Sustainability Research Reveals Effective Framework for Construction Waste Reduction

Strategic Insights -

Construction waste accounts for a significant portion of solid waste filling landfills worldwide, prompting researchers to investigate effective frameworks for reducing this waste. A study by Hangzhou Dianzi University employed the Analytic Hierarchy Process (AHP) and artificial neural networks (ANN) to develop a solid waste management assessment tool. The research found that a combination of AHP and ANN can be a key decision support tool for landfilling, incineration, and composting waste management strategies, considering environmental, economic, and social characteristics. The study suggests a management hierarchy that begins with rethink, reduce, redesign, refurbish, reuse, incinerate, compost, recycle, and eventually dispose of waste.

Key Takeaways:

  • The study found that recycling construction waste can help reduce the quantity of waste sent to landfills and the demand for energy and natural resources.
  • A management hierarchy that prioritizes rethink, reduce, redesign, refurbish, reuse, incineration, composting, recycle, and disposal is effective in reducing construction waste.
  • The proposed framework for solid waste management consists of four components: developing different level structures for fluffly AHP, calculating weights, collecting data, and making decisions.
  • The combination of AHP and ANN has emerged as a key decision support tool for landfilling, incineration, and composting waste management strategies.
  • Composting has the highest sustainable performance when a balanced weight distribution of criteria is assumed, especially when the environmental component is considered.
  • However, if social and economic features are addressed, incineration or landfilling may have more favorable characteristics.

Statistics:

  • Construction waste accounts for a significant portion of solid waste filling landfills worldwide.
  • The study used a standardized questionnaire to gather data from waste management practitioners in three industry sectors.
  • The survey data was analyzed using ANN and AHP to develop a solid waste management assessment tool.
  • The framework consists of four components, including developing different level structures for fluffly AHP, calculating weights, collecting data, and making decisions.
  • Composting has the highest sustainable performance when environmental considerations are prioritized.

Sources:

  • Lu, Y., Ge, Y., Zhang, G., Abdulwahab, A., Salameh, A. A., Ali, H. E., & Le, B. N. (2023). Evaluation of waste management and energy saving for sustainable green building through analytic hierarchy process and artificial neural network model. Chemosphere, 137708. doi: 10.1016/j.chemosphere.2023.137708
  • NewsRx. (2023, January 27). Hangzhou Dianzi University Reports Findings in Sustainability Research (Evaluation of waste management and energy saving for sustainable green building through analytic hierarchy process and artificial neural network model). Ecology, Environment & Conservation, 155.