Cross-sectoral emission interdependencies of waste management

This study examines emission interdependencies within the waste sector and between waste and other economic domains, energy, transport, water, and communications, using Life Cycle Assessment (LCA) methodologies with emphasis on process-based and hybrid approaches. The analysis employs the EXIOBASE multi-regional input-output database. Statistical correlation is applied to identify commonalities and divergences in emission drivers. Results indicate strong correlations among certain landfill waste streams, particularly organic-based materials, as well as links between plastics and wood, suggesting shared decomposition or management pathways. Moderate correlations appear in cross-sectoral interactions, especially between waste, energy, and transport, while weak correlations are observed in processes with distinct treatment mechanisms, such as landfill versus wastewater. Methodologically, the study highlights challenges posed by high-dimensional datasets, including multicollinearity, which limit the effectiveness of linear models. These findings underscore the complexity of sectoral interdependencies and the need for both integrated and material-specific strategies. By demonstrating how systemic tools like EXIOBASE can capture these linkages, the research provides a foundation for constructing more robust emission models and informing targeted mitigation policies. The results contribute to advancing environmental accounting frameworks while offering practical insights for emission reduction planning across interconnected sectors.