Evaluation of filamentous heterocystous cyanobacteria for integrated pig-farm biogas slurry treatment and bioenergy production

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Evaluation of filamentous heterocystous cyanobacteria for integrated pigfarm biogas slurry treatment and bioenergy production Yuzhen Lua, Chen Zhuoa, Yongjun Lib, Huashou Lia, Mengying Yanga, Danni Xua, Hongzhi Hea,

⁎

a

Key Laboratory of Agro-Environment in the Tropics, Ministry of Agriculture, Guangdong Provincial Key Laboratory of Eco-Circular Agriculture, South China Agricultural University, Guangzhou 510642, China b Qingyuan Polytechnic, Qingyuan 511510, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Pig farm Biogas slurry Filamentous cyanobacteria Wastewater treatment Bioenergy

The study evaluates 36 filamentous heterocystous cyanobacteria for the treatment of biogas slurry from pig farm and the accumulation of biomass for bioenergy production. The results showed that only the strains B, J, and L were able to adapt to a 10% biogas slurry. The removal rates of ammonia nitrogen, total nitrogen, and total phosphorus for strains J and L were 92.46%–97.97%, 73.79%–79.90%, and 97.14%–98.46%, respectively, higher than that of strain B. Strain J had the highest biomass productivity and lipid productivity. Based on the biodiesel prediction results, it was concluded that strains J and L are more suitable for biodiesel production. The estimation of theoretical methane potential suggests that the algal biomass of strain J also have the desirable possibility of biogas generation. In summary, algal strain J (Nostoc sp.) offers great potential for biogas slurry treatment and for the production of bioenergy.

1. Introduction The pig industry is one of the leading animal husbandry industries in China. The output value of pig industry was nearly 1.3 trillion, accounting for 56.6% of the total output value of domestic livestock and poultry in 2017 (China’s National Bureau of Statistics, 2017). At the same time, pig farms produce a significant volume of wastewater, which poses a major threat to the environment and human health when it is disposed of inappropriately (Cheng et al., 2019). Currently, wastewater from large livestock and poultry farms is usually treated using anaerobic fermentation in a biogas digester. However, biogas slurry (BS) still contains strong organic and inorganic pollutants, thus further treatment is required before recycling or discharging the wastewater into natural water bodies (Khan et al., 2018). The development of renewable and sustainable energy sources is a promising way to avoid energy crises and to prevent the worsening of global climate change (Cheng et al., 2019). In this respect, microalgae bioenergy has been proposed as a future sustainable energy source because microalgae have some obvious advantages in terms of bioenergy production when compared with energy crops (Marjakangas et al., 2015). However, microalgal biomass production is still too expensive for commercial application, with nutrient requirements accounting for around half of the cost of microalgae cultivation (Xia and Murphy, 2016). ⁎

Anaerobic digestate, which contains high nutrient levels, may be a feasible nutrient source for the cultivation of microalgae (Zhu et al., 2016). In addition to its rapid growth rate and high oil yield, microalgae can also grow in wastewater and effectively remove primary nutrients, heavy metals, and micropollutants (Miranda et al., 2017). Combining the treatment of liquid BS with microalgae production can significantly reduce the costs of both (Xia and Murphy, 2016). In addition, microalgae are rich in fat, protein and starch, which can be utilized as a non-food raw materials for energy and chemical production (Chen et al., 2012). A number of reports have investigated the feasibility of combining the microalgal treatment of piggery wastewater with lipid production from the microalgal biomass, with current research focusing on green algae, especially Chlorella (Cheng et al., 2019; Zhang et al., 2019; Zheng et al., 2019). However, because this is a group of unicellular algae, their low density and microscopic size makes their separation from cultures difficult. In fact, separating algae from culture media and removing the water from the algae can account for up to 30–40% of the total cost of biodiesel production (Miranda et al., 2017). In contrast to unicellular algae, filamentous microalgae can aggregate and be collected easily through filtration or flotation, thus reducing harvesting costs (Zhang et al., 2016). For this reason, filamentous cyanobacteria, such as Nostoc, Anabaena, Calothrix, Spirulina, have been proposed as potential sources for biodiesel production (Amit and Ghosh, 2018; Anahas and Muralitharan, 2015, 2018; Gayathri

Corresponding author. E-mail address: [email protected] (H. He).

https://doi.org/10.1016/j.biortech.2019.122418 Received 27 August 2019; Received in revised form 10 November 2019; Accepted 11 November 2019 0960-8524/ © 2019 Elsevier Ltd. All rights reserved.

Please cite this article as: Yuzhen Lu, et al., Bioresource Technology, https://doi.org/10.1016/j.biortech.2019.122418

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The selected cyanobacteria were identified by sequencing the 16S rRNA and rbcLX genes. In brief, genomic DNA was extracted using a GeneJET™ Genomic DNA Purification Kit (Thermo Scientific, USA) according to the manufacturer’s protocol. The 16S rRNA gene was amplified using polymerase chain reaction with the universal primers 27F (5′-AGAGTTTGATCMTGGCTCAG-3′) and 1492R (5′-TACGGYTACCTTGTTACGACTT-3′). The rbcLX gene was amplified using primers CX ( 5′-GGCGCAGGTAAGAAAGGGTTTCGTA-3′) and CW (5′-CGTAGCTTCC GGTGGT AT CCACGT-3′) (Rudi et al., 1998). The amplified sequences were analyzed against the NCBI database using BLAST algorithms (Altschul et al., 1990).

et al., 2018), while some have also been assessed for wastewater treatment coupled with lipid production (Amit and Ghosh, 2018; Khan et al., 2019). However, there have been no reports on the treatment of pig farm BS using filamentous cyanobacteria coupled with the use of the algal biomass in bioenergy production. Therefore, the present study aims to screen filamentous cyanobacteria for BS treatment and to evaluate the algal biomass as a potential feedstock for bioenergy production. 2. Materials and methods 2.1. Filamentous cyanobacteria

2.4. Evaluation of pollutant removal ability Thirty-six strains of filamentous heterocystous cyanobacteria were screened in the present study. Of these strains, 33 were isolated in our laboratory from samples from freshwater habitats such as paddy fields and ponds in the Guangdong, Hunan, and Hainan provinces of China. Samples were collected and pre-cultured in the nitrogen-free medium BG110 (Rippka et al., 1979) immediately after entering the lab. Purification was conducted according to the method described by Anahas and Muralitharan (2015). The remaining three strains (FACHB-85, 89, and 131) were purchased from the Freshwater Algae Culture Collection of the Institute of Hydrobiology at the Chinese Academy of Sciences. Stock cultures of the algae were maintained at 27 °C in sterilized BG110 at pH 7.5 with a light intensity of 3000 lx provided by cool white fluorescent lamps and a 16 h/8h light/dark cycle.

Ten milliliters of the algal suspension was collected every two days from each Erlenmeyer flask and centrifuged at 6000 rpm for 8 min. The supernatant was filtered through a 0.45-mm nylon membrane filter. The concentrations of NH4+-N, TN, TP, and COD in the filtrates were measured using flow injection analysis with an AA3 HR Auto Analyzer (SEAL). The concentrations of Pb, Cu, Zn, and Cr were measured using an atomic absorption spectrometer (ZEEnit700P, Analytik Jena), while the concentration of As was measured using an atomic fluorescence spectrometer (AFS-230E). 2.5. Determination of total lipid content and fatty acid profiles Lipids were extracted from the cyanobacteria following the method described by Folch et al. (1957) with modifications. Briefly, 100 mg of lyophilized algal biomass was mixed with a mixture of chloroform and methanol (2:1, v/v), homogenized with a rotary shaker for 30 min followed by ultrasonic treatment for 5 min. The process was then repeated until the extraction was complete. The mixture was centrifuged at 6000 rpm for 8 min. The supernatant was mixed with a third of the volume of distilled water and vortexed for 30 s. It was left to stand in a separation funnel so two layers could form, after which the lower layer containing the lipids was removed carefully. The pooled extracts were passed through solid anhydrous sodium sulfate and transferred to a preweighed glass tube. After the organic solvents had been removed by rotary evaporation, the crude lipids left in the tube were weighed. The lipid content was expressed as a percentage on a dry weight basis. In order to determine the fatty acid content, the samples were prepared following the method described by Miller and Berger (1985). Briefly, the lipids were boiled for 30 min with 1 mL of saponification reagent containing 15 g of NaOH in 100 mL of a methanol and water mixture (1:1, v/v) and then boiled with 2 mL of methylation reagent comprising methanol and 6 N HCl (1:1.18, v/v) at 80 °C for 20 min. The mixture was cooled and fatty acid methyl esters (FAMEs) were extracted with 1 mL of hexane. Finally, the extract was washed with 3 mL of 1.2% NaOH (w/v) and 2 μL of the organic phase was collected for analysis. The quantitative analysis of the FAMEs was conducted using a Thermo Scientific Trace 1300 gas chromatograph equipped with a CPSil 88 capillary column (Agilent, USA, 100 m × 0.25 mm I.D. × 0.20 μm) and a flame ionization detector (FID). The oven temperature was initially held at 100 °C for 1.5 min and then increased to 210 °C at a rate of 3.0 °C min−1 and held at this temperature for 40 min. The injector and FID detector temperatures were set at 230 °C and 280 °C, respectively. Injections were performed under split mode. The FAME components were identified and quantified by comparing the retention time and area of the authentic standards mix C4-C24 (NUCHEK-PREP, INC, USA). Fatty acid composition was expressed as a percentage of the weight relative to all FAMEs.

2.2. Biogas slurry (BS) The pig farm BS used in the present study was collected from a large pig farm located in Guangzhou, China. The BS was centrifuged for 8 min at 6000 rpm to settle the excess colloidal particles. After filtering the BS through a 0.45-μm membrane filter, it was stored at 4 °C. The BS consisted of 255.23 ± 3.46 mg L−1 ammonia nitrogen (NH4+-N), 411.55 ± 9.23 mg L−1 total nitrogen (TN), 14.47 ± 1.04 mg L−1 total phosphorus (TP), 100.00 ± 57.70 μg L−1 lead (Pb), 5.70 ± 0.60 μg L−1 cadmium (Cd), 54.70 ± 46.10 μg L−1 copper (Cu), 366.20 ± 35.40 μg L−1 zinc (Zn), and 23.73 ± 4.73 μg L−1 arsenic (As). It also had a pH of 8.25 ± 0.01 and a chemical oxygen demand (COD) of 1316.63 ± 33.61 mg L−1. The BS was diluted with distilled water and the pH was adjusted to 7.0. Following this, 500-mL Erlenmeyer flasks containing 200 mL of the dilute BS were autoclaved for 20 min at 121 °C. An algal suspension was then introduced to the Erlenmeyer flasks to produce an optical density (OD680) of 0.04. The culture conditions were the same as described in Section 2.1. All treatments were tested in triplicate. The specific growth rate (μ) of the algae was calculated using Eq. (1):

μ =

Nj 1 ln ⎛ ⎞ j − i ⎝ Ni ⎠ ⎜

⎟

(1)

where Ni and Nj represent the OD680 at day i and day j, respectively. The cyanobacterial biomass was harvested on day 14 via centrifugation at 6000 rpm for 8 min. The algal cells were washed with distilled water and lyophilized. 2.3. Resistant algal strain screening, domestication, and identification In the screening experiments, the pig farm BS was diluted with distilled water to produce 10%, 50%, and 100% dilutions. The culture suspension of filamentous cyanobacteria was introduced to the BS dilutions to produce an OD680 of 0.1. After four days of treatment, the OD680 of the algal culture was measured and the filament and cell morphology of the algae were observed under an optical microscope. After screening, the selected cyanobacteria were domesticated three times by continuously placing them in fresh BS.

2.6. Biodiesel quality assessment To evaluate biodiesel quality, the degree of saturation (DU), cetane 2

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number (CN), saponification value (SV), iodine value (IV), density (ρ), kinematic viscosity (ν), oxidative stability (OS), cloud point (CP), pour point (PP), higher heating value (HHV), saturated fatty acid (SFA) levels, monounsaturated fatty acid (MUFA) levels, polyunsaturated fatty acid (PUFA) levels, the allylic and bis-allylic position equivalents (APE and BAPE, respectively), long-chain saturation factor (LCSF), and cold filter plugging point (CFPP) were calculated based on the composition of the FAMEs (Anahas and Muralitharan, 2018; Mathimani et al., 2018). Biodiesel fuel specifications were taken from the biodiesel standard ASTM D6751 for the United States and EN 14,214 for Europe (Hoekman et al., 2012). 2.7. The carbohydrate and crude protein analysis The carbohydrate content was determined using phenol-sulfuric acid method employing glucose as the standard (Kochert, 1978). Crude protein content has been estimated based on the total Kjeldahl nitrogen (TKN) content as nitrogen content is multiplied by a factor (6.25) to arrive at protein content (Becker, 1994). The TKN content of dried algal biomass was estimated using a Kjelmaster K-375 (Buchi).

Fig. 1. Growth curves of cyanobacteria cultured with BG110 media or 10% BS.

were from the genera Nostoc and Anabaena, with a 99% homology, and the results were further confirmed by the results of the homology analysis of rbcLX (Table 1), which identified strains B, J, and L as Nostoc piscinale, Nostoc sp., and Anabaena variabilis, respectively.

2.8. Elemental analysis and theoretical biomethane potential (BMPth) evaluation The harvested algal biomass was dried in the oven at 60 °C and used for elemental analysis with a CHNS elemental analyser (Vario EL Cube, Elementar). The percent contents (%) of carbon (C), hydrogen (H), nitrogen (N) and sulphur (S) were detected directly, and the oxygen (O) content calculated by difference based on determination of C, H, N and S by elemental analysis. The total solids (TS) and volatile solids (VS) were determined gravimetrically using the methods described in APHA (2005). The theoretical biomethane potential (BMPTh) were calculated using Boyle’s equation (Eq. (2)) based on the elemental composition (Lesteur et al., 2010): n

BMP =

22400 × ( 2 +

a 8

−

b 4

−

12n + a + 16b + 14c

3c ) 8

mL CH 4 g−1VS

3.2. The pollutant removal ability of the filamentous cyanobacteria The change in the NH4+-N, TN, TP, and COD content of BS when treated with the heterocystous filamentous cyanobacteria strains B, J, and L over the course of the 14-day batch experiment is presented in Fig. 2, and the removal rates on day 14 are displayed in Table 2. During the 14-day treatment of the BS with algal strains B, J, and L, the TN and NH4+-N concentrations decreased gradually over time, with the TN and NH4+-N removal ability highest for strain L, though it was not significantly different from that of strain J. On day 14, the TN removal rates for algal strains J and L were 73.79% and 79.90%, respectively, both of which were significantly higher than that of strain B (54.06%). For NH4+-N, the removal rates for strains J and L were 92.46% and 97.97%, respectively, which were also significantly higher than that of strain B (82.33%, Table 2). The TP was removed very rapidly from the BS by strains B and J within in first four days, with their removal rates reaching 86.84% and 99.91%, respectively, during this period, much higher than that of strain L (54.52%). On day 14, the removal rate for strain J (98.46%) was significantly higher than that of strains B (97.03%) and L (97.14%; Table 2). Over the course of the 12-day treatment, the COD decreased gradually when treated with algal strains B and L; on day 12, the removal rates were 61.87% and 57.11%, respectively (Table 2). For strain J, the COD decreased gradually before day 8 and then increased gradually until day 14 (Fig. 2). In addition, the ability to remove heavy metals from BS was also assessed (Table 2). The removal rates of Pb by strains B, J, and L were 74.94%, 80.37%, and 82.04%, respectively. The removal rate of Pb by strain L was significantly higher than that of strain B, but there was no significant difference between strains J and B or between strains J and L. The As removal rates reached 50.55%, 49.34%, and 55.83% for strains B, J, and L, respectively, while for Cd, they were 20.07%, 2.34%, and 28.94%, respectively. There was no significant difference in As and Cd removal rates between the three strains of cyanobacteria. The Zn removal rate of strain L was 24.43%, much higher than that of strains B (9.10%) and J (6.94%). In conclusion, the filamentous cyanobacteria strains J and L effectively removed NH4+-N, TN, and TP from BS. At the same time, they also removed COD and heavy metals to some extent. A number of

(2)

where n, a, b and c represent the molar fraction of C, H, O and N, respectively, and VS represents volatile solids. 2.9. Statistical analysis All values are presented as the mean ± standard deviation. The statistical significance of the results was evaluated using one-way analysis of variance and Duncan’s tests with SPSS 19.0 (SPSS Inc., Chicago, IL, USA). Statistical significance was set at P < 0.05. 3. Results and discussion 3.1. Screening, selecting, and identifying the algal isolates that survive in BS The viability of the 36 heterocystous filamentous cyanobacteria in 10%, 50%, and 100% BS was evaluated in the screening experiment. The results showed that, at the 50% and 100% dilution ratios, the algal filaments of all 36 algal strains were broken down into single cells, and some of the algae cells were completely disintegrated, exposing their content. At the 10% dilution level, a few strains were able to maintain algal filaments with a normal morphology. After domesticating for three times consecutively, only three strains of algae, which were given the preliminary names B, J, and L, were able to adapt to the 10% BS; their growth curves are presented in Fig. 1. The algal filaments of strain J clustered together and were found at the bottom of the Erlenmeyer flask, while strain L was dispersed throughout the flask more evenly. The growth of strain B was not as strong as that of strains J and L. According to 16S rRNA analysis, the microalgal strains B, J, and L 3

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Table 1 Identification of algae by16S rRNA and rbcLX genes homology analysis.

B J L

16S rRNA rbcLX 16S rRNA rbcLX 16S rRNA rbcLX

Description

Max score

Total score

Query cover

E value

Ident

Accession

Nostoc piscinale CENA21 genome Nostoc piscinale CENA21 genome Nostoc sp. NIES-3756 DNA, complete genome Nostoc sp. NIES-3756 DNA, complete genome Anabaena variabilis ATCC 29413 partial 16S rRNA gene Anabaena variabilis ATCC 29413, complete genome

2410 1411 2407 756 2503 1594

7221 1411 9629 1180 2503 1594

99% 100% 99% 84% 99% 93%

0.0 0.0 0.0 0.0 0.0 0.0

99% 99% 98% 96% 99% 99%

CP012036.1 CP012036.1 AP017295.1 AP017295.1 HF678501.1 CP000117.1

COD differed (Fig. 2). Marjakangas et al. (2015) reported that the COD concentration increased during the incubation stage in anaerobically treated piggery wastewater with three green alga species C. sorokiniana CY1, C. vulgaris CY5, and Chlamydomonas sp. JSC-04. It was also demonstrated that, in wastewater, some microalgae can release carbon into the culture.

studies have reported that microalgae can be used to effectively treat wastewater, especially for N, P, and COD removal (Amit and Ghosh, 2018; Hena et al., 2018), and some studies have investigated the treatment of industrial, municipal and agricultural wastewater using filamentous cyanobacteria. For instance, A. spiroides can remove 63.75 ± 4.85% COD, 61.38 ± 5.39% TP, and 56.11 ± 4.03% TN from BS (Wang et al., 2017), Arthrospira platensis can remove about 98.4% COD, 98.8% PO4-P, 99.6% NO3-N and 100% NH4+-N from dairy farm wastewater (Hena et al., 2018), A. ambigua can remove 58.54% BOD, 81.25% COD, 89.52% nitrate, and 87.83% phosphate from dairy wastewater (Brar et al., 2019), and microalgae including N. muscorum produced removal rates of 92, 87, 85, 96, 90 and 81% for NH4-N, NO3N, PO4-P, TDS, BOD5, and COD, respectively, from domestic and food industry sewage (Khan et al., 2019). Singh and Thakur (2015) found that, in batch cultures of Leptolyngbya sp. ISTCY101, the NH4-N and P can be removed completely in 12 and 9 days, respectively, which is similar to the results reported in the present study in terms of N and P removal, though the changes in

3.3. The growth, biomass, and lipid production capacity of the selected cyanobacteria The growth curves of the cyanobacteria cultured with BG110 or 10% BS are shown in Fig. 1, while the specific growth rate, biomass, biomass productivity, lipid content, and lipid productivity of algae grown in BG110 or 10% BS are presented in Table 3. 3.3.1. The growth and biomass production of the selected cyanobacteria When cultured with BG110, the growth of strains B and L was significantly better than that of strain J. The order of biomass and biomass

Fig. 2. Removal of N, P and COD of BS by cyanobacteria. 4

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Table 2 The removal rate (%) of pollutants in 10% BS treated with algae on day 14.

B-BS J-BS L-BS

NH4+–N

TN

TP

Pb

As

Cd

Zn

Cu

82.33 ± 2.34b 92.46 ± 4.27a 97.97 ± 0.33a

54.06 ± 6.49b 73.79 ± 4.28a 79.90 ± 4.09a

97.03 ± 0.12b 98.46 ± 0.31a 97.14 ± 1.10ab

74.94 ± 0.00b 80.37 ± 4.74ab 82.04 ± 0.72a

50.55 ± 4.16a 49.34 ± 9.25a 55.83 ± 3.33a

20.07 ± 12.54a 2.34 ± 12.54a 28.94 ± 0.00a

9.10 ± 4.68b 6.94 ± 4.25b 24.43 ± 2.47a

– – 19.29 ± 7.20a

Note: different letters in the same column indicated the significant difference between algal strains (P < 0.05). “–”, no effects.

between strains J and L. There have been many previous reports on the lipid content of filamentous cyanobacteria. Total lipid content of 4.682%–18.651%, 5.887%–18.921%, and 1.49%–22.5% (%dwt) has been documented for heterocystous cyanobacterial strains by Anahas and Muralitharan (2015, 2018) and Gayathri et al. (2018), respectively. Oliveira et al. (2018) reported that the lipid content of Nostoc sp. was 0.43% and 1.74% in BG-11 and ASM-1 media, respectively, while that for the nonheterocystous cyanobacterial strain Limnothrix sp. was 0.43% and 1.74%, respectively. In addition, Pohndorf et al. (2016) found that the average lipid content of non-heterocystous cyanobacterium Spirulina sp. was 5.8 ± 0.6%. A comparison of the results of the present study to this past research demonstrates that the lipid content of strains B, J, and L is around the middle of the reported range for filamentous cyanobacteria. As shown in Table 3, when cultured with BG110, the lipid productivity of strains B, J, and L was 1.29, 0.76 and 1.49 mg L−1 d−1, respectively, compared with 0.38, 0.69, and 0.48 mg L−1 d−1with 10% BS, respectively. There was no significant different exhibited in the lipid productivity of strain J when cultured with BG110 or 10% BS. Interestingly, however, the lipid productivity of strain J was significantly lower than that of strains B and L in the BG110 cultures but significantly higher than both other strains in 10% BS. This indicates that strain J had the highest capacity for lipid production in wastewater, even though strain B had the highest lipid content under the same culture conditions. The reason for this is that the biomass productivity of strain J in wastewater was much higher than that of strain B, with a 2.9-fold difference between the two (Table 3). Lipid productivity is the result of biomass productivity and lipid content, and it represents a useful index for readily quantifying suitability for biodiesel production. Previous research has focused on lipid productivity associated with biodiesel production (Griffiths et al., 2009). In the present study, strain J exhibited the highest lipid productivity of 0.69 mg L−1 d−1 (a lipid content of 4.91% combined with a biomass productivity of 14.02 mg L−1 d−1) in 10% BS, which is lower than that reported for Leptolyngbya sp. ISTCY101 (about 21 mg L−1 d−1) in municipal sewage (Singh and Thakur, 2015), Spirulina sp. (2.8–7.7 mg L−1 d−1) and N. muscorum (3.2–7.6 mg L−1 d−1) in domestic sewage and food industry wastewater (Amit and Ghosh, 2018), and A. ambigua (about 2.12 mg L−1 d−1, calculated from a lipid content of 53.09 mg L−1 over 25 days) in dairy wastewater diluted three-fold with BG11 medium (Brar et al., 2019), but slightly higher than that of N. muscorum (about 0.57 mg L−1 d−1, calculated from a

productivity for the specific growth rate was L > B > J and B = L > J, respectively. However, the growth of strains J and L were much higher than that of strain B when cultured with 10% BS. The order of biomass and biomass productivity for the specific growth rate was J > L > B and L > J > B. When cultured with BG110, strain L produced the highest biomass (320.33 ± 6.01 mg L−1) and biomass productivity (22.88 ± 0.43 mg L−1 d−1), while strain J showed the highest biomass (196.33 ± 11.00 mg L−1) and biomass productivity (14.02 ± 0.78 mg L−1 d−1) in 10% BS. Therefore, it could be concluded that the tolerance ability of the algal strains to 10% BS was J ≈ L > B. In addition, the biomass and biomass productivity of strains B and L cultured with BG110 were significantly higher than that with 10% BS. It is worth noting that the biomass, biomass productivity, and specific growth rate of strain J cultured with BG110 were not significantly different from those cultured with 10% BS. This indicates that strain J had fully adapted to 10% BS after domestication. Some previous research has investigated the biomass production of filamentous cyanobacteria in wastewater. For instance, Singh and Thakur (2015) reported that the biomass productivity of Leptolyngbya sp. ISTCY101 grown in municipal sewage in batch cultures was 85 ± 0.28 mg L−1 d−1. Amit and Ghosh (2018) also found that the biomass productivity of filamentous cyanobacteria Spirulina sp. and N. muscorum was 16.6–41.1 mg L−1 d−1 in four wastewater types. In addition, Brar et al. (2019) tested dairy wastewater and found that the biomass productivity of A. ambigua was 23.64 ± 5.69 mg L−1 d−1. In the present study, we recorded a maximum biomass productivity of 14.02 ± 0.78 mg L−1 d−1 in wastewater with algal strain J, which was much lower than that of Leptolyngbya sp. ISTCY101 (Singh and Thakur, 2015), close to that of Spirulina sp., N. muscorum and A. ambigua (Amit and Ghosh, 2018; Brar et al., 2019), and higher than that of N. muscorum, which had a maximum dry biomass of 0.14 ± 0.03 g L−1 after 25 days cultivation in domestic and food industry sewage, representing a biomass productivity of 5.6 ± 1.2 mg L−1 d−1 (Khan et al., 2019). 3.3.2. Total lipid content and productivity The total lipid content and lipid productivity of algae grown in BG110 and in 10% BS is presented in Table 3. When cultured with BG110, the cellular lipid content of strains B, J, and L was 8.22%, 5.55%, and 6.51%, respectively, with only the difference between strains B and J being significant. When cultured with 10% BS, the lipid content of strain B (7.97%) was significantly higher than that of strains J (4.91%) and L (4.82%). However, there was no significant difference

Table 3 The specific growth rate, biomass, biomass productivity, lipid content and lipid productivity of algae in BG110 or in 10% BS.

B J L B-BS J-BS L-BS

Specific growth rate (d−1)

Biomass (mg L−1)

Biomass productivity (mg L−1 d−1)

Lipid content (% dw)

Lipid productivity (mg L−1 d−1)

0.19 0.18 0.20 0.14 0.19 0.21

220.67 ± 12.96B* 192.67 ± 1.53C 320.33 ± 6.01A* 67.50 ± 11.20c 196.33 ± 11.00a 140.00 ± 5.00b

15.76 ± 0.93B* 13.76 ± 0.11C 22.88 ± 0.43A* 4.82 ± 0.80c 14.02 ± 0.78a 10.00 ± 0.36b

8.22 5.55 6.51 7.97 4.91 4.82

1.29 0.76 1.49 0.38 0.69 0.48

± ± ± ± ± ±

0.00A* 0.01B 0.00A 0.00c 0.00b 0.00a

± ± ± ± ± ±

0.66A 1.70B 0.59AB* 0.88a 0.84b 0.54b

± ± ± ± ± ±

0.06A* 0.23B 0.11A* 0.03b 0.14a 0.06b

Notes: different capital letters in the same column indicated the significant difference between algal strains cultured with BG110 (P < 0.05), and different lowercase letters in the same column indicated the significant difference between algal strains cultured with 10% BS (P < 0.05). “*” indicated the significant differences (P < 0.05) for the same algae under different culture conditions. 5

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Table 4 The contents (mg g−1 dw) and the percentage composition (in bracket) of fatty acid methyl esters of algal cells. B C14:0 C16:0 C16:1 C17:0 C18:0 C18:1 C18:2 C18:3 C22:0

0.05 1.11 1.10 – 0.12 0.12 0.84 1.98 0.01

J ± 0.02 (0.96) ± 0.61 (20.87) ± 0.77 (20.65) ± ± ± ± ±

0.06 (2.16) 0.05(2.34) 0.57(15.76) 0.98 (37.11) 0.00 (0.17)

0.01 0.45 0.61 0.01 0.04 0.22 0.36 0.71 0.03

L ± ± ± ± ± ± ± ± ±

0.00 0.22 0.23 0.01 0.05 0.07 0.16 0.28 0.02

(0.41) (18.41) (24.87) (0.35) (1.80) (8.96) (14.76) (29.18) (1.26)

– 0.61 0.67 – 0.05 0.14 0.49 0.54 0.02

B-BS

± 0.13 (24.19) ± 0.15 (26.49) ± ± ± ± ±

0.04 0.05 0.13 0.13 0.01

(1.92) (5.47) (19.41) (21.59) (0.93)

– 0.41 0.52 – 0.02 – 0.28 0.73 –

J-BS

± 0.14 (20.92) ± 0.15 (26.97) ± 0.01 (1.02) ± 0.08 (14.65) ± 0.17 (37.47)

– 0.52 1.01 – 0.11 0.28 0.65 0.63 –

L-BS

± 0.17 (16.22) ± 0.24 (31.61) ± ± ± ±

0.04 0.14 0.21 0.19

(3.49) (8.74) (20.24) (19.70)

0.03 0.60 1.30 0.03 0.07 0.18 0.69 0.71 –

± ± ± ± ± ± ± ±

0.02 0.18 0.54 0.02 0.04 0.06 0.25 0.24

(0.94) (16.61) (35.96) (0.82) (1.97) (5.04) (19.09) (19.58)

Note: “-”, not detected.

lipid content of 3.56% and a biomass content of 400 mg L−1 over 25 days) in domestic and food industry sewage (Khan et al., 2019).

vary with environment and nutrient levels. For example, the fatty acid profile of A. doliolum was C16:0 (30%), C16:1 (22%), C18:3 (20%), C18:2 (14%), and C18:1 (10%), while molybdenum-deficiency resulted in a significant increase in C16:0 (42%), C18:2 (22%), and C18:1 (15%) and lower concentrations of C18:3 (10%) and C16:1 (8%; Rathore et al., 1993). Singh et al. (2014) found that the fatty acid profile of Leptolyngbya sp. ISTCY101 mainly consisted of C18:2 (21.2%), C18:0 (19.08%), C16:0 (15.21%), C16:1 (13.1%), C18:3 (8.8%), and C18:1 (7.9%) in BG11 medium, while MUFAs dominated in artificial seawater, with a dramatic increase in C18:1 levels (a maximum of 44.75% at 25 g L−1 NaCl) and an extreme reduction in C16:1, C18:0, and C18:2. When cultivated in synergistically treated municipal wastewater, the fatty acid profile of the alga was C18:0 (25.3%), C16:0 (18.22%), C18:1 (16.89%), C16:1 (10.47%), and C18:3 (10.11%; Singh and Thakur, 2015).

3.3.3. Fatty acid profiles of the cyanobacteria strains In addition to biomass and lipid content, the fatty acid composition of the lipids is also an important characteristic for assessing the suitability of algae as a feedstock for biodiesel production (Anahas and Muralitharan, 2018). The results of the quantitative analysis of the FAMEs found in the three cyanobacteria strains using gas chromatography are presented in Table 4, showing that the dominant FAMEs were C18:3 (19.58–37.47%), C16:1 (20.65–35.96%), C16:0 (16.22–24.19%), and C18:2 (14.65–20.24%), accounting for more than 87% of the total FAME content in both culture media. In the samples, there were also small amounts of C18:1 (2.34–8.96%) and C18:0 (1.02–3.49%), except for the BS culture of strain B, which did not contain C18:1. In addition, when cultivated in BG110, all three cyanobacteria strains contained a small amount of C22:0, while this FAME was not detected in any of the three algal strains when cultivated with 10% BS. There are some key differences between the results of the present study and previous reports on filamentous cyanobacteria. For example, Da Rós et al. (2013) identified the fatty acids in Trichormus sp. CENA77 as C18:1 (36.9%), C16:0 (24.9%), C18:2 (10.7%), and C12:0 (9.7%), while C18:1 (38.8%), C18:2 (26.4%), C16:0 (14.6%), and C18:3 (4.7%) were found in Leptolyngbya sp. CENA104. Steinhoff et al. (2014) also reported the major fatty acid profiles of the heterocystous filamentous cyanobacterial strains Aphanizomenon flos-aquae (C18:3, C16:0, C18:0, C18:1, and C18:2), Dolichospermum lemmermannii (C18:1, C16:0, C16:1, C15:0 and C18:3), and Nodularia spumigena (C16:0, C18:1, C18:4, C18:3, and C16:1). In addition, Anahas and Muralitharan (2015) found that the fatty acid profiles of 11 algal strains belonging to the genera Camptylonemopsis, Anabaena, Nostoc, and Calothrix contained C16:0, C18:1, C18:2, C12:0, and C18:0, while Aboim et al. (2016) reported that the major fatty acids of Lyngbya sp., Leptolyngbya sp., Limnothrix redekei, and Planktothrix pseudoagardhii were C16:0, C18:0, C6:0, and C18:1. Anahas and Muralitharan (2018) documented the fatty acid profiles of fifteen algal strains belonging to the genera Dolichospermum, Anabaena, Nostoc, Desmonostoc, Calothrix, Tolypothrix and identified the presence of C16:0, C16:1, C18:0, C18:1, C18:3 and C22:0, with C16:0 and C18:0 found in all isolates. Gayathri et al. (2018) found that, in five algal strains belonging to the genera Nostoc, Calothrix, and Scytonema, the fatty acid composition differed considerably except for C16:0, which was the dominant fatty acid in all five strains. Oliveira et al. (2018) reported that the fatty acids in Limnothrix sp. and Nostoc sp. in BG-11 and ASM-1 media were made up primarily of C14:0, C12:0, C16:0, and C18:1. In Khan et al. (2019), N. muscorum cultivated in wastewater was found to primarily contain C16:0 (43.13%), C18:2 (29.32%), C18:1 (22.67%), C18:3 (3.21%), and C18:0 (1.67%). These results demonstrate that the fatty acid profiles of filamentous cyanobacteria can vary with species or strains. Moreover, it is important to note that fatty acid profiles can also

3.3.4. Biodiesel properties of the algal lipids Table 5 presents the biodiesel properties of the lipids of three algal strains. When cultivated in BG110, the levels of SFAs, MUFAs, and PUFAs in strains B, J, and L were 23.76/20.64/26.58%, 22.36/34.83/ 32.19%, and 53.88/44.53/41.23%, respectively. The SFA content in strain L was significantly higher than that in J, while the MUFA levels in strains J and L were significantly higher than that of strain B. In addition, the order of PUFA content was B > J > L (P < 0.05). When cultivated in 10% BS, the levels of SFAs, MUFAs, and PUFAs in strains B, J, and L were 21.33/19.56/20.43%, 26.72/40.60/40.74%, and 51.95/39.84/38.84%, respectively (Table 5). The MUFA content in strains J and L was significantly higher than that of strain B, while PUFA levels in strain B were significantly higher than that of strains J and L. It is worth noting that the SFA content of strain B cultivated in 10% BS was lower than that in BG110, while the MUFA content of all three algal strains cultivated in 10% BS was higher than in BG110. In addition, the PUFA content of strains J and L cultivated in 10% BS was significantly lower than that in BG110. The UFA/SFA ratio for strains B, J, and L in BG110 was 0.86, 1.25, and 1.43, respectively; for 10% BS, it was 0.92, 1.51, and 1.57, respectively (Table 5). These variations in FAME composition influences the degree of unsaturation (DU), which in turn affects the fluidity in a cold environment (Song et al., 2013). The DU for strain B was significantly higher than that of strains J and L when cultivated in 10% BS, and was also was higher than when it was cultivated in BG110. The CN for strains J (43.10) and L (43.23) was significantly higher than that for strain B (37.39) in 10% BS, and that for strain J was higher than when it was cultivated in BG110. Although the CN of the algal samples in the present study did not meet the United States biodiesel standard ASTM D6751-02 (≥47) and the Europe Union biodiesel standard EN 14,214 (≥51), the CN for strains J and L was very close to the American standard. The low cetane number for all three strains in the present study is associated with the high PUFA content, especially for strain B (> 50%) in 10% BS. UFAs, especially PUFAs, have a lower melting point, which offers 6

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Table 5 Predicted biodiesel properties from FAME profiles of cyanobacteria and specifications in U.S. and European standards. EU standard SFA MUFA PUFA UFA/SFA DU CN ν ρ SV IV LCSF CFPP CP PP APE BAPE OS HHV

– ≥51 3.5–5.0 0.86–0.9 – ≤120 – ≤5/−20 – – – – ≥6 –

US standard

B

J

L

B-BS

J-BS

L-BS

– ≥47 1.9–6.0 0.86–0.9 – – – – – – – – ≥6 –

23.76 ± 0.52ab 22.36 ± 2.13b 53.88 ± 1.63a 0.86 130.13 ± 1.13a 37.53 ± 0.82c 3.20 ± 0.01b 0.885 ± 0.001a 208.26 ± 0.46b 155.47 ± 3.88a 3.29 ± 0.10a –6.14 ± 0.33a 6.22 ± 0.40b –0.07 ± 0.43b 110.28 ± 3.62a 92.56 ± 4.94a 4.78 ± 0.07c 39.16 ± 0.01a*

20.64 ± 3.15b 34.83 ± 2.51a 44.53 ± 0.65b* 1.25 123.89 ± 3.8b 40.54 ± 1.03b 3.28 ± 0.05a 0.883 ± 0.001b* 208.42 ± 0.42b 141.99 ± 4.36b* 3.48 ± 1.96a –5.54 ± 6.14a 4.61 ± 0.62c –1.82 ± 0.67c 98.40 ± 2.36b* 74.23 ± 1.51b* 5.24 ± 0.04b 39.19 ± 0.02a

26.58 ± 0.45a* 32.19 ± 0.47a 41.23 ± 0.89c* 1.43 114.65 ± 1.33c 43.88 ± 0.29a 3.33 ± 0.01a* 0.881 ± 0.000c 209.77 ± 0.38a 126.41 ± 1.48c 3.90 ± 0.32a* –4.21 ± 0.99a* 7.87 ± 0.32a* 1.72 ± 0.35a* 87.90 ± 2.57c* 62.98 ± 1.29c* 5.45 ± 0.06a 39.18 ± 0.01a*

21.33 ± 2.75A 26.72 ± 0.55B* 51.95 ± 2.35A 0.92 130.62 ± 5.08A 37.39 ± 1.47B 3.16 ± 0.04B 0.884 ± 0.001A 209.48 ± 0.07B* 155.40 ± 6.59A 2.49 ± 0.89A –8.65 ± 2.81A 5.76 ± 0.65A –0.57 ± 0.71A 103.90 ± 4.69A 89.37 ± 4.44A 4.86 ± 0.11B 39.13 ± 0.01B

19.56 ± 1.45A 40.60 ± 2.44A* 39.84 ± 0.99B 1.51 120.28 ± 0.47B 43.10 ± 0.18A* 3.32 ± 0.03A 0.881 ± 0.000B 209.36 ± 0.70B 130.10 ± 0.45B 3.34 ± 0.23A –6.00 ± 0.73A 3.48 ± 0.66B –3.04 ± 0.71B 88.00 ± 3.86B 59.54 ± 1.62B 5.55 ± 0.07A* 39.19 ± 0.02A

20.43 ± 1.95A 40.74 ± 1.99A* 38.84 ± 0.09B 1.57 118.41 ± 1.92B* 43.23 ± 0.46A 3.28 ± 0.02A 0.881 ± 0.000B 210.73 ± 0.25A* 128.76 ± 1.93B 2.82 ± 0.47A –7.63 ± 1.48A 3.88 ± 0.41B –2.61 ± 0.45B 82.76 ± 0.25B 58.56 ± 1.36B 5.63 ± 0.01A* 39.15 ± 0.01B

Note: EU standard: Europe Union biodiesel standard EN 14214, US standard: United States biodiesel standard ASTM D6751-02, SFA: saturated fatty acid (%), MUFA: monounsaturated fatty acid (%), PUFA: poly unsaturated fatty acid (%), UFA: unsaturated fatty acid (%); DU: degree of unsaturation; CN: cetane number, IV: iodine value, SV: saponification value (mg/g), LCSF: long-chain saturated factor, CFPP: cold filter plugging point (°C), CP: cloud point (°C), PP: pour point (°C), APE: allylic position equivalent, BAPE: bis-allylic position equivalent, OS: oxidation stability (h), υ: kinematic viscosity (mm2/s), ρ: density (g/cm3). Different lowercase letters in the same line indicated the significant difference between algal strains cultured with BG110, and the different capital letters in the same line indicated the significant difference between algal strains cultured with 10% BS. “*” indicated the significant differences (P < 0.05) for the same algae under different culture conditions; “–”, no standard reference values.

more desirable cold flow properties, but they also have a low CN and lower oxidative stability. In contrast, SFAs have a higher CN but worse cold flow properties, making them unsuitable for biodiesel at low temperatures (Ramírez-Verduzco et al., 2012). Therefore, an ideal biodiesel composition would be a balanced mix of saturated and unsaturated fatty acids with low levels of SFAs (to minimize cold flow issues), low levels of PUFAs (to minimize oxidative instability), and high levels of MUFAs (Hoekman et al., 2012). Therefore, the present study demonstrated that BS treatment improved the biodiesel characteristics of the three algal species. The density (ρ) and kinematic viscosity (ν) of the biodiesel derived from the three strains in both BG110 and 10% BS meets EU and US standards, with values that are similar to those reported by Anahas and Muralitharan (2015). The iodine value (IV) represents the susceptibility of fatty acids to oxidative attack and biodiesel lubricity (Anahas and Muralitharan, 2018). In all algal samples, the IVs ranged from 126.41 to 155.47, with those from strain J (130.10) and L (128.76) in 10% BS being very close to the EU standard (≤120). The saponification value (SV) ranged from 208.26 to 210.73 mg KOH g−1, which is in accordance with the results of Aboim et al. (2016), Anahas and Muralitharan (2018), and Gayathri et al. (2018). The cloud point (CP) and pour point (PP) are also important factors related to fuel quality in cold climates (Gayathri et al., 2018). In the present study, the CP and PP ranged from 3.48 °C to 7.87 °C, and –0.07 °C to 1.72 °C, respectively. The cold filter plugging point (CFPP) of the algae in the present study varied from −8.65 °C to −4.21 °C, which falls within the range of the results reported by Aboim et al. (2016) but is much lower than those reported by Anahas and Muralitharan (2018) and Gayathri et al. (2018). It was thus demonstrated that the cold flow properties of the biodiesel in the present study were reasonable because the CFPP represents the flow performance of biodiesel at low temperatures (Gayathri et al., 2018).

algal biomass. As shown in Table 6, on a base of VS, when cultivated in BG110, the BMPTh value of strain B was 176.69 ± 12.37 mL CH4 g−1 VS, which was higher than that of J (130.53 ± 12.79 mL CH4 g−1 VS) and L (116.61 ± 17.64 mL CH4 g−1 VS) significantly. When cultivated in 10% BS, there were no significant difference showed between the three algal strains. On a base of the volume of algal solution, when cultivated in BG110, the BMPTh value of strains B, J, and J were 166.32 ± 16.80, 184.42 ± 4.72, and 175.82 ± 11.39 mL CH4 g-1 VS) respectively, and there were no significant difference showed between the three algal strains. However, when cultivated in 10% BS, the BMPTh value of strain J was 3189.1 ± 112.3 mL CH4 L−1 algal solution, which was much higher than that of B (1032.4 ± 238.7 mL CH4 L−1 algal solution) and L (2223.6 ± 158.0 mL CH4 L−1 algal solution) significantly. The methane yield from microalgae can vary widely from 0.024 to 0.6 L CH4 g−1 VS depending on species and conditions according to the report from Roberts et al. (2016). There are some reports about the biomethane production of heterocystous cyanobacteria in normal cultural media. For instance, Chen et al. (2014) found that the biomass of Anabaena 7120 yielding 266.3 mL biogas g dry weight−1 (mainly methane). Mendez et al., (2015) addressed that the methane production were 223.1 ± 6.3 and 187.6 ± 20.3 mL g COD in−1 for A. ovalisporum and A. planctonica, respectively. And recently, a BMP value of 229 mL CH4 g−1 VS was recorded for A. variabilis (Perendeci et al., 2019). Moreover, there are also some reports about heterocystous cyanobacteria cultivated in wastewater. Mendez et al. (2016) found the methane yield were 194–218 and 181–261 mL g COD in−1 for A. ovalisporum and A. planctonica, respectively. Recently, Brar et al. (2019) found that the BMPTh value of A. ambigua NCIM2785 was 149.13 ± 6.67 mL CH4 g−1 VS when cultivated in BG110. However, it was 29.82 ± 3.62 mL CH4 g−1 VS when cultivated in the 3:1 dairy wastewater, which was much lower than the BMPTh values estimated in the present study. It demonstrates that algal strain J has high potential productivity of biomethane when cultivated in BS.

3.4. Theoretical biomethane potential (BMPth) 4. Conclusions The theoretical methane potential (BMPth) is widely used to predict the methane production of a specific organic substrate (Brar et al., 2019; Roberts et al., 2016). Table 6 presents the results of the ultimate analysis, biochemical composition analysis, and BMPTh calculation of

Three algal strains were selected from 36 filamentous heterocystous cyanobacteria strains based on their viability in BS, and their pollutant removal ability and biodiesel production were assessed. Strain J was 7

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Table 6 The ultimate analysis, biochemical composition analysis, and BMPTh calculation.

N (%) C (%) H (%) S (%) O (%) BMPTh (mL CH4 g−1 VS) BMPTh (mL CH4 L−1 algal solution) Total Kjeldahl nitrogen (%) Crude protein (%) Lipid (%) Total carbohydrate (%)

B

J

L

B-BS

J-BS

L-BS

8.45 ± 0.04A 42.84 ± 0.76A 7.38 ± 0.06A 0.16 ± 0.00B 41.17 ± 0.83B 176.69 ± 12.37A 2942.2 ± 343.0A 5.24 ± 0.19A 32.78 ± 1.16A 8.22 ± 0.66A 16.45 ± 0.81A

6.73 ± 0.05B 40.43 ± 0.97AB 7.18 ± 0.10A 0.16 ± 0.01B 45.51 ± 0.87A 130.53 ± 12.79B 2227.4 ± 204.8A 4.82 ± 0.04B 30.13 ± 0.23B 5.55 ± 1.70B 17.69 ± 0.63A

6.57 ± 0.06C 39.85 ± 1.16B 5.54 ± 0.10B 0.42 ± 0.01A 47.62 ± 1.27A 116.61 ± 17.64B 3007.1 ± 454.8A 3.05 ± 0.12C 19.09 ± 0.78C 6.51 ± 0.59AB* 18.62 ± 0.91A

7.77 ± 0.03b* 43.16 ± 1.22a 7.34 ± 0.06a 0.16 ± 0.00b 41.57 ± 1.21a 166.32 ± 16.80a 1032.4 ± 238.7c* 6.20 ± 0.09b* 38.75 ± 0.55b* 7.97 ± 0.88a 23.80 ± 0.81a*

8.77 ± 0.02a* 44.27 ± 0.27a* 7.48 ± 0.10a 0.21 ± 0.00a* 39.76 ± 1.19a* 184.42 ± 4.72a* 3189.1 ± 112.3a* 7.18 ± 0.25a* 44.86 ± 1.55a* 4.91 ± 0.84b 17.26 ± 2.95b

7.59 ± 0.04c* 43.74 ± 0.90a* 7.34 ± 0.14a* 0.23 ± 0.01a* 41.10 ± 0.79a* 175.82 ± 11.39a* 2223.6 ± 158.0b* 4.37 ± 0.16c* 27.34 ± 1.00c* 4.82 ± 0.54b 21.13 ± 1.57ab

able to remove N and P from the BS and demonstrated the highest biomass productivity and lipid productivity. In addition, the estimation of BMPth suggested that the algal strain J also have the desirable possibility of biogas generation. This is the first report on the bioenergy production from biomass of filamentous heterocystous cyanobacteria grown in pig farm BS. In summary, algal strain J (Nostoc sp.) offers great potential for the removal of BS pollutants and for the production of bioenergy (lipid and biogas productivity).

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CRediT authorship contribution statement Yuzhen Lu: Investigation, Validation, Writing - original draft. Chen Zhuo: Investigation, Validation. Yongjun Li: Data curation, Resources. Huashou Li: Conceptualization, Writing - review & editing. Mengying Yang: Investigation. Danni Xu: Investigation. Hongzhi He: Supervision, Conceptualization, Validation. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This work was supported by the Science and Technology Planning Project of Guangdong Province, China (2016A030303050 and 2019B030301007). References Aboim, J.B., Oliveira, D., Ferreira, J.E., Siqueira, A.S., Dall'Agnol, L.T., Filho, G.N.R., Gonçalves, E.C., Nascimento, L.A., 2016. Determination of biodiesel properties based on a fatty acid profile of eight Amazon cyanobacterial strains grown in two different culture media. RSC Adv. 6, 109751–109758. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J., 1990. Basic local alignment search tool. J. Mol. Biol. 215, 403–410. Amit, Ghosh, U.K., 2018. An approach for phycoremediation of different wastewaters and biodiesel production using microalgae. Environ. Sci. Pollut. R. 25, 18673–18681. Anahas, A.M.P., Muralitharan, G., 2015. Isolation and screening of heterocystous cyanobacterial strains for biodiesel production by evaluating the fuel properties from fatty acid methyl ester (FAME) profiles. Bioresour. Technol. 184, 9–17. Anahas, A.M.P., Muralitharan, G., 2018. Characterization of heterocystous cyanobacterial strains for biodiesel production based on fatty acid content analysis and hydrocarbon production. Energ. Convers. Manage. 157, 423–437. APHA, 2005. Standard Methods for the Examination of Water and Wastewater, 21st ed. American Public Health Association, American Water Works Association, Water Environment Federation. Becker, E.W., 1994. Microalgae: Biotechnology and Microbiology. The Press Syndicate of the. University of Cambridge. Brar, A., Kumar, M., Pareek, N., 2019. Comparative appraisal of biomass production, remediation, and bioenergy generation potential of microalgae in dairy wastewater. Front. Microbiol. 10, 678. https://doi.org/10.3389/fmicb.2019.00678. Chen, R., Li, R., Deitz, L., Liu, Y., Stevenson, R.J., Liao, W., 2012. Freshwater algal cultivation with animal waste for nutrient removal and biomass production. Biomass Bioenerg. 39, 128–138. Chen, M., Li, J., Zhang, L., Chang, S., Liu, C., Wang, J., Li, S., 2014. Auto-flotation of

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