Abstract
Air quality status on the East Coast of Peninsular Malaysia is dominated by Particulate Matter (PM10) throughout the years. Studies have affirmed that PM10 influence human health and the environment. Therefore, precise forecasting algorithms are urgently needed to determine the PM10 status for mitigation plan and early warning purposes. This study investigates 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. Non-linear model (Radial Basis Function) outperforms the linear model with the error reduced by 78.9% (urban), 32.1% (sub-urban) and 39.8% (rural). Association between PM10 and its contributing factors are complex and non-linear in nature, best captured by an Artificial Neural Network, which generates more accurate PM10 compared to the linear model. The results are robust enough for precise next day forecasting of PM10 concentration on the East Coast of Peninsular Malaysia.
Highlights
Air quality in a developing country such as Malaysia has decreased gradually because of rapid urbanization, industrialization and population growth [1]
Southeast Asia cities, including Malaysia are notified as surrounded by particulate matter (PM10 ) in air quality problems [2,3,4,5]
PM10 had received special attention especially in Peninsular Malaysia, as it was proven to have the highest index through the Air Pollutant Index (API) compared to other criteria pollutants annually
Summary
Air quality in a developing country such as Malaysia has decreased gradually because of rapid urbanization, industrialization and population growth [1]. Southeast Asia cities, including Malaysia are notified as surrounded by particulate matter (PM10 ) in air quality problems [2,3,4,5]. PM10 had received special attention especially in Peninsular Malaysia, as it was proven to have the highest index through the Air Pollutant Index (API) compared to other criteria pollutants annually. The status of API in the East Coast of Peninsular Malaysia was noted as having a good to moderate level, where only a few days were recorded to have unhealthy levels of PM10 concentration during the dry season months (May to September) [3]. The main sources of PM10 in Malaysia are emissions from the motor vehicles, heat and power plants, industries and open combustion
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