Spatial distribution and sources of dissolved trace metals in surface water of the Wei River, China

2013 ◽  
Vol 67 (4) ◽  
pp. 817-823 ◽  
Author(s):  
Li Jing ◽  
Li Fadong ◽  
Liu Qiang ◽  
Song Shuai ◽  
Zhao Guangshuai
Keyword(s):  
Drinking Water ◽  
Trace Metals ◽  
Trace Metal ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Environmental Data ◽  
Multivariate Statistical ◽  
Drinking Water Standard ◽  
The Impact ◽  
Wei River

For this study, 34 water samples were collected along the Wei River and its tributaries. Multivariate statistical analyses were employed to interpret the environmental data and to identify the natural and anthropogenic trace metal inputs to the surface waters of the river. Our results revealed that Zn, Se, B, Ba, Fe, Mn, Mo, Ni and V were all detected in the Wei River. Compared to drinking water guidelines, the primary trace metal pollution components (B, Ni, Zn and Mn) exceeded drinking water standard levels by 47.1, 50.0, 44.1 and 26.5%, respectively. Inter-element relationships and landscape features of trace metals conducted by hierarchical cluster analysis (HCA) identified a uniform source of trace metals for all sampling sites, excluding one site that exhibited anomalous concentrations. Based on the patterns of relative loadings of individual metals calculated by principal component analysis (PCA), the primary trace metal sources were associated with natural/geogenic contributions, agro-chemical processes and discharge from local industrial sources. These results demonstrated the impact of human activities on metal concentrations in the Wei River.

scholarly journals Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films

2021 ◽  
Vol 11 (13) ◽  
pp. 5895
Author(s):  
Kristina Serec ◽  
Sanja Dolanski Babić
Keyword(s):  
Thin Films ◽  
Learning Algorithm ◽  
Principal Component Regression ◽  
Principal Component ◽  
Conformational Transitions ◽  
Cancer Diagnostics ◽  
Dna Conformation ◽  
Support Vector ◽  
Multivariate Statistical ◽  
The Impact

The double-stranded B-form and A-form have long been considered the two most important native forms of DNA, each with its own distinct biological roles and hence the focus of many areas of study, from cellular functions to cancer diagnostics and drug treatment. Due to the heterogeneity and sensitivity of the secondary structure of DNA, there is a need for tools capable of a rapid and reliable quantification of DNA conformation in diverse environments. In this work, the second paper in the series that addresses conformational transitions in DNA thin films utilizing FTIR spectroscopy, we exploit popular chemometric methods: the principal component analysis (PCA), support vector machine (SVM) learning algorithm, and principal component regression (PCR), in order to quantify and categorize DNA conformation in thin films of different hydrated states. By complementing FTIR technique with multivariate statistical methods, we demonstrate the ability of our sample preparation and automated spectral analysis protocol to rapidly and efficiently determine conformation in DNA thin films based on the vibrational signatures in the 1800–935 cm−1 range. Furthermore, we assess the impact of small hydration-related changes in FTIR spectra on automated DNA conformation detection and how to avoid discrepancies by careful sampling.

scholarly journals Significance of building and plumbing specifics on trace metal concentrations in drinking water

1991 ◽  
Vol 18 (6) ◽  
pp. 893-903 ◽  
Author(s):  
Inderjit Singh ◽  
Donald S. Mavinic
Keyword(s):  
Drinking Water ◽  
Trace Metals ◽  
Trace Metal ◽  
Water Samples ◽  
First Flush ◽  
Single Family ◽  
Metal Concentrations ◽  
Building Height ◽  
High Rise ◽  
Family House

Samples were taken from 72 high-rise apartment suites (6 suites in 12 individual high-rise towers) and 60 single-family houses located within the Greater Vancouver Regional District. The influence of the following factors on trace metal concentrations in 1-L first-flush drinking water samples and “running” hot water samples was investigated: building height, location, plumbing age, type of plumbing, and type of building. Results of this survey show that with the exception of building height, all factors had a correlation with one or more of the trace metals investigated. The trace metals examined were lead, copper, iron, and zinc. Lead was influenced primarily by building type, copper by plumbing age and type of plumbing, and iron by location. Elevated lead levels were associated with high-rise samples. New copper plumbing systems resulted in high copper levels. Highest iron levels in the drinking water were measured in the East Vancouver location. Zinc did not show a distinct correlation with any of the factors investigated. Brass faucets were the primary source of zinc in tap water. They also contributed substantially to the lead detected in the 1-L first-flush sample. Metal concentrations measured in the high-rise and house samples were compared with the U.S. Environmental Protection Agency's (USEPA) maximum contaminant levels (MCLs) and the proposed “no-action” level for lead. In high-rise samples, the 0.01 mg/L “no-action” level proposed for lead was exceeded in 43% of the samples, and 62% of the samples exceeded the current 1.0 mg/L MCL standard for copper. In single-family house samples, these values were 47% and 73%, respectively. The average lead concentrations were 0.020 mg/L for all high-rise samples and 0.013 mg/L for house samples. Regulatory levels stated above would still be exceeded in 6% of the cases for lead and 9% of the cases for copper, even after prolonged flushing of the tap in a high-rise building. In all cases associated with single-family houses, flushing the cold water tap for 5 minutes was successful in achieving compliance levels. Key words: aggressive water, compliance, corrosive, drinking water, first-flush, GVRD, high-rise, single-family house, trace metals, USEPA.

scholarly journals Examination of Surface Water Along River-Rima Floodplain in Wamakko, Sokoto State, Nigeria.

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Abdulqadir Abubakar Usman ◽  
Murtala Abubakar Gada ◽  
Aminu Muhammad Bayawa ◽  
Ibrahim Mustapha Dankani ◽  
Saadu Umar Wali
Keyword(s):  
Drinking Water ◽  
Surface Water ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
World Health ◽  
Coliform Bacteria ◽  
Municipal Sewage ◽  
Bacteria Growth ◽  
Anthropogenic Inputs ◽  
Health Organization

This study examined the hydrochemistry of surface water along the River-Rima floodplain area. Five sampling locations were purposively selected, and, in each point, three samples were taken from surface water (river). The sampling was repeated after 20 days. Thus, a total of 30 samples were collected. Water samples obtained were subjected to laboratory tests. Results revealed that BOD, TDS, Mg2+, and Fe3+ are above the World Health Organization (WHO) and Standard Organization of Nigeria (SON) reference guidelines for drinking water quality. Isolates detected from the coliform bacteriological analysis include Enterobacter aerogene, Escherichia coli, and Citrobacter freundii with most of the samples showing coliform bacteria growth above the SON standard for drinking water. Hence, the water in the River-Rima floodplain of the Wamakko area is of low quality and unsafe for drinking. Results of principal component analysis (PCA) revealed external influences such as pollutant wash off and rock weathering as controls on hydrochemistry of surface water. There is some indication of anthropogenic inputs (Cl-, NO3-, and PO42-) based on hierarchical cluster analysis. Elements including Cl-, NO3-, and PO42- are increasingly added into surface water from human activities, mainly agriculture, and municipal sewage.

scholarly journals Characteristics of Atmospheric Metalliferous Particles during Large-Scale Fireworks in Korea

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Zang-Ho Shon ◽  
Ju-Hee Jeong ◽  
Yoo-Keun Kim
Keyword(s):  
Trace Metals ◽  
Trace Metal ◽  
Large Scale ◽  
Background Level ◽  
Trace Metal Concentration ◽  
Urban Background ◽  
Ambient Concentration ◽  
Local Background ◽  
The Impact ◽  
Concentration Levels

The effect of large-scale firework events on urban background trace metal concentrations was investigated using 24 hr data collected over 3 days at three sites in Busan Metropolitan City, Republic of Korea, during the falls (Oct.) of 2011–2013. The firework events increased local background concentrations of trace metals as follows: K (1.72 times), Sr (2.64 times), As (2.86 times), Pb (2.91 times), and Al (5.44 times). The levels of some metals did not always drop to background level one day after the firework event. The contribution of fireworks to trace metal concentration levels (and emissions) for 2011 event was negligible compared to 2012 and 2013 events due to different meteorological conditions (precipitation). In addition, the impact of firework events on the ambient concentration levels of trace metals was likely to be different depending on their chemical speciation. The impact of firework events in Busan on urban air quality (trace metal) was less intense compared to other similar festivals worldwide. The largest emission of trace metals and elements from firework burning was represented by K (128–164 kg), followed by Pb, Cd, Cu, Mg, Ba, As, Al, Ga, Co, and Na.

scholarly journals Impact of Input Filtering and Architecture Selection Strategies on GRU Runoff Forecasting: A Case Study in the Wei River Basin, Shaanxi, China

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3532
Author(s):  
Qianyang Wang ◽  
Yuan Liu ◽  
Qimeng Yue ◽  
Yuexin Zheng ◽  
Xiaolei Yao ◽  
...  
Keyword(s):  
River Basin ◽  
Prediction Accuracy ◽  
Principal Component ◽  
Time Step ◽  
Flood Peak ◽  
Runoff Forecasting ◽  
The Wei River Basin ◽  
The Impact ◽  
Wei River Basin ◽  
Wei River

A gated recurrent unit (GRU) network, which is a kind of artificial neural network (ANN), has been increasingly applied to runoff forecasting. However, knowledge about the impact of different input data filtering strategies and the implications of different architectures on the GRU runoff forecasting model’s performance is still insufficient. This study has selected the daily rainfall and runoff data from 2007 to 2014 in the Wei River basin in Shaanxi, China, and assessed six different scenarios to explore the patterns of that impact. In the scenarios, four manually-selected rainfall or runoff data combinations and principal component analysis (PCA) denoised input have been considered along with single directional and bi-directional GRU network architectures. The performance has been evaluated from the aspect of robustness to 48 various hypermeter combinations, also, optimized accuracy in one-day-ahead (T + 1) and two-day-ahead (T + 2) forecasting for the overall forecasting process and the flood peak forecasts. The results suggest that the rainfall data can enhance the robustness of the model, especially in T + 2 forecasting. Additionally, it slightly introduces noise and affects the optimized prediction accuracy in T + 1 forecasting, but significantly improves the accuracy in T + 2 forecasting. Though with relevance (R = 0.409~0.763, Grey correlation grade >0.99), the runoff data at the adjacent tributary has an adverse effect on the robustness, but can enhance the accuracy of the flood peak forecasts with a short lead time. The models with PCA denoised input has an equivalent, even better performance on the robustness and accuracy compared with the models with the well manually filtered data; though slightly reduces the time-step robustness, the bi-directional architecture can enhance the prediction accuracy. All the scenarios provide acceptable forecasting results (NSE of 0.927~0.951 for T + 1 forecasting and 0.745~0.836 for T + 2 forecasting) when the hyperparameters have already been optimized. Based on the results, recommendations have been provided for the construction of the GRU runoff forecasting model.

Risk estimation and multivariate statistical analysis of the heavy metal content of drinking water samples

2018 ◽  
Vol 34 (10) ◽  
pp. 714-725
Author(s):  
Rajan Jakhu ◽  
Rohit Mehra
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Drinking Water ◽  
Statistical Analysis ◽  
Water Samples ◽  
Multivariate Statistical Analysis ◽  
Inductively Coupled Plasma ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Drinking Water Samples

Drinking water samples of Jaipur and Ajmer districts of Rajasthan, India, were collected and analyzed for the measurement of concentration of heavy metals. The purpose of this study was to determine the sources of the heavy metals in the drinking water. Inductively coupled plasma mass spectrometry was used for the determination of the heavy metal concentrations, and for the statistical analysis of the data, principal component analysis and cluster analysis were performed. It was observed from the results that with respect to WHO guidelines, the water samples of some locations exceeded the contamination levels for lead (Pb), selenium (Se), and mercury (Hg), and with reference to the EPA guidelines, the samples were determined unsuitable for drinking because of high concentrations of Pb and Hg. Using multivariate statistical analysis, we determined that copper, manganese, arsenic, Se, and Hg were of anthropogenic origin, while Pb, copper, and cadmium were of geogenic origin. The present study reports the dominance of the anthropogenic contributions over geogenics in the studied area. The sources of the anthropogenic contaminants need to be investigated in a future study.

scholarly journals Trace metal accumulation in decapods and its use in monitoring the marine environment

2021 ◽  
Author(s):  
◽  
Annie Graham
Keyword(s):  
Trace Metals ◽  
Trace Metal ◽  
Spatial Variation ◽  
Marine Environment ◽  
Metal Accumulation ◽  
Environmental Indicators ◽  
Trophic Levels ◽  
Geochemical Data ◽  
Feeding Strategies ◽  
The Impact

<p>Coastal habitats are susceptible to severe contamination due to their exposure to both marine and terrestrial inputs, many of which contain toxic heavy metals. Trace metals in the marine environment can have severe impacts on the health of coastal ecosystems, as even those with essential functions can be toxic at high concentrations, and non-essential elements can cause impairment of biological functions even at low levels.  It is important to understand the chemistry of New Zealand’s marine environment, in order to successfully monitor any changes to the chemical profile of the environment from anthropogenic pollutants. Biological indicators are a useful tool for monitoring ecosystem health, and the impact of human activity on the environment. Crustaceans fulfil all the criteria of being good environmental indicators, as well as having a range of feeding strategies, and being present at multiple trophic levels. The aim of this research was to 1) investigate spatial variation and the effect of urbanisation in trace metal concentration in two native decapod species, Heterozius rotundifrons and Petrolisthes elongatus, which co-occur but feed at different trophic levels; and 2) examine how essential and non-essential trace metals are accumulated into different body tissues of the decapod Jasus edwardsii, a significant cultural and fishery species.  To assess spatial variation and trophic level differences between decapods, baseline data of the concentrations of thirty trace metals was collected and analysed from both species at three sites in the Wellington region. Little variation was found between the sites, despite their differences in proximity to urban development, but significant differences were found between species, with the consumer H. rotundifrons having higher concentrations of most trace metals than the filter feeder P. elongatus.  To assess trace metal accumulation into tissues of J. edwardsii, an experiment was run exposing juveniles to water doped with an elevated copper and neodymium treatment. Copper was preferentially accumulated into the organ tissue, as was expected for an essential element. Neodymium was accumulated differentially into organ and exoskeleton tissue depending on the treatment, with specimens in the elevated treatment taking it up into the shell rather than the organs. A second experiment was also run to investigate whether moulted exoskeletons would passively absorb copper from their environment, which was shown to be the case.  This research aids in understanding the importance of multiple species monitoring, as trace element accumulation was shown to be highly variable depending on species and metals, and contributes valuable geochemical data on native New Zealand species, which have been little studied in this context.</p>

scholarly journals Groundwater quality assessment using principal component analysis and hierarchical cluster analysis in Alaçam, Turkey

2021 ◽  
Author(s):  
Mehmet Taşan ◽  
Yusuf Demir ◽  
Sevda Taşan
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Groundwater Quality ◽  
Seawater Intrusion ◽  
Hierarchical Cluster Analysis ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Component Analysis ◽  
Quality Parameters ◽  
Multivariate Statistical

Abstract This study assessed groundwater quality in Alaçam, where irrigations are performed solely with groundwaters and samples were taken from 35 groundwater wells at pre and post irrigation seasons in 2014. Samples were analyzed for 18 water quality parameters. SAR, RSC and %Na values were calculated to examine the suitability of groundwater for irrigation. Hierarchical cluster analysis and principal component analysis were used to assess the groundwater quality parameters. The average EC value of groundwater in the pre-irrigation period was 1.21 dS/m and 1.30 dS/m after irrigation in the study area. It was determined that there were problems in two wells pre-irrigation and one well post-irrigation in terms of RSC, while there was no problem in the wells in terms of SAR. Piper diagram and cluster analysis showed that most groundwaters had CaHCO3 type water characteristics and only 3% was NaCl- as the predominant type. Seawater intrusion was identified as the primary factor influencing groundwater quality. Multivariate statistical analyses to evaluate polluting sources revealed that groundwater quality is affected by seawater intrusion, ion exchange, mineral dissolution and anthropogenic factors. The use of multivariate statistical methods and geographic information systems to manage water resources will be beneficial for both planners and decision-makers.

scholarly journals Water quality assessment and geochemical processes in the unconfined coastal Boa Viagem Aquifer, Recife, NE Brazil

2021 ◽  
pp. 56-77
Author(s):  
Thyego Silva ◽  
Mariucha Lima ◽  
Teresa Leitão ◽  
Tiago Martins ◽  
Mateus Albuquerque
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Water Quality Assessment ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Rock Interaction ◽  
Groundwater Samples ◽  
Water Rock Interaction

A hydrochemical study was conducted on the Quaternary Aquifer, in Recife, Brazil. Groundwater samples were collected in March–April 2015, at the beginning of the rainy season. Conventional graphics, ionic ratios, saturation indices, GIS mapping, and geostatistical and multivariate statistical analyses were used to water quality assessment and to characterize the main hydrochemical processes controlling groundwater’s chemistry. Q-mode hierarchical cluster analysis separated the samples into three clusters and five sub-clusters according to their hydrochemical similarities and facies. Principal Component Analysis (PCA) was employed to the studied groundwater samples where a three-factor model explains 80% of the total variation within the dataset. The PCA results revealed the influence of seawater intrusion, water-rock interaction, and nitrate contamination. The physico-chemical parameters of ~30% groundwaters exceed the World Health Organization (WHO) guidelines for drinking water quality. Nitrate was found at a concentration >10 mg NO3−/L in ~21% of the wells and exceeded WHO reference values in one. The integrated approach indicates the occurrence of the main major hydrogeochemical processes occurring in the shallow marine to alluvial aquifer as follow: 1) progressive freshening of remaining paleo-seawater accompanying cation exchange on fine sediments, 2) water-rock interaction (i.e., dissolution of silicates), and 3) point and diffuse wastewater contamination, and sulfate dissolution. This study successfully highlights the use of classical geochemical methods, GIS techniques, and multivariate statistical analyses (hierarchical cluster and principal component analyses) as complementary tools to understand hydrogeochemical processes and their influence on groundwater quality status to management actions, which could be used in similar alluvial coastal aquifers.

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