PM2.5 species in India reveals the importance of considering PM2.5 composition in epidemiology studies , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16418, https://doi.org/10.5194/egusphere-egu26-16418, 2026.
Every year in May, the north-west Indo-Gangetic Plain experiences its worst ozone pollution with ambient hourly ozone frequently exceeding 100 ppb. Till date however, a mechanistic study of the oxidant and radical chemistry during these periods has been lacking. Here using a novel in-situ dataset of measured ozone precursors, including isoprene and acetaldehyde and nitrogen oxides, we investigate three contrasting ambient ozone periods experienced in May 2023. While two periods had lower NOx (~10 ppb) but contrasting ozone levels of ~50 ppb (period I) and 90 ppb (period III), respectively, period II was impacted strongly by wheat residue-fire plumes and associated with high ambient average daytime ozone (~90 ppb) and higher NOx (~20 ppb). Using a detailed chemical box model, we investigated these three periods in terms of the Leighton ratio, total OH reactivity, radical concentrations and photo-chemically formed oxidation products for mechanistic insights. Furthermore, the ozone production regime and rates were investigated for all three periods. With climate change likely to increase regional temperatures, our results will also present insights on implications for ozone pollution with future climate change.
How to cite: Sinha, V., Awasthi, A., Mishra, S., Singh, R., Singh, G., Yadav, R. K., Varkrishna, M., and Kaur, C.: Investigation of factors that drive the extremely high summertime ozone pollution over the north-west Indo-Gangetic Plain using in-situ measurements and a chemical box model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16508, https://doi.org/10.5194/egusphere-egu26-16508, 2026.
Ultraviolet(UV; 100–400 nm) radiation represents the short-wavelength portion of the solar spectrum and poses significant risks to human health, including skin aging, erythema, and skin cancer. Because excessive UV exposure induces erythemal responses of the skin, the UV Index(UVI), derived from erythemally weighted UV irradiance(EUV), is widely used as a public health indicator to communicate UV-related risk levels. Accurate estimation of UVI is therefore essential for both environmental monitoring and public health applications.
In this study, we develop an empirical model to estimate UVI over South Korea using global horizontal irradiance(GHI) observations from the GK-2A geostationary satellite. The model incorporates key radiative and atmospheric parameters, including the clearness index derived from GK-2A GHI data, total ozone column, and solar zenith angle, in order to account for atmospheric attenuation processes and solar geometric effects governing surface UV radiation.
The GK-2A GHI–based UVI estimates are evaluated against satellite-derived UVI products from the Geostationary Environment Monitoring Spectrometer(GEMS) onboard the GK-2B satellite. The comparison reveals a strong agreement between the two datasets, with a correlation coefficient(R) of 0.95, demonstrating that the proposed UVI estimation algorithm based on GK-2A GHI is physically consistent with spectrally resolved UV observations from GEMS. This high level of consistency indicates that broadband solar radiation measurements can be effectively utilized to reproduce biologically relevant UV metrics.
These results highlight the potential of GHI-based UVI estimation as a robust complementary approach to conventional UV retrieval methods, particularly in regions with limited ground-based UV monitoring networks. Furthermore, the proposed framework enables high-resolution and continuous UVI monitoring, supporting applications in public health risk communication, climate studies, and operational UV exposure assessment. This study demonstrates that satellite-based GHI products can play a critical role in expanding the practical use of geostationary satellite observations for UV-related environmental and societal applications.
How to cite: Park, S., Kim, J., and Lee, Y. G.: Development of a UV Index Estimation Model Using Global Horizontal Irradiance from the GK-2A Satellite, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18243, https://doi.org/10.5194/egusphere-egu26-18243, 2026.
PM2.5 governance in Taiwan has largely emphasized macro-scale source control, while high-exposure micro-environments embedded in everyday life, such as temple incense burning, often lack actionable, comprehensible information for residents. This study examines the Jianguo Li Tudigong (Earth God) Temple in Yingge District, New Taipei City, as a community-scale “informational nudge” intervention: micro-sensors and a real-time air-quality dashboard were installed, complemented by two temple-festival environmental awareness campaigns to encourage voluntary incense-reduction without constraining religious practice.
We treat the two environmental awareness campaigns as intervention points and construct four monitoring periods (Periods 1–4) to enable pre- and post-comparisons under similar seasonal conditions, thereby reducing meteorological confounding. Measurement validity is strengthened through regular cross-calibration with reference-grade instruments and by subtracting the background PM2.5 from nearby regulatory stations to isolate local emissions attributable to on-site ritual activities. To account for fluctuations in visitor volume, donation income (incense-offering money) is used as a proxy for attendance and applied in normalization, helping distinguish behavioral change from simple crowd variation. Findings indicate an overall decline in PM2.5 following both environmental awareness campaigns, with the first intervention producing the largest reductions during peak visiting windows (9–11 a.m. and ~3 p.m.); the top 5% extreme concentrations decreased by 40-70 percent, demonstrating substantial mitigation of peak exposure risk. After the second campaign, the timing of high-concentration peaks shifted from the morning toward midday, consistent with behavioral responses, such as the temporal redistribution of visits to avoid higher-pollution hours.
Overall, the case provides empirical support for transparency-based green nudges as a culturally sensitive, low-cost, and replicable framework for improving air quality and reducing exposure risk in small-temple community settings.
How to cite: Chien, S.-S., Chen, W.-J., and Lin, C.-E.: Informational Green Nudges via Air-Quality Transparency: PM2.5 Monitoring, Environmental Awareness Campaigns, and Incense-Reduction Behavior at the Jianguo Li Tudigong Temple , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18807, https://doi.org/10.5194/egusphere-egu26-18807, 2026.
While air quality policy has traditionally focused on individual pollutants, in a real-world context, we are exposed to a mixture of pollutants simultaneously. Therefore, current air quality management approaches can fail to capture the synergistic effects of real-world exposures, which often disproportionately impact marginalized communities. This work examines existing approaches used for assessing air pollution mixtures in Canadian decision-making for air quality management and air quality research, to inform the pilot design of fit-to-purpose multi-pollutant analytical and visualization tools.
We collected data from a variety of sources to inform the design of more action-oriented mixture visualizations. These sources included decision-maker interviews and a scoping literature review. Through interviews we investigated the decision context of various decision-informing actors, focusing on data formats, availability and presentation. Interview participants have included municipal, provincial and federal environmental policy-makers and researchers, representatives of health authorities and (frontline) community advocates and researchers. The study collected the questions that these actors are seeking to answer, as well as their perceptions of the limitations of available data, including regarding data format or potential insights. As a next step, this work then combined the insights gained with technical methods for interpreting complex multipollutant data sets from the literature review. Many analysis techniques for multipollutant data sets are effective in reducing the complexity of high-dimensional data sets and produce informative multivariate patterns (e.g. dimensionality reduction techniques, clustering, correlation, and cumulative indicators). However, these methods often generate abstract, technical outputs, which can be difficult for non-expert audiences to interpret, and lack context or place-specific variables.
In a pilot demonstration, multivariate data analyses combined with situated knowledge of the decision context were translated into understandable measures of cumulative exposures to air pollutants. This synthesis is visually represented in a user-friendly, interactive dashboard and will be evaluated through user testing. The objective of the dashboard is to provide insights into the data to help answer user questions given their respective decision context. Examples of questions include: ‘What are the multipollutant profiles in the area? What are the major emission sources contributing to these profiles? What are the characteristics of the population most impacted by these multipollutant exposures?' The pilot dashboard will be tested with users to determine how the multivariate insight can best be communicated and to identify possible limitations and uncertainties. We hypothesize that the dashboard will be positively received if it supports users in answering their relevant questions, while clearly communicating how data insights are generated.
These findings contribute to ongoing efforts to refine analytical tools for multipollutant datasets and situate them within the complexities of local decision-making contexts. These approaches aim to better reflect real-world exposure patterns while balancing analytical complexity with interpretability.
How to cite: Warum, L., Pavey, B., Fernandez, L., Kutarna, S., Davis, Z., Galarneau, E., and Giang, A.: Characterizing and visualizing air pollution mixtures for air quality management decision-making in Canada, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20070, https://doi.org/10.5194/egusphere-egu26-20070, 2026.
Without emission reductions, climate change may increase ozone and PM2.5 air pollution in the United States; however, we do not know how this will affect air quality alerts that prompt people to stay indoors. Here, we use an integrated modeling framework to find distributions of daily Air Quality Index (AQI) during the smog season at the start, middle, and end-of-century. Considering natural variability, climate change may cause air quality alerts to double (increase by a factor of 2 ± 0.2) by 2100. Days when both ozone and PM2.5 exceed alert thresholds quadruple (4.3 ± 1.2). More than 100,000,000 (± 45,000,000) people experience mean air pollution deemed “Unhealthy for Sensitive Groups”, a growth of 7 (±3) times compared to 2000. If people follow alerts by staying inside, they reduce exposure to outdoor-generated pollutants. Their health benefits are similar whether the alert is caused by ozone or PM2.5. Senior (age 65+) populations receive much higher benefits per day by adapting (95CI across ozone and PM2.5: $2.80 to $147) as young adults (age 18-35; 95CI: $0.11 to $4.22) – more than 45 times higher on average. This disproportionate impact requires targeted messaging and guidance, especially as climate-related risks rise.
How to cite: Saari, R., Sparks, M., East, J., Garcia-Menendez, F., and Monier, E.: Air Quality Alerts, Health Impacts, and Adaptation Implications Under Varying Climate Policy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13710, https://doi.org/10.5194/egusphere-egu26-13710, 2026.
Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot 5
EGU26-21338 | Posters virtual | VPS4
Hazardous gaseous pollutants (NOx, SO2, TVOCs) emission from solid fuels combustion and their mitigation using novel adsorbent materialsWed, 06 May, 14:39–14:42 (CEST) vPoster spot 5
Traditional solid fuels are extensively used for domestic heating and cooking in developing countries, especially in rural and semi-urban regions. Combustion of these fuels is a major source of nitrogen oxides (NOx), sulfur dioxide (SO2), and volatile organic compounds (TVOCs), which significantly contribute to air pollution, respiratory disorders, secondary aerosol formation, and atmospheric photochemical reactions. The generation and release of these pollutants are strongly influenced by fuel moisture content, elemental composition, and inorganic constituents. This study presents a comprehensive investigation of the chemical characteristics of commonly used solid fuels and evaluates the potential of advanced functional materials for mitigating NOx, SO2, and TVOC emissions from domestic combustion sources.
Representative fuel samples, including fuel wood (FW), coal balls (CB), dung cake (DC), and crop residues (CR), were obtained from the Raipur–Durg–Bhilai region of Chhattisgarh, India, selected based on their prevalence and area-specific usage patterns. The samples were air-dried, pulverized, and homogenized prior to analysis. Moisture content was determined gravimetrically by oven drying at 105 °C. Ultimate analysis of carbon (C), hydrogen (H), nitrogen (N), sulfur (S), and oxygen (O) was performed using a CHNS/O elemental analyzer. Ionic species, including nitrate, sulfate, chloride, and major alkali and alkaline earth metals, were quantified using ion chromatography to assess their role in pollutant formation and combustion behavior. These chemical parameters were used to infer emission potential for NOx, SO2, and TVOCs.
NO emissions were generally higher for AR and DC, while FW showed the lowest NO EF. SO2 emissions followed a similar trend, with DC producing the highest levels and FW the lowest. TVOC emissions were elevated for fuels with higher moisture and inorganic content, such as AR and DC, whereas FW exhibited the lowest TVOC emission potential. CB displayed intermediate to high emissions, with particularly high TVOC formation due to its variable composition. Emission factors developed in simulated experimental chambers were validated against real-world measurements, indicating that domestic household emissions closely correspond to chamber-based estimates.
To address post-combustion emission control, advanced materials including graphene-based materials, biochar, graphitic carbon nitride (g-C3N4), metal oxides (MnO2/TiO2), zeolites, metal–organic frameworks (MOFs), covalent organic frameworks (COFs), and silica-based adsorbents were considered for NOx, SO2, and TVOC mitigation. Materials were characterized using BET surface area analysis, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM), confirming high surface activity and strong gas affinity. Their physicochemical properties, high specific surface area, tunable pore size distribution, and surface functional groups, enable efficient adsorption and catalytic transformation of pollutants. Graphene-based materials and biochar adsorb acidic gases through π–π interactions and surface oxygen functional groups, while g-C3N4 facilitates photocatalytic oxidation of NOx under visible light. Metal oxides such as MnO2/TiO2 catalyze the oxidation of SO2 to sulfate and TVOCs to less harmful products via surface redox cycles. Zeolites and MOFs provide selective adsorption of NOx and TVOCs through microporous confinement and acid–base interactions.
How to cite: Pervez, S., Sahu, D., Pervez, Y. F., Karbhal, I., and Deb, M. K.: Hazardous gaseous pollutants (NOx, SO2, TVOCs) emission from solid fuels combustion and their mitigation using novel adsorbent materials, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21338, https://doi.org/10.5194/egusphere-egu26-21338, 2026.
