A framework of characteristics identification and source apportionment of water pollution in a river: a case study in the Jinjiang River, China

2012 ◽  
Vol 65 (11) ◽  
pp. 2071-2078 ◽  
Author(s):  
Haiyang Chen ◽  
Yanguo Teng ◽  
Jinsheng Wang
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Source Apportionment ◽  
Comprehensive Evaluation ◽  
Principal Component ◽  
Anthropogenic Pollution ◽  
Ammonia Nitrogen ◽  
Support Vector ◽  
Jinjiang River

A framework for characteristics identification and source apportionment of water pollution in the Jinjiang River of China was proposed in this study for evaluation. A total of 114 water samples which were generated between May 2009 and September 2010 at 13 sites were collected and analysed. First, support vector machine (SVM) and water quality pollutant index (WQPI) were used for water quality comprehensive evaluation and identifying characteristic contaminants. Later, factor analysis with nonnegative constraints (FA-NNC) was employed for source apportionment. Finally, multi-linear regression of the absolute principal component score (APCS/MLR) was applied to further estimate source contributions for each characteristic contaminant. The results indicated that the water quality of the Jinjiang River was mainly at the third level (65.79%) based on national surface water quality permissible standards in China. Ammonia nitrogen, total phosphorus, mercury, iron and manganese were identified as characteristic contaminants. Source apportionment results showed that industrial activities (63.16%), agricultural non-point source (16.50%) and domestic sewage (12.85%) were the main anthropogenic pollution sources which were influencing the water quality of Jinjiang River. This proposed method provided a helpful framework for conducting water pollution management in aquatic environment.

scholarly journals Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China

2020 ◽  
Vol 17 (8) ◽  
pp. 2942 ◽  
Author(s):  
Wenjie Yang ◽  
Yue Zhao ◽  
Dong Wang ◽  
Huihui Wu ◽  
Aijun Lin ◽  
...  
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Surface Water ◽  
Safety Management ◽  
Temporal Distribution ◽  
Surface Water Quality ◽  
Principal Component ◽  
Organic Pollution ◽  
Sampling Point

This study was aimed at assessing the spatial and temporal distribution of surface water quality variables of the Xin’anjiang River (Huangshan). For this purpose, 960 water samples were collected monthly along the Xin’anjiang River from 2008 to 2017. Twenty-four water quality indicators, according to the environmental quality standards for surface water (GB 3838-2002), were detected to evaluate the water quality of the Xin’anjiang River over the past 10 years. Principal component analysis (PCA) was used to comprehensively evaluate the water quality across eight monitoring stations and analyze the sources of water pollution. The results showed that all samples could be analyzed by three main components, which accounted for 87.24% of the total variance. PCA technology identified important water quality parameters and revealed that nutrient pollution and organic pollution are major latent factors which influence the water quality of Xin’anjiang River. It also showed that agricultural activities, erosion, domestic, and industrial discharges are fundamental causes of water pollution in the study area. It is of great significance for water quality safety management and pollution control of the Xin’anjiang River. Meanwhile, the inverse distance weighted (IDW) method was used to interpolate the PCA comprehensive score. Based on this, the temporal and spatial structure and changing characteristics of water quality in the Xin’anjiang River were analyzed. We found that the overall water quality of Xin’anjiang River (Huangshan) was stable from 2008 to 2017, but the pollution of the Pukou sampling point was of great concern. The results of IDW helped us to identify key areas requiring control in the Xin’anjiang River, which pointed the way for further delicacy management of the river. This study proved that the combination of PCA and IDW interpolation is an effective tool for determining surface water quality. It was of great significance for the control of water pollution in Xin’anjiang River and the reduction of eutrophication pressure in Thousand Island Lake.

scholarly journals Vulnerability Assessment and Application of Bacterial Technology on Urban Rivers for Pollution Eradication

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Sarfraz Hashim ◽  
Xie Yuebo ◽  
Fiaz Ahmad ◽  
Chaudhry Arslan ◽  
Muhammad Saifullah
Keyword(s):  
Water Quality ◽  
Point Source ◽  
Oxygen Demand ◽  
Principal Component ◽  
Aquatic Organism ◽  
Ammonia Nitrogen ◽  
Complex Data ◽  
Urban Rivers ◽  
Source Information

To protect against the environmental pollution, the present research was undertaken to enumerate the Bacterial Technologies (BTs) on the restoration of polluted urban rivers, that is, Fenghu-Song Yang River (FSR) and Xuxi River (XXR). Experimental research accounted for the physiochemical parameters (pH; temperature; dissolved oxygen (DO); chemical oxygen demand (COD); total phosphorus (TP); total nitrogen (TN); and ammonia nitrogen (NH3N)) before and after the BT operation. The results declared that the BT is efficient to restore the polluted rivers up to reliable condition. These results were analyzed by using multivariate statistical techniques (principal component analysis (PCA) and cluster analysis (CA)). These techniques interpreted the complex data sets and expressed the point source information about the water quality of these rivers at SA5, SA6, and SB3 under highly polluted regions. For better understanding, water quality index (WQI) was applied to compute the single numeric value. WQI results are evidence of the above results which prove the water quality of both rivers faced under outrageous condition (below 50 WQI scores) before the BT treatment, but, after the treatment, the rivers were restored from fair to good level (above 50 WQI scores) and overall output of these scores was quite similar to detect the point source of pollution. These results described an abrupt recovery of the urban rivers up to reliable condition for aquatic organism and clear effluents from the rivers.

Dynamics of Water Quality in the Middle and Lower Reaches of the Weihe River

2014 ◽  
Vol 955-959 ◽  
pp. 3245-3258
Author(s):  
Juan Deng ◽  
Dong Feng Hu ◽  
Zhou Ping Shangguan
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Yellow River ◽  
Oxygen Demand ◽  
Ammonia Nitrogen ◽  
Pollutant Concentrations ◽  
Weihe River ◽  
Pollutant Discharge ◽  
Major Factors

The Weihe River is an upstream tributary of the Yellow River that is heavily influenced by excessive pollutant discharge. In this study, the water quality of the Weihe River was studied based on five water quality indices: CODMn (chemical oxygen demand), BOD5 (biochemical oxygen demand), NH3-N (ammonia nitrogen), DO (dissolved oxygen), and PPI (potassium permanganate index), using monitoring data collected from 13 river sections in the middle and lower reaches of the river from 2001 to 2010. Our results showed that the water quality tended to deteriorate from the upper to the lower reaches of the river. Additionally, CODMn, NH3-N and PPI were found to be the major factors resulting in water pollution over time in all river sections, but the pollutant concentrations with the interannual variability differed in every section. Therefore, many efficient and reasonable measures should be carried out to control water pollution and improve water quality in the Weihe River.

Wetland Water Quality Evaluation Research by Method of Fuzzy Comprehensive Evaluation

2014 ◽  
Vol 955-959 ◽  
pp. 1479-1483
Author(s):  
Juan Chen
Keyword(s):  
Water Quality ◽  
Comprehensive Evaluation ◽  
Evaluation Research ◽  
Fuzzy Comprehensive Evaluation ◽  
Ammonia Nitrogen ◽  
Index Method ◽  
Wetland Water ◽  
Wetland Water Quality ◽  
Phosphorus And Potassium

This thesis selects six factors, including DO, COD, BOD5, ammonia nitrogen, total phosphorus and potassium permanganate as monitoring indexes to evaluate the wetland water quality of Huangjia Lake in Wuhan City with the method of fuzzy comprehensive evaluation referring to Environmental Quality Standards for Surface Water. The result is basically identical with that of single factor index method. Evaluation results show that the wetland water quality in Hubei College of Traditional Chinese Medicine and Wuhan University of Science and Technology is of good quality with slight pollution.

scholarly journals A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1411
Author(s):  
José Luis P. Calle ◽  
Marta Ferreiro-González ◽  
Ana Ruiz-Rodríguez ◽  
Gerardo F. Barbero ◽  
José Á. Álvarez ◽  
...  
Keyword(s):  
Random Forest ◽  
Raw Materials ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Raw Material ◽  
Support Vector ◽  
Protected Designation Of Origin ◽  
Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

Water-Quality Assessment of Lv-Tang River in Zhanjiang, China

2013 ◽  
Vol 295-298 ◽  
pp. 755-758 ◽  
Author(s):  
Ya Yun Liu ◽  
Zhi Hong Li ◽  
Xiao Jian Liang ◽  
Yan Peng Lin ◽  
Rong Hao Wu ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Pollution Index ◽  
Ammonia Nitrogen ◽  
Single Parameter ◽  
Water Quality Parameter ◽  
National Quality

Based on the water quality investigation data of December in 2010, the water environment quality of Lv-tang River in Zhanjiang national urban wetland park was assessed using single water quality parameter model and integrated water quality index model. The results show that the water quality of Lv-tang River is worse than the national quality standards for Grade V. The water is polluted seriously. The main pollutants are total nitrogen (TN), ammonia nitrogen (NH3-N) and chemical oxygen demand CODCr with their average concentrations of 60.49 mg/L, 30.57 mg/L and 227.38mg/L, respectively. The averages of their single parameter pollution index are 30.25 , 19.79 and 8.74. The average of single parameter pollution index of the river is 8.23 which indicated that the river belongs to heavy pollution zone. The integrated water quality index was 22.5 showing that the river belongs to serious pollution zone.

scholarly journals Long-Term River Water Quality Trends and Pollution Source Apportionment in Taiwan

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1394 ◽  
Author(s):  
Marsha Putri ◽  
Chao-Hsun Lou ◽  
Mat Syai’in ◽  
Shang-Hsin Ou ◽  
Yu-Chun Wang
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Heavy Metal ◽  
Cluster Analysis ◽  
River Water ◽  
Principal Component ◽  
Pollution Level ◽  
Metal Levels ◽  
Metal Monitoring

The application of multivariate statistical techniques including cluster analysis and principal component analysis-multiple linear regression (PCA-MLR) was successfully used to classify the river pollution level in Taiwan and identify possible pollution sources. Water quality and heavy metal monitoring data from the Taiwan Environmental Protection Administration (EPA) was evaluated for 14 major rivers in four regions of Taiwan with the Erren River classified as the most polluted river in the country. Biochemical oxygen demand (6.1 ± 2.38), ammonia (3.48 ± 3.23), and total phosphate (0.65 ± 0.38) mg/L concentration in this river was the highest of the 14 rivers evaluated. In addition, heavy metal levels in the following rivers exceeded the Taiwan EPA standard limit (lead: 0.01, copper: 0.03, and manganese: 0.03) mg/L concentration: lead-in the Dongshan (0.02 ± 0.09), Jhuoshuei (0.03 ± 0.03), and Xinhuwei Rivers (0.02 ± 0.02) mg/L; copper: in the Dahan (0.036 ± 0.097), Laojie (0.06 ± 1.77), and Erren Rivers are (0.05 ± 0.158) mg/L; manganese: in all rivers. A total 72% of the water pollution in the Erren River was estimated to originate from industrial sources, 16% from domestic black water, and 12% from natural sources and runoff from other tributaries. Our research demonstrated that applying PCA-MLR and cluster analysis on long-term monitoring water quality would provide integrated information for river water pollution management and future policy making.

Classification and Prediction of Goldfish Population and Water Quality Using a Potentiometric E-Tongue

2017 ◽  
Vol 60 (4) ◽  
pp. 1037-1044
Author(s):  
Zhenbo Wei ◽  
Yu Zhao ◽  
Jun Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Pattern Recognition ◽  
Comprehensive Evaluation ◽  
Back Propagation ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Pattern Recognition Methods

Abstract. In this study, a potentiometric E-tongue was employed for comprehensive evaluation of water quality and goldfish population with the help of pattern recognition methods. Four water quality parameters, i.e., pH and concentrations of dissolved oxygen (DO), nitrite (NO2-N), and ammonium (NH3-N), were tested by conventional analysis methods. The differences in water quality parameters between samples were revealed by two-way analysis of variance (ANOVA). The cultivation days and goldfish population were classified well by principal component analysis (PCA) and canonical discriminant analysis (CDA), and the distribution of each sample was clearer in CDA score plots than in PCA score plots. The cultivation days, goldfish population, and water parameters were predicted by a T-S fuzzy neural network (TSFNN) and back-propagation artificial neural network (BPANN). BPANN performed better than TSFNN in the prediction, and all fitting correlation coefficients were >0.90. The results indicated that the potentiometric E-tongue coupled with pattern recognition methods could be applied as a rapid method for the determination and evaluation of water quality and goldfish population. Keywords: Classify, E-tongue, Goldfish water, Prediction.

scholarly journals Impact of Partially Treated Wastewater on Downstream Water Quality of Notwane River in Botswana

2018 ◽  
pp. 1-9
Author(s):  
Gilbert K. Gaboutloeloe ◽  
Gugu Molokwe ◽  
Benedict Kayombo
Keyword(s):  
Water Quality ◽  
Pearson Correlation ◽  
Oxygen Demand ◽  
Ammonia Nitrogen ◽  
Treated Wastewater ◽  
Nitrate N ◽  
River Stretch ◽  
Ph Range ◽  
The Impact

The impact of partially treated wastewater on the water quality of Notwane river stretch in the Gaborone region of Botswana was investigated. Water samples collected at effluent discharge point and three other sampling sites downstream were analyzed for pH, temperature, Biological Oxygen Demand (BOD5), Ammonia-nitrogen (Ammonia-N) and Nitrate-nitrogen (Nitrate-N). Sampling was conducted bi-weekly between February 2013 and April 2013. The ranges of measured parameters were:  pH (7.6-8.5), temperature (22-23ºC), BOD5 (11.2-27.0 mg/l), Ammonia-N (2.4-60.5 mg/l), Nitrate-N (20.6-28.6 mg/l). Analysis of variance, Games-Howel multiple comparisons and Pearson correlation were used to separate variable means. The results signal river non-point pollution due to runoff inflow of organics mainly from land use and domestic waste dumping by nearby dwellings. Temperature, BOD5, and pH range values were all within the Botswana Bureau of Standards (BOBS) limit while the maximum Ammonia-N and Nitrate-N were above BOBS limit by 50.5 mg/l and 6.6 mg/l, respectively. Regulations on indiscriminate waste dumping and discharge standards adherence should be enforced.

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