Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia

Kar Yong NgNorhashidah Awang2024-05-102024-05-102018Ng, K. Y., & Awang, N. (2018). Multiple linear regression and regression with time series error models in forecasting PM 10 concentrations in Peninsular Malaysia. Environmental monitoring and assessment, 190, 1-11.https://repoemc.ukm.my/handle/123456789/557Frequent haze occurrences in Malaysia have made the management of PM10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM10 variation and good forecast of PM10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants.enMultiple linear regressionRegression with time series errorPM10ForecastMultiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular MalaysiaJournal