CRITICAL AIR QUALITY ZONING BY USING METEOROLOGICAL STATION DATA AND GOOGLE EARTH ENGINE
DOI:
https://doi.org/10.14456/jesm.2025.2Keywords:
Atmospheric Stability classification, Critical Air Quality ZoningAbstract
This study aims to 1) identify critical air areas where pollution emissions have disproportionately severe impacts due to geographical conditions, determined by the proportion of very stable atmospheric conditions, and 2) examine the relationship between PM2.5 and atmospheric stability associated with air pollutant accumulation in the most critical area identified.The Monin-Obukhov Similarity Theory was applied to classify atmospheric stability using cloud cover, wind speed, and temperature data at 10 meters from 20 meteorological stations. Data was collected at 3-hour intervals from 01:00 to 22:00, eight times daily throughout 2023. Geographical data was sourced from Google Earth Engine.
Results identified five critical air areas with the highest proportions of very stable atmospheric conditions: Lampang (51.37%), Kanchanaburi/Thong Pha Phum (50.36%), Nan (49.7%), Mae Hong Son (49.29%), and Phayao (48.66%). Further analysis of Lampang province, the most critical area, revealed a significant relationship between PM2.5 levels and very stable atmospheric conditions. Health-affecting dust levels were present in 67.6% of all atmospheric stability conditions observed. This research contributes the understanding the geographical and meteorological factors influencing air pollution accumulation, potentially informing targeted air quality management strategies in critical areas.
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