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With the increasing urgency of global warming, mitigatinggreenhouse gases has become an essential agenda in many countries. Thesecountries joined hands within the Paris Agreement and supported each otherto limit the Earth's temperature to 1.5-2.0˚C. To achieve their net zero targets,looking into the future is crucial. By forecasting, countries know what kindof pathway they should take to reach their targets. This literature reviewreviewed forecasting models and approaches to project GHG emissions andachieve net zero. The reviewed studies mostly use machine learning and deeplearning models to forecast GHG emissions. Machine learning and deeplearning combined with traditional and multiple optimisations can achieve amore accurate model for predicting GHG emissions. More combinations andoptimisation of machine learning models can reach more robust and precisepredictions. However, to attain net-zero targets, forecasting should anticipatefuture emissions and consider mitigation measures. With the complexities ofadaptation and mitigation strategies, the country must plan its actions welland soundly with the support of more in-depth research.

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Achieving Net Zero: A Review of Greenhouse Gas Emission Forecasting Models and Approaches

  • 会议论文

  • 发表日期：

    2026年

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  • Katya Victory Liu,
  • Lina Gozali

摘要

With the increasing urgency of global warming, mitigatinggreenhouse gases has become an essential agenda in many countries. Thesecountries joined hands within the Paris Agreement and supported each otherto limit the Earth's temperature to 1.5-2.0˚C. To achieve their net zero targets,looking into the future is crucial. By forecasting, countries know what kindof pathway they should take to reach their targets. This literature reviewreviewed forecasting models and approaches to project GHG emissions andachieve net zero. The reviewed studies mostly use machine learning and deeplearning models to forecast GHG emissions. Machine learning and deeplearning combined with traditional and multiple optimisations can achieve amore accurate model for predicting GHG emissions. More combinations andoptimisation of machine learning models can reach more robust and precisepredictions. However, to attain net-zero targets, forecasting should anticipatefuture emissions and consider mitigation measures. With the complexities ofadaptation and mitigation strategies, the country must plan its actions welland soundly with the support of more in-depth research.