This is the accepted version of the article: Avila, Romina; Carrero, Elvira (Miguel Torres S.A.); Vicent, Teresa; [et al.]. «Integration of enzymatic pretreatment and sludge co-digestion in biogas produc- tion from microalgae». Waste Management, Vol. 124 (April 2021), p. 254-263. DOI 10.1016/j.wasman.2021.01.042 This version is available at https://ddd.uab.cat/record/237999 under the terms of the license 1 Integration of enzymatic pretreatment and sludge co-digestion in biogas production from 2 microalgae 3 Romina Avilaa, Elvira Carrerob, Teresa Vicenta, Paqui Blánqueza* 4 a Chemical, Biological and Environmental Engineering Department, Escola d'Enginyeria, 5 Universitat Autònoma de Barcelona, E-08193, Bellaterra, Barcelona, Spain. 6 b Miguel Torres S.A., Miquel Torres i Carbó 6, 08720, Villafranca del Penedès, Barcelona, 7 Spain. 8 * Corresponding author: Paqui Blánquez 9 E-mail address: paqui.blanquez@uab.cat 10 Full postal address: Chemical, Biological and Environmental Engineering Department, Escola 11 d'Enginyeria, Universitat Autònoma de Barcelona, E-08193, Bellaterra, Barcelona, Spain. 12 1 13 Abstract 14 Integration of microalgae-based systems with conventional wastewater treatment plants provides 15 an effective alternative to waste stream management. In this work, alkaline and enzymatic 16 pretreatments of a microalgal culture mainly constituted by Chlorella sp. and Scenedesmus sp. 17 and cultivated in wastewater from an industrial winery wastewater treatment plant were assessed. 18 Microalgal enzymatic pretreatments were expected to overcome algal recalcitrancy before 19 anaerobic digestion. pH-induced flocculation at pH 10 and 11 did not enhance microalgal 20 harvesting and solubilisation, achieving a performance similar to that of natural sedimentation. 21 Enzymatic hydrolysis of algal biomass was carried out using three commercial enzymatic 22 cocktails (A, B and C) at two enzymatic doses (1% and 2% (v/v)) over 3 h of exposure time at 37 23 °C. Since pretreatments at a 1% dose for 0.5 h and 2% dose for 2 h achieved higher solubilisation, 24 they were selected to evaluate the influence of the pretreatment on microalgal anaerobic 25 digestibility. Biochemical methane potential tests showed that the pretreatments increased the 26 methane production of the raw algal biomass 3.6- to 5.3-fold. The methane yield was 9-27% 27 higher at the lower enzyme dose. Hence, microalgae pretreated with enzymes B and C at a 1% 28 dose were co-digested with waste activated sludge (WAS). Even when the enzyme increased the 29 methane yield of the inoculum and the WAS, the methane yield of the raw microalgae and WAS 30 mixture was not significantly different from that obtained when algae were enzymatically 31 pretreated. Nonetheless, co-digestion may achieve the goals of a waste recycled bio-circular 32 economy. 33 34 Keywords 35 Alkaline pretreatment - Enzymatic hydrolysis - Solubilisation - Waste activated sludge - Methane 36 yield 37 38 1. Introduction 2 39 Microalgae-based wastewater treatment is a cost-effective alternative to conventional wastewater 40 treatment plants based on processes that require carbon and energy consumption. Microalgae 41 contribute to nitrogen and phosphorus removal from wastewater and CO2 fixation through 42 photosynthesis, producing biomass and oxygen. Harvested microalgal biomass can be further 43 valorised through anaerobic digestion for organic matter stabilisation and its bioconversion to 44 energy. 45 Harvesting is a crucial step for biomass recovery, but it is considered a bottleneck in microalgal 46 production due to small sizes on cells (1-30 µm) and their low concentration in water (~1 g L-1) 47 (Postma et al., 2017; Van Haver and Nayar, 2017). Microalgal cell recovery costs are estimated 48 to contribute at least 20- 30% of the total production costs (Singh and Patidar, 2018). 49 Centrifugation, filtration, and chemical flocculation are energy-intensive and resource-demanding 50 harvesting techniques that render microalgal biomass production economically infeasible. 51 Alkaline flocculation is a harvesting method that induces microalgal concentration by increasing 52 the pH of the medium (Branyikova et al., 2018; Wan et al., 2015), thus avoiding the addition of 53 chemical flocculants. Microalgal cells possess a negative surface charge that arises from 54 deprotonated carboxylate, phosphate, and hydroxyl functional groups, and mutual repulsion 55 between anionic microalgae creates stable suspensions in water (Bilal et al., 2018; Brady et al., 56 2014). Protonation and deprotonation of functional groups at microalgal surfaces rely on the 57 culture conditions and microalgal growth phase (González-Fernández et al., 2013). Flocculation 58 via pH adjustment is stimulated by H+ when changing the H+/OH- ratio in the medium (Brady et 59 al., 2014). When the pH increases to 9.5-11, some naturally available cations present in the 60 medium, such as Mg2+ or Ca2+, can precipitate and form positively charged precipitates that can 61 interact with the negatively charged microalgal surface, allowing microalgal cells to flocculate 62 through charge neutralisation and/or by a sweeping mechanism (Brady et al., 2014; Muylaert et 63 al., 2015). Normally, the concentration of magnesium in water is adequate for production of 64 microalgal flocculation when the pH of the medium is increased by the addition of a base 65 (Vandamme et al., 2016). Afterwards alkaline flocculation, the supernatant can be recovered and 66 reused after pH neutralization, and the quality of the harvested microalgae must be check to 67 assess its feasibility to be employed in a defined future use (Barros et al., 2015; Li et al., 2020). 68 Despite pH-induced flocculation is more expensive compared to gravity-based sedimentation, it 3 69 is an interesting method to pre-concentrate microalgal biomass due to its simplicity, low cost, and 70 low energy consumption (Li et al., 2020). In this study, alkaline flocculation was assessed for 71 microalgal concentration. 72 Anaerobic digestion is a technique widely employed for biomass-to-energy conversion. Generally, 73 anaerobic digestion of microalgae is restrained to the inherent nature of microalgae. The 74 recalcitrancy of microalgae biomass is strongly influenced by its cell wall structure and 75 composition which is specie-dependant, and could limit biomass hydrolysis (Soto-Sierra et al., 76 2018). Although lignin is not present in the microalgal cell wall, it is characterized by a rigid 77 structure of organic compounds with low biodegradability that protects the cells from the 78 environment. Hence, pretreatment is a mandatory step for microalgal hydrolysis during anaerobic 79 digestion, thus improving the accessibility of anaerobic microorganisms to microalgal components 80 and increasing their digestibility for biogas production. Several pretreatment methods have been 81 studied for microalgal cell wall disruption (Kendir and Ugurlu, 2018; Passos et al., 2014). 82 Compared with thermal, mechanical, and thermochemical pretreatments, enzymatic hydrolysis is 83 a biological treatment that digests microalgal cell walls, making them permeable and liberating 84 intracellular compounds or improving their accessibility to microorganisms (Gerken et al., 2013). 85 On the other hand, thermal and ultrasound pretreatments break or deform microalgal cell walls 86 without digestion (Ometto et al., 2014). Enzymatic pretreatment is performed under mild 87 conditions. This process reduces or eliminates toxic compound formation, requires low energy 88 consumption, and keeps downstream processing costs low (Mahdy et al., 2016; Zabed et al., 89 2019). Enzymatic pretreatment is more specific in cell wall hydrolysis due to enzyme specificity 90 to a certain substrate. In this sense, the appropriate enzyme(s) could be selected according to 91 the target microalgal species. Some studies reported the use of pectinases to degrade S. obliquus 92 (Ometto et al., 2014), and proteases for degradation of proteins in Porphyridium cruentum (Kendir 93 Çakmak and Ugurlu, 2020) and Chlorella vulgaris (Mahdy et al., 2016). Meanwhile, 94 carbohydrases are among the typically employed enzymes for microalgae enzymatic 95 pretreatment before anaerobic digestion. For instance, cellulase was used for the degradation of 96 the cellulose inner wall layer of the marine microalgae Nannochloropsis sp. (Maffei et al., 2018), 97 and other carbohydrase enzymes were used for Chlorella vulgaris and Scenedesmus sp. 98 hydrolysis (Mahdy et al., 2015b). As other authors have argued, a higher soluble chemical oxygen 4 99 demand (sCOD) is obtained when using enzymatic cocktails due to a greater variety of enzymes 100 that could interact with the microalgal cell wall (Carrillo-Reyes et al., 2016; Ometto et al., 2014), 101 thus contributing to enhanced digestibility for biogas production. In this work, enzymatic 102 pretreatments were tested using three different catalyst cocktails and diverse dosages. 103 In addition to microalgal pretreatment, biogas production can be upgraded by co-digestion of 104 microalgae with other carbon-rich substrates, such as waste activated sludge (WAS) (Beltrán et 105 al., 2016a; Thorin et al., 2017). Co-digestion of both substrates contributes to balancing the C/N 106 ratio, avoids ammonia inhibition from the degradation of lipid-rich substrates, enhances nutrient 107 availability for anaerobic microorganisms, and promotes the integration of wastewater treatment 108 plant (WWTP) facilities and microalgae-based systems, thus improving the economic feasibility 109 of wastewater treatment (Solé-Bundó et al., 2019). 110 This work is developed within a circular economy project in a winery company aimed at microalgal 111 cultivation for mitigation of CO2 produced in the winery company. This study evaluates the 112 efficiency of alkaline and enzymatic pretreatment methods for microalgal concentration and 113 solubilisation as well as algal biomass valorisation through co-digestion with waste activated 114 sludge generated by the company. This study provides useful information since it is the first to 115 address the effects of co-digestion of microalgae enzymatically pretreated as a co-substrate to 116 activated sludge for waste streams valorisation in WWTPs. 117 118 2. Materials and methods 119 2.1. Substrates 120 Microalgal biomass was cultivated in 9 L column photobioreactors (PBRs). Samples were taken 121 from the reactors when microalgae reached the exponential growth phase . PBRs were fed with 122 secondary effluent from a WWTP of a winery company (hereafter referred to as the company). 123 Inlet wastewater characterisation throughout a year is presented in Table S1. PBRs were located 124 inside a greenhouse chamber in which illumination was naturally provided, and the temperature 125 was approximately 20 ± 10 °C. Microscopic examination identified Chlorella sp. and 5 126 Scenedesmus sp. (Fig. S1) as the main microalgal species present in the culture (Zeiss, AixoCam 127 ERc 5 s). 128 The WAS used in anaerobic co-digestion assays was obtained from the aerobic biological 129 reactors of the company WWTP. A defined WAS and microalgal mixture (WAS:RM) composed of 130 93% WAS and 7% microalgae on a volatile solids (VS) basis was used in biochemical methane 131 potential tests (BMP)-set 2 experiments (explained below). The proportion of the mixture was 132 established according to the daily volume production of both substrates by the company. 133 2.2. Set-up for pH-induced flocculation through pH adjustment 134 A flux diagram of the performed experiments is presented in Fig. 1a. A volume of 1000 mL of 135 microalgal biomass from the PBRs was added into a 1 L glass graduated cylinder to assess the 136 effect of the alkaline pretreatment on microalgal concentration and solubilisation. Microalgae were 137 flocculated by adjusting the pH of the culture medium to pH 10 (PBR-10) and pH 11 (PBR-11) by 138 addition of 5 N sodium hydroxide (NaOH) and stirring with a magnetic stirrer until the pH was 139 adjusted to the desired value (pH-adjusted treatments, n = 3). Additionally, controls of microalgae 140 biomass without pH adjustment (PBR-10-C and PBR-11-C) were employed (n = 1) to compare 141 the effect of natural sedimentation. The initial soluble chemical oxygen demand (sCOD), initial 142 and final total suspended solids (TSS) and initial and final volatile suspended solids (VSS) in the 143 supernatant were determined from the pH-adjusted treatments and the controls. A 1 mL sample 144 of the supernatant was withdrawn from the middle of the clarified zone at the initial time and at 145 diverse exposure times during the 7 days after pH adjustment to measure the optical density 146 (OD680) and calculate the clarification efficiency (CE) according to Eq. 1: 147 CE (%) = ODi − ODt / ODi (1) 148 where ODi is the initial OD680 before adjusting the pH of the culture, and ODt is the OD680 of the 149 culture at time t after adjusting the pH to the desired value. Solids clarification in the supernatant 150 is an indirect measurement of the concentration of solids in the thickened zone, allowing 151 experimental measurement over time without distorting the sample. 6 152 After 7 days of flocculation, the microalgal pellet (concentrated microalgal biomass) was 153 separated from the supernatant, and the pH of the supernatant was measured and neutralized to 154 pH 7 by adding 2 N hydrochloric acid (HCl). Final TSS, VSS, and sCOD were determined from 155 the neutralized supernatant. 156 157 Figure 1 158 159 2.3. Enzymatic pretreatment of microalgal biomass 160 Three enzymatic commercial preparations were applied to hydrolyse the microalgal biomass and 161 increase microalgal digestibility: enzyme A, enzyme B, and enzyme C (a description of the 162 enzymes is shown in Table S2). Enzyme A (Passos et al., 2016) and enzyme B are multi- 163 enzymatic preparations composed of diverse enzymes. Enzymes A, B, and C were tested at two 164 doses of 1% and 2% (v/v) to identify the following pretreatment methods (enzyme name and 165 dose): A1, B1, C1, A2, B2, and C2. Thus, the pretreatment methods applied to the microalgal 166 biomass (M) were identified as M-A1, M-B1, M-C1, M-A2, M-B2, and M-C2. A volume of 100 mL 167 of microalgal solution was placed into Erlenmeyer flasks (250 mL), and the enzyme was added. 168 Enzymatic hydrolysis was conducted at 37 °C under orbital agitation (100 rpm). The pH was not 169 previously fixed or controlled during the pretreatment. Two sets of enzymatic hydrolysis (EH) 170 experiments were carried out (Fig. 1a and 1b). In EH-set 1, samples were removed from all the 171 trials to measure the total soluble organic matter released by analysing the sCOD of the filtrate at 172 the initial time and over an exposure time of 0.5, 1, 2, and 3 h after enzyme addition. According 173 to the results obtained, in EH-set 2, the enzymatic pretreatments were performed at the optimal 174 exposure time in both doses. All trials were carried out in triplicate. To evaluate the effect of the 175 pretreatment on microalgal solubilisation, a control reactor (RM) containing the raw microalgal 176 culture without enzymatic pretreatment and exposure to 37 °C was used. The effect of the 177 enzymatic pretreatment on the hydrolysis efficiency was determined by comparing the increase 178 in sCOD after the pretreatment and the sCOD concentration in the control. 7 179 2.4. Biochemical methane potential (BMP) tests 180 Two sets of BMP tests were performed: BMP-set 1 and BMP-set 2 (Fig. 1a and 1b). The aim of 181 BMP-set 1 was to evaluate the methane yield of the selected enzymatically pretreated microalgal 182 biomass. BMP-set 2 assessed the co-digestion efficiency of a mixture of WAS and enzymatically 183 pretreated microalgal selected in BMP-set 1. Anaerobic batch assays were performed according 184 to a previously described procedure (Martín-González et al., 2010) with consideration of 185 suggestions from other authors (Angelidaki et al., 2009; Holliger et al., 2016). BMP assays were 186 carried out in triplicate under mesophilic conditions (37 °C). BMP-set 1 tests were carried out 187 using 120 mL glass bottles (80 mL working volume), and raw microalgae without pretreatment 188 (RM) were used to compare the effect of the pretreatments on biogas production. BMP-set 2 tests 189 were performed in 900 mL aluminium bottles (600 mL working volume), and different controls 190 were used: WAS without pretreatment (WAS), WAS and raw microalgal mixture without 191 pretreatment (WAS:RM), WAS with enzyme addition (WAS-enzyme-dose), and inoculum with 192 enzyme addition (I-enzyme-dose). 193 The anaerobic sludge employed as inoculum in the biochemical methane potential (BMP) assays 194 was collected from the anaerobic digesters of the Riu Sec WWTP (Sabadell, Barcelona). To 195 guarantee the consumption of the organic matter contained in the inoculum, it was pre-incubated 196 at 37 °C for 12 days. All BMP bottles were filled with inoculum, substrate, and tap water until the 197 working volume was reached. Subsequently, the bottles were flushed with pure N2 to ensure 198 anaerobic conditions, closed, and incubated in a temperature-controlled chamber. Biogas 199 production and accumulation in the headspace of the bottles were measured with an SMC 200 pressure switch manometer (1 bar, 5% accuracy) until biogas generation ceased. Bottles 201 containing only the same amount of inoculum (blank) in the trials were used to analyse the 202 background biogas production of the inoculum. Net biogas production was determined by 203 subtracting the biogas production of the blank from the gross biogas production of the sample 204 bottles. Moreover, crystalline cellulose was employed as a reference substrate to evaluate the 205 activity of the inoculum (control). The reactors were shaken manually every time a gas sample 206 was taken. Periodically, biogas composition was determined through gas chromatography. The 207 generated biogas was expressed as the volume of methane generated per mass of VS of the 8 208 added substrate (NmL CH4 g VS-1) expressed under standard pressure and temperature (273.15 209 K and 1.0133 bar). 210 2.5. Analytical techniques 211 Hach Lange cuvettes (LCK 314, 114, and 014), and the spectrophotometer DR 3900 (Hach Lange 212 GmbH, Düsseldorf, Germany) were employed for sCOD determination using filtered supernatant 213 (GF/A glass microfibre filters, Whatman, GE Healthcare, USA). TSS, VSS, TS, and VS were 214 determined according to the procedures defined in Standard Methods (APHA, 2008). pH was 215 measured by a pH meter (Crison, Spain). 216 Carbon dioxide and methane content in the biogas were analysed using a gas chromatograph 217 (Hewlett Packard 5890, Agilent Technologies, Mississauga, Canada) equipped with a thermal 218 conductivity detector and a Supelco Porapack Q column (3 m × 3.2 mm) (Pennsylvania, USA). 219 Helium was the carrier gas (338 KPa); and the oven, injector, and detector temperatures were 220 70, 150 and 180 °C, respectively. Samples were injected with a 100 μL syringe (VICI PS Syringe 221 A-2, 0.74 mm × 0.13 mm × 50.8 mm). 222 Before volatile fatty acids (VFAs) determination, samples were centrifuged (10 min, 8000 rpm, 223 Beckman Coulter, Avanti J20 XP, USA) and then filtered (0.45 µm nylon syringe filter). VFAs were 224 analysed by a Dionex 3000 ultimate high-performance liquid chromatography (Barcelona, Spain) 225 equipped with a UV/visible detector (210 nm). The chromatographic separation was performed 226 using an ICE-COREGEL 87H3 column (7.8 × 300 mm, Transgenomic, USA), heated at 40 °C, 227 employing 0.006 mM of H2SO4 as a mobile phase at a flow rate of 0.5 mL min−1. 228 2.6. Data analysis 229 The experimental data were analysed statistically, and differences were considered significant at 230 p values below 0.05. When the null hypothesis was rejected (significance level < 0.05), post hoc 231 comparisons were performed. All statistical calculations were carried out using R software 232 (version 3.6.3). 233 The modified Gompertz equation (Nielfa et al., 2015) was employed to model biomethane 234 production and calculate kinetic parameters for anaerobic degradation according to Eq. 2: 9 Rmax .e 235 Pnet (t) = Pmax . exp {−exp [ (λ − t) + 1]} (2) Pmax 236 where Pnet(t) is the net cumulative methane yield (NmL CH4 g VS-1) at time t, Pmax is the methane 237 yield potential (NmL CH4 g VS-1), Rmax is the maximum methane production rate (NmL CH4 g VS- 238 1 d-1), t is the digestion time (d), and λ represents the lag phase (d). The hydrolysis rate of the 239 anaerobic digestion was evaluated according to Eq. 3, adjusting the experimental data to a first- 240 order kinetic model by the least squares method (Martín Juárez et al., 2018): 241 B (t) = B0 (1 − exp−KH .t ) (3) 242 where B(t) is the cumulative methane yield at time t (NmL CH4 g VS-1) obtained experimentally, 243 B0 is the ultimate methane yield (NmL CH4 g VS-1), KH is the hydrolysis rate constant (d-1), and t 244 is the digestion time (d). The values of the above parameters were estimated by an algorithm 245 developed in MATLAB R2015a (MathWorks Inc. Natick, MA, USA). 246 247 3. Results and discussion 248 3.1. Microalgal concentration through alkaline flocculation 249 When the pH of the solution was adjusted to 10 (Fig. 2), the clarification efficiency in PBR-10 250 increased by 4.4% (96.8%) compared to the untreated control (PBR-10-C, 92.5%). Comparable 251 results were obtained when adjusting the pH to 11 (Fig. 2). The clarification efficiency in PBR 252 (PBR-11) increased by 5.3% compared with the control without pH adjustment (PBR-11-C) 253 (96.7% and 91.6%, respectively). When adjusting the pH to 11, high clarification efficiencies were 254 achieved after 2 days; however, it took at least 6 days to reach similar clarification efficiencies 255 when adjusting the pH to 10. The evolution of the clarification during alkaline pretreatment at each 256 pH is shown in Fig. S2. Overall, after 7 days of pretreatment at pH 10 and pH 11, equivalent 257 efficiencies were attained compared with the controls under natural sedimentation, while slight 258 differences were observed at shorter exposure times. 259 260 Figure 2 10 261 According to our results and in agreement with other authors, the absence of flocculation of 262 Chlorella vulgaris biomass at up to pH 10.2-10.5 was reported (Smith and Davis, 2012; 263 Vandamme et al., 2012), suggesting that natural sedimentation was the main mechanism 264 involved in PBR-10 over the 7 days. Moreover, VSS reduction in the supernatant (Fig. 3) was 265 higher in the untreated controls. The results under the tested conditions indicated that adjusting 266 the pH to 10 and 11 had a slight or negligible effect on microalgal biomass flocculation compared 267 with the controls. Contrary to our results, other authors reported >95% recovery of Dunaliella 268 viridis after 24 h of adjusting the pH of the culture medium to 10 (Mixson et al., 2014) and 90% 269 recovery of Chlorella vulgaris as pH increased to 10 (Branyikova et al., 2018). Ummalyma et al. 270 (2016) obtained a 94% flocculation efficiency of the freshwater microalgae Chlorococcum sp. at 271 pH 12. Diverse results could be explained by the differences in the medium composition (Mg2+ 272 and Ca2+ content) since the amount of base needed to induce flocculation depends on the 273 buffering capacity of the culture and the concentrations of Ca 2+ and/or Mg2+ (García-Pérez et al., 274 2014; Muylaert et al., 2015; Vandamme et al., 2012). 275 276 Figure 3 277 278 Dissolved organic carbon in the supernatant increased by 1.5-fold at the end of the alkaline 279 pretreatment for PBR-11 (Table S3). This fact could be associated with the presence of dissolved 280 organic matter excreted by microalgal cells in the supernatant, also referred to as algal organic 281 matter (AOM) (Barros et al., 2015), rather than sCOD from cell wall solubilisation. Chlorella sp. 282 and Scenedesmus sp. are characterized by the high recalcitrance and robustness of their cell 283 walls (González-Fernández et al., 2012), and as reported by other authors, alkaline pretreatment 284 of Chlorella biomass was ineffective in biomass solubilisation (Bohutskyi et al., 2014). In addition, 285 dissolved organic matter has a negative charge that also interacts with hydroxides, decreasing 286 the available magnesium in the medium and requiring a higher dose of NaOH to form precipitates 287 and a higher pH to achieve the same flocculation efficiency (Barros et al., 2015). For instance, 288 Vandamme et al. (2016) reported that a longer cultivation time of Chlorella vulgaris leads to 11 289 greater excretion of AOM to the media, which mainly contains polysaccharides that interfere with 290 and inhibit alkaline flocculation, thus increasing the dose of base addition. 291 Thus, the lower recovery efficiencies in our study could be limited by the medium composition 292 (the content of Mg2+ and Ca2+) as well as the presence of AOM excreted by the microalgal 293 biomass. Overall, the results indicate that pH adjustment of the microalgal solution to pH 10 and 294 11 neither enhances microalgal harvesting nor its solubility. When comparing alkaline flocculation 295 with other harvesting techniques, such as bio-flocculation, some authors reported >98% 296 clarification after the co-pelletization of the algal biomass with filamentous fungi (Hom-Diaz et al., 297 2017) and 90% harvesting efficiency with use of a bacterial strain (Wan et al., 2013). Although 298 these results showed higher flocculation efficiencies, additional time and costs were required for 299 microorganism (fungal or bacterial) production. 300 3.2. Solubility and anaerobic digestibility of enzymatically pretreated microalgal 301 biomass 302 3.2.1.Enzymatic pretreatment of microalgal biomass 303 Microalgal biomass (0.36 ± 0.07 g VS L-1) from the PBR was enzymatically pretreated to evaluate 304 the effect of the pretreatment on biomass solubility. Enzymatic pretreatments were performed at 305 37 °C, combining the action of temperature with the catalytic activity of the enzyme. Enzymatic 306 hydrolysis was tested using three enzymes (A, B, and C) and two enzymatic loads (1% and 2% 307 v/v) over exposure times of 0.5, 1, 2, and 3 h (EH-set 1, Fig. 1a and 1b). The selection of enzyme 308 A was due to the effective organic matter solubilisation of microalgal biomass grown in open 309 ponds for wastewater treatment, as reported by Passos et al. (2016). Enzymes B and C were 310 employed due to their availability within the winery industry, as they are also applied to other 311 industrial processes, as well as their similarity in composition to enzyme A. 312 Microalgal biomass without an enzymatic treatment displayed the lowest sCOD concentrations 313 and was fairly constant over time (Table S4). In all cases, at higher enzyme doses, higher sCOD 314 was released as a result of microalgal biomass solubilisation (Fig. 4a and 4b). When comparing 315 all of the enzymatic pretreatments at the lower dose of the enzyme (Fig. 4a) and at the same 316 exposure time, COD solubilisation was negligible (p > 0.05). However, significant differences in 12 317 sCOD were found at 0.5 h when comparing pretreatments B1 and C1 (p < 0.05) (Fig. 4a). At the 318 higher dose (Fig. 4b), significant variations in sCOD were identified when comparing the diverse 319 pretreatments at each exposure time (p < 0.05) (Table S4). Furthermore, when analysing 320 pretreatments individually, significant differences were identified in sCOD at different exposure 321 times for pretreatments A2 and B2 (p < 0.05) (Table S4). Pretreatments A2 and B2 released 322 greater sCOD after 2 h, and sCOD subsequently decreased. On the other hand, the sCOD 323 concentration in pretreatment C2 remained fairly constant from the first hour. 324 325 Figure 4 326 327 While pretreatments at the 1% dose exhibited faster COD solubilisation, pretreatments at the 2% 328 dose attained greater solubilisation after 2 h of hydrolysis. According to these results, 0.5 h and 329 2 h were set as the optimum exposure times for the enzymatic pretreatments at 1% and 2% 330 doses, respectively (EH-set 2). At the 1% dose and 0.5 h exposure time, sCOD increased by 138- 331 to 159-fold, and at the 2% dose and 2 h exposure time, sCOD improved by 257- to 311-fold. 332 Higher sCOD after enzymatic hydrolysis indicates effective microalgal cell wall degradation and 333 removal of recalcitrant compounds. Comparison with other studies is not proper since the effect 334 of the pretreatment depends on the microalgal species and the conditions applied. Enzymatic 335 pretreatments were carried out at 37 °C in this study since mesophilic anaerobic digestion (37 °C) 336 was applied after the hydrolysis treatment. Moreover, studies typically treated pure microalgal 337 species. For instance, Mahdy et al. (2015b) stated that the differences in hydrolysis efficiency of 338 Chlorella vulgaris and Scenedesmus sp. were due to their diversity in the cell wall and intracellular 339 composition. Cell wall composition varies among species and growth conditions. In this work, 340 selection of enzymes agreed with the microalgal cell wall composition. In this sense, cellulase 341 hydrolyses cellulose, and glucohydrolase and xylanase degrade hemicellulose. Pectinliase and 342 poligalacturonase are responsible for the degradation of pectin, and protease catalyses the 343 breakdown of proteins. Chlorella vulgaris possesses a robust polymeric cell wall structure 344 constituted by hydrolysable (xylose, mannose, galactose, glucose, fucose, arabinose, rhamnose 13 345 and uronic acids) and resistant (glucosamine) compounds (Gerken et al., 2013). Pectin was also 346 identified in C. vulgaris (Gerken et al., 2013) and Scenedesmus sp. The cell wall consists of 347 carbohydrates composed of cellulose and hemicellulose (González-Fernández et al., 2012) in the 348 presence of sporopollenins (Carrillo-Reyes et al., 2016). Ometto et al. (2014) tested sCOD 349 released by three microalgal species after enzymatic pretreatment (24 h, 50 °C) using five 350 different enzymes and doses, showing that pectinases generated higher solubilisation of S. 351 obliquus biomass. Similarly, Maffei et al. (2018) reported cell damage, changes in cell 352 morphology, and release of microalgal intracellular components after enzymatic pretreatment of 353 Nannochloropsis sp. with cellulase and mannanase. Passos et al. (2016) likely obtained high 354 solubilisation of the algal biomass when applying enzyme A and cellulase at a 1% dose (t = 6 h, 355 37 °C). Due to the synergetic effect on the diverse macromolecules of the algal biomass, those 356 researchers highlighted the use of the enzymatic cocktail (enzyme A) over the sole enzyme 357 (cellulase), and moreover, they stated that the enzymes glucohydrolase and xylanase may have 358 had an effect once the organic matter was hydrolysed by cellulase (Passos et al., 2016). 359 3.2.2. Anaerobic digestion of enzymatically pretreated microalgal 360 biomass 361 To further test the effect of the enzymatic pretreatment on algal biomass anaerobic digestibility, 362 BMP tests of the enzymatically pretreated microalgal biomass were performed under the 363 previously defined optimal conditions of 1% and 2% enzyme doses at exposure times of 0.5 h 364 and 2 h, respectively (BMP-set 1, Fig. 1a and 1b). The microalgal biomass contained 0.44 g VS 365 L-1. 366 The net methane yield obtained in all trials in BMP-set 1 is shown in Fig. 5a and 5b. Differences 367 between methane yields achieved after pretreatments M-B1 and M-C1 (640.9 ± 19.7 and 652.0 368 ± 13.8 NmL CH4 g VS-1, respectively) were not statistically significant (p > 0.05) (Fig. 5a and Table 369 1), and biogas production amounts for both pretreatments were 5.2- and 5.3-fold higher than that 370 obtained by the untreated biomass (RM), respectively (differences were statistically significant, p 371 < 0.05). Although sCOD was reduced by 91% in M-A1 (Table 1), methane production was 43- 372 46% lower (447.5 ± 40.0 NmL CH4 g VS-1) compared with M-B1 and M-C1 (p < 0.05). Similarly, 373 M-B1 and M-C1 presented a greater methane production rate (4.3 mL d -1) than M-A1 (3.0 mL d- 14 374 1). However, the bioconversion process for M-A1 (KH = 0.194 d-1) was more than 2-fold higher 375 than that of the other pretreatments at the 1% dose (Table 1). For methane productivity, reactors 376 M-A1, M-B1, and M-C1 achieved 90% methane production after 23, 19 and 15 days, respectively. 377 The different outputs could be associated with the assorted enzyme composition of the enzymatic 378 cocktails and their interaction with the microalgal biomass. 379 380 Figure 5 381 382 Surprisingly, when the enzyme dose (2%) was increased, methane production for pretreatments 383 M-A2, M-B2, and M-C2 decreased by 9%, 27%, and 16%, respectively (Fig. 5b and Table 1) 384 compared with the pretreatment with the same enzyme at the lower dose (1%). Although higher 385 solubilisation was achieved with pretreatments at the 2% dose and t = 2 h, anaerobic digestibility 386 was lower than that with pretreatments at the lower dose (Table 1). Bearing in mind that the 387 microalgal concentration was the same in all pretreatments, one hypothesis is that the excess 388 enzyme in the pretreatments at the 2% dose might not interact with the microalgal biomass, thus 389 inhibiting anaerobic microorganisms and reducing methane yield. In contrast to digestion of raw 390 microalgae, the methane yield increased sharply when microalgae were pretreated with the three 391 enzymes at the 2% dose (p < 0.05). Moreover, significant statistically differences were found 392 between the M-A2 and M-C2 pretreatments. 393 394 Table 1 395 396 Methane production increased faster during the first 15 days for all pretreatments. For biogas 397 composition, no differences were identified among the trials (Table 1). At the end of the BMP 398 tests, pH values of the digestates between 7.2 and 7.7 suggest the stability of the process. 15 399 Moreover, the concentration of VFAs was negligible in all cases. Fig. S3 shows that the 400 relationship between methane yield and solubilisation increases after pretreatment. 401 The reduction in sCOD in BMP-set 1 was similar and higher than 90% for all trials. Nonetheless, 402 the differences obtained in the methane yield for all of the trials are not consistent with their 403 respective solubility increases after the enzymatic pretreatment. This fact suggests that the 404 solubilized organic matter is not totally converted into methane. Consequently, it was not possible 405 to identify a direct relationship between the reduction in sCOD and the methane yield. The 406 compromise between a low enzymatic dose applied at a short exposure time to achieve a high 407 methane yield represents the most favourable strategy for addressing the economic feasibility 408 and applicability of the treatment (Fig. S3). Based on these outcomes, the enzymatic 409 pretreatments of microalgae with enzyme B1 (M-B1) and C1 (M-C1) at t = 30 min were selected 410 as the proper treatments for co-digestion studies (BMP-set 2) (Fig. 1a and 1b). 411 3.3. Co-digestion of enzymatically pretreated microalgal biomass and waste activated 412 sludge 413 According to the results from the above experiments, two optimal enzymatic pretreatments 414 (enzyme B and enzyme C at a 1% dose (v/v) at t = 0.5 h) were selected to further study the co- 415 digestion of the pretreated microalgal biomass with WAS as a co-substrate (BMP-set 2, Fig. 1a 416 and 1b). This set of experiments contained 17.3 ± 0.1, 4.3 ± 0.1, and 8.5 ± 0.3 g VS L-1 inoculum, 417 WAS, and gravity-concentrated microalgae, respectively. 418 As shown in Fig. S4 (net methane yield) and Fig. 6 (cumulative methane production), the methane 419 production obtained when co-digesting enzymatically pretreated microalgae (M-B1 and M-C1) 420 with WAS (WAS:M-B1 and WAS:M-C1) was similar to values obtained when using raw 421 microalgae in the mixture (WAS:RM). Compared with WAS:RM, the net methane yield was 2% 422 and 7% lower for WAS:M-B1 and WAS:M-C1 (Fig. S4), respectively; however, this difference was 423 not statistically significant (p > 0.05). Similarly, VS reduction was similar in the three reactors 424 (Table 2). The methane yield of WAS:RM increased faster during the first days, causing a poor fit 425 for the lag phase (λ) parameter of the Gompertz model (Table 2). Compared with WAS:RM, the 426 hydrolysis rate (KH) decreased for WAS:M-B1 (0.064 d-1). However, the Rmax values showed a 16 427 higher methane production rate for this mixture (Table 2). This result could be explained by the 428 effect of the previous microalgal enzymatic hydrolysis contributing to a greater bioavailability of 429 the substrate. The major net methane yield of all the trials was obtained for WAS mono-digestion 430 (179.3 g CH4 g VS-1) (Fig. S4 and Table 2). Although the difference was not statistically significant 431 (p > 0.05), the methane yield of WAS and raw microalgae co-digested (WAS:RM) was 7% lower 432 than that obtained by WAS. Nevertheless, the co-digestion of WAS:RM improved the KH by 11% 433 and the VS reduction by 27% compared with the mono-digestion of WAS. According to our results, 434 enzymes applied to the microalgal biomass did not enhance methane production when co- 435 digested with WAS. The values of VFAs accumulated in the reactors at the end of the BMP tests 436 (Table 2) could indicate that biomasses were also converted to volatile compounds other than 437 methane. Some studies showed an enhancement in methane yield after co-digestion of sewage 438 sludge and raw microalgal biomass, attributing this result to higher nutrient availability, enhanced 439 alkalinity, and a balanced C/N ratio to avoid ammonia inhibition (Beltrán et al., 2016b; Olsson et 440 al., 2014; Solé-Bundó et al., 2020). However, Kim and Kang (2015) also observed a decline of 441 9% in methane accumulation when microalgae (Chlorella sp.) were co-digested with WAS 442 compared with WAS mono-digestion. Caporgno et al. (2015) stated that there was no synergy 443 between microalgae (25% Selenastrum capricornutum) and sludge (75% of a blend of primary 444 and secondary sludge) co-digestion and obtained lower methane than sludge alone. In the same 445 way, a mixture of microalgae (Ankistrodesmus, Chlorella, Coelastrum, Scenedesmus opoliensis, 446 Scenedesmus quadricauda, Scenedesmus sp., among others) and sludge (37% and 63% on a 447 VS basis, respectively) showed low digestibility, obtaining a lower methane yield compared with 448 the sludge alone, as reported by Olsson et al. (2018). In addition, Wang et al. (2013) observed 449 comparable methane yields of WAS alone and WAS co-digested with raw microalgal biomass 450 (Chlorella sp.). Diverse outputs after microalgae and sludge co-digestion could be related to the 451 specific features of both substrates (microalgal composition is strain-specific) as well as to the 452 different proportions of WAS and microalgae employed in the mixtures. The results of co-digestion 453 assays differed slightly from those of WAS mono-digestion. Pretreated and untreated microalgal 454 co-digestion with WAS seemed neither to have a synergetic effect nor a toxicity effect on biogas 455 production, indicating that both substrates could be digested together, thus avoiding the costs 456 associated with separated digestion processes (Elalami et al., 2019). 17 457 458 459 Figure 6 460 461 Table 2 462 463 Typically, studies report sludge co-digestion with untreated co-substrates such as the organic 464 fraction of municipal solid waste and agro-industrial and fatty wastes as co-substrates. 465 Nonetheless, few studies have assessed the co-digestion of WAS and previously treated co- 466 substrates such as microalgal biomass. An increase of 12% in methane production was achieved 467 when co-digesting a mixture of 75% secondary sludge and 25% microalgae (C. vulgaris) when 468 both substrates were thermally pretreated (120 °C, 40 min) (Mahdy et al., 2015a). Compared with 469 untreated biomasses, Scarcelli et al. (2020) reported a slight increase in methane production 470 when a thermal pretreatment (65 °C, 4 h) was applied to a WAS (60%) and microalgal (Chlorella 471 sp., 40%) mixture. Similarly, Zhang et al. (2018) studied the co-digestion of microalgae (Chlorella 472 sp.) pretreated with an enzymatic cocktail of cellulase, xylanase, and pectinase for lipid extraction 473 using energy grass (Pennisetum hybrid) as a co-substrate. As far as the authors are concerned, 474 this study assesses the co-digestion of WAS and enzymatically pretreated microalgae for the first 475 time. 476 To test the effect of the enzymes on the WAS, the same dose of enzyme applied to the microalgae 477 was directly added to the WAS in the BMP reactors WAS-B1 and WAS-C1. The results showed 478 that enzymes B1 and C1 weakly reduced the net methane yield of WAS by 5% (WAS-B1) and 479 2% (WAS-C1), respectively (Fig. S4 and Table 2), but these differences were not statistically 480 significant (p > 0.05). Nonetheless, a greater VS reduction took place in the WAS-B1 and WAS- 481 C1 reactors (30% and 27%, respectively) compared with WAS (19%), suggesting that the 482 enzymes could contribute to major solubility and further degradation of the organic matter in the 18 483 WAS. Furthermore, the hydrolysis rate of the secondary sludge slightly increased in the reactors 484 to which the enzymes were added (Table 2). 485 To verify that the enzymes did not negatively affect the inoculum, the influence of the enzymes 486 on the inoculum in biogas production was tested. The results in Fig. 6 indicated that I-B1 and I- 487 C1 exhibited 33% and 42% increases in methane production compared with the blank reactor (I), 488 respectively. This fact suggests that enzymes B and C did not inhibit the anaerobic 489 microorganisms present in the inoculum. 490 491 4. Conclusions 492 This study assessed the pretreatment of microalgal biomass for solubility enhancement and 493 further anaerobic digestion of pretreated microalgae as well as its co-digestion with WAS. 494 First, similar results were obtained when harvesting microalgae by natural sedimentation and 495 alkaline pretreatment at pH 10 and 11. Similarly, microalgal solubility was not improved by pH 496 adjustment. Hence, this pretreatment was rejected for algal biomass harvesting prior to 497 valorisation. 498 Second, enzymatic hydrolysis pretreatments were performed to enhance the solubility of the 499 microalgal biomass. The optimal pretreatment conditions were t = 0.5 h and t = 2 h for 1 and 2% 500 doses, respectively. Compared with raw microalgal biomass, the enzymatic pretreatment highly 501 enhanced the solubility and the biogas yield of the algal biomass at both doses, showing efficient 502 solubilisation and anaerobic digestibility of the biomass. Although the organic matter solubilisation 503 registered was higher for pretreatments at the higher dosage, the methane yield markedly 504 increased for microalgal biomass pretreated with the lower enzyme dosage. When co-digesting 505 microalgae with WAS, comparable methane yields were obtained for enzymatically pretreated 506 and untreated algal biomass. Since the previous enzymatic treatment of the microalgae did not 507 enhance the methane yield, it can be neglected to reduce costs. Overall, even though co-digestion 508 with microalgae under the studied conditions did not improve energy production, co-digestion is 19 509 a promising and economically feasible alternative for diverse waste stream treatments via the 510 integration of WWTP facilities and microalgae-based systems. 511 Based on the obtained outcomes, future research should include pilot-scale studies to verify these 512 results, assess the start-up of the reactor, and the influence of substrates variability along seasons 513 in the process performance. Moreover, the evaluation of hydrogen production potential should be 514 considered in future studies as an important avenue to improve energy conversion from algal 515 biomass. 516 517 Acknowledgments 518 This work has been funded by the Generalitat de Catalunya (ViTech project TES/792/2017) and 519 the Spanish State Research Agency (AEI) and the European Regional Development Fund 520 (ERDF) through the project BECAS (CTM2016-75587-C2-1-R). 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WAS = waste activated sludge. PBR = photobioreactor. EH = enzymatic hydrolysis. BMP 731 = biochemical methane potential test. M = microalgae. A1, B1, and C1 refer to pretreatments with 732 the enzymes at a 1% dose while A2, B2, and C2 refer to pretreatments with the enzymes at a 2% 733 dose. 734 30 120 100 Clarification efficiency (%) 80 60 40 PBR-10 PBR-10-C 20 PBR-11 PBR-11-C 0 0 2 4 6 8 Time (d) 735 736 Figure 2. Clarification efficiency (%) after the alkaline pretreatment at pH 10 (PBR-10) and pH 11 737 (PBR-11), and their respective untreated controls (PBR-10-C and PBR-11-C). Error bars in PBR- 738 10 and PBR-11 represent the standard deviation of the mean (n = 3). 739 31 100 VSS reduction (%) 80 60 40 20 0 PBR-10 PBR-10-C PBR-11 PBR-11-C pH 10 pH 11 740 741 Figure 3. VSS reduction in the supernatant of PBR-10 and PBR-11 after pH-adjustment and 742 neutralization, and their respective untreated controls (PBR-10-C and PBR-11-C). Error bars in 743 PBR-10 and PBR-11 represent the standard deviation of the mean (n = 3). 744 32 a 745 b 746 747 Figure 4. Soluble chemical oxygen demand (sCOD) released after enzymatic pretreatments of 748 microalgal biomass with enzymes A, B, and C, at doses of (a) 1% v/v (M-A1, M-B1, and M-C1), 33 749 and (b) 2% v/v (M-A2, M-B2, and M-C2) in EH-set 1. Boxplots represent the median value, and 750 the 25th and 75th percentile at each time. 751 34 800 M-A1 a M-B1 M-C1 600 RM NmL CH4 g VS-1 400 200 0 0 5 10 15 20 25 30 35 40 Time (d) 752 800 M-A2 b M-B2 M-C2 600 RM NmL CH4 g VS-1 400 200 0 0 5 10 15 20 25 30 35 40 Time (d) 753 754 Figure 5. Net methane yield of microalgal biomass enzymatically pretreated at (a) a 1% dose v/v 755 with enzyme A, B, and C (M-A1, M-B1, and M-C1) for 0.5 h; and at (b) a 2% v/v dose with enzyme 756 A, B, and C (M-A2, M-B2, and M-C2) for 2 h, in BMP-set 1. RM refers to microalgal biomass 757 without pretreatment. Dots represent the experimental data while continuous lines correspond to 758 the fitting by the Gompertz model. Error bars represent the standard deviation of the mean (n = 759 3). 35 760 Table 1. Parameters from the enzymatic hydrolysis of microalgae (EH-set 2) and biochemical methane potential tests (BMP-set 1). Enzymatic pretreatment Biomethane potential test (EH-set 2) (BMP-set 1) Net Gompertz model Hydrolysis rate Trial sCOD experimental Methane sCODf* reduction CH4 yield content Pmax Rmax (mg L-1) λ KH (%)** (NmL CH4 (%) (NmL CH4 (NmL CH4 r2 r2 g VS-1) (d) (d-1) g VS-1) g VS-1 d-1) RM 52.8 ± 2.7 18 ± 0 124.2 ± 7.9 73 ± 4 232.5 ± 179.1 3.2 ± 0.7 1.1 ± 0.8 0.920 0.008 0.907 M-A1 5858.7 ± 1449.8 91 ± 0 447.5 ± 40.0 69 ± 1 405.8 ± 10.7 53.7 ± 9.4 -0.2 ± 0.7 0.955 0.194 0.974 M-B1 6163.3 ± 1308.0 95 ± 1 640.9 ± 19.7 69 ± 8 627.1 ± 9.9 50.9 ± 3.2 1.2 ± 0.4 0.993 0.092 0.975 M-C1 6085.3 ± 60.0 91 ± 2 652.0 ± 13.8 68 ± 10 649.1 ± 11.6 51.6 ± 3.7 1.2 ± 0.5 0.991 0.092 0.969 M-A2 13096.0 ± 1119.4 90 ± 3 406.1 ± 39.0 70 ± 1 362.6 ± 9.1 50.9 ± 8.8 0.0 ± 0.6 0.959 0.194 0.972 M-B2 12950.0 ± 500.3 90 ± 1 467.2 ± 39.0 70 ± 7 446.0 ± 8.3 38.1 ± 3.1 0.8 ± 0.5 0.989 0.103 0.982 M-C2 11546.7 ± 1012.0 92 ± 2 548.0 ± 11.2 70 ± 8 526.7 ± 9.1 43.1 ± 3.0 0.9 ± 0.4 0.991 0.096 0.980 761 References: RM = raw microalgae (without pretreatment). Enzymatically pretreated microalgae with enzymes A, B, and C at a 1% dose = M-A1, M-B1, and M-C1. Enzymatically pretreated microalgae 762 with enzymes A, B, and C at a 2% dose = M-A2, M-B2, and M-C2. 763 (*) Soluble chemical oxygen demand at the end of the enzymatic pretreatment (0.5 h for 1% dose, and 2 h for 2% dose). 764 (**) Soluble chemical oxygen demand reduction was calculated considering sCOD values at initial and final time of the BMP tests. 765 36 350 Cumulative CH4 production (mL) 300 250 200 150 100 50 0 766 767 Figure 6. Cumulative methane production in BMP-set 2 for the following trials: WAS; WAS with 768 enzyme addition (WAS-B1 and WAS-C1); mixture of WAS and raw microalgae (WAS:RM); 769 mixture of WAS and enzymatically pretreated microalgae (WAS:M-B1 and WAS:M-C1); inoculum 770 (I); and inoculum with enzyme addition (I-B1 and I-C1). Error bars indicate the standard deviation 771 of the mean (n = 3). References: RA = raw microalgae without pretreatment. WAS = waste 772 activated sludge. I = inoculum. B1 = enzyme B at a 1 % dose. C1 = enzyme C at a 1% dose. M- 773 B1 = microalgae pretreated with enzyme B at a 1% dose (t = 0.5 h). M-C1 = microalgae pretreated 774 with enzyme C at a 1% dose (t = 0.5 h). 37 775 Table 2. Experimental and calculated parameters from the biochemical methane potential tests of WAS (waste activated sludge) and microalgae co-digestion 776 (BMP-set 2). 777 Net VFAs (mg L-1) Gompertz model Hydrolysis rate VS experimental Methane Trial reduction CH4 yield content Pmax Rmax (%) (NmL CH4 (%) Acetic Propionic (NmL CH4 (NmL CH4 λ (d) r2 KH (d-1) r2 g VS-1) acid acid g VS-1) g VS-1 d-1) WAS:RM 26 ± 2 166.0 ± 2.2 71 ± 2 34.1 ± 2.0 107.1 ± 17.9 164.7 ± 5.6 8.2 ± 0.8 -1.4 ± 1.7 0.984 0.080 0.993 WAS:M-B1 24 ± 3 162.6 ± 10.0 69 ± 10 38.5 ± 7.9 152.4 ± 4.6 158.3 ± 4.4 9.6 ± 0.9 0.9 ± 0.7 0.988 0.064 0.994 WAS:M-C1 24 ± 10 154.9 ± 16.5 70 ± 3 34.8 ± 7.2 131.5 ± 18.6 154.4 ± 5.1 7.8 ± 0.6 0.4 ± 0.7 0.989 0.055 0.992 WAS 19 ± 3 179.3 ± 11.0 70 ± 2 56.0 ± 4.6 158.3 ± 61.2 179.4 ± 6.5 8.4 ± 0.8 -1.4 ± 0.8 0.985 0.072 0.994 WAS-B1 30 ± 12 170.4 ± 6.3 70 ± 2 20.1 ± 3.7 77.1 ± 12.9 167.1 ± 6.1 8.5 ± 0.9 -1.5 ± 0.9 0.980 0.085 0.992 WAS-C1 27 ± 1 175.0 ± 9.2 68 ± 3 24.9 ± 1.7 104.7 ± 26.0 171.3 ± 6.2 8.7 ± 0.9 -1.3 ± 0.9 0.982 0.081 0.994 778 References: WAS:RM = mixture of waste activated sludge (WAS) and raw microalgae without pretreatment (RM). WAS:M-B1 and WAS:M-C1 = mixture of WAS and enzymatically pretreated microalgae 779 with enzyme B at a 1% dose and enzyme C at a 1% dose, respectively. WAS-B1 and WAS-C1 = WAS with addition of enzyme B at a 1% dose and enzyme C at a 1% dose, respectively. 38