Abstract:
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.
摘要:
道路交通已成为快速增长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理解与燃烧相关的排放和暴露的时空变化和不平等。我们结合了大阿克拉都市区(GAMA)134个地点的二氧化氮(NO2)和一氧化氮(NO)测量数据,地理上,气象,和时空混合效应模型中的人口因素,可在整个GAMA上以精细的空间(50m)和时间(每周)分辨率预测NO2和NO的浓度。用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。这些预测被用来检查人口分布,和社会经济不平等,人口普查枚举区(EA)级别的暴露。模型解释了88%和79%的NO2和NO浓度的时空变异性,分别。平均预测年度,非Harmattan和HarmattanNO2水平为37(范围:1-189),28(范围:1-170)和50(范围:1-195)µgm-3。与NO2不同,非Harmattan季节的NO浓度最高(41[范围:31-521]µgm-3)。道路交通是两种污染物的主要因素,但NO2比NO具有更高的空间异质性。对于这两种污染物,城市核心的水平要高得多,其中整个人口(100%)暴露于超过世界卫生组织(WHO)10µgm-3的年度NO2水平。NO2浓度在社会经济梯度上存在显著差异,与最富有的社区相比,最贫穷社区的居民暴露于约15µgm-3的水平高(p<0.001)。结果表明,在GAMA中,道路交通排放对空气污染浓度具有重要作用,这对该市最贫困居民的健康有重大影响。这些数据可以支持城市的气候和健康影响评估以及政策评估。