Browsing by Author "Alli, A.S."
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Item Characterisation of urban environment and activity across space and time using street images and deep learning in Accra(Scientific reports, 2022) Nathvani, R.; Clark, S.N.; Muller, E.; Alli, A.S.; Bennett, J.E.; Nimo, J.; Moses, J.B.; Baah, S.; Metzler, A.B.; Brauer, M.; Suel, E.; Hughes, A.F.; Agyemang, E.; Owusu, G.; Agyei‑Mensah, S.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.Item Spatial modelling and inequalities of environmental noise in Accra, Ghana(Elsevier Inc, 2022) Clark, S.N.; Alli, A.S.; Ezzati, M.; Moses, B.; Agyei-Mensah, S.; Owusu, G.; et al.A B S T R A C T Noise pollution is a growing environmental health concern in rapidly urbanizing sub-Saharan African (SSA) cities. However, limited city-wide data constitutes a major barrier to investigating health impacts as well as implementing environmental policy in this growing population. As such, in this first of its kind study in West Africa, we measured, modelled and predicted environmental noise across the Greater Accra Metropolitan Area (GAMA) in Ghana, and evaluated inequalities in exposures by socioeconomic factors. Specifically, we measured environmental noise at 146 locations with weekly (n = 136 locations) and yearlong monitoring (n = 10 locations). We combined these data with geospatial and meteorological predictor variables to develop highresolution land use regression (LUR) models to predict annual average noise levels (LAeq24hr, Lden, Lday, Lnight). The final LUR models were selected with a forward stepwise procedure and performance was evaluated with cross-validation. We spatially joined model predictions with national census data to estimate population levels of, and potential socioeconomic inequalities in, noise levels at the census enumeration-area level. Variables representing road-traffic and vegetation explained the most variation in noise levels at each site. Predicted dayevening- night (Lden) noise levels were highest in the city-center (Accra Metropolis) (median: 64.0 dBA) and near major roads (median: 68.5 dBA). In the Accra Metropolis, almost the entire population lived in areas where predicted Lden and night-time noise (Lnight) surpassed World Health Organization guidelines for road-traffic noise (Lden <53; and Lnight <45). The poorest areas in Accra also had significantly higher median Lden and Lnight compared with the wealthiest ones, with a difference of ~5 dBA. The models can support environmental epidemiological studies, burden of disease assessments, and policies and interventions that address underlying causes of noise exposure inequalities within Accra.Item Spatial-temporal patterns of ambient fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra(IOP publishing ltd, 2021) Alli, A.S.; Clark, S.N.; Hughes, A.; Nimo, J.; Bedford-Moses, J.; Baah, S.; Wang, J.; Vallarino, J.; Agyemang, E.; Barratt, B.; Beddows, A.; Kelly, F.; Owusu, G.; Baumgartne, J.; Brauer, M.; Ezzati, M.; Agyei-Mensah, S.; Arku, R.E.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.