Study On Co-pyrolysis And Co-combustion Characteristics Of Sewage Sludge With Wet Waste

With the rapid development of China’s economy and the increasing pace of urbanization,the production of sewage sludge(SS)has increased sharply.SS contains various harmful substances,it can seriously pollute the ecological environment.Biomass,as the fourth largest energy source after coal,petroleum,and natural gas,has a zero or even negative carbon footprint throughout its life cycle.Adding biomass can improve the combustion performance of sewage sludge and reduce carbon emissions,which is of great significance for achieving the "double carbon" target.Seven groups of samples with wet waste(Moisture content is 77.4%)and sewage sludge mixed in different proportions(0%,10%,30%,50%,70%,90%,and 100%wet waste)were named WW,S9W1,S7W3,S5W5,S3W7,S1W9,and SS,respectively.In this paper,the co-pyrolysis and co-combustion characteristics of SS,WW,and their mixtures were studied from the perspectives of thermogravimetric analysis(TGA),Fourier transform infrared spectroscopy(FTIR),gas chromatography/mass spectrometry(GC/MS),kinetics,synergistic effects,and artificial neural networks.(1)A TG analyzer was used to conduct weight loss experiments on SS and WW,and to analyze the influence of WW mixing on the weight loss process.The experimental results showed that the addition of WW can effectively enhance the pyrolysis and combustion performance of SS.With the increase of WW,the comprehensive pyrolysis index(CPI)showed exponential growth,effectively improving the pyrolysis performance of the mixture.The comprehensive combustion performance index(CCI)grows rapidly,changed from 2.25×107%2·min-2·℃-3 to 13.70×107%2·min-2·℃-3,significantly enhancing the combustion performance of the mixture,and greatly compensating for the lower CCI of SS.(2)In this paper,the theoretical and experimental values of pyrolysis were compared,which can reveal their interaction.For S9W1,S5W5,and S7W3,the mixtures showed good synergistic effects at temperatures below 320℃,and exhibited a certain inhibitory effect at temperatures above 320℃.S3W7 exhibited synergistic effects throughout the pyrolysis process,with the best pyrolysis performance.By studying the effect of mixing ratios on gas emissions during the pyrolysis and combustion processes through the difference between experimental and calculated values of gas absorption,it was found that the addition of wet garbage had an inhibitory effect on gas emissions during pyrolysis and combustion processes,and S3W7 could significantly reduce the CO2 emissions throughout the temperature range.(3)A Fourier transform infrared spectrometer was used to detect the gaseous products of co-pyrolysis of SS and WW.The experiment found that the gas generation was highest at 310℃,and the main products were-OH,-CH,CO2,C=C,phenol,CO,and NH3,with the C=O functional group having the highest proportion.Gas chromatography/mass spectrometry was used to detect the gaseous components of S3W7 at 310℃ under a nitrogen atmosphere,revealing that:1)nitrides were formed from N and carbonyl in a small amount of amino acids in SS and WW;2)carbon hydrocarbons containing C=O were produced from the thermal decomposition of hemicellulose and lignin in WW,which accounted for the largest proportion of gaseous products;3)furans(furfural)produced from the thermal decomposition of SS,and furans(2-methyl furan,5-methyl-2(5H)-furanone,etc.)produced as phenolic intermediates in the thermal decomposition of WW.(4)The Flynn-Wall-Ozawa(FWO)and Kissinger-Akahira-Sunose(KAS)models ere used to calculate the reaction activation energy of the pyrolysis and combustion processes of SS mixed with WW.The activation energy of WW was lower than that of SS and with increasing amounts of wet garbage added,the reaction activation energy gradually decreased,which was beneficial to the pyrolysis and combustion of SS.(5)An artificial neural network(ANN)model,ANN 19(5*11*1),was developed using the weight loss data during pyrolysis and combustion processes,which was the most suitable for predicting co-pyrolysis and co-combustion.ANN 19 has two hidden layers:the first hidden layer has 5 neurons,and the second hidden layer has 11 neurons.The experimental and predicted data were in good agreement,indicating that ANN 19 was the optimal model for predicting the thermogravimetric curves of SS mixed with WW.