Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutr...Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.展开更多
Wastewaters from the chemical industry are usually of high-strength and may contain minor inhibitory and recalcitrant organics that are at times not readily identifiable. This paper describes the experience of a biolo...Wastewaters from the chemical industry are usually of high-strength and may contain minor inhibitory and recalcitrant organics that are at times not readily identifiable. This paper describes the experience of a biological waste water treatment plant （WWTP） processing a COD concentration of 43000 mg·L^-1 wastewater from an oxochemical manufacturing plant. Stage improvements of the plant process by dilution of the inhibitory influent using other chemical wastewater streams resulting in a synergistic process effect, and removal of inhibitory organics by phase separation via acidification, effectively achieved process optimization producing a high quality effluent. In particular, the COD removal efficiency of granular sludge based anaerobic reactors increased from 56% to 90%. The final effluent COD decreased from 250mg·L^-1 to 50mg·L^-1, consistently meeting the COD concentration of 100 mg·L^-1 regulatory discharge limit. The success of the process enhancements supports the hypothesis that long-chain quaternary carboxylic acids act as substrate inhibitors in the biological process.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
基金the financial support from the National Key Research and Development Program of China(2019YFD1100204)the National Natural Science Foundation of China(52091545)+2 种基金the State Key Laboratory of Urban Water Resource and Environment,Harbin Institute of Technology(2021TS03)The Important Projects in the Scientific Innovation of CECEP(cecep-zdkj-2020-009)the Open Project of Key Laboratory of Environmental Biotechnology,Chinese Academy of Sciences(kf2018002).
文摘Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.
文摘Wastewaters from the chemical industry are usually of high-strength and may contain minor inhibitory and recalcitrant organics that are at times not readily identifiable. This paper describes the experience of a biological waste water treatment plant （WWTP） processing a COD concentration of 43000 mg·L^-1 wastewater from an oxochemical manufacturing plant. Stage improvements of the plant process by dilution of the inhibitory influent using other chemical wastewater streams resulting in a synergistic process effect, and removal of inhibitory organics by phase separation via acidification, effectively achieved process optimization producing a high quality effluent. In particular, the COD removal efficiency of granular sludge based anaerobic reactors increased from 56% to 90%. The final effluent COD decreased from 250mg·L^-1 to 50mg·L^-1, consistently meeting the COD concentration of 100 mg·L^-1 regulatory discharge limit. The success of the process enhancements supports the hypothesis that long-chain quaternary carboxylic acids act as substrate inhibitors in the biological process.
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.
