Statistical modeling of meteorological factors and PM2.5 levels: implications for climate change in Indonesia

Abstract

Increased air pollution in Indonesia has resulted in fluctuations in climate patterns. The development of this research lies in the response variable studied, namely the concentration of PM2.5 which is the main indicator and a serious concern in Indonesia because the high concentration of these particles has a negative impact on public health. The Air Pollution Standard Index (ISPU) with the PM2.5 parameter is used to measure air quality based on the amount of PM2.5 levels in the air.  ISPU with the PM2.5 parameter can show two possible levels of air quality, namely dangerous or not so that air quality data seen from the ISPU level of the PM2.5 parameter is binary. Meteorological factors that are thought to affect PM2.5 concentrations are air temperature, rainfall, solar irradiation, air humidity, air pressure, and wind speed. This study uses a binary logistic regression analysis method that aims to determine the influence of meteorological factors that are thought to affect PM2.5 concentrations so that they have the potential to affect climate change in Indonesia. The results of the analysis show that Indonesia with provinces that have PM2.5 concentrations still dominate, with a dangerous category of 52.94%. The meteorological factors that have a significant effect on PM2.5 concentrations are air temperature, rainfall, solar irradiation, air humidity, air pressure, and wind speed.  In addition, climate change in Indonesia is also influenced by these factors.  The research findings show that these characteristics have consequences for the Indonesian government's initiatives aimed at improving air quality and addressing climate change. Therefore, this is in line with the objectives of achieving the Sustainable Development Goals (SDGs), such as promoting Good Health and Wellbeing (SDG 3), creating Sustainable Cities and Communities (SDG 11), and undertaking Climate Action (SDG 13).