Application of a CO2-stripping system for calcium removal to upgrade organic matter removal and sludge granulation in a leachate-fed EGSB bioreactor

Xueqin Luab, Shanping Chenc, Jinghuan Luoa, Guangren Qian*a, Jianyong Liu*a, Guangyin Zhend and Yu-You Libe
aSchool of Environmental and Chemical Engineering, Shanghai University, Shanghai 2004444, PR China. E-mail: liujianyong@shu.edu.cn; grqian@shu.edu.cn; Fax: +86 21 66137761; Tel: +86 21 66137769 Tel: +86 21 66137758
bDepartment of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Aoba 6-6-06, Aramakizi, Aoba-ku, Sendai, 980-8579, Japan
cShanghai Environment Engineering Design Institute Co., Ltd., Shanghai 200232, P. R. China
dCenter for Material Cycles and Waste Management Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
eDepartment of Frontier Science for Advanced Environment, Graduate School of, Environmental Studies, Tohoku University, Aoba 6-6-20, Aramakizi, Aoba-ku, Sendai, 980-8579, Japan

Received 11th December 2015 , Accepted 13th January 2016

First published on 15th January 2016


Abstract

The application of CO2-stripping system for calcium removal to upgrade organic matter removal and sludge granulation in a leachate-fed EGSB bioreactor was evaluated. Three-dimensional excitation–emission matrix (3D-EEM) spectroscopy combined with parallel factor (PARAFAC) analysis was used to characterize the transformation of the effluent dissolved organic matter (DOM) during the operation. X-ray diffraction (XRD), Fourier-transform infrared (FT-IR) and scanning electronic microscopy (SEM) were used to assess the effects of a CO2-stripping unit on the microstructure of the granules. The introduction of the CO2-stripping system reduced the calcium concentration while upgrading methane evolution. The methane yield reached 0.33 L CH4 per g CODremoved in the bioreactor with the CO2-stripping unit compared with 0.31 L CH4 per g CODremoved without the unit as the control. The combined system produced 80% and 50–60% chemical oxygen demand (COD) and total nitrogen (TN) removal under steady-state conditions, which were 6.3% and 41.0% higher than those of the control, respectively. With 3D-EEM-PARAFAC analysis, three fluorescence components, associated as tryptophan protein-like (component 1, Ex/Em = 275–280/355–365 nm) and humic-like substances (component 2, Ex/Em = 240(295, 340)/450 nm and component 3, Ex/Em = 320/320 nm), were identified from the effluent samples. The componential characterizations confirmed the favorable influence of the CO2-stripping unit on the transformation of DOM. Further analysis through XRD, FT-IR and SEM demonstrated that the use of the unit alleviated inactivation of the granules through removing calcium, which might be the core reason for the enhancement of the EGSB performance.


1. Introduction

Expanded granular sludge bed (EGSB) bioreactors, modified from up-flow anaerobic sludge blanket (UASB) reactors, have attracted much attention due to their low energy consumption, high treatment efficiency, low sludge production and renewable energy recovery in the form of methane.1,2 In recent years, they has been universally used for treating various kinds of wastewater such as brewery wastewater, starch wastewater, molasses alcohol slops, slaughterhouse wastewater, and municipal solid waste (MSW) leachate.3,4 Several parameters affect the long-term performance of EGSB bioreactors such as the physiochemical properties of anaerobic granules, organic loading rates (OLR), pH, hydraulic retention time (HRT), temperature and superficial velocity.5–7 Anaerobic granules, which are regarded as the principle component of EGSB bioreactors, play a relatively critical role in the biological treatment process. Anaerobic granules support active biofilms but also provide the buoyancy and the settle ability necessary to enable very vigorous granule–liquid contact in the reactor.8

Many factors contribute to the sludge granulation process. One of the crucial elements is the calcium ion (Ca2+), which is found to exert a key role in the granulation process by neutralizing granules surface charges and/or binding extracellular polymeric substances (EPS).9–11 However, insufficient or excessive calcium is often detrimental to granule formation. An insufficient supply of calcium would inhibit microbial activity in denitrifying granules, and weaken the three-dimensional structure of EPS–Ca2+–EPS and the microbial community of bio-granules.11 An excessive dosage on the contrary seems to cause clogging in the bioreactor,12 which substantially deteriorates the EGSB performance. Unstable COD removal efficiency and cementation of the sludge bed in a UASB reactor was observed by van Langerak et al.13 when they treated acidified wastewater with a calcium concentration of 1200 mg L−1. Another study by Pevere et al.14 also found that calcium concentrations of 780–1560 mg L−1 in the wastewater induced CaCO3 precipitate formation, which led to scaling of granular sludge and decreased the diffusivity. Therefore, it is necessary to remove calcium from calcium-rich leachate to achieve successful performance of EGSB bioreactors. An alternative to alleviate calcium-related problems can be the carbonation pretreatment of wastewater through CO2 stripping. Jo et al.15 also used CO2 to remove Ca2+ ions from coal fly ash through a carbonation reaction of CO2 with Ca2+ ions. Nir et al.16 utilized CO2 in a seawater reverse osmosis membrane to minimize calcium carbonation to prevent fouling the membrane. Likewise, Kim et al.17 adopted biologically produced alkalinity in a UASB bioreactor to minimize the adverse effect of calcium hardness from industrial wastewaters with a respective process, and got a stable COD removal efficiency of over 90% after some calcium was removed. In our previous work,18 a scientific attempt on recirculating biogas (CO2) from a leachate-fed EGSB bioreactor for the removal of calcium and simultaneous methane purification was also carried out; by optimizing the solution pH and imported biogas (CO2), the calcium level suitable for microbial growth as well as and organic matter removal was achieved, which, as stated before, improved the sludge granulation and methane evolution to a large degree. However, the previous study mainly focused on the optimization of operational parameters (e.g. solution pH, imported biogas (CO2), etc.) as well as the exploration of calcium precipitation mechanisms. More work in investigating the functions of biogas recirculation on improving the organic matter degradation and the micro-characteristics of granules are still required. Moreover, as the core component of the EGSB system, the characteristics of granular sludge affect, or even decide the overall performance of the process. Thus, characterizing the microstructure of granules would help to further investigate the stimulating effect of biogas recirculation on the overall EGSB performance.

Based on the above-mentioned considerations, a CO2-stripping unit, used as a pretreatment of fresh leachate with a high calcium concentration to eliminate the inhibitory effect of calcium ions, was conducted in an EGSB bioreactor in this study. Effects of biogas recirculation on calcium removal, methane production, COD, TN, and NH4+–N were investigated and are discussed. Three-dimensional excitation–emission matrix (3D-EEM) spectroscopy was used to characterize the transformation of the effluent dissolved organic matter (DOM) during the operational period. Parallel factor (PARAFAC) analysis was employed to quantitatively analyze the 3D-EEM spectra and to identify the configuration and heterogeneity of the DOM fractions. In addition, X-ray diffraction (XRD), Fourier-transform infrared (FT-IR) and scanning electronic microscopy (SEM) were further performed to assess the possible effects of the CO2-stripping unit on the properties and microstructure of granular sludge. This study would provide an in-depth and comprehensive insight into the biogas recirculation process (i.e. CO2-stripping unit) while simultaneously advancing its practical applications in EGSB bioreactors as well as other kinds of bioreactor systems.

2. Materials and methods

2.1. Fresh leachate

The fresh leachate used as the feed in this study was obtained from Pudong Compost Factory in Shanghai, China. This factory has a daily handling capacity of 1300 tons of municipal solid waste (MSW), which generates about 100 tons of fresh leachate per day. The fundamental characteristics of the fresh leachate are shown in Table 1.
Table 1 Fundamental characteristics of the fresh leachate from the Shanghai Pudong Compost Factory (unit: mg L−1, except for pH)
Item Value Item Value
CODCr 37[thin space (1/6-em)]156–73[thin space (1/6-em)]865 Mg 351–387
BOD5 23[thin space (1/6-em)]351–32[thin space (1/6-em)]107 Fe 148–180
TOC 16[thin space (1/6-em)]133–24[thin space (1/6-em)]773 K 116–123
NH+4–N 789–1332 Al 44.89–75.58
TN 1599–2507 Zn 14.18–26.35
TP 102–278 Li 0.33–0.38
pH 3.76–4.89 Sr 7.41–8.71
Ca 5073–5529 B 7.71–27.77


2.2. Source of seed sludge

The seed sludge was taken from a full-scale internal circulation bioreactor in a paper mill in Shanghai, China. The anaerobic granular sludge, consisting of well-settled black granules with about 95% showing sizes from 0.5 to 2 mm in diameter, had a mixed liquor volatile suspended solid (MLVSS) concentration of 75[thin space (1/6-em)]972 mg L−1 and a mixed liquor suspended solid (MLSS) concentration of 103[thin space (1/6-em)]291 mg L−1.

2.3. Experimental set-up and its operation

The continuous biodegradation of fresh leachate was carried out in parallel in two lab-scale EGSB bioreactors A and B. The detailed schematic diagram of both reactors was shown in our previous research.18 The reactors had a working effective volume of 6 L with an inside diameter of 8 cm and a height of 120 cm, and the granular sludge occupied 1/3 of the working volume of the EGSB bioreactor. A gas–liquid–solids separator was installed at the top of the reactors. Reactor B had a CO2-stripping unit (φ 14 cm × 14 cm) with a working volume of 2 L. The biogas produced from the reactor was re-circulated to the CO2-stripping unit without any external force, and then the biogas from the CO2-stripping unit was collected by a gas sampling bag. The pH value in the carbonation unit was adjusted to 10.0 ± 0.5 through feeding a 2.0 N NaOH solution. In order to ensure sufficient mass transfer between the biogas and leachate as well as uniformity of the solution pH, the CO2-stripping unit was constantly agitated by a magnetic stirrer during the carbonation process. Afterwards, the leachate from CO2-stripping unit was used as the feed of the reactor. The temperature in the reactor was controlled with water recirculation using a heated water bath. The operational temperature was kept constant at 35 ± 1 °C and the liquid up-flow velocity (Vup) was maintained at 3.2 m h−1 based on the results of our previous research.4 Two pumps were used to feed the influent and circulate the effluent. Reactor A without a CO2-stripping unit operated under the same conditions and was also used as a control. The organic loading rate (OLR) for both reactors was set at 10–20 kg COD per m3 per d with a hydraulic retention time (HRT) of 72 h under steady-state conditions.

2.4. 3D-EEM fluorescence analysis

The leachate samples collected during the operation period were filtered through a 0.45 μm membrane and diluted by 100 times. 3D-EEM fluorescence spectra were measured using a luminescence spectrometer (FluoroMax-4, HORIBA Jobin Yvon Co., France).19 Leachate EEM spectra were recorded with scanning emission (Em) spectra from 250 to 550 nm at 5 nm increments through varying the excitation (Ex) wavelength from 215 to 400 nm at 5 nm increments. Excitation and emission slits were both maintained at 5 nm, and the scanning speed was set at 4800 nm min−1 for all the measurements. The software Origin 8.0 (Origin Lab Inc., USA) was used for handling the EEM data.

Parallel factor (PARAFAC) analysis was employed to quantitatively analyze the 3D-EEM spectra. The detailed approach of PARAFAC analysis can be found elsewhere.20,21 PARAFAC is a generalization of bilinear principal component analysis (PCA) to higher order arrays. It can decompose the three-way array X of fluorescence EEM into three matrices, A (the score matrix), B and C (loading matrices) with the elements aif, bjf and ckf using:

image file: c5ra26444h-t1.tif
where, χijk is the fluorescence intensity of the sample i at the emission wavelength j and excitation wavelength k; F is the number of components in the model; aif is directly proportional to the concentration of the fluorophore f in the sample i (defined as scores); bjf and ckf are estimates of the emission and excitation spectra for the fluorophore component f (defined as loadings), respectively. εijk is the residual term representing the invariability not accounted for by the model. PARAFAC analysis was carried out in Matlab 10.0 with the DOMFluor toolbox. The variance identified by the model, and the core consistency diagnostic as well as split-half analysis were used to find the suitable number of components. The relative concentration of fluorophore was estimated using the maximum fluorescence intensity (Fmax) values (R.U., i.e. Raman units).

2.5. Characterization of clogging materials and sludge granules

The clogging materials from the carbonation unit and sludge granules from both reactors were characterized by means of X-ray diffraction (XRD). The XRD patterns were collected over a 2θ from 5–90° in a scan step of 0.02° and measuring time of 0.1 s per step using graphite monochromated CuKα radiation (D8, Bruker AXS Inc., Germany). The accelerating voltage was 40 kV and the current was 40 mA. The diffractograms were attained with Diff-plus and analyzed using MDI Jade 5.0 software. The functional groups were analyzed using an ALPHA FT-IR spectrometer (Bruker Optics, Germany) in the range of 4000–400 cm−1. For scanning electron microscopy (SEM) analysis,22 the samples were fixed for 2 h at 4 °C with 2.5% (v/v) glutaraldehyde in 0.1 M phosphate buffer (pH 6.8). After being washed three times with phosphate buffer solution, the samples were dehydrated via successive passages through 50%, 60%, 70%, 80% and 90% (v/v) ethanol followed by freeze drying, then sputter-coated with a thin layer of gold for SEM analysis (Hitachi S-520, Japan).

2.6. Other analytical methods

The chemical oxygen demand (COD), biological oxygen demand (BOD5), total phosphorus (TP), NH+4–N, pH, mixed liquor volatile suspended solids (MLVSS) and mixed liquor suspended solids (MLSS) were estimated following standard methods.23 Total nitrogen (TN) and total organic carbon (TOC) were measured with a TOC-VCPN analyzer (SHIMADZU, Japan) using the combustion-infrared method. Metal concentrations were analyzed with ICP-AES (Optima 2100 DVICP-AES, PerkinElmer, USA). Biogas volume was recorded using a gas sampling bag connected to a gas meter, and the gas composition (CH4 and CO2) of the biogas was analyzed through gas chromatography (GC9800) with a stainless steel column (1 m × 3 mm) packed with TD-01 for the separation of CH4 and CO2 using a thermal conductivity detector (TCD) at room temperature.

3. Results and discussion

3.1. Methane production and purification

Calcium plays an important role in the EGSB reactor, and the presence of high calcium content in the leachate could damage the environment required for maintenance of the granular structure or the bacterial activity.24 A CO2-stripping unit with biogas recirculation as a pretreatment effectively enhanced the removal of calcium from the leachate, with the resulting removal efficiency being up to 92.8–96.5%.18 The noticeable decrease of calcium during the carbonation process resulted from its precipitation in the form of calcium carbonate in the presence of CO2 from the biogas. In this sense, the methane content from reactor A varied between 41.5–57.9%. In comparison, it dramatically increased to around 87–91% when the CO2-stripping unit was utilized,18 which is profoundly higher than the values (65–80%) reported by Ye et al.25 The higher methane content in the biogas achieved from bioreactor B evidently indicate that most of the CO2 was dissolved and consumed by generating CaCO3 precipitates in the carbonation unit. A higher methane content would make the biogas easier to be utilized as an energy source. Detailed mechanisms for calcium precipitation were described in our previous publication.18

The production of methane during anaerobic digestion is strongly correlated with CODremoved.26 The average methane yield was determined to be 0.31 L CH4 per g CODremoved from reactor A, suggesting that approximately 88.6% of the removed COD was converted to methane and the remaining COD (11.4%) might be regarded as synthesis of biomass25,26 as the theoretical methane production rate is 0.35 L CH4 per g CODremoved.27 Comparatively, the methane yield amounted to 0.33 L CH4 per g CODremoved from reactor B, indicating that 94.3% of the removed COD was converted to methane whereas the remaining 5.7% was presumably changed into the form of biomass. The higher methane production rate in reactor B is presumably due to less inhibition from calcium. Mineral encrustation as inert suspended solids (ISS) easily accumulates onto the granules, which may exclude the active anaerobic methanogenic microorganisms by occupying the space of the granule, resulting in weakened activity of the biomass.28,29 The presence of the CO2-stripping unit efficiently reduced the calcium content in the fresh leachate and hampered its adverse interference, which accordingly enhanced methanogenic activity and the subsequent digestion processes. The abovementioned experimental results once again confirmed the beneficial influence of the application of a CO2-stripping unit as an effective alternative to reinforce calcium removal and to improve the overall performance of an EGSB.

3.2. COD, TN and NH+4–N removal

To examine the effect of carbonation pretreatment on the overall treatment performance of an EGSB bioreactor, the process parameters in terms of COD, TN and NH+4–N removal were measured once steady-state conditions were achieved. The variation profiles of COD, TN, and NH+4–N concentrations in the influent and effluent and the corresponding removal efficiencies from bioreactors A and B are given in Fig. 1. In reactor A (Fig. 1a), the effluent COD concentrations ranged from 5226 to 16[thin space (1/6-em)]682 mg L−1 at influent concentrations of 39[thin space (1/6-em)]581–73[thin space (1/6-em)]865 mg L−1. The highest COD removal efficiency of 85–86% was observed during the first 3 days. With the progress of the experiment, the COD removal efficiency decreased stepwise and maintained at a relatively low and stable level of around 75%. This level of COD removal was similar to the previously reported removal of roughly 60–80% for an EGSB bioreactor.30 The considerable decrease in COD removal efficiency after 4 days of operation was presumably ascribed to the methanogenesis inhibition from high concentrations of calcium in the fresh leachate. Severe calcium precipitation and accumulation on the surface of sludge granules, as hypothesized by Ye et al.,25 lowered the mass transfer rate and decreased the specific methanogenesis activity of the granules, thereby greatly deteriorating the performance of the EGSB. Similar trends were also reported in a UASB treating paper water17 and an EGSB treating the fresh leachate.4,18
image file: c5ra26444h-f1.tif
Fig. 1 Performance of the EGSB bioreactors A and B: the concentrations and the removal efficiencies of (a) COD, (b) TN and (c) NH+4–N.

In comparison with reactor A, reactor B with a CO2-stripping unit always achieved higher COD removal efficiencies. As presented in Fig. 1a, the COD removal efficiency rapidly increased to more than 85% after 5 days of operation at influent COD concentrations of 37[thin space (1/6-em)]156–72[thin space (1/6-em)]834 mg L−1. Even though a slight reduction was observed after 8 days of operation, the COD removal still approached up to 80% with the effluent COD concentration of below 15[thin space (1/6-em)]000 mg L−1, 6.3% higher in contrast to reactor A. Similar results were reported by Kim et al.17 It is obvious that a higher COD removal efficiency can be achieved when biogas recirculation as a pretreatment is employed in an EGSB bioreactor.

Similar to the results of COD removal, the TN (NH+4–N, NO2–N and NO3–N) removal efficiency was always higher in reactor B compared to that in reactor A (Fig. 1b). As illustrated in Fig. 1b, the average effluent TN of reactor A increased from 1040 to 1334 mg L−1, and finally stabilized at 1579 mg L−1; the average effluent TN of reactor B declined from 1518 to 986 mg L−1, and then to 709 mg L−1. The total removal efficiencies of TN in reactor A varied between 30% and 48% during the initial 11 days, and then it sharply declined to approximately 3% on day 13. This considerable reduction might result from the inhibition of calcium to the anaerobic ammonium oxidation (ANAMMOX) reaction of anaerobic granules.31 Different to reactor A, the TN removal efficiency of reactor B gradually increased at the beginning and attained around 50–60% after 7 days of continuous operation (Fig. 1b), roughly 41.0% higher than from reactor A. The increased removal efficiencies of COD and TN obtained in reactor B confirmed the profoundly positive role played by biogas recirculation in the promotion of the EGSB performance.

Fig. 1c shows that the NH+4–N concentration in the influent was higher than that in the effluent, mainly attributable to the degradation of the nitrogenous organic substances in the leachate.25 Very interestingly, the NH+4–N concentrations in the effluent from bioreactors A and B were definitively different although the levels in the influent were relatively similar. The effluent NH+4–N concentrations in reactor A varied between 1000 and 1600 mg L−1 while the concentrations were almost less than 900 mg L−1 in reactor B (Fig. 1c). This revealed that ammonia stripping probably took place in the carbonation unit owing to the high pH value (10.0 ± 0.5). It has been reported that high ammonium concentrations can cause elevated concentrations of free ammonium (FA) in the reactor, which inhibits the phase of methenogenesis.1 Therefore, the reduced ammonium in the feed because of ammonia stripping might be another reason for the increase in the COD removal efficiency in reactor B.

3.3. 3D-EEM fluorescence analysis

3.3.1 EEM spectra. 3D-EEM spectra of the DOM fractions in leachate samples collected from the CO2-stripping unit, influent and effluent are illustrated in Fig. 1S in the ESI. Three main peaks could be identified from the fluorescence spectra at the excitation/emission wavelengths (Ex/Em) of 275–280/355–365 nm (peak A), 230–235/350–370 nm (peak B) and 315–335/405–425 nm (peak C). The first peak was attributed to tryptophan protein-like substances19,32 while the second peak was assigned to aromatic protein-like substances.33 Compared to the fluorescence peak locations of proteins (Ex/Em of 225/330–340 nm) in dissolved organic matter (DOM) for sludge samples described by Zhang et al.,34 the locations of peak B for the leachate showed a blue shift in terms of emission wavelengths. The third peak was regarded as humic-like substances derived from the biodegradation of soluble organic matter.35 Similar fluorescence signals have also been reported for DOM from landfill leachate36 and a submerged membrane bioreactor (SMBR)29 as well as extracellular substances of aerobic granules in a Plexiglas sequencing batch bioreactor (SBR).33 Although all leachate samples had similar fluorescent features with typical fluorophores of protein-like and humic-like substances, the location and intensity of the fluorescence peaks showed significant differences in the absence or presence of a carbonation unit.

The fluorescence parameters including the peak location and maximum fluorescence intensity were analyzed from EEM fluorescence spectra and are summarized in Table 2. The peak locations of the effluent displayed slight shifts in comparison with those of the influent. For reactor A, peaks B and C were red or blue shifted by around 5–10 nm along the excitation/emission axis with the variety of the operational time. In the case of reactor B, the locations of peaks A, B and C after treatment were all red shifted by 5–20, 5–15 and 5–15 nm, respectively. Such a shift suggested changes in the conformations of the fluorescence components in the leachate after the EGSB process. A red shift was attributed to the increase of carbonyl, hydroxyl, alkoxyl, and amino groups in fluorophores while a blue shift is related to the elimination of particular functional groups (carbonyl, hydroxyl, amine and aromatic rings) or a reduction in the degree of π-electron systems.34,37,38

Table 2 Fluorescence spectral parameters of organic substances present in the leachate from EGSB reactors A and Ba
Process Samples Peak A Peak B Peak C
Ex/Em Int. (×105) Ex/Em Int. (×105) Ex/Em Int. (×105)
a Inf.: influent; Eff.: effluent; Int.: intensity.
Reactor A Inf.-1d 275/355 11.78 230/360 3.31 330/415 2.97
Eff.-1d 275/355 3.68 230/370 1.3 335/425 1.45
Inf.-3d 275/355 11.03 230/360 3.03 330/420 2.61
Eff.-3d 275/355 4.06 230/355 1.42 330/420 1.52
Inf.-5d 275/355 11.12 230/355 2.91 330/415 2.65
Eff.-5d 275/355 4.41 230/355 1.59 325/425 1.67
Inf.-7d 275/355 11.16 230/355 3.04 325/415 2.75
Eff.-7d 275/355 4.31 230/360 1.57 330/420 1.66
Inf.-9d 275/355 10.36 230/365 2.81 325/410 2.59
Eff.-9d 275/355 3.31 230/360 1.31 325/420 1.64
Inf.-15d 275/355 9.99 230/350 2.7 325/410 2.57
Eff.-15d 275/355 9.99 230/350 2.7 325/405 2.58
Reactor B Inf.-1d 275/355 7.15 230/355 2.1 325/405 2.24
Eff.-1d 275/355 2.44 230/370 0.98 325/420 1.56
Inf.-2d 275/355 7.74 230/365 2.16 325/405 2.29
Eff.-2d 275/355 2.21 230/365 1.04 325/415 1.65
Inf.-4d 275/355 7.58 230/355 2.19 325/410 2.31
Eff.-4d 280/355 2.29 235/365 1.16 315/410 2.06
Inf.-6d 275/345 8.5 230/360 2.27 330/410 2.13
Eff.-6d 275/365 2.79 230/360 1.16 330/415 2.14
Inf.-7d 275/345 8.2 230/355 2.22 330/415 2.25
Eff.-7d 275/360 3.22 230/355 1.22 325/415 2.07
Inf.-9d 275/355 8.78 230/360 2.27 325/415 2.19
Eff.-9d 275/355 3.72 230/350 1.5 325/415 2.2
Inf.-11d 275/355 10.3 230/365 2.77 325/415 2.45
Eff.-11d 275/355 4.31 230/365 1.51 325/415 2.24
Inf.-12d 275/360 10.28 230/360 2.47 325/415 2.58
Eff.-12d 275/355 4.17 230/365 1.81 325/415 2.24
Inf.-13d 275/355 10.23 230/360 2.34 325/405 2.63
Eff.-13d 275/360 3.58 230/360 1.56 325/415 1.94
Inf.-15d 275/355 10.96 230/365 2.84 325/415 2.79
Eff.-15d 275/360 4.33 230/360 1.71 325/420 2.06


Generally, the change of the fluorescence peak intensities in the leachate before and after EGSB treatment is an indication of the biodegradation or transformation of the fluorescing materials. As given in Table 2, the fluorescence intensities of tryptophan protein-like and aromatic protein-like substances described respectively by peaks A and B for the effluent decreased significantly compared with the influent, however, the humic-like substances indicated by peak C maintained relatively stable regardless of the operational conditions. The experimental results clearly implied that protein-like substances in the leachate were more easily biodegraded for biogas production than humic substances. Moreover, the fluorescence intensities in the effluent from reactor B were weaker than those for reactor A, which obviously hinted that reactor B had higher efficiency in the biodegradation of organic matter and biogas recovery. The enhanced performance of an EGSB in this study was closely related to better sludge biological activity. The powerful sludge granules decomposed the high molecular fluorescing substances in the leachate, and therefore could enhance the following anaerobic digestion performance of the EGSB bioreactor.

3.3.2 PARAFAC analysis of EEM spectra. PARAFAC analysis was further employed to decompose fluorescence EEM spectra of the effluent samples from bioreactors A and B. Fig. 2 shows the contour plots of the three fluorescence components and the excitation and emission loadings of each component derived from the DOMFluor-ARAFAC model. The tryptophan protein-like fluorescence peak, which was located at the Ex/Em of 275–280/355–365 nm, was detected in component 1, possibly originated from cell lysis. Li et al.32 and Ni et al.39 observed a similar component in extracellular polymeric substances extracted from sludge. Component 2 consisted of three long emission wavelength humic-like fluorescence peaks, which were centered at 240/450, 295/450 and 340/450 nm. According to Coble,40 the peak at 295/450 nm was related to marine humic-like substances; compared with the observation of Coble, the peak in this study showed a slight shift towards longer wavelengths (red-shifted). The peak at 340/450 nm, according to Cai et al.,41 represented continental humic-like substances. In addition, one fluorescence peak at 320/320 nm was identified in component 3. Based on the protocol of Chen et al.,42 however, the peak did not seem to belong to any excitation–emission region. Several pieces of work have been conducted in recent years regarding the characterization of leachate with the help of a three-dimensional excitation–emission matrix combined with PARAFAC analysis.43–46 To date, very limited information about this component is available in the literature, with the exception of Yan et al.,47 in analyzing marine chromophoric dissolved organic matter (CDOM) via PARAFAC analysis, and they attributed this component to humic-like substances.
image file: c5ra26444h-f2.tif
Fig. 2 Contour plots of four components (left) identified using the DOMFluor-ARAFAC model and the split-half validation (right) of four components model (excitation to the left of emission spectra): (a) bioreactor A, and (b) bioreactor B.

The ARAFAC analysis provides additional quantitative information describing the distribution of the individual components in each sample.46 The Fmax of each component related to the relative concentration of the corresponding component in each effluent EEM sample can be derived from the DOMFluor-ARAFAC model. The resulting Fmax values are illustrated in Fig. 3. As can be seen, overall, the content of all of the components in the effluent samples from bioreactor B were much lower than those from bioreactor A. The componential characterizations clearly reveal that the introduction of the CO2-stripping unit affected the transformation of dissolved organic matter present in the leachate and the overall performance of the EGSB bioreactor. Application of the CO2-stripping unit alleviated the adverse impact of calcium, increased the bacterial activity, and accordingly stimulated the biodegradation and removal efficiency of the organic matter. As a result of this, the EGSB bioreactor with the CO2-stripping unit could work more stably and efficiently.


image file: c5ra26444h-f3.tif
Fig. 3 The maximum fluorescence intensities (Fmax) in the three components collected from the effluent samples of bioreactors A (a) and B (b) after 15 days of operation.

3.4. Characterizations of the clogging materials and sludge granules

To better understand the mechanisms observed within the digestion experiments (especially reactor B) performed in this study, the calcium removal and microstructural properties of the clogging materials and sludge granules collected from the EGSB bioreactors were analyzed systematically.
3.4.1 Crystalline phase analysis. The clogging materials and sludge granules were characterized through XRD analysis (Fig. 4). The XRD patterns, as illustrated in Fig. 4a, depicted that the clogging materials were composed principally of CaCO3, Mg0.064Ca0.936CO3, and Mg0.03Ca0.97CO3, which revealed that the dominant cause of clogging in the carbonation unit was calcium carbonate precipitates. It can be also found that the characteristic peaks for calcium carbonate drastically increased as the operation time elapsed, implying that the carbonation through biogas recirculation exerted a relatively positive role in the deposition of calcium carbonate. Obviously, biogas produced from the anaerobic digestion of the leachate can be recirculated for calcium precipitation and removal.
image file: c5ra26444h-f4.tif
Fig. 4 XRD pattern of the clogging materials (a) from the CO2-capturing system and sludge granules (b) from the EGSB bioreactors.

Regarding the sludge granules, the results of XRD analysis, presented in Fig. 4b, revealed that the granules from reactor A consisted of mostly calcium carbonate. The calcium content reached up to 305.96 mg g−1 TS from an initial value of 86.06 mg g−1 TS (seed sludge) on day 15 (Table 3), increasing by 255.5%, which is mainly attributed to the formation of calcium precipitates in the granular sludge. The precipitation of calcium carbonate in granular sludge was also observed by Ye et al.25 and Yu et al.11 in an UASB reactor, Lozecznik et al.28 in an anaerobic sequencing batch reactor (ASBR), as well as Liu et al.4 in an EGSB bioreactor. In contrast, the level of calcium in the granular sludge taken from reactor B remained relatively stable at 87.63 mg g−1 TS, similar to that in the seed sludge, confirming the positive role of carbonation on calcium removal. Therefore, to avoid calcium inhibition on the long-term stability of an EGSB bioreactor, leachate pretreatment, such as carbonation through biogas recirculation or chemical precipitation should be conducted.

Table 3 Metal content values of the sludge granules in the EGSB bioreactors (mg g−1 TS)
Type of sludge Ca Mg
Seed sludge 86.06 5.77
Sludge from reactor A 305.96 4.30
Sludge from reactor B 87.63 6.02


In addition to calcium, magnesium might also form precipitates together with calcium in the granules. However, it is interesting to find that no marked increase of magnesium in granules from both reactors was observed compared with the seed sludge (5.77 mg g−1 TS), and magnesium content values of around 4.30–6.02 mg g−1 TS were measured in both types of granules (Table 3), indicating that the inhibitory effect of magnesium was negligible.

3.4.2 Functional group identification. Fig. 5 depicts the FTIR patterns of the clogging materials and granular sludge. As shown in Fig. 5a, the spectra of the clogging materials exhibited characteristic bands at about 3409 cm−1, possibly due to the O–H stretching vibration (ν1). The bands at 2925 cm−1 corresponded to the asymmetric stretching vibration of the CH2 of aliphatic structures. The typical bands located at 1654 and 1540 cm−1 were attributed to the stretching and deformation vibration of the C[double bond, length as m-dash]O, C–N and N–H peptidic bond of proteins.48,49 The band present at 1429 cm−1 was associated with the C[double bond, length as m-dash]O stretching vibrations of carboxylates and OH deformation vibration of alcohols and phenols. The strong bands of ν2 and ν1-CO2−3 were found at around 1473 and 871 cm−1 respectively, mainly due to the presence of CaCO3. The band at 1049 cm−1 was linked to the C–O–C and C–O vibration of polysaccharides. These absorbance patterns at 1473 and 871 cm−1 provided further evidence for the accumulation of CaCO3 in the form of clogging materials as a result of the carbonation reaction. Moreover, the peak intensities of the functional groups, i.e., ν2 and ν1-CO2−3 resulting from the presence of CaCO3, gradually increased following the prolonged carbonation time, indicating more calcium was efficiently precipitated and removed during the carbonation process. It was also supported by the results observed in the X-ray diffraction analysis (Fig. 5a).
image file: c5ra26444h-f5.tif
Fig. 5 FTIR spectra of the clogging materials (a) from the CO2-capturing system and the sludge granules (b) from the EGSB bioreactors.

To reveal the influence of calcium on the functional groups of the sludge granules, the granules collected from both reactors were characterized using FTIR analysis. The results from Fig. 5b showed that the spectral bands at 1458 cm−1 and 873 cm−1 corresponding to ν2 and ν1-CO2−3 of CaCO3 from the granules in reactor B were relatively weaker compared to those in reactor A, which clearly revealed that the adherence of calcium inside or onto the surface of granular sludge was effectively inhibited because of the efficient calcium removal during the carbonation process. These results further demonstrated the crucial role played by biogas recirculation in controlling the negative effect of calcium ions. In addition, the strong bands located at 1653, 1540 and 1047 cm−1, representing proteins and polysaccharides respectively, confirmed the presence of a high content of extracellular polymeric substances (EPS). EPS, present outside bacterial cells and in the interior of microbial aggregates, play a key role in protecting the microorganisms in granules against toxic compounds through sorption and reaction.50 The functional groups of EPS such as hydroxyl, carboxyl, and amine can generate a negative surface charge. The negatively charged groups can act as calcium binding sites to bind calcium ions in the influent, thereby partially reducing the toxicity to anaerobic granular sludge in the EGSB bioreactor.

3.4.3 SEM observations. To locate the CaCO3 crystals in the granular sludge in more detail, SEM analysis of the granules collected from reactors A and B during the operation was performed (Fig. 6). As shown in Fig. 6a, large numbers of hexagonal-like CaCO3 phases were found to extensively form within the granules from reactor A. Apart from the CaCO3 encapsulated in the granules, CaCO3 crystals could also be identified between granules. The surface topography of the granules was densely packed, rigid and rough, suggesting serious accumulation and precipitation of calcium. When in the presence of biogas recirculation, the granular sludge seemed more regular in shape with a smooth exterior surface, and there were nearly no bulk hexagonal crystals detected (Fig. 6b), agreeing well with the XRD and FTIR observations (Fig. 4 and 5). A previous study by Ye et al.,25 reported that Methanosaeta-like species, known to exert a crucial role in the initial granulation, were predominant in the core of developed granules. Therefore, the higher CaCO3 deposition would form a hard crust in the anaerobic granules, which inevitably reduced the activity of the methanogens in the interior layer. However, the adverse effect of calcium seemed to be effectively controlled when biogas recirculation was applied. Biogas recirculation through a carbonation reaction induced the reduced calcium level in the influent, which promoted Methanosaeta-like species survival and faster granule formation.18 As a consequence, a stable and improved performance of the EGSB bioreactor was achieved.
image file: c5ra26444h-f6.tif
Fig. 6 SEM spectra of the sludge granules from bioreactor A (a) and B (b).

Based on the abovementioned results, it is therefore very reasonable to state that biogas recirculation is a cost-effective alternative for the removal of calcium and the maintenance of bacterial activity and it will be a method to eliminate the calcium inhibition of granular sludge activity and subsequent anaerobic digestion during the EGSB process of fresh leachate with high calcium concentrations.

4. Conclusion

A CO2-stripping system was developed in a leachate-fed EGSB bioreactor, with the purpose of stimulating organic matter removal and sludge granulation. The continuous performance of the bioreactor was greatly improved when the CO2-stripping unit was employed as the pretreatment to carbonize calcium-rich leachate. This strategy induced a considerable increase in methane yield, as well as COD and TN removal under steady-state conditions. Further analysis using 3D-EEM combined with PARAFAC, XRD, FT-IR and SEM evidenced that the introduction of the CO2-stripping unit promoted calcium precipitation and reduced the adverse effects on clogging and granular activity, which subsequently enhanced the methanogenic efficiency and overall process stability. The general principle described here can also be transferred into related calcium-rich wastewater treatment systems for upgrading calcium removal, process stabilization, and the sustainable production of bioenergy. This study provides an in-depth insight into the improvement of applying a CO2-stripping unit in organic matter degradation and sludge granulation improvement, advancing its practical applications.

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (21377079, 51578329), the key research project from the Science and Technology Commission of Shanghai Municipality (13DZ0511600) and the Program for Innovative Research Team in University (No. IRT13078).

References

  1. J. Y. Liu, J. H. Luo, J. Z. Zhou, Q. Liu, G. R. Qian and Z. P. Xu, Bioresour. Technol., 2012, 113, 239–243 CrossRef CAS PubMed.
  2. S. M. Tauseef, T. Abbasi and S. A. Abbasi, Renewable Sustainable Energy Rev., 2013, 19, 704–741 CrossRef CAS.
  3. Y. J. Zhang, L. Yan, L. Chi, X. H. Long, Z. J. Mei and Z. J. Zhang, J. Environ. Sci., 2008, 20, 658–663 CrossRef CAS.
  4. J. Y. Liu, J. Hu, J. P. Zhong, J. H. Luo, A. H. Zhao, F. Liu, R. J. Hong, G. R. Qian and Z. P. Xu, Bioresour. Technol., 2011, 102, 5466–5472 CrossRef CAS PubMed.
  5. A. Ahmad, R. Ghufran and Z. Abd Wahid, J. Hazard. Mater., 2011, 198, 40–48 CrossRef CAS PubMed.
  6. D. Puyol, A. F. Mohedano, J. L. Sanz and J. J. Rodriguez, Chemosphere, 2009, 76, 1192–1198 CrossRef CAS PubMed.
  7. M. X. Zheng, K. J. Wang, J. E. Zuo, Z. Yan, H. Fang and J. W. Yu, Bioresour. Technol., 2012, 107, 33–40 CrossRef CAS PubMed.
  8. T. Abbasi and S. A. Abbasi, Renewable Sustainable Energy Rev., 2012, 16, 1696–1708 CrossRef CAS.
  9. X. Lu, G. Zhen, M. Chen, K. Kubota and Y. Y. Li, Bioresour. Technol., 2015, 198, 691–700 CrossRef CAS PubMed.
  10. Y. J. Liu and D. D. Sun, Process Biochem., 2011, 46, 987–992 CrossRef CAS.
  11. H. Q. Yu, J. H. Tay and H. H. P. Fang, Water Res., 2001, 35, 1052–1060 CrossRef CAS PubMed.
  12. R. P. Beaven, A. P. Hudson, K. Knox, W. Powrie and J. P. Robinson, Waste Manage., 2013, 33, 431–444 CrossRef CAS PubMed.
  13. E. P. A. van Langerak, G. Gonzalez-Gil, A. van Aelst, J. B. van Lier, H. V. M. Hamelers and G. Lettinga, Water Res., 1998, 32, 1255–1263 CrossRef CAS.
  14. A. Pevere, G. Guibaud, E. D. van Hullebusch, W. Boughzala and P. N. L. Lens, Colloids Surf., A, 2007, 306, 142–149 CrossRef CAS.
  15. H. Y. Jo, J. H. Ahn and H. Jo, J. Hazard. Mater., 2012, 241, 127–136 CrossRef PubMed.
  16. O. Nir, M. Herzberg, A. Sweity, L. Birnhack and O. Lahav, Chem. Eng. J., 2012, 187, 275–282 CrossRef CAS.
  17. Y. H. Kim, S. H. Yeom, J. Y. Ryu and B. K. Song, Process Biochem., 2004, 39, 1393–1399 CrossRef CAS.
  18. J. Luo, X. Lu, J. Liu, G. Qian and Y. Lu, Bioresour. Technol., 2014, 173, 317–323 CrossRef CAS PubMed.
  19. G. Zhen, X. Lu, Y. Y. Li, Y. Zhao, B. Wang, Y. Song, X. Chai, D. Niu and X. Cao, Bioresour. Technol., 2012, 119, 7–14 CrossRef CAS PubMed.
  20. G. H. Yu, P. Jing He and L. M. Shao, Water Res., 2010, 44, 797–806 CrossRef CAS PubMed.
  21. X. Guo, X. He, H. Zhang, Y. Deng, L. Chen and J. Jiang, Microchem. J., 2012, 102, 115–122 CrossRef CAS.
  22. G. Zhen, X. Lu, Y. Y. Li and Y. Zhao, Appl. Energy, 2014, 128, 93–102 CrossRef CAS.
  23. APHA, American Public Health Association, Washington, D.C., 1998.
  24. H. Q. Yu, H. H. P. Fang and J. H. Tay, Chemosphere, 2001, 44, 31–36 CrossRef CAS PubMed.
  25. J. X. Ye, Y. J. Mu, X. Cheng and D. Z. Sun, Bioresour. Technol., 2011, 102, 5498–5503 CrossRef CAS PubMed.
  26. Y. Chen, J. J. Cheng and K. S. Creamer, Bioresour. Technol., 2008, 99, 4044–4064 CrossRef CAS PubMed.
  27. H. Timur and I. Ozturk, Water Res., 1999, 33, 3225–3230 CrossRef CAS.
  28. S. Lozecznik, R. Sparling, S. P. Clark, J. F. vanGulck and J. A. Oleszkiewicz, Bioresour. Technol., 2012, 104, 37–43 CrossRef CAS PubMed.
  29. T. Liu, Z. L. Chen, W. Z. Yu and S. J. You, Water Res., 2011, 45, 2111–2121 CrossRef CAS PubMed.
  30. R. H. Dai, Y. Liu, X. Liu, X. D. Zhang, C. Y. Zeng and L. Li, J. Hazard. Mater., 2011, 192, 1161–1170 CrossRef CAS PubMed.
  31. J. L. Wang and K. Jing, Process Biochem., 2005, 40, 1973–1978 CrossRef CAS.
  32. W. H. Li, G. P. Sheng, X. W. Liu and H. Q. Yu, Water Res., 2008, 42, 3173–3181 CrossRef CAS PubMed.
  33. L. Zhu, H. Y. Qi, M. L. Lv, Y. Kong, Y. W. Yu and X. Y. Xu, Bioresour. Technol., 2012, 124, 455–459 CrossRef CAS PubMed.
  34. Y. X. Zhang, P. Y. Zhang, J. B. Guo, W. F. Ma and L. P. Xiao, Bioresour. Technol., 2013, 135, 616–621 CrossRef CAS PubMed.
  35. S. S. Adav and D. J. Lee, J. Taiwan Inst. Chem. Eng., 2011, 42, 645–651 CrossRef CAS.
  36. L. Bu, K. Wang, Q. L. Zhao, L. L. Wei, J. Zhang and J. C. Yang, J. Hazard. Mater., 2010, 179, 1096–1105 CrossRef CAS PubMed.
  37. W. Chen, P. Westerhoff, J. A. Leenheer and K. Booksh, Environ. Sci. Technol., 2003, 37, 5701–5710 CrossRef CAS PubMed.
  38. Z. W. Wang, Z. C. Wu and S. J. Tang, Water Res., 2009, 43, 1533–1540 CrossRef CAS PubMed.
  39. B. J. Ni, W. M. Xie, S. G. Liu, H. Q. Yu, Y. Z. Wang, G. Wang and X. L. Dai, Water Res., 2009, 43, 751–761 CrossRef CAS PubMed.
  40. P. G. Coble, Mar. Chem., 1996, 51, 325–346 CrossRef CAS.
  41. W. Cai, X. Xu, X. Du, H. Zhu and G. Luo, Res. J. Environ. Sci., 2012, 25, 276–281 CAS , in Chinese.
  42. W. Chen, P. Westerhoff, J. A. Leenheer and K. Booksh, Environ. Sci. Technol., 2003, 37, 5701–5710 CrossRef CAS PubMed.
  43. H. Wu, Z. Zhou, Y. Zhang, T. Chen, H. Wang and W. Lu, Bioresour. Technol., 2012, 110, 174–183 CrossRef CAS PubMed.
  44. J. Wu, H. Zhang, L.-M. Shao and P.-J. He, Environ. Pollut., 2012, 162, 63–71 CrossRef CAS PubMed.
  45. F. Lu, C.-H. Chang, D.-J. Lee, P.-J. He, L.-M. Shao and A. Su, Chemosphere, 2009, 74, 575–582 CrossRef CAS PubMed.
  46. X. S. He, B. D. Xi, X. Li, H. W. Pan, D. An, S. G. Bai, D. Li and D. Y. Cui, Chemosphere, 2013, 93, 2208–2215 CrossRef CAS PubMed.
  47. L. Yan, The degree of Master, Ocean University of China, 2012.
  48. G. Zhen, X. Lu, B. Y. Wang, Y. C. Zhao, X. L. Chai, D. J. Niu, A. H. Zhao, Y. Y. Li, Y. Song and X. Y. Cao, Bioresour. Technol., 2012, 124, 29–36 CrossRef CAS PubMed.
  49. J. Laurent, M. Pierra, M. Casellas and C. Dagot, Chemosphere, 2009, 77, 771–777 CrossRef CAS PubMed.
  50. I. D. S. Henriques and N. G. Love, Water Res., 2007, 41, 4177–4185 CrossRef CAS PubMed.

Footnote

Electronic supplementary information (ESI) available. See DOI: 10.1039/c5ra26444h

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