Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.     

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.     

Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China

Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO₄ and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction.     

Effect of dissolved oxygen on nitrate removal using polycaprolactone as an organic carbon source and biofilm carrier in fixed-film denitrifying reactors

Nitrate-nitrogen(NO_3~--N) always accumulates in commercial recirculating aquaculture systems(RASs) with aerobic nitrification units. The ability to reduce NO_3~--N consistently and confidently could help RASs to become more sustainable. The rich dissolved oxygen(DO)content and sensitive organisms stocked in RASs increase the difficulty of denitrifying technology. A denitrifying process using biologically degradable polymers as an organic carbon source and biofilm carrier was proposed because of its space-efficient nature and strong ability to remove NO_3~--N from RASs. The effect of dissolved oxygen(DO) levels on heterotrophic denitrification in fixed-film reactors filled with polycaprolactone(PCL) was explored in the current experiment. DO conditions in the influent of the denitrifying reactors were set up as follows: the anoxic treatment group(Group A, average DO concentration of 0.28 ± 0.05 mg/L), the low-oxygen treatment DO group(Group B, average DO concentration of 2.50 ± 0.24 mg/L) and the aerated treatment group(Group C, average DO concentration of 5.63 ± 0.57 mg/L). Feeding with 200 mg/L of NO_3~--N, the NO_3~--N removal rates were 1.53, 1.60 and 1.42 kg/m3PCL/day in Groups A, B and C, respectively. No significant difference in NO_3~--N removal rates was observed among the three treatments. It was concluded that the inhibitory effects of DO concentrations lower than 6 mg/L on heterotrophic denitrification in the fixed-film reactors filled with PCL can be mitigated.     

Performance of a water hyacinth （Eichhornia crassipes） system in the treatment of wastewater from a duck farm and the effects of using water hyacinth as duck feed

Nowadays, intensive breeding of poultry and livestock of large scale has made the treatment of its waste and wastewater an urgent environmental issue, which motivated this study. A wetland of 688 m2 was constructed on an egg duck farm, and water hyacinth (Eichhornia crassipes) was chosen as an aquatic plant for the wetland and used as food for duck production. The objectives of this study were to test the role of water hyacinth in purifying nutrient-rich wastewater and its effects on the ducks’ feed intake, egg laying performance and egg quality. This paper shows that the constructed wetland removed as much as 64.44% of chemical oxygen demand (COD), 21.78% of total nitrogen (TN) and 23.02% of total phosphorus (TP). Both dissolved oxygen (DO) and the transparency of the wastewater were remarkably improved, with its transparency 2.5 times higher than that of the untreated wastewater. After the ducks were fed with water hyacinth, the average daily feed intake and the egg-laying ratio in the test group were 5.86% and 9.79% higher, respectively, than in the control group; the di erences were both significant at the 0.01 probability level. The egg weight in the test group was 2.36% higher than in the control group (P < 0.05), but the feed conversion ratios were almost the same. The eggshell thickness and strength were among the egg qualities significantly increased in ducks fed with water hyacinth.We concluded that a water hyacinth system was e ective for purifying wastewater from an intensive duck farm during the water hyacinth growing season, as harvested water hyacinth had an excellent performance as duck feed. We also discussed the limitations of the experiment.     

Modeling of air quality with a modified two-dimensional Eulerian model： A case study in the Pearl River Delta （PRD） region of China

A modified two-dimensional Eulerian air quality model was used to simulate both the gaseous and particulate pollutant concentrations during October 21-24, 2004 in the Pearl River Delta （PRD） region, China. The most significant improvement to the model is the added capability to predict the secondary organic aerosols （SOA） concentrations because of the inclusion of the SOA formation chemistry. The meteorological input data were prepared using the CALMET meteorological model. The concentrations of aerosol-bound species such as NO3^-, NH4^＋, SO4^2-, and SOA were calculated in the fine particle size range （〈2.5 μm）. The results of the two-dimensional model were compared to the measurements at the ground level during the PRD Intensive Monitoring Campaign （IMC）. Overall, there were good agreements between the measured and modeled concentrations of inorganic aerosol components and O3. Both the measured and the modeled results indicated that the maximum hourly O3 concentrations exceeded the China National Air Quality Standard. The predicted 24-h average SOA concentrations were in reasonable agreement with those predicted by the method of minimum OC/EC ratio.