Resour source ce re reco cove very fr from om wa waste st stre - PowerPoint PPT Presentation

Resour source ce re reco cove very fr from om wa waste st stre reams: fr from om LIFE LIFE LIVEW LIVEWASTE to to H2020 H2020 SM SMAR ART ‐ Pl Plan ant Francesco Fatone and SMART ‐ Plant Consortium

o SMART ‐ Plant SMART ‐ People The SMART ‐ Plant Consortium

Outlin tline • Livestock effluents as source of fertilizers, biofuels, reusable water: the LIFE LIVEWASTE project • Municipal wastewater treatment as source of reusable water, cellulose, fertilizers, biofuels, biopolymers: the Horizon2020 SMART ‐ Plant Innovation Action • The integration of existing plants: the SMARTechnologies • The exploitation, business plan and market deplyment strategy

Curr Curren ent scenario cenario in in Cyprus Cyprus (… (…and and in in the the EU) EU)

Ho How to to in integrate the the liv livestock efflu luent treatment pl plan ants ts towards the he cir circular ular ec econo onomy co concept? Biohythane Integrated eco ‐ innovations: TPAD, scSBR, struvite, biofiltration, dynamic composting

The The LIFE LIFE LIVEW LIVEWASTE pr prot ototype otype

Resour sources ces rec ecov over ered ed by by th the LIFE LIFE LIVEW LIVEWASTE pr prot ototype otype Unit Treatment capacity tonLIVEWASTE/year 90 ‐ 100 m 3 /tonLIVEWASTE Bio ‐ hythane production 25 ‐ 30 Struvite recovery Kg/tonLIVEWASTE 0.4 ‐ 1.2 m 3 /tonLIVEWASTE Treated effluent 0.5 ‐ 0.7 m 3 /tonLIVEWASTE Reusable treated effluent 0.5. ‐ 0.7 High quality compost Kg/tonLIVEWASTE 140 ‐ 160

Te Technology Mat Maturity is proven oven and • Environmental • Socio ‐ economic • Cost ‐ benefit sustainability is assessed Did we pass the «death valley» of innovation?

From farms to cities From manure/slurry to municipal wastewater From LIFE LIVEWASTE to SMART ‐ Plant

Curr Curren ent wa wastewat ater tr trea eatm tmen ent: t: is is this is rig right fo for the the ne next 100 100 year ars? s? 406 kgCO 2 e GHG out 750,000 (5% of CH 4 ) tonnes per year (0.1% recycled) Wastewater IN Sewage works Treated Water Out Chemicals IN Sludge out Energy IN Per ML: 634 kWh Courtesy: Bruce Jefferson (2015) (2-3% of UK)

Re Resources embedded embedded to to municipal municipal wa wastewater Parameter Value Reusable water (m 3 /capita year) 91,3 Cellulose (kg/capita year) 6,6 Biopolymers; PHA (kg/capita year) 3,3 Phosphorus in P precursors (kg/capita year) 0,9 Nitrogen in N precursors (kg/capita year) 4,6 Methane (m 3 / capita year) 12,8 Organic Fertilizer (P ‐ rich compost) (kg/capita year) 9,1 Verstraete et al. (2009) Bioresource Technology 100, 5537–5545 Salehizadej and van Loosdrecht (2004) Biotechnology Advances 22, 261–279 1 1

SM SMAR ART ‐ Plan Plant over erall all tar arget The overall target of SMART ‐ Plant is to validate and to address to the market a portfolio of SMARTechnologies that, singularly or combined, can renovate and upgrade existing wastewater treatment plants and give the added value of instigating the paradigm change towards efficient wastewater ‐ based bio ‐ refineries.

The The SM SMAR ART ‐ Plan Plant partner partners 1 3

SM SMAR ART ‐ Pl Plan ant open open the the pathway to del deliver er ci circul ular ar ec econom onomy SCALE UP 1 4

SM SMAR ART ‐ Plan Plant wo workplan st structure WP7 Ethics WP7 Ethics Scale ‐ up of low ‐ carbon footprint material recovery techniques in existing wastewater treatment plants “SMART ‐ Plant” KICK ‐ OFF MEETING Verona (Italy) 08 ‐ 09/June 2016

The The SM SMAR ARTechnol chnologi gies es Conventional Secondary Effluent Conventional Primary Conventional Activated Sludge refined by Tertiary Mainstream Sedimentation replaced by Primary replaced by Secondary Mainstream SMARTechs 2a and/or 2b SMARTech3 Upstream SMARTech1 Effluent Influent Conventional or Enhanced Anaerobic Digestion integrated by Sidestream SMARTechs 4a,4b or 5 Biogas Dehydrated sludge Water line Sludge line 1 6

SM SMAR ARTech1: ch1: Pr Primary (up (upstr tream eam) dynam dynamic sie sieving ing and and cl clean ean cellu llulo lose re recove covery Inactivation Separation course biological activity Sand ‐ /grid removal parts Fibre separation 1 7

SM SMAR ARTech1: ch1: Pr Primary (up (upstr tream eam) dynam dynamic sie sieving ing and cl and clean ean cellu llulo lose re recove covery Realization of a full ‐ scale plant  all process steps combined in one process Optimization:  Efficiencies of different process steps  Energy ‐ /chemical consumption individual process steps  Quality cellulose fiber after different process steps  Optimization interdependence Market development  Marketing and valorization of recovered cellulose  Reuse in asphalt  Raw material for composite (Brunel)  Insulation materials (In development, not sure yet) First pilot testing 1 8

SMAR SM ARTech2a: ch2a: Sec Secondar ndary mai mainstream am bi biog ogas as recove re covery by by poly polyfoam am bi biofilt ofilter  B1 Technical Part 1. An innovative anaerobic immobilized polymeric biofilter. Reaction volume ‐ 25 m 3 will be designed and 2. installed in the WWTP of Karmiel (North of Israel) 3. Characteristics: 100 ‐ 120 m 3 /d. ‐ ‐ Removal of 30 ‐ 40% of CODf ‐ Additional of 25% biogas ‐ Reduction of 25 ‐ 30% energy consumption. 4. Operation optimization, monitoring and validation: ‐ biogas yield ‐ biomass activity ‐ treated effluent quality 1 19 9

SM SMAR ARTech2b: ch2b: Sec Secondary ndary mai mainstream am SCEPPHAR SCEPPHAR SMARTech2b Mainstream SCEPPHAR  Two SBR  Buffer tank  P ‐ recovery system 2 0

SM SMAR ARTech3: ch3: Te Tertiary nutrien nutrient re recove covery by by meso solit lite and and nano nano ion ex exchange Secondary influent 10 ‐ 60 m 3 /day 2 1

SM SMAR ARTech4a/b ch4a/b Sides Sidestream am S. S.C.E.N C.E.N.A. A. 2 2

SM SMAR ARTech5 ch5 Sides Sidestream am SCEPPHA SCEPPHAR Mg(OH) 2 1-Production of VFAs Wastewater and struvite from cellulosic sewage Cellulosic Struvite S/L Fermentation sludge Sludge VFAs 2-Nitrogen removal via- Treated Reject nitrite driven by Selection Reject Water Water of PHA storing biomass Nitritation and Selection SBR VFAs Selected PHA PHA 3-PHA accumulation storing biomass extraction Fed-bacth reactor 2 3

Downs Downstream am SM SMAR ARTechA chA Pos ost ‐ pr processi ocessing ng of of re reco cove vere red cellulose cellulose and and PHA PHA fo for bio bio ‐ co comp mposites pr production oduction  Downstream SMARTechA: Incorporation of the recovered cellulosic and PHA ‐ rich materials as raw materials for the production of new type of sludge plastic composite (SPC);  Processing of SPC is to be based on the modified extrusion process used for processing classical WPC; 2 4

Downs Downstream am SM SMAR ARTechB chB Pos ost ‐ pr processing ocessing of of ce cellulosic llulosic and and P ‐ rich rich sludg sludge Biodrying  Obtain a biofuel from cellulosic Dynamic Composting  Obtain a compost rich in sludge nutrients from P-rich slduge 1000 L reactor Exhaust gases Solid fraction Cellulosic sludge Dewatering system Aerobic rotary drum Aerobic biodrying reactor (bidorying 2 nd phase) (bidorying 1 st phase) 100 -250 L reactor Bio-drying is a compost-like process, however, the eventual 1) Mixture of bulking agent + P-rich sludge (SCENA) goal of this concept is to use the metabolic heat to remove 2) Mixture of bulking agent + Mesolite recovered compounds water from the cellulosic sludge at the lowest possible + Prich sludge residence time and minimal carbon biodegradation hence 3) Mixture of mesolite recovered compounds + P-rich sludge preserving most of the gross calorific value of the waste matrix + conventional WWTP sludge 2 5

SMARTechB Post-processing of cellulosic and P-rich sludge Evaluation of P fertilizing effects of P-rich sludge and struvite P: “the disappearing nutrient” find new sources Mg: “the forgotten element” widespread deficiency,increasingly used in fertilizer programs Plant species: monocots (maize) and dicots (grapevine) 2 6

SM SMAR ART ‐ Pl Plan ant Business Business pl plan an and and mar market et deplo deployment st strate tegy Primary licensing stream Lever and Cross licensing stream 2 7

The The busi business ess model model is is develo loped pr profilin ofiling key target gr group oups: • Water utilities : grouped into basic, intermediate and advanced clusters • Chemical and downstream processing industries : related to the four main strategic pillars: Construction, additive, Agrics and Intermediates 2 8

Pu Public/private vate wa water utility utility ma managemen nagement per perspectiv pectives es to to deliv deliver cir circular ar ec econom onomy wi with the the chem chemic ical al ind industrie ries Value scenarios Water pricing Interviews Information partners Private Public Water pricing models Residual value Production function approach Optimization models and programming Water utilities needs Hedonic pricing Opportunity Cost Pricing Scenarios 2 9