Quantification and forecast of GHG emissions from municipal solid wastes by multi-expression programming method

Area of Science:

• Environmental Science
• Climate Change Studies
• Waste Management Research

Background:

• Municipal solid waste (MSW) management is a significant contributor to global greenhouse gas (GHG) emissions.
• Understanding MSW GHG emission patterns is crucial for developing effective carbon mitigation strategies.

Purpose of the Study:

• To calculate and analyze GHG emissions from MSW landfilling and incineration in Chinese provinces from 2004 to 2021.
• To identify key socioeconomic factors influencing these emissions.
• To forecast future GHG emissions from MSW using a developed explicit model.

Main Methods:

• Calculated GHG emissions based on IPCC Models for landfilling and incineration.
• Employed a panel regression model to determine factors influencing emissions (GDP, population, PCCE).
• Utilized multi-expression programming to create a predictive model for future GHG emissions.

Main Results:

• Landfilling generated approximately 1271 MtCO2-eq, while incineration produced 198 MtCO2-eq from 2004-2021.
• Landfilling emissions rose until 2020, then declined; incineration emissions showed a consistent increasing trend.
• GDP and population positively correlated with landfill emissions; GDP and PCCE positively correlated with incineration emissions.

Conclusions:

• Projected rapid decrease in landfill emissions and rapid increase in incineration emissions from 2022-2024.
• Anticipated a slowdown in incineration emission rates and a slow decrease in landfill emissions thereafter.
• Findings offer valuable insights for policymakers and the waste management sector for informed decision-making.