Forecasting of CO2 Emissions in Algeria Using Discrete Wavelet Transform

Based Autoregressive Integrated Moving Average Models

Abstract

of carbon dioxide emissions a top priority globally. Accurately forecasting these
emissions is a crucial aspect of transitioning towards a clean energy economy. This paper
introduces a new method for estimating CO2 emissions by combining the wavelet technique with
both an autoregressive integrated moving average (DWT-ARIMA) and ARIMA model, applied to
annual carbon dioxide emissions data in Algeria from 1970 to 2022. The study provides decision
makers with crucial information to help find effective environmental protection solutions in
Algeria. The results suggest that the wavelet-ARIMA model is more effective compared to the
traditional ARIMA model.