Within-neighborhood patterns and sources of particle pollution: mobile monitoring and geographic information system analysis in four communities in Accra, 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.

Prevalence of indoor air pollutants from First Nation homes in North Central British Columbia, Canada

Poor indoor air quality poses significant health risks. This study addresses the gap in knowledge regarding the prevalence of indoor air pollutants in remote and rural First Nation communities in north-central British Columbia, Canada. Dust samples from 75 homes were collected and analysed for house dust mites, pet allergens, mould antigens, and bacterial endotoxins. Indoor air quality parameters, including carbon monoxide, carbon dioxide, particulate matter, temperature, and humidity, were measured. A detailed questionnaire on household characteristics and potential pollutant sources was administered. Homes exhibited exposure to multiple pollutants, with wood stove smoke identified as a primary source. Felis domesticus (cat allergen) and Canis familiaris (dog allergen) were prevalent, with detectable levels in 64% and 60% of homes, respectively. Bacterial endotoxins were present in all households. One-third of homes exceeded recommended thresholds for 3 or more pollutants. This study provides critical insights into the prevalence and magnitude of indoor air pollutants, contributing to a broader initiative to characterise respiratory health in First Nations communities. While many homes in First Nations communities had acceptable air quality, one-third of homes exceeded thresholds for 3 or more pollutants. The results can guide ongoing community efforts to address housing concerns and advocate for increased federal funding.

High-resolution spatial and spatiotemporal modelling of air pollution using fixed site and mobile monitoring in a Canadian city

The development of high-resolution spatial and spatiotemporal models of air pollutants is essential for exposure science and epidemiological applications. While fixed-site sampling has conventionally provided input data for statistical predictive models, the evolving mobile monitoring method offers improved spatial resolution, ideal for measuring pollutants with high spatial variability such as ultrafine particles (UFP). The Quebec Air Pollution Exposure and Epidemiology (QAPEE) study measured and modelled the spatial and spatiotemporal distributions of understudied pollutants, such as UFPs, black carbon (BC), and brown carbon (BrC), along with fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) in Quebec City, Canada. We conducted a combined fixed-site (NO2 and O3) and mobile monitoring (PM2.5, BC, BrC, and UFPs) campaign over 10-months. Mobile monitoring routes were monitored on a weekly basis between 8am-10am and designed using location/allocation modelling. Seasonal fixed-site sampling campaigns captured continuous 24-h measurements over two-week periods. Generalized Additive Models (GAMs), which combined data on pollution concentrations with spatial, temporal, and spatiotemporal predictor variables were used to model and predict concentration surfaces. Annual models for PM2.5, NO2, O3 as well as seven of the smallest size fractions in the UFP range, had high out of sample predictive accuracy (range r2: 0.54-0.86). Varying spatial patterns were observed across UFP size ranges measured as Particle Number Counts (PNC). The monthly spatiotemporal models for PM2.5 (r2 = 0.49), BC (r2 = 0.27), BrC (r2 = 0.29), and PNC (r2 = 0.49) had moderate or moderate-low out of sample predictive accuracy. We conducted a sensitivity analysis and found that the minimum number of 'n visits' (mobile monitoring sessions) required to model annually representative air pollution concentrations was between 24 and 32 visits dependent on the pollutant. This study provides a single source of exposure models for a comprehensive set of air pollutants in Quebec City, Canada. These exposure models will feed into epidemiological research on the health impacts of ambient UFPs and other pollutants.

Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning

Advances in computer vision, driven by deep learning, allows for the inference of environmental pollution and its potential sources from images. The spatial and temporal generalisability of image-based pollution models is crucial in their real-world application, but is currently understudied, particularly in low-income countries where infrastructure for measuring the complex patterns of pollution is limited and modelling may therefore provide the most utility. We employed convolutional neural networks (CNNs) for two complementary classification models, in both an end-to-end approach and as an interpretable feature extractor (object detection), to estimate spatially and temporally resolved fine particulate matter (PM2.5) and noise levels in Accra, Ghana. Data used for training the models were from a unique dataset of over 1.6 million images collected over 15 months at 145 representative locations across the city, paired with air and noise measurements. Both end-to-end CNN and object-based approaches surpassed null model benchmarks for predicting PM2.5 and noise at single locations, but performance deteriorated when applied to other locations. Model accuracy diminished when tested on images from locations unseen during training, but improved by sampling a greater number of locations during model training, even if the total quantity of data was reduced. The end-to-end models used characteristics of images associated with atmospheric visibility for predicting PM2.5, and specific objects such as vehicles and people for noise. The results demonstrate the potential and challenges of image-based, spatiotemporal air pollution and noise estimation, and that robust, environmental modelling with images requires integration with traditional sensor networks.

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

Growing cities in sub-Saharan Africa (SSA) experience high levels of ambient air pollution. However, sparse long-term city-wide air pollution exposure data limits policy mitigation efforts and assessment of the health and climate effects. In the first study of its kind in West Africa, we developed high resolution spatiotemporal land use regression (LUR) models to map fine particulate matter (PM2.5) and black carbon (BC) concentrations in the Greater Accra Metropolitan Area (GAMA), one of the fastest sprawling metropolises in SSA. We conducted a one-year measurement campaign covering 146 sites and combined these data with geospatial and meteorological predictors to develop separate Harmattan and non-Harmattan season PM2.5 and BC models at 100 m resolution. The final models were selected with a forward stepwise procedure and performance was evaluated with 10-fold cross-validation. Model predictions were overlayed with the most recent census data to estimate the population distribution of exposure and socioeconomic inequalities in exposure at the census enumeration area level. The fixed effects components of the models explained 48-69 % and 63-71 % of the variance in PM2.5 and BC concentrations, respectively. Spatial variables related to road traffic and vegetation explained the most variability in the non-Harmattan models, while temporal variables were dominant in the Harmattan models. The entire GAMA population is exposed to PM2.5 levels above the World Health Organization guideline, including even the Interim Target 3 (15 μg/m3), with the highest exposures in poorer neighborhoods. The models can be used to support air pollution mitigation policies, health, and climate impact assessments. The measurement and modelling approach used in this study can be adapted to other African cities to bridge the air pollution data gap in the region.

Characterisation of urban environment and activity across space and time using street images and deep learning in Accra

The urban environment influences human health, safety and wellbeing. Cities in Africa are growing faster than other regions but have limited data to guide urban planning and policies. Our aim was to use smart sensing and analytics to characterise the spatial patterns and temporal dynamics of features of the urban environment relevant for health, liveability, safety and sustainability. We collected a novel dataset of 2.1 million time-lapsed day and night images at 145 representative locations throughout the Metropolis of Accra, Ghana. We manually labelled a subset of 1,250 images for 20 contextually relevant objects and used transfer learning with data augmentation to retrain a convolutional neural network to detect them in the remaining images. We identified 23.5 million instances of these objects including 9.66 million instances of persons (41% of all objects), followed by cars (4.19 million, 18%), umbrellas (3.00 million, 13%), and informally operated minibuses known as tro tros (2.94 million, 13%). People, large vehicles and market-related objects were most common in the commercial core and densely populated informal neighbourhoods, while refuse and animals were most observed in the peripheries. The daily variability of objects was smallest in densely populated settlements and largest in the commercial centre. Our novel data and methodology shows that smart sensing and analytics can inform planning and policy decisions for making cities more liveable, equitable, sustainable and healthy.

Between Policy and Risk Communication: Coverage of Air Pollution in Ghanaian Newspapers

Mass media plays an increasingly persuasive role in orienting political decisions, shaping social agendas, influencing individuals' actions, and interpreting scientific evidence for the public. With growing scientific understanding of the health, social and environmental consequences of air pollution, there is an urgent need to understand how media coverage frames these links, particularly in Low- and Middle-Income Countries. This paper examines how the Ghanaian print and electronic media houses are covering air pollution issues given increased efforts at reducing air pollution within the country. The main goal of this work is to track the progress of policies to reduce air pollution. We used a qualitative content analysis of selected newspapers (both traditional and online) between the periods 2016 and 2021 and we found that articles on air pollution have been increasing, with more reportage on impact and policy issues compared to causes of air pollution. A focus group with six members of the media confirmed an interest in covering health and environmental issues, particularly coverage of specific diseases and human-interest pieces. This increasing attention is likely associated with intensifying local, national, and international action to improve air quality in Ghana, and growing awareness of the health impacts of air pollution.

Particulate matter pollution at traffic hotspots of Accra, Ghana: levels, exposure experiences of street traders, and associated respiratory and cardiovascular symptoms

BACKGROUND

There are limited studies on the health effects of street trading in spite of common knowledge that individuals engaged in the trade are exposed to high levels of traffic-related air pollution per their mode of operation, and also the fact that the venture is a dominant occupation in cities of Sub-Saharan Africa (SSA) and other developing regions.

OBJECTIVE

We characterized particulate matter (PM) pollution levels at traffic hotspots of Accra, Ghana during the dry and wet seasons, and assessed exposure experiences of street traders.

METHODS

A cross-sectional study was conducted among 236 street traders operating along six selected traffic routes of Accra and a comparison group of 186 office workers. PurpleAir PA-II monitors were used to measure PM levels at the selected traffic routes. We estimated annual PM_2.5 exposure of street traders using assigned seasonal PM_2.5 levels, and information collected in a structured questionnaire on their activity patterns. Outcomes investigated were self-reported respiratory and cardiovascular symptoms.

RESULTS

PM levels at Accra traffic hotspots were high in both seasons. 1 ug/m³ increase in PM_2.5 exposure increased respiratory, cardiovascular, and overall symptoms by a factor of 0.00027 (95% CI: 0.00012, 0.00041), 0.00022 (95% CI: 0.00007, 0.00036), and 0.00048 (95% CI: 0.00023, 0.00073), respectively. Compared to office workers, high PM_2.5 exposure among street traders was associated with increased odds of coughing, catarrh (postnasal drip), sneezing, rapid heart beating, irregular heartbeat, sharp chest pains, fainting spells, headaches, and dizziness. Low and medium PM_2.5 exposure was associated with increased odds of dermatitis, rapid heart beating, and irregular heartbeat, and sharp chest pains, respectively.

CONCLUSIONS

We found consistent evidence that PM_2.5 exposure among street traders increases the occurrence of respiratory and cardiovascular symptoms. We also provide indicative measurements of PM levels at traffic hotspots of a rapidly growing SSA city with heavy vehicular traffic and yet, limited air quality monitoring capacity.

Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June-September) and short rain season (February-April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public's health.

Population awareness and attitudes toward waste-related health risks in Accra, Ghana

Despite significant knowledge about the potential health hazards of waste, there are few studies in African cities that investigate awareness of health issues related to waste management, although such research is needed to lower population exposure. This paper examines the case study of Accra in Ghana, a city dealing with serious health and pollution problems. Three focus groups and 157 households in Accra were surveyed on household waste disposal and awareness of waste-related health hazards. Surveyed households had limited knowledge of waste-related health hazards in their neighbourhoods. Although the households reported diseases that could be associated with environmental factors linked to waste management, 87% of all surveyed households did not think that someone in their household could have fallen ill of a disease that can be related to waste. In middle- and high-income neighbourhoods, waste burning increases substantially when waste is not collected.

Green infrastructure can limit but not solve air pollution injustice

Outdoor air pollution contributes to millions of deaths worldwide yet air pollution has differential exposures across racial/ethnic groups and socioeconomic status. While green infrastructure has the potential to decrease air pollution and provide other benefits to human health, vegetation alone cannot resolve health disparities related to air pollution injustice. We discuss how unequal access to green infrastructure can limit air quality improvements for marginalized communities and provide strategies to move forward.

Spatial-temporal patterns of ambient fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra

Sub-Saharan Africa (SSA) is rapidly urbanizing, and ambient air pollution has emerged as a major environmental health concern in growing cities. Yet, effective air quality management is hindered by limited data. We deployed robust, low-cost and low-power devices in a large-scale measurement campaign and characterized within-city variations in fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra, Ghana. Between April 2019 and June 2020, we measured weekly gravimetric (filter-based) and minute-by-minute PM2.5 concentrations at 146 unique locations, comprising of 10 fixed (∼1 year) and 136 rotating (7 day) sites covering a range of land-use and source influences. Filters were weighed for mass, and light absorbance (10-5m-1) of the filters was used as proxy for BC concentration. Year-long data at four fixed sites that were monitored in a previous study (2006-2007) were compared to assess changes in PM2.5 concentrations. The mean annual PM2.5 across the fixed sites ranged from 26 μg m-3 at a peri-urban site to 43 μg m-3 at a commercial, business, and industrial (CBI) site. CBI areas had the highest PM2.5 levels (mean: 37 μg m-3), followed by high-density residential neighborhoods (mean: 36 μg m-3), while peri-urban areas recorded the lowest (mean: 26 μg m-3). Both PM2.5 and BC levels were highest during the dry dusty Harmattan period (mean PM2.5: 89 μg m-3) compared to non-Harmattan season (mean PM2.5: 23 μg m-3). PM2.5 at all sites peaked at dawn and dusk, coinciding with morning and evening heavy traffic. We found about a 50% reduction (71 vs 37 μg m-3) in mean annual PM2.5 concentrations when compared to measurements in 2006-2007 in Accra. Ambient PM2.5 concentrations in Accra may have plateaued at levels lower than those seen in large Asian megacities. However, levels are still 2- to 4-fold higher than the WHO guideline. Effective and equitable policies are needed to reduce pollution levels and protect public health.

Urban Municipal Solid Waste management: Modeling air pollution scenarios and health impacts in the case of Accra, Ghana

Despite the clear link between air pollution and health, research to investigate the relationship between municipal solid waste management and air pollution and health has not been prioritized. Such research may generate scientific information that would help reduce population exposure to air pollutants. This paper examines the case study of Accra in Ghana, a city dealing with serious waste management problems. The paper proposes a methodology to estimate the impact of waste management on urban air pollution and health. The analysis is described in the following four steps: (1) collecting data on the waste sector; (2) modeling the emissions arising from waste management; (3) transforming emissions to concentration values and (4) estimating the burdens on health. The assessment has been conducted using the CCAC SWEET tool and WHO AirQ+. The method presented can be used in different locations, depending on data availability, when analyzing the impact of and potential changes to waste sector policies. The results of this health impact assessment indicate that, based on the emissions of PM_2.5 from the waste sector in Accra, a change from the business-as-usual to more sustainable options would reduce air pollutants emissions and avert 120 premature deaths in 2030. Levels of air pollution in Accra are significant and interventions to reduce PM_2.5 exposure should be promoted. The detailed analysis of the current situation provides suggestions for waste management policies in terms of impacts on health and ideas to reconsider the waste policies in Accra.

Spatial and seasonal variation of outdoor BC and PM2.5 in densely populated urban slums

A large proportion of residents in urban centers of low- and middle-income countries live in low-socioeconomic neighborhoods called "slums" characterized by low-cost housings of high population density, poor ventilation, and likely poor air quality. This study provides the first quantitative assessment of spatial and seasonal variation of outdoor BC and PM_2.5 concentrations in several densely populated slums of Mumbai, India. Mobile outdoor real-time BC and PM_2.5 monitoring was conducted along pre-designed monitoring routes in seven slums in Mumbai during the summer (May-June 2015 and May 2016) and repeated in four of them during the winter (February 2016). The measurements were repeated on the routes during different hours and days to account for the temporal variability of air pollution (n_summer = 80 trips; n_winter = 48 trips). PM_2.5 exhibited homogenous distribution inside each slum (coefficient of divergence (COD) = 0.11-0.23), while BC varied significantly showing increasing concentrations with proximity to major roads (COD = 0.26-0.64). BC/PM_2.5 ratio, an indicator of impact of traffic emissions, was higher along major roads of all slums (14-43%) and minor roads and alleys of high-traffic slums (10-17%) while lowest along alleys and minor roads of low-traffic slums (7-11%). Comparison of pollutant concentrations among major roads revealed the dominant effect of emissions from heavy-duty vehicles and traffic congestion. Significantly high concentrations were observed during winter season compared with summer for both PM_2.5 (125 ± 46 μg m^-3 in winter and 41 ± 25 μg m^-3 in summer) and BC (12 ± 6 μg m^-3 in winter and 7 ± 6 μg m^-3 in summer). The results of this study indicate that slum residents in Mumbai and similar slums around the world are at a higher risk of traffic-related air pollution, with risk being more severe in winters due to poorer dispersion conditions. Our findings suggest that targeted mitigation strategies to reduce vehicular emissions, especially in high-traffic slums, would yield required benefits.Graphical abstract.

Micro-scale particle simulation and traffic-related particle exposure assessment in an Asian residential community

Conducting studies on sharp particulate matter (PM) gradients in Asian residential communities is difficult due to their complex building arrangements and various emission sources, particularly road traffic. In this study, a synthetic methodology, combining numerical simulations and minor field observations, was set up to investigate the dispersion of traffic-related PM in a typical Asian residential community and its contribution to PM exposure. A Lagrangian particle model (GRAL) was applied to estimate the spatiotemporal variation of the traffic-related PM increments within the community. A detailed topography dataset with 5 m horizontal resolution was used to simulate a micro-scale flow field. The model performance was comprehensively validated using both in-situ and mobile observations. The coefficient of determination (R²) of the simulated vs. observed PM_2.5 reached 0.81 by an artery road, and 0.85 in alleys without significant road traffic. The maximum increments of kerbside PM exposure concentration contributed by road traffic during rush hour were found to be 38% (PM₁₀) and 40% (PM_2.5). This synthetic method was used to assess the impact of synoptic wind and canyon orientation on residents' PM_2.5 exposure related to traffic exhaust. Perfect exponential decay curves of traffic-related PM_2.5 were found within canyons. The decrease of road-traffic PM_2.5 on five different floor levels, compared with that on kerbside levels, ranged between 42% and 100%. The results demonstrated that in complex Asian communities, Lagrangian particle models such as GRAL can simulate the spatial distribution of PM₁₀ and PM_2.5 and assess the residents' outdoor exposure.

High-resolution spatiotemporal measurement of air and environmental noise pollution in Sub-Saharan African cities: Pathways to Equitable Health Cities Study protocol for Accra, Ghana

INTRODUCTION

Air and noise pollution are emerging environmental health hazards in African cities, with potentially complex spatial and temporal patterns. Limited local data are a barrier to the formulation and evaluation of policies to reduce air and noise pollution.

METHODS AND ANALYSIS

We designed a year-long measurement campaign to characterise air and noise pollution and their sources at high-resolution within the Greater Accra Metropolitan Area (GAMA), Ghana. Our design uses a combination of fixed (year-long, n=10) and rotating (week-long, n =~130) sites, selected to represent a range of land uses and source influences (eg, background, road traffic, commercial, industrial and residential areas, and various neighbourhood socioeconomic classes). We will collect data on fine particulate matter (PM_2.5), nitrogen oxides (NO_x), weather variables, sound (noise level and audio) along with street-level time-lapse images. We deploy low-cost, low-power, lightweight monitoring devices that are robust, socially unobtrusive, and able to function in Sub-Saharan African (SSA) climate. We will use state-of-the-art methods, including spatial statistics, deep/machine learning, and processed-based emissions modelling, to capture highly resolved temporal and spatial variations in pollution levels across the GAMA and to identify their potential sources. This protocol can serve as a prototype for other SSA cities.

ETHICS AND DISSEMINATION

This environmental study was deemed exempt from full ethics review at Imperial College London and the University of Massachusetts Amherst; it was approved by the University of Ghana Ethics Committee (ECH 149/18-19). This protocol is designed to be implementable in SSA cities to map environmental pollution to inform urban planning decisions to reduce health harming exposures to air and noise pollution. It will be disseminated through local stakeholder engagement (public and private sectors), peer-reviewed publications, contribution to policy documents, media, and conference presentations.

Air Quality Impacts at an E-Waste Site in Ghana Using Flexible, Moderate-Cost and Quality-Assured Measurements

Air quality information is scarce in low- and middle-income countries. This study describes the application of moderate cost approaches that can provide spatial and temporal information on concentrations of particulate matter (PM) needed to assess community and occupational exposures. We evaluated PM levels at the Agbogbloshie e-waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations, obtaining both optical and gravimetric measurements, local meteorological data and satellite aerosol optical depth. Due to overload issues, the gravimetric 24-hr samplers were modified for periodic sampling and some optical data were screened for quality assurance. Exceptionally high concentrations (e.g., 1-hr average PM10 exceeding 2000 μg/m3) were sometimes encountered near combustion sources, including open fires at the e-waste site and spoil piles. 24-hr PM2.5 levels averaged 31, 88 and 57 μg/m3 at upwind, e-waste and downwind sites, respectively, and PM10 averaged 145, 214 and 190 μg/m3, considerably exceeding air quality standards. Upwind levels likely reflected biomass burning that is prevalent in the surrounding informal settlements; levels at the e-waste and downwind sites also reflected contributions from biomass combustion and traffic. The highest PM levels occurred in evenings, influenced by diurnal changes in emission rates, atmospheric dispersion and wind direction shifts. We demonstrate that moderate cost instrumentation, with some modifications, appropriate data cleaning protocols, and attention to understanding local sources and background levels, can be used to characterize spatial and temporal variation in PM levels in urban and industrial areas.

Monitoring, Mapping, and Modeling Spatial-Temporal Patterns of PM2.5 for Improved Understanding of Air Pollution Dynamics Using Portable Sensing Technologies

Fine particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) is highly variable in space and time. In this study, the dynamics of PM2.5 concentrations were mapped at high spatio-temporal resolutions using bicycle-based, mobile measures on a university campus. Significant diurnal and daily variations were revealed over the two-week survey, with the PM2.5 concentration peaking during the evening rush hours. A range of predictor variables that have been proven useful in estimating the pollution level was derived from Geographic Information System, high-resolution airborne images, and Light Detection and Ranging (LiDAR) datasets. Considering the complex interplay among landscape, wind, and air pollution, variables influencing the PM2.5 dynamics were quantified under a new wind wedge-based system that incorporates wind effects. Panel data analysis models identified eight natural and built environment variables as the most significant determinants of local-scale air quality (including four meteorological factors, distance to major roads, vegetation footprint, and building and vegetation height). The higher significance level of variables calculated using the wind wedge system as compared to the conventional circular buffer highlights the importance of incorporating the relative position of emission sources and receptors in modeling.

Solid fuel use and early child development disparities in Ghana: analyses by gender and urbanicity

In Ghana, more than 77% of the population depends on biomass fuels for cooking. Previous studies show that solid fuel use (SFU) has adverse effects on pregnancy and child health outcomes. Yet, no previous study considered potential effects on early child development indicators (ECDI), nor how SFU effects may vary by gender, and rural and urban areas. We investigated the associations of SFU with ECDI measures, and whether these associations exhibited sex and urban/rural differences. We used the 2011-2012 Ghana's Multiple Indicator Cluster Surveys-UNICEF (N = 3326 children; 3-4 years). We derived a binary ECDI measure reflecting whether the child is developmentally on track or not from a caregiver-report of ten yes/no/do not know questions designed specifically to assess four domains of early child development: learning-cognition, literacy-numeracy, socio-emotional, and physical. We used multilevel Poisson regressions adjusting for neighborhood, household, mother, and child's characteristics to estimate covariate-adjusted prevalence ratios (PRs) of the associations between SFU and ECDI and its four dimensions. We run stratified analyses and used z-score tests of differences to evaluate effect modification by sex and urbanicity. Overall, 85% of children were exposed to SFU and 28% of children were not developmentally on track. After adjustment for confounders, children exposed to SFU were more likely to be not developmentally on track in comparison with nonexposed children (PR = 1.16; 95% confidence interval, [95% CI]: 1.10,1.22). These associations were stronger in girls (PR = 1.36; 95% CI: 1.03,1.79) in comparison with boys (PR = 0.87; 95% CI: 0.73,1.04). No difference in associations was observed between urban and rural children. Overall, these associations were mainly driven by the literacy-numeracy dimension. In this study, we show that SFU was associated with developmental delays in Ghanaian girls. Policy efforts which tackle SFU should be mindful of gender disparities in susceptibility to indoor pollution.

A versatile low-cost sensing device for assessing PM2.5 spatiotemporal variation and quantifying source contribution

This study evaluated a newly developed sensing device, AS-LUNG-O, against a research-grade GRIMM in laboratory and ambient conditions and used AS-LUNG-O to assess PM_2.5 spatiotemporal variations at street levels of an Asian mountain community, which represented residents' exposure (at the interface of atmosphere and human bodies leading to potential health impacts). In laboratory, R² of 1-min AS-LUNG-O and GRIMM was 0.95 ± 0.04 (n = 64,179 for 40 sets). After conversion with individual correction equations, their correlation in ambient tests was 0.93 ± 0.05, with absolute % difference of only 10 ± 9%. Ten AS-LUNG-O sets were installed at street sites with another one at 10 m above ground on July 1-28 and December 2-31, 2017 in Nantou, Taiwan. Important source contributions to PM_2.5 were quantified with regression analysis. Temporal variation expressed as the daily max/mean of 5-min PM_2.5 reached 13.7 in July and 12.2 in December. Spatial variation expressed as the percent coefficients of variance (%CV) across ten community locations was 22% ± 20% (max: 199%) in July and 19 ± 18% (max: 206%) in December. Incremental contribution from the stop-and-go traffic, market, temple, and fried-chicken vendor to PM_2.5 at 3-5 m away were 4.38, 3.90, 2.72, and 1.80 μg/m³, respectively. Significant spatiotemporal variations and community source contributions revealed the importance of assessing neighborhood air quality for public health protection. For long-term air quality monitoring, the percentage of available power and signals of G-sensor provided indicative information of maintenance required. Advantages of low cost (USD 650), small size, light weight, solar power supply, backup data storage, waterproof housing, multiple-sensor flexibility, and high precision and accuracy (after correction) enable AS-LUNG-O to be widely applied in environmental studies.

The role of cities in reducing the cardiovascular impacts of environmental pollution in low- and middle-income countries

BACKGROUND

As low- and middle-income countries urbanize and industrialize, they must also cope with pollution emitted from diverse sources.

MAIN TEXT

Strong and consistent evidence associates exposure to air pollution and lead with increased risk of cardiovascular disease occurrence and death. Further, increasing evidence, mostly from high-income countries, indicates that exposure to noise and to both high and low temperatures may also increase cardiovascular risk. There is considerably less research on the cardiovascular impacts of environmental conditions in low- and middle-income countries (LMICs), where the levels of pollution are often higher and the types and sources of pollution markedly different from those in higher-income settings. However, as such evidence gathers, actions to reduce exposures to pollution in low- and middle-income countries are warranted, not least because such exposures are very high. Cities, where pollution, populations, and other cardiovascular risk factors are most concentrated, may be best suited to reduce the cardiovascular burden in LMICs by applying environmental standards and policies to mitigate pollution and by implementing interventions that target the most vulnerable. The physical environment of cities can be improved though municipal processes, including infrastructure development, energy and transportation planning, and public health actions. Local regulations can incentivize or inhibit the polluting behaviors of industries and individuals. Environmental monitoring can be combined with public health warning systems and publicly available exposure maps to inform residents of environmental hazards and encourage the adoption of pollution-avoiding behaviors. Targeted individual or neighborhood interventions that identify and treat high-risk populations (e.g., lead mitigation, portable air cleaners, and preventative medications) can also be leveraged in the very near term. Research will play a key role in evaluating whether these approaches achieve their intended benefits, and whether these benefits reach the most vulnerable.

CONCLUSION

Cities in LMICs can play a defining role in global health and cardiovascular disease prevention in the next several decades, as they are well poised to develop innovative, multisectoral approaches to pollution mitigation, while also protecting the most vulnerable.

Ambient air pollution and health in Sub-Saharan Africa: Current evidence, perspectives and a call to action

BACKGROUND

People from low- and middle-income countries are disproportionately affected by the global burden of adverse health effects caused by ambient air pollution (AAP). However, data from Sub-Saharan Africa (SSA) are still scarce. We systematically reviewed the literature to describe the existing knowledge on AAP and health outcomes in SSA.

METHODS

We searched PubMed, Medline-OVID, EMBASE and Scopus databases to identify studies of AAP and health outcomes published up to November 15, 2017. We used a systematic review approach to critically analyze and summarize levels of outdoor air pollutants, and data on health effects associated with AAP. We excluded occupational and indoor exposure studies.

RESULTS

We identified 60 articles, with 37 only describing levels of AAP and 23 assessing the association between air pollution and health outcomes. Most studies (75%) addressing the relation between AAP and disease were cross-sectional. In general, exposure data were only obtained for selected cities in the framework of temporary international collaborative research initiatives without structural long-term continuation. Measurements of AAP revealed 10-20 fold higher levels than WHO standards. Of the 23 studies reporting health effects, 14 originated from South Africa, and most countries within SSA contributed no data at all. No studies, except from South Africa, were based on reliable morbidity or mortality statistics at regional or country level. The majority of studies investigated self-reported respiratory symptoms. Children and the elderly were found to be more susceptible to AAP.

CONCLUSION

AAP and its negative health effects have been understudied in SSA compared with other continents. The limited direct measurements of air pollutants indicate that AAP in SAA cities is high compared with international standards. Efforts are needed to monitor AAP in African cities, to identify its main sources, and to reduce adverse health effects by enforcing legislation.

Chemical and Biological Components of Urban Aerosols in Africa: Current Status and Knowledge Gaps

Aerosolized particulate matter (PM) is a complex mixture that has been recognized as the greatest cause of premature human mortality in low- and middle-income countries. Its toxicity arises largely from its chemical and biological components. These include polycyclic aromatic hydrocarbons (PAHs) and their nitro-derivatives (NPAHs) as well as microorganisms. In Africa, fossil fuel combustion and biomass burning in urban settings are the major sources of human exposure to PM, yet data on the role of aerosols in disease association in Africa remains scarce. This review is the first to examine studies conducted in Africa on both PAHs/NPAHs and airborne microorganisms associated with PM. These studies demonstrate that PM exposure in Africa exceeds World Health Organization (WHO) safety limits and carcinogenic PAHs/NPAHs and pathogenic microorganisms are the major components of PM aerosols. The health impacts of PAHs/NPAHs and airborne microbial loadings in PM are reviewed. This will be important for future epidemiological evaluations and may contribute to the development of effective management strategies to improve ambient air quality in the African continent.

Exposure to Outdoor Particles (PM2.5) and Associated Child Morbidity and Mortality in Socially Deprived Neighborhoods of Nairobi, Kenya

Exposure to air pollution is associated with adverse health outcomes. However, the health burden related to ambient outdoor air pollution in sub-Saharan Africa remains unclear. This study examined the relationship between exposure to outdoor air pollution and child health in urban slums of Nairobi, Kenya. We conducted a semi-ecological study among children under 5 years of age from two slum areas and exposure measurements of particulate matter (PM2.5) at the village level were aligned to data from a retrospective cohort study design. We used logistic and Poisson regression models to ascertain the associations between PM2.5 exposure level and child morbidity and mortality. Compared to those in low-pollution areas (PM2.5 < 25 µg/m3), children in high-pollution areas (PM2.5 ≥ 25 µg/m3) were at significantly higher risk for morbidity in general (odds ratio (OR) = 1.25, 95% confidence interval (CI): 1.11–1.41) and, specifically, cough (OR = 1.38, 95% CI: 1.20–1.48). Exposure to high levels of pollution was associated with a high child mortality rate from all causes (IRR = 1.22, 95% CI: 1.08–1.39) and respiratory causes (IRR = 1.12, 95% CI: 0.88–1.42). The findings indicate that there are associated adverse health outcomes with air pollution in urban slums. Further research on air pollution health impact assessments in similar urban areas is required.

Sources and levels of particulate matter in North African and Sub-Saharan cities: a literature review

In order to assess the significance of PM in ambient air, it is necessary to evaluate their physical and chemical characteristics as well as identify their major emission sources. On a global scale, particulate matter in the atmosphere arises mainly from the combustion process of motorized vehicles, but natural sources are still considered as the major contributors. In Africa, PM emissions differ from those in developed countries; human activities such as biomass burning in households, poor household waste management, and the high number of diesel-powered vehicles are the predominant anthropogenic sources. Natural contributions are also observed. Saharan dust and savanna fires are the most common atmospheric natural sources of particulate matter. The present literature review gives an overview of the status of air quality in African cities and highlights the various sources of particulate matter emissions and local human activities specific to each African region. This could likely serve as a reference to evaluate the current air quality in this region and will be a useful tool in the future to develop pollution mitigation strategies at the source. Recommendations are proposed in the conclusion in order to reduce emissions from their sources, taking into account the low-income African countries.

A Narrative Review on the Human Health Effects of Ambient Air Pollution in Sub-Saharan Africa: An Urgent Need for Health Effects Studies

An important aspect of the new sustainable development goals (SDGs) is a greater emphasis on reducing the health impacts from ambient air pollution in developing countries. Meanwhile, the burden of human disease attributable to ambient air pollution in sub-Saharan Africa is growing, yet estimates of its impact on the region are possibly underestimated due to a lack of air quality monitoring, a paucity of air pollution epidemiological studies, and important population vulnerabilities in the region. The lack of ambient air pollution epidemiologic data in sub-Saharan Africa is also an important global health disparity. Thousands of air pollution health effects studies have been conducted in Europe and North America, rather than in urban areas that have some of the highest measured air pollution levels in world, including urban areas in sub-Saharan Africa. In this paper, we provide a systematic and narrative review of the literature on ambient air pollution epidemiological studies that have been conducted in the region to date. Our review of the literature focuses on epidemiologic studies that measure air pollutants and relate air pollution measurements with various health outcomes. We highlight the gaps in ambient air pollution epidemiological studies conducted in different sub-regions of sub-Saharan Africa and provide methodological recommendations for future environmental epidemiology studies addressing ambient air pollution in the region.

Urban air pollution in Sub-Saharan Africa: Time for action

Air quality in cities of Sub-Saharan African (SSA) countries has deteriorated with the situation driven by rapid population growth and its attendant increased vehicle ownership, increased use of solid fuels for cooking and heating, and poor waste management practices. Industrial expansion in these cities is also a major contributor to the worsening air pollution. Exposure to ambient air pollution is a major threat to human health in SSA with 176,000 deaths and 626,000 DALYs in the region attributable to ambient air pollution exposure. These estimates are however likely to be much higher than reported due to the limited data emanating from the region. Recently, the adoption of the World Health Assembly resolution on air pollution and health, and Sustainable Development Goals are a welcome boost for urban air pollution control efforts in SSA. In this article, we have outlined within the broad framework of these international policy instruments, measures for addressing urban air pollution and its associated health impacts in SSA sustainably.

Hematological Differences among Malaria Patients in Rural and Urban Ghana

BACKGROUND

Scarce studies have addressed hematological differences of malaria in urban and rural regions.

METHODS

Full or complete blood cell counts from 46 and 75 individuals (age range from < 1 to 92 years) with uncomplicated malaria infection living in urban (Accra) and rural (Dodowa) Ghana, respectively, were assessed. Sickle cell trait and patients were excluded from the study.

RESULTS

Between overall groups, patients from Accra had significantly lower parasite count (p < 0.0001) and granulocyte number (p = 0.026). Children in Accra had a significantly lower parasitemia (p = 0.0013), hemoglobin (p = 0.0254), platelet count (p = 0.0148) and red blood cell levels (p = 0.0080) when compared with the children of Dodowa. In adults, mean cell hemoglobin (p = 0.0086) and parasite count (p < 0.0001) were significantly higher in Dodowa.

CONCLUSION

These results indicate that children living in urban setting may experience a greater anemic effect to malaria as compared with those living in a rural setting.

Measuring exposure levels of inhalable airborne particles (PM2.5) in two socially deprived areas of Nairobi, Kenya

INTRODUCTION

Ambient air pollution is a growing global health concern tightly connected to the rapid global urbanization. Health impacts from outdoor air pollution exposure amounts to high burdens of deaths and disease worldwide. However, the lack of systematic collection of air pollution and health data in many low-and middle-income countries remains a challenge for epidemiological studies in the local environment. This study aimed to provide a description of the particulate matter (PM2.5) concentration in the poorest urban residential areas of Nairobi, Kenya.

METHODS

Real-time measurements of (PM2.5) were conducted in two urban informal settlements of Nairobi City, Kenya"s Capital, from February 2013 to October 2013. The measurements were conducted using DustTrak II 8532 hand-held samplers at a height of about 1.5m above ground level with a resolution of 1-min logging. Sampling took place from early morning to evenings according to a fixed route of measurement within areas including fixed geographical checkpoints.

RESULTS

The study period average concentration of PM2.5 was 166μg/m(3) in the Korogocho area and 67μg/m(3) in the Viwandani area. The PM2.5 levels in both areas reached bimodal daily peaks in the morning and evening. The average peak value of morning concentration in Korogocho was 214μg/m(3), and 164μg/m(3) in the evening and in Viwandani was 76μg/m(3) and 82μg/m(3) respectively. The daily mid-day average low observed during was 146μg/m(3) in Korogocho and 59μg/m(3) in Viwandani.

CONCLUSION

The results show that residents in both slums are continuously exposed to PM2.5 levels exceeding hazardous levels according to World Health Organization guidelines. The study showed a marked disparity between the two slum areas situated only 7km apart indicating the local situation and sources to be very important for exposure to PM2.5.

"What We Breathe Impacts Our Health: Improving Understanding of the Link between Air Pollution and Health"

Air pollution contributes to the premature deaths of millions of people each year around the world, and air quality problems are growing in many developing nations. While past policy efforts have succeeded in reducing particulate matter and trace gases in North America and Europe, adverse health effects are found at even these lower levels of air pollution. Future policy actions will benefit from improved understanding of the interactions and health effects of different chemical species and source categories. Achieving this new understanding requires air pollution scientists and engineers to work increasingly closely with health scientists. In particular, research is needed to better understand the chemical and physical properties of complex air pollutant mixtures, and to use new observations provided by satellites, advanced in situ measurement techniques, and distributed micro monitoring networks, coupled with models, to better characterize air pollution exposure for epidemiological and toxicological research, and to better quantify the effects of specific source sectors and mitigation strategies.

Exposure to particulate matter in India: A synthesis of findings and future directions

Air pollution poses a critical threat to human health with ambient and household air pollution identified as key health risks in India. While there are many studies investigating concentration, composition, and health effects of air pollution, investigators are only beginning to focus on estimating or measuring personal exposure. Further, the relevance of exposures studies from the developed countries in developing countries is uncertain. This review summarizes existing research on exposure to particulate matter (PM) in India, identifies gaps and offers recommendations for future research. There are a limited number of studies focused on exposure to PM and/or associated health effects in India, but it is evident that levels of exposure are much higher than those reported in developed countries. Most studies have focused on coarse aerosols, with a few studies on fine aerosols. Additionally, most studies have focused on a handful of cities, and there are many unknowns in terms of ambient levels of PM as well as personal exposure. Given the high mortality burden associated with air pollution exposure in India, a deeper understanding of ambient pollutant levels as well as source strengths is crucial, both in urban and rural areas. Further, the attention needs to expand beyond the handful large cities that have been studied in detail.

Personal particulate matter exposures and locations of students in four neighborhoods in Accra, Ghana

Air pollution exposure and places where the exposures occur may differ in cities in the developing world compared with high-income countries. Our aim was to measure personal fine particulate matter (PM2.5) exposure of students in neighborhoods of varying socioeconomic status in Accra, Ghana, and to quantify the main predictors of exposure. We measured 24-hour PM2.5 exposure of 56 students from eight schools in four neighborhoods. PM2.5 was measured both gravimetrically and continuously, with time-matched global positioning system coordinates. We collected data on determinants of exposure, such as distances of homes and schools from main roads and fuel used for cooking at their home or in the area of residence/school. The association of PM2.5 exposure with sources was estimated using linear mixed-effects models. Personal PM2.5 exposures ranged from less than 10 μg/m(3) to more than 150 μg/m(3) (mean 56 μg/m(3)). Girls had higher exposure than boys (67 vs 44 μg/m(3); P-value=0.001). Exposure was inversely associated with distance of home or school to main roads, but the associations were not statistically significant in the multivariate model. Use of biomass fuels in the area where the school was located was also associated with higher exposure, as was household's own biomass use. Paved schoolyard surface was associated with lower exposure. School locations in relation to major roads, materials of school ground surfaces, and biomass use in the area around schools may be important determinants of air pollution exposure.

Agency, access, and Anopheles: neighborhood health perceptions and the implications for community health interventions in Accra, Ghana

Background

Social and environmental factors are increasingly recognized for their ability to influence health outcomes at both individual and neighborhood scales in the developing urban world. Yet issues of spatial heterogeneity in these complex environments may obscure unique elements of neighborhood life that may be protective or harmful to human health. Resident perceptions of neighborhood effects on health may help to fill gaps in our interpretation of household survey results and better inform how to plan and execute neighborhood-level health interventions.

Objective

We evaluate differences in housing and socioeconomic indicators and health, environment, and neighborhood perceptions derived from the analysis of a household survey and a series of focus groups in Accra, Ghana. We then explore how neighborhood perceptions can inform survey results and ultimately neighborhood-level health interventions.

Design

Eleven focus groups were conducted across a socioeconomically stratified sample of neighborhoods in Accra, Ghana. General inductive themes from the focus groups were analyzed in tandem with data collected in a 2009 household survey of 2,814 women. In-depth vignettes expand upon the three most salient emergent themes.

Results

Household and socioeconomic characteristics derived from the focus groups corroborated findings from the survey data. Focus group and survey results diverged for three complex health issues: malaria, health-care access, and sense of personal agency in promoting good health.

Conclusion

Three vignettes reflecting community views about malaria, health-care access, and sense of personal agency in promoting good health highlight the challenges facing community health interventions in Accra and exemplify how qualitatively derived neighborhood-level health effects can help shape health interventions.

Inhalable desert dust, urban emissions, and potentially biotoxic metals in urban Saharan-Sahelian air

Saharan dust incursions and particulates emitted from human activities degrade air quality throughout West Africa, especially in the rapidly expanding urban centers in the region. Particulate matter (PM) that can be inhaled is strongly associated with increased incidence of and mortality from cardiovascular and respiratory diseases and cancer. Air samples collected in the capital of a Saharan-Sahelian country (Bamako, Mali) between September 2012 and July 2013 were found to contain inhalable PM concentrations that exceeded World Health Organization (WHO) and US Environmental Protection Agency (USEPA) PM2.5 and PM10 24-h limits 58 - 98% of days and European Union (EU) PM10 24-h limit 98% of days. Mean concentrations were 1.2-to-4.5 fold greater than existing limits. Inhalable PM was enriched in transition metals, known to produce reactive oxygen species and initiate the inflammatory response, and other potentially bioactive and biotoxic metals/metalloids. Eroded mineral dust composed the bulk of inhalable PM, whereas most enriched metals/metalloids were likely emitted from oil combustion, biomass burning, refuse incineration, vehicle traffic, and mining activities. Human exposure to inhalable PM and associated metals/metalloids over 24-h was estimated. The findings indicate that inhalable PM in the Sahara-Sahel region may present a threat to human health, especially in urban areas with greater inhalable PM and transition metal exposure.

Increased risk of respiratory illness associated with kerosene fuel use among women and children in urban Bangalore, India

BACKGROUND

Kerosene is a widely used cooking and lighting fuel in developing countries. The potential respiratory health effects of cooking with kerosene relative to cooking with cleaner fuels such as liquefied petroleum gas (LPG) have not been well characterised.

METHODS

We sampled 600 households from six urban neighbourhoods in Bangalore, India. Each household's primary cook, usually the woman of the house, was interviewed to collect information on current domestic fuel use and whether there was any presence of respiratory symptoms or illness in her or in the children in the household. Our analysis was limited to 547 adult females (ages 18-85) and 845 children (ages 0-17) in households exclusively cooking with either kerosene or LPG. We investigated the associations between kerosene use and the likelihood of having respiratory symptoms or illness using multivariate logistic regression models.

RESULTS

Among adult women, cooking with kerosene was associated with cough (OR=1.88; 95% CI 1.19 to 2.99), bronchitis (OR=1.54; 95% CI 1.00 to 2.37), phlegm (OR=1.51; 95% CI 0.98 to 2.33) and chest illness (OR=1.61; 95% CI 1.02 to 2.53), relative to cooking with LPG in the multivariate models. Among children, living in a household cooking with kerosene was associated with bronchitis (OR=1.91; 95% CI 1.17 to 3.13), phlegm (OR=2.020; 95% CI 1.29 to 3.74) and chest illness (OR=1.70; 95% CI 0.99 to 2.90) after adjusting for other covariates. We also found associations between kerosene use and wheezing, difficulty breathing and asthma in adults and cough and wheezing in children, though these associations were not statistically significant.

CONCLUSIONS

Women and children in households cooking with kerosene were more likely to have respiratory symptoms and illnesses compared with those in households cooking with LPG. Transitioning from kerosene to LPG for cooking may improve respiratory health among adult women and children in this population.

Differences in health symptoms among residents living near illegal dump sites in Los Laureles Canyon, Tijuana, Mexico: a cross sectional survey

Living near landfills is a known health hazard prompting recognition of environmental injustice. The study aim was to compare self-reported symptoms of ill health among residents of four neighborhoods, living in haphazardly constructed settlements surrounded by illegal dumpsites in Tijuana, Mexico. One adult from each of 388 households located in Los Laureles Canyon were interviewed about demographics, health status, and symptoms. Distance from each residence to both the nearest dumpsite and the canyon bottom was assessed. The neighborhoods were selected from locations within the canyon, and varied with respect to proximity to dump sites. Residents of San Bernardo reported significantly higher frequencies of ill-health symptoms than the other neighborhoods, including extreme fatigue (OR 3.01 (95% CI 1.6-5.5)), skin problems/irritations (OR 2.73 (95% CI 1.3-5.9)), stomach discomfort (OR 2.47 (1.3-4.8)), eye irritation/tears (OR 2.02 (1.2-3.6)), and confusion/difficulty concentrating (OR 2.39 (1.2-4.8)). Proximity to dumpsites did not explain these results, that varied only slightly when adjusted for distance to nearest dumpsite or distance to the canyon bottom. Because San Bernardo has no paved roads, we hypothesize that dust and the toxicants it carries is a possible explanation for this difference. Studies are needed to further document this association and sources of toxicants.

Land use regression models to estimate the annual and seasonal spatial variability of sulfur dioxide and particulate matter in Tehran, Iran

The Middle Eastern city of Tehran, Iran has poor air quality compared with cities of similar size in Europe and North America. Spatial annual and seasonal patterns of SO2 and PM10 concentrations were estimated using land use regression (LUR) methods applied to data from 21 air quality monitoring stations. A systematic algorithm for LUR model building was developed to select variables based on (1) consistency with a priori assumptions about the assumed directions of the effects, (2) a p-value of <0.1 for each predictor, (3) improvements to the leave-one-out cross-validation (LOOCV) R(2), (4) a multicollinearity index called the variance inflation factor, and (5) a grouped (leave-25%-out) cross-validation (GCV) for final model. In addition, several new predictive variables and variable types were explored. The annual mean concentrations of SO2 and PM10 across the stations were 38 ppb and 100.8 μg/m(3), respectively. The R(2) values ranged from 0.69 to 0.84 for SO2 models and from 0.62 to 0.67 for PM10 models. The LOOCV and GCV R(2) values ranged, respectively, from 0.40 to 0.56 and 0.40 to 0.50 for the SO2 models; they were 0.48 to 0.57 and 0.50 to 0.55, respectively, for the PM10 models. There were clear differences between the SO2 and PM10 models, but the warmer and cooler season models were consistent with the annual models for both pollutants. Although there was limited similarity between the SO2 and PM10 predictive variables, measures of street density and proximity to airport or air cargo facilities were consistent across both pollutants. In 2010, the entire population of Tehran lived in areas where the World Health Organization guidelines for 24-hour mean SO2 (7 ppb) and annual average PM10 (20 μg/m(3)) were exceeded.

Proinflammatory effects and oxidative stress within human bronchial epithelial cells exposed to atmospheric particulate matter (PM(2.5) and PM(>2.5)) collected from Cotonou, Benin

After particulate matter (PM) collection in Cotonou (Benin), a complete physicochemical characterization of PM2.5 and PM>2.5 was led. Then, their adverse health effects were evaluated by using in vitro culture of human lung cells. BEAS-2B (bronchial epithelial cells) were intoxicated during short-term exposure at increasing PM concentrations (1.5-96 μg/cm(2)) to determine global cytotoxicity. Hence, cells were exposed to 3 and 12 μg/cm(2) to investigate the potential biological imbalance generated by PM toxicity. Our findings showed the ability of both PM to induce oxidative stress and to cause inflammatory cytokines/chemokines gene expression and secretion. Furthermore, PM were able to induce gene expression of enzymes involved in the xenobiotic metabolism pathway. Strong correlations between gene expression of metabolizing enzymes, proinflammatory responses and cell cycle alteration were found, as well as between proinflammatory responses and cell viability. Stress oxidant parameters were highly correlated with expression and protein secretion of inflammatory mediators.

An assessment of air pollution and its attributable mortality in Ulaanbaatar, Mongolia

Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM_2.5) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasibility of two current exposure assessment techniques, land use regression (LUR) modeling and mobile monitoring, and estimated the mortality attributable to air pollution in Ulaanbaatar, Mongolia. We developed LUR models for predicting wintertime spatial patterns of NO₂ and SO₂ based on 2-week passive Ogawa measurements at 37 locations and freely available geographic predictors. The models explained 74% and 78% of the variance in NO₂ and SO₂, respectively. Land cover characteristics derived from satellite images were useful predictors of both pollutants. Mobile PM_2.5 monitoring with an integrating nephelometer also showed promise, capturing substantial spatial variation in PM_2.5 concentrations. The spatial patterns in SO₂ and PM, seasonal and diurnal patterns in PM_2.5, and high wintertime PM_2.5/PM₁₀ ratios were consistent with a major impact from coal and wood combustion in the city's low-income traditional housing (ger) areas. The annual average concentration of PM_2.5 measured at a centrally located government monitoring site was 75 μg/m³ or more than seven times the World Health Organization's PM_2.5 air quality guideline, driven by a wintertime average concentration of 148 μg/m³. PM_2.5 concentrations measured in a traditional housing area were higher, with a wintertime mean PM_2.5 concentration of 250 μg/m³. We conservatively estimated that 29% (95% CI, 12-43%) of cardiopulmonary deaths and 40% (95% CI, 17-56%) of lung cancer deaths in the city are attributable to outdoor air pollution. These deaths correspond to nearly 10% of the city's total mortality, with estimates ranging to more than 13% of mortality under less conservative model assumptions. LUR models and mobile monitoring can be successfully implemented in developing country cities, thus cost-effectively improving exposure assessment for epidemiology and risk assessment. Air pollution represents a major threat to public health in Ulaanbaatar, Mongolia, and reducing home heating emissions in traditional housing areas should be the primary focus of air pollution control efforts.

The Aeroflex: a bicycle for mobile air quality measurements

Fixed air quality stations have limitations when used to assess people's real life exposure to air pollutants. Their spatial coverage is too limited to capture the spatial variability in, e.g., an urban or industrial environment. Complementary mobile air quality measurements can be used as an additional tool to fill this void. In this publication we present the Aeroflex, a bicycle for mobile air quality monitoring. The Aeroflex is equipped with compact air quality measurement devices to monitor ultrafine particle number counts, particulate mass and black carbon concentrations at a high resolution (up to 1 second). Each measurement is automatically linked to its geographical location and time of acquisition using GPS and Internet time. Furthermore, the Aeroflex is equipped with automated data transmission, data pre-processing and data visualization. The Aeroflex is designed with adaptability, reliability and user friendliness in mind. Over the past years, the Aeroflex has been successfully used for high resolution air quality mapping, exposure assessment and hot spot identification. 

A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010

BACKGROUND

Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time.

METHODS

We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden.

FINDINGS

In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2-7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5-7·0]), and alcohol use (5·5% [5·0-5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8-9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6-8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4-6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2-10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4-1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania.

INTERPRETATION

Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children.

FUNDING

Bill & Melinda Gates Foundation.

Spatial and temporal patterns of particulate matter sources and pollution in four communities in Accra, Ghana

Sources of air pollution in developing country cities include transportation and industrial pollution, biomass fuel use, and re-suspended dust from unpaved roads. We examined the spatial patterns of particulate matter (PM) and its sources in four neighborhoods of varying socioeconomic status (SES) in Accra. PM data were from 1 week of morning and afternoon mobile and stationary air pollution measurements in each of the study neighborhoods. PM(2.5) and PM(10) were measured continuously, with matched GPS coordinates. Data on biomass fuel use were from the Ghana 2000 population and housing census and from a census of wood and charcoal stoves along the mobile monitoring paths. We analyzed the associations of PM with sources using a mixed-effects regression model accounting for temporal and spatial autocorrelation. After adjusting for other factors, the density of wood stoves, fish smoking, and trash burning along the mobile monitoring path as well as road capacity and surface were associated with higher PM(2.5). Road capacity and road surface variables were also associated with PM(10), but the association with biomass sources was weak or absent. While wood stoves and fish smoking were significant sources of air pollution, addressing them would require financial and physical access to alternative fuels for low-income households and communities.

Effective mitigation efforts to reduce road dust near industrial sites: assessment by mobile pollution surveys

Assessment of spatial variation of fugitive dust sources, particularly road dust track-out from industrial sites and its subsequent re-suspension is difficult with fixed air quality monitoring stations given their sparse distribution and the highly localized nature of road dust. Mobile monitoring was employed to measure levels of road dust in the industrial area of the City of Hamilton, Ontario, Canada. Results of this monitoring were used in a Fugitive Dust Control workshop held for local stakeholders, where fugitive dust control solutions were presented. After the workshop, the City of Hamilton and cooperative industrial groups executed enhanced street cleaning and individual industries and facilities performed on-site control activities. Post-workshop mobile air monitoring was performed for comparison to the initial values to determine effectiveness of these approaches. A regression model testing the difference pre- and post-workshop yielded a statistically significant difference in PM(10) measurements demonstrating improvement. The average value of PM(10) prior to the workshop was 114 μg/m(3). Post-workshop the average value dropped to 73 μg/m(3).

Intra-urban air pollution in a rapidly growing Sahelian city

In this paper we analyze spatial and temporal variations of air pollution (PM(1), PM(2.5), PM(10), CO, NO(x), O(3), Toluene and Benzene) and climate in areas of different development typology in Ouagadougou, Burkina Faso. Analyses are based on measurements from fixed sites and car traverse measurements during field studies in 2007 and 2010. Large spatial and temporal variations were found, showing a generally poor air quality situation, with extreme levels of PM(10), commonly exceeding air quality guidelines of WHO. Pollution levels increase considerably with increased atmospheric stability. Important sources were transported dust and re-suspension of dust from unpaved roads, but also traffic emissions and biomass burning. The spatial variations are examined with focus on effects for variations in potential exposure depending on for example area of residence and daily activity pattern, showing that great differences are likely to exist. Ouagadougou, like most developing countries worldwide, currently experiences an extremely rapid population growth in combination with limited financial means. This is likely to create increasingly harmful air pollution situations for the rapidly growing populations of these areas, and shows an urgent need for increased understanding of the pollution situation as well as development of mitigation strategies.

Household and community poverty, biomass use, and air pollution in Accra, Ghana

Many urban households in developing countries use biomass fuels for cooking. The proportion of household biomass use varies among neighborhoods, and is generally higher in low socioeconomic status (SES) communities. Little is known of how household air pollution varies by SES and how it is affected by biomass fuels and traffic sources in developing country cities. In four neighborhoods in Accra, Ghana, we collected and analyzed geo-referenced data on household and community particulate matter (PM) pollution, SES, fuel use for domestic and small-commercial cooking, housing characteristics, and distance to major roads. Cooking area PM was lowest in the high-SES neighborhood, with geometric means of 25 (95% confidence interval, 21-29) and 28 (23-33) μg/m(3) for fine and coarse PM (PM(2.5) and PM(2.5-10)), respectively; it was highest in two low-SES slums, with geometric means reaching 71 (62-80) and 131 (114-150) μg/m(3) for fine and coarse PM. After adjustment for other factors, living in a community where all households use biomass fuels would be associated with 1.5- to 2.7-times PM levels in models with and without adjustment for ambient PM. Community biomass use had a stronger association with household PM than household's own fuel choice in crude and adjusted estimates. Lack of regular physical access to clean fuels is an obstacle to fuel switching in low-income neighborhoods and should be addressed through equitable energy infrastructure.