High-resolution patterns and inequalities in ambient fine particle mass (PM2.5) and black carbon (BC) in the Greater Accra Metropolis, Ghana

Low-Cost PM2.5 Sensor Performance Characteristics against Meteorological Influence in Sub-Saharan Africa: Evidence from the Air Sensor Evaluation and Training Facility for the West Africa Project

Fine particulate matter (PM2.5) pollution represents a major environmental health risk in Africa. The use of low-cost sensors (LCS) for air quality monitoring for policy and civic engagement in sub-Saharan Africa (SSA) has become paramount, as access to traditional reference-grade instruments is still sparse. Yet, studies pertaining to sensor performance under SSA's meteorological conditions and diverse emission sources are limited. Hence, we tested eight low-cost PM2.5 sensors on the market from different manufacturers containing Plantower PMS, Alphasense OPC-N3, and AVO-Sensor sensors by collocating them with the federal equivalent method Teledyne T640 to ascertain data accuracy, reliability, and responsiveness during wet and dry periods. After 6 months of collocation, PM2.5 concentrations from the LCS showed low intrasensor variability in both the wet and dry periods, but high intersensor variability with the Teledyne T640. A strong relationship existed between the LCS and Teledyne T640, with average coefficient of determination (R2) values of 0.7 (range: 05-0.9) and 0.8 (0.64-0.97) in the wet and dry periods, respectively. Larger errors were also associated with LCS data during the dry than the wet period, with the average mean absolute error and root mean squared error, respectively, 4.5 and 5.3 times higher in the dry period. Uncertainties with large errors were also observed with high PM2.5 measured in the wet period, levels that were more common during the dry period typically characterized by long-range transport of PM2.5 pollution. The results show that season significantly affects LCS performance and data quality and that care must be taken during deployment and data usage in SSA, with regular maintenance, particularly in the dry season. Strong collaborative efforts between governmental agencies, industries, and civil society are needed to come up with an effective framework for their application.

Measurement of urban vitality with time-lapsed street-view images and object-detection for scalable assessment of pedestrian-sidewalk dynamics

Principles of dense, mixed-use environments and pedestrianisation are influential in urban planning practice worldwide. A key outcome espoused by these principles is generating "urban vitality", the continuous use of street sidewalk infrastructure throughout the day, to promote safety, economic viability and attractiveness of city neighbourhoods. Vitality is hypothesised to arise from a nearby mixture of primary uses, short blocks, density of buildings and population and a diversity in the age and condition of surrounding buildings. To investigate this claim, we use a novel dataset of 2.1 million time-lapsed day and night images at 145 representative locations throughout the city of Accra, Ghana. We developed a measure of urban vitality for each location based on the coefficient of variation in pedestrian volume over time in our images, obtained from counts of people identified using object detection. We also construct measures of "generators of diversity": mixed-use intensity, building, block and population density, as well as diversity in the age of buildings, using data that are available across multiple cities and perform bivariate and multivariate regressions of our urban vitality measure against variables representing generators of diversity to test the latter's association with vitality. We find that two or more unique kinds of amenities accessible within a five-minute walk from a given location, as well as the density of buildings (of varying ages and conditions) and short blocks, are associated with more even footfall throughout the day. Our analysis also indicates some potential negative trade-offs from dense and mixed-use neighbourhoods, such as being associated with more continuous road traffic throughout the day. Our methodological approach is scalable and adaptable to different modes of image data capture and can be widely adopted in other cities worldwide.

Multinational modelling of PM2.5 and CO exposures from household air pollution in peri-urban Cameroon, Ghana and Kenya

In sub-Saharan Africa, approximately 85% of the population uses polluting cooking fuels (e.g. wood, charcoal). Incomplete combustion of these fuels generates household air pollution (HAP), containing fine particulate matter (PM2.5 ) and carbon monoxide (CO). Due to large spatial variability, increased quantification of HAP levels is needed to improve exposure assessment in sub-Saharan Africa. The CLEAN-Air(Africa) study included 24-h monitoring of PM2.5 and CO kitchen concentrations (npm2.5 = 248/nCO = 207) and female primary cook exposures (npm2.5 = 245/nCO = 222) in peri-urban households in Obuasi (Ghana), Mbalmayo (Cameroon) and Eldoret (Kenya). HAP measurements were combined with survey data on cooking patterns, socioeconomic characteristics and ambient exposure proxies (e.g. walking time to nearest road) in separate PM2.5 and CO mixed-effect log-linear regression models. Model coefficients were applied to a larger study population (n = 937) with only survey data to quantitatively scale up PM2.5 and CO exposures. The final models moderately explained variation in mean 24-h PM2.5 (R2 = 0.40) and CO (R2 = 0.26) kitchen concentration measurements, and PM2.5 (R2 = 0.27) and CO (R2 = 0.14) female cook exposures. Primary/secondary cooking fuel type was the only significant predictor in all four models. Other significant predictors of PM2.5 and CO kitchen concentrations were cooking location and household size; household financial security and rental status were only predictive of PM2.5 concentrations. Cooking location, household financial security and proxies of ambient air pollution exposure were significant predictors of PM2.5 cook exposures. Including objective cooking time measurements (from temperature sensors) from (n = 143) households substantially improved (by 52%) the explained variability of the CO kitchen concentration model, but not the PM2.5 model. Socioeconomic characteristics and markers of ambient air pollution exposure were strongly associated with mean PM2.5 measurements, while cooking environment variables were more predictive of mean CO levels.

Comprehensive health risk assessment of urban ambient air pollution (PM2.5, NO2 and O3) in Ghana

Urbanization and industrialization have drastically increased ambient air pollution in urban areas globally from vehicle emissions, solid fuel combustion and industrial activities leading to some of the worst air quality conditions. Air pollution in Ghana causes approximately 28,000 premature deaths and disabilities annually, ranking as a leading cause of mortality and disability-adjusted life years. This study evaluated the annual concentrations of PM2.5, NO2 and O3 in the ambient air of 57 cities in Ghana for two decades using historical and forecasted data from satellite measurements. The study assessed urban air quality and evaluated both carcinogenic and non-carcinogenic health risks associated with human exposure to ambient air pollutants. Alarmingly, our findings revealed the yearly median PM2.5 concentrations (50.79-67.97 µg m-3) to be significantly higher than the WHO recommendation of 5 µg m-3. Tropospheric ozone concentrations (72.21-92.58 µg m-3 ) also exceeded the WHO annual standard of 60 µg m-3. Furthermore, NO2 concentrations (3.65-12.15 µg m-3 ) surpassed the WHO threshold of 10 µg/m³ in multiple cities. Hazard indices indicated that PM2.5 and O3 pose significant non-carcinogenic health risks for younger age groups for a daily exposure duration of three hours and beyond. According to the Air Quality Life Index (AQLI) in our study, exposure to PM2.5 shortens life expectancy by 4.5-6.2 years. The ambient air of the majority (98 %) of the cities was unhealthy for sensitive groups. This study reveals the urgent need for comprehensive air quality policies in Ghanaian cities. It emphasizes the significance of robust real-time monitoring of air pollutants and the investigation of seasonal dust storm effects, to fill data gaps in Ghana and West Africa, facilitating evidence-based interventions that improve urban air quality and public health outcomes.

The Health Impacts of Air Pollution in the Context of Changing Climate in Africa: A Narrative Review with Recommendations for Action

Introduction: Despite the broad improvement in air quality, air pollution remains a major leading global risk factor for ill health and deaths each year. Air pollution has a significant impact on both health and economic growth in Africa. This paper reviews the health impacts of air pollution and the benefits of air pollution mitigation and prevention on climate change. Methods: We conducted a narrative review and synthesized current literature on the health impact of air pollution in the context of changing climate in Africa. Results: Particulate matter (PM2.5) concentrations in Africa pose significant health risks due to various sources, including household fuels and industrial emissions. Limited air quality monitoring hampers accurate assessment and public health planning. Africa's rapid urbanization exacerbates air pollution, impacting vulnerable populations disproportionately. Renewable energy adoption and improved monitoring infrastructure are crucial for mitigating air pollution's economic and health impacts. Recommendations include adopting air quality standards, identifying pollution sources, and prioritizing interventions for vulnerable groups. Integrating renewable energy into development plans is essential for sustainable growth. African leaders must prioritize environmental policies to safeguard public health amid ongoing industrialization. Conclusions: Air pollution prevention remains a vital concern that requires leaders to engage stakeholders, and other opinion leaders in society. African leaders should proactively explore new avenues to integrate non‑polluting renewable energy sources such as solar power, wind and hydropower into their national development plans.

From consumption to context: assessing poverty and inequality across diverse socio-ecological systems in Ghana

Local social and ecological contexts influence the experience of poverty and inequality in a number of ways that include shaping livelihood opportunities and determining the available infrastructure, services and environmental resources, as well as people's capacity to use them. The metrics used to define poverty and inequality function to guide local and international development policy but how these interact with the local ecological contexts is not well explored. We use a social-ecological systems (SES) lens to empirically examine how context relates to various measures of human well-being at a national scale in Ghana. Using a novel dataset constructed from the 100% Ghanian Census, we examine poverty and inequality at a fine population level across and within multiple dimensions of well-being. First, we describe how well-being varies within different Ghanian SES contexts. Second, we ask whether monetary consumption acts a good indicator for well-being across these contexts. Third, we examine measures of inequality in various metrics across SES types. We find consumption distributions differ across SES types and are markedly distinct from regional distributions based on political boundaries. Rates of improved well-being are positively correlated with consumption levels in all SES types, but correlations are weaker in less-developed contexts like, rangelands and wildlands. Finally, while consumption inequality is quite consistent across SES types, inequality in other measures of living standards (housing, water, sanitation, etc) increases dramatically in SES types as population density and infrastructural development decreases. We advocate that SES types should be recognized as distinct contexts in which actions to mitigate poverty and inequality should better incorporate the challenges unique to each.

Characterizing the distribution pattern of traffic-related air pollutants in near-road neighborhoods

In near-road neighborhoods, residents are more frequently exposed to traffic-related air pollution (TRAP), and they are increasingly aware of pollution levels. Given this consideration, this study adopted portable air pollutant sensors to conduct a mobile monitoring campaign in two near-road neighborhoods, one in an urban area and one in a suburban area of Shanghai, China. The campaign characterized spatiotemporal distributions of fine particulate matter (PM2.5) and black carbon (BC) to help identify appropriate mitigation measures in these near-road micro-environments. The study identified higher mean TRAP concentrations (up to 4.7-fold and 1.7-fold higher for PM2.5 and BC, respectively), lower spatial variability, and a stronger inter-pollutant correlation in winter compared to summer. The temporal variations of TRAP between peak hour and off-peak hour were also investigated. It was identified that district-level PM2.5 increments occurred from off-peak to peak hours, with BC concentrations attributed more to traffic emissions. In addition, the spatiotemporal distribution of TRAP inside neighborhoods revealed that PM2.5 concentrations presented great temporal variability but almost remained invariant in space, while the BC concentrations showed notable spatiotemporal variability. These findings provide valuable insights into the unique spatiotemporal distributions of TRAP in different near-road neighborhoods, highlighting the important role of hyperlocal monitoring in urban micro-environments to support tailored designing and implementing appropriate mitigation measures.

Cross-shift changes in pulmonary function and occupational exposure to particulate matter among e-waste workers in Ghana

Introduction

Little is known on the association between cross-shift changes in pulmonary function and personal inhalation exposure to particulate matter (PM) among informal electronic-waste (e-waste) recovery workers who have substantial occupational exposure to airborne pollutants from burning e-waste.

Methods

Using a cross-shift design, pre- and post-shift pulmonary function assessments and accompanying personal inhalation exposure to PM (sizes <1, <2.5 μm, and the coarse fraction, 2.5-10 μm in aerodynamic diameter) were measured among e-waste workers (n = 142) at the Agbogbloshie e-waste site and a comparison population (n = 65) in Accra, Ghana during 2017 and 2018. Linear mixed models estimated associations between percent changes in pulmonary function and personal PM.

Results

Declines in forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) per hour were not significantly associated with increases in PM (all sizes) among either study population, despite breathing zone concentrations of PM (all sizes) that exceeded health-based guidelines in both populations. E-waste workers who worked "yesterday" did, however, have larger cross-shift declines in FVC [-2.4% (95%CI: -4.04%, -0.81%)] in comparison to those who did not work "yesterday," suggesting a possible role of cumulative exposure.

Discussion

Overall, short-term respiratory-related health effects related to PM exposure among e-waste workers were not seen in this sample. Selection bias due to the "healthy worker" effect, short shift duration, and inability to capture a true "pre-shift" pulmonary function test among workers who live at the worksite may explain results and suggest the need to adapt cross-shift studies for informal settings.

Environmental Exposome and Atrial Fibrillation: Emerging Evidence and Future Directions

There has been increased awareness of the linkage between environmental exposures and cardiovascular health and disease. Atrial fibrillation is the most common sustained cardiac arrhythmia, affecting millions of people worldwide and contributing to substantial morbidity and mortality. Although numerous studies have explored the role of genetic and lifestyle factors in the development and progression of atrial fibrillation, the potential impact of environmental determinants on this prevalent condition has received comparatively less attention. This review aims to provide a comprehensive overview of the current evidence on environmental determinants of atrial fibrillation, encompassing factors such as air pollution, temperature, humidity, and other meteorologic conditions, noise pollution, greenspace, and the social environment. We discuss the existing evidence from epidemiological and mechanistic studies, critically evaluating the strengths and limitations of these investigations and the potential underlying biological mechanisms through which environmental exposures may affect atrial fibrillation risk. Furthermore, we address the potential implications of these findings for public health and clinical practice and identify knowledge gaps and future research directions in this emerging field.

Inequalities in urban air pollution in sub-Saharan Africa: an empirical modeling of ambient NO and NO2 concentrations in Accra, Ghana

Road traffic has become the leading source of air pollution in fast-growing sub-Saharan African cities. Yet, there is a dearth of robust city-wide data for understanding space-time variations and inequalities in combustion related emissions and exposures. We combined nitrogen dioxide (NO2) and nitric oxide (NO) measurement data from 134 locations in the Greater Accra Metropolitan Area (GAMA), with geographical, meteorological, and population factors in spatio-temporal mixed effects models to predict NO2 and NO concentrations at fine spatial (50 m) and temporal (weekly) resolution over the entire GAMA. Model performance was evaluated with 10-fold cross-validation (CV), and predictions were summarized as annual and seasonal (dusty [Harmattan] and rainy [non-Harmattan]) mean concentrations. The predictions were used to examine population distributions of, and socioeconomic inequalities in, exposure at the census enumeration area (EA) level. The models explained 88% and 79% of the spatiotemporal variability in NO2 and NO concentrations, respectively. The mean predicted annual, non-Harmattan and Harmattan NO2 levels were 37 (range: 1-189), 28 (range: 1-170) and 50 (range: 1-195) µg m-3, respectively. Unlike NO2, NO concentrations were highest in the non-Harmattan season (41 [range: 31-521] µg m-3). Road traffic was the dominant factor for both pollutants, but NO2 had higher spatial heterogeneity than NO. For both pollutants, the levels were substantially higher in the city core, where the entire population (100%) was exposed to annual NO2 levels exceeding the World Health Organization (WHO) guideline of 10 µg m-3. Significant disparities in NO2 concentrations existed across socioeconomic gradients, with residents in the poorest communities exposed to levels about 15 µg m-3 higher compared with the wealthiest (p < 0.001). The results showed the important role of road traffic emissions in air pollution concentrations in the GAMA, which has major implications for the health of the city's poorest residents. These data could support climate and health impact assessments as well as policy evaluations in the city.

Strangers in a strange land: mapping household and neighbourhood associations with improved wellbeing outcomes in Accra, Ghana

Urban poverty is not limited to informal settlements, rather it extends throughout cities, with the poor and affluent often living in close proximity. Using a novel dataset derived from the full Ghanaian Census, we investigate how neighbourhood versus household socio-economic status (SES) relates to a set of household development outcomes (related to housing quality, energy, water and sanitation, and information technology) in Accra, Ghana. We then assess "stranger" households' outcomes within neighbourhoods: do poor households fare better in affluent neighbourhoods, and are affluent households negatively impacted by being in poor neighbourhoods? Through a simple generalized linear model we estimate the variance components associated with household and neighbourhood status for our outcome measures. Household SES is more closely associated with 13 of the 16 outcomes assessed compared to the neighbourhood average SES. Second, for 9 outcomes poor households in affluent areas fair better, and the affluent in poor areas are worse off. For two outcomes, poor households have worse outcomes in affluent areas, and the affluent have better outcomes in poor areas, on average. For three outcomes "stranger" households do worse in strange neighbourhoods. We discuss implications for mixed development and how to direct resources through households versus location-based targets.