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Roadside PM2.5 concentrations measured with low-cost sensors and student science in Arba Minch, Ethiopia

Dingemanse, Johannes Dirk LU orcid ; Tadele, Mekdes Dawit and Tadesse, Tewodros Zerihun (2024) In Ethiopian Journal of Water Science and Technology 5 (2022). p.51-73
Abstract
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... (More)
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. (Less)
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author
; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Ambient air pollution, Traffic, Sensirion SPS30, Student measurements, Particulate matter (PM )
in
Ethiopian Journal of Water Science and Technology
volume
5 (2022)
pages
23 pages
ISSN
2220-7643
DOI
10.59122/15519k8
project
Low-cost research methods in Ethiopia
language
English
LU publication?
no
id
057d7c46-2027-418f-b7b1-ba7ba4a4edd7
date added to LUP
2024-10-25 07:24:38
date last changed
2025-04-04 13:54:34
@article{057d7c46-2027-418f-b7b1-ba7ba4a4edd7,
  abstract     = {{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.}},
  author       = {{Dingemanse, Johannes Dirk and Tadele, Mekdes Dawit and Tadesse, Tewodros Zerihun}},
  issn         = {{2220-7643}},
  keywords     = {{Ambient air pollution; Traffic; Sensirion SPS30; Student measurements; Particulate matter (PM )}},
  language     = {{eng}},
  month        = {{01}},
  pages        = {{51--73}},
  series       = {{Ethiopian Journal of Water Science and Technology}},
  title        = {{Roadside PM2.5 concentrations measured with low-cost sensors and student science in Arba Minch, Ethiopia}},
  url          = {{http://dx.doi.org/10.59122/15519k8}},
  doi          = {{10.59122/15519k8}},
  volume       = {{5 (2022)}},
  year         = {{2024}},
}