Deep decarbonization potential and implementation path under provincial differences in China's fleet electrification.

Fleet electrification is considered to be an important measure for reducing carbon emissions in the road transport industry. Considering the heterogeneity of the NEV market penetration and the vehicle types in different provinces, how to design targeted and time-sequenced road transport decarbonisation reduction strategies has become a key issue that needs to be discussed urgently. In this study, the NEVs ownership in China's 31 provinces is used as an intermediate variable.

Air Pollutant Concentration Forecasting Using Long Short-Term Memory Based on Wavelet Transform and Information Gain: A Case Study of Beijing.

Air pollutant concentration forecasting is an effective way which protects health of the public by the warning of the harmful air contaminants. In this study, a hybrid prediction model has been established by using information gain, wavelet decomposition transform technique, and LSTM neural network, and applied to the daily concentration prediction of atmospheric pollutants (PM, PM, SO, NO, O, and CO) in Beijing. First, the collected raw data are selected by feature selection by information gain, and a set of factors having a strong correlation with the prediction is obtained.