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"quality analysis"
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In-depth characterization of particulate matter in a highly polluted urban environment at the foothills of Himalaya–Karakorum Region
In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth’s system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10 µm, i.e., PM
10
are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM
10
samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24 h average PM
10
mass concentration along with standard deviation was investigated to be 586.83 ± 217.70 µg/m
3
, which was around 13 times greater than the permissible limit of the world health organization (45 µg/m
3
) and 4 times the Pakistan national environmental quality standards for ambient PM
10
(150 µg/m
3
). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90 µg/m
3
, respectively. Water-soluble ions K
+
and OC show a substantial association (
R
= 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of PM
10
, which are vital for preparing an air quality management plan in the urban environment of Peshawar.
Journal Article
Root cause analysis : a step-by-step guide to using the right tool at the right time
\"This book covers root cause analysis, with an emphasis on using quality tools to empirically investigate issues. It starts with the theoretical background and then provides step-by-step instructions for performing root cause analysis using various quality tools. The book explains how to use PDCA together with scientific methods and quality tools when investigating quality failures. The tools and concepts presented are appropriate for both the manufacturing industry and service industry\"-- Provided by publisher.
Book
Hydrochemistry and quality appraisal of groundwater in Birr River Catchment, Central Blue Nile River Basin, using multivariate techniques and water quality indices
Due to the continuous population growth and the expansion of industry and agriculture in Ethiopia, groundwater demand has been increasing to supplement the erratic surface water. Therefore, the availability of sufficient and clean groundwater should be appraised and tracked regularly to secure its multi-purposes. This work aims to assess the appropriateness of groundwater for drinking, and irrigation uses and identifies the key factors controlling groundwater quality in the Birr River Catchment (BRC), Blue Nile River Basin, Ethiopia. For this purpose, a total of 79 groundwater samples were assessed for physicochemical parameters. Major ion analysis, multivariate techniques (MCA, HCA, and PCA), and multi-hydrochemical indices were applied in the analysis of groundwater quality data. Hydrochemical analysis indicated that the principal cation and anion were Ca
2+
and HCO
3
−
, respectively. The spatial analysis of the major ions revealed a positive trend for Mg
2+
, Na
+
, K
+
, HCO
3
−
, Cl
−
, and SO
4
2−
along the groundwater flow path from the upland to the Birr river valley. Conversely, Ca
2+
shows a deleterious tendency along the groundwater flow direction. The aquifer has three principal hydrochemical facies: Ca–HCO
3
, Ca/Mg–HCO
3
, and Na–HCO
3
. The water quality analysis indicates that with the exception of TDS, Ca
2+
, Mg
2+
, and HCO
3
−
in a few locations, most of the parameters analyzed are within the WHO allowable limits and are thus considered suitable for drinking water. The combined use of Gibbs and ionic ratio plots confirmed that silicate weathering was invariably prevailing in the region. The Chloro–Alkali Indices (CAIs) have indicated that cation exchange occurs in more than 85% of groundwater samples. However, there were indications of the influence of reverse ion exchange in the rest of the data. The MCA, PCA, and HCA disclosed that geo-genic sources accompanied by human activities mainly control the groundwater quality of the catchment. However, water quality assessment indices show that groundwater in the highest proportion of the catchment is suitable for human consumption and agricultural use.
Journal Article
Multivariate Statistical Analysis for Water Quality Assessment: A Review of Research Published between 2001 and 2020
Research on water quality is a fundamental step in supporting the maintenance of environmental and human health. The elements involved in water quality analysis are multidimensional, because numerous characteristics can be measured simultaneously. This multidimensional character encourages researchers to statistically examine the data generated through multivariate statistical analysis (MSA). The objective of this review was to explore the research on water quality through MSA between the years 2001 and 2020, present in the Web of Science (WoS) database. Annual results, WoS subject categories, conventional journals, most cited publications, keywords, water sample types analyzed, country or territory where the study was conducted and most used multivariate statistical analyses were topics covered. The results demonstrate a considerable increase in research using MSA in water quality studies in the last twenty years, especially in developing countries. River, groundwater and lake were the most studied water sample types. In descending order, principal component analysis (PCA), hierarchical cluster analysis (HCA), factor analysis (FA) and discriminant analysis (DA) were the most used techniques. This review presents relevant information for researchers in choosing the most appropriate methods to analyze water quality data.
Journal Article
Multivariate and Water Quality Index Approaches for Spatial Water Quality Assessment in Lake Ziway, Ethiopian Rift
Information on water quality in aquatic environments is essential for managing and protecting surface water resources, such as lakes, reservoirs, and rivers. This study investigates the spatial status of water quality and the sources of contamination in Lake Ziway, Ethiopian Rift. Evenly distrusted lake water sampling, including the major feeding streams and effluents from floriculture and domestic waste that might have an impact on the lake’s water quality, was carried out. For hydrochemical analysis, multivariate techniques and water quality index (WQI) approaches were applied based on 44 water quality parameters. The water quality analysis result showed a non-uniform distribution of the measured physico–chemical and organic matter load indicators across the lake area. Multiple pollutants are present in the lake water at levels that exceed the World Health Organization’s recommendations. TU, EC, pH, DO, BOD, COD, Na+, K+, HCO3−, Mn2+, and a few samples for F−, Ni2+, and Pb2+ were the most commonly desecrated. Principal component analysis (PCA) identified four major components with 74.35% cumulative variance, and cluster analysis (CA) resulted in three clusters representing the central, southern, and northern sectors of the lake. The results of PCA and CA indicated that the water quality of the lake is largely controlled by sediments, nutrients, and organic sources as the key lake pollution sources. The overall water quality analysis (WQI > 300) of Lake Ziway and its major feeding rivers is categorized as unsuitable for domestic uses as well as aquatic life. The combined application of multivariate and WQI analysis showed how human-induced activities in the watershed, such as soil erosion, agriculture, industrialization, and urbanization, had a significant impact on the lake water quality and ecological integrity.
Journal Article
Combining data-intelligent algorithms for the assessment and predictive modeling of groundwater resources quality in parts of southeastern Nigeria
Machine learning algorithms have proven useful in the estimation, classification, and prediction of water quality parameters. Similarly, indexical modeling has enhanced the evaluation and summarization of water quality. In Nigeria, works that have incorporated machine learning modeling in water quality analysis are scarce. Although studies across the globe have utilized overall index of pollution (OIP) and water quality index (WQI), works that have simulated and predicted them using machine learning algorithms seem to be scarce. Studies have not simulated nor predicted OIP. In this paper, several physicochemical parameters were analyzed and used for groundwater quality modeling in southeastern Nigeria based on integrated data-intelligent algorithms. Standard methods were followed in all the analysis and modeling performed in this work. OIP and WQI were computed, and their results revealed that 80% of the groundwater resources are suitable for drinking whereas 20% are highly polluted and unsuitable. Pearson’s correlation analysis and R-mode hierarchical clustering revealed the possible sources of contamination. Meanwhile, agglomerative Q-mode hierarchical clustering and K-means (partitional) clustering were used to show the spatial demarcations of water quality in the area. Both clustering algorithms identified two main water quality classes—the suitable and unsuitable classes. Furthermore, multiple linear regression (MLR) model and multilayer perceptron neural networks (MLP-NN) were used for the estimation and prediction of the water quality indices. With low modeling errors, both MLR and MLP-NN showed very strong predictions, as their determination coefficient ranged between 0.999 and 1.000. However, MLR slightly outperformed the MLP-NN in the prediction of OIP. The findings of this paper would enhance sustainable water management in the study region and also contribute great insights to the national and global water quality prediction literatures.
Journal Article
Water quality management of heavily contaminated urban rivers using water quality analysis simulation program
Precisely management of water quality in urban rivers is of significant where water environmental capacity provides a useful tool. This study presented a water quality analysis simulation program model-based approach for dynamical load reduction in Ashi River, highly contaminated tributaries of Songhua River, China. The actual and surplus dynamic environmental capacity of CODCr and NH3-N, as the two controlling endpoints, were computed based on \"segment-end-control\" method for monthly or seasonal management. The dynamic pollution control scheme and monthly to annual control strategies were produced based on calculated results. Results show that CODCr and NH3-N need to be cut down to approximately 462.47t/a and 5.2t/a at Zhujia-Acheng down reach and 282.42 t/a and 9.25t/a Acheng down-Chenggaozi town reach, respectively under 90% hydrological design reliability to keep the water quality at class-IV. The CODCr and NH3-N of three ditches should be strictly controlled throughout the year. Some interesting temporal-spatial characteristics of surplus environmental capacity were also found in the study. This study provides local governments with technical measurements and policy recommendations for highly contaminated water body treatment. In the future, the river water quality management in the winter season should take into particular consideration.
Journal Article
ULTRAVIOLET SPECTROPHOTOMETRIC METHOD AND WATER HYDROCARBON IMPURITY SENSOR
The paper deals with the application of spectrophotometric method and the sensor for determination of contaminating hydrocarbon impurity presence in waste water. The sensor is designed on the basis of modern element base. For measurement accuracy increase it has computer processing of analysis results for the absorption spectra of liquid (water) media in the ultraviolet wavelength range. The proposed sensor and computer program enabled the study of hydrocarbon impurity presence in the water that is an important factor for continuous monitoring of the environment. The absorption spectra of gasoline, diesel fuel, synthetic motor oil, fuel oil, natural oil are given as the most frequently present as impurities in the water, measured on an automated spectrophotometric sensor model. The use of modern small-sized elements makes it possible to design a small-sized highly sensitive sensor for express analysis of the water quality.
Journal Article