Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Journal of Mathematical and Fundamental Sciences
Khwansiri Sirimangkhala
Industrial Mathematics Research Unit & Department of Mathematics, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang
Astronomy Chemistry Earth & Planetary Sciences Mathematics Physics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Modeling Haze Problems in the North of Thailand using Logistic Regression Busayamas Pimpunchat; Khwansiri Sirimangkhala; Suwannee Junyapoon
Journal of Mathematical and Fundamental Sciences Vol. 46 No. 2 (2014)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2014.46.2.7

Abstract

At present, air pollution is a major problem in the upper northern region of Thailand. Air pollutants have an effect on human health, the economy and the traveling industry. The severity of this problem clearly appears every year during the dry season, from February to April. In particular it becomes very serious in March, especially in Chiang Mai province where smoke haze is a major issue. This study looked into related data from 2005-2010 covering eight principal parameters: PM10 (particulate matter with a diameter smaller than 10 micrometer), CO (carbon monoxide), NO2 (nitrogen dioxide), SO2 (sulphur dioxide), RH (relative humidity), NO (nitrogen oxide), pressure, and rainfall. Overall haze problem occurrence was calculated from a logistic regression model. Its dependence on the eight parameters stated above was determined for design conditions using the correlation coefficients with PM10. The proposed overall haze problem modeling can be used as a quantitative assessment criterion for supporting decision making to protect human health. This study proposed to predict haze problem occurrence in 2011. The agreement of the results from the mathematical model with actual measured PM10 concentration data from the Pollution Control Department was quite satisfactory.
Co-Authors Busayamas Pimpunchat Suwannee Junyapoon