WP3: Systematic Quantification of Biogas Potential in Urban Organic Waste, DTU-E
DTU-E Ph.D. project description, Temesgen Fitamo
1. Background and motivation:
The Danish government has developed a plan ‘’energy strategy 2050’’ to become coal, oil and gas
independent nation by 2050. Obviously, wind energy is expected to have the highest renewable
energy share in Danish energy supply system however the remaining must come from other reliable
renewable energy source, mostly from biomass. Besides this, energy from biogas is needed during
periods of little wind energy and for transport sector. Moreover, EU target requires 90 % greenhouse
gas emission (GHG) reduction by 2050 that demands reduction of emission from agricultural land,
improved energy and material recycling system for biomass residues. Biogas production is the most
efficient way to reduce GHG emission due to substitution of fossil fuels and low methane (CH 4) and
nitrous oxide (N2O) emission during the application of digestate on agricultural land as a fertilizer.
Hence, biogas must be a major contributor in the Danish energy supply system to meet the 2050
energy strategy and realize 100% renewable energy reliance. Accordingly, the Danish government’s
energy plan targets a 4 fold increase in Danish biogas production. The high moisture content of
biomass suits well to anaerobic digestion for biogas production. The biogas will be upgraded and can
be utilized in a more versatile way as transport fuel, natural gas, heating and electricity. Meanwhile,
the current biogas production process is not yet fully optimized and efficient. Barriers in the form of
poor assessment of biogas production must be removed for biogas production to become
economically sustainable and the use of biogas technology to be expanded. Biogas production and
GHG emission reduction are both related invariably to the biomass composition and value chain
management from biomass production in agriculture or household up to field application. For this
reason, there is a need to develop models and decision support tools that will help politicians,
investors, farmers and biogas companies to make scientifically based decision by analyzing alternative
comprehensive biogas production value chain frame work analysis, identify barriers in investment and
new sources of alternative biomass fraction for biogas production.
This PhD research is part of a BioChain project financially supported by a grant from the Danish
Council for Strategic Research (Commission on Sustainable Energy and Environment).Systematic
quantification of biogas potential and characterization of organic pools will be carried out to develop
efficient and environmentally friendly production value chains linking the biomass characterization
with biogas production, GHG emission reduction and utilization of nutrients in the digestate.
2. General Objective of the Research
The overall purpose of the research is to develop rapid and reliable analytical method and
computational model that predicts biochemical methane potential(BMP) of various ranges of
household and industrial organic waste fractions as well as investigate the effect of hydraulic
retention time (HRT) and co-digestion of organic household waste with garden waste and wastewater
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treatment primary sludge in continuous stirred tank reactor (CSTR) and also quantification of fugitive
greenhouse gas (GHG) emissions from full scale biogas production processes. Please, see appendix A
for more detailed information on the methodologies and deliverables.
3. Methodology:
Activity 1: Rapid Biochemical methane potential (BMP) Analysis
Partial least square (PLS) model will be built using BMP data from batch assay (VDI 4630) and NIR
spectra obtained with optimal data pre-processing. The spectra and methane yield of household and
industrial organic waste fractions will be input to develop a computational model that predicts BMP.
Activity 2: Co-digestion and Effect of HRT on biotransformation of organic pools in CSTR’s
The proposed test involves running continuous stirred tank reactors (CSTRs) with household waste,
co-digestion of household waste and garden waste (green waste), co-digestion of wastewater
treatment plants (WWTPs) primary sludge and household waste and also digestion of primary sludge
without co-substrate at various hydraulic retention time (HRT) and optimal biogas production reactor
condition. Inoculum will be collected from waste water treatment plant anaerobic digesters and also
from reactors running with household waste as feedstock.
Activity 3: Quantification of Fugitive Emissions
The rate of fugitive greenhouse gas (GHG) emission is computed based on measured downwind
plumes of greenhouse gases in an appropriate distance from the biogas plant that in turn will be
compared to known rate of released tracer gas at the emission source. The atmospheric
concentration will be measured by methane/acetylene and nitrous oxide/nitrate analyzers, based on
cavity ring analytical approach. The analyzers have GPS feature to relate the measured concentrations
with the local geographical area.
4. Deliverables:
 The expected outcome of the research based on NIR analysis is rapid and reliable analytical
method and computational model that predicts biogas production.
 The outcome of CSTRs research is kinetic constant parameter, detailed physicochemical
characteristics of substrates and co-substrates during anaerobic conversion and
physicochemical composition of digestate.
 Quantification of fugitive GHG emissions from a full scale biogas plant.
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5. Timeline of Activities
CSTR,BMP Model Development
& Quantification of Fugitive Emission
CSTR 1: HHW & HHW+GW
CSTR2:HHW & HHW+GW
CSTR3:HHW & HHW+GW
CSTR4:Sludge & Sludge + HHW
CSTR5:Sludge & Sludge + HHW
CSTR6:Sludge & Sludge + HHW
Batch BMP Assay Set Up & NIR 1
Batch BMP Assay Set Up & NIR 2
Batch BMP Assay Set Up & NIR 3
Batch BMP Assay Set Up & NIR 4
Batch BMP Assay Set Up & NIR 5
Batch BMP Assay Set Up & NIR 6
BMP PLS Model development
Mass Balance
Fugitive emission measurement
campaign
Fugitive emission Quantification
Journal Article manuscript writing
Ph.D Thesis writing
2014
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