Please use this identifier to cite or link to this item: https://doi.org/10.3390/ijerph17249345
Title: The influence of south east Asia forest fires on ambient particulate matter concentrations in Singapore: An ecological study using random forest and vector autoregressive models
Authors: Rajarethinam, J.
Aik, J.
Tian, J. 
Keywords: Air quality
Forest fires
Random forest model
Vector autoregressive model
Issue Date: 2020
Publisher: MDPI AG
Citation: Rajarethinam, J., Aik, J., Tian, J. (2020). The influence of south east Asia forest fires on ambient particulate matter concentrations in Singapore: An ecological study using random forest and vector autoregressive models. International Journal of Environmental Research and Public Health 17 (24) : 1-14. ScholarBank@NUS Repository. https://doi.org/10.3390/ijerph17249345
Rights: Attribution 4.0 International
Abstract: Haze, due to biomass burning, is a recurring problem in Southeast Asia (SEA). Exposure to atmospheric particulate matter (PM) remains an important public health concern. In this paper, we examined the long-term seasonality of PM2.5 and PM10 in Singapore. To study the association between forest fires in SEA and air quality in Singapore, we built two machine learning models, including the random forest (RF) model and the vector autoregressive (VAR) model, using a benchmark air quality dataset containing daily PM2.5 and PM10 from 2009 to 2018. Furthermore, we incorporated weather parameters as independent variables. We observed two annual peaks, one in the middle of the year and one at the end of the year for both PM2.5 and PM10. Singapore was more affected by fires from Kalimantan compared to fires from other SEA countries. VAR models performed better than RF with Mean Absolute Percentage Error (MAPE) values being 0.8% and 6.1% lower for PM2.5 and PM10, respectively. The situation in Singapore can be reasonably anticipated with predictive models that incorporate information on forest fires and weather variations. Public communication of anticipated air quality at the national level benefits those at higher risk of experiencing poorer health due to poorer air quality. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Source Title: International Journal of Environmental Research and Public Health
URI: https://scholarbank.nus.edu.sg/handle/10635/196294
ISSN: 1661-7827
DOI: 10.3390/ijerph17249345
Rights: Attribution 4.0 International
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