Ghana Program Presentations

Our Technical Program Committee has curated the below sessions based on topics important to researchers, manufacturers, regulators and users of air quality monitors. This list of topics was formulated as the Ghana Conference Concept Note was finalized in order to fulfill the stated goals. We have a myriad of speakers that will share their expertise on the topics with all conference attendees. Review the presentation topics and click each presentation to learn more about what the speaker will be sharing. You can also view the current schedule here.

After reviewing the list, consider submitting becoming an exhibitor or sponsor of the conference. There is no cost to attend the event, but we do hope our industry partners will help fund the event through sponsorships.

Keynotes:

Why should we care what the data says?

When addressing air pollution, we also address a critical and easy-to-implement solution to climate change. Short-lived climate pollutants are negative in all senses, and we have proven technologies and policies to economically and immediately reduce air pollution,” says UN Environment climate change specialist Niklas Hagelberg. By reducing air pollution, we preserve and protect our climate. This keynote will focus on the connections between air quality, health and economics.

Moderator:

Ms. Sietske van der Ploeg, Clean Air Fund

Speakers:

Prof. Kofi Amegah, University of Cape Coast, (in-person) E: aamegah@ucc.edu.gh
Dr. Gabriel Okello, African Centre for Clean Air (virtual) E: gabrielokello@gmail.com

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Shaping the future of data accessibility and transparency for action

Access to trusted, scientifically-valid data can play a transformational role in the discourse on air pollution. In different contexts, the purpose or application for air quality data can vary significantly. For some, such data is useful for personal decision-making, i.e., can I send my kid out to play, or can I go for a run on this street?For others, especially in the policy context, the data can be meaningfully used for informing regulatory decisions. Transparency can also foster trust, and help strengthen accountability for action, especially as new policies and programs aimed at improving air quality are launched.

This keynote panel will discuss principles of data access and transparency, and provide a perspective on current status and best practices, as well as opportunities to expand global infrastructure to support greater data production, access, and usage and practical examples from Africa and beyond. Experts will discuss important technical and social considerations, current barriers and possible solutions. The panel will close with an interactive discussion to gather audience insights and examples on opportunities to use trusted data to accelerate evidence-informed action.

Moderator:

Pallavi Pant, Health Effects Institute E: ppant@healtheffects.org

Speakers:

Engineer Bainomugisha, AirQo E: baino@airqo.net
Iq Mead, Imperial College London, Breathe London E: m.mead@imperial.ac.uk
Christa Hasenkopf, Energy Policy Institute at the University of Chicago E: chasenkopf@uchicago.edu

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Session Topics:

Community Based Participation in Using LCS

This session will discuss using low-cost sensors in community build projects. We will review what considerations should be made when designing a project.

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Podium Presentations:

Participatory Air Quality Monitoring in African Cities: Empowering Communities, Enhancing Accountability, and Ensuring Sustainable Environments - Mr. Fidel Wabinyai (Uganda)
Presented by: Mr. Fidel Wabinyai, Data Scientist, AirQo (Uganda) E: raja@airqo.net

Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step towards achieving these important goals in African cities and beyond.
Assessment of Personal Exposure to Particulate Matter Among Furniture Manufacturers - Mr. Abdou Safari Kagabo (Rwanda)
Presented by: Mr. Abdou Safari Kagabo, Assistant Lecturer and PhD Student E: safarikaa@gmail.com

Rwanda, like the rest of the world, has placed significant attention on environmental degradation, air pollution, and climate change. This study aimed to investigate the personal exposure to particulate matter (PM) among workers in the furniture manufacturing industry in Kigali, Rwanda, based on the PM concentrations and time spent in the daily most visited environments. Data on PM exposures at work, at home, and in other microenvironments were collected using low-cost sensors (PM Pocket sensors) that were portable and wearable near the human breathing zone. Dynamic exposures to PM for five participants in five different working places were assessed. The study findings provided insights into the level of exposure to PM among furniture manufacturing workers in Kigali. PM10 mean concentrations were 66.20 µg/m3,84.24 µg/m3, 98.56 µg/m3, 93.95 µg/m3 and 64.44 µg/m3 for Participant A, Participant B, Participant C, Participant D and Participant E respectively. On the other hand, PM2.5 mean concentrations were 43.17 µg/m3 for Participant A, 60.60 µg/m3 for Participant B, 43.78 µg/m3 for Participant C, 45.76 µg/m3 for Participant D and 40.58 µg/m3 for Participant E. The results show that all concentrations exceed WHO air quality guidelines set to protect human health. In the working hours, Indoor activities including emissions from machines and generators used in carpentry were shown to be the main causes of the increase in air pollution levels in these areas. In the home environments, PM levels were influenced by outdoor emission sources mostly from nearby roads, while the PM levels during travel from or to work are highly influenced by vehicle emissions and some near-road activities like restaurant kitchens. The work microenvironment has been found to highly contribute to the daily total exposure, followed by the home microenvironment, while other microenvironments contribute less for all participants. The time spent in each microenvironment was also a significant influencing factor in the measured exposure levels for all participants. The results of this study will be useful for policymakers, employers, and workers in this industry in developing strategies to minimize exposure and promote a safe working environment.
Breathe Accra Project: A Community-Based Air Quality-Monitoring Network for the Greater Accra Metropolitan Area - Mr. Kelvin Yeboah (Ghana)
Presented by: Mr. Kelvin Yeboah, Community Engagement Officer, Breathe Accra E: yeboahkelvin8@gmail.com

The Breathe Accra Project is a community-driven initiative with a vision to accelerate air quality improvements in Accra to protect public health and help inspire greater action on air pollution in other African cities. The main objective of the project is to ensure openly accessible hyperlocal air quality data in the Greater Accra Metropolitan Area. In this presentation, I will be highlighting the objectives and activities of the Project, the roles of stakeholders under the project, and the framework and approach of our extensive community engagement efforts. The presentation will also touch on our policy engagement initiatives as well as the challenges we are facing and the solutions developed.

Poster Presentations

Utilizing Communication Strategies to Increase Public Engagement on Air Pollution - Mr. Church Essien (Nigeria)
Presented by: Mr. Church Essien, University of Uyo E: churchmessien@gmail.com

Air pollution is defined as a deviation or alteration from the normal condition of the environment (atmosphere) caused by the contamination of the indoor or outdoor environment by chemical, physical, or biological agents. This has a negative impact on the public health and well-being of individuals and communities all over the world. This could be caused by domestic combustion devices, motor vehicles, industrial activity, or forest fires. As a result, there are numerous tactics that can be used to raise awareness of this issue and inspire action to address it.
In Africa, air pollution is a significant environmental health hazard. In order to motivate action at both the individual and societal levels, it is critical to raise public knowledge and involvement as data and evidence become more widely available. In order to accomplish this goal, effective communication techniques are crucial. Diverse communication techniques can encourage individuals to engage and take action by increasing awareness of the negative effects of air pollution on health. Social media campaigns, neighborhood outreach projects, and public education programs are a few examples of these tactics. The information frequently also needs to be understandable and accessible, with simple language and illustrations. To ensure that the tactics are successful, it is crucial that they be customized for particular audiences.
Whilst there are many different types of pollutive problems occurring in Nigeria, with ones such as water pollution, noise pollution and soil pollution or damage taking place, there is also a prominent amount of air pollution taking place, which has been on record for causing a growing number of health issues and deaths over the years. In regards to numbers on record, Nigeria came in with a PM2.5 reading of 21.40 μg/m³ in 2019, placing it in 39th spot out of all countries ranked worldwide, coming in just behind other countries such as South Africa and Saudi Arabia.
A location's air quality index (AQI) is an indication of daily air quality and shows how clean or filthy the ambient air is, with accompanying public health concerns after breathing unhealthy air. In recent years, urban air quality in developing countries such as Nigeria has deteriorated, posing a significant environmental risk to human health. Following the exploration of oil and gas, as well as other natural resources, the Niger Delta region of Nigeria is exposed to the prevalence of hazardous air. As a result, the variety and number of pollutant emission sources have increased significantly. And, as a result of a lack of air quality control capabilities, the region's air quality is deteriorating.
The presence of toxins or pollutant substances in the air that interfere with human health or welfare, or cause other detrimental environmental impacts, is classified as air pollution. Notably, as in other similar places, air pollution in the Niger Delta region of is caused by a variety of sources, including petroleum refining and gas flaring, vehicle and traffic emissions, heavy duty and industrial machine incomplete combustion, open garbage burning, biomass, and so on. These air pollutants endanger the residents of the Niger Delta region's ecology and health.
Allin-Wayra: Small sensors for atmospheric science - Dr. Sebastian Diez (Argentina)
Presented by: Dr. Sebastian Diez, Researcher, Universidad del Desarrollo E: sebastian.diez@york.ac.uk

Derived from the Quechua term for "good air" or "winds of change," Allin-Wayra is IGAC's new initiative on small sensor technology within atmospheric science. With a vision for transparent, accessible, and equitable use of sensor technology, Allin-Wayra emphasizes environmental justice and a better understanding of our atmosphere. Recognizing the expanding community of atmospheric researchers using such tools, this initiative aims to build a global, inclusive sensor community, especially in areas with limited air quality monitoring. Key efforts include raising awareness about the importance of sensors, particularly in the Global South, hosting workshops, creating or adapting open-access resource platforms, and planning to publish a community-driven article that captures the collective insights and experiences gained, focusing on regions lacking comprehensive measurements.

Data Collection, Analysis and Interpretation

This session is focused on the methods for analyzing and utilizing low-cost sensor data. How can sensor data be corrected and calibrated to provide meaningful, actionable information? What kind of low-cost / reference colocations, data integrity checks and quality assurance can be created to support low-cost sensor data correction? What kind of statistical methods are appropriate for low-cost sensor data? How can low-cost sensor data be integrated with other data sources (such as health, traffic, or demographic information)? We welcome submissions that address the intricacies of sensor data and how to best use it.

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Podium Presentations:

Algorithm for estimating particulate matter concentrations using Landsat 8 multi-spectral satellite images: An urban air quality mapping over Accra, Ghana - Mr. Cosmos Wemegah (Ghana)
Presented by: Mr. Cosmos Wemegah, Assistant Research Fellow, University of Energy and Natural Resources, Earth Observation Research and Innovation Centre E: cosmossenyo@gmail.com

Air pollution is one of the major environmental challenges of urbanization in Ghanaian cities with the looming effects of poor air quality. This undermines the progress in achieving sustainable development goals 3, 11, and 13 which seek to promote good well-being of the public, making cities and communities sustainably safe and resilient and taking actions against climate change respectively. To countermine this, comprehensive monitoring and mapping of pollutant concentrations are very crucial both at the local and regional scale. However, the lack of adequate ground-based stations hinders the monitoring of air pollutants and cannot be used for assessing pollution spatially and mapping. Therefore, by integrating purple air low-cost sensors, this study seeks to develop an empirical algorithm to estimate particulate matter < 2.5 micrometers (PM2.5) from multi-spectral visible bands of Landsat 8 satellite data over Accra, Ghana. The correlation coefficient (R), root mean squared error (RMSE), and standard deviation were used in assessing the feasibility of the proposed algorithm. The findings revealed that the estimated PM2.5 using the proposed algorithm agreed very well with the ground-based measurements with R and RMSE of 0.977 and 5.106 μgm-3 respectively. The performance score of the algorithm permits the spatial assessment of pollution levels and mapping of urban pollution islands in Ghana.
Demonstrating the power of well-calibrated low cost sensors on the African continent: examples from East, West, and Central Africa - Dr. Daniel Westervelt (United States)
Presented by: Dr. Daniel Westervelt, Associate Research Professor, Columbia University, Lamont-Doherty Earth Observatory E: danielmw@ldeo.columbia.edu

This talk will highlight some recent efforts to close the air pollution data gap in Africa using surface-based observations from traditional reference monitors and consumer-grade low-cost sensors. In particular we demonstrate the effectiveness of well-calibrated low cost particulate matter sensors in several previously-unmonitored megacities including Kinshasa (DRC), Lomé (Togo), Accra (Ghana), Nairobi (Kenya), and more. We find that many consumer-grade Plantower-based low-cost PM2.5 monitoring devices, such as PurpleAir, Clarity, and QuantAQ, perform well (r-squared ~ 0.6, MAE ~ 7 µg m-3) compared to locally available reference monitors, but can be improved dramatically (r-squared ~ 0.8, MAE ~ 2) using a variety of statistical methods, including linear regression, random forest regression, and Gaussian mixture regression. These well-calibrated sensors form the basis of dense urban networks of PM2.5 monitors in several African megacities, for example in Kinshasa (DRC), where the annual mean PM2.5 in 2019 was approximately 45 µg m-3, or ~8 times the WHO annual guideline. We also demonstrate some potential use cases of sensor networks such as source apportionment of PM2.5 in Africa, which is sorely needed in order to take action to mitigate pollution. Finally, this talk will present future plans for field intensives for air quality monitoring in Africa that goes beyond cheap sensors and will discuss what the current needs are to ramp up the type of high quality measurements that are commonplace in wealthy countries.
Monitoring the Diurnal and Seasonal Variation of Ambient Particulate Matter (PM2.5) using Low-Cost Sensors in Juja, Kenya - Ms. Josephine Ndiang'ui (Kenya)
Presented by: Ms. Josephine Ndiang'ui, Master's Student, Jomo Kenyatta University of Agriculture and Technology E: jkanyeria@gmail.com

Air pollution is a major environmental concern that affects human health worldwide. Despite recent studies indicating ambient air pollution is a growing global concern strongly linked to rapid global urbanization, little has been done to monitor the air quality levels in Africa. Traditionally, air quality monitoring has relied on environmental monitoring stations, that are expensive to build and maintain. Thus, low-cost sensors offer a practical and cost-effective means of monitoring air quality. A study was conducted in Juja town, situated on the outskirts of Nairobi, along the busy Thika Superhighway. The objective of the study was to examine the daily and seasonal variation of ambient PM2.5 levels in Juja, Kenya. The data was collected from November 2019 to April 2021 from four different sites. The PM level was measured using the Purple Air Monitoring Sensor – PA-II-SD in μg/m3 on a 24hour cycle. The PM2.5 level from the low-cost Purple Air Sensors were later calibrated against a reference BAM-1022 to yield corrected PM values. The results revealed PM2.5 concentration was higher during the dry season (June - August 2020) compared to March - May 2020 (wet season) where it dropped by 5-10μg/m3 on average. The average daily PM2.5 levels were recorded at 44μg/m3 (Pine Breeze), 20μg/m3 (Toll) and 16μg/m3 (Kibariti) all exceeding the WHO guideline of 15μg/m3. JKUAT had an annual mean concentration of 16μg/m3, exceeding the WHO guidelines of 5μg/m3. The study revealed a significant link between PM2.5 levels and vehicle emissions. The concentrations of PM2.5 peaked at 5am and 5pm, likely due to the increased traffic during morning and evening hours. In addition, comparing the month of April 2021 to the previous year, the daily mean dropped by 5-10μg/m3 – the period of the new Covid -19 lockdown. Overall, low-cost sensors have provided an increased availability of data that can be used to identify patterns and trends in air quality over time.
Low-Cost Filter Collection for analysis of Chemical composition of atmospheric aerosols in Africa - Dr. Solomon Bililign (United States)
Presented by: Dr. Solomon Bililign, Professor, North Carolina A&T State University E: bililign@ncat.edu

Measuring concentrations PM2.5 and other size aerosols using low-cost sensors provides information on the level of exposure the public experiences. However

The chemical composition of aerosols is of particular importance to assess their interactions with radiation, clouds, and trace gases in the atmosphere and consequently their effects on air quality and health.

We collected ambient filter samples from small cities and large cities in Botswana and Ethiopia using 47 mm quartz fiber and Teflon membrane filters. Samples were collected for 12 or 24 hours at a flow rate of 15 L/min using a Teflon filter holder and portable sampling pump. In Palapye, Botswana, PM2.5 and black carbon measurements were carried out simultaneously.

The chemical analysis of collected aerosol from Botswana was done using a multi-stage analytical platform that combines reversed-phase liquid chromatography, diode array detection, and high-resolution quadrupole time-of-flight mass spectrometry with electrospray ionization. Based on this analysis, we were able to identify individual light-absorbing organic compounds and group them into distinct chemical classes, such as lignin pyrolysis products, nitroaromatic compounds, coumarins, stilbenes, and flavonoids. Comparison with lab generated biomass burning aerosols derived from biomass fuels from Botswana were made.

This approach offers opportunities to create collaborations between African institutions and US institutions in the collection and chemical analysis of filter samples from African Megacities while building local capacity.

Poster Presentations

Air Pollution in Urban Ouagadougou - Dr. Issoufou Ouarma (Burkina Faso)
Presented by: Dr. Issoufou Ouarma, Assistant Professor, Universite Nazi Boni & Centre Universitaire de Banfora E: ouarma.issoufou@hotmail.fr

Nowadays, ambient air pollution is a serious public health issue. Thus, Western African cities are not excluded from this phenomenon. These cities are characterized by rapid and uncontrolled growth with limited means to support this growth, thus contributing significantly to sanitary risks. Indeed, this demographic growth generates a strong need for transportation, which leads to an increase in road traffic emissions and air pollution due to the great rate of poorly maintained engines, unpaved roads, important number of imported second-hand vehicles that do not respect emission standards and poor fuel quality. This study assesses particulate and carbon monoxide air pollution levels in the streets of a West African city (Ouagadougou, Burkina Faso). A total of 16 classified measurement sites were selected in the city of Ouagadougou with a uniform spatial distribution. Of these sites, four were traffic proximity sites. For all traffic sites, the average measured concentration of carbon monoxide for an hour was 579 ± 153 μg/m3 and the average concentration for eight hours was 439 ± 87 μg/m3. For the other sites, the average value was 434 ± 191 μg/m3 and 394 ± 113 μg/m3 respectively for an hour concentrations and for eight hours’ average concentrations. For PM’s except two sites the average PM2.5 concentrations measured ranged from 18 to 32 μg/m3 and PM10 ranged from 147 to 268 μg/m3.
Spatial and temporal monitoring of PM2.5 using low-cost sensors in Burkina Faso - Dr. Bernard Nana (Burkina Faso)
Presented by: Dr. Bernard Nana, Teacher and researcher, Ecole Normale Supérieure E: nsbernard@yahoo.fr

Air pollution now causes almost seven (7) million premature deaths worldwide. Most of these deaths occur in low-income countries, particularly in Africa. However, the means of observing this air pollution in these countries are lacking. Knowledge of pollutant concentration levels and their distribution in time and space is inadequate or non-existent in most African countries. This study focuses on the temporal and spatial distribution of PM2.5 in Burkina Faso. The measurement campaign used low-cost sensor from the Clarity society. The sensors were placed at 19 sites throughout the country, including thirteen (13) in Ouagadougou, the capital, three (3) in Bobo-Dioulasso and three (3) in Koudougou, the second and third largest cities in Burkina Faso respectively. The measurements were taken over a one-year period (November 2021 to November 2022). To correct the data obtained from the sensors, correction coefficients obtained from a reference device placed near the low cost sensor Accra (Ghana) were used. A Gaussian mixture linear regression was used to obtain corrected data. The daily concentrations measured at all the sites ranged from 17 to 35 µg/m3, with an overall average of 25 µg/m3. These concentrations are higher than the WHO 24-hour standard, which is set at 15 µg/m3. Measurement values are highest during the dry season, which is dominated by harmattan winds. At all sites, between 61% and 87% of the days measured exceeded the new WHO guidelines for PM2.5. These measurements show the need to undertake an action plan to reduce air pollution in general in Burkina Faso in order to better protect the health of the population.
Analysis of PM2.5 and PM10 Particles from Low-Cost Sensor Networks in Major Urban Cities of Ghana - Mr. Emmanuel Appoh (Ghana)
Presented by: Mr. Emmanuel Appoh, Assistant Facility Manager, Afri-SET Evaluation and Testing Facility, Department of Physics, University of Ghana, Accra, Ghana E: eeappoh@yahoo.com

Air pollution is a significant environmental health risk in African cities, accounting for one in every nine deaths worldwide. In this study, PM2.5 and PM10 concentrations were measured in three major urban cities (Accra, Tema and Kumasi) in Ghana from January to June 2022. Daily PM2.5 measurements were obtained from fourteen monitoring sites utilizing low-cost sensors.
From the results of the study, the mean PM2.5 concentrations in Tema, Accra and Kumasi were 40.34, 42.65, and 50.22 g/m3, respectively. The corresponding mean PM10 concentrations were 53.36, 56.95 and 68.51g/m3 respectively. The PM2.5 fraction accounted for 67-94% of the PM10 in Tema, 68-82% in Accra and 66-84% in Kumasi. The results also show that the daily mean PM2.5 concentration from the three urban cities exceeded the Ghana air quality standard (35 g/m3) and the WHO guideline level (15 g/m3). However, the daily mean PM10 concentration from the three urban cities were lower than the Ghana ambient air quality standard (70 g/m3) but exceeded the WHO recommended guideline level (45 g/m3). Furthermore, ambient daily PM2.5 and PM10 concentrations at all the sample sites showed strong correlations with each other, indicating that they originate from similar pollution sources. The findings of this study will contribute to bridging the data gap and provide a clear understanding of the situation of air quality in the country’s major urban cities.
Air Pollution and Climate Variability in the Humid Tropical Environment of Nigeria - Dr. Felix Paul (Nigeria)
Presented by: Dr. Felix Paul, University of Uyo E: flexipaul001@gmail.com

The study was set to assess the correlation between Air pollution and Climate Variability in the Humid tropical environment of Nigeria. The sampling parameters were measured in the windward direction of the sampling locations using Kestrel 4500 Compound weather Tracker (for measurement of meteorological parametres) and The gasman auto sampler was used to monitor the concentration of Nitrogen dioxide (NO2), Sulphur dioxide (SO2) Carbon monoxide (CO), hydrogen Sulphide (H2S) and Methane (CH4), while Sim-air quality software was used to calculate the air quality index of the air pollutants. These gases contribute to the problem of global warming. The Greenhouse gas and Air pollution Interactions and Synergies (GAINS) Model was employed to consider emissions of sulphur dioxide (SO2), nitrogen oxides (NOx), particulate matter (PM2.5 and PM10), ammonia (NH3) and volatile organic compounds (VOC), as well as the greenhouse gases carbon dioxide (CO2), methane (CH4) and Nitrous oxide (N2O). The GAINS Model provides activity data and control strategies for future scenarios, estimates emissions and costs of current or future air quality policies and calculates the reductions in environmental impacts. It was found that the concentration of air pollutants such as Sulphur dioxide (SO2); Methane (CH4); Nitrogen dioxide (NO2); Hydrogen Sulphide (H2S); and Carbon monoxide (CO) were all above the regulatory standard of NiMet. Indicators of climate variability in the study area include: Temperature rise, sea level rise, coastal erosion, coastal flooding, precipitation change, windstorm, amongst others. The model shows the interdependence and correlation between Air pollution and Climate Variability in the region; as Greenhouse gases (GHG) were emitted in the region. Acid rains, black sooth and airborne diseases, are predominant meteorological hazards in the region. This study recommends that drastic measures be put in place so as to reduce the high level of pollution; reforestation should be encouraged to absorb suspended air pollutants; environmental education should be intensified and air quality monitoring stations installed at strategic locations for continuous monitoring and evaluations.
Air Quality Index and Health Dynamics in the Changing Climate of the Humid Tropical Environment of Nigeria - Dr. Felix Paul (Nigeria)
Presented by: Felix Paul, University of Uyo E: flexipaul001@gmail.com

The study was set to assess the effect of air quality index on health dynamics in the Humid Tropical Environment of Nigeria. The study employs the multi-stage sampling design. Data was analyzed using geospatial and geostatistical techniques with the mean values of the air pollutant concentrations estimated for the measurements. The standard deviation (SD) and variance was determined while the estimated coefficient of variation (CV%) was used to assess the variation in the concentration levels of the air pollutant monitored. The gasman auto sampler was used to monitor the concentration of Nitrogen dioxide (NO2), Sulphur dioxide (SO2) Carbon monoxide (CO), hydrogen Sulphide (H2S) and Methane (CH4), while Sim-air quality software was used to calculate the air quality index of the air pollutants. These gases are known to induce or cause respiratory disease in exposed humans and also contribute to the problem of global warming. It was found that the concentration of Sulphur dioxide (SO2) ranged between 0.041 and 0.050 ppm; Methane (CH4) concentration ranged between 0.137 and 0.213 ppm; Nitrogen dioxide (NO2 concentration ranged between 0.19 and 0.52 ppm; Hydrogen Sulphide (H2S) concentration ranged between 0.126 and 0.156 ppm; and Carbon monoxide (CO) concentration ranged between 77.67 and 85.33 ppm. The diseases found to be prevalent in the study area as a result of air pollution are Pulmonary Tuberculosis (5.2%), Cerebrospinal Meningitis (10%), Headache (30%), Whooping cough (10%), Measles (5%), Dizziness (23%), Catarrh (35%), Pneumonia (10%), Shortness of breath (17%), Sore throat (20%), Eye irritation (30%), Cough (25%), Sneezing (33%), and Skin irritation (30%). The average ambient air quality observed in the LGAs (SO2 = 0.046 ppm, CH4 = 0.175, NO2 = 0.36 pp, H2S = 0.146 ppm, CO = 82.5) was worse compared to the World Health Organization Air Quality Permissible Limit (SO2 = 0.01 - 0.1ppm, NO2 = 0.04 - 0.06ppm, CO = 10.0 - 20.0ppm, H2S = 0.06ppm, CH4 = 0.06ppm). This study recommends that drastic measures be put in place so as to reduce the high level of pollution; reforestation should be encouraged to absorb suspended air pollutants; environmental education should be intensified and air quality monitoring stations installed at strategic locations for continuous monitoring and evaluations.
Influence of Wind Speed, Wind Direction, Relative Humidity, and Seasonal Variability on Ambient Air Quality in Kampala Meteorological Area - Mr. Fidel Wabinyai (Uganda)
Presented by: Mr. Fidel Wabinyai, Data Scientist, AirQo E: raja@airqo.net

According to World Health Organization (WHO), air pollution is a major environmental and health problem in many urban areas around the world. Exposure to high levels of particulate matter (PM2.5 and PM10), a common air pollutant, can cause various respiratory and cardiovascular diseases, as well as premature mortality. The levels and sources of PM2.5 and PM10 vary depending on the location, season, and meteorological conditions. Therefore, it is important to monitor and analyze the spatiotemporal patterns and relationships of PM2.5 and PM10 and meteorological variables in urban environments. This study aims to investigate the influence of meteorological parameters and seasonal variations on ambient air quality in the Kampala Metropolitan Area (KMA), Uganda, using data from nine AirQo monitoring stations.

A comprehensive dataset of hourly PM2.5 and PM10 concentrations and meteorological parameters (relative humidity, wind speed and direction) for the year 2021 to 2022 was collected from the nine AirQo monitoring stations covering different land use types within the KMA. The study involved the analysis of air quality data using descriptive and inferential statistics to examine the spatiotemporal patterns and relationships of particulate matter (PM2.5 and PM10) and meteorological variables. Cluster analysis was performed to identify homogeneous groups of monitoring stations based on their PM levels and meteorological characteristics. Multiple linear regression models were developed to quantify the effects of meteorological variables on PM2.5 and PM10 concentrations at each station. The influence of seasonal variations on air quality was also assessed by comparing the mean PM levels and meteorological parameters across different seasons.

Preliminary findings revealed that wind speed and direction play a crucial role in the dispersion and transport of air pollutants. Wind speed higher than 1 m/s is associated with improved air quality due to enhanced dispersion, while wind speed less than 1 m/s leads to poor air quality. Wind direction and wind speed analysis shows that prevailing winds from the South-South-East (SSE) significantly impacted PM values. The correlation between wind speed and PM in the SSE direction was -0.854 (PM2.5) and -0.818 (PM10). All other wind directions exhibit a negative correlation, except for the South, where the correlation wind speed and PM2.5 and PM10 was 0.214 and 0.244 respectively. Seasonal variations exhibited significant influences on air quality in the Kampala Metropolitan Area. The dry season demonstrated higher pollution levels, while the wet season exhibited relatively improved air quality. The highest median PM2.5 concentration level of 45.84 µg/m3 was observed during the month of February 2021 dry season and the lowest median was 15.50 µg/m3 during the wet month of April 2021.
The highest median concentration for the PM10 of 55.41 µg/m3 was observed during the dry the month of February 20221 while the lowest median was 19.18 µg/m3 during the wet month of April 2021.

Relative humidity was found to be higher during the wet season of the year, corresponding to lower levels of particulate matter (PM2.5 and PM10), while lower humidity during the dry season corresponds to higher levels of the particulate matter. However, there was a weak to moderate positive correlation (r = 0.25 for PM2.5 and r = 0.32 for PM10) between relative humidity and particulate matter throughout the year.

This research will contribute to a better understanding of the factors influencing ambient air quality in urban areas, specifically focusing on the Kampala Metropolitan Area. The findings can assist policymakers and urban planners in implementing effective strategies to mitigate air pollution and improve public health outcomes in the region. The study emphasizes the significance of considering meteorological parameters and seasonal variations when assessing air quality in urban environments. Additionally, it will provide valuable data and insights for future studies on the effects of air pollution on climate change, biodiversity, and ecosystem services in the region. The study will also showcase the applicability and usefulness of advanced statistical and analytical methods for air quality assessment and management in urban areas. Finally, it aims to enhance public and stakeholder awareness and knowledge regarding the sources, levels, and impacts of air pollution in urban areas, promoting their active participation and collaboration in addressing this issue.

Keywords: air pollution, wind speed, wind direction, relative humidity, seasonal variability, Kampala Metropolitan Area. Particulate matter (PM2.5 and PM10)
The Difference Between Accurate and Reliable Data Relating to the Concentration of Atmosphere Constituents - Dr. Robert Mbiake (Cameroon)
Presented by: Dr. Robert Mbiake, Professor, Université of Douala E: rmbiake85@gmail.com

The atmosphere is composed mainly of 2 types of constituents: Molecules and aerosols. Beyond a certain concentration, its constituents become atmospheric pollutants with harmful effects on health and the environment. Hence the urgent need to know the evolution of their concentration both in space and time. The techniques used to measure these different concentrations depend on the size of the particle and its concentration.
While molecules have diameters of the order of 10-9µm, aerosols are 1µm on average. Thus, depending on this size, either ultra-sensitive molecular spectroscopy or the weighing technique using devices such as the Digitel DH77 or Low-Cost Sensors will be used. For molecules, the precision in the values makes it possible to identify the different isotopic species that can be encountered in the same molecular sample. When for aerosols, they are classified according to their size (PM1, PM2.5 and PM10). This grouping is mainly due to their effect on health in relation to their ability to penetrate our bodies. In this case, we have more reliable data than precise data.

In the presentation that we propose to make, we will show on the one hand, the results of the measurements obtained in the identification of the isotopic species of H14NO3 and H15NO3 whose identification data are extremely precise and on the other hand, the data obtained on PM2.5 obtained from measurements using DH77 and LCS. These results highlight the difference between precise data and reliable data.

Keywords: Molecules, aerosols, concentration, spectroscopy, LCS, DH77; HNO3 and PM2.5
Gender-dependent distribution of exposure reduction from LPG adoption in Techiman, Ghana - Ms. Misbath Daouda (United States)
Presented by: Ms. Misbath Daouda, PhD Candidate, Columbia Mailman School of Public Health E: md3851@cumc.columbia.edu

The majority of clean cooking interventions have taken place in rural areas with a very small number occurring in major urban centers. Additionally, the evaluation of these interventions has focused on women because of their role as primary cooks. As a result, the effect of clean cooking interventions in urban settings and the distribution of benefits between male and female household members are not well understood. To address these gaps, we carried out a randomized controlled trial in Techiman, a peri-urban town in central Ghana, to assess the effect of Liquified Petroleum Gas (LPG) adoption on personal exposure to carbon monoxide (CO) and particulate matter (PM2.5) among male and female members of the same household. Briefly, 159 households (318 participants) that primary used charcoal for cooking were randomized to an intervention (provision of an LPG starter kit and discounted refills) or a control arm. In each household, 72-hr CO exposure (Lascar EL-CO-USB), wearing compliance (HOBO accelerometer), and participant location (Columbus P-1 GPS) were measured pre- and post-intervention for the primary cook and a cohabitating household member of opposite gender. Exposure to PM2.5 (24-hr) was measured in a random subset of households. Stove use was also assessed by deploying up to three stove use monitors per household (Wellzion Thermocouple data logger). Across all valid CO measurements (n = 573), the median (IQR) 72-hr CO exposure was 1.45 (2.30) ppm among female participants and 0.84 (1.79) ppm among the cohabitating male participants in their household. In the post-intervention period, overall 72-hr was lower (-47.2%; 95%CI: -61.9%, -26.8%) in the intervention compared to the control arm with a greater difference among male (-57.1%; 95%CI: -74.3%, -28.5%) compared to female participants (-32.7%; 95%CI: -54.4%, -0.8%). The interpretation of these findings will be aided by the ongoing analysis of stove use and time-resolved participant location during monitoring.
Emissions from the transport sector, using low-cost, passive sampling indicate potential threat to human health in Johannesburg, South Africa - Dr. Raeesa Moolla (South Africa)
Presented by: Dr. Raeesa Moolla, Senior Lecturer, University of the Witwatersrand E: Raeesa.Moolla@wits.ac.za

Diesel and petrol fumes are known to emit anthropogenic sources of air pollutants that have a negative impact on both environmental and human health. In South Africa, petrol pump attendants still refuel vehicles, older, high emission vehicles are on the road, and a high reliance on personal vehicle usage is the norm (i.e. limited public transport network options are available). This places both employees and the general public at risk to adverse health effects; associated with inhalation of hazardous air pollutants (HAPs), from various transport sectors. A range of studies analyses the ambient concentrations and occupational exposure of VOCs, using low-cost passive samplers and hand-held weather meters, supplemented with questionnaires and hotspot modelling tools. Samples were obtained from an airport and its surroundings, bus depots, and gas refueling bays- from 2013 until 2021 (intermittently). Concentrations across all the different transport sectors indicated that employees were at a significant risk to adverse health effects associated with inhalation exposure to these pollutants, in most situations- thus the need for further analysis. However, as the sensors are limited (in number), sampling tubes are expensive and analysis is costly, data is sporadic and irregular. Some of the questions that will be unpacked are: (1) how these sensor data sets can be used in environmental health risk analysis, (2) what results can be inferred (through other methods), (3) what initiatives can be implemented to reduce exposure to air pollution in different transport contexts, and lastly (4) who is most affected by the deteriorating air quality. Lastly, issues around the limitations of in-situ measurement data sets from passive samplers and the mixed methods approach will be discussed.
Unlocking the Potential of Low-Cost Air Pollution Sensors: Insights from the QUANT Project - Dr. Sebastian Diez (Argentina)
Presented by: Dr. Sebastian Diez, Researcher, Universidad del Desarrollo / University of York E: sebastian.diez@york.ac.uk

Harnessing the potential of low-cost air pollution sensors (LCS) in the fight against air pollution presents a transformative opportunity. Their cost-effectiveness, coupled with high temporal resolution and the potential for dense network deployment, could reshape our approach to tracking key pollutants, analyzing the health repercussions of air pollution exposure, and scrutinizing clean air policies. However, the application of commercial LCS products is often ambiguous due to the lack of comprehensive understanding of their performance.
Addressing this knowledge gap is the core objective of the QUANT project. Over the past three years, this initiative has involved 52 commercial LCS devices from 14 different companies, continuously capturing air quality data across diverse urban environments in the UK, whilst being co-located with reference-grade instruments. As of November 2022, a rich dataset has been assembled, incorporating measurements of multiple pollutants captured via LCS systems of varying sensor technologies and software capabilities.
In this presentation, we will distill the initial insights drawn from this extensive study, emphasizing key factors when assessing LCS for specific tasks - including the reliability of the calibration algorithm, consistency among devices from the same manufacturer, site-specific performance, and responses to meteorological conditions.
Establishing An Integrated Ambient Air Quality Monitoring Network In The Gambia Using Low-Cost Air Sensors: The Permian Health Clean Air Initiative - Dr. Sunkaru Touray (United States)
Presented by: Dr. Sunkaru Touray, Founder & Executive Director, Permian Health | The Lung Institute E: stouray@permianhealth.org

Air pollution is a significant environmental threat to human health, responsible for about 7 million premature deaths globally. The Gambia is undergoing rapid environmental changes with increasing levels of air pollution due to population growth, large-scale urbanization, and economic development, largely powered by burning of fossil fuels that puts many citizens at risk of adverse health outcomes.

Fine particulate matter (PM2.5) are small airborne particles with an aerodynamic diameter of 2.5 microns or less and are capable of penetrating deep into the lungs and into the bloodstream, resulting in lung function and cardiovascular impairment.

Most Gambians, especially women are overrepresented in activities and occupations both in the home and outside, that exposes them to ambient air pollutants. Household air pollution (HAP) from the incomplete combustion of biomass fuels during cooking is a leading source of exposure to fine particulate matter (PM2.5), carbon monoxide (CO), and other air pollutants. Women involved in agriculture, gardening, and fish processing are also at an increased risk of developing poor health outcomes due to occupational exposures to pollutants during these activities. According to a report by the United Nations Environment Program, over 95% of the Gambian population were using solid fuels in 2008 (the last year published data was reported).

The World Health Organization (WHO) has set universal health-based Air Quality Guidelines (AQGs) published in 2021 based on an extensive body of scientific evidence relating to air pollution and its health consequences. The WHO AQGs set an annual average concentration of PM2.5 at less than 5 µg/m3, and a 24-hour average exposure target at less than 15 µg/m3 per year.6 WHO data also indicate that almost all of the global population (99%) breathe air that exceeds WHO guideline limits and contains high levels of pollutants, with low- and middle-income countries (LMIC) including The Gambia suffering from the highest exposures.2

Air quality standards (AQS) are distinct from AQGs, as they are set by each country to protect the public health of their citizens and as such are an important component of national risk management and environmental policies. Currently, there are no published national ambient air quality standards (NAAQS), policies, or legislation, and The Gambia does not have an Ambient Air Quality Monitoring Network (AAQMN).

The Permian Health Clean Air Initiative (PHCAI) is a multidisciplinary collaborative effort that seeks to promote lung health by filling air quality knowledge and evidence gaps in The Gambia. We are partnering with IQAir, a Swiss manufacturer of outdoor air monitoring stations, to deploy multiple air quality monitoring stations in The Gambia as part of an expandable Ambient Air Quality Monitoring Network (AAQMN). These stations will continuously measure air pollutants (PM1, PM2.5) and share air pollution data openly with the Gambia National Environment Agency, and private stakeholders including real estate companies, television stations, and the public. Data will be fully available on IQAir AirVisual Platform in a format that is easy to understand by the public. We will also engage with government stakeholders at the Ministry of Health, Gender and Women's Affairs, and the Ministry of Education to conduct sensitization campaigns in several communities across Gambia, and to provide training on how to integrate air quality data in policy formulation.

The AAQMN is important as it will fill important data gaps on air quality and pollution and identify further areas for research and development. Ultimately, this concept paper serves as a starting point for the development of a comprehensive air quality monitoring program that can help to protect and improve lung health in The Gambia.
AirQo Data Logger: A low-cost approach to reference grade monitors data retrieval - Mr. Anold Nsubuga (Uganda)
Presented by: Mr. Anold Nsubuga, International Network Support Engineer, AirQo E: anold@airqo.net

Addressing air quality issues in African cities requires data and evidence to show the scale and magnitude of air pollution. However, even with the limited access to available reference grade monitors, real time data access from these devices is still costly thereby limiting data accessibility and usability for action. The conventional method of data access from reference monitors requires physical presence or recurring data access subscriptions. These data access methods rely on human labor to retrieve historical data or availability of funds for real time data access subscription renewal. In this paper, we present a low-cost approach to accessing data from reference grade monitors termed the data logger whose advantages include:- remote and real time access to data, data transfer in regions without WIFI connectivity, real time fault and anomaly detection for action and maintenance procedures. The proposed data logger is a GSM-based data collection and logging solution which employs serial communication protocols to interface with reference grade monitors and log data to a cloud-based system for processing and analysis. The data logger has been implemented and well tested with several reference grade monitors in Africa.
Understanding PM2.5 variation based on ground activities in Punjab, India - Dr. Vignesh Prabhu (India)
Presented by: Dr. Vignesh Prabhu, Senior Associate, Center for Study of Science Technology and Policy E: vignesh@cstep.in

Air pollution being a global challenge, is a significant problem in many areas of the state of Punjab and addressing it will require a scientific approach to understand the existing challenges. As per the recent govt. reports, Punjab has a population density of around 551 person km-1 and around 85% of the land is under agriculture. Along with agriculture, other sectors of pollution were also found
To understand the influence of other sectors in Punjab, 44 low-cost PM2.5 sensors were installed. These sensors were installed in five districts (Amritsar, Bathinda, Hoshiarpur, Ludhiana and Mohali) of Punjab to understand the variation of PM2.5 based on the ground activities such as traffic flow, road type, crop residue burning, type of industries, time of functioning of the industries, etc. The sensors were installed over a period of 12 months after a preliminary survey of the demographic information such as population, industrial cluster, road network, fuel used for cooking and crop residue burning. Regional calibration was performed by collocating the sensors with a reference grade monitor. The calibration was carried out for almost two months and the coefficient of determination was found to be R2=0.75. 20 sensors were kept in households, amongst which, 16 sensors were kept in indoor conditions, to assess the impact of LPG and fossil fuel on the PM2.5. 15 sensors were placed close to a traffic junction to assess the impact of transportation on PM2.5. Four sensors were placed around crop residue burning sites to assess the elevation in PM2.5 due to the paddy and wheat crop residue burning activity.
To understand the variation of PM2.5 levels, the influence of various ground activities was studied in detail. The study results highlighted the variation in PM2.5 levels based on the proximity of polluting sources such as
• Transportation: PM2.5 variation was analyzed with regard to a few factors such as
a) Peak and non-peak hours. During the peak hours of 09:00 to 11:00 and 17:00 to 20:00, the PM2.5 levels were found to be ~2 times higher compared to the non-peak hours. Higher concentrations of PM2.5 during peak hours may be attributed to various factors such as increased traffic volume
b) Road type: The PM2.5 levels recorded at the sensor located on an unpaved road were found to be 1-2 times higher when compared to the sensor placed on a paved road. This significant difference in PM2.5 levels suggests that the condition of the road surface plays a crucial role in the amount of PM2.5 emissions.
c) Distance from the junction: The PM2.5 levels were significantly lower (~30 µg m-3) in the sensor located 400 meters away from the junction, compared to the sensor positioned just 90 meters away from the junction. The disparity in PM2.5 levels between the two sensors indicates that the pollution levels decrease as the distance from the junction increases. This could be attributed to factors such as vehicle emissions, or other sources of PM2.5 that are more prevalent in the immediate vicinity of the junction
d) Type of vehicular movement: PM2.5 levels were found to be ~1.5 times higher near the junction with a high modal share of heavy vehicles, in comparison to the junction with a higher presence of Light Commercial Vehicles (LCV). This suggests that the type of vehicles present near the junction has an influence on PM2.5 pollution levels. In areas where heavy vehicles dominate the traffic flow, such as trucks or buses, the PM2.5 levels were noticeably elevated
• Industrial: Sensors placed near industrial regions exhibited a day-night trend in PM2.5 and also showed ~10% higher mean PM2.5 concentrations compared to those situated farther away. The day-night trend in PM2.5 concentrations near industrial regions suggests that there are specific time periods when the levels of PM2.5 are higher. This pattern can be influenced by factors such as industrial activities, variations in emissions, or meteorological conditions throughout the day
• Domestic: households utilizing LPG for cooking showed lower PM2.5 levels compared to those relying on fossil fuel-based cooking by a factor of 2-3 times. This finding suggests that the choice of cooking fuel has a significant impact on the levels of PM2.5 in indoor environments. LPG, which is comparatively a cleaner-burning fuel to fossil fuels such as coal or wood, produces fewer PM2.5 emissions during the combustion process
• Crop Residue burning: During the crop-burning season, around 2-3 times elevation in PM2.5 levels was observed in the districts. The observed elevation in PM2.5 levels during the crop-burning season indicates poor management of crop residues in the districts. The released PM2.5 from crop burning can have detrimental effects on air quality and human health
Understanding PM2.5 derived from low-cost sensors based on ground activities holds immense potential to provide valuable insights, facilitate evidence-based decision-making, and contribute to the development of more effective strategies to address air pollution and its associated impacts.
Performance evaluation of multiple air pollution sensors: Case of an Indian coastal city - Dr. Sreekanth Vakacherla (India)
Presented by: Dr. Sreekanth Vakacherla, Scientist, Environmental Defense Fund E: svakacherla@edf.org

The role of low-cost sensors (LCS) in air pollution management is becoming increasingly popular. Multiple vendors are assembling LCS using a variety of portable laser counters and electrochemical sensors. In this study, we evaluated the performance of four different LCS in terms of their PM2.5 and NO2 measurement accuracies. We collocated the LCS with reference grade instrumentation in the city of Mumbai (a coastal city in India) in December 2022. All four LCS under investigation employed a variety of laser counters for PM measurements and different versions of Alphasense electrochemical sensors for NO2 measurements. Using the collocation data, the precision and accuracy of the LCS measurements were evaluated and quantified based on metrics such as coefficient of determination (R2), root mean square error (RMSE), and normalized root mean square error (NRMSE). The R2 values varied between 0.33 and 0.66; 0.53 and 0.77; 0.00 and 0.16; 0.86 and 0.97; 0.90 and 0.96 for PM2.5, PM10, NO2, relative humidity (RH), and air temperature (AT) respectively. Similarly, the NRMSE varied between 0.40 and 0.61 for PM2.5; 0.23 and 0.61 for PM10; 0.70 and 1.00 for NO2. The linearity and accuracy of LCS PM2.5 were found to be better than that of LCS NO2 measurements. The observed performance metrics suggest a correction to the raw LCS measurements of PM2.5 and NO2, in addition to the manufacturer’s lab calibration. A simple linear correction model including NO2, RH, and AT was not able to effectively improve the accuracy of the LCS NO2 measurements. In view of the cross-sensitivities of the electrochemical sensors, a multi-gas LCS is always preferred to deploy rather than a single gas pollutant sensor.
Machine Learning Approach for Particulate Matter Near the Quarry Industries in South-eastern Nigeria - Dr. Imoh Ekpa (Nigeria)
Presented by: Dr. Imoh Ekpa, Doctor of Atmospheric Physics, Federal University of Technology Ikot Abasi E: domphy4@yahoo.com

In South-Eastern Nigeria, several quarry operations offer employment opportunities for locals and generate income for the governments. These businesses do, however, frequently cause air pollution, and the deadliest is PM2.5 which has been found to have a deleterious impact on humans, plants, and the ecosystem, especially if the amount in the air is quite high. The Extech Model VPC300 sensor was used to measure PM2.5, PM10, and some meteorological factors at the four quarry sites and their surroundings. The machine learning method was used to predict the particulate matter after training and testing the data set. The particulate matter near the quarry areas had the highest correlation matrix, with a value of 0.9358. Additionally, three different machine learning models of LSMT, GRU, and MRA were used with MRA showing the best regression of 0.9971 with a p-value of 0.0002. The MRA mathematical model has a 99.7% accuracy rate in correctly predicting PM2.5 in the vicinity of the quarry. By comprehending the current air quality condition with the help of an accurate prediction of this pollutant concentration, such as this, the public and the government may create effective prevention or control actions.

Data Utility & Action for Air Quality Management

This session will cover data utility for the development of air quality management practices. Speakers will review case studies about low cost sensors used in monitoring urban air quality, source apportionment and health exposures. Additionally, they will discuss how the data can be used for predicting and communicating health outcomes with the aim to inspire community changes.

Watch Recording of Session

Podium Presentations:

Empowering cities with Air Quality Data Evidence to inform Policies and decision making - Dr. Simon Sambou (Senegal)
Presented by: Dr. Simon Sambou, Regional Technical Advisor for Air Quality, West Africa, C40 Cities E: ssambou@c40.org

African megacities are experiencing high levels of air pollution with significant impacts on human health. To tackle this issue, a better understanding of various sources of air pollutants and their concentration levels is key to influence air quality (AQ) improvement efforts. However, there is a huge gap in AQ monitoring network capacities in most of the African cities. To fill this gap, C40 through the African Cities for Clean Air (AC4CA) programme supports C40’s African cities to attain the data, evidence and build technical capacity needed to effectively implement ambitious AQ solutions. C40 cities’ through the Clean Air Accelerator (CAA) have committed to take ambitious actions to improve AQ and identified action priorities and needs for technical assistance. The AC4CA program has provided technical assistance and capacity building initiatives to several cities including: Addis Ababa, Dakar, Durban, Johannesburg and Lagos State. The development of AQ policies in these five cities aligns with the objectives of air quality management planning, AQ data monitoring and identify data collection gaps and strategies forward to expand low-cost sensors (LCS) networks. This will allow them create a representative database to inform decisions making. The technical assistance projects are strengthened by a series of capacity building trainings on AQ modelling and health impact analysis, air quality communication planning, and peer-to-peer learning exchanges among African cities and beyond, through the AC4CA and AQ network platforms.
Eko for Clean Air: a Case study on Public sector guidance, regulatory audit and enforcement changes driven by inclusive air quality and behavioral data collection systems in Lagos State, Nigeria - Dr. Adebola Odunsi (Nigeria)
Presented by: Dr. Adebola Odunsi, Technical Special Assistant to the GM of LASEPA E: odunsiadebolamd@gmail.com
Description coming soon!
Air quality standards and the importance of an AQI for Ghana - Mrs. Esi Nerquaye-Tettah (Ghana)
Presented by: Mrs. Esi Nerquaye-Tetteh, Ghana EPA E: esi.nerquaye-tetteh@epa.gov.gh
Health exposure assessment - Dr. Reginald Quansah (Ghana)
Presented by: Dr. Reginald Quansah, Ghana EPA E: rquansah@ug.edu.gh

Poster Presentations

Particulate Matter, Toxicity Potential, Air Quality Index, and Hazard Quotient of an Indoor Setting - Dr. Francis Olawale Abulude
Presented by: Dr. Francis Olawale Abulude, CEO, Environmatal and Sustainable Research Group, Science and Education Developmet Institute, Akure, Ondo State, Nigeria E: walefut@gmail.com

Indoor Air Pollution (IAP) is a serious problem worldwide because of the side effects it has on citizens. To mitigate this, research and policies have been put in place to reduce the particulate matter of different diameters (PM0.1-10) and their health risks. The aim of the present study was to find out the concentrations of PM and its associated health risks (toxicity potential (TP), air quality index (AQI), and hazard quotient (HQ)) in an indoor setting in Akure, Nigeria. Five rooms (two Living rooms, one kitchen, and two other rooms) were monitored for a period of one month. Concentrations of PM0.1, PM0.3, PM0.5, PM1.0, PM2.5, PM5.0, and PM10 (µg/m3) were measured with Canāree Air Quality portable Monitor A1 which auto Calculated and displayed AQI scores every 60 seconds. The results showed the overall average of particulate matter (p<0.05) as; PM1.0 (0.39±0.01), PM0.3 (7.18±3.8), PM0.5 (50.96±29.21), PM1.0 (146.29±197.7), and PM2.5 (472.6±753.0), PM5.0 (543.4±818.9), and PM10 (544.8±819.3). The mean TP levels of PM10 and PM2.5 were >10 (very high levels) which indicates potential health risks for the inhabitants. Significant variations of AQI were observed, these were higher for PM2.5, PM5.0, and PM10 than others. The AQI depicted hazardous levels of concern. The HQ levels have the potential of causing health problems for children and adults either on acute or chronic bases. In conclusion, the PM2.5 and PM10 concentrations were higher than the WHO guidelines. Efforts must be in place to reduce the sources of pollution.

Keywords: Indoor Air Quality, Indoor Air Pollution, WHO guideline, Canāree sensor, Air Quality Index
Air Quality Monitoring and Analysis: A Case Study of Akwa Ibom State - Mr. Dan Paul (Nigeria)
Presented by: Mr. Dan Paul, Member, ClimAQ Nigeria E: danpauls123@gmail.com

This talk will highlight some recent efforts to close the air pollution data gap in Africa using surface-based observations from traditional reference monitors and consumer-grade low-cost sensors. In particular we demonstrate the effectiveness of well-calibrated low cost particulate matter sensors in several previously-unmonitored megacities including Kinshasa (DRC), Lomé (Togo), Accra (Ghana), Nairobi (Kenya), and more. We find that many consumer-grade Plantower-based low-cost PM2.5 monitoring devices, such as PurpleAir, Clarity, and QuantAQ, perform well (r-squared ~ 0.6, MAE ~ 7 µg m-3) compared to locally available reference monitors, but can be improved dramatically (r-squared ~ 0.8, MAE ~ 2) using a variety of statistical methods, including linear regression, random forest regression, and Gaussian mixture regression. These well-calibrated sensors form the basis of dense urban networks of PM2.5 monitors in several African megacities, for example in Kinshasa (DRC), where the annual mean PM2.5 in 2019 was approximately 45 µg m-3, or ~8 times the WHO annual guideline. We also demonstrate some potential use cases of sensor networks such as source apportionment of PM2.5 in Africa, which is sorely needed in order to take action to mitigate pollution. Finally, this talk will present future plans for field intensives for air quality monitoring in Africa that goes beyond cheap sensors and will discuss what the current needs are to ramp up the type of high quality measurements that are commonplace in wealthy countries.
Effect of Air Pollution on Huan Health Status in Akwa Ibom State - Mr. Ini Jimmy (Nigeria)
Presented by: Mr. Ini Jimmy, Vice President & Administration, The Speakers' Network E: jimmyini93@gmail.com

Air pollution is a pressing global environmental issue that poses significant risks to human health. In Akwa Ibom State, Nigeria, rapid industrialization, urbanization, and the associated increase in emissions have resulted in elevated levels of air pollutants. Understanding the effect of air pollution on human health status in Akwa Ibom State is crucial for implementing effective interventions to protect the well-being of the population. This study provides an overview of the impact of air pollution on human health, with a specific focus on respiratory health, cardiovascular diseases, and other related health outcomes in Akwa Ibom State. The causes of air pollution include burning of fuel wood, mining, use of fossil fuel in automobiles and power generating plants in commercial and residential buildings, among other anthropogenic activities. These has raised concerns and generated doubts to researchers as they seek data and results from developing countries based on spot pollution research results. To erase these doubts, this research involved an in-depth analysis of the spatial concentration of air pollutants in Akwa Ibom State on a local scale, integrating health records to scientific field data. The reason for speculative data is hereby eroded with this study, leaving no doubts to the authenticity of data from developing countries. The study will employ a comprehensive approach, examining both outdoor and indoor air pollutants and their impact on various health outcomes. This research shall assess the levels and sources of outdoor and indoor air pollutants in Akwa Ibom State, investigate the relationship between air pollution and respiratory health issues among the population, examine the relationship between air pollution and cardiovascular diseases in the study area and determine the impact of air pollution on overall mortality rates and life expectancy in Akwa Ibom State. The research will employ a cross-sectional study design to collect data on air pollution exposure and health outcomes at a specific point in time. The target population will consist of residents in Akwa Ibom State who have been exposed to varying levels of air pollution.
Understanding the effect of air pollution on human health status in Akwa Ibom State is crucial for policymakers, healthcare professionals, and the community. By quantifying the relationship between air pollution and various health outcomes, this research shall provide evidence-based recommendations for interventions and policies aimed at reducing air pollution levels and mitigating its adverse effects. Implementing effective strategies will help protect the health and well-being of the population, reduce healthcare costs, and promote sustainable development in Akwa Ibom State.
Medical Implications of Air Contamination in selected polluted areas of Nigeria - Mr. Victory Dennis (Nigeria)
Presented by: Mr. Victory Dennis, Student, University of Uyo E: victorydennis76@gmail.com

The study assessed air pollution in Nigeria. The study has the objectives of identifying areas with high pollution in the study areas; examine the predominate cause of air pollution in the study area and the effect of the predominate causes of air pollution on the health and livelihood of people in the study areas. The instrument used for data collection are structured questionnaire, interviews, EPA’s air pollution monitor and Airnow. The administration of questionnaire and interviews were carried out by the team of researchers and data collection were analyzed using descriptive analysis such as percentage analysis to answer research question and results shown on air quality test sheet. Result shows that major cause of air pollution was due to smog caused level ozone (03) others includes areas with high fossil fuel burning and alternate power provision options giving rise to particulate matter (PM10, PM2.5). Air pollution has antagonistic effects on health and can be reduced by buying foods and cultivating foods locally to cut down on fossil fuel burning resulting from Pullman and rather embrace more ecofriendly modes of transportation like walk, bicycle, public transportation, electric cars or cars that consumes less gas. Health preventive measures includes using noise masks outside where the is high air pollution, wear sunscreen when outside, stay away from harmful smoke and also not intensify it, avoid opening windows if your indoors in areas of high pollution. ‘’Ozone is weaker in the morning, so avoid much outdoor activities’’, Walke. Avoid destruction of wetlands and wetland resources, plant more trees and green as it acts as climate modifier. Government and lawmakers should implement policies that allows for access to most facilities (like public transportation, reliable electricity supply), enact laws that allows for every diameter of living residence having trees around it as well as offices having green urbane plants to help reduce unnecessary generation of air pollutant.
Characterizing Aerosol Sources from Low-Cost Particle Sensors - Dr. Vikas Kumar (India)
Presented by: Dr. Vikas Kumar, PhD Scholar, Indian Institute of Technology Bombay E: 214400003@iitb.ac.in

Low-cost sensors (LCS) have the potential to significantly provide accurate and reliable measurements of air quality in real-time. This improves our ability to monitor, identify sources of pollution and develop mitigation strategies for effective air quality management. However, recent research focuses on monitoring, exposure assessment and calibration of LCS. In this study, we investigated the applicability of LCS for characterizing aerosol sources. Non-negative matrix factorization (NMF) was applied to the data collected for 15 days across five sites in Mumbai using Alphasense OPC-N2. NMF resolved two factors for three sites, namely aromas (S2), hostel hub (S3) and central library (S4), while three factors were resolved for two sites, namely construction site (S1) and main gate (S5). Two common sources were resolved for all the sites: dust and traffic and mixed sources, which agree with the sources identified by studies in the literature. The third factor resolved at sites S1 and S5 is representative of heavy-duty diesel vehicles (HDDVs) and is present for a very short period. This is the advantage as episodic activities can also be captured due to the availability of high temporal resolution of the data. In low- and middle-income countries with limited air quality monitoring capabilities, the network of low-cost sensors can give the regulatory agencies a rough estimate of the pollution sources as relative concentrations are sufficient for source characterization. The triangulation of the sources characterized by a network of LCS can help identify the region's major sources. This study indicates that a careful evaluation of correlation coefficients amongst various elements, coupled with a knowledge of the sources present in the region, can identify possible source types. This study provided evidence that despite their inherent limitations, LCS can be useful in attaining interpretable information about pollution sources and recommends extensive use of LCS for source characterization in the future.
The Influence of Nearby Pollution Sources on Ambient Air Quality: A Case Study of Ho, Tamale and Takoradi - Mr. Maxwell Seyram Sunu (Ghana)
Presented by: Mr. Maxwell Seyram Sunu, Environmental Protection Agency, Ghana E: seyramsunu@gmail.com

Cities in sub-Saharan Africa (SSA) are in economic transition and undergoing significant expansion. With the rapid growth, SSA cities are experiencing high levels of air pollution from diverse sources. In Additionally, environmental noise pollution is becoming a major public health concern in cities. Yet, there is a dearth of robust city-wide data for understanding space-time variations and inequalities in emissions and exposures, which is essential for evidence-based policies to create accountability towards equitable urban living.

Using a network of low-cost sensors, we have developed consistent and transferable protocol for generating rich environmental data in SSA cities. We showcase an extensive environmental measurement campaign, which has illuminated the patterns and dynamics of environmental quality in Accra, one of the fastest growing SSA cities. With this approach, we were able to map out at fine spatial (50 - 100 m) and temporal (daily - weekly) resolution multiple air pollutants, including ambient PM2.5, black carbon (BC), and oxides of nitrogen (NO and NO2), as well as environmental noise levels in to inform policy evaluation and climate and health impacts assessment in SSA context.

The data show significant disparity in pollutant concentrations across land use factors and socioeconomic gradient, with residents in the poorest communities and those in the inner-city core at higher risk of exposure. Further, we show that the entire population in Greater Accra Metropolis is exposed to air quality levels above local and international health-based guidelines.

Our innovative approaches to data collection and analytics using low-cost sensors can help track inequalities in SSA cities and their environment over space and time and can identify and support deprived and marginalised groups, and to create accountability towards equitable urban development.
Air Pollutant Concentrations and Epidemiological Impacts in the Humid Tropical Environment of Nigeria - Dr. Ekanem Ekanem (Nigeria)
Presented by: Dr. Ekanem Ekanem, University of Uyo E: ekanemekanem@uniuyo.edu.ng

This study attempts to assess the Epidemiological impacts of air pollutant concentrations in the Humid Tropical Environment of Nigeria. Epidemiological data will be accessed from the Federal Ministry of Health and from various State Ministries of Health and shall be examined in relation to the ambient Air Quality data of the States and the National Ambient Air Quality Standard data. The study shall cover a period of ten years ; from 2012 to 2022. The study employs the multi-stage sampling design. Data shall be analyzed using geospatial and geostatistical techniques with the mean values of the air pollutant concentrations estimated from the measurements. The standard deviation (SD) and variance will be determined while the estimated coefficient of variation (CV%) will be used to assess the variation in the concentration levels of the air pollutant monitored. ArchGIS software will be used to generate the pollutants concentration maps, while Sim-air quality software will be used to calculate the air quality index of the air pollutants. The diseases expected to be prevalent in the study area as a result of air pollution are pneumonia, pulmonary tuberculosis, measles, cerebrospinal meningitis (CSM), and whooping cough (pertusis). This study shall therefore probe to understand the air quality dynamics within the humid tropical environment of Nigeria. It will provide a detail outlook of spatial air pollutant concentration from a non-point source perspective and determine the effect of air pollution on health.

Key words: Air pollution, air quality index, epidemiological data, health effects, World Health Organization.

Policy Management

There are few opportunities to evaluate the utility of air quality sensor data in relation to air quality improvements resulting from targeted interventions such as, for instance, introduction of car free days in African Cities. The state of sensor technology has matured over time for some pollutants such as PM2.5, though still lags for trace gas measurements. The use of data from these sensors informing policy action across Africa has been growing, but there still are limited documented examples of this impact. This is partly due to the need for accurate, reliable, and readily available data to make effective decisions for reducing air pollution. This session aims to review how policy makers can use/are using and interpreting LCS data for clean air action. In addition, the session aims to look forward towards what are future needs for sensor technology and supporting data to inform policy and regulatory actions.

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Podium Presentations:

Using a low-cost sensor network for evidence driven air quality management in an African city: lessons from Kampala, Uganda - Dr. Alex Ndyabakira (Uganda)
Presented by: Dr. Alex Ndyabakira, Head Air Quality Management at Kampala Capital City Authority E: andyabakira@musph.ac.ug;

Establishing air quality monitoring networks remains a major challenge to attaining clean air for resource limited settings. Luckily, sensors which are inexpensive to purchase and maintain also known as low-cost sensors offer an affordable alternative for these settings. We present lessons learnt from establishing a low-cost air quality monitoring network in Kampala, Uganda.
Following a baseline assessment in 2018 which showed that Kampala city had high levels of air pollution, the Kampala Capital City Authority (KCCA) top leadership conducted a benchmarking visit for air quality monitoring to the United States of America (USA). Upon return, KCCA established an air quality monitoring network with clarity node sensors. These were later supplemented with locally made sensors manufactured by Makerere university airqo project to boast the monitoring coverage. These low-cost sensors are calibrated using the four reference stations owned and operated by Makerere University and US Embassy which ensures that the data from this network is of high quality. They are temperature stable and have not presented operational or maintenance challenges in Ugandan weather conditions. To inform policy, we assessed the trends of air pollution by reviewing data for the years 2020-2022. The effect of the natural experiment of COVID-19 induced lockdowns in 2020 and 2021 was considered as part of the evidence.
We used the above evidence to prioritize actions for rational resource use; 1) initiated targeted awareness raising and sensitization interventions, 2) started the pollution source attribution study 3) expanded monitoring infrastructure to monitor new areas and gases 3) initiated the city AQM policy 4) conducted access to energy study 5) developed the clean air action plan with data driven targets 5) provided input into revision of the climate change action plan 6) Implemented strategies for reduction of sectoral pollution. We continuously monitor the impact of our interventions on air pollution trends using data from the low-cost monitoring network.
Low-cost air quality monitoring sensing network provides a more sustainable inexpensive alternative for air quality management programs in African cities. Having locally, country-made low-cost sensors- offers the cheapest yet very sustainable prospects for achieving the ambitious clean air targets.
Air Pollution in Africa: Creating Healthier Cities for Future - Mr. Egide Kalisa (Rwanda)
Presented by: Mr. Egide Kalisa, Lecturer at University of Rwanda E: kalisa.egide@gmail.com

Air pollution is estimated as the largest cause of premature human mortality worldwide. This is a concern in sub-Saharan Africa due to a prevalence of ageing diesel and second-hand gasoline vehicles, dusty roads, trash burning, and solid-fuel combustion for cooking. Policies to reduce air pollution and protect health have been established in high-income countries. Such policies are, however, non-existent in Africa, where the air pollution problem is growing and gravely under-studied due to the lack of funding to install reliable ground-level monitoring networks and the lack of air quality standards. The present study used low-cost air quality sensors to investigate how children are exposed to air pollution at school and in transit to or from school. The findings showed that schoolchildren in Africa are frequently exposed to particulate matter air pollution levels exceeding the recommended World Health Organization air quality guidelines. Education can help to produce citizens who are literate in environmental science and policy. Continuing air quality measurement in schools and more intervention studies are needed to protect schoolchildren’s health and reduce exposure to air pollution in classrooms across Africa.
Johannesburg's Innovative Utilization of LCS Data to Embrace Ambitious Clean Air Targets - Mr. Lindelani Munyadziwa (South Africa)
Presented by: Mr. Lindelani Munyadziwa, Specialist Air Quality Monitoring and Modeling, City of Johannesburg E: lindelanibramleym@joburg.org.za

With urbanization and industrialization on the rise, cities worldwide are facing unprecedented challenges in combating air pollution and its detrimental effects on public health and the environment. Johannesburg, the economic hub of South Africa, has emerged as a progressive city in tackling air pollution by adopting an innovative approach that leverages Low-Cost Sensor (LCS) data. This abstract explores how Johannesburg utilizes LCS data to embrace ambitious clean air targets, focusing on the city's strategy, implementation, and outcomes.
Johannesburg's approach involves deploying a network of Clarity LCS devices strategically throughout the city, providing high-resolution air quality data in real-time. These sensors measure various pollutants, such as particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), enabling the city to monitor pollution hotspots, identify pollution sources, and assess the effectiveness of mitigation measures.
By leveraging LCS data, Johannesburg looks to develop a much more comprehensive understanding of its air quality landscape. The city's clean air targets encompass a range of initiatives, including the promotion of sustainable transportation via the vehicle emission strategy, low emission zone linked to corridors of freedom, the enforcement of industrial regulations, and public awareness campaigns. The LCS data acts as a crucial tool in evaluating the success of these measures, facilitating evidence-based decision-making and policy adjustments.
Part of what is in the Air Quality Management Plan (2019) for the city, Johannesburg has established a vision which is to achieve acceptable air quality levels in the City. An important part in AQMP was to set out several goals to enhance air quality within the city. One of the goals related to air quality management is to develop and maintain a comprehensive air quality management system. This system encompasses data collection, monitoring, analysis, and reporting to facilitate effective decision-making and evidence-based interventions for improving air quality. Bringing in low-cost sensors supports that goal and they also supplement the already existing continuous monitoring network in areas not monitored for criteria pollutants. LCS enables the deployment of a larger number of sensors, resulting in increased spatial coverage and finer-grained data collection.
Furthermore, Johannesburg's approach prioritizes data transparency and public engagement. Real-time air quality information collected from LCS devices is made accessible to citizens through user-friendly online platforms and in near future, looks to incorporate LCS data into the mobile application for air quality SAAQIS. This fosters public awareness, enables individuals to make informed decisions about outdoor activities, and encourages behavioural changes that contribute to better air quality.
Although the data collected from LCS is not used for regulatory purposes yet , the data helps in building a baseline and creating an understanding of the air quality in the areas monitored ,and the devices play a crucial role in expanding the coverage and accessibility of air quality data, and fostering community participation in addressing air pollution challenges.

Johannesburg's innovative approach in leveraging LCS data to embrace ambitious clean air targets sets an example for other cities grappling with air pollution challenges. Continued efforts to refine and expand the LCS network, along with the integration of advanced analytical tools, will further enhance Johannesburg's ability to achieve its clean air objectives, thus improving the quality of life for its residents and setting a new standard for air quality management.
Fusing small sensors with policymaking: a transdisciplinary approach to measuring urban air pollution - Mr. Seán Schmitz (Germany)
Presented by: Mr. Seán Schmitz, Research Associate, Research Institute for Sustainability, Helmholtz Centre Potsdam E: sean.schmitz@rifs-potsdam.de

The pressures of the Anthropocene require urgent responses from both policymakers and scientists alike. Trapped in a confluence of environmental, social, and economic pressures, cities have become a uniquely difficult environment for policymakers and scientists seeking to address these issues. In Berlin, Germany, new laws have been passed in the past 5 years seeking to transform the city’s mobility infrastructure to be climate neutral and environmentally friendly. Given Berlin’s size, history, and diverse governance structures, these new mobility measures (e.g. new bike lanes, temporary street closures) are typically implemented piecemeal in heterogeneous districts that makes measuring their individual environmental impacts challenging. In this study, several measurement campaigns using low-cost sensors (LCS) were planned and executed in collaboration with policymakers. The LCS were calibrated and the experimental data provided using an open-source, 7-step methodology for maximum transparency (Schmitz et al., 2021). To evaluate the impact of individual mobility measures’ on local air quality LCS were deployed to capture before-after measurements of nitrogen oxides (NOx) and particulate matter (PM). Through the implementation of a new bike lane, cyclists’ exposure to NO2 was reduced by 20%; in another case, the closure of a street to vehicle traffic reduced local air pollution to the levels of the urban background. These results were subsequently integrated by policymakers into their decision-making process when determining the success of each measure.

Poster Presentations

Enhancing Community Participation in Air Quality Management: A leverage on Climate Change and Health Frameworks in Kenya - Dr. Godwin Opinde (Kenya)
Presented by: Dr. Godwin Opinde, Researcher & Lecturer, Kenyatta University E: opinde.godwin@ku.ac.ke

Globally air pollution is associated with millions of premature deaths annually. The management of air quality in developing countries is impeded by insufficient resources due to competing priorities. The campaign on climate change and health priority areas coupled with resource allocation inclined towards them in developing countries has led to development of fairly robust frameworks to enhance community participation in these sectors of the economy. This papers views climate change and health agenda as potential synergy twin enabling air quality management in developing countries. It explores the potential of leveraging on current efforts in climate change and health interventions to enhance community participation in air quality management in Kenya. The paper assesses the existing frameworks for climate change and health management from national to ward level and teases out potential areas of synergy with air quality management efforts in the devolved government dispensation in Kenya. The paper is based on content analysis of review of literature.
Inseparable link between Air Pollution and Climate Change: Cleaning the Air as a Strategy for Climate Mitigation - Dr. Solomon Bililign (United States)
Presented by: Dr. Solomon Bililign, Professor, North Carolina A&T State University E: bililign@ncat.edu

Air Pollution- the leading environmental risk factor for mortality, is cause to 7 million premature deaths and as many as 23 million emergency room visits in 2015. It is a silent killer and expected to get worse. It is given very little attention by policy makers because the death due to Air pollution is not as dramatic and media attention grabbing as those directly linked to climate.
Often called short-lived climate pollutants (SLCPs), particulate matter tropospheric ozone and methane contribute to both the warming of the climate as well as air pollution. Air pollution can significantly affect the water cycle. By reducing solar radiation reaching the earth particulate matter can affects the rate at which water evaporates and moves into the atmosphere. and affect clouds' formation.
Climate change induced hotter summers come with an increase in stagnation events stationary domes of hot air that can cause air pollutants to get trapped and persist in the lower atmosphere. Climate warming causes the Earth to experience more extreme weather, such as heat waves and drought, which can negatively impact air quality as an increase in ground ozone levels. Although they may seem to be two very different issues by reducing air pollution, we also protect the climate.
While air pollution is a universal problem and impacts everyone, the main victims are low-income communities, communities of color and people in low- and middle-income countries. Our work is focused on laboratory measurement of optical and chemical properties of biomass burning emissions from biomass fuels from Africa to understand their impact on climate and health. The populations in African megacities are growing at the fastest rates of all global regions. Africa is projected to have the fastest urban growth rate in the world: by 2050, Africa's cities will be home to an additional 950 million people, and thirteen of the world’s largest twenty megacities will be in Africa by 2100. The acute levels of indoor and outdoor air pollution in Africa have already become the most significant environmental contributor to premature death, outpacing both malaria and HIV with 1.1 million premature deaths in 2019.
The link between air quality and climate change will be discussed and some results of laboratory studies will be presented.

Making Sense of Sensor Data

This session invites abstracts on the topic of understanding air quality sensor data. We look forward to welcoming presenters working on unpacking complex air quality information for the everyday user. What sensor data can be trusted, and what should be used with caution? How do we get useful, actionable data out of low-cost air sensors? What are the best practices for quality control and quality assurance of air sensor data? What kind of data from air sensors should be shared to the general public, and how? These are just some of the questions we hope to address in this session. We also welcome submissions on novel applications of air sensor data including linking sensor data to other data streams.

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Podium Presentations:

Getting useful, actionable data out of low cost sensors in Africa - Ms. Garima Raheja (United States)
Presented by: Ms. Garima Raheja, PhD Candidate at Columbia University E: garima.raheja@columbia.edu

Metropolises in sub-Saharan Africa experience high levels of ambient air pollution, yet remain scarcely measured by reference-grade monitors. Combining insights from many years of data collected by newly established and field-calibrated Purple Air low-cost sensor networks, we apply simple methods such as multiple linear regression, as well as novel more complex methods such as Gaussian mixture regression to develop correction models. We also present the development of a Global Gaussian Mixture Regression model.
Preliminary study of in-car air pollution using optical particle counters - Dr. Bertrand Tchanche (Senegal)
Presented by: Dr. Bertrand Tchanche, Assistant Professor at Alioune Diop University E: bertrand.tchanche@uadb.edu.sn

In past decades, a surge in vehicle imports has been witnessed in almost all African countries. These vehicles are old and use low quality fuels, producing significantly higher tailpipe emissions than newer car. Most roads are unpaved or poorly maintained adding further emissions due to resuspension of road dust due to wind and vehicle movement. On the other hand, traffic congestion has become an issue in most megacities, adding to already worsening air quality caused by industrial and domestic emissions. Available literature on traffic related air pollution has mostly focussed on dispersion of traffic exhausts, besides discussing contribution from tyre wear and road conditions. However, there is a lack of studies on personal exposure of drivers and passengers to air pollution. Personal exposure of individuals depends on the time spent in different microenvironments and level of pollution in each microenvironment. If we focus on travel mode, personal exposure of drivers and passengers can vary significantly by the mode: motorbikes, cars, buses, taxis, local trains etc., and the route taken by each journey, indicating temporal and spatial variations in exposure to air pollution. In this study, we present first results of an ongoing evaluation of air pollutants concentration in various transportation systems. A set of instruments including a Particles Plus 8301-AQM1 Series handled particle counter, an IQAir AirVisual Pro, and a temtop M2000 2nd are used to measure PM, CO2, and TVOC concentrations. Several means of transportation including horse carriages, motorbikes, taxis, and minibuses were examined along with their itineraries in the city of Thiès in Senegal. During this first phase, other sources of pollutants unexpected were identified including maintenance of vehicles, open burning of solid waste on roadsides, infiltration of exhaust inside vehicle cabins, dusty seats, etc. Unregulated and congested traffic could increase the exposure duration specially at roundabouts or on congested roads. In-vehicle levels of concentrations higher than the outside levels, suggesting increased exposure risk of drivers and passengers. The situation may be critical in crowded minibuses carrying sensitive and vulnerable population groups (children elderly, pregnant women, and those with existing health conditions).
PM2.5 levels in an unstudied area of rural Ghana using relatively low-cost sensors - Dr. Solomon Otoo Lomotey (Ghana)
Presented by: Dr. Solomon Otoo Lomotey, University of Environment and Sustainable Development, Somanya E: solomotey@uesd.edu.gh

Exposure to PM2.5 is the leading cause of air pollution-induced deaths globally. The use of relatively low-cost sensors has shifted the paradigm in the last decade for monitoring PM2.5 pollution in regions previously difficult to monitor. This is of specific importance in low-and middle-income countries because of the limited evidence of PM2.5 pollution, a prerequisite for PM2.5 management and control. In low- and middle-income countries such as Ghana, PM2.5 monitoring is very limited due to the cost of running regulatory monitors and the lack of human capital. In this study, we aim to establish the transferability of correction factors developed using relatively low-cost Airnote PM Monitors for their utility in a homogenous environment. We use data from a relatively low-cost Airnote PM installed at the University of Environment and Sustainable Development (UESD) campus, Somanya (a mango-vegetated area), in the Eastern region of Ghana, from March 2023 to May 2023, for monitoring PM2.5. A correction factor developed using the same monitor for collocation work at the University of Ghana was applied to correct the raw PM2.5 values. PM2.5 values increased (from 15 to 50 µg/m3) in March, possibly linked to harmattan, and decreased (from 30 to 14 µg/m3) in April, reaching their lowest points (from 20 to 15 µg/m3) in May. Strong diurnal changes in PM2.5 levels were observed in all months, suggesting that April's rains may have influenced the substantial decrease in PM2.5 levels. The daily variations of temperature, relative humidity, and PM2.5 data that were acquired from the sensor, respectively, were subjected to Lomb-Scargle periodogram analyses. Our findings indicate the presence of oscillations with periods (in days) ranging from 2 to 10 days. It implies that there is a coupling dynamic between these pollutants and the winds carrying these pollutants which needs to be investigated. The observed PM2.5 values exceeded 15 µg/m3, which is the WHO 24-hour average Air Quality threshold, during 61% of the reported data. The findings from this preliminary work are useful for air pollution management and control using relatively low-cost sensors in environments previously unmonitored with limited capabilities, as observed in wider swaths of Ghana and Africa.

Poster Presentations

Hardware Measures, Software Models - Dr. Sebastian Diez (Argentina)
Presented by: Dr. Sebastian Diez, Researcher, Universidad del Desarrollo E: sebastian.diez@york.ac.uk

Sensor technologies, widely deployed for environmental monitoring, are fundamentally governed by hardware and software systems. While hardware limitations are well documented, software-based adjustments remain largely unexplored and can make data interpretation difficult. In an era dominated by Big Data and AI, this study underscores the need for transparency in the underlying data generation process (DGP), especially in sensitive areas such as air quality decision-making. Despite the appeal of software solutions, we argue that the focus should be on improving the measurement-driven nature of sensor data by improving the quality of hardware. The commercial sensor industry is faced with the dilemma of balancing proprietary rights, transparency, and data quality. In light of these challenges, we advocate for more detailed information on data manipulation processes and the availability of raw data. In particular, the deployment of sensor technologies in the Global South requires a careful approach to ensure the quality and representativeness of the data, without imposing external solutions. As such, the scientific community plays a crucial role in developing capacities and promoting practices that are respectful of local contexts. Ultimately, transparency in sensor PGDs is critical to building trust, cultivating healthy competition, and generating data that can drive decisions to improve people's quality of life.

Utilizing Various Communication Strategies to Increase Public Engagement on Air Pollution

Air pollution is an important environmental health concern in Africa. As data and evidence becomes more readily available, it is crucial to increase public engagement and awareness and encourage action, both at the individual and societal levels. Effective communication strategies are essential to achieve this goal. Utilizing various communication strategies can help to raise awareness about the health impacts of air pollution and inspire people to engage and take action. These strategies can include social media campaigns, community outreach programs, and public education initiatives. Often, the information also needs to be accessible and easy to understand, using clear language and visuals. Importantly, the strategies also need to be tailored to specific audiences to ensure that they are effective.

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Podium Presentations:

Role of Journalism in increasing Public engagement on Air Pollution; Insights from EJN media Workshop in Nairobi - Dr. Jackline Lidubwi (Kenya)
Presented by: Dr. Jackline Lidubwi, Project Coordinator, Internews Network E: jlidubwi@internews.org

Air pollution is an important environmental health concern in Africa. As data and evidence becomes more readily available, it is crucial to increase public engagement and awareness and encourage action, both at the individual and societal levels. Effective communication strategies are essential to achieve this goal. Utilizing various communication strategies can help to raise awareness about the health impacts of air pollution and inspire people to engage and take action. These strategies can include social media campaigns, community outreach programs, and public education initiatives. Often, the information also needs to be accessible and easy to understand, using clear language and visuals. Importantly, the strategies also need to be tailored to specific audiences to ensure that they are effective.

This abstract highlights a media workshop organized by Internews' Earth Journalism Network (EJN) in collaboration with the Clean Air Catalyst project consortium, funded by the U.S. Agency for International Development (USAID), on the topic of air pollution in Nairobi, Kenya. The workshop aimed to enhance reporting on air pollution and its impacts, addressing the significant threat it poses to human life and the environment.
The World Health Organization (WHO) estimates that approximately 7 million people die each year due to indoor and outdoor air pollution, with 99% of the global population residing in areas where air quality often falls below recommended guidelines. Recognizing the urgency of this issue, the media workshop titled "Air Pollution in Kenya: Sources and Impacts" was conducted from May 8-10 in Nairobi, with the participation of 30 journalists representing various local, national, and international media organizations.
The workshop brought together journalists from different beats and news platforms, including business dailies, environmental magazines, radio stations, and broadcast television. The participants, comprising both full-time and freelance journalists, received training on understanding the sources and impacts of air pollution in Kenya. Notably, gender diversity was also emphasized, with approximately half of the participants being women.
By providing journalists with essential knowledge and skills related to air pollution, this workshop aimed to empower them to report effectively on this critical environmental issue. Ultimately, the goal is to raise awareness, stimulate public discourse, and drive positive action to mitigate the impacts of air pollution in Nairobi and beyond.
Youth-driven citizen science for healthy climate resilient cities - Dr. Monika Kamkuemah (South Africa)
Presented By: Dr. Monika Kamkuemah, Postdoctoral Fellow, University of Pretoria E: monika@urbanbetter.science

Climate change has far-reaching impacts on public health, and addressing the challenges associated with climate change requires a comprehensive understanding of its implications on human well-being. Air pollution specifically stands out as a pressing issue within the climate and health framework. Poor air quality has severe health implications, affecting respiratory health, cardiovascular well-being, and overall quality of life. Air pollution and the food and built environments are key pathways that influence climate and population health and shape planetary health risks. By focusing on air quality, the built environment and health, we can develop effective strategies to mitigate the adverse effects of climate change on public health and promote sustainable development. Furthermore, rapid urbanisation and a young population present an opportunity for transformative action in African cities. However, there has yet to be a cohesive youth-led movement for clean air due to factors such as normalisation of pollution and limited access to air quality data.

By integrating climate and health advocacy and research, we can foster synergies, leverage expertise from both domains, and develop comprehensive solutions that address the intertwined challenges of climate change and public health. UrbanBetter conducted a proof of concept pilot (the Cityzens4CleanAir campaign) showing that wearable sensors can be an effective tool for advocacy, generating government engagement, media interest, and engaging youth on the topic of air quality in three African cities. The first phase of the Cityzens for Clean Air (C4CA) campaign ran from July to November 2022 in Cape Town, Lagos and Accra and at COP27. Building on this success, UrbanBetter is now in operations to institutionalise youth participation in air quality management by embedding these wearable campaigns more deeply in Lagos and Accra and developing the training materials and digital infrastructure to enable more wearables campaigns in more places. In this talk, we will demonstrate our approach and achievements to date as we scale up this intervention.
Communicating air sensor data: co-designing visualisations through the Breathe London Community Programme - Dr. Kayla Schulte (United Kingdom)
Presented by: Dr. Kayla Schulte, Imperial College London E: k.schulte21@imperial.ac.uk

This project contributes to the growing literature surrounding how participatory methods can support community-led air quality sensing projects and environmental knowledge exchange. It presents the methods and findings from a participatory workshop held for the Community Programme branch of the Breathe London project. Breathe London is the world’s first real-time calibrated air sensor network delivering high quality, freely available PM2.5 and NO2 data at over 400 locations across London, UK. The Community Programme has awarded free sensors to 40 different groups across London, whose applications were selected by an independent panel of judges who work in the air quality action arena.

The workshop brought together residents and groups taking part in the Breathe London Community Programme, alongside data scientists to co-design visualisations using data from their Breathe London nodes. The aim was to generate visualisations that were effective at communicating air quality trends to non-specialist audiences. The approach adopted in the workshop is rooted in science and technology studies (STS), specifically the theoretical concepts of coproduction and materiality. These concepts reinforce the potential for co-created visualisations to simultaneously materialise data from air sensors, alongside the vast knowledge and context held by the Community Programme members.

The outcomes of the workshop are presented and reviewed in terms of their success at effectively communicating air quality trends to different audience groups identified by the Community Programme members. We conclude with recommendations for future collaborative air quality visualisation endeavors.
Enabling participatory approaches to co-designing of air quality management solutions: The AirQo Experience - Ms. Maclina Birungi (Uganda)
Presented by: Ms. Maclina Birungi, Marketing Communications Lead, AirQo E: maclina@airqo.net

Air pollution remains a major environmental health issue accounting for over 7 million deaths per year according to the World Health Organisation. Moreover, there is still a shortage of access to evident air quality data and awareness of the magnitude of air pollution at a grass root level. Tackling the air pollution challenge requires a multifaceted approach that involves engaging all key stakeholders including grassroots communities, yet this is still a limitation.

Participatory approaches to co-designing of air quality management solutions can foster transformative change among grassroots communities by bringing to light the knowledge, focus and power that rests untapped among community voices.

Through understanding the perceptions and attitudes of community members towards air quality issues, there is potential to establish a solid knowledge base that provides a snapshot of the state of air quality affairs in terms of knowledge gaps, available air quality interventions, perceived health risks, perceived roles of who is primarily responsible for addressing air quality in the community and the best means to communicate air quality data and how this data can be interpreted by a layman person thus unravelling the untapped potential among grassroots community members in enhancing participatory air quality management.

We demonstrate that participatory community involvement through knowledge sharing enhances transformative education and awareness raising of air pollution and its effects in formal, informal and non-formal spaces. Furthermore, engaged community members also tend to be more receptive to air pollution communication messages and voluntarily become advocates/champions of cleaner air at the grassroots level using data and evidence.

Poster Presentations

Role of Researchers and Communication Experts in the transfer of knowledge relating to air pollution: Mastery of the knowledge transfer process - Dr. Robert Mbiake (Cameroon)
Presented by: Dr. Robert Mbiake, Professor, Université of Douala E: rmbiake85@gmail.com

The obvious and serious threat of air pollution urgently requires the transfer of knowledge acquired in laboratories to the populations most concerned, to reduce its impact and make the object of scientific research useful. This work can only be done by clarifying the field of competence of the various stakeholders in the chain, which is made up of three essential links.
-   Scientific researchers in search of the truth about air pollution and of observed facts;
-   Communication researchers looking for techniques and tools to simplify communication, using terms understandable by all from the results obtained by scientists;
-   Communication experts who already have since their basic training, the language and the approach necessary for a fluid exchange with the populations (Journalists and influencers).
In our presentation, we try to define the competence field of the different links in the chain and the bridge that allows them to move from one link to another.

Keywords: Air pollution - knowledge - Transmission - Use
Air quality data collection, analysis and interpretation - Mr. Nsikak Charles (Nigeria)
Presented by: Mr. Nsikak Charles, Tropical Research and Conservation Center E: israelcharles0808@gmail.com

In recent years, the quality of air has become a growing concern due to its significant impact on human health and the environment. To effectively address this issue, robust data collection, analysis, and interpretation methods are crucial. This abstract provides a comprehensive overview of the processes involved in gathering, analyzing, and interpreting air quality data. The first step in the data collection process involves the deployment of monitoring stations strategically placed in various locations to capture a representative snapshot of air quality. These stations employ a range of sensors to measure key pollutants such as particulate matter (PM), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and sulfur dioxide (SO2). Data collected from these sensors is recorded at regular intervals, forming a continuous stream of information. Data analysis in air quality studies often involves exploratory data analysis (EDA), correlation analysis, regression modeling, and machine learning algorithms. These techniques help uncover relationships between pollutant levels and various factors, such as meteorological conditions, traffic patterns, and industrial emissions. Advanced machine learning models can be developed to predict future air quality based on historical data, providing valuable insights for decision-making and policy formulation. Ultimately, the comprehensive process of data collection, analysis, and interpretation of air quality data plays a vital role in understanding the dynamics of air pollution and formulating effective strategies to mitigate its adverse effects. By leveraging the affordability, scalability, and accessibility of LCS, it becomes possible to establish comprehensive air quality monitoring networks that cover larger areas. However, it is essential to address quality assurance, data management, and interpretation challenges to ensure the reliability and effective utilization of LCS data in Africa cities.

Adapting Low Cost Sensors for smart air quality monitoring in African Cities

Achieving a high resolution air quality network using conventional air quality monitoring is not practical because of the prohibitive costs. Low-cost sensors have the potential to close the air quality data gaps in data hungry countries such as those in the global South, but establishing a stable data pipeline from sensor networks for continuous monitoring is impeded by unique environmental and infrastructural challenges. Data transmission, availability and reliability are particularly constrained by internet connectivity, unreliable power supply, environmental factors such as dust, rain, humidity, uniquely specific to many African countries. Developing custom-sensor platforms tailored to the unique conditions of the global south is a critical step towards bridging the data gaps. This session aims to highlight the practical considerations of setting up a sustainable data pipeline for low-cost sensor platforms, while highlighting the successful case studies of moving from ‘sensors to data’.

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Podium Presentations:

Low-cost Sensors Development and Deployment - Mr. Gideon Maina (Kenya)
Presented by: Mr. Gideon Maina, Senior IoT Engineer, sensors.AFRICA, Code for Africa E: gideon@codeforafrica.org

Air pollution is a growing environmental challenge in urban areas globally. Among the affected areas are in Sub Saharan Africa, where outdoor air pollution is responsible for approximately 49,000 deaths annually (World Bank, 2012). In response to this, researchers, civic groups and local governments have embarked on air quality monitoring programmes. Reference grade monitors, which tend to be very costly, pose a challenge for interested parties due to limited resources available within the region. This has led most parties to opt for low cost air-quality monitors in the affected areas. The low cost monitors offer an opportunity to get real time data that can help in the campaign to reduce air pollution.

The operations of these monitors, however, face various challenges including haphazard power supply and unreliable wifi connectivity. This calls for alternative approaches to be adopted in developing monitors. As a result of this, it is necessary to explore alternative sources of power and network service providers to guarantee consistent and constant data collection. This is especially important when doing air quality monitoring in low income areas and public spaces.

As such, the installation of traditional low-cost sensors will require the use of alternative sources of power and network solutions. Among the alternative technologies that have been explored include use of solar panels and batteries as power sources. Researchers and technologists select the wattage of the solar panels depending on the number of sensors incorporated and overall power consumption of the interfaced system. The current draw for a typical low-cost particulate matter sensor ranges from 50mA to 200mA. When a GSM module is incorporated for transmission of real-time data, an extra battery and higher-wattage solar panel may be necessary due to frequent transmission power bursts reaching 2A. All solar panels require a battery with an acceptable capacity up from 10,000mAH, which can cater for the energy demands for at least a day; this however is subjective to the use-case. Applications that do not need real-time data have lower energy requirements, and a memory card can be used to log data that is sent at certain intervals, such as hourly or half daily. Case studies of these can be seen in the sensors.AFRICA outdoor air quality monitor and indoor air quality monitor respectively.

Additionally, NB-IoT, LTE-M, LoRa and Sigfox offer reasonable alternatives for network provision. They fall under the category of Low-Power Wide Area Networks (LPWAN). NB-IoT is a subset of LTE that uses a narrow band of 200kHz designed for low-power network applications. This standard uses less bandwidth than the designated/stipulated bandwidth for that channel. Therefore, it is suitable for real-time data transmission due to its relatively low latency. LoRa, on the other hand, is a low-power wide area network standard that offers a longer range than NB-IoT. On top of that, it guarantees a longer battery life, which adds to the solutions surrounding power issues. Sigfox is also a worthy alternative to LoRa as it offers extended range and leverages on an existing network.
AirQo sensor kit: an air quality sensing kit custom designed for low-resource settings - Mr. Deo Okedi (Kenya)
Presented by: Mr. Deo Okedi, AirQo E: deokedi@airqo.net

Air pollution remains a major public health risk. People living in urban spaces are among those most affected by exposure to unhealthy levels of air pollution. Yet many urban spaces especially in low- and middle income countries lack high resolution and long term data on the state of air quality. Without high resolution air quality data on the different spaces in a city, citizens and authorities are unable to quantify the challenge and take action. This is in part attributed to the high cost of air quality monitoring equipment that are expensive to set up, maintain and not design for local operating conditions that characterize environments in such contexts. In this paper, we describe AirQo sensor kit, a low-cost sensing hardware designed for and custom designed to work in low-resource settings and outdoor urban environments. We describe the design of the air quality sensing device, 3D-printed enclosure, installation-mount, fabrication and deployment configurations. We demonstrate that the low-cost sensing hardware provides a complete solution comparable to the traditional monitoring system and inspires action to tackle air pollution issues. The sensor kit presented in this paper has been widely deployed in cities in Eastern, Western and Central African countries.
The Lifecycle of Low-Cost Sensor Networks for Air Quality Data in African Cities - Mr. Usman Ahmed (Nigeria)
Presented by: Mr. Usman Ahmed, Hardware Engineer, Code for Africa E: usman@codeforafrica.org

The use of low-cost sensors (LCS) has emerged as an affordable and accessible solution for air pollution monitoring, addressing the limited access to reference-grade monitors in African cities. These sensors play a crucial role in bridging the data gap.However, in order to establish practical and reliable air quality sensor networks in African cities, it is essential to consider the unique conditions faced on the continent throughout their lifecycle

Selection of suitable LCS involves considering factors like specific parameters to be measured, power sources, data storage/transmission capabilities, and local weather conditions. During deployment, careful site selection is necessary to ensure restricted access and prevent vandalism. For solar-powered sensors, optimal placement with direct exposure to sunlight is crucial. Sensors must be positioned in areas where readings are not influenced by immediate environmental factors, e.g. placing air quality monitors away from pollution sources, but in areas with free air flow ensures accurate representation of ambient air quality.

Maintenance of sensor networks is vital and typically requires the expertise of an engineer; it can be facilitated by empowering volunteers with basic training. This highlights the importance of community ownership and involvement in the sensor network to ensure long-term sustainability. LCS degrade overtime and require replacement to ensure high-quality data. Availability of parts for replacement and repairs is critical, emphasizing the need to manufacture sensor kits within Africa for accessibility.

By incorporating these considerations, African cities can utilise LCS networks for air pollution monitoring that provides actionable data to address environmental challenges & promote public health.

Poster Presentations

A Sensor Evaluation Centre for Africa: Afri-SET - Dr. Allison F. Hughes (Ghana)
Presented by: Dr. Allison F. Hughes, Professor, University of Ghana E: ahughes@ug.edu.gh

Despite their many drawbacks, the use of low-cost sensors is an essential part of reaching any country’s air quality management goals. This is especially true in Africa where reference-grade air quality measurements are uncommon. Therefore, confidence in the use of (and resulting data from) low-cost sensors is paramount for air quality practitioners, policy-makers, and ordinary individuals alike. The Sensor Evaluation and Training Centre for West Africa (Afri-SET West) is a new facility dedicated to address these issues. This presentation provides an overview of the services offered at Afri-SET: low-cost sensor evaluations against reference-grade monitors in an urban West African setting, open-access per-model low-cost sensor calibrations, in-person and virtual training sessions, and a number of data hosting services especially to aid in the creation of value-added products from low-cost sensor data. We will also cover the protocols used at Afri-SET and present some of the first results of low-cost sensor evaluations from the facility. This presentation is sister to the live tours of the Afri-SET facility occurring at ASIC Ghana.
Design, testing and cost analysis of low-cost air quality monitoring systems - Dr. Jacob Mbarndou (Cameroon)
Presented by: Dr. Jacob Mbarndou, Research Scientist, Research Centre for Nuclear Science and Technology, Institute of Geological and Mining Research, Yaoundé, Cameroon E: mtjfirst@yahoo.fr

More Africans than in the past are living in cities, where atmospheric pollution reaches high levels. Exposure to air pollution can lead to a wide range of diseases: asthma, headaches, stroke, lung cancers, etc. In a context of long-term exposure, air pollutants can affect every part of the body. Fine particles have been recognized as a leading cause of several diseases including cancer. However, data on atmospheric pollution are still scarce in African cities due to the lack of monitors, the high upfront cost of standard monitors being an obstacle. However, low-cost IoT components owing to their features are bringing hope. In the framework of the IoT4AQ project, investigations are being carried out to develop inexpensive and climate adapted monitors. Local parameters including dust concentration levels, weather data, communications systems, and electrical grids have been analysed. IoT components including LCD screens, LEDs, RTC modules, GPRS modules, microcontrollers (Arduino, Raspberry Pi, ESP32, etc.) and various sensors (dust, gas, temperature, relative humidity, etc.) available on the market were assessed to evaluate their cost-effectiveness. Geolocation, data storage and autonomous operation options were studied. Basic designs obtained include Arduino Mega 2560/GPRS/PMSDS011 and ESP32/Wi-Fi/PPD42NS. These basic configurations were tested in the lab to map their performance. They displayed low energy consumption, low cost (~€120), light weight (~200 g) and could accommodate more parameters. Next steps will be the performance comparison with market available low-cost sensors and integration of gas sensors and battery for autonomous operation.

Keywords: air pollution, low-cost sensors, IoT devices
AirQo sensor kit: an air quality sensing kit custom designed for low-resource settings - Mr. Joel Ssematimba (Uganda)
Presented by: Mr. Joel SSematimba, Hardware Development and Manufacturing Lead, AirQo E: joel@airqo.net

Air pollution remains a major public health risk. People living in urban spaces are among those most affected by exposure to unhealthy levels of air pollution. Yet many urban spaces especially in low- and middle income countries lack high resolution and long term data on the state of air quality. Without high resolution air quality data on the different spaces in a city, citizens and authorities are unable to quantify the challenge and take action. This is in part attributed to the high cost of air quality monitoring equipment that are expensive to set up, maintain and not design for local operating conditions that characterize environments in such contexts. In this paper, we describe AirQo sensor kit, a low-cost sensing hardware designed for and custom designed to work in low-resource settings and outdoor urban environments. We describe the design of the air quality sensing device, 3D-printed enclosure, installation-mount, fabrication and deployment configurations. We demonstrate that the low-cost sensing hardware provides a complete solution comparable to the traditional monitoring system and inspires action to tackle air pollution issues. The sensor kit presented in this paper has been widely deployed in cities in Eastern, Western and Central African countries.
Design and Development of Indoor Occupancy Sensors for Enhanced Energy Conservation in University of Lagos, Akoka, Lagos, Nigeria - Mr. Manessah Shitta (Nigeria)
Presented by: Mr. Manasseh Shitta, Research Officer, National Centre for Energy Efficiency and Conservation (Energy Commission of Nigeria), University of Lagos, Akoka, Nigeria E: mbshitta@gmail.com

The importance of energy efficiency in the ever-growing cost of energy cannot be over emphasised. The Demand side of the electricity if not properly managed either using technology or developing attitudes that may results in reducing energy consumption, the cost would keep growing. Like any institution of learning, the energy demand of University of Lagos is increasing by the day. This is evident in the energy consumption of this great institution. The increase in energy consumption is traced to wastage because of unwholesome behaviors of occupant of the buildings within the institution. There is need to reduce electricity consumption by reducing wastages in lighting spaces, walk-ways, and backyards through design and development of motion and occupancy sensor switch to reduce electricity wastages. This work utilises pyroelectric infrared (PIR) sensor, effect transistors, capacitors, diode resistors and lithium-ion battery as backup. These components where assembled and packaged using soldering ions. The device developed accepts a range of voltage between 220 to 250 V from the source while the device is in turn connected to a lamp source and regulates the powering on and off the lamp to reduce human interference in switching which is often forgotten. This is demonstrated and it was observed that the device would enhance the performance of buildings by reducing the number of times lamps are left ON while there is no occupant. This calls for policy towards development of these devices to improve availability of research equipment in Africa.
Development of a Correction Model for Low-Cost Sensors for Ambient PM2.5 Monitoring in the City of Mombasa - Mr. Moses Njeru (Kenya)
Presented by: Mr. Moses Njeru, Air Quality Researcher, University of Nairobi E: moses.njeru@uonbi.ac.ke

The paucity of surface measurements of fine particulate matter (PM2.5) limits estimates of air pollution mortality in Sub-Saharan Africa. If well calibrated, low-cost sensors have the potential to provide reliable data especially where reference monitors are unavailable. We evaluate the performance of Clarity Node-S PM sensors against a Tapered element oscillating microbalance (TEOM) and develop a calibration model for sensor correction in Mombasa. Raw Clarity Node-S data from January 2023 through April 2023 was moderately correlated with the TEOM-1400a measurements (R2=0.61) but also exhibited a mean absolute error (MAE) of approximately 7.03 µg m–3. Employing three calibration models, namely, multiple linear regression, gaussian mixture regression (GMR) and random forests (RF) decreased the MAE to 4.28, 3.93, and 4.40 µg m–3 respectively. The R2 score improved to 0.63 for the MLR model but all other models registered a decrease in precision (R2=0.44 and 0.60 respectively).
Characterizing PM2.5 levels in Basic schools network of Purple Air (PA) monitors in rural communities in Ghana - Mr. Mujtaba Mohammed Nuhu (Ghana)
Presented by: Mr. Mujtaba Mohammed Nuhu, Senior Health Research Officer, Kintampo Health Research Centre E: mohammed.mujtaba@kintampo-hrc.org

Ambient air pollution data are lacking in resource limited countries. Low cost sensors (LCS) are being promoted to fill this gap but primarily for cities. We report on a school-based LCS network for rural communities. Our objectives were to augment exposure assessment in the context of an ongoing study examining child lung development trajectories in the Ghana Randomized Air Pollution and Health (GRAPHs) cohort and assess the feasibility of school-based monitoring in rural resource limited communities. The network consists of Purple Air SDII (PA) monitors at the Kintampo Health Research Center (KHRC) and the primary school location within each community (currently 31 of 35 GRAPHs communities). For power and security, the PAs were normally deployed outside of the head teacher’s office. The PA data was adjusted using a calibration factor developed through a long-term colocation of PA sensors with a reference grade monitor Beta Attenuation Monitor (BAM) in Accra. Average daily PM2.5 concentrations (Mean; SD) were higher during the Harmattan season (73 ug/m3; 23) compared to the non-Harmattan season (33 ug/m3; 38). In the Harmattan season, across all sites, more than 50% of daily averages exceeded the WHO target. Preliminary analysis found no significant differences in concentrations between schools that cook lunch on site and those that do not. Problems encountered include data gaps due to theft of SD memory cards and unreliable power, the latter resulting in pivoting to 3 solar powered deployments and 4 deployments in other parts of the community. School-based monitoring with LCS appears to be a promising approach to measuring ambient concentrations in rural communities. Calibration of LCS in rural settings remains a central challenge.
NILU’s Sensor Data Infrastructure: Innovative Management of Air Quality Sensor Networks - Dr. Nuria Castell (Norway)
Presented by: Dr. Nuria Castell, Senior Scientist, NILU - Climate and Environmental Research Institute E: ncb@nilu.no

Sensor networks have the potential to provide air quality data with high temporal and spatial resolution, but the generated data are often of questionable quality, limiting their uptake by authorities. To address this challenge, NILU developed a Sensor Data Infrastructure (NSDI).
NSDI includes automated algorithm-based methods for calibration and quality assurance and data assimilation methods for merging sensor data with other already existing data, for instance, air quality models. NSDI web-based solution allows easy data visualization, network management, and downloading files. Access to the data can also be done through a REST API (an Application Programming Interface that conforms to the design principles of the REST, REpresentational State Transfer architectural style) interface. NSDI is built following a scalable approach to handle large amounts of heterogeneous data, allowing to handle increasing computational requirements cost-effectively. The infrastructure is built to be sensor agnostic, and is currently handling data from different sensor manufacturers, as well as non-commercial sensors. This enables the integration of relevant air quality data from various sources to determine air quality at a particular location and time. Currently, the NSDI serves municipalities and community science projects in Norway, Denmark, Sweden, Finland, and Poland. NILU has also developed laboratory and field calibration routines to increase data quality. Data from sensor co-location against reference instrumentation is used in machine learning algorithms to improve data quality. Data correction and calibration are two-folded, automatic algorithms are implemented to operate in real-time in the sensor data infrastructure, but also more sophisticated corrections are done a posteriori. Automated algorithms allow us to present the data to the public in real time, while posterior expert-based corrections allow us to decrease uncertainty when using the data in publications.
Assessing the Spatial Transferability of Calibration Models across a Low-cost Sensors Network - Mr. Vasudev Malyan (India)
Presented by: Mr. Vasudev Malyan, PhD Scholar, Indian Institute of Technology Bombay E: malyanvasudev@iitb.ac.in

Networks of low-cost sensors (LCS) are expanding around the globe to gather high spatiotemporal data owing to their economic feasibility, and compact size. In this study, we investigated the spatial transferability of the calibration models developed using ML algorithms for a network of APT-MAXIMA LCS installed in Delhi. The site-specific calibration models perform well at each site with high R2 and significantly low RMSE values compared to the uncalibrated LCS measurements. These models were transferred to the other sites and their performance was evaluated based on the EPA sensor evaluation criterion (R2 ≥ 0.70). We also investigated the effect of distance between the sites (D), source composition, PM ratios, and particle size distribution (PSD), on the performance of calibration models. The models developed at the Mundka (S10) and Punjabi Bagh (S16) sites complied with the evaluation criterion for each site irrespective of the distance between the sites. Additionally, it was found that it is not necessary for models developed at two different sites to be inter-transferable. Categorical calibration of LCS based on the site background viz. commercial, industrial, and residential, indicated the importance of source mixture on the performance of calibration models. The PM Ratios (PM1/ PM2.5 and PM2.5/PM10) reported by the APT-MAXIMA sensors did not vary across sites indicating that the algorithm used in the PMS5003 modules cannot truly apportion the PM1/PM2.5/PM10 mass fractions but provides a proxy of these measurements through inbuilt algorithms. Evaluation of the PSD at different sites supported our findings. We also introduced the concept of choosing representative locations for deployment of reference monitor to conduct collocation studies and develop the calibration models for LCS. The sites were clustered based on the performance of transferable models and a reference map was produced using interpolation for Delhi. In order to get the best transferability within the network, hotspots were identified to develop calibration models. This work is useful for monitoring agencies, especially in countries with sparse network of monitors, as it serves as a collocation guide to calibrate a network of LCS.
Performance evaluation of low-cost Atmotube sensors for air quality measurements - Ms. Aishah Shittu (United Kingdom)
Presented by: Ms. Aishah Shittu, University of Leeds E: eeais@leeds.ac.uk

My focus is on particulate matter (PM2.5) parameter. The study involves the colocation of multiple Atmotubes low-cost sensors using several metrics to assess intra-sensor variability and how well these sensors measurements compare with a nearby reference grade instrument.
Sensing the city: The why and how of sensor network operation and data for mapping multiple air pollutants (and noise pollution) in sub-Saharan Africa - Dr. Raphael E. Arku (United Kingdom)
Presented by: Dr. Raphael E. Arku, Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts E: rarku@umass.edu

Cities in sub-Saharan Africa (SSA) are in economic transition and undergoing significant expansion. With the rapid growth, SSA cities are experiencing high levels of air pollution from diverse sources. In Additionally, environmental noise pollution is becoming a major public health concern in cities. Yet, there is a dearth of robust city-wide data for understanding space-time variations and inequalities in emissions and exposures, which is essential for evidence-based policies to create accountability towards equitable urban living.

Using a network of low-cost sensors, we have developed consistent and transferable protocol for generating rich environmental data in SSA cities. We showcase an extensive environmental measurement campaign, which has illuminated the patterns and dynamics of environmental quality in Accra, one of the fastest growing SSA cities. With this approach, we were able to map out at fine spatial (50 - 100 m) and temporal (daily - weekly) resolution multiple air pollutants, including ambient PM2.5, black carbon (BC), and oxides of nitrogen (NO and NO2), as well as environmental noise levels in to inform policy evaluation and climate and health impacts assessment in SSA context.

The data show significant disparity in pollutant concentrations across land use factors and socioeconomic gradient, with residents in the poorest communities and those in the inner-city core at higher risk of exposure. Further, we show that the entire population in Greater Accra Metropolis is exposed to air quality levels above local and international health-based guidelines.

Our innovative approaches to data collection and analytics using low-cost sensors can help track inequalities in SSA cities and their environment over space and time and can identify and support deprived and marginalised groups, and to create accountability towards equitable urban development.
Validating the reproducibility and reliability of data collected by Purple Air and Temptop 1000 series low-cost monitors in ambient air quality studies - Dr. Paul Njogu (Kenya)
Presented by: Dr. Paul Njogu, Senior Research Fellow, Jomo Kenyatta University of Agriculture and Technology E: njogupaul@jkuat.ac.ke

The use of Low-cost air quality monitors (LCM) has become common in African cities for ambient air monitoring. This has been necessitated by the high costs of the deployment and operation of reference monitors. The accuracy and reproducibility of the data generated by different low-cost monitors is imperative for comparability and reliability. This is important where two different monitors are used which normally is the case. This study was undertaken to compare the data collected by a Purple Air Monitor (PAM) and Temptop (TMTP) 1000 Airing model from the United States of America. The two monitors used deployed side by side and exposed to similar ambient air conditions. Measured values of humidity, temperature, Pm10 and Pm2.5 were recorded every from the Temptop whereas Purple Air data was extracted from the SD card after the sampling period. Data from PA was analyzed averaged for the two laser sensors and compared with that generated by Temptop. The study found agreement in all PM2.5 levels measured at 99% confidence level whereas the PM10 showed no significant difference at 95% confidence level. Variations were noted for Temperature and humidity recorded by the two sensors though not significantly different at p=0.05. The study reveal that the two monitors can be used interchangeably with the TMTP providing more accurate measurements. The average data correction factor based on colocation with a BAM monitor was 0.2 and 0.3 for TMTP and PA respectively.
Air Pollution Control using a Homemade Non-Thermal Plasma Technology - Dr. Prince Asilevi Jr. (Ghana)
Presented by: Dr. Prince Asilevi Jr., Researcher, Regional Water and Environmental Sanitation Centre Kumasi, Department of Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana E: ev_asilevi@yahoo.com

This poster presentation focuses on the development of a homemade laboratory-scale dielectric barrier discharge (DBD) system for air pollution control. The research explores the use of non-thermal plasma (NTP) generated by the DBD system to degrade volatile organic compounds (VOCs) present in flue gas. The study investigates the efficiency of the system in removing formaldehyde (HCHO) from synthesised flue gas under different concentrations, simulating both indoor and outdoor conditions. The poster highlights the electrical, chemical, and physical processes involved in generating plasma and optimizing degradation conditions. The results demonstrate a removal efficiency of up to 99% without causing secondary pollution, with ambient oxygen and water vapor playing crucial roles. The findings provide both theoretical and experimental evidence for the feasibility of using DBD NTP for air pollution control.
Characterizing PM2.5 levels in a peri-urban setting in Ghana - Dr. Sulemana Watara Abubakari (Ghana)
Presented by: Dr. Sulemana Watara Abubakari, Kintampo Health Research Centre E: watarazys@gmail.com

Air quality monitoring is slowly expanding in low- and middle-income countries but tends to focus on major urban centers. This presentation will report on a network of low-cost PM2.5 sensors deployed in Techiman, a peri-urban town in central Ghana that is similar to the settings where most of the population growth is expected by 2030. We deployed 24 Purple Air SDII (PA) monitors across schools and hospitals according to a predefined 1km-grid of desired locations. Where a school or hospital location could not be identified, the nearest participant home was used. We also collocated one PA with a Beta Attenuation Monitor (BAM 1022, Met One instrument) and other LCS (Modulair, QuantAQ; Airnote, Blues Wireless) at the Kintampo Health Research Centre office in Techiman. To better understand potential contributing sources, fieldworkers carried out a point-based community emissions survey designed to ascertain the presence (and, if applicable, the distance) of particulate matter-generating activities within 500-meter radius such as commercial cooking and trash burning sites. A quarter of sensors were deployed approximately 1m away from major roads which were all tarred and 75% of sensors were in the vicinity of neighborhoods where cooking activities and/or trash burning sites were present. Hourly PM2.5 concentrations suggest elevated levels in the late afternoon whereas day of the week concentrations do not suggest any distinct pattern throughout the week. Further data analysis is ongoing and focuses on timing and location of polluting sources. Challenges included power supply issues interfering with BAM stable deployment and concerns from students about on-site activities being monitored.
Plastic waste burning in Ghana communities and schools - Dr. Steve Chillrud (United States)
Presented by: Dr. Steve Chillrud, Lamont-Doherty Earth Observatory of Columbia University E: chilli@ldeo.columbia.edu

The burning of solid waste, including plastics, is thought to be a significant source of air pollution emissions in rural and peri-urban communities of Ghana. Community members and school children routinely collect and burn plastic waste at informal trash heaps near households and schools. The open burning of trash is inefficient and can result in smoldering for hours to weeks. In addition, plastic waste is commonly used to ignite fires for household cookstoves. These sources of plastic combustion may produce a toxic mixture of emissions, including phthalates, antimony and microplastics, that could be harmful to those nearby, especially children. We have started testing methods to quantify PM2.5 exposure from trash burning. Two personal PM2.5 samplers were placed about ~3-4 meters from a smoldering trash heap (~2m in depth) located in a community member’s backyard along a ravine. Samplers were positioned ~2m above ground, placed ~30m apart and safeguarded from rain using a customized rainhat, consisting of a 4-inch PVC pipe with 1.5-cm holes drilled and a 3D printed roof, attached with a hose-clamp to an angle iron. The samplers (UPAS v2+, Access Sensors Technologies) are equipped with a filter for PM2.5 collection and have an integrated Sensiron SPS30 Sensor for continuous measurement of PM2.5, temperature, and relative humidity. Preliminary findings showed highly variable concentrations over 24 hours, with peak 30-second gravimetric adjusted concentrations over 5,000 µg/m3, largely influenced by sampler position and wind direction. The 24-hr average concentrations from the gravimetric filters were 487 and 603µg/m3. Our findings suggest that trash burning is a significant source of PM2.5 in the community and that an individual’s exposure will depend on dispersion patterns. There is a critical need to understand exposure to plastic burning and associated health effects, and to reduce exposure, especially among school children in rural and peri-urban Ghana

Mobilizing Resources to Support Air Quality Monitoring Research

One of the difficulties African scientists working on air pollution research encounter is the lack of laboratory and field equipment to generate reliable data essential for air quality policy formulation. Substantial investment in infrastructure, equipment, and personnel over the past few decades has led to significant improvement in air quality in the Global North such as Europe and North America. Therefore, the need for investment in equipment and trained personnel for air quality research both in the laboratory and field of the Global South cannot be overemphasized. However, air pollution is not yet a top concern for the governments of some Global South nations, leading to a lack of resources for this critical infrastructure.

Moderated By:

Dr. Allison Hughes, University of Ghana

Panel Discussion

Mr. Desmond Appiah, Clean Air Fund E: dappiah@cleanairfund.org
Dr. Langley Dewitt, IGAC E: langley@igacproject.org
Dr. Rose Alani, University of Lagos E: ralani@unilag.edu.ng

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Poster Presentations:

Philanthropic Opportunities in the Global Air Quality Data Landscape - Dr. Christa Hasenkopf (Germany)
Presented by: Dr. Christa Hasenkopf, Director of Air Quality Programs, Energy Policy Institute at the University of Chicago E: chasenkopf@uchicago.edu

Air pollution philanthropy is under-funded relative to the impact of air pollution on global health, amounting to a mere 63.8 million USD in funds globally each year and the entire African continent receiving approximately 300,000 USD in 2021 (1). One of the artifacts that this underfunding leaves is that basic data gaps for PM2.5, one of the most health-harmful air pollutants, remain across entire countries (2). Meanwhile, we know from examples on nearly every continent over the past several decades that sustained air quality monitoring is a necessary step toward cleaner air. It’s also relatively cheap. Investing in a single PM2.5 monitor in each of 17 countries – spending nominally about 2 million USD – would provide public air quality data for 1 billion people (3). We argue that providing resources for local actors in countries to build air quality data infrastructure is one of the most effective and efficient ways a philanthropy can contribute to addressing air pollution.

We present a country-level data gap analysis of the global PM2.5 landscape. In it, we identify where PM2.5 has the largest impact, in terms of highest concentrations and size of population affected, where there are the least on-the-ground monitors (of both reference grade and informal sensing types), and where there is the least philanthropic funding available. We also share a qualitative analysis of various local efforts in these "low hanging" places that are poised or already filling PM2.5 data gaps – and seek community input to identify more local actors in such locations. The intent of this work is to create a concrete picture to attract a larger amount of philanthropic funding to the field in the places that need it most, to connect this work with local actors, and to outline potential new partnership structures to fill PM2.5 data gaps across the world.

Sensor Evaluation & Analysis: Best Approaches to Evaluate Sensors

This is a moderated panel discussion on best approaches to evaluate sensors independently by reputed national institutions.

Moderated By:

Dr. Mike Giordano, AfriqAir E: mikegiordano@afriset.org

Panel Discussion

Dr. Allison Hughes, University of Ghana E: ahughes@ug.edu.gh
Dr. Nuria Castell, NILU E: ncb@nilu.no
Dr. Adrien Arfire, Airparif E: adrian.arfire@airparif.fr
Dr. Brigitte Language, North-West Universtiy E: 23034149@gmail.com

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