ASAQ Seminar Series

3 Dec 2025, 09:00 → 4 Dec 2025, 17:30 UTC

Online

Bertrand TCHANCHE (Alioune Diop University)

Welcome to the ASAQ Annual Seminar.

Air quality research in Africa has grown in recent years but remains limited compared to other continents. Most studies focus on urban centers, with significant gaps in monitoring, data availability, and health impact assessments. The continent faces rising air pollution due to rapid urbanization and industrialization, yet systematic research and policy responses lag the scale of the problem.

We are pleased to announce this year’s Annual Seminar of the African Society for Air Quality (ASAQ), dedicated to advancing air quality research across Africa. This year’s seminar will bring together leading scientists to address the urgent challenges of air pollution on the continent.

Key topics will include:

• Pollutants and sources,
• Trends of ambient and indoor air pollution,
• AI and air quality data analytics,
• Instrumentation and advances in air quality monitoring,
• Health impacts,
• Effective management strategies,
• Ongoing projects and collaboration, 
• Training and capacity building
• Sustainable data infrastructure.

All those who wish to present their work on one of the above topics are requested to submit an abstract of less than 200 words.

Deadline for abstract submission: 16^th November 2025

Participation in the seminar is totally free of charge.

For any inquiries or questions, please contact us at: afs4aq@gmail.com.

Wednesday 3 December

09:00 → 09:30 Opening session

09:30 → 10:45 Trends of Ambient Air Pollution: S1

Convener: Dr Bertrand TCHANCHE (Alioune Diop University)

09:30 Environmental exposure disparities in urban markets: A Comparative air quality assessment in Lusaka, Zambia.

Background and study objective: To quantify PM2.5 and PM10 exposure differences between market infrastructure types and characterize temporal patterns.
Methods: Two low-cost PurpleAir sensors were installed to continuously monitor PM2.5 and PM10 concentrations for 8-week weeks (May 25–July 9, 2025), during dry season, in the exposed and control markets. Measurements were recorded every 2 minutes between 7 am and 7 pm. Data analysis synchronized monitoring periods when all sensors were active to minimize temporal confounding. Welch’s two-sample t-tests were conducted, with statistical significance, p<0.05.
Results: Total 16,079 observations were recorded. Exposure sites demonstrated significantly higher mean concentrations of PM2.5 (32.7 versus 27.6 μg/m³; difference: 5.1 μg/m³; 95% CI: 3.9–6.2; t = 8.63, p < 0.001) and PM10 (44.4 versus 33.3 μg/m³; difference: 11.1 μg/m³; 95% CI: 9.7–12.6; t = 15.05, p < 0.001) compared to control sites, an increase of 18.5% and 33.3%, respectively. PM2.5 levels at exposure sites exceeded the WHO 24-hour guideline value (15 μg/m³) by 118%. Diurnal patterns were observed at both locations, peak concentrations occurred mid-afternoon.
Conclusion: PM2.5 concentrations were significantly higher in unpaved, high-traffic market environments.

Speaker: Emmy Nkhama (Levy Mwanawasa Medical University)

09:45 Atmospheric Fine Particulate Matter (PM 2.5), Black Carbon, and Organic Carbon Levels in Oshakati, Namibia

INTRODUCTION: Ambient air pollution, particularly fine particulate matter (PM₂.₅; aerodynamic diameter ≤2.5 μm), poses a growing public health concern, contributing to cardiovascular, respiratory, and metabolic diseases. In Africa, where over 1.1 million deaths were attributed to air pollution in 2019, monitoring efforts remain limited due to the lack of ground-based data and electronic health records. Namibia does not have an air quality act, meaning there is no legal requirement to track air pollution levels, potentially exposing the population to harmful pollutant concentrations.
METHODOLOGY: This study measured ambient PM₂.₅ concentrations and selected chemical components—black carbon (BC) and organic carbon (OC) at an urban background site at the University of Namibia, Oshakati Campus (-17.78664, 15.69364). PM₂.₅ was sampled every sixth day from July 2021 to February 2023 using personal air samplers equipped with PTFE membrane filters, operating at a flow rate of 4.0 L/min for 24-hour collection periods. A total of 72 samples were obtained. BC and organic carbon OC levels were determined via an OT21 optical transmitter, which analyzed light absorption at 370 nm to estimate biomass-burning contributions.
RESULTS: Results showed PM₂.₅ concentrations ranging from 0.5 to 47.7 μg/m³, with a mean of 10.6 μg/m³, exceeding the WHO’s updated annual guideline of 5 μg/m³. The daily WHO limit of 15 μg/m³ was surpassed on 13 occasions. Average BC and OC concentrations were 0.8 μg/m³ and 0.9 μg/m³, respectively. Seasonal variations indicated the highest pollutant levels in winter, followed by spring, autumn, and summer.
CONCLUSION: This study provides the first documented assessment of PM₂.₅ and its carbonaceous components in Oshakati. Elevated pollutant levels, particularly in winter, suggest potential health risks for the local population, even at concentrations below established regulatory limits. Given the absence of national air quality monitoring regulations, these findings highlight the urgent need for systematic air pollution tracking and policy development in Namibia. Further research should include source apportionment studies and health risk assessments to better understand exposure impacts and inform mitigation strategies.

Speaker: Anna Alfeus (University of Namibia)

10:00 Mitigating traffic emissions: Strategies using Black Carbon as an indicator

A significant component of urban particulate matter (PM2.5) is black carbon (BC). BC is a primary pollutant and is emitted during the combustion of carbonaceous fuels. It is one of the most powerful light-absorbing substances in the atmosphere and significantly contributes to climate change. Black carbon particles can penetrate deep into the respiratory tract and contribute to respiratory and cardiovascular diseases. One of the major sources of BC is traffic, particularly diesel-powered vehicles. We will present the results of a recently published on-road measurement study that independently monitored the efficiency of the European vehicle emission standards. The study shows that diesel particulate filters (DPFs) reduce black carbon (BC) emission factors by 88% compared to pre-DPF Euro 4 diesel-powered cars [1]. We will also show the impact that the emission standards have on ambient air BC levels, and alternative mitigation strategies such as excluding super emitters from the vehicle fleet [2], and the impact of restricted areas and low-emission zones [3].

[1] Ježek Brecelj et al., Atmo.Chem.Phys., 2025

[2] Ježek et al., Atmo.Envir., 2018

[3]Titos et al., Atmo.Envir., 2015

Speaker: Irena Ježek Brecelj (Aerosol d.o.o.)

ASAQ2025 - Jezek Brecelj - Effective strategies to mitigate traffic emissions using Black Carbon as an indicator.pdf

10:15 Trends of Air Pollution in the Lazio Region of Central Italy: Insights from Satellite and Ground-Based Observations

Long-term monitoring of air pollutants is essential to evaluate the effectiveness of emission-reduction measures and to support compliance with the European Union (EU) Ambient Air Quality Directive (AAQD). In the Lazio region, including the metropolitan area of Rome, multiple studies provide complementary insights into trends of atmospheric pollution using satellite and ground-based remote sensing products.
Analysis of Aerosol Optical Depth (AOD) over the Lazio region shows a ~19 % decrease over the last 20 years, reflecting long-term improvement in particulate pollution (Terenzi et al., 2025). As AOD alone cannot fully represent local anthropogenic pollution, nitrogen dioxide (NO₂) vertical column density from the TROPOspheric Monitoring Instrument (TROPOMI) provides complementary information, enabling attribution to sources such as traffic and domestic heating (Bassani et al., 2023; 2021). Further analyses combining TROPOMI NO₂, formaldehyde (HCHO), and carbon monoxide (CO) with AOD helped identify persistent pollution hotspots, including in rural regions. Regarding climate, TROPOMI regional methane (CH₄) observations indicate a ~4 % increase in recent years, highlighting emerging air-quality and climate challenges. Complementing these regional-scale observations, the ground-based SkySpec spectrometer allowed identification of the spatial and temporal distribution of NO₂ and nitrous acid (HONO) within ~7 km radius areas.
These studies demonstrate the effectiveness of integrating satellite and ground-based remote sensing products for a comprehensive understanding of temporal and spatial trends in air pollution, supporting identification of emission sources, evaluation of mitigation strategies, and verification of implemented measures.

Speaker: Cristiana Bassani (Ialian National Research Council - Institute of Atmospheric Pollution Research (CNR-IIA))

10:45 → 11:00 BREAK

11:00 → 12:30 Atmospheric Pollution and Health Impacts: S2

Convener: Cristiana Bassani (Ialian National Research Council - Institute of Atmospheric Pollution Research (CNR-IIA))

11:00 PERFORMANCE OF PRE-CONSUMER WASTE COTTON MEMBRANE FOR FILTERING AEROSOLIZED PATHOGENS

Filter membranes and facemasks are among the most efficient methods to prevent respiratory pathogen transmission, even better than hand washing in terms of direct protection. For example, many people wore low-cost cotton masks during the COVID-19 pandemic with little efficacy. This study describes a simple method to develop porous membranes from waste cotton fabric using vacuum filtration. Natural cotton fibers were partially dissolved at various temperatures to maximize porosity, and the membrane collected at 80 °C (0.13 g fibers) provided the best pore uniformity. Scanning electron and tensile testing provided an average porosity of 57.87–62.60% and average pore area of 0.69 ± 0.46 μm, which were somewhat smaller than the 7 ± 0.2 μm pores of surgical masks. The membranes showed 72.4% sodium particle filtration efficiency and 99.8% bacterial filtration efficiency, which degraded to 82.4% after ten wash cycles consistent with BSEN14683:2019. Overall the data suggest waste cotton-derived filter membranes can be effective, eco-friendly pathogen filtration methods , in further research.

Speaker: Joshua William (PhD Students)

11:15 Source-Specific VOC exposure and health risk assessment in Abidjan (Côte d'Ivoire): A comparaison of traffic and domestic fires emissions

This study, conducted as part of the DACCIWA-FP7-WP2 project, investigated the health risks associated with urban air pollution and volatile organic compounds (VOCs) in Abidjan, Côte d'Ivoire. Two contrasting environments were monitored: a traffic site in Adjamé and a domestic fires site in Yopougon. Sixteen VOCs, including aromatics, alkanes, alkenes and monoterpenes (C₅–C₁₀), were identified using gas chromatography. Average total VOC concentrations were similar at both sites (85 µg/m³), but their diurnal patterns differed: rush-hour peaks were observed at the traffic site, while a morning peak was observed at the domestic fires site due to cooking and food smoking. BTEX compounds (benzene, toluene, ethylbenzene and xylenes) dominated, representing79.6–86% of total VOCs. Benzene concentrations reached9.8 µg/m³ in Yopougon, surpassing the European safety limit of 5µg/m³ and nearly doubling the level in Adjamé(4.5µg/m³). The estimated lifetime cancer risks(LCRs) for benzene were 6.7×10⁻² at the domestic fire site and 3.1×10⁻² at the traffic site, which far exceeds the acceptable threshold of 10⁻⁶. While non-carcinogenic risks were moderate, the carcinogenic potential, especially from benzene and ethylbenzene, poses serious public health concerns. These results highlight the need for stringent air quality regulations and targeted interventions to mitigate chronic exposure in Abidjan’s urban areas.

Speaker: Julien BAHINO (Université Félix Houphouet-Boigny Abidjan-Cocody)

ASAQ_COV.pdf

ASAQ_COV.pptx

11:30 Levels of Air Pollutants in School Environments in Hawassa City, Ethiopia, and Assessment of Potential Human Health Risks

Abstract

This study highlights significant concerns about air pollution in Hawassa City, Ethiopia, particularly within school environments. It found elevated levels of volatile organic compounds (VOCs), particulate matter (PM2.5 and PM10), and inorganic gaseous pollutants (NO2, CO, SO2), both indoors and outdoors. Highest total VOCs (TVOCs) concentration (83 μg/m3) was observed in the classroom of School 2, while the smallest TVOC concentration, 37 μg/m3 in the playground of School 8. The highest cumulative cancer risk (CCR × 106) and the total hazard ratio indicator (THRI) values were 126 and 1.58E-01 respectively, in the classroom of School 4. The hazard quotient (HQ) value indicated moderate health risks from PM exposure in many locations. Additionally, a notable proportion of outdoor sites had air quality deemed unhealthy for sensitive groups, with PM levels surpassing WHO standards in most sampling sites. The findings highlight significant health risks for children, including potential harmful effects from benzene exposure, as indicated by CCR and THRI values. Overall, the results underscore the urgent need for improved air quality management in schools to protect vulnerable populations from adverse health effects associated with air pollution.

Speaker: Dr Abebech Nuguse Amare (Hawassa University)

Dr Abebech PPT of Air pollution in primary schools in Hawassa city.pdf

11:45 BREAK

11:55 INDOOR AIR POLLUTION RELATED RESPIRATORY SYPTOMS AND ASSOCIATED FACTORS AMONG PREGNANT WOMEN IN HAWASSA CITY, SOUTHERN ETHIOPIA, 2025.

Abstract
Introduction:Exposure to indoor air pollution is major risk factor for respiratory disease, heart diseases and lung cancer. It is estimated over 4 million people died globally because of household air pollution where most of these people live in low and middle income countries in Asia and Africa. In Ethiopia, indoor air pollution is responsible for more than 50,000 deaths annually and causes nearly 5% of disease burden. Women exposed to indoor smoke 3 times more likely to suffer from chronic bronchitis and other COPD than women who cook and heat with electricity, gas or other cleaner fuel. This study can be used to understand indoor air pollution, respiratory related disease and increase public awareness among pregnant women.
Objective:to assess Indoor air pollution related respiratory symptoms and associated factors among pregnant women’s in Hawassa city, Southern Ethiopia,2025.
Method: A community-based cross sectional study design was conducted. The study was conducted from March 1-15,2025. Randomly selected pregnant women in Hawassa city were selected through simple random sampling (table of random sampling). About 197 samples will be selected.
Result: A total of 243 study participants were aimed in this study and 96.3%(234), were enrolled. The prevalence of respiratory symptoms among mothers in Hawassa city was 32.1% at 95% [CI: 26.4%–37.8%]. pregnant women who work in a poor (dusty or smelly) environment were 2.602 times more likely to develop respiratory symptoms than their counterparts (AOR = 2.602 at 95% CI: 1.122-6.036).Those respondents who had new carpet/furniture in HH were 1.134 times more likely to develop respiratory symptoms compared with their counterparts (AOR = 1.134 at 95% CI: 1.036-1.503).
Conclusion: The study enriches the prevalence of Indoor air related respiratory symptoms among pregnant women through different factors; The finding of this study revealed that dusty or smelly environment and presence of new carpet or furniture was associated with respiratory symptoms. The results can contribute to increasing knowledge on indoor air pollution related respiratory symptoms and necessary for suitable policy making.
Key word: indoor air pollution, pregnant women, respiratory symptom

Speaker: Bethlehem Yemane (Lecturer and Researcher)

12:10 Characterization of Air Pollutants and Health Impacts Associated with Charcoal Production in the Awi Zone

Charcoal production in low- and middle-income regions will continue to present multifaceted environmental and public health challenges due to emissions generated during biomass carbonization and related processes. This review will synthesize future trends in pollutant generation, emission dynamics, exposure pathways, and associated health and ecological impacts. It will further explore advancements in monitoring technologies, modeling frameworks, and mitigation strategies that will inform policy and intervention design. The review will highlight the necessity of integrated, evidence-based approaches that balance sustainable livelihoods with emission reduction and ecosystem protection.

Speakers: Desta Gebeyehu (Injibara University), Dr Muluken Mekuyie (Hawassa University)

13:30 → 14:30 Instrumentation and advances in air quality monitoring: S3

Convener: Abebech Nuguse Amare (Hawassa University)

13:30 Global and custom calibration approaches for Clarity’s Node-S air quality measurements.

For air quality monitoring in Africa and around the world, where sparse regulatory networks and challenging infrastructure often affect data collection, remote air quality sensors are an affordable ultimatum.
Clarity Movement provides advanced, IoT-enabled air quality monitoring solutions that combine precision sensing with global connectivity. The Clarity Node-S, integrates solar power, cellular communication, and weatherproof design to deliver reliable air quality data.
Two calibration systems are available: global pre-calibration and custom collocation calibration. The global calibration, applied at the factory using an extensive dataset of millions of measurements, provides consistent baseline performance across PM₂.₅ and NO₂ monitoring meanwhile, custom collocation calibration fine-tunes sensor output can further correct for local conditions, improving measurement precision (R² > 0.9 in optimal settings) by accounting for regional temperature, humidity, and pollution profiles.
Their ability to maintain accurate, MCERTS-certified performance in remote and variable environments makes them ideal for expanding measurement coverage across urban and rural areas alike. By combining flexible calibration and autonomous operation, Clarity’s system supports more equitable access to reliable air quality data, advancing public health and environmental research across the world.

Speaker: Marta O'Brien (Clarity Movement)

Marta O'Brien ASAQ 2025 Presentation - Global and custom calibration approaches Clarity Movement.pdf

13:45 An Overview of the Use of Low-Cost Electronic Sensors for Environmental Monitoring in Cameroon

Abstract: This work is a review of the various applications of low-cost electronic sensors used for environmental monitoring. It aims to provide an overview of the design, development, and application of electronic devices that we have carried out over the past five years in our research institute in Cameroon. These devices measure : air quality (Carbon monoxide (CO), Carbon Dioxide (CO2), Liquefied Petroleum Gas (LPG), Nitrogen dioxide (NO2), Sulfur dioxide (SO2), Ozone (O3), and Particulate Matter (PM)), water quality (Total Dissolved Solids (TDS), Electrical Conductivity (EC), pH, and Temperature), and radioactivity (ambient dose rate and radon gas). Industry, innovation, and infrastructure, responsible consumption and production, and the fight against climate change are goals 9, 12, and 13 of the World Health Organization's (WHO) Sustainable Development Goals (SDGs), which are aligned with this work. These locally manufactured devices leverage Internet of Things (IoT) technology and electronic sensors to provide in situ, real-time measurements of toxic gases, dust particles, water pollutants, and environmental radioactivity. Comparative analyses validated the accuracy and reliability of these devices against conventional and reference equipment, demonstrating their suitability for monitoring air and, water quality and ionizing radiation in urban areas, healthcare facilities, and industrial and mining sites.

Speaker: Mr Mbarndouka Taamté Jacob (Research Centre for Nuclear Science and Technology, Institute of Geological and Mining Research)

14:00 System Architecture and Deployment Engineering of AI_R for Indoor and Outdoor Air Quality Sensing

AI_R is a low-cost, scalable air-quality monitoring and prediction system that uses efficient sensing hardware, affordable IoT connectivity, and AI-based analytics to support informed decisions in public health, risk management, and environmental governance. The system includes two sensing solutions: an outdoor unit built around the Sensirion 55 sensor and the Nordic nRF9160 LTE-M/NB-IoT module with LoRa included for specific cases. It’s typically deployed in mines, industrial sites, and other harsh environments. The indoor unit is mostly used for buildings, conference spaces, hospitality settings, and homes, which connects to the cloud via Wi-Fi.

A key engineering feature of AI_R is its smart deployment tool, which enables true plug-and-play installation. The tool automatically captures essential deployment metadata, including node ID, physical location, firmware version, description, and configuration parameters, significantly reducing installation complexity and human error. The system supports over-the-air (OTA) firmware updates and leverages a centralized configuration database to ensure scalable, secure, and maintainable deployments across large, distributed networks. A companion Android user application provides real-time monitoring and device management for indoor deployments. Field experience has proven the architecture's effectiveness. Deployments across industrial sites, schools and homes have demonstrated rapid, error-free node registration and reliable operation over extended periods.

Speakers: Brenton Tapfumanei Munhungewarwa (University of Johannesburg (ZA)), Donald Ngobeni (University of the Witwatersrand and iThemba Labs)

14:30 → 14:40 BREAK

14:40 → 15:40 Instrumentation and advances in air quality monitoring: S4

Convener: Marta O'Brien (Clarity Movement)

14:55 Smart Pollution Monitoring for Sustainable Mobility: Low-Cost Environmental Sensing for Air Quality Assessment

Rapid urbanization and the growing demand for sustainable mobility are intensifying challenges related to air pollution and environmental management across African and global cities. This contribution introduces a smart pollution monitoring framework that integrates real-time environmental sensing with compact, low-power instrumentation to support cleaner and more efficient transportation systems. The research focuses on the Bosch BME688 metal oxide (MOX) sensor, a multi-gas device capable of detecting nitrogen dioxide (NO₂), isobutylene (C₄H₈), and volatile organic compounds (VOCs), while simultaneously measuring temperature, humidity, and pressure. Experimental results from both controlled laboratory tests and real-world deployments demonstrate the sensor’s capacity for distributed, high-resolution air quality monitoring and its sensitivity to environmental conditions that influence pollutant detection. A custom gas chamber, programmable thermal profiles, and LabVIEW-based control software were developed to enhance measurement precision and reproducibility. The findings highlight the potential of low-cost, scalable environmental sensing systems to complement conventional monitoring stations, enabling wider coverage and improved understanding of urban air quality dynamics. Such technologies can support evidence-based policy, strengthen local research capacity, and contribute to sustainable mobility planning and public health protection across the African continent.

Speaker: Salvatore Dello Iacono (University of Brescia)

20251204_SDI_ASAQ_AirQualityAfrica.pdf

15:10 Evaluation of Low-Cost passive sampling for urban ammonia (NH₃) measurement: Insights from the Akouédo Landfill, Côte d’Ivoire

This study, conducted as part of the European DACCIWA project (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa), presents the first long-term measurements of atmospheric ammonia (NH₃) near the Akouédo landfill in Abidjan, Côte d’Ivoire. From February 2015 to March 2017, simultaneous passive sampling was performed using INDAAF sensors and ALPHA badges. Ammonia concentrations were determined by ion chromatography to compare sensor performance and assess temporal variability in this polluted urban environment. A strong correlation was observed between the two samplers (r = 0.90; R² = 0.82), indicating consistent temporal patterns. Moderate discrepancies occurred during peak pollution events (MAE = 11.55 ppb; RMSE = 13.16 ppb), with the ALPHA sampler showing a systematic overestimation (mean bias = –28.3%) relative to INDAAF. Concentrations ranged from 8.0–59.0 ppb (mean = 29.2 ppb) for INDAAF and 16.4–73.2 ppb (mean = 40.8 ppb) for ALPHA. Seasonal trends revealed a marked increase in NH₃ levels during the rainy season (June), likely linked to enhanced microbial activity and waste decomposition. The strong agreement between passive samplers demonstrates their suitability as cost-effective tools for monitoring ammonia pollution and evaluating air quality dynamics in tropical urban environments.

Speaker: Julien BAHINO (Université Félix Houphouet-Boigny Abidjan-Cocody)

ASAQ_NH3.pdf

ASAQ_NH3.pptx

15:25 The Role of X-ray Spectrometry in the Evaluation of Ambient Air Particulates in the Middle East; an Innovative Perspectives to Estimate a Wide Range of Pollutants

The present work aims to investigate the presence and related concentration of different pollutants and their species in a wide range of ambient air particulates collected from different regions in the Middle East. Ambient air particulates were collected from different cities in the Middle East including; Cairo-Egypt, Amman-Jordan, Taif, and Jeddah-Saudi Arabia. The collected particulates are Total Suspended Particulates (TSP, > 100 µm), air particulate matter with an aerodynamic diameter equal or less than 10 µm (PM10,  10 µm), air particulate matter with an aerodynamic diameter equal or less than 2.5 µm (PM2.5,  2.5 µm), and fractionated air particulates ranging from 16 µm to 0.06 µm. For this purpose, laboratory-based X-ray fluorescence and advanced X-ray synchrotron radiation techniques were involved. These techniques include multi-secondary target Energy dispersive X-ray fluorescence (EDXRF), total reflection X-ray fluorescence (TXRF), Synchrotron Radiation micro X-ray fluorescence (SR-µXRF), and complementary X-ray absorption near-edge structure (XANES) spectroscopy. The annual mass concentrations of the collected ambient air particulates exceed the recommended annual mass concentrations of the European Commission (EC) air quality standards (25 µg/m3) and the World Health Organization (WHO) standards (10 µg/m3). The elemental analysis and elemental mapping were presented. Using the linear combination fitting for the XANES data, the elemental speciation of the most toxic elements (Cr, Mn, Cu, As, Ni, and Pb) was demonstrated. The statistical analysis, including enrichment factors, Pearson’s correlation analysis, principal component analysis, and positive matrix factorization, reveals more information about the source identification of the collected ambient air particulates.

Speaker: Prof. Abdallah Shaltout (National Research centre, Egypt)

15:40 → 15:50 BREAK

15:50 → 16:50 Pollutants and sources: S5

Convener: Julien BAHINO (Université Félix Houphouet-Boigny Abidjan-Cocody)

15:50 Pollutant and Sources

Pollution remains one of the most significant environmental challenges of the modern world, affecting air, water, soil, and overall ecosystem stability. This abstract provides an overview of major pollutants and the human activities that generate them. Air pollutants such as carbon monoxide, sulfur dioxide, nitrogen oxides, and particulate matter primarily originate from transportation, industrial processes, and the burning of fossil fuels. Water pollution arises from agricultural runoff, sewage discharge, industrial effluents, and plastic waste, introducing contaminants like heavy metals, pathogens, and microplastics into aquatic systems. Soil pollution results from excessive use of chemical fertilizers, pesticides, and improper waste disposal, leading to reduced soil quality and potential health risks. Additional forms of pollution—such as noise, light, and radioactive pollution—stem from urbanization, energy production, and technological development. Understanding the sources and types of pollutants is essential for designing effective mitigation strategies. This overview highlights the urgent need for stronger environmental regulations, adoption of cleaner technologies, and increased public awareness to reduce pollutant impacts and protect both human health and natural ecosystems.

Speaker: Atuyambe Lynn

16:05 SOURCES OF AMBIENT FINE PARTICULATE MATTERS IN OSHAKATI, SWAKOPMUND AND WALVIS BAY, NAMIBIA USING POSITIVE MATRIX FACTORIZATION: A LONG-TERM PROJECT FROM 2026

Introduction: Fine particulate matter is a toxic air pollutant with an aerodynamic size of less than 2.5 microns that can endanger human health and climate. The WHO have set and recently revised air quality guidelines upon which countries can use as a yardstick to set their own air quality standards. Namibia does not have air quality standards, leading to unregulated levels and unknown sources of ambient fine particulate matters that people in Namibia are exposed to.
Purpose: To determine the sources of ambient fine particulate in Oshakati, Walvis Bay and Swakopmund, Namibia.
Methods: This study will (i) collect PM2.5 filter samples every sixth day for 1 year sampling period; (ii) Determine the chemical composition in every filter in PM2.5; and (iii) apply the chemical species of ambient fine particulate matters to identify sources contributions in positive Matrix factorization (PMF) model.
Expected results: Descriptive statistics for PM2.5, and its chemical composition will be presented in tables and graphs. Black carbon, organic carbon and trace elements data will be used as markers to identify the sources influencing PM2.5 concentrations.
Conclusion: The study will reveal the sources of ambient fine particulate matters. Similar studies can be replicated in other cities in Namibia.
References
Alfeus, A., Molnar, P., Boman, J., Hopke, P. K., & Wichmann, J. (2024). PM2. 5 in Cape Town, South Africa: Chemical characterization and source apportionment using dispersion-normalised positive matrix factorization. Atmospheric Pollution Research, 15(3), 102025.
Health Effects Institute. (2024). State of Global Air 2024. Special Report. Boston, MA. https://www.stateofglobalair.org/ resources/report/state-global-air-report-2024
Namibia Nature Foundation. 2022. Namibia State of Pollution Report.
World Health Organization. 2022, ‘Air Quality Guidelines - Update 2021’, WHO Regional Office for Europe, Copenhagen, Denmark.
WHO.2021 Review of evidence on health aspects of air pollution: REVIHAAP project: technical report.

Speaker: Anna Alfeus (University of Namibia)

16:20 The INAIL BRiC CELLOPHAN project: Characterization of Emissions in Workplaces of Airborne Microplastics and Nanoplastics

Workers are mainly exposed to micro- and nano-plastics (MNP) by inhalation. Air concentration of MNP in indoor environments can be far higher than outdoors, particularly in workplaces where production, use or disposal of plastic materials is carried out.
However, differently from engineered MNP, secondary MNP released in workplaces remains uncontrolled, since few data exist on MNP indoor air concentrations, and the lack of validated sampling, identification and quantification methods prevents the assessment of workers’ exposure. (Murashov et al., 2021).
In this context, the CELLOPHAN project is investigating three different workplaces, in Italy, where plastic materials are processed, namely a water bottling plant, a tyre fixing and car repair shop, and a textile factory.
A multi-device and multi-technique approach is being employed for field measurements and lab analyses, respectively, of airborne particulate matter in the indoor air of workplaces, at sites with different exposure conditions (close to emission spots; average exposure areas; Offices). All measurements and samples were collected during working hours. This contribution aims at presenting the preliminary results on the chemical composition, particle size distribution and morphology analyses of indoor airborne PM at the three facilities during the 2023-2024 field campaigns.

Speaker: Dr Adriana PIETRODANGELO (National Research Council (Consiglio Nazionale delle Ricerche) - Institute of Atmospheric Pollution Research, Italy)

16:35 Sampling and Identifying Airborne Microplastics: Techniques, Findings, and Challenges

Airborne microplastics (MPs) have emerged as an increasingly recognized component of atmospheric pollution, yet their sampling, characterization, and quantification remain challenging due to their diverse physical forms and low ambient concentrations. This sharing session provides an overview of the approaches and research in microplastics sampling in outdoor and indoor air environments. Emphasis is placed on developing reliable sampling strategies which include active and passive collection methods to ensure representative capture of fibres, fragments, and other types. The session also highlights analytical workflows, including sample pre-treatment, microscopic identification to determine size, shape, colour characteristics. To identify the polymer composition of collected MPs, micro-Raman spectroscopy is employed as a key analytical tool. This technique enables fingerprinting of individual particles, allowing differentiation between common polymers such as polyethylene, polypropylene, polystyrene, and polyester. Findings from recent studies indicate that fibres consistently dominate airborne MP profiles, particularly in indoor environments. Environmental conditions such as increased wind speed have been shown to elevate MP concentrations, while higher relative humidity tends to reduce airborne particle suspension. Micro-Raman analysis further reveals a prevalence of synthetic textiles mainly polyester and rayon suggesting strong contributions from human activities and indoor sources.

Speaker: Nor Ruwaida Binti Jamian (Universiti Teknologi Malaysia)

16:50 → 17:00 Closure day I

Thursday 4 December

09:00 → 10:30 Trends of indoor air pollution: S6

Convener: Dr Bertrand TCHANCHE (Alioune Diop University)

09:00 The effect of chimney fitted improved stove on kitchen fine particulate matter (PM2.5) concentrations in rural Ethiopia

Background
Millions of Ethiopian people cook with biomass fuels using traditional stoves, releasing harmful pollutants and contributing to a significant public health crisis. Improved stoves offer a potential escape route, but their effectiveness needs close scrutiny. This study delves into the impact of chimney-fitted stoves on kitchen PM2.5 concentrations in rural Ethiopian households.
Method
We conducted a randomized controlled trial with 86 households equally divided (1:1 ratio) between intervention and control groups. The 24-h average kitchen PM2.5 concentrations was measured using Particle and Temperature Sensor (PATS+) at baseline and after intervention. All relevant sociodemographic and cooking related characteristics were collected at baseline and dynamic characteristics were updated during air monitoring visits. Three distinct statistical models, including independent sample t-tests, paired sample t-tests and one-way analysis of variance were used to analyze the data using Statistical Package for the Social Sciences (SPSS) software for Windows (v 24.0).
Result
At baseline, the average 24-h kitchen PM2.5 concentrations were 482 μg/m3 (95% CI: 408, 557) for the control and 405 μg/m3 (95% CI: 318, 492) for the intervention groups. Despite remaining elevated at 449 μg/m3 (95% CI: 401, 496) in the control group, PM2.5 concentrations reduced to 104 μg/m3 (95% CI: 90,118) in the intervention group, indicating a statistically significant difference (t = 6.97, p < 0.001). All three statistical analyses delivered remarkably consistent results, estimating a PM2.5 reductions of 74% with the before-and-after approach, 76% when comparing groups, and 74% for difference in difference analysis. Beyond the overall reduction, homes with primary school completed women, larger kitchens, smaller family size, and those specifically baking Injera (the traditional energy-intensive staple food), witnessed even greater drops in PM2.5 levels.
Conclusion
Pregnant women in our study encountered dangerously high PM2.5 exposures in their kitchens. While the intervention achieved a significant PM2.5 reductions, unfortunately remained above the WHO's safe limit, highlighting the need for further interventions.

Speaker: Habtamu Demelash (Debre Tabor University)

Habtamu_ASAQ Seminar Series.pdf

Habtamu_ASAQ Seminar Series.pptx

09:15 Fuel and Ventilation Determinants of Restaurant Air Pollution in a West African Campus: Phase-Resolved PM2.5, HCHO, and TVOCs vs WHO Air-Quality Guidelines

Cooking emissions represent a growing yet understudied contributor to urban air pollution across African cities. This study evaluated indoor and near-outdoor air quality in four restaurants within the Federal Polytechnic Ede, Nigeria, using a Temtop M2000C sensor to measure CO2, PM2.5, PM10, formaldehyde (HCHO), total volatile organic compounds (TVOC), temperature, and humidity under three phases: before, during, and after cooking. Comparative analysis across fuel types (charcoal, firewood, and gas) and spaces (kitchen vs dining) revealed that PM2.5, HCHO, and TVOC concentrations peaked during cooking, exceeding WHO 2021 Air-Quality Guideline limits by factors of 2-6 in charcoal- and firewood-based kitchens. Gas-fueled kitchens showed markedly lower pollutant loads. Ventilation efficacy, expressed as post-cooking decay rate, was up to 65% higher in restaurants with mechanical hoods or cross-flow windows than in naturally ventilated spaces investigated in this study. Phase-resolved pollutant trends highlight the combined influence of fuel choice and ventilation on exposure risk. The findings provide the first quantitative evidence linking commercial cooking practice to air-quality exceedances in a West African setting and emphasize practical mitigation measures, such as hood installation, fuel switching, and improved air-exchange design, to protect worker and customer health.

Speaker: Festus Ben (Centre for Advanced Materials Research and Development, Department of Physics, Federal Polytechnic Ede, Ede, Nigeria.)

Dr Ben Air Pollution Studies.pdf

09:30 Students’ Perception-Based Assessment of Indoor Environmental Quality in a Nigerian University

This study assesses students’ perceptions of indoor environmental quality (IEQ) in classroom settings at Dennis Osadebay University, Asaba, Nigeria, focusing on factors influencing their general comfort and learning conditions. Using structured questionnaires, data were collected from students across multiple faculties within the university to evaluate their satisfaction with thermal comfort, air quality, lighting, and noise levels. The questionnaire included rating scales and open-ended questions to capture both quantitative and qualitative insights. Results indicate varying levels of comfort, with notable concerns related to thermal conditions and indoor air quality during certain periods. The findings highlight the importance of integrating occupant feedback through questionnaires to identify comfort challenges and inform improvements in classroom environmental management. This study underscores the value of student-centered evaluations in creating healthier and more conducive learning environments at Dennis Osadebay University and similar Nigerian higher education institutions.

Speaker: Gabriel Friday Ibeh (Dennis Osadebay University Asaba Delta Nigeria)

09:45 BREAK

09:55 Preliminary Assessment of Indoor Particulate Matter and Microclimate Conditions in Scientific Research Laboratories

Laboratory activities can increase particulate matter (PM) levels and alter temperature and relative humidity (RH), affecting PM dispersion. Continuous exposure to poor air quality and adverse microclimates can negatively impact human health, highlighting the need to monitor
these in labs in scientific institutions. To determine indoor air quality and its association with microclimate conditions in laboratory areas of a scientific research institution. Concentrations of PM, temperature and RH were measured using Atmotube samplers during working hours. Descriptive statistics summarized PM and climate variables; t-tests and multiple linear regression assessed PM and Air Quality Score (AQS) variations with temperature and humidity
Generally the mean(SD) concentrations of PM1, PM2.5, PM10, temperature and RH in the environmental sample lab (16(7.0) μg/m3, 18.4(7.6) μg/m3, 19.9(8.0) μg/m3, 24.7(1.2) °C and 56.0(12.8)), where higher than those in the biological sample lab (9.1(2.3) μg/m3, 10.9(2.4) μg/m3, 11.9(2.5) μg/m3, 28.8(2.9) °C and 44.5(9.0)) with statistically significant differences (p= 0.000). AQS ranged from 3 to 92. Regression analysis showed the RH was a significant predictor of PM levels, while both RH and temperature exhibited statistically significant on the AQS (p=0.000). Temperature and RH significantly influence overall air quality in laboratories, underscoring the need for targeted monitoring and control strategies to reduce exposure risks and enhance occupational health within scientific research institutions.

Speaker: Dr Lawrencia Osae-Nyarko (CSIR Water Research Institute (Biomedical and Public Health Research Division))

Indoor Air Quality and microclimate in research labs_LON.pdf

10:10 Smart Classrooms for Healthy Learning: IoT-Driven Indoor Air Quality Monitoring and Fault Detection

The contribution presents the implementation of an IoT-based monitoring system on the CLE campus of the University of Turin. The system integrates environmental sensors within classrooms to track indoor air quality in real time. Sensor data is centralized through a digital asset management platform, enabling continuous oversight of building performance and related users’ comfort. Detected anomalies or faults in Indoor Environmental Quality (IEQ) parameters will be used to trigger alerts to support timely interventions and promote healthier learning environments.

Speaker: Lavinia Chiara Tagliabue (Università degli Studi di Torino)

10:30 → 10:40 BREAK

10:40 → 11:40 AI and air quality data analytics: S7

Convener: Rafael Borge (Universidad Politécnica de Madrid (UPM))

10:40 Cost-effective, High impact : the AI_r system for Air Quality Monitoring

Effective air quality monitoring is essential because it alerts communities when pollution levels are high, allowing people to take necessary precautions. Traditionally, reliable monitoring requires reference-grade stations, but these are expensive and limited—especially in low-resource settings. The South African Consortium for Air Quality Monitoring (SACAQM) developed the AI_R system, which integrates IoT technologies, cost-effective sensors, and artificial intelligence to provide real-time air quality data. The system is equipped with advanced technologies such as LTE and GPS connectivity and has been deployed across multiple indoor and outdoor locations in Gauteng Province, South Africa. Deployment takes place in government buildings, including clinics, hospitals, and community centres, and also extends to a growing citizen-science network where we collaborate directly with local communities. These cost-effective sensors generate rich spatial and temporal datasets and offer valuable insights, including the identification of highly polluted areas. They also show strong potential as practical alternatives to reference-grade monitoring stations. We applied forecasting models to data collected from the AI_R system to predict the next 24 hours of PM₂.₅ concentrations. The combination of the AI_R system with predictive modelling provides an efficient early-warning tool for anticipating air quality conditions and supporting timely public health interventions.

Speaker: Manal Karmoude (University of the Witwatersrand (ZA))

ASAQ_seminar_manal.pdf

ASAQ_seminar_manal.pptx

10:55 Applicability of the explainable machine learning techniques in surface Ozone simulation and formation sensitivity analysis

Gaining insight into the response of surface ozone (O3) formation to its precursors, primarily nitrogen oxides (NOx) and volatile organic compounds (VOC), is still challenging due to the complex formation mechanisms involved.
The subject of this study concerns a methodology for analysing O3 sensitivity to NOx and VOC precursors. The approach is based on the Machine Learning (ML) techniques to identify the complex, non-linear relationships between input features and model output, combined with the Shapley additive explanation (SHAP) method to explore the impact of each feature on O3 concentrations.
To this end, a ML-XGBoost model has been developed to predict O3 concentrations based on hourly data of pollutants and meteorological parameters acquired during several years in an urban area. The SHAP approach has been applied to evaluate the main drivers explaining the changes in O3 predicted concentrations. Finally, the ML model has been applied to derive O3 formation sensitivity curves from measured data of VOC and NOx.
A range of findings have been identified in various seasonal contexts, demonstrating the efficacy of a ML model based on observational data in investigating the drivers of O3 formation. This knowledge is crucial for the effective management of O₃ pollution.

Speaker: Roberta Valentina gagliardi (istituto superiore di sanità)

GagliardiAndenna_ASAQ2025.pdf

GagliardiAndenna_ASAQ2025.pptx

11:10 A Scalable Framework for Sensor Data: Intra-Domain Transfer Learning in Wi-Fi Networks and Air Quality Monitoring

Large building and campus WiFi networks generate a huge amount of data from user activity and device counts. Working with data at this scale creates major challenges, as it becomes computationally expensive and slow to train models. To solve this, we propose using intra-domain transfer learning. Our method involves first training a model on one large, resource-rich WiFi dataset. We then adapt this pre-trained model to work with other, similar datasets, instead of building a new model from scratch each time.
This approach is highly efficient. Our results show that the transferred models perform nearly as accurately as custom-trained ones, but require significantly less time and CPU usage to get up and running. We frame this as a time-series forecasting problem for user counts. Finally, we explore how this method can bridge domains. By successfully transferring models between WiFi data and other sensor systems, like air quality monitors, we demonstrate a path toward creating resource-efficient and rapid-deployment solutions for a wide range of smart building applications.

Speakers: Mr Raghav Chandna (University of the Witwatersrand and iThemba Labs), Prof. Bruce Mellado Garcia (University of the Witwatersrand and iThemba Labs)

asaq_slides (2).pdf

11:25 "LIVESTAQSENS": AI-Calibrated Network of CH₄ and NH₃ Sensors for Monitoring Air Quality in Livestock Farming

Intensive livestock farming, with high animal density, is widely used to meet the growing demand for meat but negatively impacts air, water, soil, climate, and biodiversity. Ammonia (NH₃) and methane (CH₄) are the main air pollutants, and farmers are adopting strategies to reduce their emissions. This requires continuous, widespread monitoring using reliable, low-cost devices. However, conventional systems are often expensive and require specialized maintenance, discouraging regular use.
This work, along with the LivestAQsens project (Emilia-Romagna PR-FESR 2021-2027 project – Website: www.livestaqsens.it), aims to create a monitoring network using MOX chemical sensors for CH₄ and NH₃, supported by self-calibrating algorithms. MOX sensors are fabricated using screen-printing technology and chemical wet synthesis, ensuring compact size, low cost, and ease of use. The network’s core consists of an array of five thick-film gas sensors, optimized for livestock environments, housed in a small unit with dedicated electronics and a main control unit for data transfer via Wi-Fi. Data, including temperature and humidity, are sent to a remote server in real-time. Calibration algorithms based on machine learning ensure accurate, reliable monitoring, adjusting sensor calibration dynamically based on environmental conditions. This solution supports effective strategies to reduce the environmental and climate impacts of livestock farming.

Speaker: Ambra Fioravanti

11:40 → 11:50 BREAK

11:50 → 12:30 Instrumentation and advances in air quality monitoring: S8

Convener: Abdallah Shaltout (National Research centre, Egypt)

11:50 Field evaluation of a Low-Cost PM₁₀ Monitoring Instrument under Humid Savanna conditions at the Lamto geophysical station, Côte d’Ivoire

This study evaluates the performance of the low-cost AirQino sensor for measuring PM₁₀ concentrations in a humid savanna environment at the Lamto Geophysical Station, Côte d’Ivoire. A 40-day co-location campaign was conducted with a reference TEOM analyzer. Raw results indicate a moderate but significant correlation between AirQino and TEOM measurements (r = 0.51; R² = 0.26), with a systematic underestimation of PM₁₀ concentrations (NMB = −34.3%). The root mean square error (RMSE = 12.15 µg m⁻³) and mean absolute error (MAE = 8.51 µg m⁻³) reflect substantial variability, likely linked to high relative humidity. To correct these biases, several multivariate calibration models were tested. The most effective configurations, integrating meteorological variables (temperature, relative humidity) and gaseous co-pollutants (CO, NO₂, O₃), significantly improved performance (r = 0.77; R² = 0.60; RMSE = 7.57 µg m⁻³; CVMAE ≈ 28%; bias ≈ 0%). These results emphasize the critical influence of environmental conditions on sensor accuracy. Although AirQino cannot fully replace reference-grade instruments without prior calibration, it offers a reliable and cost-effective alternative for spatiotemporal PM₁₀ monitoring in data-scarce regions when locally adjusted with appropriate correction models.

Speaker: Julien BAHINO (Université Félix Houphouet-Boigny Abidjan-Cocody)

ASAQ_PM10_ air Qino 2.pdf

ASAQ_PM10_ air Qino 2.pptx

12:05 Density functional theory-based exploration of structural, electronic, mechanical, thermodynamic, and optical properties of α-NiS for CO2 adsorption

In this study, we performed comprehensive first-principles calculations based on density functional theory to investigate the structural, electronic, mechanical, thermodynamic, and optical properties of α-nickel sulfide (α-NiS), with a particular emphasis on its potential for CO2 adsorption. Structural optimization confirms the stability of the α-NiS phase, yielding lattice parameters, a = b = 3.425 Å, c = 5.286 Å, in good agreement with experimental data. Electronic band structure analysis reveals a semiconducting nature with a bandgap of 1.98 eV. Mechanical and thermodynamic analyses confirm the elastic and thermal stability of α-NiS, supporting its suitability for surface reactions. Optical property calculations indicate that α-NiS exhibits strong absorption across a broad spectral range, highlighting its potential in photonic and catalytic systems. To evaluate its gas adsorption capabilities, CO2 adsorption on both Ni- and S-terminated surfaces was investigated. The results show that CO2 binds more strongly to the Ni-terminated surface through ionic interactions, forming Ni–O bonds with a bond length of 2.36 Å and a bond angle of 95.5°, while interaction with the S-terminated surface is weaker and predominantly covalent. The calculated adsorption energies of -2.71 eV (Ni-side) and -0.98 eV (S-side) further confirm the thermodynamic favorability of CO2 adsorption on the Ni-terminated surface, suggesting α-NiS as a promising candidate for gas capture applications.

Speaker: Fikadu Geldasa (Walter Sisulu University)

13:30 → 14:30 Instrumentation and advances in air quality monitoring: S9

Convener: Abdallah Shaltout (National Research centre, Egypt)

13:30 Improvement of low-cost sensor accuracy in challenging environmental conditions to obtain near-reference data

It is well-known the limitations that low-cost sensors have related to the environmental conditions effect, cross-sensitivities, and drifts over time. Currently, manufacturers apply different techniques to mitigate these limitations, most of them based on Machine Learning and AI models. However, these models have several disadvantages, such as they require a large amount of reference data to train and test the model, being valid in that specific case, and they need additional training to update the model to the new environmental conditions.
Currently, LCS have shown data accuracy close to reference instruments, however, it is not uncommon that manufacturers show field evaluation during wintertime or when the temperature is low. However, it is more difficult to find accurate data results at high temperatures (>25ºC), typically found in summertime or tropical areas, in which poorer performance of the sensor is expected.
Being aware of this and discarding the use of any Machine Learning due to its limitations, Kunak has been working on a new correction to get the most precise and accurate data in these environmental conditions. Kunak has solved all the challenges encountered in LCS, increasing the accuracy of the data, and reducing the error with respect to the reference instruments, without using any external data, or any other postprocessing model based on Machine Learning or AI. Thus, it is possible to monitor data accuracy near-reference, which allows the use of the LCS to complement the measurements of regulatory instruments, at higher spatial and temporal resolution.

Speaker: Dr Edurne Ibarrola (Kunak Technologies)

ASAQ PPT_Edurne Ibarrola.pdf

ASAQ PPT_Edurne Ibarrola.pptx

13:45 Application of the Decoupled Direct Method (DDM) to support an advanced air pollution assessment system in Madrid (Spain)

Source apportionment methods are key to understand the complex, non-linear contribution processes of different emitting sectors to ambient air quality and the potential benefits on air quality that emission abatement measures may entail. This contribution illustrates the application of the Decoupled Direct Method (DDM) as the basis of a platform to inform and support the decision-making process at city scale. The SIMAD (advanced air pollution and climate change analysis and assessment system for the city of Madrid) system relies on CMAQ-DDM-3D (version 5.4) with 1 km2 resolution. We computed hour-specific sensitivities to the emissions of the main policy-relevant subsectors in the city (road traffic, residential, commercial and institutional sectors and solvents use). Sensitivities of the target pollutants consider the main relevant precursors in each case (NOX for NO2, NOX and VOC for O3 and NOX, VOC, SO2, NH3 and primary PM for PM2.5). A reduced form model was built using DDM sensitivity coefficients in a Taylor series expansion so SIMAD can be used to both, keep track of air quality changes as emissions are updated and as a screening tool to design measures to meet the goals of the new EU Air Quality Directive and to assess population exposure.

Speaker: Rafael Borge (Universidad Politécnica de Madrid (UPM))

ASAQ_R.Borge_04dec25.pdf

14:00 Design and optimization of high-performance H₂ sensors for leak detection in production, storage and utilization environments

Hydrogen (H₂) is a promising clean fuel, but its flammability in the 4–75% range necessitates rapid leak detection. Chemiresistive gas sensors offer an efficient solution due to their low cost, small size, and tunable properties. This study focuses on optimizing functional materials for H₂ sensing. (Ti,Sn)O₂ solid solutions were chosen for their superior sensing performance over pure oxides, and Pd was added to enhance catalytic activity and mitigate humidity effects. SnO₂, TiO₂, and (Ti,Sn)O₂ with a Ti:Sn ratio of 25:75 (TS25) were synthesized using standard procedures, with Pd-loaded samples (TSP) prepared by adding 1.5 at% Pd. FE-SEM and XRD analyses revealed nanoparticle morphologies (~10 nm) and single-phase structures: cassiterite SnO₂, anatase TiO₂, and rutile solid solutions. Screen-printed sensing layers were fired at 600 °C and electrically tested, confirming n-type behavior. At their optimal temperatures, the response to 100 ppm H₂ followed this order: TSP (400 °C), TS25 (450 °C), SnO₂ (450 °C), and TiO₂ (550 °C). Both TSP and TS25 detected H₂ from 0–1000 ppm, even at 60% humidity. Selectivity tests revealed CO as the main interferent, though H₂ still induced the strongest response.
Research supported by the Emilia-Romagna PR-FESR 2021-2027 Project “SENSIDROGEN” (www.sensidrogen.it).

Speaker: Ambra Fioravanti

14:30 → 15:30 Training and capacity building: S10

Convener: Anna Alfeus (University of Namibia)

14:30 ACTRIS European Research Infrastructure Consortium: delivering harmonised, high-quality atmospheric data and services

European Research Infrastructures provide coordinated efforts for scientific data to address global challenges, such as air pollution and climate change, by facilitating extensive collaboration across wide geographical areas.
Aerosol, Clouds, and Trace Gases Research Infrastructure (ACTRIS) is at the forefront of these efforts, offering data, tools and services on short-lived atmospheric components: aerosol particles, clouds and reactive trace gases.
The most important ACTRIS service is the high-quality data, which is openly available to users from all over the world. The data are harmonised through the standard operating procedures and processing protocols as well as quality controlled via regular calibration of the instruments. Besides data, various virtual tools for processing the data online are also available at the portal.
Another essential ACTRIS service is to provide access to the state-of-the-art measurement facilities, both fixed stations and mobile platforms, that can be deployed e.g., in targeted air quality campaigns. ACTRIS also provides training and education related to instruments and processing of atmospheric data.

ACTRIS is taking an active role in discussions and implementations of a new Air Quality Directive that was recently taken into effort in the EU. We provide service tools to improve and harmonize air quality measurements (https://riurbans.eu/project/#service-tools).

Speakers: Anna Franck (ACTRIS ERIC), Prof. Tuukka Petäjä (Institute for Atmospheric and Earth System Research, Finland)

ACTRIS_AQ2025_pdf.pdf

14:45 Breathing Green: Empowering Northern Ghanaian Youth for Cleaner Air

Air pollution is a big problem in Tamale, especially during the Harmattan season when dust, smoke, and open burning make the air very bad. Many young people suffer from this, but few are involved in finding solutions. The Breathing Green project helps to change that by training and supporting students to become clean air ambassadors in their schools and communities.

The project teaches young people about air pollution, climate change, and how they can help through education, art, and media. It also gives them a voice to talk about clean air on local radio and in their neighborhoods. Through school clubs, clean air walks, and small community actions, students help others to understand why clean air is important for health and for the future.

By training 50 students to reach over 500 people in Tamale, Breathing Green is building awareness and inspiring change. This project shows that when the youth breathe good air, the future also breathes better.

Speaker: Amina Amponsah Fordjour

15:00 Plastic waste management and recycling

Plastic waste is one of the biggest problems in my community. Every day, people use plastic bags, bottles, and straws and throw them away after one use. These plastics block gutters, destroy the soil, and make our environment dirty. My project focuses on helping people understand the need to manage and recycle plastic waste instead of burning or dumping it.

The main idea is to use education and recycling to create change. I will organize community education programs, school talks, and radio discussions to teach people how to separate and reuse plastic waste. I will also work with local plastic collectors and small recycling industries to show how plastic can be turned into new useful products. This will reduce pollution, create jobs, and make the environment cleaner.

With support and funding, I hope to provide waste bins at key places, train more youth to take part in plastic recycling, and raise awareness about how recycling helps to reduce greenhouse gases and protect the climate. This project will help my community live cleaner, healthier, and more sustainable lives, one plastic at a time.

Speaker: Amina Amponsah Fordjour

15:30 → 16:00 PANEL DISCUSSION

Topics: 1) Recent developments (sources, ongoing projects, sensors deployments, data generation...), 2)Collaboration N-S and S-S

16:00 → 16:30 Closing session