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Ioannis Markidis WISE CDT PhD Student, University of Bath

Anaerobic digestion of sewage and domestic wastes. How small can it be?. Ioannis Markidis WISE CDT PhD Student, University of Bath Supervisors: Dr Marta Coma & Dr Tom Arnot. Research Aim. Substrate. - Influent COD - Volatile solids - Particle size - Methane potential. Biogas.

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Ioannis Markidis WISE CDT PhD Student, University of Bath

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  1. Anaerobic digestion of sewage and domestic wastes. How small can it be? IoannisMarkidis WISE CDT PhD Student, University of Bath Supervisors: Dr Marta Coma & Dr Tom Arnot

  2. Research Aim Substrate - Influent COD - Volatile solids - Particle size - Methane potential Biogas - Biogas yield - Methane content - Produced volume • Scale down AD • Optimize biogas production • Explore added value options • Decentralized approach VOLUME ↓ - Nutrients (P, N) - Heavy metals - COD removal - Quantity - Organic loading rate - HRT / Volume - Sludge age - Temperature & pH Digestate MODELLING

  3. Challenges: Benefits & Restrictions Why small scale? Local treatment (reduced transportation and costs) Local fertilizer & renewable energy production More flexible & simpler infrastructure (low footprint) Reduced load in existing sewers and WWTP Local economic & social benefits • Technical limitations (operational conditions, gas leakage, feedstock availability) • Feedstock limitations (co-digestion unavailable) • Economies of scale • Policies, energy prices, gate fees

  4. What was found in literature Publications in Scopus, since 2002, with the keyword ‘’Anaerobic digestion’’

  5. AD database construction Parameters Feedstock type • Food waste • Sewage • Biogas yield (m3 kg-1 VS) • Methane content (%) • Source separated black waste • Farm - animal • Organic loading rate (kg COD m-3d-1) • COD removal efficiency (%) Application • Full scale • Pilot • Reactor volume and type • Lab • Feasibility studies • Hydraulic retention time (d) • Temperature (o C)

  6. Feedstock types and operational parameters

  7. Feedstock types and operational parameters

  8. Analysing the literature data

  9. Developing a simple AD model • To predict the influence of various parameters on the process • To correlate gas production and substrate composition • To simulate the outcomes of literature cases • To explore various additional potential scenarios • COD based kinetics (Monod equation) • Stoichiometry & Elemental balances (Buswell equation) • Mass balances • Reactor design (operational parameters)

  10. Factors affecting the AD process • Baseline composition: % carbohydrates, proteins, lipids, VFA and non biodegradable fraction • Fixed parameters: Volume, HRT, ODM, DM, Temperature, Kinetics

  11. The influence of composition ‘’Small variations in composition can have strong impacts on the methane produced’’

  12. Factorial analysis of variations in composition

  13. Model simulations versus the literature data

  14. Outcomes & future steps • 68% of small scale AD applications are installed in rural areas • Gather more data from industrial collaborators and existing AD plants • Dilute influents require larger reactor volumes - Hard to maintain a low OLR • So pre-treatment / dewatering is needed – reduced household water use will be beneficial • The developed is model robust and can be widely used • Use advanced process modelling tools to simulate small scale AD scenarios • Small variations in composition have a big impact on the methane produced • Lab experiments to validate the modelling results and test feedstocks • SA: Early indications of the limits within which small AD might work • Life cycle assessment to evaluate the economic potential of small scale AD

  15. Thank you for your attention! Questions?

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