Chemical Engineering and Process

The Air Pollutant Index (API) readings in areas in Kelantan, Kuala Lumpur, and Johor recorded air quality at unhealthy levels as of 4pm today.

According to the air pollutant index management system website, Segamat in Johor recorded an unhealthy API reading of 152 whereas Cheras, Kuala Lumpur as well as Kota Baru and Tanah Merah, Kelantan recorded an API reading of 106, 107 and 104 respectively.

An API of zero to 50 indicates good air quality; 51 to 100 (moderate); 101 to 200 (unhealthy); 201 to 300 (very unhealthy) and 300 and above (hazardous).

Meanwhile, Health Minister Dr Zaliha Mustafa, through a video uploaded on TikTok today, highlighted the haze condition in Sekijang, where the buildings are almost obscured by pollution and visibility is less than 200m.

For the past few days, we have heard the news that the country has been affected by the haze in a few areas and one of the areas involved that have been badly affected is my constituency, which is Sekijang, a town in Segamat, she said.

She said the area recorded an unhealthy API reading of approximately 145 to 150 yesterday and advised people in the area to be cautious of outdoor activities.

The Sekijang MP also explained that haze consists of smoke and dust particles that can be risky if it excessively enters the respiratory tract.

Haze is not good for health and can cause diseases such as eye inflammation, itchy nose, sore throat, cough, flu and itchy skin, she said, citing cardiovascular diseases as its long-term effects.

Dr Zaliha also reminded people to stay home during the haze, especially children with asthma.

Based on the article above and being worried about the condition of air quality has sparked your interest to investigate and forecast the impacts caused by air pollution. You and your team are given a task to investigate and analyze this scenario through Markov Chain.

You should be able to use Markov Chain to predict the impact caused by air pollution in the short and long term. Common air pollutants include particulate matter (particularly PM10 and PM2.5), carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2) and nitrogen oxides (NOx), acid gases, heavy metals, volatile organic compounds (VOCs), solvents, pesticides, radiation, and bio-aerosols.

You may choose 1 of the sources of pollution, then use Markov Chain to predict its impact on humans and other living organisations in the short and long term.