Presentation + Paper
19 October 2023 The CAMS reanalysis PM2.5 product representing PM2.5 trend over Chonburi Province Thailand
Pramet Kaewmesri, Nuntikorn Kitratporn, Jiratiwan Kruasilp, Phukrit Sriwilas, Chanika Sukawattanavijit
Author Affiliations +
Abstract
The primary objective of this research is to investigate the common characteristics and causes of PM2.5 pollution in Chonburi province, Thailand. The study specifically focused on examining the relationship between PM2.5 pollutants and time. The study utilizes the CAMS global reanalysis (EAC4) dataset provided by the European Centre for Medium Range Weather Forecasts (ECMWF). The data present variations in the total amount of PM2.5 over three distinct periods: Period I (2006 to 2010), Period II (2011 to 2015), and Period III (2016 to 2020). The study employs various statistical analyses, including assessments of PM2.5 levels annually and monthly, trend regression analysis of monthly PM2.5 data, identification of the highest annual mean PM2.5 concentrations, examination of the standard deviation associated with the highest annual PM2.5 mean, and exploration of potential spatial patterns of PM2.5 trends across Chonburi province using CAMS products. Overall, this research contributes to a better understanding of the PM2.5 pollution problem in the area, which is essential for formulating effective environmental policies and public health strategies to mitigate the adverse impacts of air pollution on the local population. The spatial patterns and trend analyses generated from CAMS products enable evidence-based decision-making and can inform policymakers on appropriate measures to improve air quality and safeguard public health in Chonburi province.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pramet Kaewmesri, Nuntikorn Kitratporn, Jiratiwan Kruasilp, Phukrit Sriwilas, and Chanika Sukawattanavijit "The CAMS reanalysis PM2.5 product representing PM2.5 trend over Chonburi Province Thailand", Proc. SPIE 12734, Earth Resources and Environmental Remote Sensing/GIS Applications XIV, 1273403 (19 October 2023); https://doi.org/10.1117/12.2680278
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KEYWORDS
Linear regression

Air quality

Statistical analysis

Atmospheric monitoring

Chemical composition

Atmospheric modeling

Data modeling

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