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Da Sheng Lingjun Bu Shumin Zhu Yangtao Wu Jue Wang Nan Li Shiqing Zhou 《环境科学学报(英文版)》2022,34(7):21-27
Pre-oxidation has been reported to be an effective way to remove algal cells in water, but the released algal organic matter (AOM) could be oxidized and lead to the increment in disinfection by-product (DBP) formation. The relationship between pre-oxidation and AOM-derived DBP formation needs to be approached more precisely. This study compared the impact of four pre-oxidants, ozone (O3), chlorine dioxide (ClO2), potassium permanganate (KMnO4) and sodium hypochlorite (NaClO), on the formation of nitrogenous (N-) and carbonaceous (C-) DBPs in AOM chlorination. The characterization (fluorescent properties, molecular weight distribution and amino acids concentration) on AOM samples showed that the characterization properties variations after pre-oxidation were highly dependent on the oxidizing ability of oxidants. The disinfection experiments showed that O3 increased DBP formation most significantly, which was consistent with the result of characterization properties variations. Then canonical correspondent analysis (CCA) and Pearson's correlation analysis were conducted based on the characterization data and DBP formation. CCA indicated that C-DBPs formation was highly dependent on fluorescent data. The formation of haloacetic acids (HAAs) had a positive correlation with aromatic protein-like component while trichloromethane (TCM) had a positive correlation with fulvic acid-like component. Pearson's correlation analysis showed that low molecular weight fractions were favorable to form N-DBPs. Therefore, characterization data could provide the advantages in the control of DBP formation, which further revealed that KMnO4 and ClO2 were better options for removing algal cells as well as limiting DBP formation. 相似文献
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The Piratininga Lagoon is a coastal, choked, and brackish ecosystem in SE Brazil, where uncontrolled discharge of domestic sewage led to eutrophication, increasing massive proliferation of benthic macroalgae, and decrease of the lagoon mean depth. In 1992, a dam was constructed by the local Municipality at its tidal channel aiming at stabilising its water level. Main physico-chemical parameters, together with macroalgae biomass, nutrient concentrations in the water column, particulate organic carbon, and chlorophyll a were recorded monthly at 4 sampling stations within the Piratininga lagoon from April 1994 to April 1995. The data, compared with “before-lock” existing studies, show that nutrients and chlorophyll a concentrations significantly increased after the lock construction. Based on the functioning of the ecosystem, we propose to harvest the algal mats before their decomposition period in order to partly remove the nutrient stocks from the lagoon and the future ecosystem modelling to predict the impact of natural and anthropogenic eutrophication. 相似文献
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In this paper, an integrated numerical and fuzzy cellular automata model was developed to predict possible algal blooms in Dutch coastal waters basing on the irradiance, nutrients and neighbourhood conditions. The numerical module used Delft3D-WAQ to compute the abiotic conditions, and fuzzy cellular automata approach was applied to predict the algal biomass that was indicated by chlorophyll a concentration. The simulated results of year 1995 were compared with that from BLOOM II model, and the advantages, disadvantages as well as future improvement were presented. In general, through this study, it is seen that the integrated modelling deserves more research inputs because: (1) the hydrodynamic processes and nutrients concentrations can be simulated in details by numerical method; (2) the irregular and sparse water quality and biological data, and the empirical knowledge from experts can be explored by the fuzzy logic technique; (3) the spatial heterogeneity, local interactions and the emerge of patchiness could be well captured through the cellular automata paradigm. 相似文献
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The Piratininga Lagoon is a coastal, choked, and brackish ecosystem in SE Brazil, where uncontrolled discharge of domestic sewage led to eutrophication, increasing massive proliferation of benthic macroalgae, and decrease of the lagoon mean depth. In 1992, a dam was constructed by the local Municipality at its tidal channel aiming at stabilising its water level. Main physico-chemical parameters, together with macroalgae biomass, nutrient concentrations in the water column, particulate organic carbon, and chlorophyll a were recorded monthly at 4 sampling stations within the Piratininga lagoon from April 1994 to April 1995. The data, compared with “before-lock” existing studies, show that nutrients and chlorophyll a concentrations significantly increased after the lock construction. Based on the functioning of the ecosystem, we propose to harvest the algal mats before their decomposition period in order to partly remove the nutrient stocks from the lagoon and the future ecosystem modelling to predict the impact of natural and anthropogenic eutrophication. 相似文献
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Jianzhang Sun Baoyu Gao Yuanxia Luo Moxi Xue Xing Xu Qinyan Yue Yan Wang 《Frontiers of Environmental Science & Engineering》2018,12(3):11
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Hong Li Mijail Arias Anouk Blauw Arthur E. Mynett Steef Peters 《Ecological modelling》2010,221(20):2435-2446
Physically based numerical modelling follows from the basic understanding of the underlying mechanisms and is often represented by a set of (partial differential) equations. It is one of the main approaches in population dynamics modelling. The emphasis of the model introduced in this paper is on the simulation of short-term spatial and temporal dynamics of harmful algal bloom (HAB) events. Total suspended matter (TSM) concentration is one of the dominant factors for harmful algal bloom (HAB) prediction in North Sea. However, the modelling of suspended matter contains a high degree of uncertainty in this area. Therefore, this research aims to achieve a better estimation for the short-term prediction of harmful algal bloom development in both space and time by using spatially distributed TSM retrieved from remotely sensed images as physically based model inputs. In order to supply complete spatially covered datasets for the physically based model instrument: generic ecological model (GEM), this research retrieves TSM information from MERIS images by means of proper estimation techniques including biharmonic splines and self-learning cellular automata. A better estimation of HAB spatial pattern development is achieved by adding spatially distributed TSM data as inputs to original GEM model, and it proved that chlorophyll-a concentration in this area is very sensitive to TSM concentration. 相似文献