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Abstract: Resource-efficient nitrogen management is of high environmental and economic interest, and manure represents the major nutrient flow in livestock-intensive regions. Ammonia stripping/scrubbing (SS) is an appealing nitrogen recovery route from manure, yet its real-life implementation has been limited thus far. In nutrient surplus regions like Flanders, treatment of the liquid fraction (LF) of (co–)digested manure typically consists of nitrification/denitrification (NDN) removing most N as nitrogen gas. Integrating SS before NDN in existing plants would expand treatment capacity and recover N while maintaining low N effluent values, yet cost estimations of this novel approach after process optimisation are not yet available. A programming model was developed and calibrated to minimise the treatment costs of this approach and find the balance between N recovery versus N removal. Four crucial operational parameters (CO2 stripping time, NH3 stripping time, temperature and NaOH addition) were optimised for 18 scenarios which were different in terms of technical set-up, influent characteristics and scrubber acid. The model shows that SS before NDN can decrease the costs by 1 to 56% under optimal conditions compared to treatment with NDN only, with 1 to 8% reduction for the LF of manure (22–29% recovered of N treated), and 11 to 56% reduction for the LF of co-digested manure (42–67% recovered of N treated), primarily dependent on resource pricing. This study shows the power of modelling for minimum-cost design and operation of manure treatment yielding savings while producing useful N recovery products with SS followed by NDN.

Abstract: The agri-food value chain is a major cause of nitrogen (N) and phosphorus (P) emissions and associated environmental and health impacts. The EU's farm-to-fork strategy (F2F) demands an agri-food value chain approach to reduce nutrient emissions by 50% and fertilizer use by 20%. Substance flow analysis (SFA) is a method that can be applied to study complex systems such as the agri-food chain. A review of 60 SFA studies shows that they often lack detail by not sufficiently distinguishing between nodes, products and types of emissions. The present study aims to assess the added value of detail in SFAs and to illustrate that valuable indicators can be derived from detailed assessments. This aim will be attained by presenting a highly-detailed SFA for the livestock-intensive region of Flanders, Belgium. The SFA distinguishes 40 nodes and 1827 flows that are classified into eight different categories (e.g. by-products, point source emissions) following life cycle methods. Eight novel indicators were calculated, including indicators that assess the N and P recovery potential. Flanders has a low overall nutrient use efficiency (11% N, 18% P). About 55% of the N and 56% of the P embedded in recoverable streams are reused providing 35% and 37% of the total N and P input. Optimized nutrient recycling could replace 45% of N and 48% of P of the external nutrient input, exceeding the target set by the F2F strategy. Detailed accounting for N and P flows and nodes leads to the identification of more recoverable streams and larger N and P flows. More detailed flow accounting is a prerequisite for the quantification of technological intervention options. Future research should focus on including concentration and quality as a parameter in SFAs.

Keywords: A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)

Impact Factor: 11.1

DOI: 10.1016/J.JCLEPRO.2023.137278

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	“Ammonia stripping and scrubbing followed by nitrification and denitrification saves costs for manure treatment based on a calibrated model approach”. Vingerhoets R, Brienza C, Sigurnjak I, Buysse J, Vlaeminck SE, Spiller M, Meers E, Chemical engineering journal 477, 146984 (2023). http://doi.org/10.1016/J.CEJ.2023.146984 Abstract: Resource-efficient nitrogen management is of high environmental and economic interest, and manure represents the major nutrient flow in livestock-intensive regions. Ammonia stripping/scrubbing (SS) is an appealing nitrogen recovery route from manure, yet its real-life implementation has been limited thus far. In nutrient surplus regions like Flanders, treatment of the liquid fraction (LF) of (co–)digested manure typically consists of nitrification/denitrification (NDN) removing most N as nitrogen gas. Integrating SS before NDN in existing plants would expand treatment capacity and recover N while maintaining low N effluent values, yet cost estimations of this novel approach after process optimisation are not yet available. A programming model was developed and calibrated to minimise the treatment costs of this approach and find the balance between N recovery versus N removal. Four crucial operational parameters (CO2 stripping time, NH3 stripping time, temperature and NaOH addition) were optimised for 18 scenarios which were different in terms of technical set-up, influent characteristics and scrubber acid. The model shows that SS before NDN can decrease the costs by 1 to 56% under optimal conditions compared to treatment with NDN only, with 1 to 8% reduction for the LF of manure (22–29% recovered of N treated), and 11 to 56% reduction for the LF of co-digested manure (42–67% recovered of N treated), primarily dependent on resource pricing. This study shows the power of modelling for minimum-cost design and operation of manure treatment yielding savings while producing useful N recovery products with SS followed by NDN. Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL) DOI: 10.1016/J.CEJ.2023.146984 Additional Links: UA library record; WoS full record Permanent link \| Save citation: RTF PDF LaTeX \| Export record: BibTeX Endnote ISI RIS Word XML
	“Detailed nitrogen and phosphorus flow analysis, nutrient use efficiency and circularity in the agri-food system of a livestock-intensive region”. Vingerhoets R, Spiller M, De Backer J, Adriaens A, Vlaeminck SE, Meers E, Journal of cleaner production 410, 137278 (2023). http://doi.org/10.1016/J.JCLEPRO.2023.137278 Abstract: The agri-food value chain is a major cause of nitrogen (N) and phosphorus (P) emissions and associated environmental and health impacts. The EU's farm-to-fork strategy (F2F) demands an agri-food value chain approach to reduce nutrient emissions by 50% and fertilizer use by 20%. Substance flow analysis (SFA) is a method that can be applied to study complex systems such as the agri-food chain. A review of 60 SFA studies shows that they often lack detail by not sufficiently distinguishing between nodes, products and types of emissions. The present study aims to assess the added value of detail in SFAs and to illustrate that valuable indicators can be derived from detailed assessments. This aim will be attained by presenting a highly-detailed SFA for the livestock-intensive region of Flanders, Belgium. The SFA distinguishes 40 nodes and 1827 flows that are classified into eight different categories (e.g. by-products, point source emissions) following life cycle methods. Eight novel indicators were calculated, including indicators that assess the N and P recovery potential. Flanders has a low overall nutrient use efficiency (11% N, 18% P). About 55% of the N and 56% of the P embedded in recoverable streams are reused providing 35% and 37% of the total N and P input. Optimized nutrient recycling could replace 45% of N and 48% of P of the external nutrient input, exceeding the target set by the F2F strategy. Detailed accounting for N and P flows and nodes leads to the identification of more recoverable streams and larger N and P flows. More detailed flow accounting is a prerequisite for the quantification of technological intervention options. Future research should focus on including concentration and quality as a parameter in SFAs. Keywords: A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL) Impact Factor: 11.1 DOI: 10.1016/J.JCLEPRO.2023.137278 Additional Links: UA library record; WoS full record; WoS citing articles Permanent link \| Save citation: RTF PDF LaTeX \| Export record: BibTeX Endnote ISI RIS Word XML