| Literature DB >> 31598285 |
Liangang Hou1, Jun Li1, Zhaoming Zheng1, Qi Sun1, Yitao Liu1, Kai Zhang1.
Abstract
The river sediment contains a lot of pollutants in many cases, and needs to be treated appropriately for the restoration of water environments. In this study, a novel method was developed to convert river sediment into denitrifying sludge in a sequencing batch reactor (SBR). The river sediment was added into the reactor daily and the hydraulic retention time (HRT) of the reactor was gradually reduced from 8 to 4 h. The reactor achieved in the N O 3 - N removal efficiency of 85% with the N O 3 - N removal rate of 0.27 kg N m-3 d-1. Response surface analysis represents that nitrate removal was affected mainly by HRT, followed by sediment addition. The denitrifying sludge achieved the highest activity with the following conditions: N O 3 - N 50 mg l-1, HRT 6 h and adding 6 ml river sediments to 1 l wastewater of reactor per day. As a result, the cultivated denitrifying sludge could remove 80% N O 3 - N for real municipal wastewater, and the high-throughput sequence analysis indicated that major denitrifying bacteria genera and the relative abundance in the cultivated denitrifying sludge were Diaphorobacter (33.82%) and Paracoccus (24.49%). The river sediments cultivating method in this report can not only obtain denitrifying sludge, but also make use of sediment resources, which has great application potential.Entities:
Keywords: cultivation; denitrification; denitrifying bacteria; sediment
Year: 2019 PMID: 31598285 PMCID: PMC6774965 DOI: 10.1098/rsos.190304
Source DB: PubMed Journal: R Soc Open Sci ISSN: 2054-5703 Impact factor: 2.963
Figure 1.Schematic diagram of the reactor.
Figure 2.Changes of nitrogen form during cultivation process in effluent and influent.
Design and results of RSA experiments.
| no. | HRT | SA | NC | NRR | no. | HRT | SA | NC | NRR |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 6 | 4 | 80 | 80.38 | 10 | 6 | 6 | 50 | 85.5 |
| 2 | 6 | 6 | 50 | 85.5 | 11 | 6 | 6 | 50 | 85.5 |
| 3 | 6 | 6 | 50 | 85.5 | 12 | 8 | 6 | 80 | 86.25 |
| 4 | 8 | 8 | 50 | 85.75 | 13 | 4 | 4 | 50 | 77.65 |
| 5 | 8 | 4 | 50 | 83.14 | 14 | 8 | 6 | 20 | 85.91 |
| 6 | 6 | 6 | 50 | 85.5 | 15 | 6 | 8 | 80 | 83.07 |
| 7 | 4 | 8 | 50 | 80.18 | 16 | 4 | 6 | 80 | 77.73 |
| 8 | 4 | 6 | 20 | 77.72 | 17 | 6 | 4 | 20 | 76.69 |
| 9 | 6 | 8 | 20 | 80.18 |
Response surface regression model analysis of variance test. Note: R2 = 0.9551, Radj = 0.8975; the difference is significant (p < 0.05), the difference is highly significant (p < 0.01), the difference was extremely significant (p < 0.001).
| source | sum of squares | d.f. | mean square | ||
|---|---|---|---|---|---|
| model | 191.14 | 9 | 21.24 | 16.56 | 0.0006 |
| A-HRT | 96.4 | 1 | 96.4 | 75.17 | <0.0001 |
| B-SA | 16.02 | 1 | 16.02 | 12.49 | 0.0095 |
| C-NC | 6 | 1 | 6 | 4.68 | 0.0673 |
| AB | 0.0016 | 1 | 0.0016 | 0.001248 | 0.9728 |
| AC | 0.027 | 1 | 0.027 | 0.021 | 0.8883 |
| BC | 0.16 | 1 | 0.16 | 0.12 | 0.7343 |
| A2 | 4.2 | 1 | 4.2 | 3.27 | 0.1133 |
| B2 | 33.51 | 1 | 33.51 | 26.13 | 0.0014 |
| C2 | 28.44 | 1 | 28.44 | 22.17 | 0.0022 |
| residual | 8.98 | 7 | 1.28 | ||
| lack of fit | 8.98 | 3 | 2.99 | ||
| pure error | 0 | 4 | 0 | ||
| cor total | 200.12 | 16 |
Figure 3.Response surface. (a) SA and HRT. (b) SA and NC. (c) NC and HRT.
Figure 4.Scanning electron microscopy (SEM) images of the sediments, (a) (×2000) bar length: 50 µm; (b) (×50000) bar length: 2 µm.
Figure 5.High-throughput sequencing analysis of the sediment after cultivation.
Figure 6.Changes of in municipal wastewater treatment.