埃塞俄比亚阿尔巴明奇利用低成本传感器和学生科学测量的路边 PM2.5 浓度

Jan Dirk Dingemanse, M. Tadele, Tewodros Zerihun Tadesse
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引用次数: 0

摘要

接触 PM2.5 是最大的健康威胁之一,在低收入国家的城市地区,交通和生物质燃烧是主要来源。在埃塞俄比亚,这两种来源的结合表明路边暴露量很高。由于缺乏收集数据的资源,埃塞俄比亚只进行了很少的路边暴露研究。使用低成本传感器和学生科学可以部分弥补资源的不足。在为期六周的时间里,学生们利用自制的低成本传感器在阿尔巴明奇的四个固定地点和两辆公共交通三轮车内收集了 PM2.5 数据。对数据进行了分析,以深入了解浓度水平、时间变化、空间变化以及路旁和路面浓度之间的差异。平均浓度范围为 13-36 微克/立方米。早晨时段的浓度最高(6:00-10:00 为 42 ± 12,10:00-17:00 和 17:00-21:00 分别为 20 ± 1 和 32 ± 4),当地公交车站的浓度最高(36.2 微克/立方米)。路边的浓度变化最大,平均高于路旁的浓度(33 ± 25 和 30 ± 22 µg/m3 对 23.3 ± 18 和 22.6 ± 18 µg/m3)。从日均水平来看,不同地点的浓度显示出很高的相关性(R2 0.8-0.95)。这表明可以将一个地点的浓度插值到其他地点。此外,PM2.5 浓度超过了空气质量准则。在埃塞俄比亚,有十多个城市的人口和交通流量高于阿尔巴明奇。在这些城市,预计会出现类似或更高的超标情况。以这项研究为例,其他大学同样可以在其所在城市利用低成本传感器和学生科学开展研究。在应用这些方法时,课程教师和大学之间的合作将提高对埃塞俄比亚城市 PM2.5 暴露的洞察力。关键词:环境空气污染;交通;Sensirion SPS30;学生测量;颗粒物
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Roadside PM2.5 concentrations measured with low-cost sensors and student science in Arba Minch, Ethiopia
Exposure to PM2.5 poses one of the biggest health threats, with traffic and biomass burning as dominant sources in urban areas of low-income countries. In Ethiopia, the combination of these two sources suggests a high roadside exposure. Because of a lack of resources for data collection, only few studies were conducted on roadside exposure in Ethiopia. Using low-cost sensors and student science could partially remedy this lack of resources. Students collected PM2.5 data in Arba Minch at four stationary locations and inside two public transport tricycles during a period of six weeks with self-made low-cost sensors. Data was analyzed to gain insight into concentration levels, temporal variation, spatial variation, and difference between next to the road and on-road concentrations. Average concentrations ranged from 13-36 µg/m3. Concentrations were highest during morning hours (42 ± 12 for hours 6:00-10:00, versus 20 ± 1 and 32 ± 4 for 10:00-17:00 and 17:00-21:00, respectively), and concentrations were highest at the local bus station (36.2 µg/m3). On-road concentrations showed the highest variation and were on average higher than concentrations next to the road (33 ± 25 and 30 ± 22 µg/m3 versus 23.3 ± 18 and 22.6 ± 18 µg/m3). On a daily average level, concentrations at different locations showed a high correlation (R2 0.8-0.95) amongst each other. This suggests the possibility to interpolate concentrations from one location to other locations. Moreover, the PM2.5 concentrations exceeded air quality guidelines. In Ethiopia, more than ten cities have higher populations and traffic flows than Arba Minch. In those cities, similar or higher exceedances are expected. With this study as an example, other universities could likewise conduct research with low-cost sensors and student science in their cities. Cooperation across course instructors and universities in applying these methods will increase the insight in PM2.5 exposure in Ethiopian cities. Keywords: ambient air pollution; traffic; Sensirion SPS30; student measurements; Particulate Matter
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