Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors
<p>East African countries face an increasing threat from poor air quality stemming from rapid urbanization, population growth, and a steep rise in fuel use and motorization rates. With few air quality monitoring systems available, this study provides much needed high temporal resolution da...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-10-01
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Series: | Atmospheric Chemistry and Physics |
Online Access: | https://www.atmos-chem-phys.net/18/15403/2018/acp-18-15403-2018.pdf |
Summary: | <p>East African countries face an increasing threat
from poor air quality stemming from rapid urbanization, population growth,
and a steep rise in fuel use and motorization rates. With few air quality
monitoring systems available, this study provides much needed high temporal
resolution data to investigate the concentrations of particulate matter (PM)
air pollution in Kenya. Calibrated low-cost optical particle counters (OPCs)
were deployed in Kenya in three locations: two in the capital Nairobi and
one in a rural location in the outskirts of Nanyuki, which is upwind of
Nairobi. The two Nairobi sites consist of an urban background site and a
roadside site. The instruments were composed of an AlphaSense OPC-N2 ran with a Raspberry Pi low-cost microcomputer,
packaged in a weather-proof box. Measurements were conducted over a 2-month
period (February–March 2017) with an intensive study period when all
measurements were active at all sites lasting 2 weeks. When collocated, the
three OPC-N2 instruments demonstrated good inter-instrument precision with a
coefficient of variance of 8.8±2.0 % in the fine particle fraction
(PM<sub>2.5</sub>). The low-cost sensors had an absolute PM mass concentration
calibration using a collocated gravimetric measurement at the urban
background site in Nairobi.</p><p>The mean daily PM<sub>1</sub> mass concentration measured at the urban
roadside, urban background and rural background sites were 23.9, 16.1
and 8.8 µg m<sup>−3</sup>, respectively. The mean daily PM<sub>2.5</sub> mass concentration
measured at the urban roadside, urban background and rural background sites
were 36.6, 24.8 and 13.0 µg m<sup>−3</sup>, respectively. The mean daily PM<sub>10</sub>
mass concentration measured at the urban roadside, urban background and rural
background sites were 93.7, 53.0 and 19.5 µg m<sup>−3</sup>, respectively. The urban
measurements in Nairobi showed that PM concentrations
regularly exceed WHO guidelines in both the PM<sub>10</sub> and
PM<sub>2.5</sub> size ranges. Following a <q>Lenschow</q>-type approach we can
estimate the urban and roadside increments that are applicable to Nairobi
(Lenschow et al., 2001). The median urban increment is
33.1 µg m<sup>−3</sup> and the median roadside increment is
43.3 µg m<sup>−3</sup> for PM<sub>2.5</sub>. For PM<sub>1</sub>, the
median urban increment is 4.7 µg m<sup>−3</sup> and the median roadside
increment is 12.6 µg m<sup>−3</sup>. These increments highlight the
importance of both the urban and roadside increments to urban air pollution
in Nairobi.</p><p>A clear diurnal behaviour in PM mass concentration was observed at both
urban sites, which peaks during the morning and evening Nairobi rush hours;
this was consistent with the high roadside increment indicating
that vehicular traffic is a dominant source of PM in the
city, accounting for approximately 48.1 %, 47.5 % and 57.2 % of the total
PM loading in the PM<sub>10</sub>, PM<sub>2.5</sub> and PM<sub>1</sub> size
ranges, respectively. Collocated meteorological measurements at the urban
sites were collected, allowing for an understanding of the location of major
sources of particulate matter at the two sites. The potential problems of
using low-cost sensors for PM measurement without gravimetric calibration
available at all sites are discussed.</p><p>This study shows that calibrated low-cost sensors can be successfully used
to measure air pollution in cities like Nairobi. It demonstrates that low-cost
sensors could be used to create an affordable and reliable network to
monitor air quality in cities.</p> |
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ISSN: | 1680-7316 1680-7324 |