scholarly journals Positive effects of COVID-19 lockdown on river water quality: evidence from River Damodar, India

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Baisakhi Chakraborty ◽  
Biswajit Bera ◽  
Partha Pratim Adhikary ◽  
Sumana Bhattacharjee ◽  
Sambhunath Roy ◽  
...  
Keyword(s):  
Water Quality ◽  
River Water ◽  
Ecological Risk ◽  
Risk Index ◽  
Principal Component ◽  
Potential Ecological Risk ◽  
River Water Quality ◽  
Trophic State Index ◽  
River Health ◽  
Positive Effects

AbstractThe global economic activities were completely stopped during COVID-19 lockdown and continuous lockdown partially brought some positive effects for the health of the total environment. The multiple industries, cities, towns and rural people are completely depending on large tropical river Damodar (India) but in the last few decades the quality of the river water is being significantly deteriorated. The present study attempts to investigate the river water quality (RWQ) particularly for pre- lockdown, lockdown and unlock period. We considered 20 variables per sample of RWQ data and it was analyzed using novel Modified Water Quality Index (MWQI), Trophic State Index (TSI), Heavy Metal Index (HMI) and Potential Ecological Risk Index (RI). Principal component analysis (PCA) and Pearson’s correlation (r) analysis are applied to determine the influencing variables and relationship among the river pollutants. The results show that during lockdown 54.54% samples were brought significantly positive changes applying MWQI. During lockdown, HMI ranged from 33.96 to 117.33 with 27.27% good water quality which shows the low ecological risk of aquatic ecosystem due to low mixing of toxic metals in the river water. Lockdown effects brought river water to oligotrophic/meso-eutrophic condition from eutrophic/hyper-eutrophic stage. Rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for restoration of river health from huge anthropogenic stress.

scholarly journals Heavy Metals Distribution, Sources, and Ecological Risk Assessment in Huixian Wetland, South China

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 431
Author(s):  
Liangliang Huang ◽  
Saeed Rad ◽  
Li Xu ◽  
Liangying Gui ◽  
Xiaohong Song ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Ecological Risk ◽  
South China ◽  
Ecological Risk Assessment ◽  
Risk Index ◽  
Pollution Index ◽  
Principal Component ◽  
Potential Ecological Risk ◽  
Anthropogenic Sources

This research has focused on the source identification, concentration, and ecological risk assessment of eight heavy metals in the largest karst wetland (Huixian) of south China. Numerous samples from superficial soil and sediment within ten representative landuse types were collected and examined, and the results were analyzed using multiple methods. Single pollution index (Pi) results were underpinned by the Geoaccumulation index (Igeo) method, in which Cd was observed as the priority pollutant with the highest contamination degree in this area. As for the most polluted landuse type, via applying Nemerow’s synthetical contamination index (PN) and Potential ecological risk index (RI), the river and rape field posed the highest ecological risks, while moderate for the rest. To quantify the drivers of the contaminants, a principal component analysis (PCA) was carried out and weathering of the watershed’s parent carbonate rocks was found to be the main possible origin, followed by anthropogenic sources induced by agricultural fertilizer. Considering the impacts of these potentially toxic elements on public health, the results of this study are essential to take preventive actions for environmental protection and sustainable development in the region.

scholarly journals Study of the Water Quality of a Tropical Reservoir

2018 ◽  
Author(s):  
Alberto Quevedo-Castro ◽  
Jesús L. López ◽  
Jesus Gabriel Rangel-Peraza ◽  
Erick Bandala ◽  
Yaneth Bustos-Terrones
Keyword(s):  
Water Quality ◽  
Ecological Risk ◽  
Trophic State ◽  
Risk Index ◽  
Trophic State Index ◽  
Tropical Reservoir ◽  
State Index ◽  
Using Data

A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level and ecological risk were assessed through the water Quality Index (WQINSF-BROWN), Trophic State Index (TSICARLSON) and the Ecological Risk Index (RIHAKANSON). Using data from physical, chemical and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQINSF-BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state classified as “Mesotrophic” (TSIGENERAL-AVERAGE = 43.04). The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. Through this type of applied methodologies will help as decision making tools in the dam, as well as for application in other dams in the region.

scholarly journals Implications of Soil Potentially Toxic Elements Contamination, Distribution and Health Risk at Hunan’s Xikuangshan Mine

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1532
Author(s):  
Jing Bai ◽  
Wen Zhang ◽  
Weiyin Liu ◽  
Guohong Xiang ◽  
Yu Zheng ◽  
...  
Keyword(s):  
Health Risk ◽  
Ecological Risk ◽  
Toxic Elements ◽  
Risk Index ◽  
Principal Component ◽  
Mining Area ◽  
Potential Ecological Risk ◽  
Parent Material ◽  
Potentially Toxic Elements ◽  
Hunan Province

A field survey was conducted to determine the pollution grade, sources, potential ecological risk, and health risk of soil potentially toxic elements (PTEs) in Xikuangshan Mine (XKS), the largest antimony (Sb) deposit in the world. A total of 106 topsoil samples were collected from 6 sites in XKS to measure the concentrations of PTEs Cr, Zn, Cd, Pb, As, Hg, and Sb. The results show that the average concentrations of these elements at all six sites were generally greater than their corresponding background values in Hunan province, especially Sb, Hg, and As. Correlation and principal component analyses suggested that Cd, Zn, Pb, Hg, and Sb were primarily released from mining and other industrial and human activities, while Cr and As were mainly impacted by the parent material from pedogenesis. A risk index analysis showed that, overall, sites were at very high ecological risk, and Sb is the highest ecological risk factor, followed by Cd and Hg. According to health risk assessment, oral ingestion is the main non-carcinogenic and carcinogenic risk exposure route. The higher potentially non-carcinogenic and carcinogenic risks happen to the local children who live in the vicinity of mining area. It revealed that the mining and smelting processes of XKS have negatively influenced the local people, therefore, we should pay increasing attention to this practical issue and take effective measures to protect the ecology of XKS.

scholarly journals Improved Principal Component-Fuzzy Comprehensive Assessment Coupling Model for Urban River Water Quality: A Case Study in Chongqing, China

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1375
Author(s):  
Siyuan Zhao ◽  
Jing Chen ◽  
Qiu Jin ◽  
Huazu Liu ◽  
Wei Yang ◽  
...  
Keyword(s):  
Water Quality ◽  
River Water ◽  
Principal Component ◽  
Coupling Model ◽  
Domestic Sewage ◽  
Comprehensive Assessment ◽  
River Water Quality ◽  
Urban River ◽  
Fuzzy Comprehensive Assessment

An improved principal component-fuzzy comprehensive assessment coupling model for urban river water quality is proposed, which fully considers the influence of water quality and quantity. This model can not only choose the key indexes, but also specify the spatial variation and class of water quality. This proposed model was used to assess the water quality of the Qingshui and Fenghuang streams in Chongqing, China. Data of twelve indexes used in the assessment were collected from 17 monitoring points. The assessment results show that the key indexes include TN, TP, NH3-N, CODcr, pH, DO and velocity. Water quality of 14 monitoring points is classified as class Bad V, and that of the remaining points is class V. Mainly affected by the deposition of garbage and discharge of domestic sewage, water quality of the midstream is the worst. The upstream is mainly influenced by farmland non-point source pollution and rural domestic sewage pollution. The downstream is close to the scenic area, and environmental control measures such as river dredging and artificial aeration are regularly carried out. The water quality of it is the best. The results provide valuable information that allow local environmental departments to discover the source of pollutant and formulate water resource management strategies.

Application of Principal Component Analysis for the Estimation of Source of Heavy Metal Contamination in Sugarcane Soil

2014 ◽  
Vol 651-653 ◽  
pp. 1402-1409
Author(s):  
Gui Ping Xu ◽  
Xiao Fei Wang ◽  
Li Jun Chen
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Principal Component Analysis ◽  
Ecological Risk ◽  
Metal Contamination ◽  
Heavy Metal Contamination ◽  
Risk Index ◽  
Principal Component ◽  
Component Analysis ◽  
Potential Ecological Risk

Concentrations of heavy metals in sugarcane soil of Guangxi were determined and the potential ecological risk index was used simultaneously to evaluate the extent of heavy metals enrichment contamination. Results showed that the pollution extent of heavy metals in sugarcane soil by potential ecological risk followed the order: Cd>Pb>Cu>Zn, Cu and Zn were slightly polluted, with small potential ecological harm, while Pb and Cd were above moderately polluted, with heavy potential ecological harm. Principal component analysis was applied to estimate the sources of heavy metals contamination, the results indicated that the first two components accounted for 61.016% and 26.920% of the total variance respectively, 4 kinds of heavy metal elements had similar sources, tailing dam lead-zinc concentrator upstream along the coast was the main sources of heavy metal contamination.

Distribution Characteristics and Ecological Risk Assessment of Arsenic in the Surface Sediment of Bohai Sea

2012 ◽  
Vol 610-613 ◽  
pp. 932-935
Author(s):  
Lian Kai Zhang ◽  
Hui Yang ◽  
Wei Jin
Keyword(s):  
River Water ◽  
Ecological Risk ◽  
Significant Positive Correlation ◽  
Risk Index ◽  
Arsenic Concentration ◽  
Potential Ecological Risk ◽  
Ecological Risk Index ◽  
Sampling Points ◽  
Estuary Sediment ◽  
Sediment Ph

Arsenic is a carcinogen to both humans and animals. Thirteen typical surface sediment samples were taken at Tanghe and Daihe in Qinhuangdao, April, 2011. Hydride generation atomic fluorescence spectrometry (HG-AFS) was used to analyze arsenic (As) concentration. The correlations of sediment arsenic and sediment organic matter (SOM), pH, river water arsenic were discussed. Index of geoaccumulation (Igeo) and potential ecological risk index were cited to assess the arsenic pollution level and its potential ecological risk. The results show that, arsenic in river water sediment, estuary sediment and coast sediment of Daihe are lower than the average level of other Chinese rivers. Arsenic Igeo of these sediments are cleanliness. However, Arsenic concentration in the sampling points of Tanghe is higher than the average level of domestic rivers except river water sampling points. Their Igeo are light pollution. The potential ecological risk index of the two rivers are slight ecological harm. Arsenic concentration of different sampling points in the two rivers distributes as: estuary sediment As>coast sediment As> river water sediment As. The correlation among sediment arsenic, water arsenic, SOM and sediment pH are: 1) Arsenic in sediment has a extremely significant positive correlation with that in water at p<0.01; 2) Sediment arsenic shows a significant positive correlation with SOM at p<0.05; 3) However, there is a negative correlation between sediment pH and sediment arsenic.

The ecological risk assessment and suggestions on heavy metals in river sediments of Jinan

2017 ◽  
Vol 76 (8) ◽  
pp. 2177-2187 ◽  
Author(s):  
Xu Wang ◽  
Lijun Ren ◽  
Fengchao Jiao ◽  
Wenjie Liu
Keyword(s):  
Heavy Metals ◽  
Ecological Risk ◽  
Risk Index ◽  
River Sediments ◽  
Principal Component ◽  
Potential Ecological Risk ◽  
Moderate Degree ◽  
Multivariate Statistical ◽  
Ecological Risk Index ◽  
Heavy Metals Pollution

The concentrations of eight heavy metals (Cr, Hg, As, Pb, Cd, Cu, Zn, Ni) in six river sediment samples were collected for evaluation of the degree of the heavy metals pollution distribution and ecological risk of three main rivers' sediments in Jinan. Multivariate statistical techniques were used to determine the most common pollution sources. The results illustrated that all of the metals in Damatou and Xinfengzhuang sections of the Xiaoqing River were much higher than the background value, and the level of potential ecological risk index was very high. The remaining four sections had a low or moderate degree of ecological risk. Principal component analysis (PCA) showed that all metals, with the exception of As, formed the first component explaining 86.85% of the total variance and industry sources could be considered as the first component, while As alone could be the second component, representing agricultural source. The elements Cr and Zn were grouped together while the remaining six metals formed a separate category. Among all heavy metals, Hg and Cd were the most significant contributors to the pollution. Therefore, the prevention of pollution should pay more attention to controlling the sources, especially Hg and Cd.

Predict River Water Quality Based on Bayesian Hierarchical Model

2013 ◽  
Vol 409-410 ◽  
pp. 208-213
Author(s):  
Mei Liu ◽  
Wen Qian Shi ◽  
Jun Lu
Keyword(s):  
Water Quality ◽  
River Water ◽  
Hierarchical Model ◽  
Eastern China ◽  
Principal Component ◽  
Bayesian Hierarchical Model ◽  
River Water Quality ◽  
Agricultural Watershed ◽  
Bayesian Hierarchical ◽  
Five Factors

According to many uncertain problems of river eutrophication, a Bayesian hierarchical model was established to predict water quality. We applied the hierarchical method to assess river water quality in an agricultural watershed in eastern China. The procedure followed was developing a hierarchical model relating eutrophication response - the level of chlorophyll (Chla). Through Principal Component Analysis (PCA), five factors strong related with Chla were selected to establish Bayesian hierarchical model to predict the water quality. Results showed that Bayesian hierarchical model was very realistic. Furthermore, in Bayesian perspective, predictions expressed as probabilities, rather than a single value, involving more uncertainty information, can be essential to environmental management and decision-making.

Sign in / Sign up

Export Citation Format

Share Document