Spatial-Temporal Variation And Local Source Identification Of Air Pollutants In A Semi-Urban Settlement In Nigeria Using Low-Cost Sensors

AEROSOL AND AIR QUALITY RESEARCH(2021)

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摘要
Low-cost sensors were deployed at five locations in a growing, semi-urban settlement in southwest Nigeria between June 8 and July 31, 2018 to measure particulate matter (PM2.5 and PM10), gaseous pollutants (CO, NO, NO2, O-3 and CO2), and meteorological variables (air temperature, relative humidity, wind speed and wind-direction). The spatial and temporal variations of measured pollutants were determined, and the probable sources of pollutants were inferred using conditional bivariate probability function (CBPF). Hourly PM2.5 and PM10 concentrations ranged from 20.7 +/- 0.7 to 36.3 +/- 1.6 mu g m(-3) and 47.5 +/- 1.5 to 102.9 +/- 5.6 mu g m(-3), respectively. Hourly gaseous pollutant concentrations ranged from 348 +/- 132 to 542 +/- 200 ppb CO, 21.5 +/- 7.2 ppb NO2 and 57.5 +/- 11.3 to 64.4 +/- 14.0 ppb O-3. Kruskal-Wallis ANOVA on ranks determined statistically significant spatial differences in the hourly-average pollutant concentrations. Diel variation analyses indicated that CO2, PM2.5, and PM10 peaked in the early hours of most days, O-3 at noon while NO, NO2, and CO peaked in the evening. Most pollutants were of anthropogenic origins and exhibited the highest contributions from the southwest at most sampling locations. There were strong similarities between pollutants source contribution at two of the monitoring sites that were in residential areas with a frequently used paved road. Mitigation strategies need to be established to avoid further deterioration of ambient air quality that negatively affect public health.
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关键词
Temporal variation, Low-cost sensors, Particulate matter, CBPF, Source identification
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