Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore
Ever since the industrial revolution in the 18th century, there has been an increasing need for energy to power human activity. From global transportation to lighting our homes at night, energy is essential to human life. Burning fossil fuels is the main source of energy for the world and it release...
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2022
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sg-ntu-dr.10356-1582292023-07-07T19:34:29Z Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore Teo, Aaron Bao Long Wong Kin Shun, Terence School of Electrical and Electronic Engineering EKSWONG@ntu.edu.sg Science::Mathematics::Series Ever since the industrial revolution in the 18th century, there has been an increasing need for energy to power human activity. From global transportation to lighting our homes at night, energy is essential to human life. Burning fossil fuels is the main source of energy for the world and it releases harmful pollutants into the air. These air pollutants mainly come from power plants and motor vehicles. 95% of Singapore’s electricity is generated by burning natural gas and neighbouring countries also burn fossil fuels for energy. This releases air pollutants such as sulphur dioxide (SO2) and small particulate matter (PM10) which can cause health problems in humans when inhaled. The elderly, children and those with asthma are most vulnerable to air pollutants. Therefore, it is important to keep track of air quality in Singapore. Singapore’s National Environment Agency closely monitors the concentration of air pollutants, and their results are published on their website. This project is focused on SO2 and PM10 air pollutants in the North, South, East, West and Central regions of Singapore. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-06-01T23:43:28Z 2022-06-01T23:43:28Z 2022 Final Year Project (FYP) Teo, A. B. L. (2022). Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158229 https://hdl.handle.net/10356/158229 en A2248-211 application/pdf Nanyang Technological University |
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Science::Mathematics::Series Teo, Aaron Bao Long Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore |
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Ever since the industrial revolution in the 18th century, there has been an increasing need for energy to power human activity. From global transportation to lighting our homes at night, energy is essential to human life. Burning fossil fuels is the main source of energy for the world and it releases harmful pollutants into the air. These air pollutants mainly come from power plants and motor vehicles. 95% of Singapore’s electricity is generated by burning natural gas and neighbouring countries also burn fossil fuels for energy. This releases air pollutants such as sulphur dioxide (SO2) and small particulate matter (PM10) which can cause health problems in humans when inhaled. The elderly, children and those with asthma are most vulnerable to air pollutants. Therefore, it is important to keep track of air quality in Singapore. Singapore’s National Environment Agency closely monitors the concentration of air pollutants, and their results are published on their website. This project is focused on SO2 and PM10 air pollutants in the North, South, East, West and Central regions of Singapore. |
author2 |
Wong Kin Shun, Terence |
author_facet |
Wong Kin Shun, Terence Teo, Aaron Bao Long |
format |
Final Year Project |
author |
Teo, Aaron Bao Long |
author_sort |
Teo, Aaron Bao Long |
title |
Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore |
title_short |
Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore |
title_full |
Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore |
title_fullStr |
Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore |
title_full_unstemmed |
Data analysis & one-day prediction of SO2 and PM10 pollutants in Singapore |
title_sort |
data analysis & one-day prediction of so2 and pm10 pollutants in singapore |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/158229 |
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1772828983617912832 |