Today’s ecology is erected with miscellaneous framework. However, numerous sources deteriorate it, such as urban rivers that directly cause the environmental pollution. For chemical pollution abatement from urban water bodies, many techniques were introduced to rehabilitate the water quality of these water bodies. In this research, Bacterial Technology (BT) was applied to urban rivers escalating the necessity to control the water pollution in different places (Xuxi River (XXU); Gankeng River (GKS); Xia Zhang River (XZY); Fenghu and Song Yang Rivers (FSR); Jiu Haogang River (JHH)) in China. For data analysis, the physiochemical parameters such as temperature, chemical oxygen demand (COD), dissolved oxygen (DO), total phosphorus (TP), and ammonia nitrogen (NH3N) were determined before and after the treatment. Multicriteria Decision Making (MCDM) method was used for relative significance of different water quality on each station, based on fuzzy analytical hierarchy process (FAHP). The overall results revealed that the pollution is exceeding at “JHH” due to the limit of “COD” as critical water quality parameter and after treatment, an abrupt recovery of the rivers compared with the average improved efficiency of nutrients was 79%, 74%, 68%, and 70% of COD, DO, TP, and NH3N, respectively. The color of the river’s water changed to its original form and aquatic living organism appeared with clear effluents from them.
Massive ecosystem wide effects have been associated with their broad proliferation and toxin production [
To control environmental pollution would be a huge challenge for the planner and policy maker, due to treatment cost as well as the unbridled population acceleration. Here we need solution that efficiently resolves these critical pollution problems and could be used to rehabilitate the existing systems. In the last decades, some conventional technologies and methods have been developed and applied. To begin the application of reaeration (traditional technology) as adopting a series of weirs [
Ecofriendly and sustainable environmental demand is the hot and impressive topic due to public, economic, and legislation pressure. The best selection in complex framework is based on the sustainability of nutrient removal, biodegradation of suspended particles, and removal efficiency of the system. In this situation, the major preference is to adopt any system that is more reliable for energy consumptions, conversion of chemicals into biomass, complex infrastructure, and the repairing or maintenance cost of the system. Bacterial Technology (BT) provides a plenty of opportunities for effectively treating these issues [
Due to these considerations, we can adopt the new technique as BT with complete confidence. Their bacteria are usually hired to vitiate pollutants or nutrients into simple or nontoxic entity and produce suitable effluents [
In the past, the water quality index approach was considered as the best tool to determine the water quality of the water bodies [
Xuxi River (XXR) is situated in Wuxi City, Chang Nan District of China, geographically as (31°56.29′N and 120°28.14′E). Its upper stream starts from the Jing-Hang main canal and travels towards the ancient small canal. The selected river length for the experiment is 1360 m with 4.5 m of upstream surface average width and about the average depth of 1.4 m. River is under north subtropical humid zone and is marked by muddy sediments. This zone is facing four distinct seasons with the phenomenon of climatic influence circulation. Fenghu (FH) and Song Yong (SY) Rivers were selected, FH River is placed on the tail of the SY River, and both of them are situated in Wenzhou (Rui’an) City (120°39.13′E and 27°46.49′N), Zhejiang Province, China. Most of the Wenzhou area is placed under the typhoon zone, and the FH River is taking water from Wenruitang and Liangmian Rivers. The SY River is starting from cave bridge and falls directly into the FH River. The SY River length is about 280 m with the average breadth 5–18 m and 1–3 m water depth, and FH river length is about 740 m with the average breadth 6–15 m and 1 m water depth. For monitoring and sample collection of the experiment, the selected reaches of both rivers were divided into six points. The appearance of the river water color was blackish or greenish, and bubbles were blowing on the surface of water. These rivers are situated under the commercial and highly polluted area, and almost 2000 m3 sewage water enters into them [
The remaining sites of Gankeng River (22°33.24′N and 114°34.63′E), Xia Zhang River (31°26.49′N and 119°49.13′E), and Jiu Haogang River (30°18.59′N and 120°09.07′E) are placed in Shenzhen City, Yixing City, and Hangzhou City of China. The averaged physiographic conditions of these rivers are the same as the above rivers. On the basis of Chinese surface water quality standard, the rank or class of water quality in the source section was determined to be grade V (Table
Water quality parameters before BT and Chinese National Standard.
Sampling time | Monitoring project | |||||||
---|---|---|---|---|---|---|---|---|
Water temperature °C | pH | DO |
COD |
TP |
TN |
NH3N | ||
National standard GB3838-2002 | Class V index | 6–9 | 2.00 | 15.00 | 0.0 | 2.00 | 2.00 | |
A | 14:40 | 16.1 | 7.5 | 2.5 | 10.90 | 0.96 | 14.80 | 10.60 |
River water quality class | — | V | V | Inferior V | Inferior V | Inferior V | ||
B | 16:00 | 27.2 | 8.77 | 2.81 | 12.10 | 0.82 | 14.90 | 11.20 |
River water quality class | — | V | V | Inferior V | Inferior V | Inferior V |
Bacterial Technology (BT) is applied in a simple way, and its procedure is held under three kinds of material as Bacterial Clusterization (BC), Nature Liquid, and Biological Filter Media (4 : 3 : 3). BC is an important material that has a mixture of three types of ingredients as beneficial bacteria (bacilli,
By implementation of BT on site, the bacterial amount as BC is added to the selected points of each river as shown in Figure
Schematic diagram of the Xuxi River and sampling points during BT.
The sampling network was managed to cover the complete range along the inlet and outlet points of the rivers and determined the dominant point sources that have an impact on the water quality. Both of the sites are located under the area of population and industrialization, so the samples were collected from various depths (0.5 ft and >1.5 ft), at each monitoring station. The samples were collected from 8:30 AM to 4:30 PM during the period of experiment and 5 to 8 times in each month. To evaluate the water quality, the samples were kept in polyethylene bottles and stored in insulated ice cooler that were delivered to the laboratory on the same day. All the samples were saved at 4°C until the analysis and processing.
All mathematical and statistical calculation was analyzed by using Excel 2007 and MATLAB Fuzzy Logic Function. There have been various methods on Multiattribute Decision Making (MADM) and the most useful is AHP which especially is based on pairwise comparisons on a ratio scale [
AHP is an MCDM method that provides the hierarchical framework to illustrate the concern objective and developed the scale of priority based on the application judgment [
AHP for judgment.
We define the concern objectives and consequence of the unstructured problem and the recognition of the specific characteristics.
The AHP is based on the decision disintegration of the hierarchy unstructured problem that resides in the decision problem of the most important element [
Hierarchical structure of decision problem.
For pairwise comparison matrices of each element of the hierarchy structure are compared as follows:
For the decision of the relative significance between hierarchy elements in matrix
Scales for pairwise comparison [
1 | Equal importance |
3 | Moderate importance |
5 | Strong importance |
7 | Very strong importance |
9 | Extreme importance |
2, 4, 6, 8 | Intermediate values between adjacent scale values |
The relative weights of elements in each pairwise comparison matrix are determined by some methods like eigenvalue method. The relative weights (
The matrices consistency property is determined to ensure that the judgments of decision makers either are consistent or need more iterations. Consistency Index (CI) can be measured from the following equation:
The reciprocal matrix is generated from the random Consistency Index that would be known as the random index (RI). A sample size of 100 was used to generate the average RI for the matrices of order of 1–15 [
Random inconsistency indices [
Number of criteria | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|
||||||||||
RI | 0 | 0 | 0.58 | 0.9 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 |
At the end, the relative decisions of element weights are compiled to gain the whole alternatives rating as follows:
Despite the recognition of AHP often this method is censured to sufficiently handle its failure for the imprecision and latent uncertainty associated with the grading of the decision maker’s perception of exact values [
Fuzzy triangular Number.
In order to compose pairwise alternatives comparison under each criterion or benchmark, a triangular fuzzy comparison matrix is indicated as follows:
Total alternatives preferences and weights can be acquired from different method. In this study, these two approaches or techniques will be posed in renewal.
A fuzzy analytical hierarchy process (FAHP) has been developed to evaluate the status of water quality at the selected stations along each river under a Multicriteria Decision Making framework. A decision support mechanism has been introduced to select and prioritize stations, with specific reference to the universal principle as written below: Moving water tends to contain more DO than stagnant water. The DO concentration is inversely proportional to temperature. Health of water quality is based on the requirement of organism that lives in it. pH scale verifies the acidity and alkalinity of wastewater. The overenrichment of a body of water by nutrients like nitrates and phosphates is cause of eutrophication.
The various water quality parameters have been considered as criteria to evaluate water quality status at a given station of each project site. Pairwise comparisons of the criteria and the stations have been performed to assess water quality using linguistic variables.
The selected urban rivers are situated under the appalling environment and the river’s conditions were awful before the operation of BT. The huge amount of sewage was loaded directly and entered into these rivers. In addition, it is observed that there was not any preliminary facility to control or dump the domestic sewage. Therefore, the sewage is partially or directly a part of the urban river without any pretreatment. Under this alarming situation, the river’s color was changed into greenish representing the thick oil floats and debris. Therefore, in this sewer condition, any living organism in the river water could not exist.
BT has been applied and water samples from the selected points were collected before and after the treatment of the experiment. The physiochemical parameters were collected on the specific monitoring points on every site. The range, mean, and standard values of each parameter are in Table
Water quality data of experiment.
Parameters | GB2828-2002 (CNS) | XXU | GKS | XZY | FSR | JHH | |
---|---|---|---|---|---|---|---|
Tem. (°C) | 15–30 | Mean |
24.7 |
25.5 |
16.5 |
16.2 |
28.7 |
|
|||||||
DO (mg/L) | 2 | Mean |
1.69 |
1.79 |
1.83 |
1.14 |
3.4 |
|
|||||||
COD (mg/L) | 15 | Mean |
14.5 |
16.4 |
59.7 |
43.5 |
59.01 |
|
|||||||
NH3N (mg/L) | 2 | Mean |
15.21 |
16.87 |
22.49 |
13.59 |
21.44 |
|
|||||||
TP (mg/L) | 0 | Mean |
0.91 |
1.2 |
0.83 |
1.3 |
1.9 |
(a) Contrast diagram of Fenghu and Song Yang Rivers. (b) Contrast diagram of Xia Zhang River. (c) Contrast diagram of Xuxi River. (d) Contrast diagram of Jin Haogang River. (e) Contrast diagram of Gankeng River.
The fundamental statistics of these restoration experiments are based on 2760 total water samples (23 sampling stations × 4 sampling frequencies × 5 replications × 6 months) and are summarized in Table
FAHP developed a selection support tool that describes the pairwise priority of the station with the particular beneficial reference, such as domestic, aquatic status, irrigation, and recreational and industrial enterprises. The pairwise comparison matrix was formulated due to the variations and the complicity of the water quality parameters on each site, and the comparisons were accomplished based on the convincing of engineering results and each water quality parameter of all sites was formulated in Table
Pairwise comparison matrix of the various water quality parameters.
Parameters | DO | COD | TP | NH3N | Temperature |
---|---|---|---|---|---|
DO | 1 | 1/3 | 1 | 1/1.5 | 1/5 |
COD | 3 | 1 | 2 | 1/1.5 | 1 |
TP | 1 |
|
1 |
|
1 |
NH3N | 1.5 |
|
2 | 1 | 1/1.5 |
Temperature | 5 | 1 | 1.5 | 1.5 | 1 |
For the evaluation of the relative weights, the comparisons of all five locations with each parameter (Tables
Location-wise comparison matrix for temperature.
Site | XXU | GKS | XZY | FSR | JHH |
---|---|---|---|---|---|
XXU | 1.00 | 0.33 | 0.67 | 2.00 | 0.29 |
GKS | 3.00 | 1.00 | 1.49 | 4.00 | 0.67 |
XZY | 1.50 | 0.67 | 1.00 | 2.00 | 1.00 |
FSR | 0.50 | 0.25 | 0.50 | 1.00 | 0.33 |
JHH | 3.50 | 1.50 | 3.00 | 3.00 | 1.00 |
Location-wise comparison matrix for DO.
Site | XXU | GKS | XZY | FSR | JHH |
---|---|---|---|---|---|
XXU | 1.00 | 1.50 | 0.33 | 0.29 | 0.57 |
GKS | 0.67 | 1.00 | 0.29 | 0.50 | 1.00 |
XZY | 3.00 | 3.50 | 1.00 | 4.00 | 1.00 |
FSR | 3.50 | 2.00 | 0.25 | 1.00 | 3.00 |
JHH | 1.75 | 1.00 | 0.33 | 0.33 | 1.00 |
Location-wise comparison matrix for COD.
Site | XXU | GKS | XZY | FSR | JHH |
---|---|---|---|---|---|
XXU | 1.00 | 2.00 | 4.00 | 0.80 | 4.00 |
GKS | 0.50 | 1.00 | 0.33 | 0.59 | 4.00 |
XZY | 0.25 | 3.00 | 1.00 | 0.67 | 1.00 |
FSR | 1.25 | 1.70 | 1.50 | 1.00 | 2.00 |
JHH | 0.25 | 0.25 | 0.25 | 0.50 | 1.00 |
Location-wise comparison matrix for NH3N.
Site | XXU | GKS | XZY | FSR | JHH |
---|---|---|---|---|---|
XXU | 1.00 | 0.80 | 0.40 | 1.33 | 0.67 |
GKS | 1.25 | 1.00 | 0.67 | 2.00 | 0.33 |
XZY | 2.50 | 1.50 | 1.00 | 9.09 | 1.00 |
FSR | 0.75 | 0.50 | 0.11 | 1.00 | 0.40 |
JHH | 1.50 | 3.00 | 0.40 | 2.50 | 1.00 |
Location-wise comparison matrix for TP.
Site | XXU | GKS | XZY | FSR | JHH |
---|---|---|---|---|---|
XXU | 1.00 | 4.00 | 1.49 | 0.67 | 0.20 |
GKS | 0.25 | 1.00 | 0.67 | 0.29 | 0.33 |
XZY | 0.67 | 1.50 | 1.00 | 0.67 | 1.00 |
FSR | 1.50 | 3.50 | 1.50 | 1.00 | 0.67 |
JHH | 5.00 | 3.00 | 0.25 | 1.50 | 1.00 |
The main concern in this present contribution is to explain the actual BT function to mitigate the pollution from urban water bodies. AHP based on FAHP results are applied to the ranking of the water quality parameters (Table
Criteria ranking of water quality parameters.
Parameters | Scores | Ranking |
---|---|---|
Temperature (°C) | 0.305 | 1 |
COD (mg/L) | 0.277 | 2 |
DO (mg/L) | 0.204 | 3 |
TP (mg/L) | 0.116 | 4 |
NH3N (mg/L) | 0.097 | 5 |
Criteria ranking of sites (overall inconsistency = 0.076).
Site | Scores | Ranking |
---|---|---|
JHH | 0.310 | 1 |
FSR | 0.241 | 2 |
XXU | 0.191 | 3 |
XZY | 0.175 | 4 |
GKS | 0.083 | 5 |
Ranking criteria of each water quality parameter in each location.
After the evaluation of the current status from the results, the actual pollution status of each site after the BT operation is revealed. Figure
Temperature is the major concern under the metabolism process of the bacteria, with higher temperature during the summer (20–30°C) and lower values in the winter season (10–18°C). The plus advantage of BT does not require destruction of an already built system. BT has no effect on the natural environment because it does not involve the use of chemicals. Therefore, it is helpful for friendly ecology. It is free from all other issues, as high construction and maintenance costs can be a huge burden to organization and policy makers.
In view of this, with revolutionary calculations, the adoption of BT has been concluded to be the most convenient approach for developing countries [
In order to rehabilitate the urbanized water bodies as lakes, rivers, and streams, BT is sustainable and reliable for public health with no maintenance and further general costs to minimize the traditional system. In this study, we demonstrate the interpretation of the water pollution problems of a complex dataset through MCDM techniques, because chemometric research enables us to discuss the similarities and dissimilarities along the observing stations among the variables that could not be clearly visible for assessment of the analytical data in a table. This research emphasized that the BT offers an ingenious and innovative solution for rehabilitation of the urban water bodies up to the suitable water quality. BT is efficient due to its simplicity, being economically affordable and reproducible on any scale of the operation; hence, it can provide tenable and long-term solution to the various water related pollution problems all over the world.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This research is held under the project of “Environment Protection and Microbial Water Purification Demonstration Project.” The authors thank “Shenzhen Berson Biotechnology Co., Ltd.” for supporting and helping them to complete the experiment. The authors are also grateful to all anonymous reviewers and proofreader that have helped to improve the quality of this paper.