Assessing the ambient air quality patterns associated to the COVID-19 outbreak in the Yangtze River Delta: A random forest approach.

ABSTRACT: The novel coronavirus (COVID-19), first identified at the end of December 2019, has significant impacts on all aspects of human society. In this study, we aimed to assess the ambient air quality patterns associated to the COVID-19 outbreak in the Yangtze River Delta (YRD) region using a random forest (RF) model. To estimate the accuracy of the model, the cross-validation (CV), determination coefficient R², root mean squared error (RMSE) and mean absolute error (MAE) were used. The results demonstrate that the RF model achieved the best performance in the prediction of PM₁₀ (R² = 0.78, RMSE = 8.81 μg/m³), PM_2.5 (R² = 0.76, RMSE = 6.16 μg/m³), SO₂ (R² = 0.76, RMSE = 0.70 μg/m³), NO

SUBMITTER: Hasnain A 

PROVIDER: S-EPMC9770002 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature