Effect of particle size on the biomethanation kinetics of mechanically pretreated Sargassum spp biomass

doi:10.21203/rs.3.rs-2957784/v1

Purpose

The collection and use of Sargassum spp. as feedstock for the production of valuable products such as biomethane by anaerobic digestion (AD) would mitigate the negative impact of the blooms and the costs related to waste management in the Dominical Republic.

Methods

In this work, the effect of the particle size of pelagic Sargassum spp. biomass, as a result of mechanical pretreatments, on the biomethanation was determined. The Biochemical Methane Potential (BMP) of the samples was determined using an Automatic Potential System Test II (AMPTS® II). The kinetic parameters of the reaction were scientifically evaluated by using First order kinetic Model and modified Gompertz Model.

Results

We observed that BMP increased by 78.85% when particles were reduced from 50000 µm to 505 µm and by 73.61% when particles were reduced from 50000 µm to 107 µm.

Conclusion

A low methane yield from biomass S.3 compared to S.2 could be related to the excessive reduction of particle size. The fine particles are subject to the formation of aggregates and consequently, the contact area between the algae cells and the microorganisms that operate the anaerobic digestion process decreases.

macroalga

Sargassum sp

anaerobic digestion

kinetics

granulometry

energy analysis

Sargasso was first sighted in the 15th century by Christopher Columbus at the area known as the Sargasso Sea. Sargassum spp. is not only found in the Sargasso Sea but its extension is much wider, as reported by the great Atlantic Sargassum belt (GASB)[1], it extends from South Africa to the Gulf of Mexico and blooms occur in the central Atlantic Ocean and the Caribbean Sea since 2011 [2]. Although there are 2000 species of brown macroalgae, the Caribbean sea is characterized by the presence of the holopelagic species Sargassum natans (morphotypes I and VIII) and S. fluitans (morphotype III)[3]. These Sargassum spp. have invaded the beaches of the southern and eastern coasts of the Dominican Republic, affecting the tourism, fishing, biodiversity, and health of the nearby communities[4]. This macroalga is rich in nutrients and bioactive substances and can also be used for the production of green energy[5]. The recovery and valorization of Sargassum spp. would mitigate the negative impact of the blooms and the costs related to waste management[6]. In the areas covering green and circular economies, algal biomass arouses considerable interest as feedstock towards value-added products, from food to fuels. For instance, algal biomass can be used for the production of biogas via anaerobic digestion[7] (AD). However, AD is influenced by various factors such as composition of the inoculum, composition of the substrate, temperature, pH and experimental configuration[8]. Plant biomass, including Sargassum spp., are generally rich in cellulose, and lignocellulose, which is known to be a rigid and complex structure that inhibits the AD process[9]. Thus, the pre-treatment of the Sargassum spp. biomass is required to improve the AD process, and consequently increase the biogas yield. There are several types of pre-treatment: mechanical, thermal, chemical, enzymatic[4]. Mechanical pre-treatment is a known technique which consists in reducing biomass into small particles with the aid of knives, blades, blenders. Biomass cutting or grinding increases the surface-to-free volume ratio of the lignocellulose matrix, which improves the hydrolysis of complex carbohydrates into sugars by fermentation or anaerobic digestion[10] due to the higher surface area available to microorganisms that results in an increase of biodegradability[11].

All the pre-treatments mentioned involve an energy consumption that varies according to the pre-treatment and the operating conditions. Evaluation of energy consumption is important for both the economics and energy balance of biomass conversion[12].

The rate and stability of the anaerobic digestion process is significantly affected by the particle size and the choice of equipment used for the mechanical pretreatment of the biomass[13]. A study conducted on Sargassum muticum showed that the yields of methane increased by 54.5% when the biomass was chopped[14]. A study conducted on the macroalga Sargassum fulvellum shows that the production of methane increases by 52.34% on biomass with particle size of 75–850 µm compared to that with higher particle size (106 µm,4.75 mm)[15]. Other studies conducted mainly on municipal solid waste samples showed that the yield of organic material with a particle size of 10 mm in diameter leads to an increase in yield of 20% compared to that with a particle size of 100 mm[16]. In another study conducted on organic residues from typical Japanese cuisine, the reduction of particle size from 0.888 to 0.718 mm increased the methane production in 28% [11]. Similarly, for sisal fiber waste, a 22% increase in biogas production was observed when the fiber length changed from 100 mm to 2 mm[17]. There is literature available on the effect of substrate particle size on the anaerobic digestion of some Sargassum spp. or other organic material, however, studies regarding the effect of particle size on the biomethanation kinetics of the pelagic S. natans (morphotypes I and VIII) and S. fluitans (morphotype III) have not been conducted.

This work represents an important contribution in understanding how the size of these specific Sargassum spp., that affect the Caribbean coasts, influence the biomethanation kinetics using granulometric analysis. In addition, the energy consumed during mechanical pretreatment of the biomass for the obtention of different particle sizes, and the energy produced on the anaerobic digestion of the Sargassum spp. biomass were estimated. This aspect is important to evaluate the potential cost of the pre-treatment, for this reason the energy necessary to reduce the size of the sample has been estimated.

2.1 Substrate and inoculum

Fresh Sargassum spp., accumulated on barriers located to a distance of 300 meters from the eastern coast of the Dominican Republic, was collected in Punta Cana during Spring season. On the same day of collection, the biomass was stored at 4°C. Samples were washed with deionized water, and epiphytes and non-structural elements were removed from the biomass. Excess water was removed from the biomass with absorbent paper towel, and samples were air dried indoors for several days until constant weight was achieved.

The inoculum was prepared by diluting fresh cow manure in tap water in a 1:1 ratio and mixed with a wooden stick until completely dissolved.

2.2 Biomass pre-treatment

Sargassum spp. was subjected to mechanical pre-treatment under different conditions: S.1 (Fig. 1, a), sample chopped with scissors; S.2 (Fig. 1, b), sample milled (505 µm) using Philips (Milan, Italy) mixer (2200W) for 1 min at maximum speed; S.3 (Fig. 1, c), sample grounded to powder (107 µm) using Moulinex mixer (Écully, France) for 2 min. The determination of total solids (TS) and volatile solids (VS) was performed taking into account the Laboratory Analytical Procedure (LAP) [18]. Total moisture and TS were determined on the Sargassum sample by drying in an oven at 105 ° C ± 2 ° C. The total moisture was calculated by Eq. 1:

$$M=\frac{{m}_{i}- {m}_{f}}{{m}_{i }}\bullet 100 \left(\%\right) (\text{E}\text{q}.1)$$

where m_i was the initial mass of the dried sample before oven drying, m_f was the mass of the sample after drying in oven at 105°C ± 2°C.

The ash content was determined by calcination in a muffle at 550 ° C ± 10° C for 6 h. The method provides for the incineration of an aliquot of the test sample in an oxidizing atmosphere until the organic substance is completely burned and a constant mass is reached. The ash content was calculated by Eq. 2:

$$Ash=\frac{{m}_{c}}{{m}_{i }}\bullet 100 \left(\%\right) (\text{E}\text{q}.2)$$

where m_i was the initial mass of the dried sample before oven drying and m_c was the residual mass of the sample after calcination in muffle at 550°C ± 10°C for 6h.

The volatile solids were calculated by Eq. 3:

$$VS=\frac{{m}_{d}- {m}_{c}}{{m}_{i }}\bullet 100 \left(\%\right) (\text{E}\text{q}.3)$$

where mi was the initial mass of the dried sample before oven drying, mf was the mass of the sample after drying in oven at 105°C ± 2°C.

2.3 Granulometric analysis of biomass

The granulometric analysis of the mechanically pre-treated biomass samples (S.2, S.3) was carried out using a Mastersize2000 (Malvern, UK) laser diffractometer to determine the average surface to volume diameter. The analyzer has two accessories for sample dispersion in the cell. For S.2 (505 µm), the test was conducted by dry dispersion with the accessory Scirocco 2000, at a pressure of 1.9 bar and feed rate of 50%. However, S.3 (107 µm) was analysed by wet dispersion with the Hydro2000MU using water as dispersant fluid due to the agglomeration tendency of materials with small particle size.

2.4 Anaerobic digestion through Automatic Potential System Test II (AMPTS-II)

The Biochemical Methane Potential (BMP) was developed through anaerobic digestion tests performed using the Automatic Methane Potential Test System II (AMPTS-II®) manufactured by BPC instruments (Lund, Sweden). The AMPTS-II consists of 15 channels that measure the gas flow from 15 batch 500 ml reactors. The instrument is able to directly measure the methane produced by passing the biogas produced through caustic soda filters that eliminate the carbon dioxide. Each reactor contained 450 ml of inoculum that had 6.67 ± 0.40% TS containing 22.45 ± 0.60% of ashes, and 77.55 ± 0.40% of VS. Conad cornstarch (Bologna, IT) was used as a positive control to validate the efficiency of the inoculum. The samples were run in duplicates 2, with an inoculum to substrate ratio equal to 3 under mesophilic conditions (37 ° C). The BMP test lasted 30 days.

2.5 Mathematical Kinetic model

In this work the authors proposed two kinetic models, the first-order kinetic model (Eq. 4) and the modified Gompertz model (Eq. 5) to evaluate the performance of the AD of different Sargassum spp. samples.

The production of biomethane by anaerobic digestion process can be described by first order kinetics

$$\text{y} \left(\text{t}\right)=\text{A}\text{*}\left(1-{e}^{-kt}\right) (Eq.4)$$

where y(t) is the cumulative biogas production (NmL · g^− 1_VS), A is the biogas production potential (NmL · g^− 1_VS) and k was estimated by taking the reciprocal of the time from the start of the BMP assay until when y(t) equaled 0.632A [19] [20]. However, this model does not adequately predict biomethane production trends [21] [22].

The modified Gompertz model (Eq, 5) was used to validate the experimental data. It is assumed that the biogas production corresponds to the specific growth rate of methanogenic bacteria in the digester [23].

$y \left(t\right)=A*\text{exp}\{ -\text{exp}[ \frac{u*e}{A} \left(m-t\right)+1]\}$ (Eq. 5)

where y(t) is the cumulative biogas production (NmL · g^− 1_VS), A is the biogas production potential (NmL · gVS^− 1), u is maximum biogas production rate (NmL · g^− 1_VS · day^− 1), e is a mathematical constant (2.718282), m is the lag phase period (days), and t is the cumulative time for biogas production (days). It is possible to determine the kinetic constants A, u and m applying a nonlinear regression model by OriginPro19 software.

2.6 Energy analysis

The energy consumed (${E}_{C}$) to reduce the particle size of the samples can be calculated using Eq. 6; where P is the power measured in kW and t is the time expressed in hours.

${E}_{C}=P \left(kW\right)*t \left(h\right)$ (Eq. 6)

To evaluate the effect that the energy consumed has on the energy balance, it is necessary to calculate the energy produced (Ep) expressed in kWh (Eq. 7), following the anaerobic digestion process. $.$The higher calorific value of biomethane[24] is on average equal to 45.28MJ/ m³ therefore from 1 m³ of biomethane, taking into account that 1 kWh is equal to 3.6 MJ, 12.3KWh are obtained.

${E}_{P}$ = 12.3 kWh * BMP₃₀ (Eq. 7)

In this work the effect of energy consumption on the energy produced is evaluated. The available energy (E_d), expressed in kWh, indicates the difference between the energy produced and the energy consumed to reduce the particle size (Eq. 8). The energy consumed in the production of biomethane is not taken into account.

${E}_{d}={E}_{P}- {E}_{C}$ (Eq. 8)

2.7 Statistical analysis

For the comparison of BMP (Nm³ /t)) of the experimental units, one-way analysis of variance (ANOVA) and Tukey’s test were carried out using Origin Pro 2019 from Origin Lab (Northampton, MA, USA). For the comparison of the biomass composition, unpaired t test was used (GraphPad). The data was assumed to be normal, independent and equal variance.

3.1 Biomass characteristics post-pretreatment

The volatile solids of the milled Sargassum spp. biomass with particle sizes of 505µm (61.02 ± 0.44%) and 107 µm (62.07 ± 0.40%) were not significanlty different (p = 0.130). However, the volatile solids of the chopped biomass (71.02 ± 0.40%) was higher (p < 0.005) than those from the milled and crushed biomass. Similarly, the ash content of the chopped biomass (28.98 ± 0.23%) was lower (p < 0.001) than those of the milled biomass. The difference between the biomass with particle sizes of 505µm (39.00 ± 0.30%) and 107 µm (37.93 ± 0.20%) is considered to be not quite statistically significant (p = 0.052).

3.2 Granulometric analysis of Sargassum spp.

The crushed biomass (S2) reduced its monomodal size distribution all within the range detectable by the analysis tool (Fig. 2a), although it appears very wide. The comminution by the milling (S3) was more efficient, as the particle size distribution shifted towards lower sizes (see Fig. 2a). For both, S.2 and S.3, characterized by laser diffraction, the surface to volume mean, d_SV, drops drastically from 86 to 15 µm, as more fine particles are produced by the last type of the comminution pretreatment (milling, S3). In fact, the particle size distribution widens in amplitude, as signaled by the increase of the parameter span indicated in Table 1, and also it becomes a bimodal curve (see Fig. 2a). The sample now appears characterized as a mixture of two parts, one is of finer particles that represent more than 40% and the rest of bigger ones. This aspect is relevant because, increasing the fines presence in a solid sample increases the superficial area, but also introduces agglomeration problems[25], so the bigger particles of the sample help to prevent this.

It is evident that S3 (Fig. 2c) has the highest distribution frequency within the range of finer particles (from 0 to 45 µm), while sample S2 predominantly consists of particles in the range of 200 m to 1000 µm. In the sample S3, the size classes bigger than 1mm disappeared resulting in the presence of fine particles due to the milling process. This aspect is crucial, because there is an useful mix between fine content and coarse particle that reflects into a macroscopic behavior of S3: high superficial area with agglomeration[25].

Table 1 Granulometric analysis and biomethanation of Sargassum spp. at different particle sizes due to mechanical pretreatment.

	Granulometric Analysis
Pretreatment	Span [-]	d_SV [µm]	d_V [µm]	Methane yield (Nml/g VS)
Chopped (S1)	-	-	50000.0 ± 0.5	17.17 ± 2.14 ^a
Crushed (S2)	2.088	86.0 ± 0.1	505.0 ± 0.1	79.68 ± 2.77 ^b
Milled (S3)	7.730	15.0 ± 0.1	107.0 ± 0.1	65.08 ± 2.18 ^c

3.3 Effect of particle size on the biomethane production

After the 30 day-period, the methane yield increases with the decrease of the particle size (Fig. 3). The methane yield goes from 17.17 Nml/g VS to 79.68 Nml/g VS when the average size of the sample goes from 50000 µm to 505 µm, and from 17.17 Nml/g VS to 65.08 Nml/g VS when the average size of the sample go from 50000 µm to 107 µm. The methane yield (Nml/g VS) for the chopped biomass (S1) were significantly lower (p < 0.0005, Table 1) than those for the mechanically pretreated biomass (S2 and S3). Similarly, the methane yield of the biomass with particle sizes equal to 107 µm (S3) is higher than (p = 0.0279) that with particle size equal to 505 µm (S2). However, there is no difference (p = 0.06156) between the methane yield of S2 and S3.

A low methane yield from biomass S.3 compared to S.2 could be related to the excessive reduction of particle size. Sample S.3 is characterized by an average particle size of 107.0 ± 0.1 µm. The granulometric analysis of sample S.3 highlighted the predominant presence of fine particles in the range between 0–45 µm. These fine particles are subject to the formation of aggregates and consequently, the contact area between the algae cells and the microorganisms that operate the anaerobic digestion process decreases [25]. Furthermore, the excessive decrease in particle size increases the presence of volatile fatty acids which inhibit the methanogenesis process[26]. In a work by Izumi et al. conducted on food waste it is reported that when the size of the food waste sample was excessively reduced (0.7 mm) the methane yield did not increase due to the accumulation of volatile fatty acids[11].

3.3 Biomethanation kinetics

The parameters from the First kinetic model are shown in Table 2. The parameters from the modified Gompertz model were calculated. The maximum methane yields (Table 3), A (Nml /g VS), are in agreement with the experimental methane yields (Table 1). The methane yield for S2 was higher ( p = 0.0114) than that from S3. Similarly, the methane production rate, u (Nml /g VS.day), is higher ( p < 0.004) after mechanical pretreatment, and the biomass wih smallest particle size (S3) experienced a reduction in the rate (p = 0.0145) compared to S2.

The lag phase m, of the sample S1 indicates that less than 3 days are required before the methane production starts. There was not significant difference ( p > 0.074) between chopped (S1) and milled (S2, S3) biomass in terms of lag phase. The correlation coefficient (R²) for each experimental unit was above 0.980, indicating that the model fits the experimental data well.

Table 2

Kinetic parameters of the First kinetic model
Pretreatment	A (Nml /g VS)	k (day^− 1)	R²
Chopped (S1)	18.919	0.107	0.951
Crushed (S2)	160.529	0.025	0.982
Milled (S3)	167.248	0.018	0.981

Table 3

Kinetic parameters of the Modified Gompertz model
Pretreatment	A (Nml /g VS)	u (Nml /g VS.day)	m (day)	R²
Chopped (S1)	17.677 ^a	1.75 ^a	1.57	0.988
Crushed (S2)	86.085 ^b	4.495 ^b	2.315	0.996
Milled (S3)	72.823^c	3.526^c	2.573	0.993
The different letters within the column means there is a significant difference between the values at the 0.05 level using unpaired t-test

The two kinetic models fit the experimental data well. The modified Gompertz model shows more accurate results, while the first order kinetic model is less accurate in estimation. The difference between the experimental A value and the A value obtained using the modified Gompertz model for system S.1, S.2, S.3 are 0.35%, 6.86%, and 9.24%, respectively. While the differences between the experimental A value and the A value obtained using the first order kinetic model for system S.1, S.2, S.3 are 9.20%, 50.36%, and 61.08%, respectively.

The parameter u (NmL · g^− 1VS · day^− 1) indicates the maximum biogas production rate that can be obtained in each system. Sample S.2 shows the highest value of parameter u.

The parameter m indicates the period required to start the production of biomethane. Sample S.1 shows a delay period equal to 1.749 days, sample S.2 a delay period equal to 2.322 days while sample S.3 a delay period equal to 2.568 days. For samples characterized by finer particle size the delay time is longer than for sample S.1.

The hydrolysis rate constants (k) of the different sample S.1, S.2, S.3 have been determined from the first-order model and they are equal to 0.107, 0.025 and 0.018 (day^− 1). The first order kinetic model, as already highlighted in other works, does not fit the data precisely. In fact, according to this model, the greater the k, the faster the degradation. On the other hand, from the results obtained, samples S.2 and S.3 show a higher biomethane yield than sample S.1 which instead shows a higher k value.

The experimental data were fitted with the two models are shown in Fig. 3.

3.4 Energy analysis

Table 4 shows the data obtained from the energy analysis. For sample S2 it is estimated that it is possible to produce 37.03Nm³/ton of biomethane and therefore the energy produced is equal to 455.5 kWh. To obtain the particle size desired of sample S2 (505 µm), the sample was crushed with a mixer. A container with a capacity of 1L can contain 91.1g of sargassum biomass as it is, therefore its density is equal to 91.1g/L. Considering a mixer with a power of 2200W and a capacity of 20L, to blend 1 ton you need to use the blender 555 times for 1 minute for a total of 555 minutes (about 9 hours). Therefore, the energy needed to mix 1 ton of Sargassum spp. is equal to 19.8kWh, which corresponds to 4.3% of the energy produced. For sample S3 it is estimated that it is possible to produce 32.88Nm³/ton of biomethane and therefore the energy produced is equal to 404.4 kWh. To obtain the granulometry of sample S3 (107 µm), the sample was milled with a grinder, in this case it takes twice as long and therefore a consumption of about 39.6 kWh is estimated, corresponds to 9.8% of the energy produced. In contrast, sample S.1 was cut with knives, therefore, no mechanical energy was used, it is estimated that it is possible to produce 9.62 Nm³/ton of biomethane and therefore the energy produced is equal to 118.3 kWh.

It can be concluded that if on one hand the pre-treatment involves an energy expenditure, on the other hand it allows to obtain a higher yield and therefore does not negatively affect the energy balance. In particular, for sample S.2 the best results are obtained in terms of yield of biomethane produced and useful energy. Furthermore, as already observed, sample S.3 shows a higher reaction rate than sample S.2. This means that the reaction produces a greater quantity of methane in a shorter time, and therefore also the production cost, in terms of energy, is lower.

Table 4

Energy analysis parameters. BMP (Nm3/t) is the biochemical methane potential, Ep (kWh) is the energy produced, Ec (kWh) is the energy consumed, and Ed (kWh), is the difference between Ep and Ec.
Pre-treatment	BMP (Nm³/t)	E_p (kWh)	E_c (kWh)	E_d = E_p - E_c
Chopped (S1)	9.62	118.3	-	118.3
Crushed (S2)	37.03	455.5	19.8	435.7
Milled (S3)	32.88	404.4	39.6	364.8

The anaerobic digestion (AD) of Sargassum spp is affected by its particle size. In this work, the effect of the particle size of pelagic Sargassum spp. biomass on the methane production was determined. The biomass was mechanically pretreated using three different methods that resulted in different particle sizes. S.1 (50000 µm) was reduced to pieces with knives / scissors, S.2 (505 µm) was crushed with a mixer and S.3 was pulverized with milling machine (107 µm). For samples S.2 and S.3 a granulometry study was conducted. This study showed how the surface to volume mean, d_SV, drops drastically from 86 to 15 µm from sample S.2 to sample S.3. The increase of fine particle in solid materials increases the superficial area, but also introduces agglomeration problems. This explains the reduction in biomethane yield of S3 (65.08 ± 2.18 Nml/g VS) compared to S.2 (79.68 ± 2.77 Nml/g VS) that has higher particle size. Furthermore, an energy analysis was performed to estimate the optimal particle size reduction considering the methane production and energy demand during mechanical pretreatment. From the energy analysis it emerged that the energy required to reduce 1 ton of Sargassum spp. biomass into powder varies according to the type of mechanical pre-treatment. 19.8 kWh was required to reach a particle size of 505 µm, while 39.6 kWh is needed for a particle size of 107 µm. The energy required to pre-treat the biomass to reach a particle size of 107 µm is 9.8% of the energy produced, however, only 4.3% is needed to reach 505 µm. In conclusion, mechanical pretreatment that generates a Sargassum spp. biomass with particle size below 505 µm does not improve the performance of biomethanation of the material in terms of kinetics and energy expenditure.

Competing interests

The authors have no conflicts of interest to declare that are relevant to the content of this article.

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Effect of particle size on the biomethanation kinetics of mechanically pretreated Sargassum spp biomass

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Abstract