Urban air pollution is typically caused by a wide variety of emission sources, including commercial/residential fuel traffic, manufacturing, and combustion, and consists of a complex mix of gaseous and particulate air pollutants such as nitrogen dioxide (NO2), sulfur dioxide (SO2), fine particulate matter (PM2.5) and ground-level ozone (PM2.5) (defined as aerodynamic diameter particulate matter (PM2.5) air quality has been a big concern in many countries. According to the World Health Organization (WHO) (2018), more than seven million people die each year because of this disease, and more than 80 percent of the population of urban areas live in places where air quality increases above WHO (2020) guideline limits. As stated by Apte et al. (2018), global and national life expectancy has been lowered due to air pollution. In addition to correlations with decreased life expectancy overall, epidemiological studies suggest potential associations for different cardiovascular and pulmonary disorders, including strokes, between short-and long-term exposure to air pollutant requirements and increased morbidity, mortality, and hospital admissions. The assessment of long-term air monitoring data and atmospheric PM2.5 characterization will help to increase understanding of the state of air quality and explain the sources of urban particulate pollution. Mass concentration is the global normative metric for measuring and tracking the exposure of particulate matter (PM). Based on epidemiology and the subsequent guidelines of international organizations, national legislation in many developing countries sets fixed thresholds, limits, and/or target values for PM mass concentrations (WHO, 2000; IARC, 2013).
Growing use is being made of low-cost sensors, satellite modelling and citizen scientists, non-scientists interested in specific issues who collect or analyze data to contribute to scientific research, or advocate for environmental or public health improvements. Several organizations such as New York City Community Air Survey (NYCCAS), AirVisual, and Air Matters, just to name a few have developed into this field of community engagement and community-based participatory research by developing air quality toolkits for 'citizen-science' and AQI modelled using satellite to accessible pollution source data, Using fresh, low-cost air pollution surveys to construct community air pollution surveys. The World EPAs (Environmental Protection Agencies) have made available air quality data showing more than 15,000 stations in 2000 major cities from 132 countries. The world currently operates more than 30,000 recognized air quality monitoring stations, of which more than 12,000 are published in the World Air Quality Index project. The AQI standard for any single published station is based on the US EPA Instant-Cast standard (The World Air Quality Index Project Team, 2020).
According to Iskandaryan et al. (2020) and Giffinger et al. (2020), a smart city is a city in which there are six main components, including smart economy, smart transport, smart environment, smart citizens, smart life, and smart management, or The use of smart computing technologies to render critical infrastructure components and services of a city, including city governance, education, and smart management The availability of data produced by sensors is a significant characteristic of smart cities (Trilles et al., 2017; Granell et al., 2020). In other words, because of the above explanation, there is the aspiration of Lagos becoming a smart town in Nigeria.
In Nigeria and the African continent, Lagos is the most populous city in (Campbell, 2012). The megacity has Africa's fourth highest GDP and houses one of the continent's biggest and busiest seaports (Lees et al., 2015). It is one of the world's fastest growing cities.
In Nigeria, Nigerian scientists and their international collaborators have taken a variety of air quality measurements (Osimobi et al., 2019 Daful et al., 2020; Croitoru et al., 2020). These are, however, limited-point measurements around the city (background, commercial, roadways, and informal settlement households) and limited numbers of contaminants, primarily PM2.5 and PM10. In certain cases, PM levels appear far above the World Health Organization (WHO) 24-h average guideline.
The prospect of building low-cost PM sensors and the use of IoT has attracted the attention of many researchers around the world in recent years (Obayan et al., 2018; Johnston et al., 2019; Chojer et al., 2020). Much of the study centered on the followings: i assessment and calibration of various PM sensor systems (Bulot et al., 2019; Suriano, 2002; Suriano et al., 2020; Markowicz and Chili'ski, 2020); (ii) local air pollution sources detection (Morawska et al., 2018; Rogulski, 2018); (iii) effects on air pollution of meteorological and topographical parameters (Rogulski, 2017; Rogulski, 2018), and (iv) studies to determine the risk of athletic activities linked to exposure to air pollution (Nieckarz and Zoladz, 2020). The present paper is the first attempt, to the best of our knowledge, to draw the attention of researchers to the use of satellite model (IoT).
This does not, however, take away the fact that Lagos State does not have an active monitoring method for air quality. The current monitoring scheme employs relatively large, heavy and expensive air pollutant analyzers, with device prices ranging from EUR 5000 to EUR 30,000. The results of air quality monitoring are collected for enhanced decision-making in a database. It takes time to process the laboratory results and, even then, the results could be unreliable as certain parameters differ on site and in-lab. This research, therefore, is a development in this part of the nation in the field of air quality monitoring. The main objective of the study is to use satellite data (Internet of Things, IoT) systems in order to track Lagos' air quality. The satellite data will concentrate only on the most important parameters because of financial constraints.
It is expected that the study will last for 24 months. Consequently, the purpose of the study was to carry out a 40-day preliminary air quality assessment (PM2.5, PM10, CO, NO2, SO2, and O3) at five separate locations (Opebi, Ojudu, Ikeja, Maryland, and Eti-Osa) in Lagos State, Nigeria, and to assess the effect of meteorological parameters (wind speed, temperature, and humidity) on air quality.