Evaluating of spatial interpolation techniques for accurate air quality prediction: An overview
Air pollution is a primary environmental concent in modern society. It threatens human health, ecological balance, and climate stability. The leading causes of air pollution include urban growth, industrial activities since the Industrial Revolution, fossil fuel emissions, motor vehicle traffic, inf...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/33/e3sconf_gases2025_07008.pdf |
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| Summary: | Air pollution is a primary environmental concent in modern society. It threatens human health, ecological balance, and climate stability. The leading causes of air pollution include urban growth, industrial activities since the Industrial Revolution, fossil fuel emissions, motor vehicle traffic, inferior fuels, and power plants. This study reviews existing research aimed at assessing air quality by using Geographic Information Systems (GIS) methodologies to monitor air quality, which has helped to address air pollution problems. The study found that spatial interpolation techniques in Geographic Information Systems (GIS), specifically the Inverse Distance Weighting (IDW) and Kriging methods, effectively assess air quality by predicting concentrations of various air pollutants, such as SO2, NO2. CO. and PM2.5, in unmonitored regions. |
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| ISSN: | 2267-1242 |