Data analysis of NO2 and PM2.5 air pollutants in Singapore city

Abstract

Air pollution has been a significant public health issue affecting millions of people worldwide. Notably, it has been demonstrated that certain subpopulations of humans, such as children and the elderly, are more vulnerable to inhaled ambient pollutants. The World Health Organisation (WHO) has established Air Quality Guidelines (AQGs) for countries, including Singapore, to mitigate the disease burden of ambient air pollution. Even though it might be a difficult task for many countries struggling with high pollution levels, WHO has recommended interim targets to allow modest but considerable improvements in air quality and hence health benefits for the population. The primary source of air pollution in Singapore comes from motor vehicles and industries. As industrial sectors continue to expand and the population of motor vehicles has been growing over the last few years, air pollution will only worsen. Air monitoring sensors are installed across Singapore to monitor air pollution. The data will be captured and uploaded to the National Environmental Agency (NEA) website every hour. With these available data, the main purpose of this project is to analyse the trends and study the geographic correlation for PM2.5 and NO2 in Singapore using Python Programming language.