A data-driven approach for PM2.5 estimation in a metropolis: random forest modeling based on ERA5 reanalysis data

A data-driven approach for PM2.5 estimation in a metropolis: random forest modeling based on ERA5 reanalysis data

Air pollution in urban environments, particularly from fine particulate matter (PM _2.5 ), poses significant health risks. Addressing this issue, the current study developed a Random Forest (RF) model to estimate hourly PM _2.5 concentrations in Ankara, Türkiye. Utilizing ERA5 reanalysis data, the m...

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Bibliographic Details
Main Authors: Serdar Gündoğdu, Tolga Elbir
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Environmental Research Communications
Subjects:
PM2.5 estimation
random forest
ERA5 reanalysis
Ankara
Online Access:https://doi.org/10.1088/2515-7620/ad352d

Internet

https://doi.org/10.1088/2515-7620/ad352d

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