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.

中文翻译：

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撒哈拉以南非洲城市空气污染的不平等：加纳阿克拉环境 NO 和 NO2 浓度的实证模型

道路交通已成为快速发展的撒哈拉以南非洲城市空气污染的主要来源。然而，缺乏可靠的全市数据来了解燃烧相关排放和暴露的时空变化和不平等。我们将大阿克拉都市区 (GAMA) 134 个地点的二氧化氮 (NO ₂ ) 和一氧化氮 (NO) 测量数据与时空混合效应模型中的地理、气象和人口因素相结合，以预测 NO ₂和 NO整个 GAMA 范围内精细空间（50 m）和时间（每周）分辨率的浓度。通过 10 倍交叉验证 (CV) 评估模型性能，并将预测总结为年度和季节性（多尘 [Harmattan] 和多雨 [非 Harmattan]）平均浓度。这些预测用于检查人口普查查点区 (EA) 层面的人口分布和暴露的社会经济不平等。该模型分别解释了 NO ₂和 NO 浓度的 88% 和 79% 的时空变异性。非 Harmattan 和 Harmattan NO _{2 的}平均预测年度水平为 37（范围：1–189）、28（范围：1–170）和 50（范围：1–195）µ分别为gm ^-3。与 NO ₂不同，NO 浓度在非 Harmattan 季节最高（41 [范围：31–521]µgm ^-3 )。道路交通是两种污染物的主导因素，但NO ₂的空间异质性高于NO。对于这两种污染物，市中心的水平要高得多，那里的全体人口 (100%) 每年接触的二氧化氮_水平超过了世界卫生组织 (WHO) 10 的指导值µgm ^-3。不同社会经济梯度的 NO ₂浓度存在显着差异，最贫困社区的居民接触的水平约为 15µ与最富有的人相比，gm ^{−3更高（}p< 0.001）。结果表明，道路交通排放在 GAMA 空气污染浓度中发挥着重要作用，这对该市最贫困居民的健康具有重大影响。这些数据可以支持该城市的气候和健康影响评估以及政策评估。