5.2.1 Materials
Ten varieties of seaweed were collected from beaches in Cork, in the south of Ireland (51°N, -9°E). The seaweeds were beach cast and harvested from their natural environment. The samples were taken in August to represent peak growing conditions [28]. Nine of the seaweeds were brown, one was green. The brown species were: Ascophylum nodosum, Himalthalia elongate, Laminaria digitata, Saccorhiza polyschides, Fucus spiralis, Fucus serratus, Fucus vesiculosus, Alaria esculenta and Saccharina latissima. The green species
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was Ulva lactuca. Approximately 25 kg of each species was collected. These seaweeds are the most commonly occurring around the coast of Ireland.
Inoculum was sourced from a combination of numerous lab scale reactors processing grass silage, dairy slurry and macro-algae; all of these reactors operated at 37oC.
5.2.2 Methods
5.2.2.1 Method design
Proximate and ultimate analysis and sample preparation for BMP assay
A representative sample of each seaweed was sampled for TS and VS using the standard method of drying (105oC for 24 hours and further baking at 550oC) [29]. Samples were prepared for ultimate analysis by drying for 24 hours at 105oC and then finely grinding to
pass through a 600 µm sieve. Samples were analysed for C, H, N, and O (O calculated by difference) on an ash free basis using a CE 440 elemental analyser.
Prior to digestion, samples were macerated using a Buffalo macerator to a particle size of less than 4 mm. The pH of the samples, were measured using a Jenway 3510 pH meter. The prepared samples were placed in sealed containers and frozen at -20oC; they were
defrosted prior to BMP assessment. 5.2.2.2 BMP assay
The Bioprocess AMPST II® system was used to conduct BMP assays. All samples were assessed in triplicate. In each run of the system one of the samples was inoculum and one was cellulose. An inoculum to substrate ratio (I:S) on a VS basis, of 2:1 was used [30]. The reactor vessels had a working volume of 400 ml with a total head space of 250 ml. After the calculated inoculum and substrate amounts were placed in the reactor vessels, nitrogen was flushed through the system to create anaerobic conditions. Each reactor vessel was placed inside a water bath constantly maintained at 37oC. A mixing system was connected to each reactor vessel and was continuously operated at a speed of 30 rpm, alternating between on and off for 60 second periods. The biogas produced was passed through a solution of 3M NaOH to remove CO2, H2S and other impurities. The biomethane was then
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passed through a gas tipping device which recorded the volume of gas produced for each reactor vessel. This data was constantly recorded and logged for each day. Each BMP assay was ran in triplicate and assessed for standard deviation. The total average biomethane produced from the inoculum was subtracted from the average biomethane produced by each sample to determine specific biomethane production. All results were automatically adjusted for standard temperature and pressure and overestimation error was eliminated for the flush gas.
In total 14 BMP assays in triplicate were conducted for this experimental procedure. These included for the 10 species of seaweed. The assays were carried out in two runs; thus a BMP of the inoculum and of cellulose were carried out twice.
5.2.2.3 Kinetic analysis
The kinetic analysis allows a viewpoint on the biodegradability and the rate of
biodegradability of the substrate. Kinetic and statistic modelling was applied to the output of the BMP system. Data was taken from cumulative production curves and input to a Matlab code to output kinetic values. A first order differential equation was used to determine the decay constant values (Eqn. 5.1). The modified Gompertz formula (Eqn. 5.2) was used to develop a list of variables to describe the decay process of organic matter in batch tests [31].
= . 1 − exp Eqn. 5. 1
= ∙ exp{ − exp[ ∙ ∆ − ] + 1} Eqn. 5. 2
Where,
Y(t) is the cumulative biomethane yield (L CH4 kg−1 VS) at a digestion time, t (days).
Ym is the maximum biomethane potential (L CH4 kg−1 VS) of the substrate added.
k the decay constant (days -1) is a measure of the rate that the substrate has been degraded.
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M(t) is the cumulative biomethane yield (L CH4 kg−1 VS) at a given time t (days).
P is the maximum biomethane potential (L CH4 kg−1 VS) of the substrate from the BMP test.
Rmax is the maximum biomethane production rate (L CH4 kg−1 VSd-1).
Δ the lag phase is a measure of how long it takes (days) before biochemical methane production starts to occur.
t is the time (days).
T50 is the half-life (days) and is a measure of how long it takes to produce half of the
maximum cumulative yield of biomethane.
R2 is a measure of how the kinetic equation model fits the curve of biomethane production (%).
5.2.2.4 Theoretical biomethane calculation
The ultimate analysis data allows the theoretical biomethane yield to be calculated. Using the Buswell equation (Eqn. 5.3) values are input to give a maximum potential methane yield through conversion of VS to methane and carbon dioxide [32]. The molar volume of the gases is taken as 22.414 L at 0oC and 1 atm. However a short coming of using the
Buswell equation is that it does not take into account maintenance and anabolism of the microbial community. Also some of the VS content present in macro-algae consists of proteins and fibres which are difficult to break down. This leads to a reduction in BMP yields when compared to yields derived from the Buswell equation. Therefore an over estimation of biomethane yields occur which leave theoretical yields as ceiling values for BMP assays.
"# $%&'+ () − %*−'+, $+& → (#++ %.−'*, "$* + (#+− %.+'*, "&+ (Eqn. 5.3)
5.2.2.5 Statistical analysis
Statistical analyses were performed using the software SAS 9.3 (SAS Institute Inc., Cary, NC, USA). Analysis of variance (ANOVA) was carried out in order to assess the influence of
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substrate on biochemical methane yield with the BMP run regarded as a block effect and substrate regarded as the main effect. The significance of differences in methane yield between substrates was determined by multiple comparisons applying the test procedure SIMULATE in SAS [33]. The significance level α, was set to p < 0.05.