Monitoring of drinking water distribution system by SCADA in Antalya City, Turkey

Antalya water and wastewater administration has recently completed SCADA (Supervisory Control And Data Acquisition) system. The system enabled the on-line continuous monitoring of many water quantity and quality parameters such as flow rate, pressure, temperature, pH, turbidity, electrical conductivity, and free residual chlorine. Additionally, water levels in the distribution reservoirs, water pumps, energy consumption and the closing valves are monitored and controlled by the SCADA system. Beside the on-line continuous monitoring, field sampling and lab analyses of other water quality parameters such as total organic carbon, THM, bromide, iron, nitrogen and phosphorous groups, and coliform bacteria were conducted. The results of field sampling agreed with the on-line monitoring values. The SCADA system proved to be very useful for reducing water losses, improving water quality, reducing energy consumption and improving the reliability of the system

Water Contaminants Detection Using Sensor Placement Approach in Smart Water Networks

Incidents of water pollution or contamination have occurred repeatedly in recent years, causing significant disasters and negative health impacts. Water quality sensors need to be installed in the water distribution system (WDS) to allow real-time water contamination detection to reduce the risk of water contamination. Deploying sensors in WDS is essential to monitor and detect any pollution incident at the appropriate time. However, it is impossible to place sensors on all nodes of the network due to the relatively large structure of WDS and the high cost of water quality sensors. For that, it is necessary to reduce the cost of deployment and guarantee the reliability of the sensing, such as detection time and coverage of the whole water network. In this paper, a dynamic approach of sensor placement that uses an Evolutionary Algorithm (EA) is proposed and implemented. The proposed method generates a multiple set of water contamination scenarios in several locations selected randomly in the WDS. Each contamination scenario spreads in the water networks for several hours, and then the proposed approach simulates the various effect of each contamination scenario on the water networks. On the other hand, the multiple objectives of the sensor placement optimization problem, which aim to find the optimal locations of the deployed sensors, have been formulated. The sensor placement optimization solver, which uses the EA, is operated to find the optimal sensor placements. The effectiveness of the proposed method has been evaluated using two different case studies on the example of water networks: Battle of the Water Sensor Network (BWSN) and another real case study from Madrid (Spain). The results have shown the capability of the proposed method to adapt the location of the sensors based on the numbers and the locations of contaminant sources. Moreover, the results also have demonstrated the ability of the proposed approach for maximising the coverage of deployed sensors and reducing the time to detect all the water contaminants using a few numbers of water quality sensor

Implications of climate change: how does increased water temperature influence biofilm and water quality of chlorinated drinking water distribution systems?

Temperature variation can promote physico-chemical and microbial changes in the water transported through distribution systems and influence the dynamics of biofilms attached to pipes, thus contributing to the release of pathogens into the bulk drinking water. An experimental real-scale chlorinated DWDS was used to study the effect of increasing temperature from 16 to 24°C on specific pathogens, bacterial-fungal communities (biofilm and water samples) and determine the risk of material accumulation and mobilisation from the pipes into the bulk water. Biofilm was developed for 30 days at both temperatures in the pipe walls, and after this growth phase, a flushing was performed applying 4 gradual steps by increasing the shear stress. The fungal-bacterial community characterised by Illumina MiSeq sequencing, and specific pathogens were studied using qPCR: Mycobacterium spp., Mycobacterium avium complex, Acanthamoeba spp., Pseudomonas aeruginosa, Legionella pneumophilia, and Stenotrophomonas maltophilia. Sequencing data showed that temperature variation significantly modified the structure of biofilm microbial communities from the early stages of biofilm development. Regarding bacteria, Pseudomonas increased its relative abundance in biofilms developed at 24°C, while fungal communities showed loss of diversity and richness, and the increase in dominance of Fusarium genus. After the mobilisation phase, Pseudomonas continued being the most abundant genus at 24°C, followed by Sphingobium and Sphingomonas. For biofilm fungal communities after the mobilisation phase, Helotiales incertae sedis and Fusarium were the most abundant taxa. Results from qPCR showed a higher relative abundance of Mycobacterium spp. on day 30 and M. avium complex throughout the growth phase within the biofilms at higher temperatures. The temperature impacts were not only microbial, with physical mobilisation showing higher discolouration response and metals release due to the increased temperature. While material accumulation was accelerated by temperature, it was not preferentially to either stronger or weaker biofilm layers, as turbidity results during the flushing steps showed. This research yields new understanding on microbial challenges that chlorinated DWDS will undergo as global temperature rises, this information is needed in order to protect drinking water quality and safety while travelling through distribution systems

The relationship between employees' organizational support with motivation, job satisfaction and organizational commitment: A case of textile firm

Bu araştırmanın amacı, bir tekstil işletmesi çalışanlarının algıladığı örgütsel desteğin motivasyon, iş tatmini ve örgütsel bağlılıkla ilişkisini belirlemektir. Çalışma, nicel araştırma yöntemi desenine sahiptir. Araştırma, 27-30 Temmuz 2019 tarihleri arasında Ordu ilinde yapılmıştır. Araştırmanın hipotezleri tekstil işçilerinin oluşturduğu bir örneklem üzerinde test edilmiştir. Anket, 160 tekstil çalışanı tarafından yanıtlanmıştır. Anket, algılanan örgütsel destek, motivasyon, iş tatmini ve örgütsel bağlılık olmak üzere 24 soru içeren beşli bir Likert ölçeğidir. Tekstil çalışanlarından, ek olarak 8 adet demografik soruyu cevaplamaları istenmiştir. Verileri analiz etmek için uygun istatistiksel yazılımlar kullanılmıştır. Sonuçlar, algılanan örgütsel destek, iş tatmini, örgütsel bağlılık ve içsel motivasyon arasında istatistiksel olarak anlamlı ve pozitif ilişki olduğunu göstermektedir. Ayrıca, algılanan örgütsel desteğin içsel motivasyonu, iş tatminini ve örgütsel bağlılığı anlamlı bir şekilde etkilediğini göstermiştir. İçsel motivasyonun iş tatminini ve örgütsel bağlılığı anlamlı bir şekilde etkilediği de ortaya konulmuştur. Ancak, dışsal motivasyonun algılanan örgütsel destek, iş tatmini ve örgütsel bağlılıkla anlamlı bir ilişkisi bulunamamıştır.The purpose of this study is to determine the relationship between the perceived organizational support of textile workers and motivation, job satisfaction and organizational commitment. The study has a quantitative research method design. The research was conducted between 27-30 July 2019 in Ordu. The hypothesis of the study were tested on a sample of textile workers. The survey was answered by 160 textile workers. The survey is a five-point Likert scale that includes 24 questions: perceived organizational support, motivation, job satisfaction and organizational commitment. Textile workers were also asked to answer 8 demographic questions. The data were analyzed using appropriate statistical software. The results showed that a statistically significant and positive relationship was found between perceived organizational support, job satisfaction, organizational commitment and intrinsic motivation. In addition, it has been shown that perceived organizational support significantly affects intrinsic motivation, job satisfaction, and organizational commitment. It has been shown that intrinsic motivation significantly affects job satisfaction and organizational commitment. However, there was no significant relationship between extrinsic motivation and perceived organizational support, job satisfaction and organizational commitmen

URBAN WATER LOSSES MANAGEMENT IN TURKEY: THE LEGISLATION AND CHALLENGES

Water losses from water distribution networks (WDNs) have become a crucial problem in many countries such as Turkey, where country average non-revenue water (NRW) is almost 45% of system input volume (SIV). Municipalities are responsible for water supply in Turkey but only a few of them have started to improve their WDNs for management of water losses and provide good application examples; whereas many of the other municipalities have no activities to reduce water losses. The Turkish Ministry of Forestry and Water Affairs issued a new directive to control and reduce water losses from WDNs recently. With the issue of the new directive, all municipalities are now obliged to reduce water losses in WDNs within a given time frame. This paper represents a discussion and evaluation for the contents of the new Turkish directive on water losses management for the first time. Moreover, other existing guidelines and some country practices are presented to provide recommendations for the management of urban water losses. Reduction of water losses contributes directly to protection of water quality in WDNs and public health

The Relatıonshıp Between Employees' Organızatıonal Support Wıth Motıvatıon, Job Satısfactıon And Organızatıonal Commıtment: A Case Of Textıle Fırm

Bu araştırmanın amacı, bir tekstil işletmesi çalışanlarının algıladığı örgütsel desteğin motivasyon, iş tatmini ve örgütsel bağlılıkla ilişkisini belirlemektir. Çalışma, nicel araştırma yöntemi desenine sahiptir. Araştırma, 27-30 Temmuz 2019 tarihleri arasında Ordu ilinde yapılmıştır. Araştırmanın hipotezleri tekstil işçilerinin oluşturduğu bir örneklem üzerinde test edilmiştir. Anket, 160 tekstil çalışanı tarafından yanıtlanmıştır. Anket, algılanan örgütsel destek, motivasyon, iş tatmini ve örgütsel bağlılık olmak üzere 24 soru içeren beşli bir Likert ölçeğidir. Tekstil çalışanlarından, ek olarak 8 adet demografik soruyu cevaplamaları istenmiştir. Verileri analiz etmek için uygun istatistiksel yazılımlar kullanılmıştır. Sonuçlar, algılanan örgütsel destek, iş tatmini, örgütsel bağlılık ve içsel motivasyon arasında istatistiksel olarak anlamlı ve pozitif ilişki olduğunu göstermektedir. Ayrıca, algılanan örgütsel desteğin içsel motivasyonu, iş tatminini ve örgütsel bağlılığı anlamlı bir şekilde etkilediğini göstermiştir. İçsel motivasyonun iş tatminini ve örgütsel bağlılığı anlamlı bir şekilde etkilediği de ortaya konulmuştur. Ancak, dışsal motivasyonun algılanan örgütsel destek, iş tatmini ve örgütsel bağlılıkla anlamlı bir ilişkisi bulunamamıştır.The purpose of this study is to determine the relationship between the perceived organizational support of textile workers and motivation, job satisfaction and organizational commitment. The study has a quantitative research method design. The research was conducted between 27-30 July 2019 in Ordu. The hypothesis of the study were tested on a sample of textile workers. The survey was answered by 160 textile workers. The survey is a five-point Likert scale that includes 24 questions: perceived organizational support, motivation, job satisfaction and organizational commitment. Textile workers were also asked to answer 8 demographic questions. The data were analyzed using appropriate statistical software. The results showed that a statistically significant and positive relationship was found between perceived organizational support, job satisfaction, organizational commitment and intrinsic motivation. In addition, it has been shown that perceived organizational support significantly affects intrinsic motivation, job satisfaction, and organizational commitment. It has been shown that intrinsic motivation significantly affects job satisfaction and organizational commitment. However, there was no significant relationship between extrinsic motivation and perceived organizational support, job satisfaction and organizational commitment

Zastosowanie różnych technik optymalizacji i sztucznych sieci neuronowych (SSN) do prognozowania zużycia węgla: studium przypadku

The demand for energy on a global scale increases day by day. Unlike renewable energy sources, fossil fuels have limited reserves and meet most of the world’s energy needs despite their adverse environmental effects. This study presents a new forecast strategy, including an optimization-based S-curve approach for coal consumption in Turkey. For this approach, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA) are among the meta-heuristic optimization techniques used to determine the optimum parameters of the S-curve. In addition, these algorithms and Artificial Neural Network (ANN) have also been used to estimate coal consumption. In evaluating coal consumption with ANN, energy and economic parameters such as installed capacity, gross generation, net electric consumption, import, export, and population energy are used for input parameters. In ANN modeling, the Feed Forward Multilayer Perceptron Network structure was used, and Levenberg-Marquardt Back Propagation has used to perform network training. S-curves have been calculated using optimization, and their performance in predicting coal consumption has been evaluated statistically. The findings reveal that the optimization-based S-curve approach gives higher accuracy than ANN in solving the presented problem. The statistical results calculated by the GWO have higher accuracy than the PSO, WOA, and GA with R2 = 0.9881, RE = 0.011, RMSE = 1.079, MAE = 1.3584, and STD = 1.5187. The novelty of this study, the presented methodology does not need more input parameters for analysis. Therefore, it can be easily used with high accuracy to estimate coal consumption within other countries with an increasing trend in coal consumption, such as Turkey.Zapotrzebowanie na energię w skali globalnej rośnie z dnia na dzień. W przeciwieństwie do odnawialnych źródeł energii, paliwa kopalne mają ograniczone rezerwy i zaspokajają większość światowego zapotrzebowania na energię pomimo ich niekorzystnego wpływu na środowisko. Niniejsze opracowanie przedstawia nową strategię prognozowania, w tym oparte na optymalizacji podejście oparte na krzywej S dla zużycia węgla w Turcji. W tym podejściu algorytmy optymalizacji genetycznej (GA) i optymalizacji roju cząstek (PSO), optymalizacja Gray Wolf (GWO) i algorytm optymalizacji wielorybów (WOA) należą do metaheurystycznych technik optymalizacji stosowanych do określenia optymalnych parametrów krzywej S. Ponadto algorytmy te oraz sztuczna sieć neuronowa (SSN) zostały również wykorzystane do oszacowania zużycia węgla. Przy ocenie zużycia węgla za pomocą SSN jako parametry wejściowe wykorzystuje się parametry energetyczne i ekonomiczne, takie jak moc zainstalowana, produkcja brutto, zużycie energii elektrycznej netto, import, eksport i energia ludności. W modelowaniu SSN wykorzystano strukturę Feed Forward Multilayer Perceptron Network, a do uczenia sieci wykorzystano propagację wsteczną Levenberg-Marquardt. Krzywe S zostały obliczone za pomocą optymalizacji, a ich skuteczność w przewidywaniu zużycia węgla została oceniona statystycznie. Wyniki pokazują, że podejście oparte na optymalizacji opartej na krzywej S zapewnia większą dokładność niż SSN w rozwiązaniu przedstawionego problemu. Wyniki statystyczne obliczone przez GWO mają wyższą dokładność niż PSO, WOA i GA z R2 = 0,9881, RE = 0,011, RMSE = 1,079, MAE = 1,3584 i STD = 1,5187. Nowość tego badania, prezentowana metodyka nie wymaga dodatkowych parametrów wejściowych do analizy. Dzięki temu może być z łatwością wykorzystany z dużą dokładnością do oszacowania zużycia węgla w innych krajach o tendencji wzrostowej zużycia węgla, takich jak Turcja

Investigation of individual and competitive adsorption of Cu(II), Cd(II), and Pb(II) on montmorillonite in terms of surface complexation and kinetic properties of Cu(II) adsorption

In this study, individual and competitive Cu(II), Cd(II), and Pb(II) adsorptions on montmorillonite were searched by considering surface acidic functional groups of adsorbent. pH dependency of adsorptions and kinetic properties of Cu(II) adsorption was investigated. Cu(II) adsorption on montmorillonite fits pseudo-first-order reaction with the 0.008k value. Individual and competitive heavy metal adsorptions were modeled using Langmuir, Freundlich, Temkin, and Dubinin-Astakhov isotherms. Adsorption capacities were calculated using equations of related linearized models. The adsorption capacities of individual metal adsorption, obtained from linearized models, are higher than the yielded capacities from competitive adsorption experiments. All adsorption energies calculated from linearized Dubinin-Astakhov model varied between 7 and 16kJ/mol. The values of adsorption energies gained for metal adsorption in competition did not significantly differ from those of individual adsorption. Since montmorillonite surface behaves as a weak acid and has a strong buffer effect at pH values between 2 and 3, the pH dependency of adsorption was explained by taking into account the surface acidic properties of adsorbent and introduced preferred surface sites beyond adsorption with increasing pH. Cu(II), Cd(II), and Pb(II) existence on loaded montmorillonite was proved by the aid of SEM-EDX results