Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey)

Köklü, Rabia; Şengörür, Bülent; Topal, Bayram

doi:10.1007/s11269-009-9481-7

Cited by 135 publications

(77 citation statements)

References 24 publications

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“…To avoid duplicate tracks in dist (a, b), the Euclidean distance (euclidean), an application of the Malinowski space, was used. The Malinowski space can be solved using the matrix value of p = ∞ in Equation (4). The pdist shows that object ρ ∈ C Figure 1.…”

Section: Testbed Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Aquatic ecosystem health is often impaired tivities, such as intake of urban sewage and urban storm water [2]. Therefore, ng of urban streams is necessary to evaluate the impact of urban pollution on erous methods exist to monitor and analyze these parameters, including discrete r analysis, and use of monitoring networks [4]. with user-friendly software and hardware and facilitated data analysis by interested using their smartphones.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, onitoring of urban streams is necessary to evaluate the impact of urban pollution on . Numerous methods exist to monitor and analyze these parameters, including discrete , water analysis, and use of monitoring networks [4]. However, continuous efficient rk with a 99.99% efficient communication platform was developed to allow collection of data with user-friendly software and hardware and facilitated data analysis by interested iduals using their smartphones.…”

Section: Introductionmentioning

confidence: 99%

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Internet of Things-Based Arduino Intelligent Monitoring and Cluster Analysis of Seasonal Variation in Physicochemical Parameters of Jungnangcheon, an Urban Stream

Baloch

2017

Water

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Abstract:In the present case study, the use of an advanced, efficient and low-cost technique for monitoring an urban stream was reported. Physicochemical parameters (PcPs) of Jungnangcheon stream (Seoul, South Korea) were assessed using an Internet of Things (IoT) platform. Temperature, dissolved oxygen (DO), and pH parameters were monitored for the three summer months and the first fall month at a fixed location. Analysis was performed using clustering techniques (CTs), such as K-means clustering, agglomerative hierarchical clustering (AHC), and density-based spatial clustering of applications with noise (DBSCAN). An IoT-based Arduino sensor module (ASM) network with a 99.99% efficient communication platform was developed to allow collection of stream data with user-friendly software and hardware and facilitated data analysis by interested individuals using their smartphones. Clustering was used to formulate relationships among physicochemical parameters. K-means clustering was used to identify natural clusters using the silhouette coefficient based on cluster compactness and looseness. AHC grouped all data into two clusters as well as temperature, DO and pH into four, eight, and four clusters, respectively. DBSCAN analysis was also performed to evaluate yearly variations in physicochemical parameters. Noise points (NOISE) of temperature in 2016 were border points ( esent case study, the use of an advanced, efficient and low-cost technique for an stream was reported. Physicochemical parameters (PcPs) of Jungnangcheon h Korea) were assessed using an Internet of Things (IoT) platform. Temperature, DO), and pH parameters were monitored for the three summer months and the fixed location. Analysis was performed using clustering techniques (CTs), such ring, agglomerative hierarchical clustering (AHC), and density-based spatial cations with noise (DBSCAN). An IoT-based Arduino sensor module (ASM) .99% efficient communication platform was developed to allow collection of ser-friendly software and hardware and facilitated data analysis by interested their smartphones. Clustering was used to formulate relationships among arameters. K-means clustering was used to identify natural clusters using the nt based on cluster compactness and looseness. AHC grouped all data into two temperature, DO and pH into four, eight, and four clusters, respectively. was also performed to evaluate yearly variations in physicochemical parameters. E) of temperature in 2016 were border points (ƥ), whereas in 2014 and 2015 they ts (ɋ), indicating a trend toward increasing stream temperature. We found the were within the permissible limits set by the Water Quality Standards for River . o monitoring; urban stream; data analysis; clustering technique; internet of l parameters (PcPs) of a stream are critical to the health of aquatic ecosystems. edge of the temperature, pH, and dissolved oxygen content of a stream allows its ability to sustain aquatic life [1]. Aquatic ecosystem health is often impaired tivities, such as intake of urban sewage and urb...

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Section: Testbed Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Internet of Things-Based Arduino Intelligent Monitoring and Cluster Analysis of Seasonal Variation in Physicochemical Parameters of Jungnangcheon, an Urban Stream

Baloch

2017

Water

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“…The application of different mathematical tools, such as principal component analysis (PCA) and cluster analysis (CA), allows the interpretation of complex data matrices to better understand the water quality and ecological status of the studied system (Kotti et al 2005;Koklu et al 2010;Ogleni and Topal 2011;Awadallah and Yousry 2012). These studies showed the ability of PCA and CA for the evaluation and interpretation of complex data sets to get better information about water quality and the design of the monitoring network for effective management of water resources.…”

Section: Introductionmentioning

confidence: 99%

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

Gomes

Pires

Figueiredo

et al. 2014

Water Resour Manage

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This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as "bad" or "very bad". PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

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An overview of Brazilian companies' readiness to implement industrial symbiosis

Agudo,

Bezerra,

Gobbo Júnior

2023

Bus Strat Env

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Industrial symbiosis (IS) is a strategy that focuses on the exchange of resources between colocated industries. Despite the benefits of IS, companies often face challenges in implementing it, primarily due to technical, economic, and information barriers. Therefore, this paper aims to investigate the feasibility of implementing IS among Brazilian companies. To achieve this, a survey was conducted with 201 colocated companies using a previously developed instrument to assess their levels of symbiotic readiness. The findings resulted in the creation of a typology of symbiotic readiness levels, accompanied by practical recommendations for each level. In general, the surveyed companies are making progress toward implementing IS, as evidenced by their attempts to exchange waste and by‐products with other colocated industries. However, overcoming barriers related to information sharing, trust‐building, access conditions, infrastructure, and partnership formation remains challenging. This study provides valuable evidence from an emerging country regarding the readiness levels of companies to implement IS, offering insights and recommendations for managers and public authorities to promote IS. It is important to note that as companies reach mature stages of IS implementation, they can collaborate to transform the conditions of the industrial parks, ultimately fostering future industrial ecosystems.

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Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey)

Cited by 135 publications

References 24 publications

Internet of Things-Based Arduino Intelligent Monitoring and Cluster Analysis of Seasonal Variation in Physicochemical Parameters of Jungnangcheon, an Urban Stream

Internet of Things-Based Arduino Intelligent Monitoring and Cluster Analysis of Seasonal Variation in Physicochemical Parameters of Jungnangcheon, an Urban Stream

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

An overview of Brazilian companies' readiness to implement industrial symbiosis

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