Bio-methane production variation under different draw solute reverse diffusions in an anaerobic digester simulated for FO-AnMBR

Transcription

1 Bio-methane production variation under different draw solute reverse diffusions in an anaerobic digester simulated for FO-AnMBR Sheng Li 1, Youngjin Kim 2,3, Sherub Phuntsho 2, Ho Kyong Shon 2, TorOve Leiknes 1, Noreddine Ghaffour 1* 1 King Abdullah University of Science and Technology (KAUST), Water Desalination and Reuse Center (WDRC), Biological and Environmental Sciences & Engineering Division (BESE), Thuwal, , Saudi Arabia 2 School of Civil and Environmental Engineering, University of Technology, Sydney (UTS), Post Box 129, Broadway, NSW 2007, Australia 3 School of Civil, Environmental and Architectural Engineering, Korea University, 1-5 Ga, Anam-Dong, Seongbuk-Gu, Seoul, , Republic of Korea Abstract This study was conducted to investigate the relationship among the reverse diffusion of fertilizer draw solute, bacteria community and bio-methane production rate in the FDFO- AnMBR system. Three fertilizers were evaluated in this study, namely KCl, KNO3 and KH2PO4. Results showed that bio-methane production decreased with the increase in reverse fertilizer diffusion. The pyrosequencing results revealed that bacteria communities of different fertilizers were clearly different from each other. The bacteria community of sludge with KH2PO4 added was very similar to the blank control. The sludge with KCl exhibited a higher similarity to the sludge with KH2PO4 than KNO3. Moreover, the nitrogen gas production species (Proteobacteria: Comamonas) was found to have a higher abundance (1.2) in sludge with KNO3 than the sludge with other fertilizers (0). This study demonstrated that the fertilizer reverse diffusion has a negative effect on the bio-methane production, probably by influencing the sludge bacteria community via environment modification. Keywords: Fertilizer, FO, AnMBR, methane, pyrosequencing 1

2 1 Introduction Water scarcity and environmental pollution have driven the development of water reuse in the urban water management [1]. In the past two decades, forward osmosis (FO) has received attention in the wastewater treatment filed due to its low energy consumption, and relatively less fouling than other membrane processes. FO is a membrane separation process driven by the osmotic pressure difference between feed solution and draw solution [2]. Since this process is not driven by the external pressure, the energy consumption is much lower than the reverse osmosis technology. It has been reported that the fouling of FO membranes is also less sever than RO, and mostly reversible via hydraulic cleaning [3]. However, FO is not one-step purification process, because the water extracted from the feed solution into the draw solution that is normally inorganic salts, and the pure water needs to be recovered from the diluted draw solution. The recovery process will still consume energy. Lately, fertilizer-drawn forward osmosis (FDFO) has received increased interest since the diluted draw solution can be used directly for irrigation purposes and therefore no recovery process is required [4, 5]. In FDFO, the FO process was driven by fertilizers (draw solution) and thus the water drawn from the wastewater (FO feed) is used to dilute the fertilizer solution which can then be directly used for fertigation. By combining FDFO and AnMBR, users can have multiple benefits, namely bio-methane production, higher effluent quality than ultrafiltration based AnMBR systems and direct fertigation. Different fertilizers have been compared in terms of water flux, bio-methane production rate and reverse diffusion. However, it is still not clear why different fertilizers exhibited different bio-methane production rates. It could be related to the bacteria community variation caused by different reverse diffusion rates of different fertilizers, but there is no substantial proof to support this hypothesis. 2

3 Therefore, this study investigated the impact of gradual reverse fertilizer diffusion on the methane production in a hybrid FDFO-AnMBR system by dosing three different fertilizers, which amount was pre-determined via FO experiments, into parallel anaerobic fermentation bottles step by step. The methane production was monitored for all conditions to check the effects of fertilizer dosage, and the corresponding sludges under different conditions were also collected and analyzed via pyrosequencing to illustrate the bacteria community difference of different conditions and its relation with the methane production difference. 2 Materials and Methods 2.1 Anaerobic sludge Anaerobic sludge collected from one digester of a wastewater treatment plant was used as the seed sludge in this study. The characteristics of anaerobic sludge are: 3.05% total solids; mg/l MLSS; ph 7.2 and 1,850 mg/l COD. 2.2 Model substrates and reversed draw solutes To maintain the bioactivity of the BMP apparatus, glucose were dosed in the bottles every two days as substrate for the anaerobic fermentation. The amount of glucose dosed every two days in this study was based on the synthetic wastewater recipe used in our previous study [6] assuming 1 L wastewater treated per day. Three fertilizers, namely KCl, KNO3 and KH2PO4 were used as model draw solutes of FDFO process for this study. The amount of dosed fertilizer per day was based on the predetermined reverse salt flux (KH2PO4 showed the lowest reverse diffusion of 0.8 mmol, while KCl and KNO3 were 4.9 and 19.6 mmol, respectively), membrane area of 20 cm 2 and a 24-hour operation. 3

4 2.3 Bio-methane potential (BMP) apparatus Because the bacteria community could change over time, in order to investigate the effect of reverse salt flux (RSF) on the performance of a hybrid system incorporated with anaerobic membrane bioreactor (AnMBR) and fertilizer drawn forward osmosis (FDFO) under identical initial conditions, the bio-methane potential experiments were conducted in a batch mode for different substrates addition[7] using a BMP apparatus (depicted in Figure S2). The BMP apparatus is composed of 7 fermentation bottles submerged in a water bath at a temperature of 35 ± 1 C. The generated biogas from these bottles was connected to an array of inverted 1000 ml plastic mass cylinders submerged in the 1 M NaOH solution to collect and measure the biogas. The NaOH solution plays an important role to remove CO2 and H2S from biogas to better evaluate CH4 production potential. Air volume in each mass cylinder was recorded 2 times per a day. Detailed description of BMP apparatus used in this study is given elsewhere [7]. Figure 1. Schematic diagram of bio-methane potential apparatus. 2.4 Experimental protocol First of all, the quality of anaerobic sludge was characterized and described in Section 2.1. The RSFs of FDFO process was determined for three different fertilizers and then the corresponding amount of each fertilizer was added into the BMP apparatus together with 4

5 glucose for the bacteria growth in anaerobic sludge fermentation. One fermentation bottle was filled with DI water as blank control, while the rest six bottles were filled with fertilizers (each fertilizer was duplicate). After mixing the anaerobic sludge with the substrates and fertilizers, all bottles were purged with nitrogen gas. The dissolved oxygen in fermentation bottles was measured after nitrogen gas purging to ensure the value was lower than 0.5. The fermentation bottles were then submerged in a water bath of 35 C and connected to the biogas collecting cylinder described in Section 2.3. During fermentation, glucose was added into the anaerobic sludge every two days as indicated in Section 2.2. On the other hand, the corresponding amounts of different reverse diffused fertilizers were dosed every three days to simulate the gradual accumulation in an AnMBR system. The produced bio-gas volume was continuously recorded, and the methane, nitrogen concentration within the collected biogas was determined after the experiment. Moreover, the corresponding anaerobic sludge under different fertilizer addition was collected for bacteria composition investigation via pyrosequencing. 2.5 Bio-methane determination The biogas in each cylinder was collected by a 1-liter gas-sampling bag. After the collection, the volumes of bio-methane, nitrogen and carbon dioxide were determined by a portable methane detection apparatus (Multitec 560, Orangeth). The specific biogas volume was calculated based on the Eq.1. VV ss = CC mm VV bb Where Vs is the produced specific biogas volume, Cm is the measured percentage of specific biogas and Vb is the recorded volume of biogas mixture. 2.6 DNA extraction and pyrosequencing The sludge samples collected from columns of the BMP apparatus were stored under -20 C 5

6 before shipping to DNASense Apps Company in Denmark for 454 pyro-sequencing. During the shipment, sludge samples were kept in the dry ice at a temperature of -20 C. The DNA of all bacteria in sludge samples were extracted through the FastDNA Spin kit for soil (MP Biomedicals, USA), using 4x the normal bead beating to enable recovery of bacteria that are difficult to lyse [8]. V1-3 primer containing 27F AGAGTTTGATCCTGGCTCAG and 534R ATTACCGCGGCTGCTGG was used. PCR was run with following programs: 1) initial denaturation at 95 C for 2 min, 30 cycles of amplication (95 C for 20 s, 56 C for 30 s, 72 C 60s) and a final elongation at 72 C for 5 min. Forward and reverse reads for both bacteria were trimmed for quality using Trimmomatic v [9] with the settings SLIDINGWINDOW:5:3 and MINLEN:275. Because the V3-5 region for archaea is longer than what is possible to merge, only the first 275 bp of read 1 was used for further analysis. Bacteria reads were dereplicated and formatted for use in UPARSE workflow [10]. The dereplicated reads were clustered, using the usearch v cluster_otus command with default settings. OTU abundences were estimated using the usearch v usearch_global command with id Taxnomy was assigned using the RDP classifer [11] as implemented in the parallel_assign_taxonomy_rdp.py script in QIIME [12], using the MiDAS database v.1.20 [13]. The results were analyzed in R [14] through the Rstudio IDE using the ampvis package v [8]. 3 Results and discussion 3.1 Methane production in anaerobic fermenters Figure 1 shows the methane and nitrogen gas volume produced during the anaerobic 6

7 fermentation. Around 272 ml produced biogas was methane when there was no fertilizer in the sludge (DI), while the methane volume within biogas for sludges with fertilizers varied depends on the type of fertilizer used but all lower than the DI condition. KH2PO4 dosage exhibited the closest methane volume as DI condition (238 ml), followed by 170 ml of KCl dosage and less than 65 ml of KNO3 dosage. Interestingly, the sludge with KNO3 exhibited a high nitrogen gas concentration (1166 ml), much more than the other conditions which were between 820 and 990 ml. The nitrogen gas concentration displayed an opposite trend as the methane concentration for sludge with different fertilizers. The dosage of fertilizer simulated the reverse fertilizer diffusion of FDFO-AnMBR. Since the dosages of fertilizers were based on simulated FDFO processes, the impact of fertilizer reverse diffusion in the anaerobic bio-methane production can thus be demonstrated. Fertilizers effect on changing the biogas production rate and composition could be due to the variation of bacteria community in the sludge with different fertilizer dosage. 7

8 N2 CH4 250 Nitrogen in produced biogas (ml) Methane in produced biogas (ml) 0 DI KCl KNO3 KH2PO4 Reverse diffused fertilizers 0 Figure 1: The nitrogen (N2) and methane (CH4) gas percentages in the produced biogas for anaerobic fermenters with different reverse diffused fertilizers. 3.2 Bacteria structure affected by the fertilizers 40 bacteria species were detected to have more than 0.1% relative abundance in all samples (Figure 2). 8 of these 40 bacteria species exhibited different abundances at different fertilizer conditions (Figure 3). Within these 8 species, Trichococcus [15, 16], Proteiniphilum [17], f_009e01-b-sd-p15_otu_19, Syntrophorhadus [18], f_spirochaetaceae_otu_58 are acetogensis bacteria, capable of biodegrading organics into acetate. Sludge without fertilizer (the DI condition) showed similar abundances on all species to sludge with KH2PO4, confirming the similar bacteria composition of these two conditions. It indicated that the similar methane production for these two conditions was 8

9 likely because the simulated KH2PO4 reverse diffusion did not caused significant changes on the sludge microbial composition. Since the reverse diffusion of KH2PO4 was the lowest one among the three tested fertilizers, it indicated the reduction of methane production in FO-AnMBR could be minimized by limiting the reverse draw solute reverse diffusion. Regarding the sludge with KCl addition, the abundance percentages of most species were similar to the DI condition, except for the Enterococcus and Trichococcus. Enterococcus is a Lactic acid production bacteria [19]. The Enterococcus was higher in KCl condition than DI and KH2PO4, which could produce more lactic acid instead of acetate, which might not suitable for the consumption of Methanogens. Moreover, the lower abundance of Trichococcus in KCl and KNO3 conditions could lead to an even lower acetate production in digester and thus a lower methane production, and this has been confirmed by the methane production shown in Figure 1. Sludge with KNO3 exhibited the lowest methane production, and interestingly, besides the lower abundance of Trichococcus, the abundances of all other acetogenesis bacteria in this condition were lower than other three conditions. On another hand, three species in sludge with KNO3 exhibited higher abundance percentages than other conditions, which include Enterococcus, vadinbc27 wastewater-sludge group and Comamonas. As mentioned above, Enterococcus produce lactic acid not acetate during anaerobic digestion and might lead to the lower methane production. Comamonas is an anoxic denitrifier [20], so it could utilize the nitrate in sludge as electron accepter and produced nitrogen gas, and consequently out compete other acetogenesis bacteria and indirectly reduce the methane production. This can be confirmed by the higher detected nitrogen gas production in sludge with KNO3 addition. There is another possibility that the nitrate is toxic for the acetogensis bacteria and led to the reduced 9

10 abundances. Figure 2: 40 most abundant bacteria species at different draw solute reverse diffusion conditions. (Values are average of duplicates for sludge samples with fertilizer dosage) Figure 3: 8 abundant bacteria species showing different abundances at different draw solute reverse diffusion conditions. (Values are average of duplicates for sludge samples with fertilizer dosage) 10

11 4 Conclusions This study investigated the impact of gradual fertilizer reverse diffusion on the biomethane production of a hybrid FDFO-AnMBR system by simulating the anaerobic fermentation in parallel bottles with different experimentally determined fertilizer dosages. In contrast of previous reports with one time high dosage, different inorganic fertilizer with gradual dosage exhibited different extent of negative impact on the biomethane production, probably due to the gradual increase of reverse draw solute give time to microbe community to adjust themselves to the new environment. The reverse draw solute diffusion exhibited a significant effect on the variation of bacteria community in the anaerobic system. The lower reverse diffusion is, the higher methane can be produced. The low methane production after addition of KNO3 increased the abundance of denitrification bacteria through the elevated nitrate concentration and outcompeted the methanogens. This study demonstrated the relationship between the fertilizer reverse diffusion, methane production and bacterial communities in the hybrid FDFO-AnMBR system. Acknowledgements The research reported in this paper was supported from the SEED program of King Abdullah University of Science and Technology (KAUST), Saudi Arabia, ARC Future Fellowship (FT ) and University of Technology Sydney chancellor s postdoctoral research fellowship. The help, assistance and support of the Water Desalination and Reuse Center (WDRC) staff are greatly appreciated. References 11

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