Development of a Novel Feedforward Neural Network Model Based on Controllable Parameters for Predicting Effluent Total Nitrogen

The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.

The implication from six years of field experiment:the aging process induced lower rice production even with a high amount of biochar application

The single high-dose application of biochar to increase rice yield has been well reported.However,limited information is available about the long-term effects of increasing rice yield and soil fertility.This study was designed to perform a 6-year field experiment to unveil the rice yield with time due to various biochar application strategies.Moreover,an alternative strategy of the Annual Low dose biochar application(AL,8×35%=2.8 t ha^(−1))was also conducted to make a comparison with the High Single dose(HS,22.5 t ha^(−1)),and annual Rice Straw(RS,8 t ha^(−1))amendment to investigate the effects on annual rice yield attributes and soil nutrient concentrations.Results showed that the rice yield in AL with a lower biochar application exceeded that of HS significantly(p<0.05)in the 6th experimental year.The rice yield increased by 14.3%in RS,10.9%in AL,and 4.2%in HS.The unexpectedly higher rice yield in AL than HS resulted from enhanced soil total carbon(TC),pH,and available Ca.However,compared to AL,liable carbon fraction increased by 33.7%in HS,while refractory carbon fraction dropped by 22.3%.Likewise,biochar characterization showed that more oxygen functional groups existed in HS than in AL.Decreasing inert organic carbon pools due to the constant degradation of the aromatic part of biochar in HS led to a lower soil TC than AL,even with a higher amount of biochar application.Likewise,the annual depletion lowered the soil pH and available Ca declination in HS.Based on the obtained results,this study suggested AL as a promising strategy to enhance rice productivity,soil nutrient enrichment,and carbon sequestration in the paddy ecosystem.