Marzuki Ismail

TL;DR: It was found that the PM2.5 concentrations showed a high reduction during the 2020 Malaysia Movement Control Order, but the reduction did not solely depend on MCO, thus the researchers suggest a further study considering the influencing factors that need to be adhered to in the future.

TL;DR: Observations have been made on the long‐term trends of major air pollutants in Malaysia including nitrogen dioxide, carbon monoxide, the ozone and total suspended particulate matter (particularly PM10), and sulfur dioxide, emitted from industrial and urban areas from early 1970s until late 1998.

TL;DR: In this paper, the forecasting performance of a linear (Multiple Linear Regression) and two non-linear models (Multi-Layer Perceptron and Radial Basis Function) utilizing meteorological and gaseous pollutants variables as input parameters from the year 2000-2014 at four sites with different surrounding activities of urban, sub-urban and rural areas.

TL;DR: In this article, an accurate model based on Machine Learning algorithms to predict ozone levels in Malaysia was proposed to predict high level of tropospheric ozone concentration exceeding allowable level has been reported in Malaysia.

TL;DR: In this paper, three different stepwise multiple linear regression (MLR) models for predicting the PM10 concentration were then developed based on three different prediction hours, namely t+1, t+2, and t+3.