In the quest for sustainable management of liquid fraction of manure- insights from a life cycle assessment

Main Presenter: Rahul Ravi 

Co-Authors: Miriam Beyers Claudio Brienza Hongzhen Luo Ivona Sigurnjak Sander Bruun Erik Meers

As nitrate vulnerable zones, Flanders and the Netherlands are bound by legal limits for application of animal manure and its derivatives. The Nitrates Directive limits nitrogen (N) application to 170 kg N ha-1 y-1 and local legislation can limit phosphorus (P) application as low as 40 kg P205 ha-1 y-1.

Consequently, surplus manure is often processed, and solid-liquid separation of animal manure is used as a starting point where N is predominantly up-concentrated in liquid fraction (LF) and P in solid fraction (SF). The P-rich SF of manure is transported to P-deficient regions, and the N-rich LF is treated through conventional aerobic treatment, i.e. nitrification-denitrification (NDN) (Sigurnjak et al. 2019). While NDN is a popular choice to manage LF owing to ease of operation, the shortcoming is that the N as a nutrient is converted to N2 gas, hence ‘lost’ for the further use in agriculture. In recent years, however, with the circular economy-led impetus, full-scale installations are implementing innovative techniques to valorise the N from LF. For example, ammonia (NH3) stripping-scrubbing from LF can yield ammonium nitrate or ammonium sulphate (depending on the choice of used acid), whereas manure evaporation in combination with/ without a reverse osmosis (RO) module can yield an N and K (Potassium) concentrate. The ensuing products are seen as potential substitutes for mineral N and K fertilizer.

A life cycle assessment (LCA) is conducted to understand the trade-offs between the aforementioned LF valorisation techniques (stripping-scrubbing, reverse osmosis, evaporation), considering NDN as the business-as-usual case. A consequential perspective is applied and the system boundaries encompass LF processing and subsequent field application of the product. The LCA model uses primary data from full-scale installations, complemented by uncertainty and global sensitivity analyses of the results. These results are then used to identify the potential for the technology in terms of environmental benefits as well as key parameters driving uncertainty.

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