A comparison of chemical MSW compositional data between China and Denmark

Area of Science:

• Environmental Science
• Waste Management
• Chemical Engineering

Background:

• Accurate chemical waste composition data is crucial for effective municipal solid waste management and pollution potential assessment.
• Existing waste composition datasets are predominantly from developed countries, limiting their applicability in developing nations.

Purpose of the Study:

• To establish a representative dataset for Chinese waste (CN dataset) chemical characteristics.
• To evaluate the reliability of the CN dataset and a Danish waste (DK dataset) by comparing estimations with laboratory analyses.
• To identify key waste components influencing data accuracy.

Main Methods:

• Compilation and screening of data to create the CN dataset.
• Summarization of the DK dataset from existing literature.
• Quantitative evaluation of both datasets by estimating chemical waste compositions in four Chinese cities.
• Comparison of estimations with actual laboratory analysis results.

Main Results:

• The CN dataset yielded significantly lower discrepancies from actual values compared to the DK dataset in most cases.
• Moisture content (food waste, paper, textiles, plastics), carbon content (food waste), and oxygen content (plastics) were identified as critical factors causing divergences.
• Fractional waste composition in China shares similarities with other developing countries but differs markedly from developed countries.

Conclusions:

• The developed CN dataset enhances the accuracy of chemical waste composition assessments in China.
• The findings suggest that the CN dataset's applicability may extend to other developing countries with similar waste profiles.
• Attention to specific parameters like moisture, carbon, and oxygen content is vital for improving waste data reliability.