Enhancing Denitrification in Constructed Wetland with Algae Addition

doi:10.21203/rs.3.rs-464778/v1

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Enhancing Denitrification in Constructed Wetland with Algae Addition

https://doi.org/10.21203/rs.3.rs-464778/v1

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published 06 Aug, 2021

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Constructed wetlands (CWs) can be used for tertiary treatment of wastewater; however, carbon source shortages limit denitrification. We studied the effect of algae addition as an external carbon source in CWs and found that the nitrogen removal efficiency of CWs is highly dependent on the algae dosage. Optimal nitrogen removal can be achieved by adding 80 mg·L^− 1 dry weight algae to the influent when the chemical oxygen demand/nitrogen (COD/N) ratio reaches 5.3. Longitudinal changes in the nitrogen concentrations, organic matter concentrations, and nitrogen functional genes were also analyzed. The algae addition strengthened the anoxic environment, boosted the volatile fatty acid concentrations, and proliferated the nitrite reductase gene (nirS) and the nitrite oxidoreductase alpha subunit gene (nxrA), thereby expanding the active space for denitrification. The integration of algal ponds with CWs could potentially provide enough carbon to enhance denitrification during treatment of wastewater with a low COD/N ratio.

Environmental Engineering

Environmental Policy

constructed wetland

denitrification

carbon source

tertiary wastewater treatment

algae addition

nitrogen functional genes

Constructed wetlands (CWs) have been widely used for wastewater treatment (Vymazal, 2007), as they are cost-effective, environment-friendly, and highly efficient. However, CWs exhibit poor denitrification performance when used for tertiary treatment of municipal wastewater, owing to the lack of carbon sources in the secondary effluent. Microbial transformations account for the majority of total nitrogen (TN) removal from wastewater (Kadlec and Knight, 1996). Nitrification and denitrification are typical pathways for the reduction of nitrogen and account for a nitrogen removal rate of 54–94% in CWs, as shown in earlier studies (Vymazal, 2005; Han et al, 2019). Denitrifying bacteria use carbon as an electron donor. Therefore, denitrification is the limiting factor when wastewater with a low chemical oxygen demand/nitrogen (COD/N) ratio is treated in CWs (Zhang et al., 2016), and an external carbon source should be added (Hume et al., 2002b). Moreover, the addition of carbon sources enhances nitrate removal by creating anaerobic microsites (Hamersley et al., 2002).

The use of organic matter with a low molecular weight can improve the denitrification in CWs, but is costly and increases the risk of high COD concentrations in the effluent. In addition, a large proportion of the carbon input is consumed by aerobic bacteria (Lin et al., 2002). The use of plant litter as an external carbon source is relatively cost-effective. However, complex pretreatment procedures, such as alkali treatment (Wen et al., 2010; Huang et al., 2012), acid treatment (Ding et al., 2013), fermentation (Fu et al., 2018), and pyrolyzation into biochar (Jia et al., 2020) are required to manage the high cellulose contents. High molecular weight polymers (HMPs) act as carbon sources and provide biofilm support. However, the use of these carbon sources is limited by their relatively high cost and treatment complexity. Therefore, it is necessary to find an alternative carbon source for tertiary treatment of wastewater using CWs.

Algae have been utilized for wastewater treatment since 1957 (Oswald et al., 1957). During proliferation, they take in nitrogen and phosphorus and produce organic matter. Single-celled green algae, such as Chlorella vulgaris and Scenedesmus sp., contain many proteins, fatty acids, and polysaccharides; hence, they can be used as carbon sources for denitrification (Hume et al., 2002a). The results of research on biofuel production have indicated that it is feasible to cultivate green algae using municipal wastewater or secondary effluent from water treatment plants as a nutrition source (Gouveia et al., 2016). In recent years, several researchers have used a combined system integrating a high-rate algal pond (HRAP) with a CW for high nitrogen synthetic wastewater treatment (Ding et al., 2016; Zhao et al., 2016). The results have demonstrated that algae not only assimilate nitrogen in the algal pond and increase the dissolved oxygen (DO) concentrations of the influent to the CW, but also act as a carbon source in the CW. Nevertheless, there are still no detailed studies on the role of microalgae as a carbon source. The aim of this study was to evaluate the nitrogen removal rate in CWs under different algal dosages and determine the nitrogen transformations in response to the algae.

2.1. Construction of wetland

Six horizontal subsurface flow CWs (HSSF-CWs), which were named CW1, CW2, CW3, CW4, CW5, and CW6, were installed in a greenhouse on the campus of Tongji University. The dimensions of each plot were: 120 cm (length) × 45 cm (width) × 65 cm (height) (Fig. 1). To describe the different areas easily, we defined the first 30 cm long section as the first quarter, 30–60 cm as the second quarter, 60–90 cm as the third quarter, and 90–120 cm as the fourth quarter. The substrate was ceramsite (Φ = 5–8 mm). Canna indica L. and Iris sibirica L., which are frequently used in China were planted in all of the plots, with a total density of 20 plants·m^-2. Nine outlets were on the side of each plot (Fig. 1), labeled ②-⑩, which allowed for sampling.

2.2. Constructed wetland operation

Synthesized wastewater meeting the water quality of First-Grade-A standard, according to the “Discharge standard of pollutants for municipal wastewater treatment plant (WWTP)” (GB18918-2002), was treated by the HSSF-CW using Chlorella. vulgaris as the external carbon source. To simulate WWTP effluent, the following chemicals were added to the synthetic wastewater: KNO₃(72.2 mg·L^-1), NH₄Cl (19.1 mg·L^-1), KH₂PO₄ (1.7 mg·L^-1), and sodium acetate (NaAc, 64.1 mg·L^-1). Trace metals (e.g., Fe²⁺, Mo⁴⁺), mineral salts (e.g., Ca²⁺, K⁺, Mg²⁺), and vitamins (Kit V-1, Sigma Chemical Co., USA) were added, ensuring that nitrate (NO₃^--N) and carbon were the only limiting resources for the denitrifying bacteria (Fleming and Horne, 2002). All of the plots were fed with synthetic wastewater for 6 months to enter a stable phase before sampling.

The results of our previous studies on carbon-releasing algae have shown that the soluble chemical oxygen demand reaches a stationary phase after ten days (data not shown), and that the maximum carbon release is 370 mg COD_Cr·g^-1 (dry weight, DW). Reportedly, the maximum soluble carbon released by cattail litter is 220 mg·COD_Cr·g^-1 DW, while canna litter released 120 mg·COD_Cr·g^-1 DW (Ding et al., 2013). This suggests that C. vulgaris releases a higher COD_Cr concentration than plant litter.

Six HSSF-CW plots were employed for this study. The hydraulic loading (HLR) of CW1, CW2, and CW3 was 100 mm·d^-1 and that of CW4, CW5, and CW6 was 200 mm·d^-1. CW1 and CW4 had no algae input, and the COD_Cr/N of CW1 and CW4 was 3.3. The algae carbon source was added to the influents of CW2, CW3, CW5, and CW6. The COD_Cr/N of CW2 and CW5 was 4.3 and that of CW3 and CW6 was 5.3.

2.3. Sample collection and physicochemical analyses

Influent and effluent samples were collected every week between 8:00 and 9:00 AM. Samples were obtained from the nine outlets on the sides of the CWs (Fig. 1, ②-⑩). The DO and the oxidation-reduction potential (ORP) were measured in situ using a Thermo Orion 5 Star portable meter (Thermo-Orion Inc., Waltham, MA, USA).

The COD_Cr concentrations of the water samples were determined using the potassium dichromate method with a spectrophotometer (DR/2800, Hach Co., Loveland, CO, USA). The total nitrogen (TN), ammonium (NH₄⁺-N), NO₃^--N, and nitrite (NO₂^--N) contents were determined using a flow injection analyzer (Seal AA3, Bran+Luebbe, GER). The methods were based on the “Methods for Chemical Analysis of Water and Waste” (State Environmental Protection Administration of China, 2002).

After the samples were filtered through a 0.45 µm filter membrane, the dissolved organic carbon (DOC) concentrations of the influent, effluent, and discharge from the nine outlets were analyzed using a total organic compound (TOC) analyzer (V-CPN, Shimadzu, Guangdong, China). The volatile fatty acid (VFA) concentrations were determined using a gas chromatograph (6890N, Agilent, CA, USA) equipped with a flame ionization detector and a CB-Wax column. The VFAs were analyzed according to the method described by Wen (2010). Two replicates of each sample were used for the analyses.

2.4. DNA extraction

After eight months of CW operation, 50 g samples of the substrate were collected at each sampling site in the HSSF-CWs (sampling sites were located in the middle of the substrates, but at precisely the same height and length as outlets ①-④, Fig. 1). After placing each sample into a 150 mL sterile flask containing 40 mL of water, the flasks were shaken at 100 rpm for 1 h at 25 °C and the precipitates were collected in bottles. After centrifuging (twice) at 10,000 g for 15 min at 4 °C, the concentrated litter was collected and used for further analyses (Butterworth, 2014). The total genomic DNA was extracted using a D5625-01 Soil DNA Kit (OMEGA Bio-tek, Inc., USA).

2.5. Real-time polymerase chain reaction assay

To quantify the total 16S ribosomal ribonucleic acid (16S rRNA) content, as well as 7 functional genes in the N cycle that encode the main catalytic enzymes from the corresponding processes, a real-time polymerase chain reaction (PCR) assay was performed using an ABI StepOnePlus detection system (Applied Biosystems, USA). Quantitative PCR (qPCR) was carried out using a two-step amplification procedure. The thermal cycling conditions were as follows: 15 s at 95 °C, 45 cycles of 20 s at 57 °C, and 30 s at 72 °C. All of the samples were analyzed in triplicate.

2.6. Data analysis

Two-way analysis of variance (ANOVA) was performed at a significance level of P < 0.05 to analyze the difference between the nitrogen removal rates under different influent COD_Cr/N ratios and different HLRs. Statistical analyses were performed using SPSS ver. 20.0.

where c_a1 is the concentration of a in the CW influent (mg·L^-1), c_a2 is the concentration of a in the effluent (mg·L^-1), and HLR is the hydraulic loading rate (mm·d^-1). The removal efficiency is expressed in g·m^-2·d^-1.

A redundancy analysis (RDA) was performed using the R statistical platform and vegan package (R Development Core Team, 2016) to examine the potential effects of the main physicochemical factors (ORP, COD, TN, NH₄⁺-N, NO₃⁻-N, NO₂⁻-N, TOC, and VFAs) on the N functional genes.

3.1 COD_Cr removal

The influent COD_Cr/N had a significant influence on the COD_Cr removal rate and efficiency (P <0.05, Table 1. Table 1 is put at the end of this paper). Without algae input, the COD_Cr removal rate was approximately 85%, while it increased to above 90% at COD_Cr /N=4.3 and 5.3. However, HLR did not have a significant influence on the COD_Cr removal rate (P>0.05). When the HLR increased from 100 mm·d^-1 to 200 mm·d^-1, the COD_Cr removal efficiency almost doubled.

Table 1

COD, Nitrogen removal rates and efficiencies of CW1–CW6

Group	Influent COD/N	HLR (mm·d^-1)	Removal rate (%)			Removal efficiency (g·m^-2·d^-1)
Group	Influent COD/N	HLR (mm·d^-1)	COD	TN	NH₄⁺-N	COD	TN	NH₄⁺-N
CW1	3.3	100	85.7±9.8	20.6±6.5	74.1±9.5	4.23±0.05	0.215±0.069	0.371±0.054
CW2	4.3	100	90.7±1.2	52.5±13.2	87.8±3.2	5.89±0.06	0.873±0.211	0.521±0.020
CW3	5.3	100	92.3±2.3	80.5±6.6	91.6±3.8	7.39±0.11	1.35±0.11	0.630±0.027
CW4	3.3	200	84.6±4.2	12.6±6.9	73.4±9.1	8.43±0.15	0.568±0.180	0.562±0.175
CW5	4.3	200	91.2±3.7	51.1±11.5	85.5±7.4	12.0±0.2	1.63±0.37	1.01±0.09
CW6	5.3	200	90.9±3.1	61.1±8.4	74.7±8.0	14.4±0.3	2.06±0.28	0.991±0.054

All data are presented as the means ± SD (standard deviation); n=8 for each group

3.2 Nitrogen removal

At HLR=100 mm·d^-1, the NH₄⁺-N removal rate increased with increasing influent COD_Cr/N ratio (Table 1 ). However, at HLR=200 mm·d^-1, the NH₄⁺-N removal rate decreased at COD_Cr/N=5.3. Both COD_Cr/N and HLR exerted significant influences on the TN removal rate (P <0.05). The highest TN removal rate of 80.5% was achieved at COD_Cr/N=5.3 and HLR=100 mm·d^-1, with a TN removal efficiency of 1.35 g·m^-2·d^-1. The TN removal rate decreased with an increasing HLR or a decreasing COD_Cr/N ratio. The nitrogen profiles of CW1–CW6 are shown in Fig. 2.

At an HLR of 100 mm·d^-1, TN was mostly reduced in the first and second quarters of the CWs. With the input of algae, the TN concentrations rapidly decreased in the CWs. In the second quarter of the CWs, the TN removal rates reached 18.01, 63.5, and 72.6% at COD_Cr/N ratios of 3.3, 4.3, and 5.3, respectively.

At an HLR of 200 mm·d^-1, the main reaction zone in which N removal occurred after algae addition extended into the third and fourth quarters of the CWs. The TN concentrations in the bottom parts of the CWs were higher. In the middle of the CW, at a COD_Cr/N ratio of 4.3, the TN removal rates in the upper and bottom parts were 73.3%, and 44.9%, respectively. At a COD_Cr/N ratio of 5.3, the TN removal rates in the upper and bottom parts were 69.3% and 24.6%, respectively. In contrast, the main reaction zone of TN removal did not expand without algae input; the TN concentration decreased by 39.9% in the first and third quarters of the CW, but changed insignificantly in the other parts.

The NH₄⁺-N profile was similar to that of TN. The NH₄⁺-N concentrations decreased along the CWs. At an HLR of 100 mm·d^-1, the NH₄⁺-N removal rates in the second quarters of the CWs were 89.9%, 85.0%, and 60.8% at COD_Cr/N ratios of 3.3, 4.3, and 5.3, respectively. At each COD_Cr/N ratio, the NH₄⁺-N concentrations in the second half of the CW were below 1.0 mg·L^-1.

At an HLR of 200 mm·d^-1, the main active zone of each group extended into the third and fourth quarters of the CWs. At a COD_Cr/N ratio of 3.3, 61.4% of the NH₄⁺-N was removed in the first two quarters of the CW. After algae addition, the concentration in the bottom part was notably higher than in the upper parts. At a COD_Cr/N ratio of 4.3, the NH₄⁺-N removal rate was 69.8% in the upper part of the first half of the CW, whereas it was 0.8% in the bottom part. At a COD_Cr/N ratio of 5.3, NH₄⁺-N removal rates of 41.9% and 0% occurred in the upper and the bottom parts, respectively. With an increase in the HLR, the NH₄⁺-N concentrations in the bottom parts increased and became higher than those in the upper parts in CWs to which algae were added; the opposite was true for the removal efficiency.

The NO₃^--N profile complemented the NH₄⁺-N profile. At an HLR of 100 mm·d^-1 and a COD_Cr/N ratio of 3.3, the NO₃^--N concentration was 4.32 mg·L^-1 at the front and 6.10 mg·L^-1 at the end. At a COD_Cr/N ratio of 4.3, the NO₃^--N concentration was 2.45 mg·L^-1 at the front and 4.49 mg·L^-1 at the end.

At an HLR of 200 mm·d^-1 and COD_Cr/N ratios of 3.3 and 4.3, the NO₃^--N concentration increased, whereas it did not increase at a COD_Cr/N ratio of 5.3. The addition of sufficient algae enhanced NO₃^--N removal in the first quarter of the CW and was conducive to NO₃^--N removal in the last three quarters of the CWs.

The NO₂^--N concentration of the control group was higher than 2 mg·L^-1 for all HLRs throughout the CWs. At an HLR of 200 mm·d^-1, it reached 5.10 mg·L^-1in the bottom area. At COD_Cr/N ratios of 4.3 and 5.3 and an HLR of 100 mm·d^-1, the NO₂^--N concentration was very low. However, at an HLR of 200 mm·d^-1, the NO₂^--N concentration increased in the second half of the CW, at COD_Cr/N ratios of 4.3 and 5.3, reaching 3.05 and 2.98 mg·L^-1, respectively.

At an HLR of 100 mm·d^-1, the NO₂^--N concentration of the control group was higher than 2 mg·L^-1 throughout the CWs. However, at COD_Cr/N ratios of 4.3 and 5.3, the concentrations were much lower. At an HLR of 200 mm·d^-1 and any COD_Cr/N ratio, the effluent NO₂^--N concentrations were high.

3.3. Oxidation-reduction potential profiles

The addition of algae led to a sharp decline in the ORP level in the CWs, especially in the first and second quarters (Fig. 3). The profile indicates that the ORP level of the bottom area was lower than that of the upper area. In contrast, at COD_Cr/N ratios of 3.3 and 4.3, the ORP levels of the front part were higher than those of the other parts. At a COD_Cr/N ratio of 5.3, the highest ORP was obtained in the rhizosphere.

3.3. Organic matter profiles

At an HLR of 100 mm·d^-1, the DOC concentration gradually decreased along the inflow and approached zero in the second quarter of the CW (Fig. 4). After the addition of algae, the active zone extended into the third quarter of CWs.

The VFA concentrations were extremely low at each sampling site in the control group. With increased algae addition, the VFA concentrations increased. The highest concentration was observed in the lower front area, which was greater than 8 mg·L^-1 (COD_Cr). This area overlapped with the zone that contained high TN and NH₄⁺-N concentrations.

3.4. Nitrogen functional genes

Based on the qPCR results, the absolute abundance of 16s rRNA at site ① was higher than at the other sites (data not shown), which can be attributed to the abundant organic matter, nitrogen, and phosphorous in this area. The addition of algae increased the microbe quantities at each sampling site. At a COD_Cr/N ratio of 5.3, the absolute abundance of site 1 increased from 1.32 × 10⁵ to 8.64 × 10⁵ copies. The algae addition also enhanced the total amounts of bacteria in the second half of the CWs. Note that the absolute abundance of 16s rRNA at site 4 was higher than at sites 2 and 3 at COD_Cr/N ratios of 4.3 and 5.3. Based on the algae addition, the absolute abundance of 16s rRNA at site 4 increased from 3.33 × 10⁵ to 2.82 × 10⁶ and 5.71 × 10⁶ copies, respectively.

The result (Fig. 5) indicate that nitrite reductase gene (nirS), nitrite oxidoreductase alpha subunit gene (nxrA), and anammox were dominant among the nitrogen functional genes. The copies of nirS accounted for 74.7–96.6% of the nitrogen functional genes. The abundance of nirS decreased alongside the CWs. With an increase in the COD_Cr/N ratio from 3.3 to 4.3 and 5.3, the total abundances at the four sampling sites increased from 5.03 × 10⁵ to 5.34 × 10⁵ and 7.37 × 10⁵ copies, respectively. After the algae addition, the nirS abundance also increased at the other three sampling sites.

At a COD_Cr/N ratio of 3.3, the anammox abundances at sites 1 and 2 were 6.63 × 10³ and 7.10 × 10³ copies, respectively, whereas the abundances were 1.57 × 10⁴ and 5.80 × 10³ copies, respectively, at a COD_Cr/N ratio of 4.3, and 2.51 × 10⁴ and 5.09 × 10³ copies, respectively, at a COD_Cr/N ratio of 5.3.

The algae addition also increased the abundance of nxrA in the second half of the CW. The sum of the abundances at sites 3 and 4 was 3.67 × 10³ copies when the COD_Cr/N = 3.3, whereas the sum increased to 7.54 × 10³ and 2.72 × 10⁴ copies at COD_Cr/N ratios of 4.3 and 5.3, respectively.

4.1 Effects of algae addition on ORP and VFAs

Biodegradation of organics was carried out by both aerobic and anaerobic microorganisms, depending on the availability of oxygen (Kumar, 2019). As the ORP results show (Fig. 3), with an increasing COD_Cr/N and an increasing HLR, the CWs became less favorable for aerobic bacteria. The ORP levels of CW1, CW2, CW4, and CW5 were almost all above 0 mv, while the ORP levels of some parts of CW3 and CW6 were below 0 mv. Huang et al. (2019) found that DO was rapidly consumed through aerobic respiration when using glucose and NaAc as additional carbon sources. It is possible that COD_Cr was reduced by both aerobic and anaerobic microorganisms in CW3 and CW6. This phenomenon also agrees with the findings of Ong. (2010).

DOC and VFA concentrations increased with the influent COD_Cr/N ratio. In CW2, CW3, CW5, and CW6, the ORP dropped to below 0 mv in some parts of the CWs. ORP plays an essential role in VFA production, and the highest VFA production from wood waste occurred at ORP = -200 to -100 mv (Jun et al., 2016). However, Kim (2016) found that the estimated maximum VFA production was 0.26 g total VFAs/g COD_Cr at a HRT of 2.14 days and a pH of 6.44. The higher pH values in CW1–CW6, which were all above 8, may have caused relatively less VFA production in this study. VFA concentrations and types were reported to have significant influences on the denitrification rate (Wen et al., 2010; Kim et al., 2016). Wen (2016) found that the ratio of VFAs: available carbon sources (including reducing sugar, proteins, and VFAs) had a strong positive correlation with the nitrate removal rate. In this study, at a COD_Cr/N = 5.3, the area of high DOC concentrations (>9 mg·L^-1) extended into the middle of the CWs, and VFAs were detected even in the last quarter of the CWs. This would enable denitrification in the last two quarters of the CWs.

4.2 Effect of algae addition on nitrogen removal

The results of the RDA for the nitrogen functional genes and environmental factors (ORP, TOC, VFAs, NH₄⁺-N, NO₃^--N, NO₂^--N) are illustrated in Fig. 6. The denitrifying functional gene nirS was closely related to the VFA concentrations in the CWs, whereas the NO₃^--N concentrations and the ORP levels were key factors that affected anammox and the nitrifying functional gene nxrA.

At an HLR of 100 mm·d^-1, the removal of NH₄⁺-N mainly occurred in the first quarter of the CWs; however, the active space expanded to the end of the CWs after algae addition. Concentrations became higher in the first quarter and in the bottom parts of the CWs where the ORP levels were relatively low. Oxygen concentrations above 1.5 mg·L^-1 have been reported as necessary for nitrification (Vymazal, 2007), and oxidation of organic matter restrained the activity of autotrophic ammonia oxidation bacteria by DO competition (Li et al., 2017). Based on the distribution of ammonia mono-oxygenase (amoA), the abundances of amoA at each sampling point decreased abruptly after algae addition. It is possible that the addition of algae led to decreases in the nitrification rates of the CWs, thereby expanding the active space.

In this study, NaAc was used as the COD in the synthetic water, as it is easily oxidized and decomposed. Thus, the NO₃^--N content decreased in the first quarter of the CWs in the control group. The NO₃^--N concentrations increased with nitrification from the front to the back of the CW because more carbon became available for denitrification. The concentration of soluble carbon increased after algae addition (Fig. 4), and VFAs were detected throughout the CWs. VFAs are easily biodegradable carbon sources for denitrification (Feng et al., 2006). The NO₃^--N concentrations decreased continuously because carbon was available, even in the third and fourth quarters of the CWs. Zhang (2016), who used plant fermentation broth as the external carbon source in their study, found that TN was mostly removed in the first quarters of HSSF-CWs with or without external carbon sources. In Zhang’s study, the influent contained only NO₃^--N, and the NO₃^--N profile was not affected by nitrification. In contrast, the abundance of the nitrate reductase gene (narG) increased after algae addition, especially at the back ends of the CWs, demonstrating that the algae promoted denitrification and expanded the active space.

NO₂^--N concentrations increased along the inflow from the fronts to the ends of the CWs (Fig. 2). The accumulations decreased with the addition of algae, which might be attributed to (1) the strengthening of denitrification, (2) the prevention of short-cut nitrification, and (3) the promotion of anammox. With respect to (1), Hu et al. (2020) reported that when the influent N was mainly NO₃^--N, the NO₂^--N concentrations first increased, but then decreased if the carbon content was high. A lower hydraulic retention time (HRT) was conducive to short-cut nitrification. NirS was more abundant than nirK (Fig. 5) and the nirS abundance increased with the addition of algae, which promoted VFAs. With respect to (2), higher HRT and organic matter loads led to the strengthening of the anoxic environment (Fig. 3). Ammonia–oxidizing bacteria (AOB) have higher oxygen affinities than nitrite-oxidizing bacteria (NOB). At a low DO concentrations, AOB are predominant (Ma et al., 2009). The abundance of nxrA did not increase with the addition of algae (Fig. 5). With respect to (3), in the front parts of the CWs, the abundance of anammox increased significantly with the addition of algae and was significantly correlated with the ORP level (Fig. 6). Hou et al. (2018) suggested that anammox could coexist with denitrifying bacteria, even in an environment with a high COD/N ratio, and anammox might play a dominant role in nitrite removal. Therefore, factors (1) and (3) were likely the main reasons for the effective removal of nitrogen in this study.

In summary, the addition of algae increased the N load of the influent, whereas the anoxic environment caused the nitrification rate to decrease. However, the NOB abundance increased, particularly in the fourth quarter of the CWs, and short-cut nitrification could be avoided. The added algae decomposed anaerobically in the CWs and caused the accumulation of soluble organic compounds (typically VFAs), thus promoting denitrification throughout the CWs. This was the main reason for the expansion of the active space of TN removal toward the back parts of the CWs (Fig. 2). In contrast, the addition of algae strengthened the anoxic environment, particularly in the front parts, and promoted anammox to some extent.

We studied the effect of algae addition on N removal in CWs. The results indicate that algae addition significantly improved the N removal efficiency in the CWs. At COD_Cr/N=5.3 and HLR=100 mm·d^-1, the removal rate reached 80.5%. With the addition of algae, the ORP level changed thus the VFA concentrations increased, nirS and nxrA proliferated, promoting denitrification and anammox. Therefore, the TN removal improved and the active space expanded. A combined algae pond–constructed wetland system could be a valuable solution for advanced treatment of domestic sewage.

Acknowledgements

The authors thank Shan Huang for previous experiments and Yurui Li, Jiayin Guo, and Xiangyu Xu for experiment assistance.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the figshare repository, https://figshare.com/articles/dataset/Untitled_Item/14423687

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by the National Natural Science Foundation of China [grant numbers 51578395, 51778455] and the National Major Program of Science and Technology of China [grant number 2017ZX07603-003].

Authors' contributions

JH: Methodology, Data curation, Investigation, Visualization, Writing - original draft. FZ: Methodology, Formal analysis, Writing - review & editing. JW: Funding acquisition, Formal analysis, Writing - review & editing. SPC: Conceptualization, Supervision, Writing - review & editing.

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You are reading this latest preprint version

Enhancing Denitrification in Constructed Wetland with Algae Addition

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Materials And Methods

2.1. Construction of wetland

2.2. Constructed wetland operation

2.3. Sample collection and physicochemical analyses

2.4. DNA extraction

2.5. Real-time polymerase chain reaction assay

2.6. Data analysis

3. Results And Discussion

3.1 COD_Cr removal

3.2 Nitrogen removal

3.3. Oxidation-reduction potential profiles

3.3. Organic matter profiles

3.4. Nitrogen functional genes

4. Discussion

4.1 Effects of algae addition on ORP and VFAs

4.2 Effect of algae addition on nitrogen removal

5. Conclusions

Declarations

Acknowledgements

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors' contributions

References

Status:

Journal Publication

Version 1

Enhancing Denitrification in Constructed Wetland with Algae Addition

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Materials And Methods

2.1. Construction of wetland

2.2. Constructed wetland operation

2.3. Sample collection and physicochemical analyses

2.4. DNA extraction

2.5. Real-time polymerase chain reaction assay

2.6. Data analysis

3. Results And Discussion

3.1 CODCr removal

3.2 Nitrogen removal

3.3. Oxidation-reduction potential profiles

3.3. Organic matter profiles

3.4. Nitrogen functional genes

4. Discussion

4.1 Effects of algae addition on ORP and VFAs

4.2 Effect of algae addition on nitrogen removal

5. Conclusions

Declarations

Acknowledgements

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors' contributions

References

Status:

Journal Publication

Version 1

3.1 COD_Cr removal