Abstracts of the 7th International Electronic Conference on Atmospheric Sciences (ECAS-7)

1. Introduction

The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7) was held online from 4 to 6 June 2025. The conference focused on a wide range of topics related to atmospheric science, open to subject areas concerning a topic of importance, especially interdisciplinary or transdisciplinary science.

In recent decades, significant strides have been made in all areas of atmospheric science. We have seen the proliferation of remote sensing technologies, their instrumentation, and techniques for their use in research and operational weather forecasting. We have also seen advances in synoptic and dynamic meteorology, which have greatly enhanced weather forecasting. Advances in the capabilities of atmospheric modelling as well as increases in computing power have enhanced our understanding of atmospheric behaviors at all scales of time and space. Additionally, there have been discoveries related to the behavior of smaller-scale systems, especially those that interact or intersect with human activity, health, and economics. These have inspired techniques for warning people that these events could affect them. An enhanced understanding of the interannual and interdecadal variability in our climate has also led to the development of long-range forecasting and projection. In conclusion, the conference sessions covered the following:

S1.

Biosphere, Hydrosphere, Land–Atmosphere Interactions;

S2.

Air Quality and Human Health;

S3.

Biometeorology;

S4.

Meteorology;

S5.

Atmospheric Techniques, Instruments, and Modeling;

S6.

Climatology;

S7.

Air Quality;

S8.

Aerosols;

S9.

Air Pollution Control.

2. Session 1: Biosphere, Hydrosphere, Land–Atmosphere Interactions

2.1. Analyzing the Relationship Between Vegetation and Temperature Changes in the Sylhet Region

Sk. Tanjim Jaman Supto

• Department of Environmental Research, Nano Research Centre, Sylhet 3114, Bangladesh

As global temperatures continue to rise, understanding the relationship between climate and vegetation is crucial for agriculture and for mitigating and adapting to environmental changes. The complex interaction between vegetation and climate becomes even more significant as temperatures increase, making it essential to comprehend these changes in the environment. This study examines how vegetation dynamics in the Sylhet Region have been affected by long-term temperature changes over the past four decades. This study aims to uncover changes in temperature trends and vegetation growth over recent decades and how it has impacted the climate of the Sylhet region. This research utilizes the Normalized Difference Vegetation Index (NDVI) data from satellites, and statistical analysis techniques are used to examine the relationship between vegetation and temperature in Sylhet. This research shows how changes in temperature affect vegetation health and density. Satellite imagery shows a steady decrease in vegetation density in the Sylhet region. Local climatic variables such as temperature, precipitation, and humidity, as well as anthropogenic factors like urbanization and deforestation, are identified as primary factors behind the loss of vegetation. This study shows a decreasing effect of climate-driven changes on vegetation over time by closely examining the relationship between NDVI and regional climatic parameters. This implies that in recent years, the direct impact of climatic variability has been less significant than the involvement of human-induced variables, such as urbanization, land-use changes, and deforestation, in shaping vegetation patterns.

2.2. Assessing the Impact of Regional Climate Variability on Forest Vulnerability in Assam Using a GIS and Machine Learning-Based Approach

Sayanta Ghosh ¹, Aakash Warman ¹, Pranjul Chauhan ², Aniruddh Soni ², Jitendra Vir Sharma ³

¹ 

Centre for Geospatial Technology Application, Land Resources Division, The Energy and Resources Institute (TERI), 6C, India Habitat Centre, Lodhi Road, New Delhi 110 003, India Contact no (Office): +91 11 7110 2100

² 

Centre for Biodiversity & Ecosystem Services, Land Resources Division, The Energy and Resources Institute (TERI), India

³ 

Land Resources Division, The Energy and Resources Institute (TERI), 6C, India Habitat Centre, Lodhi Road, New Delhi 110 003, India

Assam, one of India’s richest regions in terms of biodiversity, faces significant environmental threats due to regional climate variability and anthropogenic pressures. This study explores a GIS and machine learning (ML)-based approach to assess the impact of climate change on forest and biodiversity vulnerability across the state. This analysis involves eight parameters: the Biological Richness Index (BRI), Disturbance Index (DI), Forest Canopy Density (FCD), Fire Point Intensity (FPI), Biomass Extraction Intensity (BEI), Slope, Standardized Precipitation Index (SPI), and Flood Vulnerability Index (FVI). Using the Analytical Hierarchy Process (AHP), these indicators were weighted and synthesized to develop a composite Forest and Biodiversity Vulnerability Index (FBVI). The major focus of this study is the delineation of climate change hotspots and their correlation with forest and biodiversity vulnerability zones. The assessment identified 19 grids as very highly vulnerable and 68 grids as highly vulnerable in terms of their forests and biodiversity. Climate change hotspot mapping revealed a further 38 grids experiencing very high climate exposure and 47 grids with high climate exposure which significantly overlap with vulnerable forested regions. This correlation suggests that regions with high climate sensitivity are also at increased risk of forest degradation, biodiversity loss, and ecosystem instability. An analysis of the trend over 22 years indicates a 1.56% decline in total forest cover and a 4.06% reduction in very dense forest cover, driven by factors such as a 9.3% increase in cropland area and a 1% expansion in settlements. The FPI analysis highlights six districts as very highly prone to fire incidents, while nine districts are highly prone to such events. The Standardized Precipitation Index (SPI) trends classify seven districts as very highly drought-prone zones, further exacerbating forest vulnerability. The Flood Vulnerability Index (FVI) identifies regions highly susceptible to flooding, stressing the compounded impacts of hydrological changes on Assam’s forest ecosystems. The results emphasize the urgent need for climate-adaptive forest management strategies, including remote sensing-based monitoring, participatory conservation approaches, and policy-driven interventions.

2.3. Dynamics of Changes in Height of Snow Cover of Chronological Series of Birch Plantations (Middle Taiga Subzone of European North)

Maria Vladimirovna Medvedeva ¹, Nadezhda Nikolaevna Nikolaeva ¹, Vitaly VladimirOvich Vorobiev ¹, Alexandra Vladimirovna Ukhanova ²

¹ 

Forest Research Institute of the Karelian Research Centre of the Russian Academy of Sciences (FRI KarRC RAS)

² 

Institute of Biology, Ecology and Agricultural Technologies of Petrozavodsk State University

Snow cover plays an important role in soil formation and has a significant impact on vegetation. The need to study snow cover has been increasing in recent years due to global climate change. Special attention should be paid to the study of the dynamics of snow cover in artificially created biogeocenoses, in order to understand the general trends in the interaction of soils, snow mass, and vegetation under anthropogenic influence. This is especially true for the taiga zone of the European North, which is characterized by great variability in the natural environment. Insufficient attention to this problem has determined the purpose of this work: to study the depth of snow cover in a chronological series of the birch bark of various grasses. In the middle taiga subzone of Karelia, a change in the depth of snow cover was carried out in birch plantations of different ages.

The research conducted has shown that the formation of snow cover changes dramatically in space and time and depends on abiotic and biotic factors. It was found that stable snow cover had formed by 30 October 2023. The period of snowfall in the studied areas was 7 months. The maximum height of the stable snow cover was 80 cm, with a minimum of 5 cm. An analysis of the results showed that the distribution of snow on the site depends on the microsite (crown-window): higher indicators were noted “under the crown” compared to the microsite “window”. This study confirms the role of the phytocomplex in the formation of snow cover and established general trends in changing the thickness of snow cover depending on the age of birch planting. The results obtained are the basis for creating a database for the predictive monitoring of the carbon footprint of terrestrial ecosystems of the boreal zone of the European North.

2.4. New Consideration Within Atmospheric Sciences on Whether Characteristic Lightning Strikes Belong to an Atmospheric Environment

Dursun Acar ¹, Ozcan Kalenderli ², Demet Biltekin ³

¹ 

EMCOL Eastern Mediterranean Centre for Oceanography and Limnology Maslak, Istanbul Technical University, Sarıyer, İstanbul, Türkiye

² 

Faculty of Electrical and Electronics, Istanbul Technical University, Maslak, Sarıyer, İstanbul, Türkiye

³ 

Eurasia Institute of Earth Sciences, Istanbul Technical University, Maslak, Sarıyer, İstanbul, Türkiye

While examining how the orientation of particles and droplets in the air subject to static electric fields during atmospheric transport affect sedimentation processes, an important point that has been overlooked throughout the history of electricity was realized. The type of lightning and its refraction angle with respect to the pathway of the electrical discharges seen in the air column, which is pushed by a buffer area of atmospheric fronts, or in the lower stable air flows moving from upper unstable air layers are the same in a given geographical region. The similarity seen in the refraction angles within the whole column of a lightning strike during grounding is quite impressive, as is the similarity in the shape of different lightning strikes at different times in history. When historical lightning photographs taken in the same geological region are examined, we can see that this shape has not changed in 100 years. The shape of lightning strikes seen at different times in the same region and relevant visual evidence have been collected.

The characteristic atmospheric features that create stable erosion and transportation properties are more important than geological stratigraphy and have a greater effect on our findings. The geological lithography of these areas is the second most impactful feature. The different types of suspended material involved in float laminarization processing during transportation is the reason a separated laminar column flow occurs under the same atmospheric conditions. The physical multi-layered separation these materials experience is the result of their varying physical properties, such as their static electric field, humidity, or internal relative displacements. Multi-laminar volumetric leakages of the same air density by the same type of suspended material occur at different heights in the main air column, with an increased number of layers occurring due to static electricity. The pathway of a lightning strike always has the same refraction shape, making this a regional marker of constant atmospheric conditions in a stable climate.

2.5. Ocean–Atmosphere Interaction Responses to Marine Heatwaves

Romaissa Harid ¹, Azzedine Hadef ²

¹ 

ECOSYSMarL: Laboratoire des Écosystèmes Marins et Littoraux, ENSSMAL: École Nationale Supérieure des Sciences de la Mer et de l’Aménagement du Littoral, Dély Ibrahim 16320, Algeria

² 

LIBEB: Laboratory of Interactions, Biodiversity Ecosystems and Biotechnology, University of 20 August 1955 Skikda, University of Skikda B.P. 26 El-Hadaik, Skikda 21000, Algeria

Ocean–atmosphere interaction is defined as the exchange of energy at the interface of the ocean and atmosphere. The ocean surface energy, which is largely related to Sea Surface Temperature (SST), determines the stability of the lower atmosphere and ocean surface ecosystems and mechanisms. Marine Heat Waves (MHWs) are characterized by Sea Surface Temperature hotspots, which are practically linked to increases in air temperature. This strongly influences phytoplankton production, causes the appearance of specific phytoplankton blooms, and indirectly impacts the marine food web. In this work, we used Sea Surface Temperature of MODIS remote sensing data and their equivalent daily Ocean Color MODIS remote sensing data for over 20 years in the Algerian Basin (South-Western Mediterranean Sea). Mainly, we found the location of Marine Heat Waves specific to the Algerian Basin. However, the Marine Heat Waves generate specific phytoplankton blooms in coastal areas which are highly related to seasonality (regional climate). For example, some phytoplankton species bloomed after days of increased sea surface temperature. Moreover, the days on which these specific phytoplanktonic blooms (such as the coccolithophore bloom) appeared are sometimes followed by rainy days because of the chemical composition of phytoplankton species (coccolithophore species live on the ocean surface and have limestone shells).

3. Session 2: Air Quality and Human Health

3.1. The Impact of Smog on Public Health and Antimicrobial Resistance in Pakistan

Muhammad Taqi Abbas, Mishaal Khawar, Zainab Munir

• Department of Biomedical Engineering, Riphah International University, Islamabad (Lahore Campus)

Introduction: Since 2016, smog has been an annual health and environmental crisis in Pakistan, commonly known as the “fifth season”. This hazardous phenomenon results from a combination of vehicle emissions, industrial pollution, crop residue burning, and fossil fuel consumption. Smog season intensifies in October, dropping visibility considerably while increasing respiratory problems and antimicrobial resistance. We seek to analyze the correlation between deteriorating air quality and rising public health concerns, specifically antimicrobial resistance.

Methods: This study was supported by multiple sources, including the existing literature, environmental data, air quality indices (AQIs), and public health reports, to assess the impact of smog on respiratory ailments and antimicrobial resistance. The global study on particulate matter proved to be resourceful. Additionally, we reviewed the data from the U.S. Environmental Protection Agency (EPA) and NASA’s research statistics regarding cross-border crop burning. The relation between airborne pollution levels and antimicrobial resistance rates was interpreted based on the direct correlation found between them.

Results: In 2024, Pakistan’s urban cities reported toxic AQI levels, with Multan reaching an unprecedented 1392, followed by Lahore (826), Peshawar (575), and Rawalpindi (271). A 10% rise in PM 2.5 levels caused a 2.6% increase in antimicrobial resistance in Pakistan. This led to premature deaths and difficulty in disease management. The government was forced to take temporary measures such as school closures, enforcing work-from-home policies, and limiting commercial activities. However, these short-term actions failed to deal with the root causes of pollution.

Conclusions: The smog crisis in Pakistan is causing serious environmental and public health concerns, particularly by accelerating antimicrobial resistance. Without resolute action, it will continue to jeopardize public health and strain the health care system. Policy recommendations involve stricter emissions standards, large-scale afforestation, investment in clean energy, and global collaboration to reduce crop burning. While emergency measures provide momentary relief, long-term sustainable solutions are necessary to mitigate the problem.

3.2. Assessment of Indoor Air Quality in an Academic Laboratory: A Comparative Study with a Controlled Room

Fabiana Carriera ¹, Cristina Di Fiore ¹, Alessia Iannone ¹, Gaetano Settimo ², Pasquale Avino ^{1, 3}

¹ 

Department of Agricultural, Environmental and Food Sciences (DiAAA), University of Molise, Via De Sanctis, 86100 Campobasso, Italy

² 

Environment and Health Department, Italian National Institute of Health, viale Regina Elena 299, I-00185 Rome, Italy

³ 

Institute of Atmospheric Pollution Research, Division of Rome, c/o Ministry of Environment and Energy Security, 00147 Rome, Italy

Introduction: University laboratories are complex environments characterized by confined spaces, high occupant density, and the frequent use of potentially hazardous chemicals. These factors contribute to elevated concentrations of airborne pollutants, which may pose health risks to students and laboratory personnel. Ensuring adequate indoor air quality (IAQ) is therefore crucial for safeguarding well-being and maintaining operational efficiency. This study aims to quantitatively assess IAQ in an analytical chemistry laboratory by comparing it with a controlled room under similar baseline conditions.

Methodology: Air quality was assessed using a DustTrak aerosol monitor for real-time measurements of particulate matter (PM) concentrations, specifically PM₁₀, PM_2.5, PM₁, and total PM. Measurements were conducted in both the laboratory and the controlled room to facilitate a direct comparison of environmental conditions.

Results: The findings indicate that PM_2.5 concentrations within the laboratory consistently exceeded the recommended exposure threshold of 15 µg/m³. This increase was particularly evident during student activities, suggesting that occupant presence and experimental procedures contributed to the emission and resuspension of particulate matter.

Conclusions: The elevated levels of particulate matter observed in the laboratory highlight the need for improved ventilation strategies and pollution mitigation measures. Maintaining optimal IAQ in laboratory environments is essential to protect the health and productivity of students and academic staff.

3.3. Exposure to PM_2.5 While Walking in the City Center

Anna Mainka ¹, Witold Nocoń ², Aleksandra Malinowska ³, Julia Pfajfer ³, Edyta Komisarczyk ³, Pawel Wargocki ⁴

¹ 

Department of Air Protection, Faculty of Energy and Environmental Engineering, Silesian University of Technology, Poland

² 

Department of Automatic Control and Robotics, Silesian University of Technology, Poland

³ 

Silesian University of Technology

⁴ 

International Centre for Indoor Environment and Energy, Department of Environmental and Resource Engineering, Technical University of Denmark

Physical activity, such as walking, plays a key role in preventing noncommunicable diseases. However, in urban environments, pedestrians are often exposed to elevated air pollution levels, especially fine particulate matter (PM_2.5), which poses significant health risks. This study investigates personal exposure to PM_2.5 while commuting on short walking routes in Gliwice, Poland, a city known for its high air pollution levels. It compares measurements made using a low-cost air quality sensor with data from stationary air quality monitoring stations and an air quality laboratory at the Silesian University of Technology (SUT). The aim of this study is to assess real-time PM_2.5 exposure and address data gaps for health risk assessments. This study was conducted between January and November 2022, focusing on the participants’ daily walking routines to the university campus. Data analysis included pollutant concentrations, environmental conditions, and statistical comparisons between different seasons (heating and non-heating). The results indicated that PM_2.5 levels measured by the low-cost sensor were lower than those recorded at the stationary sites, with average concentrations of 7.3 µg/m³ during both seasons. The stationary data from the monitoring station and the SUT laboratory reported higher average concentrations of 12.3 and 20.1 µg/m³, as well as 16.0 and 29.1 µg/m³, during the non-heating and heating season, respectively, showing statistically significant seasonal variations, unlike the low-cost sensor. The results suggest that low-cost sensors, while useful for real-time individual exposure monitoring, may lack the sensitivity needed to detect seasonal variations compared to reference-grade instruments. Overall, this study emphasizes the importance of appropriate measurement methods for assessing air quality and highlights the potential role of low-cost sensors in personal exposure tracking, raising awareness about air pollution.

3.4. Assessing Air Quality Through Biomonitoring of Neodymium in Urban and Rural Tree Bark Across Leicestershire (UK)

Antonio Peña-Fernández ^{1, 2}, Carmen Lobo-Bedmar ³, María de los Ángeles Peña ⁴

¹ 

Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Ctra. Madrid-Barcelona, Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.

² 

Leicester School of Allied Health Sciences, De Montfort University, Leicester LE1 9BH, UK.

³ 

Departamento de Investigación Agroambiental. IMIDRA. Finca el Encín, Crta. Madrid-Barcelona Km, 38.2, 28800 Alcalá de Henares, Madrid, Spain.

⁴ 

Departamento de Ciencias Biomédicas, Universidad de Alcalá, Crta. Madrid-Barcelona Km, 33.6, 28871 Alcalá de Henares, Madrid, Spain

Air quality for neodymium (Nd) was biomonitored in the English county of Leicestershire after low levels of the element were detected in topsoils from various urban parks in the city of Leicester. Thin layers of bark were collected from 55 and 41 trees growing in the city of Leicester and surrounding rural areas, respectively. Nd was monitored by ICP-MS in clean/ground/homogenised samples [LoD = 0.504 ng/g dry weight (dw)]. The levels of Nd were higher in bark samples collected in Leicester city (median and ranges, in ng/g dw): 8.382 (2.021–198.91) and 7.778 (1.577–59.123). The higher concentrations of Nd in bark collected from trees growing in Leicester could be attributed to its technological uses. The Nd content varied between bark samples collected in the four cardinal sub-areas into which the city was divided (medians, ng/g dw): 45.132 (SE) > 14.397 (SW) > 7.709 (NE) > 5.950 (NW). This trend differed from the concentrations found in trees growing in the three Leicestershire cardinal points (medians, ng/g dw): 28.175 (NW) > 7.215 (NE) > 1.772 (SE). Finding a hypothesis that could explain the differences found in airborne Nd content across the monitored region is challenging as the atmospheric transport of Nd is poorly understood. Our results show a high dispersion of Nd across Leicestershire, which would be little influenced by its distribution in the topsoil, as the enrichment factors obtained as a function of the average Nd and scandium content in the upper continental crust were lower than unity in both areas (0.383 and 0.423). However, further studies are needed to identify the potential sources of Nd that could have contributed to the observed trends, because the levels found were higher than those described in bark from trees growing in uncontaminated areas. The development of a ¹⁴³Nd/144Nd isotope map could help to distinguish sources of pollution.

3.5. Carcinogenic Health Risk for the Child Population of the City of Kazan (Tatarstan) Caused by Exposure to Atmospheric Air

Tansu Gazieva ¹, Natalya Stepanova ¹, Suryana Fomina ¹, Gulnaz Gataullina ¹, Karolina Maltseva ¹, Aygul Gayazova ¹, Elizaveta Kuznetsova ¹, Natalya Arkhipova ^{1, 2}, Niyaz Salahov ¹

¹ 

Department of Bioecology, Hygiene and Public Health, Kazan (Volga Region) Federal University, Kazan 420008, Russian Federation

² 

Kazan Federal University

Introduction: According to epidemiological research data, the regional quality of atmospheric air is the cause of considerable population morbidity growth, its vulnerable groups in particular.

Methods: The assessment of carcinogenic risk (ICR) for the health of children aged 3–6 years living in four zones of Kazan was performed corresponding to atmospheric air monitoring points. Data on air pollution (with formaldehyde, soot, and benzol) were obtained based on the research results of FSFHI “The Center of Hygiene and Epidemiology in the Republic of Tatarstan” for the years 2017–2023. A daily dose via the chronic inhalation route was calculated at the level of the upper 95th % of the confidence bound of average annual concentrations.

Results: An average annual level of carbon (soot) exceeded the standards in all zones by a factor of 2.32–9.96. A high level of ICR for children’s health was observed in all zones: 2.69 × 10⁻³ in the first zone; 6.68 × 10⁻² in the second; 7.4 × 10⁻³ in the third, and 1.18 × 10⁻² in the fourth zone. The highest levels of ICR exceeding the allowable level (1 × 10^–4) registered in the territories, where enterprises of the first and second classes of hazard (chemical complex) were concentrated, which was especially true of zones 2 and 4. In the residential area of the first and third zones with a high level of truck traffic load, the levels of ICR varied from 2.69 × 10⁻³ to 7.4 × 10⁻³, with the largest contribution of soot to its concentration value.

Conclusions: The results dictate the necessity of developing and implementing of such strategies reducing atmospheric emissions as transport and industry modernization and regulation, as well as organizing the continuous monitoring of pollutants for the efficient assessment of the total level of carcinogenic substances in residential zones.

3.6. Correlation Between Hair Element Concentration, Sex, and Body Mass Index in Young Italian Population

Alessia Iannone ¹, Debora Mignogna ^{1, 2}, Sergio Passarella ¹, Pasquale Avino ^{1, 2}

¹ 

Department of Agriculture, Environmental and Food Sciences, University of Molise, Via De Sanctis, 86100 Campobasso, Italy

² 

Institute of Atmospheric Pollution Research, Division of Rome, c/o Ministry of Environment and Energy Security, 00147 Rome, Italy

Introduction: Human hair is an excellent biological indicator for assessing human health conditions. It can provide an indication of mineral levels and accumulation of toxic metals resulting from long-term or acute exposure. This study investigates the relationship between the concentration of toxic elements in hair and Body Mass Index (BMI) in adolescents with no environmental or occupational exposure. The latter physiological factor influences the metabolism of both essential and toxic elements in the human body, providing a valuable diagnostic framework for various diseases.

Methodology: Instrumental Neutron Activation Analysis (INAA) was used for a highly sensitive and accurate element determination. The collected samples were pre-treated with acetone and drying before the analysis.

Results: The results obtained suggested the abundance of zinc (Zn) (100 µg g⁻¹), followed by iron (Fe), and copper (Cu), all with concentrations above 1 µg g⁻¹. A weak positive correlation was found between Zn and K, while magnesium (Mg) levels proportionally increased with BMI (173 ± 129 µg g⁻¹; 24.0 < BMI < 25.4). Further statistical analyses, including cluster analysis and principal component analysis, suggested low similarity between sulphur (S) and chlorine (Cl), which were indirectly associated with BMI. The data obtained have been studied and discussed with data from an inorganic fraction of particulate matter, PM₁₀ and PM_2.5, registering very low levels of the elements investigated (As = 1.06 ng m⁻³, Cr = 3.3 ng m⁻³, and Ni = 3.5 ng m⁻³ in fine granulometric fractions).

Conclusions: The results provide an important basis for assessing the effects of anthropogenic phenomena, such as atmospheric emissions, in urban areas. Although no significant correlations with BMI were found for any of the elements studied, the findings represent a baseline for further and more comprehensive understanding of the mechanisms of the accumulation or release of toxic elements in the bodies of individuals exposed in relation to BMI.

3.7. Evaluation of the Role of Natural and Anthropogenic Sources on Acellular and In Vitro Toxicity Indicators of AtmospherIc Aerosol (TOX-in-AIR): Preliminary Results

Antonio Pennetta ¹, Ermelinda Bloise ¹, Daniela Cesari ¹, Giuseppe Deluca ¹, Adelaide Dinoi ¹, Lorena Carla Giannossa ², Livia Giotta ³, Maria Rachele Guascito ³, Giulia Lionetto ³, Gianna Manelli ², Annarosa Mangone ², Serena Potì ^{1, 3}, Paola Semeraro ¹, Florin Unga ¹, Daniele Contini ¹

¹ 

Institute of Atmospheric Sciences and Climate—ISAC-CNR, 73100 Lecce, Italy

² 

Department of Chemistry, University of Bari Aldo Moro, 70126 Bari, Italy

³ 

Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy

Introduction: Fine particulate matter (PM_2.5) is a significant risk for public health. The mechanisms underlying its toxicity are still not fully understood, with contrasting results across acellular, cellular, and in vivo toxicity metrics. The TOX-IN-AIR project aims to analyse correlations between toxicity indicators and chemical composition, considering seasonal and site dependencies, and assess the contributions of natural and anthropogenic sources and their nonlinear interactions.

Methods: Two campaigns were conducted in winter and summer in Lecce, Italy. The Mobile Laboratory for Gas and Aerosol Measurements (MAGA) and the Environmental-Climate Observatory (ECO) platforms were used for the urban and urban background sites, respectively. PM_2.5 samples were collected on Teflon and quartz filters. Particle size distributions, meteorological data, and gas concentrations were measured online. In the laboratory, the PM_2.5 fraction was weighed, and subsequently, the chemical composition was measured by ED-XRF. The filters were then fractionated and subjected to (a) chemical characterization; (b) acellular determination of oxidative potential; and (c) cellular in vitro analysis.

Results and Conclusions: The PM_2.5 mass concentrations were very similar between the ECO and MAGA sites during both campaigns. Particle number concentrations (diameter ≤ 2.5 μm) were higher at the urban site compared to the suburban site, particularly during the winter period. Coarse particles (diameter ≥ 2.54 μm) were similar at the two sites. Peaks in coarse particles were observed during three days in both campaigns, attributed to long-range Saharan dust transport. The results of source apportionment by using the PMF receptor model will be presented.

This work was co-funded by Next Generation EU—Mission 4—Ministry of University and Research (MUR)—Call PRIN 2022 PNRR—Project TOX-IN-AIR, P2022JKPS.

3.8. Health Risk Assessment of Atmospheric Air Pollution: A Case Study of Adolescents and Adults in Kazan

Daniya Gizatullina, Mikhail Nikolaev, Daniyar Akberov, Tansu Gazieva, Amr Elbahnasawy, Suryana Fomina, Emiliya Valeeva, Natalya Stepanova, Rustem Saifullin

• Kazan (Volga region) Federal University, IFMB

Introduction: The state policy of many countries is aimed at reducing atmospheric air pollution. The purpose of this work is to assess the health risk of adolescents and adults associated with the impact of atmospheric air chemicals in the city of Kazan.

Materials and Methods: This study was carried out on the basis of the data of socio-hygienic monitoring (2015–2022). Non-carcinogenic risk assessments were carried out in accordance with Guideline 2.1.10.3968-23 to calculate the average daily doses for adolescents (14–17 years old) and the adult population. The total risk of carcinogenic effects (HQs) and the hazard index of non-carcinogenic effects (HIs) were calculated.

Results: The main contributors to the risk (HQ) for adolescents and adults in Kazan are carbon at 32.8%, nitrogen dioxide at 21.7%, PM₁₀ at 20.7%, formaldehyde at 8.5%, and PM_2.5 at 8.2%. Annual mean concentrations for the city of Kazan for carbon were 0.189 mg/m³, for nitrogen dioxide 0.081 mg/m³, for PM₁₀ 0.074 mg/m³, for formaldehyde 0.004 mg/m³, and for PM_2.5 0.02 mg/m³. The cumulative risk of non-carcinogenic effects is 4.1 (high risk) for adolescents and 2.9 (alarming risk) for adults. The highest toxic load is respiratory: HI = 3.8 for adolescents (alarming risk) and HI = 2.7 for adults (acceptable risk). Mortality indices are HI = 1.7 and HI = 1.2, respectively, remaining within acceptable limits. Dental and systemic diseases ranked third, with HI = 1.4 for adolescents and HI = 1.0 for adults.

Conclusions: The comparative assessment of non-carcinogenic effects in adolescents corresponds to a high level, requiring comprehensive risk reduction measures, while for adults it is alarming, requiring routine wellness interventions.

3.9. Health Risk Associated with Inhalation Exposure to Aromatic Hydrocarbons (BTEX) in the City of Novi Sad

Ljilja Torovic ¹, Stanka Bobić ², Slobodan Radišić ², Nataša Dragić ^{2, 3}, Sanja Bijelović ^{2, 3}

¹ 

Department of Pharmacy, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia

² 

Center for Hygiene and Human Ecology, Institute of Public Health of Vojvodina, 21000 Novi Sad, Serbia

³ 

Department of Hygiene, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia

Road traffic is one of the major sources of air pollutants, including aromatic hydrocarbons. The current study assessed the presence of benzene, toluene, ethylbenzene and xylenes (BTEX) in the City of Novi Sad’s ambient air and the health risk for its inhabitants.

A total of 686 24 h air samples were collected at two sites in the City of Novi Sad during 2024 and analyzed using a GC-MS method.

As expected on traffic sites, BTEX compounds were quantified in the majority of the samples: toluene 94.3% > benzene 88.3% > xylenes 75.6% > ethylbenzene 59.0%. The mean concentrations (µg/m³) of benzene and toluene were higher at urban traffic sites (1.7 vs. 1.3; 3.9 vs. 2.3), while ethylbenzene and xylenes reached higher means at suburban traffic sites (1.0 vs. 1.7; 2.6 vs. 4.2). Benzene’s annual concentration was in compliance with the calendar year limit established by Directive 2008/50/EC. The hazard index (HI), calculated as a sum of hazard quotients related to reference inhalation concentrations of individual compounds, was used as a measure of non-carcinogenic risk. The HI values on suburban (0.087) and urban traffic sites (0.085) indicated no health risk. Benzene and xylenes were the main HI contributors (>98%). The carcinogenic risk was based on benzene and ethylbenzene inhalation risk units. In the case of children, it was very similar on suburban and urban traffic sites (2.1 × 10⁻⁶ and 2.3 × 10⁻⁶), while in the case of adults, it was slightly higher on urban traffic sites (9.1 × 10⁻⁶ vs. 8.2 × 10⁻⁶). However, the health risk was low regardless of the population group. As expected, due to its higher inherent carcinogenic potential as well as its higher population exposure level, benzene showed a 2.5-fold higher impact on carcinogenic risk than ethyl benzene.

Although the estimated values of the risk indicators are low, it is of utmost importance to reduce exposure to carcinogenic compounds in ambient air.

3.10. Health Risks Associated with Inhalation Exposure to Benzo(a)Pyrene in the City of Novi Sad

Ljilja Torovic ¹, Stanka Bobić ², Slobodan Radišić ², Nataša Dragić ^{2, 3}, Sanja Bijelović ^{2, 3}

¹ 

Department of Pharmacy, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia

² 

Center for Hygiene and Human Ecology, Institute of Public Health of Vojvodina, 21000 Novi Sad, Serbia

³ 

Department of Hygiene, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia

Polycyclic aromatic hydrocarbons (PAHs) in the ambient air can pose serious health risks for humans when inhaled and are usually adsorbed on particulate matter (PM). The current study aimed to investigate the content of benzo(a)pyrene (BaP), the most famous representative of PAHs, in PM₁₀ (inhalable PM, with diameter up to 10 µm) in ambient air in the City of Novi Sad and to assess the associated health risks.

PM₁₀ sampling performed at five monitoring sites (basic-rural/urban, urban/suburban-traffic, industrial) in the City of Novi Sad during 2024 resulted in 1340 samples, which were analyzed using the GC-MS method.

The overall share of the samples with quantified amounts of BaP was 46.6 (53.8% basic-rural > 53.7% suburban-traffic > 49.3% industrial > 45.2% urban-traffic > 34.6% basic-urban site). The lowest mean concentration was recorded at the basic-urban site (0.5 ng/m³), while the highest was related to suburban-traffic (0.9 ng/m³); when averaged over all monitored sites, the BaP level was 0.7 ng/m³. The annual level of BAP was in compliance with regulatory requirements. The health risks were estimated using the hazard quotient (HQ) and lifetime cancer risk (LCR) approaches. The HQ was below the limit value of 1 in all monitored sites (0.24–0.47, overall average 0.37), indicating no risk. LCR was negligible for both children (from 4.5 × 10⁻⁸ to 8.0 × 10⁻⁸, mean 6.4 × 10⁻⁸) and adults (from 1.8 × 10⁻⁷ to 3.2 × 10⁻⁷, mean 2.5 × 10⁻⁷).

Although the estimated values of the risk indicators are low, the population is still exposed not only to BaP but also to other polycyclic aromatic hydrocarbons, with some of them also being carcinogens. As exposure occurs not only via inhalation but also through the consumption of foods such as grilled and smoked food, it is of utmost importance to reduce the population’s exposure to carcinogenic compounds via all relevant exposure pathways.

3.11. Health Risks Associated with Inhalation Exposure to Toxic Metal(loid)s in the City of Novi Sad

Sanja Bijelović ^{1, 2}, Danijela Lukic ², Milan Jovanović ², Nataša Dragić ^{1, 2}, Ljilja Torovic ³

¹ 

Department of Hygiene, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia

² 

Center for Hygiene and Human Ecology, Institute of Public Health of Vojvodina, 21000 Novi Sad, Serbia

³ 

Department of Pharmacy, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia

The toxic metal(loid)s bound to particulate matter (PM) in ambient air can cause serious harm to human health. The current study aimed to investigate the toxic element composition of PM₁₀ (diameter up to 10 µm) and to address the risks to human health.

Sampling of PM₁₀ was performed at five sites (basic-rural/urban, urban-/suburban-traffic, industrial) in the City of Novi Sad during 2024. A total of 1357 samples was subjected to microwave digestion followed by the ICP-MS determination of lead (Pb), cadmium (Cd), arsenic (As), and nickel (Ni) content.

The overall share of the samples with quantified amounts of elements was 85.3% Pb > 65.2% As > 36.6% Cd > 27.7% Ni. The lowest mean concentrations (ng/m³) were recorded at the basic-urban site (Pb 4.5, Cd 0.15, As 0.80, Ni 3,0), while the highest were related to the suburban-traffic (Pb 5.9, Cd 0.24, As 0.83) and urban-traffic site (Ni 4.2); the order of the concentrations averaged over all monitored sites (ng/m³) was as follows: Pb 5.1 > Ni 3.4 > As 0.80 > Cd 0.20. The Hazard index (HI), an indicator of non-carcinogenic risk, ranged from 0.29 in the basic-rural/urban to 0.38 in the suburban-traffic site, with a mean of 0.32 (averaging over all the sites), revealing no health risk. Ni was the element with by far the highest contribution to non-carcinogenic risk (68.3%). Carcinogenic risk for children ranged from 6.8 × 10⁻⁷ (basic-urban) to 7.6 × 10⁻⁷ (urban-traffic), with a mean of 7.2 × 10⁻⁷, showing negligible risk. In the case of adults, carcinogenic risk varied only slightly, with a mean of 2.9 × 10⁻⁶, indicating low risk. As was the element with by far the highest contribution to carcinogenic risk (68.7%), followed by Ni (16.1%), Pb (8.0%), and Cd (7.2%).

Considering that toxic metal(loid)s are ubiquitous contaminants, low levels of risk indicators related to the inhalation exposure are not enough to ensure protection of human health.

3.12. Issues and Challenges Around Classification of Respiratory Sensitizers/Allergens in the United Nations Globally Harmonized System

Wells Utembe ^{1, 2}, Charlene Andraos ^{3, 4, 5}

¹ 

National Institute for Occupational Health, National Health Laboratoty Service

² 

Environmental Health Division, School of Public Health and Family Medicine, University of Cape Town, 7925, South Africa

³ 

Toxicology and Biochemistry Department, National Institute for Occupational Health (NIOH), National Health Laboratory Services (NHLS), Johannesburg 2000, South Africa

⁴ 

School of Public Health, University of the Witwatersand, Johannesburg 2193, South Africa

⁵ 

Unit for Environmental Sciences and Management, Faculty of Natural and Agricultural Sciences, North West University, Potchefstroom, 2531

Introduction: The United Nations Globally Harmonized System (GHS) of classification and labelling provides specifications for the classification, management, and communication of hazards, crucial for protecting workers and consumers. However, issues and challenges exist in its application, particularly concerning respiratory sensitizers, many of which can become airborne pollutants in occupational settings and in broader environments, where they may engulf entire regions.

Methods: This is a narrative review that assesses relevant GHS documents and internationally accepted methods for determining respiratory sensitizers.

Results: Chemical sensitization is complex and depends on factors like allergen nature, dose, and exposure route, including inhalation. Sensitization initially involves the induction of specialized immunological memory in an individual by exposure to an allergen, followed by elicitation, which is the production of an allergic response following exposure of a sensitized individual to an allergen. Consequently, predictive tests also involve both induction and elicitation, followed by classification as Category 1, 1A or 1B, depending on the evidence. Unfortunately, GHS classification relies heavily on epidemiological data captured retrospectively with diagnostic testing rather than on prospective (predictive) data. Moreover, there are issues regarding the potency of chemicals and absence or presence of no-adverse-effect levels (NOAELs). Accurately assessing airborne exposure to sensitizers can be challenging, especially in complex environments, making it difficult to establish clear dose–response relationships. Lastly, the potential for certain respiratory sensitizers to become airborne and persist in the atmosphere increases the risk of prolonged inhalation exposure, underscoring the necessity for accurate GHS classification.

Conclusions: Challenges exist in interpreting results and accurately classifying sensitizers, potentially underestimating risks associated with airborne exposure. Users of GHS SDSs and labels must be aware of these limitations, particularly concerning inhalation exposure and potential airborne pathways. Further research is needed to improve GHS classification and understanding of the atmospheric behavior of sensitizers.

3.13. Lanthanum Biomonitoring Using Tree Bark: Urban vs. Rural Patterns in Leicestershire, the UK

Antonio Peña-Fernández ^{1, 2}, Carmen Lobo-Bedmar ³, Manuel Higueras ⁴, Gurminderjeet S. Jagdev ², María de los Ángeles Peña ⁵

¹ 

Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Ctra. Madrid-Barcelona, Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain

² 

Leicester School of Allied Health Sciences, De Montfort University, Leicester LE1 9BH, UK

³ 

Departamento de Investigación Agroambiental. IMIDRA. Finca el Encín, Crta. Madrid-Barcelona Km, 38.2, 28800 Alcalá de Henares, Madrid, Spain

⁴ 

Scientific Computation & Technological Innovation Center (SCoTIC), Universidad de La Rioja, Logroño, Spain

⁵ 

Departamento de Ciencias Biomédicas, Universidad de Alcalá, Crta. Madrid-Barcelona Km, 33.6, 28871 Alcalá de Henares, Madrid, Spain

The presence and distribution of lanthanum (La) in the topsoil and wild edible mushrooms in the English city of Leicester could pose some risks to the population. A biomonitoring study was carried out to determine the air quality for La across the region of Leicestershire. Bark samples (2–6 mm thick) were collected from 55 trees in the city and 41 surrounding rural areas. La was measured using ICP-MS in appropriately mineralised samples [LoD = 0.00068 ng/g dry weight (dw)]. Higher levels were found in the bark collected from the trees growing in Leicester (median and ranges, in ng/g dw)—9.679 (2.128–150.769) vs. 8.344 (1.815–59.801)—a distribution consistent with the trend found in the topsoils and which could be attributed to its technological use and traffic volumes. The La content varied between the bark samples collected in the three cardinal sub-areas into which Leicestershire was divided (medians, ng/g dw): 29.772 (NW) > 7.855 (NE) > 2.027 (SE). However, this pattern was different to the distribution of La in the topsoil samples monitored across Leicestershire, which showed statistical significance (p-value = 0.03997, medians, mg/kg): 25.874 (SE) > 24.290 (NE) > 19.470 (SW) > 13.401 (NW). In general, our results showed lower airborne La contamination in Leicestershire, which is supported by the lower levels of La in the bark from the monitored trees compared to those reported in the literature for trees growing in uncontaminated areas, and low enrichment factors (0.383 and 0.393) in the urban and rural areas, which were calculated using the averages in the Earth’s continental crust and the scandium content. Moreover, the enrichment calculated in the topsoils (1.118 and 0.909) also suggests little anthropic influence on the presence/distribution of this metal in the English region studied. Leicestershire’s atmosphere represents a minimal risk to the population in terms of La.

3.14. Occurrence of Persistent Chemical Pollutants, Heavy Metals, in Regions Influenced by Different Human Activities by Means Honey Matrix

Sergio Passarella ^{1, 2}, Sonia Ganassi ^{1, 2}, Alessia Iannone ^{1, 2}, Fabiana Carriera ^{1, 2}, Ivan Notardonato ^{1, 2}, Antonio De Cristofaro ^{1, 2}, Pasquale Avino ^{1, 2}

¹ 

DiAAA, University of Molise, via De Sanctis, 86100 Campobasso, Italy

² 

IIA-CNR, Rome Research Area-Montelibretti, 00015 Monterotondo Scalo, Italy

Introduction

The insect’s body may potentially absorb pollutants from its surroundings while it is in flight. Furthermore, the sources of bee products, such as pollen, nectar and water, can be exposed to environmental contaminants, which can be transferred to bee products. Because of these characteristics, bees and honey are low-cost tools that are increasingly being used for environmental biomonitoring, which seeks to detect environmental contaminants within a reasonable radius (1.5–3 km) surrounding the hive. Heavy metals, defined as inorganic chemical pollutants, are a class of contaminants that can be found either in nature or as a result of anthropogenic activity. Anthropogenic sources of heavy metals encompass a wide range of activities, including mining, smelting, vehicle emissions, and the production of cosmetics. These pollutants are of particular concern due to their ability to generate reactive oxygen species (ROS) and disrupt vital bodily functions. This study investigates heavy metals in honey to verify the safety of the honey and evaluate environmental pollution in specific areas, highlighting the interconnectedness of honey and the environment.

Methods

Honey samples, collected from six hives located in the Molise Region of Italy, were mineralised and then analysed with ICP-AES, in accordance with the EPA method 6010C.

Results

The most common metals are aluminium, selenium and antimony. Cobalt, nickel, and cadmium exhibit the highest levels of variability, with standard deviations of 253.3%, 207.2% and 82.4%, respectively. Principal component analysis (PCA) and Pearson correlation were usedto ascertain which metals most accurately represent the data sample and how they are associated with each other in order to hypothesise the anthropic pollution sources.

Conclusions

In the atmospheric domain, forest fires and vehicular traffic were identified as the two main sources of anthropogenic pollution.

3.15. Urban Green Spaces and Human Health: Assessing the Allergenic Potential

Aboubakr Boutahar ^{1, 2}, Paloma Cariñanos ³

¹ 

Biology, Ecology, and Health Laboratory, Department of Biology, Faculty of Sciences of Tetouan, Abdelmalek Essaâdi University, Mhannech II, Tetouan 93002, Morocco

² 

Biology, Environment, and Sustainable Development Laboratory, ENS, Abdelmalek Essaadi University, Tetouan 93000, Morocco

³ 

Department of Botany, Faculty of Pharmacy, University of Granada, 18071 Granada, Spain

Urban green spaces play a vital role in enhancing ecological balance, providing recreational opportunities, and supporting public health in cities. However, their allergenic potential presents significant challenges, especially in areas where urban vegetation planning does not account for the impact of allergenic plant species. This study focuses on evaluating the allergenic risks associated with the Moulay Rachid Garden, a key public park in Tetouan, northern Morocco, that is characterised by a Mediterranean climate. By analysing the park’s vegetation composition and calculating IUGZA values, the research explores the relationship between urban green space design and allergenic risks. The findings highlight how both native and introduced plant species influence pollen concentrations, with direct implications for public health. This study emphasises the importance of strategic vegetation management to reduce allergenic risks. It advocates for hypoallergenic green space planning as a critical approach to promoting climate resilience, improving public health, and creating more sustainable urban environments. In addition, the results underline the significance of considering allergenic potential in urban planning, particularly in Mediterranean and African contexts, where plant diversity and climate conditions create unique challenges. This research contributes to the growing body of knowledge on urban green spaces and their role in fostering healthier, allergy-aware cities.

4. Session 3: Biometeorology

4.1. Trends in Intense Heat and Cold Conditions in Cuba

Beatriz Velázquez ¹, Antonio Vladimir Guevara ¹, Osniel Armas ²

¹ 

Instituto de Meteorología (INSMET) La Habana-Cuba

² 

Empresa Cubana de Navegación Aérea (ECNA)

Climate change has various negative environmental consequences, such as rising temperatures and the intensification of extreme weather events. These repercussions represent one of the greatest challenges for sustainable development and the population’s well-being. Heat/cold waves are among the meteorological events associated with climate change. A trend analysis should be used to assess the change in the behavior of a variable over long periods. Therefore, the objective of this work was to analyze the trends in extreme heat and cold events, expressed through the indicators of Intense Cold Conditions and Intense Heat Conditions, during the period 1981–2023. This study covered the entire country, and 67 meteorological stations belonging to the Institute of Meteorology’s network of stations were used. The existence of a trend is determined mainly using the Mann–Kendall statistic (Sneyers, 1975), in the direct and inverse sense, and change points are determined using Pettitt’s test. The Spearman’s and Wald–Wolfowitz tests were used as alternative tests. The significance level was chosen as 0.05 since the 95th percentile provides a good result in meteorology. In general, the existence of highly significant increasing trends was confirmed in the series corresponding to CCIsv and CCIcv in Cuba. However, this did not occur for CFIsv and CFIcv, for which, although they showed a lower number of cases in recent years in the multiannual analyses, the existence of trends could not be confirmed.

4.2. And for Those Outside the Center of the Gaussian? An Analysis of the Needs and Potential Responses for Elderly and Disabled People Living in the Urban System

Letizia Cremonini ¹, Teodoro Georgiadis ², Marianna Nardino ¹, Federico Carotenuto ¹, Edoardo Fiorillo ¹

¹ 

CNR—Institute for the BioEconomy

² 

Institute for the BioEconomy—IBE

Climate change in urban areas is not neutral concerning different social groups and vulnerable people. People such as the elderly or people with disabilities are more exposed in terms of vulnerability than the rest of the population simply because they are less mobile. This is not the only aspect to be taken into account; in fact, the vulnerabilities mentioned above are often linked to situations of chronic illness, low social income, and potential situations of energy poverty, which prevent de facto protection from heat waves, at least in one’s own home. The protection of those beyond the limits of the average individual is, therefore, a major social and economic challenge in a system of “advanced countries” in which the demographic pyramid of the young population is shrinking and that of the elderly is growing considerably, which is also thanks to developments in medicine and quality of life. The first results of the European CARMINE project are presented, which, in a specific study area (the metropolitan city of Bologna, Italy), aimed to study the mobility pathways of these frailties to reach potential markets and to identify the NBS that could potentially be used along the highlighted pathways to protect the physiological balance of these sectors of the urban population.

5. Session 4: Meteorology

5.1. An Analysis of Fire Dynamics in the State of Alagoas and Their Relationship with Meteorological Variables

Katyelle Ferreira da Silva ^{1, 2}, Helber Barros Gomes ^{1, 2}, Janaína M. Pinto do Nascimento ^{3, 4}, Marisol Osman ^{5, 6}, Maria Cristina Lemos da Silva ^{1, 2}, Daniel Milano Costa de Lima ⁷, Heliofábio Barros Gomes ^{1, 2}, Mayara Christine Correia Lins ^{1, 2}, Fabrício Daniel Silva dos Santos ^{1, 2}, Glauber Lopes Mariano ^{1, 2}, Thomás Rocha Ferreira ^{1, 2}, Paulo Vítor de Albuquerque Mendes ^{1, 2}, Antonella Awanes Santos ¹

¹ 

Federal University of Alagoas

² 

Institute of Atmospheric Sciences—ICAT

³ 

Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA

⁴ 

NOAA OAR Global Systems Laboratory (GSL)

⁵ 

Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Ciencias de la Atmósfera y los Océanos

⁶ 

CONICET—Universidad de Buenos Aires, Centro de Investigaciones del Mar y la Atmósfera (CIMA), CNRS—IRD—CONICET—UBA, Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI), Buenos Aires, Argentina

⁷ 

Federal University of Campina Grande

Studies that address the dynamics of fires in the state of Alagoas and their relationship with meteorological conditions remain scarce, especially ones that use Machine Learning in their methodology. Thus, to analyze the spatiotemporal dynamics of fires in the state of Alagoas and their relationship with meteorological variables, daily data from the VIIRS active fire detection product (on board the S-NPP and NOAA-20 satellites) were used to analyze fires from 2012 to 2023 in the state of Alagoas. The dataset was filtered, including only Fire Radiative Power (FRP) values above zero and considering only detections that were greater than 24 h. Subsequently, the clustering methodology of Nascimento et al. was used, using the DBSCAN algorithm to identify and group fires. To analyze the behavior of meteorological variables, a range of ERA5 reanalysis variables were used. The results showed significant variability in the climatology of the FRP and Fire Radiative Energy (FRE), where the highest FRP averages occurred in the months of October to March, with the highest records occurring mainly in January (~10 MW/h), February (~9 MW/h), March (~9 MW/h), and December (~9 MW/h). During these months, the climatology of temperature at 2 m presented the highest records, mainly in the sertão (~37 °C). In addition, the climatology of relative humidity varied between 0 and 50% throughout these months in the sertão, coastal, and forest zone regions. The climatology of the FRE presented the highest averages in the months of November (~9000 MJ) and December (~8000 MJ), where the highest records of wind speed were obtained, mainly on the coast and in the forest zone (~6 m/s). The highest concentrations of FRP and FRE and the longest stretch of days of fires occurred on the coast and in the forest zone.

5.2. An Evaluation of the Impact of Emissions from Airports in Egypt

Zeinab Salah, Rania EZZ-ELDEEN, Mostafa Salmoon, Ahmad Elattar

• Egyptian Meteorological Authority

Studying the impact of aircraft emissions on the climate and environment is a complex and important issue, especially given the increasing frequency of extreme weather events linked to climate change. In this study, we examine the potential impact of aircraft emissions from four Egyptian airports on their surrounding areas using the Graz Lagrangian dispersion model (GRAL). Furthermore, we investigate how climate change may interact with potential increases in airport capacity in the future. To analyze the dispersion of pollutants emitted by aircraft at the selected airports, we utilized the GRAL model, which incorporates various inputs related to emission sources and meteorological data. The meteorological data for the studied periods (2021, 2025, 2030, and 2035) were derived from the output of the ICTP regional climate model (RegCM4), using the RCP4.5 climate change scenario as input for the dispersion model. The emissions were calculated based on the expected emissions from several aircraft types during 2021, which served as our reference year. We assumed that airport capacity would increase over the coming years until 2035, leading to an expected rise in pollutants emitted by aircraft. Our results indicate that, based on projected rates of emissions for carbon monoxide, sulfur dioxide, and nitrogen oxides, an increase in the capacity of these airports will not result in pollutant concentrations exceeding the maximum limits established by Egyptian Environmental Law, either at the airports or in the surrounding areas.

5.3. Estimation of Irrigated Tea Evapotranspiration Using Micrometeorological Modeling in Data-Scarce Environment

Phathutshedzo Eugene Ratshiedana ¹, Tumelo Shwatja ²

¹ 

School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South Africa

² 

Geo-information sciences, Agricultural Research Council–Natural Resources and Engineering, Pretoria 0083, South Africa

Water scarcity has become a critical and concerning global issue due to climate variability and demographic changes. The increasing demand for food and fiber places immense pressure on the agricultural sector to meet the needs of a growing population, which often requires large volumes of water for irrigation in water-limited environments. This leads to significant water loss through evapotranspiration (ET), which is the combined water loss through evaporation and plant transpiration. ET also shows the volume of water that must be replenished in subsequent irrigation schedules. In South Africa, a major challenge in irrigation management is the lack of measured actual evapotranspiration (ETa) data due to the limited availability of measurement devices. To address this, micrometeorological models offer a practical alternative. This study estimated crop evapotranspiration (ETc) using the Priestley–Taylor and Makkink models, validated against the Penman–Monteith standard model. The results revealed that both the Priestley–Taylor and Makkink methods effectively quantified ETc, with the Priestley–Taylor method showing higher accuracy. These findings show that in the absence of direct ETa measurements, ETc can be reliably estimated using meteorological data, enabling precise adjustments to irrigation schedules. This contributes to improved irrigation water management, promoting the conservation of scarce water resources while ensuring irrigation efficiency.

5.4. Evaluation of an Integrated Low-Cost Pyranometer System for Application in Household Installations

Theodore Chinis ¹, Spyridon Mitropoulos ¹, Pavlos Chalkiadakis ², Ioannis Christakis ²

¹ 

Department of Surveying and Geoinformatics Engineering, University of West Attica, 28, Ag. Spyridonos Str., 12243 Egaleo, Greece

² 

Department of Electrical and Electronic Engineering, University of West Attica, P. Ralli & Thivon 250, 12244 Egaleo, Greece

The climatic conditions of a region are a constant object of study, especially in our days as climate change is clearly affecting the way and quality of life, and are studied through meteorological data. Meteorological installations include a set of sensors to monitor the meteorological and climatic conditions of an area. Meteorological data parameters comprise measurements of temperature, humidity, precipitation, wind speed and direction, and instruments include oratometers and pyranometers, etc. Specifically, the pyranometer is a high-cost instrument that has the ability to measure the intensity of sunshine on the surface of the earth, expressing measurements in Watt/m². In this research work, both the implementation and the evaluation of an integrated low-cost pyranometer system are presented. The proposed pyranometer device consists of affordable modules: both the microprocessor and sensor. In addition, a central server, as an information system, was created for data collection and visualization. The data from the measuring system is transmitted via a wireless network (Wi-Fi), over the Internet, to an information system (central server), which includes a database for collecting and storing the measurements, and visualization software. The end user can retrieve the information through a webpage.

5.5. GNSS Meteorology and Machine Learning for Nowcasting: A Two-Step Approach to Precipitation Prediction

Laura Profetto ^{1, 2}, Alberto Ortolani ^{2, 3}, Giovanna Maria Dimitri ¹, Luca Fibbi ^{2, 3}, Andrea Antonini ²

¹ 

University of Siena

² 

LAMMA Consortium

³ 

CNR—IBE

Global Navigation Satellite System (GNSS) Meteorology has emerged as a valuable tool for atmospheric monitoring, providing high-resolution, near-real-time data that can significantly enhance nowcasting applications. By analyzing GNSS signal delays caused by atmospheric water vapor, it is possible to retrieve accurate estimates of Precipitable Water Vapor (PWV), a crucial parameter in short-term weather forecasting. This study presents a novel two-step machine learning framework for precipitation nowcasting, integrating GNSS-derived PWV with meteorological observations.

In the first step, a Random Forest (RF) model estimates precipitation based on GNSS-derived PWV, surface weather parameters, and auxiliary atmospheric variables. In the second step, a Long Short-Term Memory (LSTM) network predicts precipitation for the next hour, leveraging temporal dependencies within the data to improve forecasting accuracy. This hybrid approach combines the ability of RF to capture nonlinear relationships with the strength of LSTM in modeling sequential patterns.

The proposed methodology demonstrates interesting performance as compared to traditional forecasting models, particularly for extreme weather events such as intense rainfall and thunderstorms. The integration of GNSS meteorology with advanced machine learning techniques enhances short-term precipitation forecasting, offering a reliable tool for meteorological services, disaster prevention agencies, and early warning systems. This study highlights the potential of GNSS-based nowcasting for real-time decision-making in weather-related risk management.

5.6. Influence of Quasi Biennial Oscillation(QBO) on Tropical Cyclones in North Indian Ocean from 1979 to 2017

Dhruba Banerjee

• Faculty Member, Department of Physics, Swami Vivekananda Institute of Science and Technology, Dakshin Gobindapur, South 24 parganas, West Bengal 700145, India

This study investigates the occurrence of tropical cyclones in the North Indian Ocean region, examining the influence of solar activity on the Quasi-Biennial Oscillation (QBO) and El Niño-Southern Oscillation (ENSO). The primary objective is to assess the impact of QBO and ENSO on tropical cyclone formation. The equatorial QBO anomaly is analyzed across pressure levels ranging from 10 hPa to 70 hPa, with a particular focus on 30 hPa, using data from the Freie Universität Berlin. To establish a correlation, a normalized occurrence rate of tropical cyclones was derived following the methodologies of Sonnemann and Grygalashvyly (2007) and Ekaterina Vorobeva (2019).

Between 1979 and 2017, a total of 389 tropical cyclones formed in the North Indian Ocean, specifically in the Bay of Bengal and the Arabian Sea. This study primarily examines cyclonic activity during the pre-monsoon (May–August) and post-monsoon (October–December) seasons, utilizing data from the India Meteorological Department (IMD). The results indicate that tropical cyclones predominantly occur during the easterly QBO phase, with 24 out of 39 years exhibiting easterly winds and 15 years experiencing westerly winds.

Statistical analyses, including regression analysis, correlation coefficients, and tests of statistical significance, reveal a strong positive correlation between QBO and tropical cyclone activity. Specifically, a correlation coefficient of 0.7 suggests a significant association between QBO variations and cyclone occurrence in this region.

5.7. Insights into Lightning Activity in Cuba Using GOES-16 GLM Observations

Daniela Lobaina Castillo ¹, Adrián Luis Ferrer-Hernández ², Lourdes Álvarez-Escudero ², Albenis Pérez-Alarcón ^{3, 4}

¹ 

Department of Meteorology, Instituto Superior de Tecnologías y Ciencias Aplicadas (InSTEC), University of Havana

² 

Centro de Física de la Atmósfera, Instituto de Meteorología (INSMET), La Habana, Cuba

³ 

Centro de Investigación Mariña, Environmental Physics Laboratory (EPhysLab), Universidade de Vigo, Campus As Lagoas s/n, 32004 Ourense, Spain

⁴ 

Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal

Lightning is a natural hazard that significantly impacts human safety, infrastructures, and ecosystems. In recent decades, it has been monitored as a key indicator of severe weather and to understand climate change. This work examines the behaviour of lightning in Cuba from 2018 to 2022 using the Geostationary Lightning Mapper (GLM) onboard the Geostationary Operational Environmental Satellite 16 (GOES-16). We focused the analysis on the annual trends and spatial distribution of the keraunic level, i.e., the number of thunderstorm days and the total and cloud-to-ground lightning flash density. Our results showed a GLM efficiency of ~60–70% for detecting thunderstorms, which is aligned with previous studies using surface weather station data. In addition, we obtained an equation to determine the relationship between the number of thunderstorm days and the cloud-to-ground lightning flash density per year over an area of 1 km². Overall, this research resulted in the first keraunic level map developed for Cuba, using geostationary satellite data, and it provided the first maps of the total and cloud-to-ground lightning flash density. Although the keraunic level values were underestimated compared with reports from weather stations, they captured the characteristic climatic behaviour of thunderstorms in the study area. In summary, our findings demonstrate the feasibility of using GLM data to study thunderstorms and lightning activity in Cuba.

5.8. On the Architecture of a Meteorological Station Based on the Internet of Things (IoT)

Diego Abraham Jasso Reyes ¹, Carlos Iván Cabrera Perdomo ¹, Raúl Alberto Reyes Villagrana ²

¹ 

Unidad Académica de Ciencia y Tecnología de la Luz y la Materia, Universidad Autónoma de Zacatecas, Parque Científico y Tecnológico QUANTUM Ciudad del Conocimiento, C.P. 98160, Zacatecas, Zacatecas, México

² 

Investigador por México de la SECIHTI—Universidad Autónoma de Zacatecas, México

The state of Zacatecas, Mexico, has a territorial extension of 75,275.3 km² and is located in the center-north of the country. The climate of Zacatecas is classified as arid and semi-arid. However, in recent decades, the climate in the region has changed, making it necessary to observe, predict, and determine which renewable energy source would be ideal for supporting the metereological sector, depending on the region. Agriculture and livestock farming are also affected. For this reason, the description of a portable prototype that is designed, developed, and implemented to measure meteorological variables and obtain indirect variables is presented. A microcontroller from the Arduino family was used for this purpose. The variables of temperature, humidity, and atmospheric pressure were measured. The variables of the UV index, thermal sensation, dew point, altitude above sea level, and air density were measured indirectly. An interface was created to check the data in real time via the Internet. The information can be checked from a cell phone, an electronic tablet, or a computer using a program developed in the HTML language. The information can also be stored on a micro-SD memory device. The first results were collected over 45 days. The sampling of the data that were read by the system took 10 s. The data were compared with those obtained from a commercial meteorological station, which produced similar results. The design of the meteorological station will be further improved by adding new measurement variables and setting up a series of portable stations in different regions of the state.

5.9. Severe Wind Shear at Soekarno–Hatta International Airport: The Role of Sea Breeze Front and Meteorological Factors

Yesi Ratnasari, Finkan Danitasari

• Meteorology, Climatology, and Geophysic Agency for Indonesia (BMKG)

Wind shear presents a significant hazard to aviation, particularly during critical flight phases such as takeoff and landing. On 12 February 2025, six aircraft at Soekarno–Hatta International Airport conducted go-arounds due to wind shear events between 07:35 UTC and 08:37 UTC. This study employs meteorological observations (AWOS and METAR), remote sensing data (Doppler radar and wind profiler), and pilot reports (PIREPs) to investigate the underlying meteorological mechanisms and assess the effectiveness of issued warnings.

Doppler radar detected a Sea Breeze Front (SBF) moving inland, which created sharp thermal and pressure gradients, further intensifying wind shear along the final approach path. Wind profiler data revealed substantial vertical wind variations of up to 3000 m, while surface observations recorded gusts reaching 28 knots, indicating significant near-surface turbulence. METAR reports issued “WS ALL RWY” (wind shear affecting all runways) warnings at 07:30 UTC and 08:00 UTC, coinciding with pilot-reported wind shear encounters. Additionally, Wind Shear Warnings and an Aerodrome Warning for strong winds were disseminated via the Aeronautical Message Handling System (AMHS) and other communication channels, ensuring timely and effective communication with relevant stakeholders. This proactive approach enabled air traffic controllers and flight crews to implement risk mitigation measures, minimizing operational disruptions.

These findings offer crucial insights into the operational impacts of wind shear and underscore the need for continuous advancements in meteorological support for aviation. Strengthening early warning systems and fostering interdisciplinary collaboration between meteorologists, air traffic controllers, and pilots are essential for enhancing aviation safety, particularly in tropical regions prone to localized wind shear phenomena.

5.10. Unveiling Mechanisms Behind Typhoon Track Sensitivity and Predictability over Different Topographies: A Dynamic Modeling Perspective

Hung-Cheng Chen

• School of Mechatronics and Intelligent Manufacturing, Huanggang Normal University, Huanggang, Hubei 438000, China

This study investigates the intricate dynamics of typhoon-like vortex track deflections over complex terrain, explicitly focusing on Taiwan Island. We develop a novel dynamic model based on the conservation of potential vorticity (PV) that incorporates a topographic adjusting parameter (α) and a meridional adjusting velocity (MAV) to capture the vortex’s response to terrain variations. We elucidate the fundamental mechanisms driving track sensitivity and predictability using idealized simulations and real-case scenarios that use Taiwan’s topography. Our results show that steeper terrain gradients consistently deflect tracks, with this topographic steering effect amplified for stronger vortices due to their more significant α value, leading to an enhanced MAV and more pronounced deflections. Shallower impinging angles, resulting in prolonged interactions with steep terrain, further enhance these deflections. We identify distinct Track Diverging Zones (TDZs) and Track Converging Zones (TCZs) associated with Taiwan’s Central Mountain Range (CMR), highlighting the significant impact of the initial position of a vortex and terrain resolution on forecast reliability. The model successfully captures the key features of vortex–topography interactions, providing a physical basis for understanding the observed variability in typhoon tracks near Taiwan. This work demonstrates the practical value of a dynamic modeling perspective and PV analysis in improving typhoon track forecasting and risk assessments in regions with complex topography. It suggests that future research should focus on refining numerical models.

6. Session 5: Atmospheric Techniques, Instruments and Modeling

6.1. Advances in Remote Sensing and Machine Learning Techniques for Air Quality Monitoring

Alexander Uzhinskiy

• Meshcheryakov Laboratory of Information Technologies, Joint Institute for Nuclear Research, 6 Joliot-Curie, Dubna 141980, Russia

Various techniques are used to assess air quality. Basic parameters such as particulate matter (PM) and certain gases can be easily obtained from local meteorological stations. However, for more detailed data, such as heavy metal concentrations, researchers must collect and analyze samples in laboratories. Due to natural limitations, regulatory monitoring is often restricted in both spatial and temporal coverage.

Satellite imagery provides a valuable source of atmospheric and surface data. Each year, new missions with advanced sensors enhance remote sensing capabilities. Modern instruments like Sentinel-5 offer near-ready air quality data, including information on gases and aerosols. However, the Sentinel-5’s orbital cycle and resolution remain limited. Meanwhile, widely used public satellite missions such as Landsat, MODIS, and Sentinel provide high-resolution data with frequent updates. Integrating in situ measurements with satellite data and machine learning techniques enhances air quality monitoring. Modeling helps fill gaps in in situ data, provides detailed assessments of specific areas, and enables a partial automation of environmental control processes.

This report reviews widely used satellite-based programs, tools for efficient data processing, and machine learning approaches for air quality estimation. It highlights the effectiveness and advantages of ML-driven remote sensing for air quality monitoring. Additionally, we discuss commercial satellite missions, firsthand experiences, and future directions for advancing air quality monitoring technologies.

6.2. An Analysis of the Association Between Polycyclic Aromatic Hydrocarbon Pollution and Environmental Factors in the Urban Atmosphere

Minyi Wang, Kameda Takayuki

• Graduate School of Energy Science, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan

Polycyclic aromatic hydrocarbons (PAHs) are key atmospheric pollutants with significant carcinogenic potential that pose serious environmental and public health challenges due to their wide distribution and complex sources. In the atmosphere, PAHs exist in both gas and particle phases, with their concentrations and distributions influenced by atmospheric pollutants and meteorological conditions. This study systematically analyzed urban atmospheric PAHs using high-resolution spatiotemporal sampling data obtained from long-term monitoring. By integrating major atmospheric pollutants and meteorological parameters, spatiotemporal variations, potential sources, and complex environmental interactions of PAHs were comprehensively explored. Advanced machine learning algorithms and statistical methods were employed to identify the key factors driving PAH concentration changes and to reveal nonlinear associations with meteorological conditions and pollution sources. The results indicated significant seasonal and spatial variations in PAH concentrations, highlighting the influence of specific meteorological factors such as temperature, wind speed, and atmospheric pressure. Furthermore, the optimization of clustering and association rule mining algorithms allowed for more precise identification of emission sources and their interactions with environmental variables. These findings provide a novel perspective on the dynamic behavior of PAHs and contribute to a comprehensive understanding of their spatiotemporal distribution, sources, and environmental interactions. This study offers valuable insights for developing effective pollution control strategies, optimizing urban air quality management, and mitigating public health risks associated with PAH exposure.

6.3. Applying Remote Sensing Techniques to Investigate the Trajectory of Smoke Plumes During Biomass Burning Events

Gabriel Marques da Silva ¹, Mateus Fernandes ¹, Laura Silva Pelicer ¹, Gregori de Arruda Moreira ^{1, 2}, Alexandre Cacheffo ^{1, 3}, Fábio Juliano da Silva Lopes ^{1, 4}, Giovanni Souza ¹, Luisa D’Antola de Mello ¹, Eduardo Landulfo ¹

¹ 

Center of Lasers and Applications (CELAP), Energy and Nuclear Research Institute, São Paulo 05508-000, Brazil

² 

Federal Institute of Education, Science and Technology of São Paulo (IFSP), Campus Registro, São Paulo 11900-000, Brazil

³ 

Institute of Exact and Natural Sciences of Pontal (ICENP), Federal University of Uberlândia (UFU), Campus Pontal, Ituiutaba 38304-402, Brazil

⁴ 

Department of Environmental Sciences, Institute of Environmental, Chemical and Pharmaceutical Sciences (ICAQF), Federal University of São Paulo (UNIFESP), Campus Diadema, São Paulo 09913-030, Brazil

The wildfires in Brazil in 2024 reached unprecedented levels, serving as yet another indicator of the effects of climate change. LIDAR measurements conducted in São Paulo detected intense aerosol plumes generated during the wildfire period in August and September in the Mato Grosso do Sul and Pará regions. This study investigates the potential transport of aerosol plumes generated by these wildfires to São Paulo. To analyze the relationship between these plumes and wildfires in other regions of Brazil, data from the recently launched EarthCARE satellite, backward trajectory analysis using the HYSPLIT model, and AERONET sun photometers and Raman–LIDAR measurements were utilized. As part of the EarthCARE satellite calibration and validation process, this study compared three days of LIDAR data collected for São Paulo. After validating the backscatter and extinction coefficients and the LIDAR ratio, the HYSPLIT model was used to determine the potential trajectories of the aerosol plumes on the days with the highest heat source index. Once the source locations were identified, their correlation with wildfire-affected areas was examined. Sun photometer data were analyzed to infer the properties of the aerosol plumes. The results indicated three trajectories that coincided with fire hotspots, enabling the identification of wildfires in the city of Corumbá (Mato Grosso do Sul) and São Félix do Xingu (Pará) as the likely primary sources of the aerosol plumes observed in São Paulo.

6.4. Coupling Between Urban Sublayers: High-Resolution LES Modeling of Microclimate and Energy Dynamics in Bolognina

Daniela Cava ¹, Daiane de Vargas Brondani ¹, Tony Christian Landi ¹, Oxana Drofa ¹, Edoardo Fiorillo ², Umberto Giostra ³, Luca Mortarini ⁴

¹ 

Institute of atmospheric sciences and climate—Italian National Research Council

² 

Institute for the bioeconomy—Italian National Research Council

³ 

University of Urbino, Department of Pure and Applied Sciences (DiSPeA)

⁴ 

University of Milan

The rapid growth of the global urban population in recent years emphasises the need to understand urban environments in order to build sustainable, resilient cities and enhance residents’ quality of life. Despite its significance, the urban microclimate remains one of the most complex and least understood phenomena, largely due to the heterogeneity of urban environments. The physical structure of cities alters the exchange of momentum, energy, and pollutants between the surface and the atmosphere, creating an urban surface layer where classical turbulence laws no longer apply.

This study uses LES (PALM-4U) simulations to analyse key micrometeorological parameters with high spatio-temporal resolution in the Bolognina district of Bologna. The area is a typical example of Italian urbanisation. PALM-4U is coupled with the GLOBO-BOLAM-MOLOCH system. The MOLOCH model, developed specifically for Italy, provides more accurate mesoscale predictions than models like COSMO and WRF, which is crucial for LES simulations. Data from remote sensing, municipal datasets, and a census of over 5000 trees within a 1 km² area were used as static drivers for the Bolognina study.

The case study spans three days, from 23 to 25 August 2023, characterized by clear skies, intense daytime solar radiation, and light winds—optimal conditions for turbulent flow detachment from the surface and the development of the UHI effect.

The study aims to investigate (i) the role played by the type of pavement and urban vegetation in mitigating or amplifying the UHI effect and influencing thermal comfort; (ii) how different pavements and vegetation affect the micrometeorological processes in the roughness sublayer (RSL), thereby influencing the flow in the inertial sublayer (ISL); and (iii) the intensity of the coupling between the RSL and ISL and how it modifies the closure of the energy balance in the urban boundary layer.

6.5. Effect of the Form of the Error Correlation Functions on the Uncertainty in the Estimation of Atmospheric Aerosol Distribution When Using Spatial–Temporal Optimal Interpolation

Natallia Miatselskaya, Andrey Bril, Anatoli Chaikovsky

Center of Optical Remote Sensing, Institute of Physics of the National Academy of Sciences of Belarus, Nezalezhnasti Ave., 68-2, 220072 Minsk, Belarus

A common approach to estimate the spatial–temporal distribution of atmospheric species properties is data assimilation. This comprises methods to combine information from different sources for obtaining the best estimate of a system state. Data assimilation is based on minimizing the error in the estimate (optimal interpolation and Kalman filtering methods) or on minimizing the cost function (variational methods). Under certain conditions, variational methods turn out to be equivalent to optimal interpolation or Kalman filtering. All data assimilation techniques require an understanding of data error statistics. Optimal interpolation is a relatively simple and computationally cheap non-sequential method. In the optimal interpolation method, error correlations can be modeled with analytical functions on the base of the gathered data. In the present work, we investigate the effect of the form of the error correlation functions on the uncertainty in the estimate when using the spatial–temporal optimal interpolation (STOI) technique. We apply STOI to the estimation of aerosol distribution over Europe. To perform STOI, we use results of the chemical transport model GEOS-Chem simulations, as well as observations from a ground-based radiometric network AERONET that provides data on aerosol properties with low uncertainty. We show that the results of the STOI estimation are very tentative to the form of the error correlation functions. We perform some tuning of the correlation function parameters to improve the accuracy of the estimation.

6.6. Insights into Air Quality Index (AQI) Variability with Explainable Machine Learning Techniques

Claudio Andenna ¹, Roberta Valentina Gagliardi ²

¹ 

INAIL-DIT, Via del Torraccio di Torrenova 7, 00133, Rome, Italy

² 

Istituto Superiore di Sanità

Air pollution is a global environmental and health issue and is also strongly interlinked with the issue of climate change. A thorough understanding of the complex nonlinear phenomena that govern the spatiotemporal variability of air pollution is still lacking, although this knowledge is essential for defining effective strategies to safeguard public health and environmental sustainability, and to counteract climate change.

In recent decades, machine learning models (MLMs) have shown great potential in the air pollution research sector due to their capability in describing complex non-linear phenomena. Moreover, thanks to interpretability methods developed in the fields of Explainable Artificial Intelligence (XAI), MLM results can be interpreted for assessing the impact of individual factors and their interrelationships on the model output, also providing visual representations which can facilitate the comprehension of such complex phenomena.

In this study, the XGBoost algorithm and SHAP (SHapley Additive exPlanations) method have been employed to explore the influence of several driving factors, namely air pollutants (including surface ozone (O₃) and fine particulate matter (PM_2.5)) and meteorological parameters, on air quality index (AQI) variability.

Based on the air pollutant and meteorological data, acquired at different typologies of air quality monitoring stations over the 2018–2022 period, an XGBoost MLM has been developed to simulate the AQI temporal pattern, obtaining good model performance. Subsequently, the SHAP method has been employed to explore the importance of each driving factor and the relationship with the model output. Special focus is given to the interaction effect among driving factors on AQI.

6.7. Modeling the Role of Urban Green Spaces in Cooling Urban Environments: The Case of Villa Ada, Rome

Daiane de Vargas Brondani ¹, Tony Christian Landi ², Oxana Drofa ², Vito Imbrenda ³, Alessandra Gaeta ⁴, Rosa Coluzzi ³, Stefano Decesari ², Daniela Cava ¹, Umberto Giostra ⁵, Luca Mortarini ⁶

¹ 

Institute of Atmospheric Sciences and Climate, National Research Council, 73100 Lecce, Italy

² 

Institute of Atmospheric Sciences and Climate, National Research Council, 40129 Bologna, Italy

³ 

Institute of Methodologies for Environmental Analysis, National Research Council, 85050 Tito Scalo, Italy

⁴ 

Italian Institute for Environmental Protection and Research, 00144 Rome, Italy

⁵ 

Department of Pure and Applied Sciences University of Urbino, 61029 Urbino, Italy

⁶ 

Department of Earth Sciences “A. Desio” University of Milan, 20133 Milan, Italy

Cities worldwide are facing the dual challenges of urban heat islands (UHIs) and the increasing frequency of heatwaves. Concrete and asphalt, combined with reduced vegetation, cause urban areas to retain more heat than their rural counterparts. This not only leads to discomfort but also poses significant health risks, including heat-related illnesses and increased mortality rates. Urban green spaces, such as parks, play a crucial role in mitigating UHI effects through shading and evapotranspiration, which help cool urban environments.

This study focuses on Villa Ada, a 160-hectare park in central Rome, characterized by relatively unmanaged vegetation. We aim to assess its effectiveness in reducing local UHI effects during a heatwave from 8 to 10 October 2023. Using the Parallelized Large-Eddy Simulation Model (PALM), we simulate three urban greenery scenarios: (1) replacement of the park with asphalt, (2) replacement of the park with short grass, and (3) replacement of short grass areas with trees featuring high leaf area density, representing the most adaptive scenario.

The preliminary results suggest that Villa Ada exerts a cooling effect on its immediate surroundings, with increased tree coverage leading to more substantial temperature reductions. These findings underscore the critical role of urban green spaces in mitigating UHI effects and highlight the importance of strategic urban planning that preserves and enhances such areas. Future research should explore the long-term impacts of different vegetation management strategies and their implications for urban climate resilience.

6.8. Numerical Weather Prediction Models Using Atmospheric and Weather Parameters to Enhance Accurate Weather Forecasting and Risk and Hazard Mitigation

Okoro Njoku Onyema ¹, Onugwu Alexander ², Nwokporo Ifeanyi ³

¹ 

Department of Industrial and Medical Physics, David Umahi Federal University of Health Science, Uburu, Ebonyi State, Nigeria

² 

Department of Physics with Electronics, Evangel University Akaeze, Ebonyi State, Nigeria

³ 

Department of Science Laboratory Technology, Federal College of Agriculture Ishiagu, Ebonyi State, Nigeria

Numerical Weather Prediction (NWP) models are essential tools for forecasting atmospheric weather conditions and mitigating weather-related hazards. This research investigates the integration of certain atmospheric and weather parameters (rainfall, temperature, relative humidity, cloud cover, geomagnetic storms, and solar radiation) into NWP models to enhance the forecasting accuracy to a high degree. This research evaluates different NWP approaches, including deterministic and ensemble models, focusing on the parameterization schemes and data assimilation techniques. The NWP model was selected due to its flexibility in regional forecasting. Simulations were conducted using different parameterization schemes to ascertain the impact of geomagnetic and solar influences on weather conditions. This research employed data assimilation techniques, including 4D-Var, to integrate real-time observations into the model. The results demonstrate forecast reliability that was improved by a reasonable percentage by the addition of solar and geomagnetic influences, contributing to improved disaster preparedness and climate risk management and control. A stronger correlation (R = 0.85) between the modeled and observed cloud cover was obtained when both solar and geomagnetic influences were incorporated. The outcomes of this research are expected to offer valuable insights for improving weather forecasting accuracy, strengthening early warning systems, and enhancing preparedness for potential weather-related disasters, thereby providing more robust and effective risk and hazard management strategies. This study underscores the role of comprehensive atmospheric modeling techniques in strengthening early warning systems and reducing the uncertainties in weather forecasts.

6.9. Photochemical Processes of Tropospheric Ozone Formation: The Role of Nox and Methane in Atmospheric Chemistry

Arina Okulicheva ¹, Margarita Tkachenko ^{1, 2}, Sergey Smyshlyaev ¹

¹ 

Russian State Hydrometeorological University, St. Petersburg, Russia

² 

Laboratory for the Study of the Ozone Layer and the Upper Atmosphere. St. Petersburg State University, St. Petersburg, Russia

Growing urbanization and industrialization heighten air pollution concerns. Tropospheric ozone, a challenging pollutant, draws scientific attention. Nitrogen oxides (NOx) and methane (CH4) are key, influencing ozone dynamics. Methane and NOx are primary precursors in tropospheric ozone’s complex formation. Elevated methane can substantially increase ozone, while excess NOx triggers self-regulation. Atmospheric reactions, including ozone destruction, illustrate this complexity, where NO reacts with O3.

Research on long-term NOx and methane emissions is crucial for understanding climate change. Analyzing scenarios fixing 2010 NOx levels while varying methane to 2100 offers insights into climate consequences. Elevated ozone has adverse effects: deteriorating air quality, respiratory issues, vegetation damage, and an enhanced greenhouse effect.

Advanced atmospheric chemistry modeling and data analysis are employed in this research. Global climate models like SOCOL-v3 simulate atmospheric processes and chemical reactions involving NOx and methane. These models, incorporating meteorological data, emissions inventories, and chemical reaction mechanisms, predict tropospheric ozone formation accurately. They enable the analysis of complex atmospheric interactions and forecast future air quality scenarios under varying emission conditions

Integrated chemical climate modeling, scenario analysis, and synergistic pollutant effects are crucial in current research. Understanding these interactions is vital for effective air quality management. Continued growth in pollutant concentrations underscores the need for emission control measures. This research’s practical applications include enhancing air quality monitoring, developing pollution reduction strategies, forecasting atmospheric changes, and shaping environmental policies. Future studies should focus on detailed interactions between atmospheric components and innovative air quality control approaches. International cooperation is essential for effective tropospheric ozone management.

Funding: Russian Science Foundation project under the contract No.23-77-30008.

6.10. Study of Spatial and Temporal Variability of Tropospheric Ozone over Russia

Yana Virolainen ¹, Alexander Polyakov ¹, Georgy Nerobelov ^{1, 2}, Svetlana Akishina ¹

¹ 

St. Petersburg State University

² 

Russian State Hydrometeorological University

Tropospheric ozone is a greenhouse gas and a reactive and toxic pollutant detrimental to human health and ecosystem productivity. Therefore, the study of tropospheric ozone column (TrOC) variability by means of measurements and modeling is an essential task.

The IKFS-2 spectrometer aboard the Meteor-M N2 satellite measured outgoing thermal radiation in the 5–15 µm spectral range with an un-apodised spectral resolution of 0.4 cm⁻¹ in 2015–2022. A retrieval technique based on the artificial neural network (ANN) algorithm and the method of principal components has been developed for interpreting the IKFS-2 spectral measurements. For the ANN training, we used TrOCs derived from ozonesonde measurements at different ground-based sites taken from the archive created by the TOAR-II HEGIFTOM working group, thus solving the problem of calibration of the IKFS-2 TrOC data product. The uncertainty estimated for IKFS-2 TrOC measurements equals ~3 DU (~12–15%). The IKFS-2 TrOC data product has been validated by comparison with independent TrOC measurements at the NDACC IRWG and with IASI satellite measurements.

The spatiotemporal variability of TrOC over Russia was studied based on IKFS-2 and IASI satellite measurements, as well as the WRF-Chem numerical modeling and EAC4 reanalysis data. The seasonal variability in TrOCs was estimated, and the observed anomalous values in TrOC distribution were analyzed. It was revealed that over most of the territory of Russia, except for certain regions of Siberia and the Far East (Kamchatka region), a decrease in TrOC was observed over the 2016–2022 period.

This research was supported by SPbU grant No. 116234986.

6.11. Testing a Technique for Retrieving the Rain Drop Size Distribution Moments from X-Band Polarimetric Radar Data During a Warm Rain Event

Merhala Thurai ¹, GyuWon Lee ², Kyuhee Shin ²

¹ 

Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523, USA

² 

Department of Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Daegu 41566, Republic of Korea

A method for retrieving the moments of rain drop size distributions (DSDs) from X-band polarimetric radars is tested using data from a warm rain event which occurred near Incheon, Republic of Korea. The method involves the use of attenuation-corrected radar reflectivity for horizontal polarization, attenuation-corrected differential reflectivity, and specific attenuation for horizontal polarization. The method had been previously tested for an event in Greeley, Colorado, USA, and had resulted in very encouraging results. In this paper, we apply the same method to an isolated warm rain cell which occurred during the summer season of 2020 in Incheon. The height profiles of the retrieved moments were examined. We showed that the application of our retrieval method results in very plausible results in terms of the dominant microphysical processes associated with warm rain events. We also included a convergence region where the drop break-up process is clearly highlighted as being the dominant process. With such encouraging results, our future plan will be to increase the accuracy of the retrieval method by reducing the parameterization errors, for example, by using finely tuned shape parameters to represent the underlying function of the DSDs for warm rain events. The tuning will entail accurate measurements of the full DSD spectra in Incheon.

7. Session 6: Climatology

7.1. A Spatiotemporal Analysis of the Occurrence of Fires in the Caatinga Biome: A Climatological Approach Using Machine Learning

Katyelle Ferreira da Silva Bezerra ^{1, 2}, Helber Barros Gomes ^{1, 2}, Janaína M Pinto do Nascimento ^{3, 4}, Marisol Osman ^{5, 6}, Maria Cristina Lemos da Silva ^{1, 2}, Daniel Milano Costa de Lima ⁷

¹ 

Federal University of Alagoas

² 

Institute of Atmospheric Sciences—ICAT

³ 

Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA

⁴ 

NOAA OAR Global Systems Laboratory (GSL)

⁵ 

Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Ciencias de la Atmósfera y los Océanos

⁶ 

CONICET—Universidad de Buenos Aires, Centro de Investigaciones del Mar y la Atmósfera (CIMA), CNRS—IRD—CONICET—UBA, Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI), Buenos Aires, Argentina

⁷ 

Federal University of Campina Grande

The Caatinga is a semi-arid forest biome with a climate that is marked by severe droughts and recurrent fires, resulting in a loss of biodiversity. This research uses daily data from the VIIRS active fire detection product (onboard the S-NPP and NOAA-20 satellites) to analyze fires from 2012 to 2023 in the Caatinga Biome, where the data set was filtered, including only Fire Radiative Power (FRP) values above zero and considering only detections that were longer than 24 h. The clustering methodology of Nascimento et al. was then applied, using the DBSCAN algorithm to identify and group the fires. The latitude, longitude, and time coordinates were transformed into a common Cartesian space, allowing for the identification of patterns in the distribution of fires, in which unique identifiers, called “fire_id”, were used to identify the frequency, duration, and intensity of these fires. The climatology of the FRP and Fire Radiative Energy (FRE) data showed significant variability, especially from July onwards, where the highest climatological averages of the FRP occurred in November (~17 MW/h) and October (~16 MW/h), respectively. The highest climatological averages of the RES occurred in August (300,000 MJ) and September (200,000 MJ), respectively. The annual distribution showed FRP peaks throughout all years, with a significant increase in 2021 (~1500 MW/h), but the highest frequency of fire_id markers was recorded in October 2023 (7455). In addition, the highest fire_id frequencies occurred mainly in the months of September to November. A kernel density analysis, which mapped the spatial distribution of the FRP density, showed that the states of Bahia and Piauí had the highest FRP intensities, indicating a significant concentration of fires in these regions. These results contribute to the development of prevention and mitigation strategies, both in the short and long term.

7.2. Significance of Summertime Heat-Low over Northern Indian Subcontinent in the Changing Climate

Prashant Singh

• Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany

The Indian heat-low, a strong atmospheric circulation pattern marked by low pressure and high temperatures, significantly impacts weather patterns over Pakistan and northern India. Understanding how terrestrial heating patterns vary over time is critical to climate change. Such changes can profoundly impact large-scale systems such as the heat-low and monsoon. The evolving characteristics of the heat-low area over the Indian subcontinent from 1950 to 2020 are investigated using a decadal analysis of reanalysis data (ERA5). The data show that the heat-low trend shifted eastward over this period. Furthermore, as part of the CMIP5 RCP8.5 ensemble, the CMCC-CMS model predicts a further eastward shift in this circulation pattern between 2050 and 2100. The heat-low pattern’s eastward movement substantially impacts the monsoon circulation system, potentially resulting in large adjustments in rainfall patterns across the Indian subcontinent. The results of both the ERA5 and CMCC-CMS models support the idea of an eastward shift in rainfall, demonstrating the possibility of altered precipitation distribution in the future. Furthermore, this study emphasizes the possible drying of the western Indian subcontinent, including Pakistan and western India, because of the altering heat-low trend. These findings highlight the necessity of considering changing atmospheric circulation patterns in climate change assessments and the need for a better understanding of the associated implications for regional climate dynamics.

7.3. Advancements and Challenges in Climate Modeling: From Conventional GCMs to Artificial-Intelligence-Driven Predictions

Sk. Tanjim Jaman Supto

• Department of Environmental Research, Nano Research Centre, Sylhet 3114, Bangladesh

The field of climate modeling is undergoing a significant transformation, moving away from the traditional General Circulation Models (GCMs) and toward the use of sophisticated artificial intelligence (AI)-based prediction systems. Research has shown that artificial intelligence (AI) has the potential to improve climate modeling’s regional accuracy and computing efficiency. Nevertheless, these investigations have frequently functioned in discrete settings and oversimplified situations without a thorough connection with basic physical concepts. This drawback emphasizes the necessity of a more comprehensive strategy that can handle the intricacies of climatic variability and guarantee reliable model validation. In order to assess the possibilities and challenges of hybrid models in comparison to conventional GCMs, this study synthesizes proven climate models, AI methodologies, and their accuracy in climate predictions and analyzes existing climate models to evaluate the potential and limitations of hybrid models compared to traditional GCMs. Integrated AI-driven models show notable improvements in predicting regional variations in climate and accelerating simulation processes, especially when dealing with the growing presence of extreme weather occurrences. However, it is important to have consistent datasets and open evaluation procedures in order to guarantee accuracy and deal with the difficulties that come with model benchmarking. This research highlights how crucial it is to maintain interdisciplinary cooperation in order to properly utilize what artificial intelligence (AI) has to offer in climate modeling. This partnership is essential to creating more accurate and useful climate projections, which will eventually guide successful mitigation and adaptation plans for a changing global environment. In order to have a greater understanding of our climate’s future, we must keep pushing the limits of the existing modeling tools.

7.4. Assessment of Climate Variability and Trends in Water Availability in South America

Daniel Milano Costa de Lima ¹, Helber Barros Gomes ^{1, 2, 3, 4, 5}, Maria Cristina Lemos da Silva ^{2, 6}, Katyelle Ferreira da Silva Bezerra ², Paulo Vítor de Albuquerque Mendes ²

¹ 

Universidade Federal de Campina Grande, UFCG

² 

Universidade Federal de Alagoas, UFAL

³ 

Max Planck Institute for Meteorology, MPI-M

⁴ 

University of Connecticut, UConn

⁵ 

TEMPO OK TECNOLOGIA EM METEOROLOGIA LTDA, TOK

⁶ 

Instituto Nacional de Pesquisas Espaciais, INPE

This study examines the climatic water availability, defined as precipitation minus potential evapotranspiration (PET), in continental South America during historical (1960–2014) and future (2015–2100) periods. Observed (CRU TS, ERA5) and modeled (CMIP6) data were used, with future projections under the SSP2-4.5 and SSP5-8.5 scenarios derived from an ensemble of five models best representing the continent. To improve the drought analysis, the SNIPE (Standardized Nonparametric Indices of Precipitation and Evaporation) methodology was applied. This method aggregates the data over multiple time scales (1, 3, 6, and 12 months) and uses nonparametric rescaling to produce standardized indices (zero mean, unit variance). Unlike the SPI and SPEI indices, which rely on parametric assumptions that may bias the results if the data deviate from the assumed distributions, SNIPE uses a distribution-free approach, making it a robust tool for drought assessment. Historical data from both the observed and modeled sources show similar water availability patterns: drought in Patagonia, the Atacama, the Central Andes, and the Brazilian northeast and high availability in the Amazon and southeast Brazil. Future projections indicate an expansion and intensification of drought, mainly affecting transition zones such as the Brazilian Cerrado, the edges of the Amazon, the Chaco, and the semiarid areas of the Brazilian northeast, with more pronounced changes under SSP5-8.5. Correlation analyses between SNIPE and various climate indices (AMO, ONI, PDO, SAM, TNA, TSA, and TPI-IPO) reveal that indices such as TPI-IPO, ONI, and TSA play key roles in the water regime dynamics in southeastern South America (including the areas of southern/southeastern Brazil, Paraguay, Uruguay, and northeastern Argentina), a region frequently impacted by floods. These findings underscore SNIPE’s potential to enhance forecasting systems and water resource management strategies.

7.5. Future Projections (2015–2100) of Daily Temperature Range (DTR) in South America: Multiregional Analysis Based on CMIP6 Models

Daniel Milano Costa de Lima ¹, Helber Barros Gomes ^{1, 2, 3, 4, 5}, Maria Cristina Lemos da Silva ^{2, 6}, Paulo Vítor de Albuquerque Mendes ², Katyelle Ferreira da Silva Bezerra ²

¹ 

Universidade Federal de Campina Grande, UFCG

² 

Universidade Federal de Alagoas, UFAL

³ 

Max Planck Institute for Meteorology, MPI-M

⁴ 

University of Connecticut, UConn

⁵ 

TEMPO OK TECNOLOGIA EM METEOROLOGIA LTDA, TOK

⁶ 

Instituto Nacional de Pesquisas Espaciais, INPE

This study investigates future projections of the DTR over the South American area using CMIP6 modeled data on the maximum (Tmax) and minimum (Tmin) temperatures under two socioeconomic scenarios, SSP2-4.5 (low greenhouse gas emissions) and SSP5-8.5 (high emissions). The continental region was divided into 10 subregions, with the boundaries drawn based on their climatic characteristics, and for each one, ensembles of the five best-performing models were generated. This selection of models is based on a comparison of their historical series with an observed reference series obtained from the Climatic Research Unit (CRU)’s time series (TS). The statistical analysis, which used the modified Mann–Kendall test and the Theil–Sen slope estimator, reveals that Tmin and Tmax show an increasing trend over time. However, the increase in Tmin is more pronounced, resulting in a reduction in the DTR in most subregions. For example, it is estimated that in SSP2-4.5, the DTR will decrease by approximately −0.71 °C between the periods 2015–2025 and 2090–2100, while in SSP5-8.5, this reduction could reach approximately −1.04 °C. Some areas, such as the south of northeast Brazil, southeast Brazil, south Brazil, and Uruguay, show opposite patterns, with an increase in the DTR. These results reinforce the influence of anthropogenic factors in modulating the DTR, and the findings provide support for the development of policies to adapt to and mitigate the impacts of climate change on the South America continent.

7.6. Impact of Biogenic Emissions on Climate and the Ozone Layer

Eugene Rozanov ^{1, 2}, Tatiana Egorova ¹, Vladimir Zubov ^{2, 3}

¹ 

PMOD/WRC, 7260 Davos Dorf, Switzerland

² 

Laboratory for the Study of the Ozone Layer and the Upper Atmosphere, Saint-Petersburg State University, Saint Petersburg 199034, Russia

³ 

Voeikov Main Geophysical Observatory, Saint Petersburg 194021, Russia

We analyze the influence of both biogenic natural emissions and anthropogenic emissions on atmospheric chemistry and climate using the SOCOLv4 Earth climate model. To achieve our objective, we simulated climate behavior from 2015 to 2100 using two IPCC scenarios: SSP2-4.5 and SSP5-8.5. Additionally, we created an artificial scenario wherein all biogenic emissions in SSP2-4.5 were replaced with those from the SSP5-8.5 scenario. The last scenario helps elucidate the contribution of biogenic emissions to the differences observed between the climates simulated with SSP2-4.5 and SSP5-8.5. The model results indicate that the impact of using biogenic emissions from the SSP5-8.5 scenario instead of those from the SSP2-4.5 scenario for the calculation of the future climate is significant for the tropospheric ozone, potentially leading to an increase of up to 10% in the troposphere. Regionally, changes in tropospheric ozone can vary, showing positive effects in regions like Australia and South Africa, while resulting in a negative response for Russia. The distribution of the surface temperature response resembles the tropospheric ozone change pattern. We observed significant warming in South America and the high latitudes of the Northern Hemisphere, alongside cooling in parts of Russia. A more detailed description of the local and seasonal features will be presented in this talk. The Saint Petersburg State University supported this work under research grant 116234986.

7.7. Long-Term Seasonal Investigation of Land Surface Temperature in Cairo

Motahhareh Zargari, Isidro A. Pérez, M. Ángeles García

• Department of Applied Physics, Faculty of Sciences, University of Valladolid, Paseo de Belén, 7, 47011 Valladolid, Spain

Cairo is one of the most populous cities in the world. The city’s unplanned urbanization has led to significant challenges, including an increase in Land Surface Temperature (LST), which is defined as the skin temperature of the land. LST is crucial for studies on radiative temperature in this densely populated and rapidly developing metropolitan area. The aim of this research is to analyze the seasonal variations in LST using MODIS Aqua satellite data, which offer a spatial resolution of 1 km and a temporal resolution of twice daily over an extended period from 2003 to 2022. This analysis involves calculating longitudinal and latitudinal temperature differences during both day and night to assess LST variations across different seasons, as well as annually, between the central area defined by coordinates (29°89′ to 30°15′ N and 31°17′ to 32° E) and the surrounding regions extending from south to north (29°69′ to 30°35′ N) and from west to east (30°65′ to 31°75′ E). Additionally, this study examines the daytime and nighttime averages of the spatial and temporal distributions of LST for each season. The results indicate that, compared to daytime measurements, both the city and its suburbs exhibit a closer alignment with the annual average during nighttime across south-to-north and west-to-east charts. During nighttime, temperature differences suggest that central areas experience higher temperatures than surrounding suburbs; however, conditions differ during daytime measurements when temperature differences indicate that central areas have cooler temperatures compared to neighboring suburbs. The warm seasons—summer, autumn, and spring—show higher temperatures in central Cairo compared to the cold season. The number of LST values peaks in summer rather than in other seasons in Cairo. This research contributes to a broader understanding of LST dynamics and provides valuable insights for policymakers, urban planners, and researchers alike.

7.8. Microclimate Analysis Through Advanced Modelling: A Case Study in Lecce, Italy

Francesco Giangrande ¹, Gianluca Pappaccogli ¹, Rita Cesari ², Antonio Esposito ¹, Riccardo Buccolieri ¹

¹ 

University of Salento, Lecce, Italy

² 

CNR-ISAC, Lecce, Italy

The present study aims to analyse the effects of climate change on the urban environment, focusing on sustainable urban planning and an analysis of microclimate and thermal comfort. The considered study area is composed of a square domain of app. 400 × 400 m in the city of Lecce (Italy), where temperature and relative humidity data are still being measured.

The analysis involves a modelling chain that uses ERA5 data to provide the boundary conditions for the 1D Multi-Layer Urban Canopy Model (MLUCM) based on the BEP + BEM (Building Effect Parameterization + Building Energy Model) model, which subsequently generates the inputs for ENVI-met (https://envi-met.com/, accessed on 9 November 2025), a CFD model used for microclimate simulations and thermal comfort studies. This methodology allows us to bridge the gap between different scales.

Another model applied in this work is PALM-4U, which is an advanced atmospheric simulator for the simulation of urban atmospheric boundary layers, as well as urban climate and the interactions between the built environment and the atmosphere. It can work in turbulence-resolving LES (Large Eddy Simulation) mode, and is suitable for a wide range of applications, such as urban climate, air quality and pollutant dispersion, urban ventilation, and thermal comfort. Among the advantages of PALM-4U are its high spatial and temporal resolution, its modular approach, and the fact that it represents support for real data, as well as being open-source.

The modelling outputs are first validated against measured data and are further employed to develop strategies for adapting to climate change by improving urban thermal comfort for citizens.

7.9. Modeling the Impact of a Supervolcanic Eruption on the Climate System Under Present and Future Conditions

Margarita Tkachenko, Eugene Rozanov

• Laboratory for the Study of the Ozone Layer and the Upper Atmosphere. St. Petersburg State University

Powerful volcanic eruptions are among the most significant natural factors globally affecting Earth’s climate system, capable of causing substantial changes in temperature, atmospheric circulation, and air chemical composition.

This study presents a powerful volcanic eruption (similar to the Tambora eruption in 1815) impact on the climate system under various background conditions. We performed a series of experiments with the chemistry–climate model SOCOL-MPIOM for three time periods: present conditions and two future climate scenarios: SSP3-7.0 and SSP2-4.5. The experimental design is based on quasi-random sampling methodology, allowing the optimal exploration of key model parameter space with minimal numerical experiments.

The climatic effect of a powerful volcanic eruption intensifies in the warmer climate of the late 21st century, manifesting in a deeper temperature drop (up to 2.5–3 K for SSP2-4.5) and a longer recovery period, compared to the present period (1–1.5 K).

Unlike the temperature response, the ozone layer reaction demonstrates a complex spatial structure with pronounced latitudinal asymmetry: a decrease in ozone content at high latitudes (up to −8 DU) and an increase in tropical latitudes (+4–6 DU). This effect is associated with changes in circulation and the photochemical processes of ozone formation.

The most intense analog of the historical ‘year without summer’ is observed in the SSP2-4.5 scenario, which may be related to higher concentrations of methane and NOx in this scenario, affecting photochemical processes in the atmosphere and enhancing the radiative effect of volcanic aerosols.

The recovery timescales of the ozone layer (5–7 years) exceed the period of temperature relaxation (3–4 years), indicating the long-term impact of volcanic forcing on the chemical composition of the atmosphere and highlighting the importance of considering chemical feedback when assessing the climatic consequences of powerful volcanic eruptions. This work was supported by Saint Petersburg State University under research grant 116234986.

7.10. Response of Cloud Cover and Climate to Geomagnetic Field Changes

Tatiana Egorova, Eugene Rozanov

• PMOD/WRC, 7260 Davos Dorf, Switzerland

We aimed at addressing how the weakening of the geomagnetic field affects cloud properties and climate, and whether this weakening could lead to an environmental crisis, as suggested by paleoclimatic data. To investigate this, we performed climate simulations driven by the relationship between geomagnetic field strength, atmospheric ionization rates, global electric circuit, and the cloud life cycle. The ionization rates were calculated using a model applicable to both regular and geomagnetic excursion periods. Our model modifications focused specifically on the cloud parameterization scheme, introducing a dependency of the cloud droplet coagulation on the global electric field strength. This dependency was determined as a function of fair weather vertical electric currents (J_z), which were interactively calculated from the simulated atmospheric ion concentrations and conductivity. The model results indicate that the impact of the geomagnetic field weakening on the atmospheric electrical currents is the most pronounced in the middle and low latitudes, leading to an increase in J_z of up to 20%. We also observed statistically significant changes in cloud cover and surface cooling of about 0.4 K in global and annual mean surface temperatures. Local and seasonal effects are even more pronounced; for instance, substantial temperature drops of up to 2 K are observed in the Northern Hemisphere. These findings will be described in further detail during the talk. However, based on our results, we cannot conclude that the introduced mechanism would lead to a large-scale environmental crisis. This work is supported by the Swiss National Science Foundation (project Spark GECO; CRSK-2_221368).

7.11. Spatiotemporal Evolution of Drought Episodes in Austria: A High-Resolution Assessment from 1950 to 2023

Jakob Ernst ¹, Milica Stojanovic ¹, Albenis Pérez-Alarcón ^{1, 2}, Rogert Sorí ³

¹ 

Environmental Physics Laboratory (EPhysLab), Centro de Investigación Mariña, Universidade de Vigo, Campus As Lagoas s/n, 32004 Ourense, Spain

² 

Instituto Dom Luiz (IDL), Facultade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal

³ 

University of Vigo

Drought is among the most severe climate-related hazards, posing significant threats to ecosystems and economies worldwide. Consequently, numerous countries have conducted locally focused studies to develop effective adaptation strategies. In this study, we examined the occurrence and evolution of drought in Austria, a relatively small country (83,878 km²) in Central Europe. Our analysis was based on long-term ERA5-Land monthly datasets spanning 1950–2023, incorporating precipitation, surface net radiation, surface pressure, 2 m air and dew point temperatures, and 10 m wind speed components. The precipitation and temperature data from this source exhibited strong agreement with observed datasets, supporting their reliability for this study. These datasets enabled the calculation of the Standardised Precipitation Index (SPI) and the Standardised Precipitation-Evapotranspiration Index (SPEI) at 1-, 3-, 6-, and 12-month timescales. Drought episodes were identified using a threshold of −0.84, with duration determined from the first month the index falls below zero, continuing until it reaches −0.84, and ending before the last month the index becomes positive. Severity was calculated as the sum of all SPI/SPEI values throughout each episode. Given that index variability decreases as the temporal scale increases, the highest number of drought episodes was identified using SPI1 (123) and SPEI1 (124), primarily affecting the western half of the country. The spatial distribution of drought episodes suggests a strong influence of topography. Furthermore, we found a statistically significant relationship between the severity of drought episodes and the affected area. However, differences between SPI and SPEI were consistently small across all temporal scales, indicating that evapotranspiration does not play a crucial role in the severity of drought episodes. These findings contribute to a historical understanding of drought in Austria and will be extended to future periods under different socioeconomic and climate scenarios.

7.12. The Atmospheric Hydrological Cycle and the El Niño Southern Oscillation in the Inter-American Seas

Graciela González González ¹, José Rolando Boffill Váquez ²

¹ 

Posgrado en Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, Ciudad de México 04510, México

² 

Posgrado en Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, Sisal 97351, México

The hydrological cycle plays a fundamental role in the Earth’s climate system. It is the result of a continuous circulation of water on the planet through a series of interconnected reservoirs, which involves processes of evaporation, atmospheric transport of humidity, condensation, precipitation, and surface runoff. To analyze the dynamics of water vapor in the atmosphere, a diagnosis of the integrated humidity flow in the vertical can be made with information from atmospheric humidity and wind data, while the divergence of the flow, net evaporation, and precipitation contribute to explain the precipitable water in the atmosphere. Various studies show that El Niño conditions affect the interannual and interdecadal variability in rainfall in the tropical Americas, by modifying the flow of humidity towards the region, as well as the activity of easterly waves and tropical cyclones in the Atlantic. A first approximation can be made by comparing El Niño and La Niña years and their effects on the rainy season in the intra-American seas. This comparison is made from the components of the atmospheric water balance equation. A comparison is made between the summer of 1982, characterized by the presence of an El Niño event, and the summer of 2010, influenced by a La Niña event. The main finding is that during El Niño, the moisture content in the Atlantic and eastern Caribbean region is significantly lower compared to during La Niña. This decrease in humidity translates into a reduction in rainfall in the tropical Americas.

7.13. Warming Projections of the Eastern Mediterranean in CMIP6 Simulations According to SSP2-4.5 and SSP5-8.5 Scenarios

Ioannis Logothetis ^{1, 2}, Dimitrios Melas ¹, Kleareti Tourpali ¹

¹ 

Laboratory of Atmospheric Physics, Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

² 

Centre for Research and Technology Hellas, Chemical Process and Energy Resources Institute, Thermi, 57001 Thessaloniki, Greece

This study investigates the future temperature changes in the climate-vulnerable region of the eastern Mediterranean. The results from seventeen (17) CMIP6 (6th Phase of Coupled Model Intercomparison Project) model simulations are analyzed in order to study the temperature changes. The analysis is focused on the moderate and extreme emissions in the Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5, respectively). The fifth generation ECMWF reanalysis (ERA5) is used as reference dataset in order to investigate the performance of CMIP6 simulations to accurately reproduce the mean temperature in the eastern Mediterranean region. The results show that CMIP6 model simulations vary regarding their efficiency to capture the mean temperature. In particular, Kling-Gupta efficiency Index (KGE) values fluctuate from −0.13 to 0.46. Future projections show that significant warming is shown during the last period of the 21st century (related to the historical basis period that covers the years from 1970 to 2000). The continental Balkan and Turkish regions are recognized as the most affected areas regarding future warming. The increase in temperature ranges from 1.5 °C to 4.5 °C for SSP2-4.5 and from 3.0 °C to 8.0 °C for SSP5-8.5 scenarios, respectively. Finally, the seasonal analysis indicates that summer (JJA) shows the maximum temperature increase compared to the other seasons.

8. Session 7: Air Quality

8.1. Assessment of NO₂ and CO Air Pollutions in the Marmara Region Using Sentinel-5P TROPOMI Observations

BURCU Sağlam Doğan ¹, Zehra Yiğit Avdan ²

¹ 

Department of Remote Sensing and Geographical Information Systems, Earth and Space Sciences Institute, Eskisehir Technical University, 26555 Eskisehir, Turkey

² 

Department of Environmental Engineering, Eskisehir Technical University, 26555 Eskisehir, Turkey

Air pollutant gases emitted by anthropogenic activities significantly contribute to climate change and pose serious threats to human health. Among these pollutants, nitrogen dioxide (NO₂) and carbon monoxide (CO) are particularly significant contributors to urban air pollution. Satellite-based remote sensing has long been employed to monitor global air quality. This study aimed at investigating the temporal and spatial changes in average atmospheric NO₂ and CO concentrations in the Marmara Region of Türkiye during the summer (July–August) and winter (January–February) seasons between 2019 and 2024. For this purpose, we utilized high-resolution measurements from the recently launched Sentinel-5P TROPOMI sensor, which provides detailed insights into local air quality and pollution levels. Data processing was conducted using Google Earth Engine (GEE), and spatial distribution patterns were mapped in ArcGIS Pro (https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview, accessed on 9 November 2025). Within this framework, the study was structured around the following key research question: “How have NO₂ and CO concentrations changed seasonally and annually before and after the COVID-19 outbreak?” The findings revealed that NO₂ and CO concentrations exhibited seasonal fluctuations throughout the study period, with significant increases and decreases at specific intervals. Notably, a sharp decline in these pollutant levels was observed during the COVID-19 pandemic in 2020, whereas a considerable rebound has been detected in certain regions since 2021. Moreover, NO₂ and CO concentrations were found to be significantly higher in cities characterized by high population density and intensive industrial activities, such as Istanbul, Bursa, and Kocaeli. These findings offer critical insights into the spatiotemporal changes in NO₂ and CO emissions, underscoring the effectiveness of Sentinel-5P satellite data as a powerful tool for air quality monitoring. This study serves as a roadmap for policymakers by supporting policy development processes in cities striving to enhance air quality and ensure sustainable air pollution management through comprehensive spatial analyses of NO₂ and CO concentrations.

8.2. Efficient Nitrous Oxide Capture from Dam Lake Treatment by Malt Dust-Derived Biochar

Pelin Soyertaş Yapicioğlu, Irfan Yesilnacar

• Environmental Engineering Department at Harran University, Şanlıurfa, Turkey

According to the European Union (EU) Green Deal, the greenhouse gas (GHG) emissions from water resources should be reduced by 30% until 2030. Dam lake treatment is one of the main important GHG resources according to the European Union (EU) Green Deal. Due to the natural texture of dam lakes, they emit nitrous oxide (N₂O) emissions at higher amounts. The main aim of this study was the reduction in the N₂O emissions resulting from dam lake treatment using malt dust-derived biochar. The biochar was derived from malt dust using a slow pyrolysis process under three various temperatures: 250 (M1), 300 (M2) and 500 °C (M3). A biochar adsorption process was applied as not only as a water treatment technique but also as a nitrous oxide emission reduction method. Before and after the biochar adsorption process, N₂O was sampled and measured seasonally using gas chromatography equipped with an electron capture detector (GC-ECD). The water samples were taken seasonally from Ataturk Dam Lake inTurkey. Also, the GHGs originating from water treatment were collected and adsorbed using the same biochar to determine the experimental nitrous oxide capture ability of biochar in a gas adsorption column. On average, a 21.1% reduction in N₂O emissions from dam lake treatment was reported using malt dust-derived biochar. The maximum nitrous oxide capture capacity corresponded to the malt dust-derived biochar produced at the minimum temperature (M1). This study verified that malt dust-derived biochar was an efficient N₂O adsorbent and air pollutant disposer. The Box–Behnken experimental design method was performed using MATLAB (https://www.mathworks.com/products/matlab.html, accessed on 9 November 2025) to determine the optimum operating parameters for the minimum N₂O emission. The statistical analysis results revealed that the optimum parameters were 4 mg/L of dissolved oxygen (DO) and 11 mg/L of nitrate (NO₃⁻) concentration for the minimum N₂O emission.

8.3. Size Distribution and Seasonal Evolution of Airborne Metals in Antarctic Atmospheric Particulate Matter

Lorenzo Massi ^{1, 2}, Federico Girolametti ¹, Behixhe Ajdini ¹, Matteo Fanelli ³, Silvia Illuminati ¹, Cristina Truzzi ¹, Anna Annibaldi ¹

¹ 

Department of Life and Environmental Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy

² 

Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University, 30123 Venice, Italy

³ 

Institute of Biological Resources and Marine Biotechnology, National Research Council, 60131 Ancona, Italy

Introduction: Aerosols play a crucial role in Earth’s climate system, influencing the balance of radiation and cloud formation. Antarctica, despite its remoteness, provides an ideal environment in which to study background aerosol composition and the long-range transport of pollutants. This study investigates size-segregated elemental composition, seasonal variations, and potential sources of atmospheric aerosols in Antarctica. Methods: Seven size-segregated aerosol samples were collected at Faraglione Camp (~3 km from Mario Zucchelli Station) between November 2019 and January 2020 using a high-volume cascade impactor. Samples were analyzed for major (Na, Ca, K, Mg), minor (Al, Fe, Mn), and trace elements (Cd, Cr, Cu, Hg, Ni, V) using ICP-OES, GF-AAS, and DMA after acid microwave digestion. Results: The elemental concentrations of PM₁₀ followed the order K > Na > Al Ca > Mg Fe > Mn > Cr > Ni > Cu V > Cd Hg. Seasonal trends were element-specific, influenced by katabatic winds and pack ice melting. Notably, Mg, Cu, Cr, and Hg peaked in late November/mid-December, likely due to sea spray emissions, while Fe, V, and Mn showed a decreasing trend. The size distribution analysis identified three modes of particle dispersion: accumulation (0.1–1 µm) and two coarse fractions (~2.5–3 µm and ~9.5 µm). Crustal enrichment factors (EFs) indicated geogenic origins for Mn and Fe (EF~1), while Cu, Ni, K, Ca, and V enrichment was linked to soil resuspension. Mg and Na showed moderate enrichment (EF~10), associated with sea spray, while Cd, Cr, and Hg exhibited high EFs (10 < EF < 100), suggesting an anthropogenic influence. Conclusions: These findings underscore the importance of continuous monitoring in assessing the contributions of aerosols to polar environments and their potential climatic and ecological impacts.

8.4. Backward Trajectory and Potential Source Locations of Ambient PM_2.5 at University of Lagos, Nigeria

Francis Olawale Abulude ¹, Abiodun A. Okunola ²

¹ 

Environmental and Sustainable Research Group, Science and Education Development Institute

² 

Department of Agricultural and Biosystems Engineering, Landmark University, PMB 1001, Omu Aran 251101, Nigeria

Globally, Particulate Matter (diameter 2.5—PM_2.5) and other pollutants have created a lot of problems health wise. It is not possible to mitigate their effects without quantifying the amount within the environment both indoors and outdoors. On this premise, the PM_2.5 within the University of Lagos (UNILAG), Nigeria (Central Laboratory and the Main gate of the campus) was evaluated with the aim of disseminating the outcome to stakeholders who would work towards mitigating the potential pollution around the surroundings. Also, a HYSPLIT model was used to track backward trajectories and the potential source locations of PM_2.5. The eight-month (1 August 2023 to 1 March 2024) air quality data were obtained from AirQo at Makerere University, Uganda. The data were subjected to Anderson—Darling Normality Testing and were compared with the National Environmental Standards and Regulations Enforcement Agency (NESREA) and World Health Organization (WHO) standards. The results were as follows. Main gate: minimum (7.23 µg/m³), maximum (180.50 µg/m³), mean (26.69), Std. (19.07), and A-Squared (104.28); Central lab: gate: minimum (6.32 µg/m³), maximum (181.13 µg/m³), mean (24.26), Std. (20.86), and A-Squared (227.28). The means of the two locations were 5.34 times (Main gate) and 4.86 times (Central Lab) higher than the WHO annual limit, while they were 1.34 times (Main gate) and 1.21 times (Central Lab) higher than the NESREA annual limit, which may likely be due to high local emissions from solid fuel combustion, waste burning, and high vehicular movements within the vicinity. The air mass came from the ocean in a southwestern direction. These findings demonstrated the significance of local emission sources in determining fluctuations in PM_2.5 within the university and the necessity of focused mitigation techniques to solve serious environmental air pollution issues.

8.5. Effects of Nitrogen Oxide (NO and NO₂) Concentration Levels and Meteorological Variables on Ozone (O₃) Formation in the Petrochemical Industry Area in the Monterrey Metropolitan Area, Mexico

Jailene Marlen Jaramillo-Perez, Bárbara Azucena Macías-Hernández, Edgar Tello-Leal, René Ventura-Houle

• Faculty of Engineering and Science, Autonomous University of Tamaulipas

The petrochemical industry emits large amounts of nitrogen oxides (NOx). It is the second source of volatile organic compounds (VOCs), which, through photochemical reactions, can form tropospheric ozone (O₃) and, together with geographic and meteorological conditions, determine pollution’s spatial and temporal behavior. The objective of this study is to assess the influence of air pollutants NOx, NO₂, and NO, as well as meteorological factors, on O₃ concentration levels in the city of Cadereyta, Nuevo Leon, which is characterized by its petrochemical industry as part of the metropolitan area of Monterrey, Mexico. The data were analyzed using the Spearman correlation coefficient, identifying a weak to moderate negative association between NOx and NO₂ with O₃ in the spring season and a null relationship in the summer. However, the fall and winter seasons observed a moderate to strong negative relationship. Subsequently, a multiple linear regression analysis determined the influence of air pollutants NOx, NO₂, and NO, as well as meteorological factors, on O₃ concentration levels. In this sense, when the concentration levels of NOx and NO₂ decrease, the concentration of O₃ will increase proportionally according to the year’s season. The prediction model obtains a coefficient of determination (R²) of 0.61 and a value in the root-mean-square error (RMSE) metric of 0.0107 ppm. In the prediction model, all variables presented a significant effect on the interpretation of the dependent variable, and the independent variables that provided the most significance in the variation in the concentration levels of O₃ were NOx and NO₂.

8.6. Evaluation of Modelling and Remote Sensing Tools for Improving Air Quality in Surroundings of Open-Pit Mines

Raúl Arasa Agudo ¹, Oscar Hernandez ², Elisa Etzkorn ³, Milagros Herrera ⁴, David Fuertes ⁴, Eliot Llopis ⁴, Jesús De la Rosa ⁵, Ana Sánchez de la Campa ⁵, Francisco Vázquez ⁶, Emilio San Juan ⁶

¹ 

Applied Research and Customer Success Departments, Meteosim, Barcelona, Spain

² 

Solutions Department, Meteosim, Barcelona, Spain

³ 

Applied Research Department, Meteosim, Barcelona, Spain

⁴ 

GRASP Earth, France

⁵ 

Center for Research in Sustainable Chemistry, University of Huelva, Huelva, Spain

⁶ 

Environmental Area, Atalaya Mining, Spain

The nature of the activities carried out in open-pit mines necessitates appropriate and efficient management of the dispersion of pollutants generated and of local air quality levels. The blasting, excavation, and transportation of minerals are some of the main mining activities that can cause the release of particles into the atmosphere. These particles may contain heavy metals and other chemical species that can affect the respiratory health of people living near mines.

In this contribution, innovative techniques related to air quality modelling and remote sensing have been evaluated. These three techniques aim to address previously unanswered questions and sources of uncertainty identified based on the authors’ experience, with areas such as the following: (1) recommended emission factors for blasting activity in copper mines do not exist; (2) to adapt environmental management and ensure compliance with legislation, the concentration of particulate matter for the next few hours, depending on meteorological conditions and the mine operation plan, should be known; and (3) methods of generating a heat map of the particulate matter levels in the mine and nearby populations.

To respond to these questions, we have tested innovative techniques: (a) a semi-empirical approach based on real data and Gaussian dispersion modeling has been used to accurately estimate the emission factors of particulate matter in the atmosphere related to blasting activity; (b) a data-science model has been prepared to generate a nowcasting of the levels of particulate matter considering, mainly, the evolution of the meteorological conditions and a large amount of historical data; and (c) an air quality monitoring service has been used that derives particulate matter properties from space by transforming public satellite data, and other public sources has been tested. These techniques have been evaluated over one of the most relevant open-pit mines in southern Europe: the Riotinto mine, Huelva (Spain).

8.7. Impact of Urban Morphology on Vehicular Pollutant Dispersion: A Modelling and Experimental Approach in the City of Lecce (Italy)

Chiara Metrangolo ¹, Adelaide Dinoi ², Gianluca Pappaccogli ¹, Prashant Kumar ³, Riccardo Buccolieri ¹

¹ 

Laboratory of Micrometeorology, Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, University of Salento, S.P.6 Lecce-Monteroni, 73100 Lecce, Italy

² 

National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), S.P.6 Lecce-Monteroni, 73100 Lecce, Italy

³ 

Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK

This study, conducted within the framework of the PNRR Italian National Centre for Sustainable Mobility CNMS (European Union—Next Generation EU—PNRR—MISSIONE 4—COMPONENTE 2- INVESTIMENTO 1.4—Spoke 7—Code CN00000023, CUP: F83C22000720001), investigates the impact of urban morphology on the dispersion of vehicular pollutants, specifically nitrogen dioxide (NO₂) and particulate matter ≤ 10 µm (PM₁₀). The aim is to analyse pollutant concentration patterns in areas characterised by different urban forms and to evaluate potential strategies for improving air quality in sensitive locations such as school environments.

The primary phase of this study focuses on the city of Lecce, integrating modelling with ADMS-Roads, QGIS elaborations and meteorological analyses to estimate pollutant dispersion under varying urban morphologies. In this initial phase, traffic data is kept constant for consistency. The preliminary modelling results indicate a strong influence of urban morphology on the dispersion of traffic-related pollutants. Urban forms characterised by a low planar area index (λ_p) have been observed to lead to increased NO₂ and PM₁₀ levels, with concentrations decreasing in areas with higher λ_p.

In addition to modelling efforts, experimental measurement campaigns will be carried out near two schools in Lecce to assess real-world pollutant concentrations. These campaigns will employ an air quality monitoring station, a meteorological station and a traffic-counting camera. The meteorological and traffic flow data collected will enable the reproduction of real scenarios in ADMS-Roads and will be used to validate the model through comparison with measured air quality data and enabling future scenario simulations that assess mitigation measures to reduce traffic-related emissions. This, in turn, will improve air quality in sensitive areas such as school environments.

8.8. Particulate Matter (PM_2.5) Prediction in Tashkent Using Machine Learning

Umida Madiyarova, Jaloliddin Erkinov, Babaa Moulay Rachid

• New Uzbekistan University, Tashkent, Uzbekistan

Air pollution is a growing concern in urban areas, and fine particulate matter poses significant risks to public health. Fine particulate matter is defined as particles that are 2.5 microns or less in diameter (PM_2.5). Emissions from the combustion of gasoline, oil, diesel fuel, and wood produce much of the PM_2.5 pollution found in outdoor air.

This work explores the use, for the first time, of machine learning techniques to predict PM_2.5 air quality levels in Tashkent, Uzbekistan. The primary goal is to develop robust predictive models that can accurately estimate PM_2.5 concentrations based on environmental and temporal factors. Open-source air quality datasets from ten automated air quality monitoring stations were utilized, and additional features, such as weather conditions and seasonal trends, were implemented to improve model accuracy. A hypothesis-driven approach was adopted to test the relevance of these features and assess their impact on model performance. This study employed a range of regression models, starting with linear regression and progressively advancing to more sophisticated methods, including ensemble models such as Random Forest and Gradient Boosting.

The performance of these models was evaluated using the R² metric, with a focus on balancing accuracy and model interpretability.

Our results exhibit the great potential of machine learning in addressing urban air quality challenges and pave the way for informed environmental strategic decision making in Tashkent city and similar urban contexts.

8.9. Quantifying Urban Air Quality Across Global Megacities

Ibrahim Alsafari ^{1, 2}, Swarnali Sanyal ³, Viney Aneja ¹

¹ 

Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University

² 

King Abdul Aziz University

³ 

Department of Climate, Meteorology & Atmospheric Sciences, University of Illinois Urbana-Champaign

This study aims to understand the trends in air pollutant concentrations across five megacities, Shanghai, Delhi, Paris, Los Angeles, and São Paulo, from the year 2018–2020. Relevant Air Quality Data for PM_2.5, PM₁₀, O₃, NO₂, and SO₂ were obtained from sources such as the World Air Quality Index and the U.S. Embassy and Consulates’ air quality monitors, and compared with various meteorological elements to ascertain the annual and seasonal trends in air quality. The findings revealed significant variations in key pollutants such as PM_2.5, PM₁₀, Ozone (O₃), Nitrogen Dioxide (NO₂), and Sulfur Dioxide (SO₂). According to our findings, Shanghai exhibited an overall decrease in PM_2.5 and SO₂ levels over the period, while concentrations for O₃ and PM₁₀ remained stable. Delhi showed significant seasonal fluctuations in PM_2.5 and PM₁₀ levels, with the highest pollution levels during the paddy burning season and the lowest during the monsoon season, with a notable reduction in NO₂ and SO₂ concentrations, reflecting better vehicular and industrial emissions standards. Paris displayed a clear downward trend in PM_2.5, PM₁₀, and NO₂ levels, exhibiting the effectiveness of their measures in reducing emissions from vehicle and industrial sources.

PM_2.5 and PM₁₀ levels in Los Angeles showed slight variations throughout the year with sudden unexpected peaks in air pollution, with a consistent decline in NO₂ and SO₂ concentrations, indicating improved air quality management. São Paulo showed variability in PM_2.5 and NO₂ levels, while O₃ concentrations fluctuated, reflecting the complexities of urban pollution control. This study highlights the impact of regulatory measures, industrial activities, and meteorological conditions on air quality, and emphasizes the importance of continuous monitoring and effective pollution control strategies.

8.10. Size-Resolved Aerosol Mass Concentrations, Elemental Composition, and Long-Range Transport Effects in Four Moroccan Coastal Cities

Abdelfettah Benchrif ¹, Mounia Tahri ¹, Bouchra Oujidi ², Hamid Bounouira ³

¹ 

Division of Earth and Environment Sciences (DSTE), Geochemistry and Chemical Pollution Unit (UGPC), National Centre for Nuclear Energy, Science and Technology (CNESTEN), Rabat B.P. 1382, Morocco

² 

Faculty of Sciences, Mohammed V University, RP 10000, Rabat B.P. 1014, Morocco

³ 

Neutron Activation Analysis Laboratory, National Centre for Nuclear Energy, Science and Technology (CNESTEN), Rabat B.P. 1382, Morocco

Morocco has experienced notable urban and industrial growth in recent years, resulting in increasing air pollution concerns. This study investigates the characteristics of size-resolved aerosols (PM₁₀ and PM_2.5) and their sources across four distinct locations: two Mediterranean coastal cities (Tetouan and Nador) and two Atlantic coastal cities (Kenitra and Salé). Aerosol samples were collected and analyzed for elemental composition (Al, Fe, Ni, V, Cu, Cr, Zn, and Pb) using a range of analytical techniques such as Total X-ray Fluorescence (TXRF), Atomic Absorption Spectroscopy (AAS), Microwave Plasma Atomic Emission Spectrometry (MP-AES), and Instrumental Neutron Activation Analysis (INAA). Gravimetric analysis was performed to determine daily PM mass concentrations. To evaluate the effects of long-range transport, air mass back-trajectories were generated using the HYSPLIT™ model. Source apportionment was conducted using inter-elemental ratios, Positive Matrix Factorization (PMF) receptor modeling, and air mass back-trajectory statistics. The analysis of inter-elemental ratios highlighted urban emissions, largely attributable to traffic and construction activities, as the primary anthropogenic source. Contributions from long-range transport were identified by linking PM mass concentrations with air mass flow directions, demonstrating the significant impact of emissions from the Mediterranean Basin and the Atlantic Ocean on air quality in Moroccan cities. Moreover, the PMF source apportionment indicated that the contributing sources vary between PM fractions. For PM_2.5, major sources were identified as vehicle exhaust/non-exhaust emissions, regional secondary aerosols, and local anthropogenic activities. In contrast, PM₁₀ was predominantly associated with soil dust, re-suspended road dust, and fresh/aged sea salt emissions. Finally, the study highlighted that the PM_2.5/PM₁₀ ratio is site-dependent. Mediterranean coast cities presented higher PM_2.5/PM₁₀ ratios (>0.5), indicating a significant contribution from fine anthropogenic particles. Conversely, Atlantic coastal cities displayed ratios below 0.5, suggesting a predominance of coarse particles, likely emanating from local pollution sources characteristic of those areas.

8.11. The Air Pollution Impacts of California’s 2018 Wildfires

Muhammad Shehzaib Ali ^{1, 2}, Swarnali Sanyal ³, Viney P Aneja ¹

¹ 

North Carolina State University, Raleigh, NC 27695, USA

² 

Department of Marine, Earth and Atmospheric Sciences

³ 

University of Illinois, Urbana, IL, USA.

Wildfires emit large quantities of air pollutants into the atmosphere and are emerging as a significant global threat. As global warming increases the frequency, intensity, and duration of wildfires, the resulting air pollution also increases. This study investigates the role of meteorological conditions and topographical features on the three-dimensional transport and distribution of PM_2.5 during California’s unprecedented 2018 wildfire season, with a particular focus on two major wildfires: the Mendocino Complex Fire and the Camp Fire. Multiple data sources, such as EPA ground monitoring stations, MODIS satellite products, and HYSPLIT trajectories, were integrated to analyze the horizontal and vertical pollutant transport patterns. The results revealed that persistent low-pressure systems and weak winds (≤2 m/s) created pronounced atmospheric stagnation, leading to pollutant accumulation near the surface. An analysis of PM_2.5-AOD (Aerosol Optical Depth) correlations demonstrated stronger relationships during wildfire events compared to baseline periods, indicating the significant role of the wildfire-induced aerosols throughout the atmospheric column. HYSPLIT back trajectory analysis during peak pollution episodes revealed that while air masses originated from the Pacific Ocean, they remained confined to lower atmospheric layers (below 1.5 km), exacerbating surface-level pollution. Due to these conditions, the Camp Fire, despite its shorter duration, demonstrated more severe air quality impacts than the larger Mendocino Complex Fire, highlighting the significant role of burning intensity and meteorological conditions in pollution transport.

9. Session 8: Aerosols

9.1. Association Between Particle-Bound Reactive Oxygen Species and In Vitro Oxidative Responses Induced by Traffic-Related Urban Nanoparticles

Gianluca Di Iulio ^{1, 2}, Francesca Costabile ^{2, 3}, Carmina Sirignano ^{2, 3}, Marco Paglione ^{3, 4}, Matteo Rinaldi ^{3, 4}, Maurizio Gualtieri ⁵, Silvia Canepari ⁶, Lorenzo Massimi ⁶, Maria Agostina Frezzini ⁷, Ferdinando Pasqualini ²

¹ 

Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy

² 

Institute of Atmospheric Sciences and Climate, National Research Council of Italy (CNR-ISAC), 00133 Rome, Italy

³ 

National Biodiversity Future Center (NBFC), 90133 Palermo, Italy

⁴ 

Institute of Atmospheric Sciences and Climate, National Research Council of Italy (CNR-ISAC), 40129 Bologna, Italy

⁵ 

Department of Earth and Environmental Sciences, University of Milano-Bicocca, 26126 Milan, Italy

⁶ 

Department of Environmental Biology, University of Rome Sapienza, 00185 Rome, Italy

⁷ 

Regional Environmental Protection Agency (ARPA), 00173 Rome, Italy

Exposure to fine particulate matter (PM1) has been associated with health impacts, but understanding PM1 concentration–response (PM1-CR) relationships remains incomplete, especially at low PM1 levels. Here, we present data related to the RHAPS experiment carried out in the Po Valley in 2019 [1].

This study investigated the association between particle-bound reactive oxygen species (PB-ROS) and in vitro pro-oxidative responses. To mimic exposure of the lungs to ambient air, we employed an Air–Liquid Interface (ALI) model using cultures of human bronchial epithelial cells (BEAS-2B). PB-ROS were measured using the DCFH assay via two approaches: offline 24-h resolution measurements from PTFE filters (PB-ROS_filter) and semi-continuous (2-h resolution) measurements using a Particle-Into-Liquid Sampler (PILS) (PB-ROS_PILS).

A comparative analysis of the PB-ROS_filter and PB-ROS_PILS measurements showed significant differences in the types of ROS detected, primarily driven by the sampling resolution. The PB-ROS_filter measurements predominantly identified long-lived species, which are more stable and indicative of aged aerosols, associated with secondary organic aerosols (SOAs). In contrast, PB-ROS_PILS measurements revealed transient PB-ROS related to urban nanoparticles, which are abundant during the day due to traffic emissions and photochemical processes. Statistically significant correlations suggest that transient PB-ROS are influenced by fresh traffic nanoparticles, with the Condensation Sink (CS) playing a decisive role in their persistence in the atmosphere. The CS having a low value indicates atmospheric conditions in which condensable compounds (including ROS) do not sink rapidly into pre-existing accumulation-mode particles and may form nanoparticles [1].

Finally, this study highlights a positive correlation between the mass-normalized PB-ROS_PILS and oxidative stress gene expression, underscoring the potential health implications of short-lived ROS. Limitations of this study relate to the limited temporal coverage of the PILS and the absence of fully online ROS detection methods for characterizing highly reactive species, which may pose immediate health risks in urban environments with fresh emissions.

9.2. Development of an Analytical Method for Atmospheric Humic-like Substances That Uses High-Performance Liquid Chromatography and an Automated Pretreatment Technique

Mera Koki, Arita Daiki, Kameda Takayuki

• Department of Energy and Environmental Engineering, Graduate School of Energy Science Kyoto University, Kyoto 606-8501, Japan

Introduction: Humic-like substances (HULISs) are a group of substances with no specific chemical structure, resembling the humic substances found in soil and water. They constitute the main component of water-soluble organic matter in the atmosphere and are known to exhibit absorption properties in the ultraviolet to visible light range, potentially influencing atmospheric radiative balance. Understanding their environmental dynamics is therefore crucial. However, existing analytical methods for HULISs involve labor-intensive pretreatment steps, which can lead to reduced quantification accuracy and hinder improvements in analytical efficiency. To address this issue, this study aims to develop a system for HULIS analysis using high-performance liquid chromatography (HPLC) equipped with an integrated sample cleanup mechanism, enabling the direct analysis of atmospheric particles through their simple extraction using water.

Methods: The automated system for sample cleanup and detection consists of four HPLC pumps, an autosampler, a cleanup column (Oasis-HLB, 3 mmφ × 20 mm, Waters), a column heater, a six-port valve, and a photodiode array detector (DAD). The following steps were performed in accordance with a time program:

1.

Before sample injection, the flow path was cleaned with ultrapure water.

2.

The cleanup column was conditioned with methanol and ultrapure water.

3.

The system was acidified with hydrochloric acid (pH = 2).

4.

After injecting the sample, the HULISs in the acidified sample were adsorbed onto the column.

5.

HULISs were eluted with a 2% ammonia–methanol solution (w/w) and detected using the DAD.

Results and Conclusions: This automated pretreatment analysis system achieved highly favorable peaks. The recovery rate of a 100 mg/L standard fulvic acid solution was 91.2 ± 0.9% with this method, under optimal conditions. We are planning to optimize the time program conditions and apply this system to actual atmospheric samples.

9.3. Evaluation of Oxidative Potential of Nitrogen-Containing Heterocyclic Compounds and Their Metal Complexes by the DTT Assay

Siwoo Kim, Takayuki Kameda

• Department of Socio-Environmental Energy Science/Graduate School of Energy Science, Kyoto University, Kyoto 606-8501, Japan

Atmospheric particulate matter (PM) is known to induce oxidative stress by generating reactive oxygen species (ROS) when inhaled. To understand the sources of ROS production by PM, evaluating its individual components is essential. Previous studies have reported that metals and oxidized derivatives of polycyclic aromatic hydrocarbons (PAHs) exhibit high ROS generation capacity. However, the diversification of energy sources has raised concerns about the emergence of new harmful air pollutants, such as nitrogen-containing organic compounds, including nitrogen heterocyclic compounds (PANHs). PANHs can act as ligands, forming coordination complexes with metals such as iron, but the ROS production capability of such complexes remains unclear.

This study evaluated the oxidative potential (OP) of coordination complexes as an indicator of ROS production using the Dithiothreitol (DTT) assay. Test samples included 1,10-Phenanthroline iron(II) perchlorate (Fe-phen), Tris(1,10-Phenanthroline) cobalt(II) bis(hexafluorophosphate) (Co-phen), and Tris(2,2′-Bipyridine) cobalt(II) bis(hexafluorophosphate) (Co-bpy). For comparison, divalent iron [Fe(II)], cobalt [Co(II)], copper [Cu(II)], and manganese [Mn(II)] were also tested. DTT consumption rates were measured spectrophotometrically at 415 nm after reaction with the test samples for 20 min.

The formation of coordination complexes generally increased OP compared to individual metal ions or ligands. Notably, the Fe-phen complex exhibited a DTT consumption rate 50 times higher than Fe(II) alone, while the Co-bpy complex showed a 10-fold increase compared to Co(II). Furthermore, the DTT consumption rates of all complexes exceeded those of Cu(II), which has previously been reported to exhibit relatively high OP. To thoroughly evaluate the contribution of these complexes to the OP of atmospheric particles, it is essential to obtain atmospheric concentration data for each complex. Therefore, future studies should focus on developing sample preparation methods as well as separation and analytical techniques for detecting and quantifying these complexes in real atmospheric particles.

9.4. Integrating Planetary Health and Nature-Based Solutions: Assessing the Impacts of Traffic-Related Air Pollution on Human and Plant Health in Urban Forests

Carmina Sirignano ^{1, 2}, Lina Fusaro ^{2, 3}, Daiane de Vargas Brondani ^{1, 2}, Gianluca Di Iulio ^{1, 4}, Luca Mortarini ^{1, 5}, Andrea Scartazza ⁶, Chiara Anselmi ⁶, Stefano Listrani ⁷, Alessandro Giammona ^{2, 8}, Clarissa Gervasoni ^{2, 8}, Annamaria Altomare ^{9, 10}, Tony Christian Landi ¹, Alessandro Di Giosa ⁷, Maria Crisitina Facchini ¹, Stefano Decesari ^{1, 2}, Carlo Calfapietra ^{2, 6}, Gloria Bertoli ^{2, 8}, Francesca Costabile ^{1, 2}

¹ 

Institute of Atmospheric Sciences and Climate (CNR-ISAC)

² 

National Biodiversity Future Center (NBFC)

³ 

Institute of BioEconomy (CNR-IBE)

⁴ 

Department of Public Health and Infectious Diseases, Sapienza University of Rome, Italy

⁵ 

Department of Earth Sciences “Ardito Desio”, ‘Università degli Studi di Milano’

⁶ 

Research Institute on Terrestrial Ecosystems (CNR-IRET)

⁷ 

Regional Environmental Protection Agency (ARPA) Rome, Italy

⁸ 

Istituto di Bioimmagini e Sistemi Biologici Complessi (CNR-IBSBC)

⁹ 

Research Unit of Gastroenterology, Università Campus Bio-Medico di Roma

¹⁰ 

Department of Sciences and Technologies for Sustainable Development and One Health, Università Campus Bio-Medico di Roma

Addressing climate change, biodiversity loss, global pollution, and planetary health requires novel holistic approaches. Here, we present the initial results of the NBFC project (www.nbfc.it/en (accessed on 1 September 2025)), combining numerical modelling and observational data to assess the interplay between exposure to urban air pollution and human and plant health.

The analysis was conducted in an urban forest in Rome (Italy). We assessed the potential of freshly emitted traffic-related air pollution (TRAP) to cause oxidative stress and inflammation in humans and plants. Fresh TRAP is characterized by high levels of emerging atmospheric pollutants (black carbon, ultrafine particles, and reactive oxygen species; EC/2024/2881) and low levels of fine particulate matter (PM_2.5), which in an urban environment can occur after precipitation or ventilation events. TRAP-associated epigenetic markers of inflammation and oxidative stress (microRNA) were assessed on human lung epithelial cell lines and human specimens over sub-daily periods (6–12 h). Functional traits related to photosynthetic machinery were analysed on two evergreen species, Quercus ilex L. and Laurus nobilis L., which were sampled at increasing distances from a major road and expected to have different sensitivities to PM_2.5-induced oxidative stress. The Parallelized Large-Eddy Simulation Model (PALM) was used to simulate vegetation cover variations, using two nested domains with different resolutions and treating aerosol as a passive tracer.

The preliminary results show pro-oxidative and inflammatory responses in humans after exposure to fresh TRAP. A reduction in TRAP-related BC is observed when air masses traverse specific urban forest transects with a higher leaf index, particularly during months of high vegetative activity.

An analysis of these findings can provide proof of a cause–effect relationship between short-term exposure to fresh TRAP and oxidative stress in humans and plants, with implications for chronic responses. In a highly urbanized world, this evidence could be pivotal for motivating the widespread implementation of nature-based solutions (NBSs) to address planetary health.

9.5. Seasonal Characteristics of Spectral Absorption and BC Source Apportionment at a Background Site in the Southern Balkans

Nestor Kontos ^{1, 2}, Martha Seraskeri ^{1, 2}, Miltiadis Mihalopoulos ^{1, 2}, Paraskevi Kardolama ^{1, 2}, Marina V Karava ^{1, 2}, Iliana Tasiopoulou ^{1, 2}, Rafaella-Eleni P Sotiropoulou ^{2, 3}, Dimitris Kaskaoutis ⁴, Efthimios Tagaris ^{1, 2}

¹ 

Department of Chemical Engineering, University of Western Macedonia, 50100 Kozani, Greece

² 

Air & Waste Management Laboratory, Polytechnic School, University of Western Macedonia, 50100 Kozani, Greece

³ 

Department of Mechanical Engineering, University of Western Macedonia, 50100 Kozani, Greece

⁴ 

National Observatory of Athens

Carbonaceous aerosols constitute a major component of the lower atmosphere in both urban and rural environments, originating from a variety of natural sources and anthropogenic combustion processes. This study examines the seasonal variability of BC and its fractions related to fossil fuel combustion (BC_ff) and biomass burning (BC_bb), along with the spectral absorption characteristics associated with BC and BrC. Aethalometer (AE-33) measurements were performed and analysed at a continental background site in NW mountainous Greece (Kozani, 40.27° N, 21.76° E, 768 m a.m.s.l) throughout the year 2023. The measuring station, located within the University of Western Macedonia campus, is mostly affected by regional background aerosol plumes with different optical and physicochemical characteristics. Major contributing sources include emissions from nearby lignite-fired power plants, the long-range transport of polluted air masses from the Balkan region, and, to a lesser extent, local emissions such as traffic within the university campus—where private vehicle use is restricted—and domestic heating in nearby villages (1–2 km away), particularly during the winter season. Furthermore, secondary aerosol formation plays a role in modifying the local aerosol burden. Hourly BC concentrations ranged from ~0.1 μg m⁻³ to ~2.2 μg m⁻³, with higher concentrations noted during winter due to enhanced residential biomass burning for heating. The BC_bb is about 50% during winter and much lesser (~25%) during summer, reflecting the absence of combustion processes and dominance of fossil-fuel sources, although the summer BC concentrations are low. Absorption due to BrC is mostly detected during winter, while its summer values are significantly lower. The contribution of BrC to the total absorption recorded is about 44% at 370 nm during winter, dropping to 16% during summer. This seasonal contrast reflects the influence of biomass combustion in the winter and the dominance of secondary organic aerosol formation and naturally occurring sources of BC during the summer.

9.6. Using the Synergy of the Spectral Dependence of Scattering and Absorption for Aerosol Type Identification and the Application of This Method over a Continental Background Site in NW Greece

Martha Seraskeri ^{1, 2}, Nestor Kontos ^{1, 2}, Miltiadis Mihalopoulos ^{1, 2}, Paraskevi Kardolama ^{1, 2}, Marina V Karava ^{1, 2}, Iliana Tasiopoulou ^{1, 2}, Rafaella-Eleni P Sotiropoulou ^{2, 3}, Dimitris G. Kaskaoutis ^{1, 2}, Efthimios Tagaris ^{1, 2}

¹ 

Department of Chemical Engineering, University of Western Macedonia, 50100 Kozani, Greece

² 

Air & Waste Management Laboratory, Polytechnic School, University of Western Macedonia, 50100 Kozani, Greece

³ 

Department of Mechanical Engineering, University of Western Macedonia, 50100 Kozani, Greece

Aerosol particles suspended in the atmosphere originate from a variety of natural and anthropogenic sources, with their optical, physical, and chemical properties often serving as indicators of their origin. However, long-range aerosol transport, ageing processes, and the mixing (external and internal) of various types in the atmosphere render aerosol-type identification a real challenge. Nevertheless, several techniques and classification matrices have been established for the better classification of aerosols into groups representative of their specific or dominant sources.

In this context, this study focuses on the first attempt at aerosol-type classification using in situ measurements from an aethalometer and a nephelometer at a continental background site in NW Greece (Kozani; 40.27° N, 21.76° E, 768 m). The classification matrix was based on the combined analysis of the Absorption Ångström Exponent (AAE) and the Scattering Ångström Exponent (SAE) values over a one-year period (2023).

Using appropriate threshold values, seven key aerosol types were identified and analyzed in terms of their seasonal, monthly and diurnal variations. The Black Carbon (BC)-dominated type was the most frequent, indicative of a regional background atmosphere influenced by fossil fuel combustion. A mixed Brown Carbon (BrC)–BC type was also frequently observed in winter, along with occasional occurrences of a pure BrC type, both of which are associated with biomass burning for residential heating in nearby villages. Another common category was a mix of large aerosols and BC, present throughout the year, while dust was detected episodically, primarily during Saharan dust transport events. Two types of aerosol, characterized by AAE values below 1 for fine (SAE > 1) and coarse (SAE1), were of lower frequency, indicating a possible mixing of carbonaceous aerosols with inorganic species of weaker spectral absorption. We analyzed the spectral absorption and scattering coefficients of each type of aerosol, as well as their single scattering albedo and PM_2.5 levels, which exhibit substantial seasonal variations.

10. Session 9: Air Pollution Control

10.1. A Holistical Approach for the Minimization of Nitrous Oxide (N₂O) Emissions from Brewery Wastewater Treatment Using Malt-Sprout-Derived Biochar

Pelin Yapicioğlu

• Department of Environmental Engineering, Engineering Faculty, Harran University, Sanliurfa, Turkey

Industrial wastewater treatment is regarded as one of the significant greenhouse gas (GHG) resources by the Intergovernmental Panel on Climate Change (IPCC). Nitrous oxide (N₂O) is a major GHG which could be released from agro-industrial wastewater treatment plants. From this point of view, this study investigated the minimization of the nitrous oxide (N₂O) emissions originating from brewery wastewater treatment using malt-sprout-derived biochar. The main objective of the study was the minimization of N₂O emissions from brewery wastewater treatment using the biochar adsorption process. The hypothesis of this study was that biochar could effectively uptake the N₂O from wastewater due to the higher adsorption capacity from the soil. This study was unique in that malt-sprout-derived biochar was used as the N₂O adsorbent for brewery wastewater treatment. The biochar was derived using slow pyrolysis at three different temperatures: 300 (MS1), 400 (MS2), and 550 °C (MS3). The malt sprout and industrial wastewater were ensured from a full-scale brewery industry wastewater treatment plant in Turkey. The correspondence between the N₂O emission and wastewater treatment quality was investigated by Monte Carlo simulation. The gas resulting from wastewater treatment was collected and determined using gas chromatography equipped with an electron capture detector (GC-ECD). N₂O was sampled and measured seasonally, before and after the biochar adsorption process. Furthermore, gas adsorption was performed using the same biochar to verify the N₂O capture capacity of the biochar and minimize the GHG emissions. An average of 25.6% of minimization in N₂O emissions from brewery wastewater was reported using malt-sprout-derived biochar. The simulation results showed that the total Kjeldahl nitrogen (TKN) and ammonium (NH₄-N) had the highest correspondence with N₂O emissions. The highest N₂O uptake capacity was correlated with the biochar derived at the lowest temperature (MS1).

10.2. Reducing Carbon Dioxide (CO₂) Emissions in Residential Buildings Through Envelope Renovation

Samuel Aires Master Lazaro ¹, Xiangyu Li ¹, Vanessa Fathia Baba ²

¹ 

College of Civil Engineering, Taiyuan University of Technology, No. 79 West Street Yingze, Taiyuan 030024, China

² 

College of Economics & Management, Taiyuan University of Technology, No. 79 West Street Yingze, Taiyuan 030024, China

The construction sector significantly influences environmental development and is a significant source of carbon dioxide (CO₂) emissions worldwide. Over the years, the sector’s decision-making procedures have frequently prioritised economic concerns over sustainability. Nonetheless, recently, there has been growing recognition of the importance of evaluating the environmental impacts at every stage of a building’s lifecycle, from the design process to its demolition. This study uses Design Builder software to simulate a base case residential building in Mozambique, aiming to identify the most impactful design parameters for reducing its CO₂ emissions while reducing its energy consumption. By analysing data from both the base case and modified design schemes, this research reveals that employing 95 mm thick foamed expanded polystyrene (EPS) panels for roofing and double glazing of 6 mm/13 mm within an air/wood frame for exterior windows can reduce the energy consumption by 42.14% and decrease CO₂ emissions by 42.20% compared to these values in conventional construction designs. These results emphasise how crucial it is to use alternative building materials to reduce energy consumption and lessen the environmental impact of residential buildings. This study also urges stakeholders to embrace progressive policies and practices that promote sustainable growth in the industry and push for a paradigm change that strikes a balance between environmental and economic viability.

10.3. A Spatiotemporal Downscaling Framework Based on Machine Learning for Hourly 1 km PM_2.5 Mapping in China

Jingru Cao, Qingqing He

• School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China

PM_2.5 pollution is a global environmental problem, and its hourly exposure characteristics are closely related to short-term health risks. Traditional estimation methods are mainly based on satellite AOD, which are limited by AOD’s daily timescale and cloud/snow interference, resulting in difficulties in meeting the short-term prediction needs of PM_2.5 pollution and in achieving high spatial resolution. This study proposes a spatiotemporal downscaling framework based on the Light-GBM (ST-Light-GBM) algorithm that integrates multi-source data. It innovatively integrated the daily 1 km PM_2.5 data derived from AOD and other auxiliary predictors as a primary predictor for the hourly modeling instead of using the satellite AOD directly. Based on this, coupling with meteorological high-temporal-resolution data, this study successfully constructed a 1 km, hourly PM_2.5 concentration prediction model. Testing on China in 2019, cross-validation results showed that the model was significantly superior to traditional methods in three dimensions (the random 10-fold cross-validation (10CV) R² reached 0.94, the spatial 10CV R² was 0.85, and the temporal 10CV R² was 0.92). The modeling process results indicated that incorporating the daily average variation in PM_2.5 is important in capturing the hourly fluctuation characteristics, with a 0.84 correlation coefficient with hourly measurements and ranking top in variable importance analysis. The framework developed in this study realizes the importance of daily PM_2.5 in the dynamic downscaling modeling of hourly concentration, providing a theoretical paradigm for building a “daily constraint-hourly response” PM_2.5 prediction model, and produces gap-free PM_2.5 data with both high spatial and temporal resolution for supporting refined pollution prevention and control and health risk assessment.

10.4. Assessing Air Quality Through Tree Bark Biomonitoring of Praseodymium in Leicestershire, UK

Antonio Peña-Fernández ^{1, 2}, María de los Ángeles Peña ³, Carmen Lobo-Bedmar ⁴

¹ 

Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Ctra. Madrid-Barcelona, Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.

² 

Leicester School of Allied Health Sciences, De Montfort University, Leicester LE1 9BH, UK.

³ 

Departamento de Ciencias Biomédicas, Universidad de Alcalá, Crta. Madrid-Barcelona Km, 33.6, 28871 Alcalá de Henares, Madrid, Spain

⁴ 

Departamento de Investigación Agroambiental. IMIDRA. Finca el Encín, Crta. Madrid-Barcelona Km, 38.2, 28800 Alcalá de Henares, Madrid, Spain.

Praseodymium (Pr) has been detected in the air of the city of Leicester (England). To further biomonitor air quality for Pr, thin layers of bark were collected from 96 trees in Leicester (n = 55) and surrounding rural/suburban areas (41). Pr was monitored by ICP-MS [LoD = 0.157 ng/g dry weight (dw)]. Levels were slightly higher in the samples collected from trees growing in urban areas (median and ranges, in ng/g dw): 2.611 (0.714–47.603) and 2.450 (0.757–14.839). Pr content varied between bark samples collected across the city (medians, in ng/g dw): 11.374 (SE) > 4.183 (SW) > 2.471 (NE) > 1.967 (NW), and between the three quadrants into which the rural areas were divided: 7.348 (NW) > 2.244 (NE) > 0.881 (SE). Finding a hypothesis that could explain the differences found is challenging as the atmospheric transport of this metal and other rare earth elements (REEs) is poorly understood. However, our results could suggest that the airborne Pr content is little influenced by its presence in the topsoils, as the patterns found were different for the two main areas: NE > SW > SE > NW and SE > NE > SW > NW. Levels were much higher than the range reported in bark samples (1.85–2.69 ng/g dw) collected in an area of eastern Washington (US) with little anthropic pollution, suggesting that the air quality of Leicestershire would have some anthropic input. However, the enrichment factors (0.436 and 0.487), calculated in relation to the average Pr concentration in the Earth’s continental crust and the scandium content, were very low in both areas, suggesting no discernible enrichment. These values were also lower than those observed for other REEs monitored in the same bark samples, reinforcing the minimal anthropogenic input of Pr into the air of Leicester city and surrounding areas, as REEs are known to behave as a coherent group of elements in plants.

10.5. Concept and Development of Air Quality Sensor for Citizen Science

Dmitriy Gordienko, Valeriia Polkhanove, Semen Sochilov, Anastasiia Varlamova, Alexander Vikulov

• Bauman Moscow State Technical University, 2nd Baumanskaya Str., 5, Moscow 105005, Russia

This paper presents the concept and development of an autonomous DIY air quality sensor for citizen science. Large civil monitoring projects often rely on air quality calculations based on PM_2.5 and PM₁₀ dust readings in combination with some gases and do not cover the full list of air quality indicators. The authors have analyzed existing air quality calculation methodologies and attempted to conceptualize a universal AQI monitoring device for use in citizen science and by volunteers. This device is based on the available ESP32 DevKit v1 platform to which compatible sensors have been selected to monitor AQI indicators such as PM_2.5 and PM₁₀ dust particles, Ozone, Carbon Monoxide, Nitrogen Dioxide, Sulphur Dioxide, and Ammonia. The SD card module was chosen for data storage, the NB-IoT module for data transmission, and a battery pack for autonomy. The housing, sensor design components and fasteners were also selected. All components are available on the international market. Based on the selected element base, an electrical connection diagram was designed, the device’s design, presented in the form of 3D models, was developed, and the assembly process was described. The cost of the device was also evaluated and compared to the price level of existing DIY devices used in citizen science.

10.6. Daily High-Resolution XCO₂ Mapping Across China Using OCO-2 Data and Machine Learning Model

Yuan Liu, Qingqing He

• School of Resource and Environmental Engineering, Wuhan University of Technology, China

Accurately monitoring the spatiotemporal distribution of atmospheric CO₂ is essential for understanding the carbon cycle, formulating effective emission reduction strategies, and achieving carbon neutrality. However, research in this area is constrained by a lack of high-quality carbon monitoring data. While satellite remote sensing technologies can provide atmospheric CO₂ data with a high spatial resolution and broad coverage, inherent limitations often result in substantial data gaps. Addressing these gaps and generating high-resolution, gap-free CO₂ concentration datasets have thus become a critical research focus. This study utilizes column-averaged dry air CO₂ mole fraction (XCO₂) data retrieved from the OCO-2 satellite (2021–2022) as its observational input. It integrates XCO₂ data from the coarse-resolution CarbonTracker (CT) reanalysis (3° × 2°) and multiple environmental variables as the predictive inputs to develop and optimize an extreme random tree (ET) model. The goal is to generate a daily, high-resolution (0.01°) XCO₂ dataset with full spatial coverage across China. Spatiotemporal cross-validation demonstrates the model’s high accuracy and stability, yielding an R² of 0.93 and an RMSE of 0.75 ppm. Independent validation using data from the TCCON and WDCGG sites further confirms the model’s effectiveness in capturing atmospheric CO₂ dynamics. This approach not only bridges critical gaps in the existing observational networks but could also enhance carbon cycle analyses and related research. Additionally, it can be extended to longer time series and broader regions, providing robust scientific support for policymakers in climate decision-making.

10.7. Research on Synchronous Estimation of Ultra-High Spatiotemporal Resolution Concentrations for Six Standard Air Pollutants Using Satellite Remote Sensing and Street View Data

Zizheng Li, Qingqing He

• School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China

PM_2.5, PM₁₀, sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) are six fundamental pollutants in atmospheric pollution, posing significant threats to human health and the ecological environment. Given the high spatiotemporal heterogeneity of atmospheric pollutants, there is a lack of in-depth exploration into the fine spatial variations and interactions among multiple atmospheric pollutants, at ultra-high spatiotemporal resolution. In addition, most of the current studies are single-pollutant predictions, which are deficient in time and resource consumption compared with multi-pollutant synergistic predictions. To address these issues, we integrated ground-measured pollutant data, top-of-atmosphere (TOA) radiation remote sensing data, Baidu Street View data, reanalysis data, and other relevant spatiotemporal data. Using a multi-output extremely randomized trees model, we collaboratively predicted six atmospheric pollutants, generating an ultra-high-spatiotemporal-resolution (temporal resolution: hourly; spatial resolution: 100 m) dataset of atmospheric pollutants in Wuhan, where air quality still suffers from concentration exceedances in the year 2023. The ten-fold cross-validation R² for PM_2.5, PM₁₀, O₃, NO₂, CO, and SO₂ models were 0.71–0.95, respectively. Synergistic prediction models consume only one-fifth the time of single prediction models. The spatiotemporal analysis revealed that among them, the annual average values of PM_2.5 and PM₁₀ exceeded the first-level concentration limits in China. In addition, the annual average values of pollutants have obvious spatial and temporal heterogeneity, showing a distinct spatial pattern of higher concentrations in urban centers and decreasing outwards. Correlation analyses on annual and hourly scales showed some correlation between atmospheric pollutants. In addition, the correlation between them was found to be dynamic over time at the hourly scale. These findings provide a comprehensive, high-resolution dataset of atmospheric pollutants in Wuhan, offering valuable insights into their spatiotemporal distribution and interactions.

10.8. Tree Bark Biomonitoring of Lutetium Contamination in Leicestershire, England

Antonio Peña-Fernández ^{1, 2}, Carmen Lobo-Bedmar ³, Gurminderjeet S. Jagdev ², Mark D. Evans ², María de los Ángeles Peña ⁴

¹ 

Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Ctra. Madrid-Barcelona, Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain.

² 

Leicester School of Allied Health Sciences, De Montfort University, Leicester LE1 9BH, UK.

³ 

Departamento de Investigación Agroambiental. IMIDRA. Finca el Encín, Crta. Madrid-Barcelona Km, 38.2, 28800 Alcalá de Henares, Madrid, Spain.

⁴ 

Departamento de Ciencias Biomédicas, Universidad de Alcalá, Crta. Madrid-Barcelona Km, 33.6, 28871 Alcalá de Henares, Madrid, Spain

Tree bark was used to gain an understanding of the atmospheric presence of lutetium (Lu) in Leicestershire (UK). Bark samples were collected from 96 trees in Leicester (n = 55), as well as from the surrounding rural/suburban areas (41). Lu was monitored using ICP-MS in cleaned/ground/homogenised samples mineralised with HNO₃/H₂O₂ [LoD = 0.000654 ng/g dry weight (dw)]. The results were compared with those of previous studies performed on 106 mushrooms and 850 topsoils collected from the same areas. Slightly higher levels were found in bark samples collected in rural areas (median and ranges, in ng/g dw): 0.584 (0.402–1.071) vs. 0.580 (0.182–2.118), which is in line with the trend detected in the topsoils [0.123 (0.069–0.162) vs. 0.117 (0.084–0.182), mg/kg]. This may be logical as metals released into the air from pollution sources will eventually reach the soil surface. However, the content of Lu was higher in mushrooms collected in the main urban area [0.347 (0.285–293.837) vs. 0.196 (0.780–8.116), ng/g dw)], which could be explained by the small effect of topsoils on the levels of Lu detected in mushrooms, as they showed no statistical correlation (p-value = 0.506). Furthermore, our previous observations showed minimal anthropic contamination in the topsoils, which could explain the similar concentrations of Lu in the bark of trees monitored in the urban and rural areas. Lu content varied between bark samples collected across the city of Leicester (median values, in ng/g): 0.892 (SE) > 0.646 (SW) > 0.585 (NE) > 0.544 (NW). Similarly, lower concentrations were found in the soil samples monitored in parks located in the northwest quadrant. The calculated enrichment factors were 2.15 and 2.58 using scandium relative to the upper continental crustal concentration, suggesting particulate phase deposition of Lu at natural background levels in both areas of Leicestershire. However, further studies are required as the atmospheric transport of Lu and other lanthanide elements is poorly understood.