PM2.5 forecasting based on LSTM model in Northeastern Thailand 2014-2021

Name: Sudarat Chadsuthi

Organization : Naresuan University. Faculty of Science

Name: Suparinthon Anupong

Organization : Mahidol Wittayanusorn School (MWIT). Department of Chemistry

Email : suparinthon.anu@mwit.ac.th

keyword: Long short-term memory

LCSH: Air -- Pollution -- Mathematical models

LCSH: Particulate matter -- Measurement

LCSH: Neural networks (Computer science)

LCSH: Air quality -- Forecasting

Abstract: Air pollution is a critical environmental issue impacting human health and ecosystems globally. Among various pollutants, fine particulate matter (PM₂.₅) is particularly concerning due to its ability to penetrate deep into the lungs and enter the bloodstream, causing severe health problems. This study employs Long Short-Term Memory (LSTM) networks to forecast PM₂.₅ concentrations based on related air pollutants: PM₁₀, CO, SO₂, NO₂, and O₃. LSTM networks, a type of recurrent neural network (RNN), are adept at capturing long-term dependencies in time series data, making them ideal for modeling the complex temporal dynamics of air pollutant interactions. Air pollution data were obtained from monitoring stations in northeastern Thailand from 2014 to 2021. The results demonstrate that the LSTM model can effectively predict PM₂.₅ concentrations, providing valuable insights for public health. This approach underscores the potential of machine learning techniques in enhancing air quality forecasting and understanding the influence of various chemical pollutants on PM₂.₅ levels.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2025

Modified: 2025-10-24

Issued: 2025-10-24

บทความ/Article

application/pdf

BibliograpyCitation : In The Chemical Society of Thailand under the Patronage of Professor Dr. Her Royal Highness Princess Chulabhorn Krom Phra Srisavangavadhana and Suranaree University of Technology. Institute of Science. School of Chemistry. Pure and Applied Chemistry International Conference 2025 (PACCON 2025) (pp.243-247). Bangkok : The Chemical Society of Thailand under the Patronage of Professor Dr. Her Royal Highness Princess Chulabhorn Krom Phra Srisavangavadhana in association with the School of Chemistry, Institute of Science, Suranaree University of Technology, 2025

eng

©copyrights King Mongkut's University of Technology North Bangkok

ลำดับที่.	ชื่อแฟ้มข้อมูล	ขนาดแฟ้มข้อมูล	จำนวนเข้าถึง	วัน-เวลาเข้าถึงล่าสุด
1	PACCON 2025pp.243-247.pdf	770.93 KB

ใช้เวลา

0.032647 วินาที