Google Academic

Articole

Academic

Aproximativ 304 rezultate (0,02 sec.)

The use of satellite-retrieved aerosol optical depth (AOD) data and statistical modeling
provides a promising approach to estimating PM 2.5 concentrations for a large region …

Salvați Citați Citat de 309 ori Articole cu conținut similar Toate cele 5 versiuni

[Free GPT-4]
[DeepSeek]

[PDF] nih.gov

Predicting monthly high-resolution PM2. 5 concentrations with random forest model in the North China Plain

K Huang, Q ** …

Salvați Citați Citat de 226 ori Articole cu conținut similar Toate cele 12 versiuni

[Free GPT-4]
[DeepSeek]

[PDF] iop.org Full View

Air quality improvements and health benefits from China's clean air action since 2013

Y Zheng, T Xue, Q Zhang, G Geng… - Environmental …, 2017 - iopscience.iop.org

Aggressive emission control measures were taken by the Chinese government after the
promulgation of the'Air Pollution Prevention and Control Action Plan'in 2013. Here we …

Salvați Citați Citat de 266 ori Articole cu conținut similar Toate cele 6 versiuni

[Free GPT-4]
[DeepSeek]

[PDF] ucdavis.edu

Spatiotemporal prediction of continuous daily PM2. 5 concentrations across China using a spatially explicit machine learning algorithm

Y Zhan, Y Luo, X Deng, H Chen, ML Grieneisen… - Atmospheric …, 2017 - Elsevier

A high degree of uncertainty associated with the emission inventory for China tends to
degrade the performance of chemical transport models in predicting PM 2.5 concentrations …

Salvați Citați Citat de 239 ori Articole cu conținut similar Toate cele 6 versiuni

Identifying the spatiotemporal dynamic of PM2. 5 concentrations at multiple scales using geographically and temporally weighted regression model across China …

B Guo, X Wang, L Pei, Y Su, D Zhang… - Science of The Total …, 2021 - Elsevier

Abstract Fine particulate matter (PM 2.5) is closely related to the air quality and public health.
Numerous models have been introduced to simulate the PM 2.5 concentrations at large …

Salvați Citați Citat de 127 ori Articole cu conținut similar Toate cele 9 versiuni

Creează alerta

Citați

Căutare avansată

Salvat în Bibliotecă

Predicting monthly high-resolution PM2. 5 concentrations with random forest model in the North China Plain

Air quality improvements and health benefits from China's clean air action since 2013

Spatiotemporal prediction of continuous daily PM2. 5 concentrations across China using a spatially explicit machine learning algorithm

Identifying the spatiotemporal dynamic of PM2. 5 concentrations at multiple scales using geographically and temporally weighted regression model across China …