A numerical simulation of PM2.5 concentration using the WRF-Chem model during a high air pollution episode in 2019 in Jakarta, Indonesia

Rista Hernandi Virgianto, Rayhan Rivaniputra, Nanda Putri Kinanti, Agung Hari Saputra, Aulia Nisaul Khoir


Jakarta, as a megapolitan city, is always crowded with thousands of vehicles every day which results in decreased air quality due to combustion emissions and may have a significant impact on human health. Particulate matter (PM2.5) is a pollutant that has an aerodynamic diameter of fewer than 2.5 micrometers and is very easy to enter the human respiratory system so it can affect health. In the dry season, rain as the main natural mechanism for reducing PM2.5 occurs very rarely, causing an accumulation of PM2.5 concentrations in the atmosphere. The weather research and forecasting model coupled with the chemistry (WRF-Chem) model is a dynamic model that works with atmospheric chemistry combined with meteorological variables simultaneously. This study aims to simulate the concentration of PM2.5 in Jakarta during the high air pollution episode from 20 to 29 June 2019 with the WRF-Chem model based on the T1-MOZCART chemical scheme. Spatial analysis was conducted to determine the distribution of PM2.5 concentrations during high air pollution episodes in Jakarta. Validation of the simulation model was based on three observation sites, one in South Jakarta and two in Central Jakarta. The results showed that the highest correlation is 0.3 and the lowest root mean square error (RMSE) is 26.4, while the simulations still tend to overestimate the PM2.5 concentration.

Full Text:


DOI: http://doi.org/10.11591/ijaas.v11.i4.pp335-344


  • There are currently no refbacks.

International Journal of Advances in Applied Sciences (IJAAS)
p-ISSN 2252-8814, e-ISSN 2722-2594
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Web Analytics View IJAAS Stats