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[Estimation of PM2.5 Hourly Concentration in Sichuan Province Based on GTWR-XGBoost Model].
Wu, Di; Du, Ning; Wang, Li; Wu, Yu-Hong; Zhang, Shao-Lei; Zhou, Bin; Zhang, Xian-Yun.
Afiliação
  • Wu D; Mining College, Guizhou University, Guiyang 550025, China.
  • Du N; Mining College, Guizhou University, Guiyang 550025, China.
  • Wang L; Mining College, Guizhou University, Guiyang 550025, China.
  • Wu YH; Mining College, Guizhou University, Guiyang 550025, China.
  • Zhang SL; Mining College, Guizhou University, Guiyang 550025, China.
  • Zhou B; Mining College, Guizhou University, Guiyang 550025, China.
  • Zhang XY; Mining College, Guizhou University, Guiyang 550025, China.
Huan Jing Ke Xue ; 44(7): 3738-3748, 2023 Jul 08.
Article em Zh | MEDLINE | ID: mdl-37438273
ABSTRACT
Aerosol optical depths of satellites and meteorological factors have been widely used to estimate concentrations of surface particulate matter with an aerodynamic diameter ≤ 2.5 µm. Research on a high time resolution and high-precision PM2.5 concentration estimation method is of great significance for timely and accurate air quality prediction and air pollution prevention and mitigation. Himawari-8 AOD hour product and ERA5 meteorological reanalysis data were used as estimation variables, and a GTWR-XGBoost combined model was proposed to estimate hourly PM2.5 concentration in Sichuan Province. The results showed that① the performance of the proposed combination model was better than that of the KNN, RF, AdaBoost, GTWR, GTWR-KNN, GTWR-RF, and GTWR-AdaBoost models in the full dataset; the fitting accuracy indexes R2, MAE, and RMSE were 0.96, 3.43 µg·m-3, and 5.52 µg·m-3, respectively; and the verification accuracy indexes R2, MAE, and RMSE were 0.9, 4.98 µg·m-3, and 7.92 µg·m-3, respectively. ② The model had a high goodness of fit (R2 of the whole dataset was 0.96, and R2 of different times ranged from 0.91 to 0.98) when applied to the estimation of PM2.5 concentration hour. It showed that the model had good time stability for hourly estimation and could provide accurate estimation information for regional air quality assessment. ③ In terms of time, the annual average PM2.5hourly concentration estimation showed an inverted U-shaped trend. It began to increase gradually at 0900 am to a peak of 44.56 µg·m-3 at 1100 and then gradually decreased. Moreover, the seasonal variation was very obvious, with winter>spring>autumn>summer. ④ In terms of spatial distribution, it showed the characteristics of high in the east and low in the west and a high degree of local pollution.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Huan Jing Ke Xue Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Huan Jing Ke Xue Ano de publicação: 2023 Tipo de documento: Article