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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

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2018 Impact Factor: 3.883

Front. Environ. Sci. Eng.    2019, Vol. 13 Issue (6) : 83    https://doi.org/10.1007/s11783-019-1167-7
RESEARCH ARTICLE
Characteristic and correlation analysis of influent and energy consumption of wastewater treatment plants in Taihu Basin
Luxi Zou1, Huaibo Li1, Shuo Wang1,2,3(), Kaikai Zheng1, Yan Wang1, Guocheng Du4, Ji Li1,2()
1. Jiangsu Key Laboratory of Anaerobic Biotechnology, School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, China
2. Jiangsu College of Water Treatment Technology and Material Collaborative Innovation Center, Suzhou 215009, China
3. Department of Civil Engineering, Schulich School of Engineering, University of Calgary, Calgary T2N 1N4, Canada
4. Ministry Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi 214122, China
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Abstract

Poor biodegradability and insufficient carbon source are discovered from influent.

Influent indices presented positively normal distribution or skewed distribution.

Average energy consumption of WWTPs in Taihu Basin was as high as 0.458 kWh/m3.

Energy consumption increases with the increase in influent volume and COD reduction.

The total energy consumption decreases with the NH3-N reduction.

The water quality and energy consumption of wastewater treatment plants (WWTPs) in Taihu Basin were evaluated on the basis of the operation data from 204 municipal WWTPs in the basin by using various statistical methods. The influent ammonia nitrogen (NH3-N) and total nitrogen (TN) of WWTPs in Taihu Basin showed normal distribution, whereas chemical oxygen demand (COD), biochemical oxygen demand (BOD5), suspended solid (SS), and total phosphorus (TP) showed positively skewed distribution. The influent BOD5/COD was 0.4%–0.6%, only 39.2% SS/BOD5 exceeded the standard by 36.3%, the average BOD5/TN was 3.82, and the probability of influent BOD5/TP>20 was 82.8%. The average energy consumption of WWTPs in Taihu Basin in 2017 was 0.458 kWh/m3. The specific energy consumption of WWTPs with a daily treatment capacity of more than 5 × 104 m3 in Taihu Basin was stable at 0.33 kWh/m3. A power function relationship was observed between the reduction in COD and NH3-N and the specific energy consumption of pollutant reduction, and the higher the pollutant reduction is, the lower the specific energy consumption of pollutant reduction presents. In addition, a linear relationship existed between the energy consumption of WWTPs and the specific energy consumption of influent volume and pollutant reduction. Therefore, upgrading and operation with less energy consumption of WWTPs is imperative and the suggestions for Taihu WWTPs based on stringent discharge standard are proposed in detail.

Keywords Taihu Basin      Wastewater treatment plant      Influent characteristics      Energy consumption evaluation      Specific energy consumption      SPSS correlation analysis     
Corresponding Authors: Shuo Wang,Ji Li   
Issue Date: 31 October 2019
 Cite this article:   
Luxi Zou,Huaibo Li,Shuo Wang, et al. Characteristic and correlation analysis of influent and energy consumption of wastewater treatment plants in Taihu Basin[J]. Front. Environ. Sci. Eng., 2019, 13(6): 83.
 URL:  
http://academic.hep.com.cn/fese/EN/10.1007/s11783-019-1167-7
http://academic.hep.com.cn/fese/EN/Y2019/V13/I6/83
Water treatment capacity (104 m3/d) Number
Nanjing Wuxi Changzhou Suzhou Zhenjiang
>20 0 2 1 1 0
10–20 0 5 2 5 0
5–10 1 5 3 17 2
1–5 2 34 11 55 8
<1 12 5 15 8 10
Tab.1  Distribution of WWTPs in Taihu Basin
Pollution Influent
(mg/L)
Effluent
(mg/L)
Removal rate (%) Reduction quantity
(t)
National mean (mg/L)
BOD5 103.51 5.05 95.12 1161.40 81.64
COD 259.96 26.28 89.89 2731.64 219.97
SS 137.95 6.49 95.30 1389.83 148.54
NH3-N 21.37 1.02 95.23 234.39 22.83
TN 28.94 8.50 70.63 230.12 30.36
TP 3.16 0.18 94.30 37.92 3.70
Tab.2  Wastewater quality analysis of influent and effluent of WWTPs in Taihu Basin
Pollution N Average (mg/L) Intermediate (mg/L) Standard deviation (mg/L) Skewness Kurtosis Kolmogorov–Smirnov Sig. Shapiro–Wilk
Sig.
BOD5 204 103.51 97.21 52.98 1.341 2.963 0.000 0.000
COD 204 259.96 230.32 128.79 1.418 2.747 0.000 0.000
SS 204 137.95 122.17 72.81 1.127 2.021 0.000 0.000
NH3-N 204 21.37 21.78 7.09 -0.085 -0.328 0.200 0.107
TN 204 28.94 29.13 8.25 0.257 0.614 0.200 0.195
TP 204 3.16 2.80 1.56 1.097 1.395 0.000 0.000
Tab.3  Statistical analysis and normality test of influent quality
Fig.1  Distribution law of influent pollutants in WWTPs at Taihu Basin: COD (a), BOD5 (b), SS (c), TP (d), TN (e), NH3-N (f).
Fig.2  Proportional relationship of nutrients in influent water: BOD5/COD (a), SS/BOD5 (b), BOD5/TN (c), BOD5/TP (d).
Water Quality Index COD SS TN NH3-N TP
BOD5 y = 0.2994x + 26.09
R2 = 0.5397
y = 0.3276x + 58.75
R2 = 0.2064
y = 0.9107x + 77.584
R2 = 0.0205
y = 0.9557x + 83.509
R2 = 0.0167
y = 9.3509x + 74.378
R2 = 0.0774
COD y = 0.8661x + 140.48
R2 = 0.2397
y = 2.7144x + 181.41
R2 = 0.0205
y = 2.5296x + 205.89
R2 = 0.0194
y = 26.31x + 176.79
R2 = 0.1017
SS y = 1.7042x + 88.637
R2 = 0.0373
y = 2.5228x + 84.029
R2 = 0.0605
y = 10.04x + 106.22
R2 = 0.0464
TN y = 0.809x + 11.646
R2 = 0.4840
y = 2.3775x + 21.423
R2 = 0.2024
NH3-N y = 2.2134x + 14.378
R2 = 0.2372
Tab.4  Relevance and regression analysis of wastewater quality indicators
Fig.3  Relevance of water quality indicators in influent Water: COD (a), TN (b), SS (c), TP (d).
Sample (N) Minimum
(kWh/m3)
Maximum
(kWh/m3)
Average
(kWh/m3)
Standard Deviation
(kWh/m3)
Intermediate
(kWh/m3)
Kolmogorov-
Smirnov Sig.
Shapiro-Wilk
Sig.
204 0.16 1.32 0.458 0.225 0.385 0.158 0.051
Tab.5  Energy consumption characteristics of WWTPs in Taihu Basin in 2017
Scale
(104 m3/d)
AO AAO OD SBR MBR
<1 y = 0.436x0.1642
R2 = 0.0917
y = 0.4013x-0.141
R2 = 0.132
y = 0.3809x0.2475
R2 = 0.351
y = 0.2896x-0.279
R2 = 0.2275
1–5 y = 0.4675x1.0759
R2 = 0.6668
y = 0.5203x-0.253
R2 = 0.0747
y = 0.7683x-0.644
R2 = 0.6504
y = 0.3388x0.0163
R2 = 0.0009
y = 0.7922x-0.4
R2 = 0.3717
5–10 y = 1.372x0.9959
R2 = 1
y = 0.2917x-0.01
R2 = 0.0001
y = 0.4488x-0.066
R2 = 0.0226
y = 0.7525x-0.426
R2 = 0.6747
10–20 y = 0.3035x-0.007
R2 = 0.0001
y = 1.1595x0.9562
R2 = 1
y = 51.245x-1.858
R2 = 1
y = 0.92x-0.295
R2 = 0.3601
>20 y = 12.754x-1.137
R2 = 0.9965
Tab.6  Functional relation between influent volume and specific energy consumption
Fig.4  Relation between energy consumption and wastewater treatment volume: A/O process (a), AAO process (b), Oxidation ditch process (c), SBR process (d), MBR process (e), All (f).
Fig.5  Relation between COD specific energy consumption and COD reduction:<15 mg/L (a), 15–20 mg/L (b), 20–30 mg/L (c), 30–40 mg/L (d), 40–50 mg/L (e), All (f).
Effluent
(mg/L)
COD specific energy consumption (kWh/kg)
Average Minimum Maximum
<15 2.28 1.35 3.50
15–20 2.19 0.81 9.62
20–30 2.97 0.76 14.69
30–40 1.78 0.42 4.80
40–50 1.77 0.72 4.10
Tab.7  Relationship between effluent COD concentration and specific energy consumption
Fig.6  Relation between NH3-N specific energy consumption and NH3-N reduction: (a)<1 mg/L, (b) 1–3 mg/L, (c) 3–5 mg/L, (d) All.
Effluent
(mg/L)
NH3-N Specific Energy Consumption (kWh/kg)
Average Minimum Maximum
<1 35.78 8.70 150.12
1–3 37.40 8.68 134.85
3–5 21.35 7.79 88.36
Tab.8  Relationship between effluent NH3-N concentration and specific energy consumption
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