Improvement of PM<sub>2.5</sub> Forecast in China by Ground-Based Multi-Pollutant Emission Source Inversion in 2022

This study employs an ensemble Kalman filter assimilation method to validate and update the pollutant emission inventory to mitigate the impact of uncertainties on the forecasting performance of air quality numerical models. Based on nationwide ground-level pollutant monitoring data in China, the em...

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Bibliographic Details
Main Authors: Lili Zhu, Xiao Tang, Wenyi Yang, Yao Zhao, Lei Kong, Huangjian Wu, Meng Fan, Chao Yu, Liangfu Chen
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/15/2/181

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