Simulation Research On The Distribution Of C,N And P In The Products And By-products Of Anaerobic Digestion

Anaerobic digestion(AD)of biowastes is an increasing research interest in recent years for its advantages in reducing the greenhouse gas emissions and effectively converting biomasses into sustainable energy resources.However,it is not yet an effective renewable energy generator because of the diversity of substrates,low efficiency of methane production and issues related to the treatment of supernatants and residues(by-products of biogas plants)involved in the process.Knowledge of the distributions of carbon(C),nitrogen(N)and(P)in the products and by-products during AD processes serves the purposes for the efficient conversion of C and utilization of nutrients(N and P).In this study,84 types of different digesters were conducted,and the semi-continuous reactor of swine manure was also started and operated for 135 days,with the purpose of understanding the fate of C,N and P under different conditions.Besides,the fates of C,N and P were simulated by mathematical models in which design and optimization of AD processes can be more rational.Predicting digesters behavior under changing conditions was conducted using Artificial Neural Network(ANN).The performance of semi-continuous reactor was simulated by the improved Anaerobic Digestion Model No.1(ADM 1)model considering solid-liquid process.Main contents and results of the present study are as follows:(1)The biochemical methane potential(BMP)tests were conducted for seven different substrates:corn straw,rice straw,wheat straw,swine manure from pigs fed feedstuff(SM1),swine manure from pigs fed foodstuff(SM2),cattle manure and chicken manure.The results indicate that C,N,and P contents in reaction products of swine manure were similar with that of chicken manure,while cattle manure led to the same result as straws.Moreover,there was no significance difference among three kinds of straws.The maximum CH4 yields were obtained at the ratio of 4:6,2:1,and 3:lfor feeding biowastes of rice straw to SM1,corn straw to chicken manure,and SM1 to chicken manure,respectively.The ammonia nitrogen(NH4+-N)concentration was found directly correlated to the amount of swine manure or chicken manure,but was contrary to the amount of cattle manure or straws.(2)The results of C,N,and P contents in the gas,liquid and solid phases for seven different substrates indicate that the conversion efficiency of C in a substrate into methane was highest in SM2(15.8%),and greater liquid and solid stream nutrient levels were found in the swine manures and chicken manure than in the cattle manure and straws.The mass balances of C,N and P for each different substrate were distinct,but all balances were close to 100%in this study.Further study revealed that CH4 yields and lignin of substrates fitted a linear negative relationship well,and the chemical oxygen demand(COD)/total organic carbon(TOC),NH4+-N and total phosphorus(TP)concentrations in the supernatant had positive linear relationships with the protein,total ammonia nitrogen(TAN)/protein and potassium of substrates,respectively.The NH4+-N concentrations were well simulated by the multiple linear regression model.(3)Artificial neural network(ANN)based models were explored and validated to predict the fate of C,N and P,with the inputs of the substrates composition,the ratio of different substrates,respectively.ANN model based on the principal component analysis(PC-ANN)models with the inputs of the substrates compositions were provided for estimating the fate of C(CH4 yields and COD concentrations in the supernatant),showing higher prediction accuracies than the original ANN models.The fate of N(NH4+-N concentrations in the supernatant)was well predicted by the ANN model with two inputs namely,total Kjeldahl nitrogen(TKN)and TAN in substrates.The models also developed for wide applications to validate the CH4 yields and NH4+-N concentrations for the new databases outside the established data range which obtained from the literature,with regression coefficient(R2)values of 0.705 and 0.791,respectively.The PO43-concentrations can hardly be simulated by the ANN model with the inputs of the substrates compositions,but can be predicted with the inputs of the ratio of different substrates.Besides,optimization of process parameters was conducted using ANN coupled genetic algorithm(GA)model(ANN-GA).The maximum CH4yield of 431.2 mL/g VS was predicted by ANN-GA with optimum process parameters such as substrate concentration 3 g VS/L of which straw,swine manure,cattle manure and chicken manure constitute 62.65%,1.86%,3.72%and 31.8%,respectively.(4)The results of C,N and P fates in the semi-continuous reactor for swine manure under different conditions indicate that the COD.NH4+-N,inorganic phosphorus(PO43-)and volatile fatty acids(VFAs)concentrations in the supernatant increased with the total solid(TS)concentration of swine manure.The performance and the fate of C,N and P were simulated by the improved ADM1 model for liquid-solid processes.The results indicate that the model was able to reflect the trends which were observed from the experimental data.However,the predicted CH4 yields were higher than the experimental data,and the concentrations of organic components were underestimated during the period of higher TS concentrations.The model showed good simulated results for NH4+N concentrations.The model can be applied to simulate the changes of PO43-concentrations in the overall trend but failed to simulate the fluctuation trends of it.The simulated results of carbohydrates,protein and lipids were higher than the experimental data under the condition of higher TS concentration,indicating that a proportion of substrate remained unhydrolyzed in the digesters.According to the comparison of predicted and experimental data,means for further promotion of the CH4 yields are supposed to be improvement the biodegradability of substrate and reactor,promoting the hydrolysis of substrate,immobilizing strains,as well as reducing NH4+-N concentrations in the system.