This session aims to address the current challenges, methodological approaches and wider relevance of observing and modelling meteorology-atmospheric environment interactions around the world. We welcome contributions including, but not limited to, integrating multi-source data (such as, on-situ monitoring, remote sensing, etc.) with controlled experiments to identify the key processes, modelling of the interactions between climate change and air pollution as well as the future projections, assessment the impact of extreme weather on air pollution and future trends, and illustrating the development of cities and the effects of urban climate on regional air quality. Research that reveals the impact of air pollution on the environment, ecology and human health is also welcome.
Poor air quality is the cause of 8,1 millions deaths annually. The Metropolitan Area of São Paulo is home to more than 20 million people and frequently presents poor air quality, creating a concerning public health issue. Its location presents some unique features: 1) despite being 700 meters above sea level, it is frequently influenced by the sea breeze circulation that comes up the coastal escarpment and the predominant wind direction in Sao Paulo, influenced by the sea breeze, is from southeast; 2) considering a southeast-northewest direction, the sea breze circulation comes from a coastal area (in the city of Cubatao) that contains an industrial complex and the largest harbor in Latin America (in the city of Santos), passes through Sao Paulo and eventually reaches another metropolitan area, centered in the city of Campinas, that also has relevant industrial activities; 3) the three metropolitan areas also form a very active economic axes that presents an intense road traffic among the 3 areas and combine approximately 25 million inhabitants. The present work analyses the influence of synoptic and mesoscale atmospheric circulations, such as sea breeze, urban heat island, cold fronts, and topographic influences, on the air quality of the Cubatão-São Paulo-Campinas region, focusing on an acute ozone pollution episode. We use the WRF model with the Single Layer Urban Canopy Model for the meteorological simulations. Air pollutant emissions were simulated using the EDGAR global dataset and MEGAN for biogenic emissions. Traffic emissions were then adjusted using local inventories. Air quality was simulated with CMAQ. The chosen episode was from 3rd to 6th October 2019, during the austral spring, when the pollutant exceeded local air quality standards. Considering NOX, sea breeze helps decrease the concentrations near the surface because of transport and dispersion due to the increased wind speed, but also because sea breeze creates an internal boundary layer. The returning branch of the sea breeze transports polluted air back to the ocean above the internal boundary layer. During pre-frontal conditions, wind is mainly from the northwest, transporting pollutants to the coast, increasing air temperature, and favoring a deeper boundary layer and vertical dispersion. These patterns also delay sea breeze propagation over the plateau and are crucial to a steep increase in ozone concentration. The front passage changes wind direction and increases its velocity, favoring transport from the coast to the continent, augmenting atmospheric instability and vertical dispersion of pollutants. A better understanding of the mechanisms that cause high ozone concentrations is key to forecasting these occurrences and choosing effective measures to prevent them.
How to cite: Ribeiro, F. and Valdambrini, N.: Influence of synoptic and local circulations on high ozone concentration episode, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13549, https://doi.org/10.5194/egusphere-egu26-13549, 2026.
Under continued climate change, urban ozone pollution emerges as a multistressor whose processes governing its interactions with extreme events remain poorly characterized, particularly the enhancement of concentrations during heatwaves and the occurrence of compound heat and ozone episodes. In Brazil, this issue is further shaped by a large vehicular fleet operating on biofuels, emitting substantial amounts of volatile organic compounds (VOCs), key precursors of tropospheric ozone. This study presents a quasi continental, long term assessment (2010–2025) of ozone trends during heatwaves across distinct pollution and meteorological regimes. We integrate in situ measurements of ozone, meteorological variables and co occurring pollutants such as PM2.5, NOx, and VOCs in 8 of the larger metropolitan areas in southern, southeastern and northeastern Brazil. Highest MDA8hO₃ levels were observed in the metropolitan regions of Rio de Janeiro and São Paulo, notably in spring and summer, with frequent exceedances of the air quality standard (100 µg m⁻³). In the southern and northeastern regions, concentrations are lower, with median values of 25-50 µg m⁻³. Recirculation and stagnation regimes are associated with higher pollution levels in most cities, although Salvador, Belo Horizonte and Rio de Janeiro exhibit an increase in ozone under ventilated conditions. Atmospheric circulation also modulates the temperature ozone relationship, with clear differences among climatic regions. Precursor rich areas (high NOx and more reactive VOCs) show a stronger association between MDA8hO3 and daily maximum temperature. Ozone enhancement during heatwaves varies regionally with pollution levels and prevailing circulation. In São Paulo, at stations directly influenced by vehicular emissions, ozone enhancement reaches 52% under heatwave conditions combined with stagnation. Ozone waves occurred in all southeastern cities within high emission zones. Consequently, combined heat and ozone waves were also detected, especially in Belo Horizonte, where 61% of ozone wave events occurred during heatwaves in spring and summer. These findings indicate that ongoing climate change, through the intensification of heatwaves, is likely to increase the frequency of high ozone episodes in densely populated areas, posing escalating public health challenges. The results underscore the need for integrated mitigation and adaptation strategies, including strengthened control of ozone precursor emissions, particularly within the Brazilian context of biofuel driven vehicular emissions.
This work was developed under the scope of Project OVERHEAT.SA - COllaboratiVE Research on Compound Drought and HEATWave events in South America financed by CNPQ grant number 443285/2023-3.
How to cite: Monteiro dos Santos, D., Albuquerque, R., Russo, A., Peres, L., Trigo, R., and Libonati, R.: Heatwave Driven Urban Ozone Extremes Modulated by Circulation and Pollution Regimes in Brazilian Metropolitan Areas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-911, https://doi.org/10.5194/egusphere-egu26-911, 2026.
Urbanization substantially alters surface energy fluxes, boundary-layer structure and urban ventilation, with direct consequences for local climate and air quality. While numerous modelling studies have examined individual cities, a globally consistent framework to compare urban meteorological impacts across megacities is still lacking. Here, we develop a unified WRF-based diagnostic framework, built around radial urban-rural analysis, to quantify urban-induced meteorological modifications in a global catalogue of megacities using month-long simulations for May and October 2024. The set spans a wide range of climatic and geographic settings, including inland megacities (e.g. Delhi, Beijing, Paris, Cairo, Mexico City, Moscow, Dhaka, Tehran, Johannesburg) and coastal megacities (e.g. New York, Barcelona, Tokyo, Shanghai, Lagos, Los Angeles, Mumbai, Istanbul, São Paulo).
The methodology aggregates key meteorological variables such as 2-m air temperature (T2m), 10-m wind speed (WS10) and planetary boundary-layer height (PBLH), into concentric 5-km rings from 0 to 60 km around each city centre. This radial design explicitly tracks how these meteorological fields evolve from rural surroundings towards the urban core. Urban effects are then expressed as inner-outer ring contrasts relative to a rural baseline, providing a simple, reproducible “urban-effect intensity” metric that is directly comparable across cities, seasons and model configurations.
Across the 14 megacities analysed so far, the urban core (0-15 km) is consistently warmer, more deeply mixed and less windy than the rural ring (45-60 km), with a much stronger signal over non-coastal cities. Averaged over inland sites, near-surface temperature is enhanced by ~1.8 °C during the day and ~3.6 °C at night (~12-28 % above rural), compared with only ~1.1-1.4 °C (5-8 %) over coastal cities. Daytime PBLH in non-coastal urban cores is ~230 m higher than in rural surroundings (~30 % increase), and nocturnal PBLH can be nearly doubled (~80 %), whereas coastal cities exhibit more modest enhancements (~50-90 m; ~13-18 %).
At the individual-city scale, Delhi and Moscow show the clearest extremes: daytime PBLH enhancement reaches ~526 m in Delhi and ~441 m in Moscow, with nocturnal PBLH nearly tripled (~274 %) and more than doubled (~206 %), respectively. Night-time T2m difference is also strongest in Delhi (~6 °C), followed by Beijing, Mexico City and Moscow (>3-4 °C, >30 % above rural), while all cities show similar urban wind slow-downs of ~0.7-0.9 m s⁻¹ (~15-20 %).
Considered jointly, the temperature, PBLH and wind-speed diagnostics reveal a consistent urban signal of sustained warming, enhanced mixing depths and reduced low-level winds in urban cores, strongest in large inland megacities and muted but still evident in coastal cities. These meteorological changes are expected to strongly influence urban air quality, which we will investigate explicitly in future work.
Keywords: Megacity, Urbanisation, Meteorology, UHI and WRF
How to cite: Wagay, A. A., Uikey, A., AchutaRao, K., Paasonen, P., Petäjä, T., Sinclair, V., Gani, S., and Guttikunda, S.: Impacts of Urbanization on Meteorological Dynamics in Megacities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8950, https://doi.org/10.5194/egusphere-egu26-8950, 2026.
Ozone has emerged as a critical air quality challenge in many regions, with its formation and accumulation controlled not only by precursor emissions but also by meteorological conditions and boundary-layer dynamics. This study investigates ozone pollution across three representative regional types: a densely populated urban area, an industrial-port region, and a rural background site characterized by relatively limited anthropogenic emissions. The aim is to elucidate the dominant controlling processes under different emission and meteorological regimes. Long-term air quality observations were combined with UAV-based vertical measurements and backward trajectory analysis to characterize the spatiotemporal variability of ozone across these regional settings. Long-term trend analyses reveal pronounced seasonal variability in surface ozone levels across all three regions, with no evident long-term decreasing trend, despite overall reductions in ozone precursor emissions. In contrast, PM2.5 concentrations show a consistent decline, highlighting differences in the governing mechanisms of gaseous and particulate air pollutants. Precursor concentrations remain notably higher in the industrial–port region compared with urban and rural areas, reflecting the influence of emission structure on ozone formation potential. Correlation analyses show generally weak to moderate relationships between surface ozone and meteorological variables, with weak winds and synoptic-scale atmospheric stability favoring ozone accumulation. UAV-based vertical observations further reveal frequent nighttime formation of stable boundary layers and elevated residual ozone layers across seasons, suggesting that vertical carryover processes play an important role in modulating next-day surface ozone. Backward trajectory analyses demonstrate that high-ozone episodes are primarily associated with regional stagnation and short-range transport rather than long-range transport. Overall, this study highlights the critical role of boundary-layer dynamics, vertical ozone structures, and regional meteorological conditions in influencing ozone pollution across various regional typologies. These findings provide transferable insights for the development of effective ozone mitigation strategies and air quality management in coastal and industrialized regions.
How to cite: Yen, T.-J., Peng, Y.-P., and Wang, S.-H.: Interactions between Meteorological Conditions and Surface Ozone in Urban, Industrial, and Rural Environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8777, https://doi.org/10.5194/egusphere-egu26-8777, 2026.
Electricity is an indispensable resource for human activity. Despite its importance, power generation imposes a significant environmental burden by contributing to air pollution and climate change. Meteorological and climatic conditions, geographic terrain, industrial characteristics, and human activities further influence air pollution. To quantitatively investigate these influences, this study conducts a time–frequency analysis of particulate matter (PM). The study areas were selected based on the locations of coal-fired power plants in Taiwan, including Linkou, Shalu, Qiaotou, and Xiaogang, enabling the investigation of regionally distinct air pollution characteristics.
Building on our previous study, which identified pronounced regional heterogeneity in PM behavior across these four monitoring stations, this work further explores the scale-dependent and time-lagged dynamics underlying such differences. Time-Dependent Intrinsic Cross-Correlation (TDICC) is applied to examine the scale-dependent and time-lagged coupling relationships between PM and meteorological and gaseous pollutant factors. This analysis reveals delayed PM responses associated with meteorological conditions and gaseous pollutants, providing complementary insights beyond conventional correlation analyses.
By integrating all correlation analysis results, this study develops an integrated heat risk map to illustrate how different factors influence PM at multiple time scales at each station. The resulting heat risk map highlights distinct spatial patterns and regional heterogeneity in PM-related risk, offering a comprehensive understanding of the spatiotemporal characteristics and potential source contributions of PM. This integrated framework provides practical insights for identifying high-risk areas and dominant influencing factors, supporting more targeted air pollution management and mitigation strategies under varying meteorological conditions.
Keywords: Power Plants; Air pollution; Particulate Matter; Meteorological influences; Time–frequency analysis; Time-lag effects; Heat risk map analysis
How to cite: Yao, S. T. and Tsai, C. W.: Spatial-Temporal Variations of Particulate Matter Influenced by Hydro-Meteorological and Gaseous Pollutants Factors: A Case Study of Taiwan Coal-Fired Power Plants, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16253, https://doi.org/10.5194/egusphere-egu26-16253, 2026.
While overall the global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2 radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. The anthropogenic origin is connected to large extent with the urban environment. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedbacks of global warming on emissions, e.g., permafrost thaw.
The main goal of the EC Horizon Europe project FOCI, is to assess the impact of key radiative forcers, where and how they arise, the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global Earth System Models and into Regional Climate Models coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world, with final emphasis to selected cities environment in convection permitting scale. We will develop new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. Mutual interactions of the results and climate services producers and other end-users will provide feedbacks for the specific scenarios optimization and potential application to support the decision making, including climate policy.
Overall introduction to coupled RCM-CTM modelling experiment strategies and preliminary results will be presented in addition to the contemporary status of the project. Historical simulations results are validated against reanalyses data and the assessment of impact of chemistry involvement is shown. Preliminary results of future scenarios will be presented as well.
How to cite: Halenka, T., Sokhi, R., Finardi, S., and Machado-Crespo, N.: Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts: Modelling of Chemistry-Climate Interactions over Scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21716, https://doi.org/10.5194/egusphere-egu26-21716, 2026.
In the context of China’s “dual carbon” goal, emissions of air pollutants are expected to significantly decrease in the future. Thus, the direct climate effects of black carbon (BC) aerosols in East Asia are investigated under this goal using an updated regional climate and chemistry model. The simulated annual average BC concentration over East Asia is approximately 1.29 μg/m3 in the last decade. Compared to those in 2010–2020, both the BC column burden and instantaneous direct radiative forcing in East Asia decrease by more than 55% and 80%, respectively, in the carbon peak year (2030s) and the carbon neutrality year (2060s). Conversely, the BC effective radiative forcing (ERF) and regional climate responses to BC exhibit substantial nonlinearity to emission reduction, possibly resulting from different adjustments of thermal-dynamic fields and clouds from BC-radiation interactions. The regional mean BC ERF at the tropopause over East Asia is approximately +1.11 W/m2 in 2010–2020 while negative in the 2060s. BC-radiation interactions in the present-day impose a significant annual mean cooling of -0.2 to -0.5 K in central China but warming +0.3 K in the Tibetan Plateau. As China’s BC emissions decline, surface temperature responses show a mixed picture compared to 2010–2020, with more cooling in eastern China and Tibet of -0.2 to -0.3 K in the 2030s, but more warming in central China of approximately +0.3 K by the 2060s. The Indian BC might play a more important role in East Asian climate with reduction of BC emissions in China.
How to cite: Gao, P. and Zhuang, B.: Changes in the direct climate effect of black carbon aerosols in East Asia under the “dual carbon” goal of China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8924, https://doi.org/10.5194/egusphere-egu26-8924, 2026.
Cloud droplet nucleation, effective radius and cloud–water autoconversion rate (P) parameterization schemes are included in the fourth version of the Regional Climate Model (RegCM4). For cloud droplet nucleation, an empirical scheme (GI99), a semiempirical scheme (GH93), and a scheme based on aerosol activation theory (AG00) are involved. For P, a scheme dependent only on the cloud water mixing rate (Default), a scheme involving the droplet growth rate (BR67), a scheme highly correlated with aerosol components (BH94), a scheme weakly dependent on the components (TC80), a scheme involving the droplet size (LB95) and a scheme that derives a formula mathematically (IBS2) are adopted and tested. Dispersion (ε) is important when calculating the effective radius. Effective radius schemes with/without ε effects are further compared. An optimal combination of schemes is proposed. For cloud droplet nucleation, GH93 and AG00 are better. For P, LB95, BH94, and Default schemes could better simulate precipitation. Considering the ε effect would improve simulation accuracy. Overall, the AG00, BH94 and two-parameter-ε schemes are recommended for improving model simulations of precipitation in East Asia. The P schemes are compared when the aerosol 2nd indirect effects are investigated in East Asia. The change of net radiative flux at the top of the atmosphere from the schemes is -3.63 ± 4.05 W∙m-2 in central to eastern China. The aerosol 2nd indirect effect is the most significant in the BH94 scheme, with average changes in cloud optical depth, net radiative flux, and precipitation of 1.63, -10.58 W∙m-2, and -0.01 mm∙d-1, respectively.
How to cite: Zhao, R., Zhuang, B., Xie, M., and Wang, T.: Comparative Study of Parameterization Schemes for Aerosol Indirect Effects in East Asia Based on RegCM4, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4735, https://doi.org/10.5194/egusphere-egu26-4735, 2026.
To reveal the patterns and causes of ozone (O₃) suppression under extreme high temperatures in the North China Plain (NCP), this study utilized O₃ observation data, surface meteorological observation data, and ERA5 reanalysis data from 2014 to 2023. The Z-test method was employed to define the critical temperature (Tx) for ozone suppression, and the spatio-temporal characteristics of this phenomenon as well as the influencing mechanisms of atmospheric circulation were analyzed. The results indicate that ozone suppression in the NCP is concentrated in five cities, including Beijing, located along the Yanshan Mountains and Northern Taihang Mountains. The critical temperature Tx ranges from 33 to 35°C. May, June, and July are the months when ozone suppression is most likely to occur in major cities of the region; Tx values are relatively higher in June and July (34-37°C) and lower in May and September. In terms of interannual variation, the maximum Tx value of 37.6°C was recorded in 2023, which is positively correlated with the frequency of extreme high temperatures in summer. Atmospheric circulation analysis shows that the geopotential height negative anomaly occurs over Northeast Asia during the occurrence of ozone suppression, the NCP region is affected by northwest winds which facilitates pollutant diffusion. Meanwhile, the region is controlled by a high-pressure warm ridge, promoting subsidence and warming. These two factors result in a negative correlation between high temperatures and O₃ concentrations. A case study in July 2023 verified that the subsidence motion dominated by upper-tropospheric northwest winds not only drives temperature rise but also improves diffusion conditions, serving as the key meteorological cause of ozone suppression. This study provides scientific support for the precise prevention and control of ozone pollution and the optimization of climate models in the NCP.
How to cite: Qiu, Y.: Spatio-temporal Characteristics of Ozone Suppression and Its Response to Atmospheric Circulation Under High-Temperature Conditions in the North China Plain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2427, https://doi.org/10.5194/egusphere-egu26-2427, 2026.
Extreme heat and surface ozone pollution frequently co-occur during summer and pose a growing risk to human health under climate warming. This co-occurrence is expected to intensify in the future, as global climate change is projected to increase the frequency, intensity, and duration of heatwaves. At the same time, ozone remains a major air quality concern in Europe despite substantial reductions in precursor emissions, and its health impacts are well documented even at concentrations below current regulatory standards.
Previous studies have shown that temperature is a key meteorological driver of high ozone episodes, particularly in summer when photochemical activity is strongest. However, recent work on compound climate extremes has demonstrated that univariate or linear approaches can substantially underestimate risk when extremes occur simultaneously, highlighting the need for multivariate extreme-value methods.
Moreover, spatial heterogeneity related to urbanization, land use, topography, and local meteorological conditions is often acknowledged but rarely examined in terms of how it modifies the occurrence and strength of heat–ozone extremes at the local scale. Ozone formation is governed by complex, nonlinear interactions between temperature, emissions, boundary-layer processes, and deposition, making its response highly variable in space and time. As a result, simple correlation-based analyses may underestimate the true influence of temperature on ozone, particularly under extreme conditions and in heterogeneous environments.
Previous studies in Germany and Bavaria have linked ozone and temperature observations using either nearest station matching or reanalysis products such as ERA5, often assuming limited influence of urban heat island effects on daily maximum temperature. While this approach reflects established practice in regional air-quality studies, it may introduce uncertainty in spatially heterogeneous environments, particularly for local-scale compound extremes. Matching based solely on proximity or large-scale fields may not fully capture the influence of land use and station setting. To address this methodological challenge, the present study adopts a land-use–informed, multi-scale matching perspective to evaluate the sensitivity of compound heat–ozone dependence to spatial scale.
This study aims to quantify compound heat–ozone extremes in Bavaria using multivariate analysis, with a focus on (i) how urban–rural setting and local spatial context shape compound risk, and (ii) how dependence strengthens during heatwave extremes and multi-day heatwave conditions.
By bridging statistical extreme-value analysis with atmospheric chemistry interpretation, this work provides a physically consistent and regionally relevant assessment of heat–ozone risks in southern Germany.
How to cite: Forghanifar, M. and Lu, M.: Spatial Heterogeneity of Compound Heat and Ozone Extremes: A Multivariate Extreme Value Perspective in Southern Germany, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6640, https://doi.org/10.5194/egusphere-egu26-6640, 2026.
Urban coastal environments exhibit spatial heterogeneity in air pollutant distributions due to complex built environments and diverse emission sources. In these regions, land-sea breeze circulations transport ozone precursors and modulate near-surface ozone (O3) variability. However, the limited spatial coverage in conventional air quality monitoring networks constrains the ability to resolve these coupled advection-chemistry interactions.
In this study, we conducted spatially dense, multi-point measurements of CO, NO, NO2, O3, PM10, and PM2.5 using a network of cost-effective air quality sensors in Ulsan, a highly industrialized coastal city in South Korea. Sensors were deployed across industrial, residential, forested, and urban background environments. Two-week intensive campaigns in both summer and winter during 2023–2025 enabled characterization of the seasonal and diurnal variability of pollutant distributions.
Pollutant concentrations and diurnal patterns differed distinctly among emission environments. CO and NO concentrations were highest at industrial and residential sites and peaked during morning and evening commuting hours, whereas PM exhibited a more spatially homogeneous distribution. In contrast, surface O3 decreased with increasing NOx levels, reflecting enhanced O3 loss via NO titration during periods of elevated traffic and industrial emissions.
During sea-breeze events. The inland-bound transport of O3-rich marine air led to pronounced spatial gradients in surface ozone. Ozone levels decreased over industrial and residential areas due to strong NO titration and subsequently increased farther inland in forested regions where NOx concentrations remained lower. Using these spatial O3 gradients, we estimated O3 advection rates and outlined an observationally constrained approach for evaluating the surface O3 chemical budget. This study are expected to advance the understanding of sea-breeze-driven surface O3 variability in coastal cities and provide observational constraints for interpreting surface O3 budgets.
How to cite: Han, S., Park, Y., and Choi, W.: Air Pollutant Variability in a Coastal Urban Environment: Measurement-Based Estimation of Ozone Advection Rates from Spatial Gradients During Sea-Breeze Periods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8905, https://doi.org/10.5194/egusphere-egu26-8905, 2026.
The sensitivity of surface ozone (O3) to temperature, often termed the climate penalty factor (CPF), quantifies the increase in O3 per unit temperature rise. While previous studies have characterized CPF under present-day conditions, its temporal evolution over multi-decadal timescales remains poorly understood. This study investigates long-term changes in summer (JJA) CPF across East Asia from 1980 to 2024 using GEOS-Chem simulations driven by MERRA-2 reanalysis. Anthropogenic emissions are held constant to isolate meteorology-driven changes, whereas biogenic emissions are allowed to respond to meteorological conditions. Using a regression-based decomposition approach, we separate the contributions of direct temperature effects from indirect effects mediated by co-varying meteorological conditions. Preliminary results reveal that CPF has increased in most East Asian regions over the past four decades, with distinct spatial patterns. Northern regions exhibit CPF changes primarily driven by direct temperature effects, while southern coastal regions show dominant contributions from indirect effects. These findings suggest that the mechanisms underlying O3-temperature sensitivity differ regionally and have evolved over time. Our results demonstrate the nonstationary nature of CPF and its regional heterogeneity, with implications for projecting future air quality and designing region-specific control strategies in a warming climate.
How to cite: Jeong, J., Park, R., Yeh, S.-W., and Lee, S.: Nonstationary Summer Ozone-Temperature Climate Penalty over East Asia: Decadal Trends and Regional Variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8944, https://doi.org/10.5194/egusphere-egu26-8944, 2026.
Ozone pollution has emerged as a critical air quality concern in China, especially in megacity area such as Beijing in recent years. Characterized by its complex, nonlinear interactions among precursor pollutants and significant spatiotemporal variations, ozone poses challenges for numerical models in terms of forecasting accuracy. In contrast, statistical forecasting models offer several advantages, including reduced data requirements, lower computational costs, and enhanced predictive accuracy, making them a viable option for practical ozone forecasting applications. In this study, we evaluate multiple time series models (such as ARIMA, NNAR, STLF, ETS etc.) for ozone concentration forecasts in Beijing. During the ozone pollution season, ARIMA and NNAR achieved correlation coefficients of approximately 0.65 between predicted and observed values. The ensemble model outperformed these, with a correlation coefficient of around 0.7 and an RMSE of about 45 µg m⁻³. For clear-day pollution events, after accounting for rainfall influence, the ensemble model's correlation coefficient reached approximately 0.9, with an RMSE reduced to about 40 µg m⁻³. The results demonstrate that time series models are effective for both mid-term and short-term ozone forecasting, while the ensemble model based on multiple time series approaches further enhances performance, offering high accuracy, temporal resolution, and spatial universality, particularly during severe pollution episodes. Daily maximum temperature, radiation precipitation are key meteorological factors that significantly influence ozone concentration. Incorporating maximum temperature into a dynamic ARIMA model significantly improved ozone forecasts, raising the correlation coefficient to about 0.75 and reducing RMSE. Future improvements could integrate more meteorological covariates to improve the performance of ozone forecasting models.
How to cite: Li, Y., Pu, W., Zhu, X., Wang, J., Quan, W., and Zhang, N.: Statistical Forecasting of Ozone in Beijing: Evaluating Multiple Time Series Models and the Impact of Meteorological Factors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9071, https://doi.org/10.5194/egusphere-egu26-9071, 2026.
High pressure weather is associated with atmospheric inversions, low wind speeds and little or no clouds and precipitation. High-pressure systems that stay stationary over a region for more than 5 days, called high-pressure blocking events, can cause elevated pollution levels due to the limited vertical mixing, and lack of aerosol removal through precipitation. In this study we have used meteorological and PM2.5 data from southern Sweden to investigate the evolution of pollution levels during high-pressure blocking events. We have used data from one rural and one urban station between 1995 and 2024. Moreover, we have used data from another meteorological station from between 1946 and 2024 to determine whether the frequency of high-pressure blocking events in the region is changing.
We find that the PM2.5 concentrations increase significantly during high pressure blocking events at both the rural and urban location. At both stations, the average increase is about 12 μgm-3 over a 12-day period. The PM2.5 levels are however substantially higher at the urban station than at the rural station. After the high-pressure blocking events are terminated, the PM2.5 levels drop to lower levels within 1 day. The increase in PM2.5 levels during the blocking events is stronger when winds from the south east dominate the event and during events with a higher average pressure. The increase is also stronger during wintertime compared to summertime at the urban station. The analysis of high-pressure blocking frequency show that there is no significant change in the number of blocking events over the period 1946 to 2024 in this region. This study shows that high-pressure blocking events results in increasing PM2.5 levels in southern Sweden but that there is no increase in these types of events here.
How to cite: Sporre, M. and Bergelv, F.: Relation Between High-Pressure Blocking and Aerosol Concentrations in Southern Sweden, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10709, https://doi.org/10.5194/egusphere-egu26-10709, 2026.
Mobile monitoring platforms equipped with low-cost sensors (LCS) are increasingly used to enhance the spatial coverage of air quality monitoring networks. In this study, we systematically evaluated the performance of ATMOS sensors for measuring PM₂.₅ by assessing their accuracy, precision and agreement with a reference-grade Beta Attenuation Monitor (BAM). Six identical ATMOS units were co-located and operated continuously for 27 days during the winter season at a Continuous Ambient Air Quality Monitoring Station (CAAQMS) situated at an urban background site within the IIT Bombay campus. The site is influenced by nearby traffic emissions and a lake, representing complex urban micro-environment. This study investigated the role of meteorological conditions in modulating PM₂.₅ concentration and its measurement by LCS relative to BAM observations. Diurnal variations in temperature and relative humidity recorded by ATMOS sensors showed strong agreement with BAM, yielding Pearson correlation coefficients of 0.89 and 0.96, respectively. In contrast, PM₂.₅ measurements from the LCS exhibited systematic biases with temperature–humidity regimes and between daytime (06:00–18:00 local time) and nighttime (18:00–06:00 local time). During daytime conditions characterized by relative humidity ≤70% and temperatures >20°C, the LCS consistently underestimated PM₂.₅ concentrations compared to BAM. Conversely, nighttime conditions with elevated relative humidity (>70%) and lower temperatures (<20°C) led to overestimation by the LCS. Optimal agreement between the LCS and BAM was observed within a temperature range and relative humidity range of 15–25°C and 30%–60%,respectively, indicating favorable operating conditions for the sensors. Hourly PM₂.₅ distributions from LCS revealed enhanced particulates (100–130 µg/m³) during daytime hours at certain days, coinciding with high relative humidity (>80%). These observations underscore the influence of humidity on PM₂.₅ measurements relative to temperature, likely through hygroscopic particle growth. Overall, the findings demonstrate that low-cost PM₂.₅ sensors can provide robust and consistent measurements under a range of meteorological conditions when their environmental sensitivities are explicitly characterized. These results support the application of LCS for air quality monitoring and exposure assessment, particularly when combined with regime-specific corrections or calibration strategies.
How to cite: Pathak, M. and C. Phuleria, H.: Meteorological Modulation of Diurnal PM2.5 Variability: Performance of Low-Cost Sensors at an Urban Background Site in Mumbai, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20864, https://doi.org/10.5194/egusphere-egu26-20864, 2026.
Urban air quality monitoring is essential due to the high concentration of anthropogenic pollution sources in cities. While regulations such as the 2030 EU air quality targets emphasize the need to reduce harmful pollutants, conventional ground-based networks often lack sufficient coverage and spatial detail. Satellite observations offer a powerful complement, providing continuous, high-resolution data to capture urban-scale variability and identify localized pollution hotspots.
This study focuses on analyzing seasonal air pollution patterns across the municipality of Rome by integrating multi-source datasets, including satellite measurements, ground-based observations, meteorology, land cover, and population distribution. Sentinel-5P TROPOMI data (2018–2024) were used to track the spatiotemporal variability of key trace gases such as NO₂, HCHO, CO, and CH₄. Daily measurements were processed into seasonally aggregated Level-3 products through the Products Algorithm Laboratory (PAL), with quality assurance filtering applied to ensure reliability. These data allowed the identification of emission hotspots and seasonal trends in precursor gases that drive secondary PM₂.₅ formation.
Aerosol optical depth (AOD) derived from MODIS Terra and Aqua observations using the MAIAC algorithm provided complementary information on aerosol distribution. Monthly AOD datasets were analyzed after reprojection to a consistent WGS84 grid, enabling direct comparison with TROPOMI-derived trace gas concentrations.
PM₂.₅ data were collected from the Regional Agency for Environmental Protection (ARPA) ground-based network. Hourly measurements from different ground-based stations were used to analyze the seasonal trend of PM₂.₅ across the city. This combination allowed for the evaluation of seasonal coupling between gaseous precursors, aerosols, and particulate matter, highlighting periods of increased secondary aerosol formation.
Meteorological factors were incorporated using ERA5 reanalysis data, providing hourly fields for wind, temperature, precipitation, radiation, and boundary layer dynamics. These variables helped interpret observed seasonal patterns by linking atmospheric transport, mixing, and photochemical activity to pollutant distributions.
Population dynamics, derived from high-resolution WorldPop datasets, were integrated to assess human exposure and explore how population density interacts with pollution patterns. By combining satellite, ground-based, meteorological, and demographic data, the study delivers a detailed, seasonally resolved understanding of air quality across Rome. This framework supports targeted interventions, prioritization of mitigation measures, and evidence-based planning for urban air quality management.
How to cite: Bassani, C., Terenzi, V., Fois, F., Tratzi, P., Perilli, L., Petitta, M., and Paolini, V.: Seasonal Urban Air Quality Characterization in Rome Using Integrated Satellite, Meteorological and Demographic Data , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20295, https://doi.org/10.5194/egusphere-egu26-20295, 2026.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 5
EGU26-4386 | ECS | Posters virtual | VPS3
Surface energy forcing modulates ozone variability independently of air temperature over the Tibetan PlateauTue, 05 May, 15:15–15:18 (CEST) vPoster spot 5
Meteorological normalization of surface ozone typically relies on air temperature to proxy both photochemical activity and boundary-layer dynamics. However, this approach implicitly assumes that the thermal state adequately represents radiative energy input—an assumption that remains untested in high-elevation environments where strong solar forcing and a thin atmosphere may decouple temperature from the surface energy balance. Here, we examine how surface energy forcing modulates ozone variability independently of air temperature using continuous station-level measurements in Lhasa (3650 m a.s.l.), Tibetan Plateau. By stratifying days based on net radiative input while explicitly constraining thermal conditions through a counterfactual matched-pair analysis, we isolate energy-driven processes without invoking reanalysis-based boundary-layer estimates. Results demonstrate that high-energy states consistently exhibit enhanced morning ozone growth (median +4.3 ppb h-1) and elevated daytime concentrations relative to temperature-matched low-energy states. These enhancements are accompanied by coherent multi-tracer responses, including moisture drying and the dilution of primary pollutants, which provide observational constraints on energy-driven vertical coupling that are distinct from temperature-dependent photochemistry. Furthermore, a rate-based robustness analysis confirms that these signals persist across varying stratification thresholds. We conclude that surface energy forcing represents a previously under-constrained structural factor in conventional ozone attribution frameworks, particularly in complex terrain where thermal and radiative states frequently decouple.
How to cite: Zhao, C., Wang, Y., Liu, Y., Li, W., Gongga, D., Quzhen, D., Ao, Y., Yue, J., Zhong, X., and Du, X.: Surface energy forcing modulates ozone variability independently of air temperature over the Tibetan Plateau, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4386, https://doi.org/10.5194/egusphere-egu26-4386, 2026.
