The low-cost sensors and IoT have come to the rescue due to the high cost and operational complexity of equipment and methodologies in environmental monitoring. They are relatively inexpensive and reliable. It is on this assumption that we have decided to use the World Air Quality satellite data supplied by air matters.com. This study is a 40-day preliminary work in which air quality (Air Quality Index (AQI), PM 2.5 , PM 10 , NO 2 , CO, SO 2 , and O 3 ) and meteorological (temperature, humidity, and wind speed) parameters were monitored. The data collected was for ve locations in Lagos State, Nigeria (Ojodu, Opebi, Ikeja, Maryland, and Eti-Osa). The data obtained were subjected to basic statistical analyses. The ndings showed that the Opebi had the highest mean value of PM 2.5 (69.28 µg/m 3 ), PM 10 (107.38 µg/m 3 ), and CO (1392 µg/m 3 ). The mean values of O 3 are as follows: 32.52, 38.7, 36.2, 37.85, and 36.13µg/m 3 for Ikeja, Maryland, Opebi, Ojodu, and Eti-Osa respectively. Opebi had the highest value (3179µg/m 3 ), followed by Eti-Osa (2978µg/m 3 ), and the lowest value in Maryland (1943µg/m 3 ) among the CO reference locations. AQI of all locations presented the levels of contamination as 'Unhealthy for Vulnerable Groups'. The pollutants were much higher than the World Health Organization (WHO) guidelines. There were relationships between the parameters monitored and meteorological in uences, and the effects of natural and man-made activities may be the sources of the elevated pollutants throughout the locations.

No abstract

The low-cost sensors and IoT have come to the rescue due to the high cost and operational complexity of equipment and methodologies in environmental monitoring. They are relatively inexpensive and reliable. It is on this assumption that we have decided to use the World Air Quality satellite data supplied by air matters.com. This study is a 40-day preliminary work in which air quality (Air Quality Index (AQI), PM2.5, PM10, NO2, CO, SO2, and O3) and meteorological (temperature, humidity, and wind speed) parameters were monitored. The data collected was for five locations in Lagos State, Nigeria (Ojodu, Opebi, Ikeja, Maryland, and Eti-Osa). The data obtained were subjected to basic statistical analyses. The findings showed that the Opebi had the highest mean value of PM2.5 (69.28 µg/m3), PM10 (107.38 µg/m3), and CO (1392 µg/m3). The mean values of O3 are as follows: 32.52, 38.7, 36.2, 37.85, and 36.13µg/m3 for Ikeja, Maryland, Opebi, Ojodu, and Eti-Osa respectively. Opebi had the highest value (3179µg/m3), followed by Eti-Osa (2978µg/m3), and the lowest value in Maryland (1943µg/m3) among the CO reference locations. AQI of all locations presented the levels of contamination as 'Unhealthy for Vulnerable Groups'. The pollutants were much higher than the World Health Organization (WHO) guidelines. There were relationships between the parameters monitored and meteorological influences, and the effects of natural and man-made activities may be the sources of the elevated pollutants throughout the locations.

No abstract

Owing to the effect on people, livestock, and materials, air pollution is a hazard globally. To this end, stakeholders have taken on the challenge of quantifying the environment with the use of tools and eventually using the data produced to provide solutions to the problems. However, low-cost sensors and IoT have come to the rescue due to the high cost and operational complexity of equipment and methodologies in environmental monitoring. They are relatively inexpensive and reliable. It is on this assumption that we have decided to use the World Air Quality satellite data supplied by air matters.com. This study is a 40-day preliminary work in which air quality (AQI, PM 2.5 , PM 10 , NO 2 , CO, SO 2 , and O 3) and meteorological (temperature, humidity, and wind speed) parameters were monitored. The data collected was for five locations in Lagos State, Nigeria (Ojodu, Opebi, Ikeja, Maryland, and Eti-Osa). The data obtained were subjected to basic descriptive, multivariate and time series statistical analyses. The findings showed that the AQI of all locations presented the levels of contamination as 'Unhealthy for Vulnerable Groups', there were relationships between the parameters monitored and meteorological influences, and the effects of natural and man-made activities may be the sources of the elevated pollutants throughout the locations.