Inferensi
Vol 7, No 1 (2024)

Determinants of PM2.5 Concentration in DKI Jakarta Province: A VAR Model Approach

Jayadri, Bertolomeus Laksana (Politeknik Statistika STIS, Jakarta)
Pangastuti, Mafitroh (Politeknik Statistika STIS, Jakarta)
Farhan, Muh (Politeknik Statistika STIS, Jakarta)
Kartiasih, Fitri (Politeknik Statistika STIS, Jakarta)



Article Info

Publish Date
25 Mar 2024

Abstract

Air pollution in the DKI Jakarta Province is a serious issue as it is related to public health and environmental concerns. Therefore, this research aims to analyze the causality of PM2.5 concentration with meteorological factors such as air temperature, humidity, rainfall, and wind speed. The data source used is from the MERRA-2 satellite, which provides information at a spatial resolution of 0.5° × 0.625°. The data covers the period from January 1, 1980, to November 1, 2023, with hourly time intervals. The research variables involve PM2.5 concentration as the response variable, as well as predictor variables such as air temperature, humidity, rainfall, and wind speed. The analytical method employed is the Vector Autoregressive (VAR) approach, as all variables are stationary at the level.  The constructed VAR model tends to indicate that meteorological variables have a low explanatory power for PM2.5 concentration, while changes in PM2.5 concentration itself have sustained impacts in both the short and long term. This suggests that the fluctuations in PM2.5 concentration in DKI Jakarta Province are not significantly influenced by meteorological factors.

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Journal Info

Abbrev

inferensi

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

Description

The aim of Inferensi is to publish original articles concerning statistical theories and novel applications in diverse research fields related to statistics and data science. The objective of papers should be to contribute to the understanding of the statistical methodology and/or to develop and ...