Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, p...Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.展开更多
By predicting influent quantity,a wastewater treatment plant(WWTP)can be well controlled.The non-linear dynamic characteristic of WWTP influent quantity time series was analyzed,with the assumption that the series was...By predicting influent quantity,a wastewater treatment plant(WWTP)can be well controlled.The non-linear dynamic characteristic of WWTP influent quantity time series was analyzed,with the assumption that the series was predictable.Based on this,a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction.Reasonable forecasting results were achieved using this method.展开更多
Effluents from wastewater treatment plants（WWTPs） containing microorganisms and residual nutrients can influence the biofilm formation. Although the process and mechanism of bacterial biofilm formation have been wel...Effluents from wastewater treatment plants（WWTPs） containing microorganisms and residual nutrients can influence the biofilm formation. Although the process and mechanism of bacterial biofilm formation have been well characterized, little is known about the characteristics and interaction of bacteria, archaea and eukaryotes in the early colonization, especially under the influence of WWTP effluent. The aim of this study was to characterize the important bacterial, archaeal and eukaryotic species in the early stage of biofilm formation downstream of the WWTP outlet. Water and biofilm samples were collected 24 and 48 hr after the deposition of bio-cords in the stream. Illumina Miseq sequencing of the 16 S and 18 S rDNA showed that, among the three domains, the bacterial biofilm community had the largest alpha and beta diversity. The early bacterial colonizers appeared to be ＂biofilm-specific＂, with only a few dominant operational taxonomic units（OTUs） shared between the biofilm and the ambient water environment. Alpha-proteobacteria and Ciliophora tended to dominate the bacterial and eukaryotic communities, respectively, of the early biofilm already at 24 hr, whereas archaea played only a minor role during the early stage of colonization. The network analysis showed that the three domains of microbial community connected highly during the early colonization and it might be a characteristic of the microbial communities in the biofilm formation process where co-occurrence relationships could drive coexistence and diversity maintenance within the microbial communities.展开更多
The diffusion of municipal wastewater treatment technology is vital for urban environment in developing countries. China has built more than 3000 municipal wastewater treatment plants in the past three decades, which ...The diffusion of municipal wastewater treatment technology is vital for urban environment in developing countries. China has built more than 3000 municipal wastewater treatment plants in the past three decades, which is a good chance to understand how technologies diffused in reality. We used a data-driven approach to explore the relationship between the diffusion of wastewater treatment technologies and collaborations between organizations. A database of 3136 municipal wastewater treatment plants and 4634 collaborating organizations was built and transformed into networks for analysis. We have found that： 1）.the diffusion. networks are assortative, arid the .pattems of diffusion vary across technologies; while the collaboration networks are fragmented, and have an assortativity around zero since the 2000s. 2） Important projects in technology diffusion usually involve central organizations in collaboration networks, but organizations become more central in collaboration by doing circumstantial projects in diffusion. 3）The importance of projects in diffusion can be predicted with a Random Forest-model at a good accuracy and precision level. Our findings provide a quantitative understanding of the technology diffusion processes, which could be used for waterrelevant policy-making and business decisions.展开更多
文摘Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.
基金The work was supported by the Natural Science Foundation of China for Distinguished Young Scholars(Grant Nos.50225926 and 50425927)the National High-Tech Research and Development(863)Program of China(Grant No.2004AA649370)+1 种基金the Teaching and Research Award Program for Excellent Youth Teachers in Higher Education Institu-tions of MOE,China(TRAPOYT)in 2000the Specialized Research Fund for the Doctoral Program of Higher Education of Ministry of Education of China(Grant No.20020532017).
文摘By predicting influent quantity,a wastewater treatment plant(WWTP)can be well controlled.The non-linear dynamic characteristic of WWTP influent quantity time series was analyzed,with the assumption that the series was predictable.Based on this,a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction.Reasonable forecasting results were achieved using this method.
基金supported by the National Key Research and Development Program of China (No. 2016YFC0502801)
文摘Effluents from wastewater treatment plants（WWTPs） containing microorganisms and residual nutrients can influence the biofilm formation. Although the process and mechanism of bacterial biofilm formation have been well characterized, little is known about the characteristics and interaction of bacteria, archaea and eukaryotes in the early colonization, especially under the influence of WWTP effluent. The aim of this study was to characterize the important bacterial, archaeal and eukaryotic species in the early stage of biofilm formation downstream of the WWTP outlet. Water and biofilm samples were collected 24 and 48 hr after the deposition of bio-cords in the stream. Illumina Miseq sequencing of the 16 S and 18 S rDNA showed that, among the three domains, the bacterial biofilm community had the largest alpha and beta diversity. The early bacterial colonizers appeared to be ＂biofilm-specific＂, with only a few dominant operational taxonomic units（OTUs） shared between the biofilm and the ambient water environment. Alpha-proteobacteria and Ciliophora tended to dominate the bacterial and eukaryotic communities, respectively, of the early biofilm already at 24 hr, whereas archaea played only a minor role during the early stage of colonization. The network analysis showed that the three domains of microbial community connected highly during the early colonization and it might be a characteristic of the microbial communities in the biofilm formation process where co-occurrence relationships could drive coexistence and diversity maintenance within the microbial communities.
文摘The diffusion of municipal wastewater treatment technology is vital for urban environment in developing countries. China has built more than 3000 municipal wastewater treatment plants in the past three decades, which is a good chance to understand how technologies diffused in reality. We used a data-driven approach to explore the relationship between the diffusion of wastewater treatment technologies and collaborations between organizations. A database of 3136 municipal wastewater treatment plants and 4634 collaborating organizations was built and transformed into networks for analysis. We have found that： 1）.the diffusion. networks are assortative, arid the .pattems of diffusion vary across technologies; while the collaboration networks are fragmented, and have an assortativity around zero since the 2000s. 2） Important projects in technology diffusion usually involve central organizations in collaboration networks, but organizations become more central in collaboration by doing circumstantial projects in diffusion. 3）The importance of projects in diffusion can be predicted with a Random Forest-model at a good accuracy and precision level. Our findings provide a quantitative understanding of the technology diffusion processes, which could be used for waterrelevant policy-making and business decisions.
