Analysis of Sewage Sludge Recovery System in EU - in Perspectives of Nutrients and Energy Recovery Efficiency, and Environmental Impacts

The purpose of this research is to contribute to sewage sludge management by providing a scientific benchmark of the performance of sewage sludge recovery systems (SSRS). This can serve as input to improved policy development, management practices and technology development. This report also contributes to the BioTEnMaRe project by examining resource recovery efficiency (nutrients and energy) and life cycle environmental impacts quantitatively in a systems-wide perspective. Firstly, a literature study on the status quo provides an understanding of the technologies and state-of-the-art strategies for sludge management. As well, a review of previous researches on the performances of sludge treatment system was carried out to identify the potential academic improvements in this field. The research method is comprised of material flow analysis (MFA) and life cycle assessment (LCA). Based on the principles of MFA and LCA, a non-quantitative generic model was built to describe the profile and framework of the sludge recovery system. In addition, an analysis at more specific level was carried out by using the European Union (EU) as the study case, according to the generic model. Three technological configurations were used as the three following scenarios; composting combing land application, anaerobic digestion combining land application and CHP, and anaerobic digestion combining land application and biogas upgrading. The scenarios each have their own advantages and disadvantages. In summary, Scenario 1 has the highest relative nutrients recovery efficiency, but it cannot recover energy in sludge. Although Scenario 3 represents the highest energy recovery efficiency, it does not perform as well as Scenario 2 in terms of environmental impacts. Scenario 2 performs the best with regards to environmental impacts, and it also has acceptable performance in nutrient and energy recovery efficiency. Therefore, Scenario 2 can be considered as the optimal option.