Real-Time Vehicular Air Quality Monitoring Using Sensing Technology for Chennai

Abstract

Air pollution in urban areas is posing a great threat to urbanites all over the world. Various factors which contribute to air pollution are industrial, commercial and domestic activities. Statistics show that among these sources, motorised transportation is the highest contributing air pollution in recent past. Further, it may increase unless any major mitigation measures are planned and implemented. Therefore, assessing quality of the atmospheric air for breathing time to time is very important to control further damage. Currently, to access air quality-related data is limited. To overcome this, authors have designed and developed an air quality monitoring instrument (AQMI) using solid-state gas sensors and GPS module. It was used to measure the air pollution levels at Chennai city in real time and analysed the air pollutants levels in two different periods and suggested mitigation measures. Air quality on four routes in Chennai has been measured in 2013 and 2017 and compared in order to study the impact of air quality due to Vardhah cyclone. Four routes are considered in Chennai, namely Avadi to Tambaram (route 1—R1), Neelankari to T. Nagar (route 2—R2), Avadi to Chennai central (route 3—R3) and Tonakela camp to Redhills bus stand (route 4—R4). It is observed that the air pollution monitored in 2013 on the three routes shows about 60–70% locations having concentrations exceeding Central Pollution Control Board (CPCB) norms and one route has exceeding values at three places. After monitoring air quality in 2017, it was found that at some places, the pollution levels are increased when compared to that of 2013 due to further increase in vehicular traffic as well as Vardhah cyclone. Air quality data obtained using AQMI could serve various applications. Health conscious people could also take advantage of this to navigate through pollution-free areas. Patients with air pollution-related health problems would find data valuable to determine the less polluted routes.