| Currently, the self-purification ability of natural water bodies such as rivers and lakes is declining. The random discharge of great amount of agricultural and industrial wastewaters without any treatment for contaminants caused serious eutrophication problems. Phosphorus has been proven to be an important limiting factor. As an effective alternative for traditional treatment technologies, constructed wetland (CW) was developed gradually on the basis of ecological functions of natural wetlands and was used increasingly for the treatment of different kinds of wastewater regarding to the advantages of lower cost, lower energy consumption, convenient operating and maintaining conditions.Integrated constructed wetland was proposed as an integration of the landscape and ecological functions of different kinds of CWs. Combing the advantages of different CWs,integrated constructed wetland has a higher stability and anti-impact ability than the individual equipment. Currently, great effort has been applied to researches about CWs. However, it is still indistinct on the contaminant dynamics in the system. Moreover, the design and construction of CWs was mainly on the basis of empirical dataset, resultingin a decline of the modeling accuracy. As a result, the ecological function of CWs could not be exhibited and the application and development of CWs was limited.From the aspect of existence forms of phosphorus in the CW with intermittent feeding water, the distributions of phosphorus in the sediment were analyzed. Based on the discipline of transference, the adsorption and desorption characteristics at the sediment-water interface were analyzed and critical parameters were estimated based on datasetfrom incubation experiments. With the method of trace experiment in the field, the actual hydraulic retention time was estimated and its distributions were simulated by the revised Gauss model. The actual flow pattern in the CW was described and the hydraulic efficiency was calculated. Based on the theory of contaminant reactor and the degrad ation first order kinetics, relative first order removal parameters for the removal of phosphorus were estimated. Through the use of dynamic software package STELLA, four submodels including the hydrology submodel, the above-ground plant biomass submodel,the suspended solid submodel and the phosphorus submodel were developed and the phosphorus dynamics in the system was quantified.Surface (0~10cm) and subsurface (10~20cm) sediment samples were collected andforms of phosphorus were extracted and analyzed in the laboratory. Impacts of particlesize and organic matter on the distributions of phosphorus were analyzed. The results indicated that the amount of total phosphorus in the sediment ranged from139.73mg/kgto242.03mg/kg. No significant difference was found between the amount of phosphorus in the surface and subsurface sediments (p>0.05) and the amount of phosphorus in the surface and subsurface sediments was198.15±32.45mg/kg and160.44±15.62mg/kg respectively. Inorganic phosphorus comprising of71.83~97.28%in the total phosphorus, was found to be the main existence form in the sediment. The phosphorus extracted bycalcium (65.17~98.71%) contributes to the most of inorganic phosphorus. The particle size has no significant impact on the distributions of phosphorus extracted by calcium. The amount of absorbable and organic phosphorus in sediments with fine particle size (φ<2μm) was greater, while the amount of phosphorus extracted by iron was smaller compared with that in other mediate. Positive relationship was observed between the amount of iron and organic phosphorus, and the organic matter, while an opposite relationshipwas observed between the calcium extracted and absorbable phosphorus, and organicmatter.By using the sediment samples collected from the CW system, batches of incubation experiments were designed in the laboratory to analyze the phosphorus adsorption/desorption characteristics at the sediment/water interface. The results indicated that net adsorption processes exist for phosphorus. The equilibrium concentration was4.23±1.77~22.52±2.71mg/L. Besides of surface adsorption, a chemical adsorption mechanism exists. T he maximum adsorption velocity was found during the first20min. The experiments reached an equilibrium status after24h and proposes intended to prolong or shorten the hydraulic retention time contribute little to the improvement of phosphorus adsorption. The sediment in the CW system has a high phosphorus adsorption ability as indicated by the high k values of250.23~403.28L/mg. The maximum phosphorus adsorptions were286.82~604.63mg/kg.Field tracer experiments were performed in order to estimate the actual hydraulic retention time and to describe its distributions. The tanks in series model was used to simulate the field datasets and analyze the flow characteristics in the CW system with intermittent feeding water. The results showed that a higher inlet elevation may favor the dispersion of tracer and lead to a higher tracer recovery. The revised Gauss model was efficient in simulating the distributions of hydraulic retention time under different operating conditions. Model parameters were different as the plant species and inlet design varies. Compared with other treatment ponds, B and F have more short flow areas.The death districts in the subsurface and macrophyte treatment ponds had no significanteffects on the removal of phosphorus (ε:0.73~0.79). A high mixture degree of flow existed in the system as indicated by the high N values of1.6~2.1. The hydraulic efficiency of the CW was23~43%.In the case of optimum operating parameters, the first-order kinetic model was used to fit data collected from the field and microcosm studies. The results showed that the influent concentration was positively correlated to the background concentration andthe removal rate constant. The averaged background concentrations for phosphorus in the CW were0.004±0.003~0.019±0.015mg/L. The removal rate constants were calculatedhigher at the estimated C*values than the values calculated at a zero background concentration. The averaged removal rate constants at the estimated C*values and zeros were0.69±0.48m/d and0.55±0.37m/d respectively. The removal rate constant declined as the system operated. The k values declined as the temperature increased during the micr ocosm studies. No significant difference was observed for the calculated θkvalues (0.936~0.957). The k20values for different treatment cells were0.366~0.925m/d and were ranked as RE>CR>CA>CT. The C*has little fluctuations as the temperature changed. TheC*in treatment cells CA, CR, CT were negatively correlated to the temperature. While the C*in treatment cell RE changed positively with the temperature variations. The averaged θc*values for different treatment cells were0.935~1.029and were ranked as RE>CR>CA>CT.The dynamic model software package STELLA was used to simulate the dynamicprocesses of water elevation, vegetation and suspended solid in the CW system. The transformation of phosphorus among different parts was quantified by integrating differentsubmodels. The results showed that the CW system in this present study has the capacity to sequester89.1%of the total phosphorus in the influent. The averaged areal phosphorus removal in different treatment ponds ranged from0.25g/m2/d to2.58g/m2/d. Themain mechanism for the removal of phosphorus in the system was sedimentation. However, the amount of phosphorus released through the processes of degradation and suspension of organic matter was about1/4. The averaged releasing velocity was0.3~6.9g/m2/d. Macrophytes play an important role in the removal of phosphorus. While most of the phosphorus absorbed by macrophytes were returned to the sediment environment during their metabolism. By harvesting the macrophyte, about43.1%of the total phosphorus could be removed at the absorption velocity of0.3~7.9g/m2/d. The phosphorus dynamic model developed in this study produced a reasonable match between the predictedand observed effluent concentration values. However, the generalization of this model should be studied further because of the discrepancy between the model hypothesizes and actual operating conditions. |
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