Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

Elemental composition is a key parameter in solid waste treatment and disposal. This study has proposed a method based on infrared spectroscopy and machine learning algorithms that can rapidly predict the elemental composition (C, H, N, S) of solid waste. Both noise and moisture spectral interference that may occur in practical application are investigated. By comparing two feature selection methods and five machine learning algorithms, the most suitable models are selected. Moreover, the impacts of noise and moisture on the models are discussed, with paper, plastic, textiles, wood, and leather as examples of recyclable waste components. The results show that the combination of the feature selection and K-nearest neighbor (KNN) approaches exhibits the best prediction performance and generalization ability. Particularly, the coefficient of determination (R2) of the validation set, cross validation and test set are higher than 0.93, 0.89, and 0.97 for predicting the C, H, and N contents, respectively. Further, KNN is less sensitive to noise. Under moisture interference, the combination of feature selection and support vector regression or partial least-squares regression shows satisfactory results. Therefore, the elemental compositions of solid waste are quickly and accurately predicted under noise and moisture disturbances using infrared spectroscopy and machine learning algorithms.

Emission control and phase migration of PCDD/Fs in a rotary kiln incinerator:hazardous vs medical waste incineration

This study was carried out in a full-scale(50 t/d)rotary kiln incinerator to explore the removal characteristics of polychlorinated dibenzo-p-dioxins and dibenzofurans(PCDD/Fs)by different units of air pollution control devices(APCDs),and special interest was focused on the“memory effect”phenomenon of PCDD/Fs in the wet scrubber(WS),which usually caused an undesirable rise in PCDD/F emission concentrations.The general removal efficiency of PCDD/Fs by APCDs was 99.4%(from 14.11 at exhaust heat boiler(EHB)outlet to 0.09 ng I-TEQ/Nm^(3)at stack)under medical waste(MW)incineration condition,and 99.2%(from 19.91 to 0.16 ng I-TEQ/Nm^(3))under hazardous waste(HW)incineration condition.The PCDD/F concentrations in flue gas decreased along the APCDs except for WS,in which the“memory effect”was observed.In detail,WS largely increased the I-TEQ concentration of gas-phase PCDD/Fs from 0.047 to 0.188 ng I-TEQ/Nm^(3)in the flue gas,and the concentration of particulate-phase PCDD/Fs increased from 0.003 to 0.030 ng I-TEQ/Nm^(3).In addition,this study found that phase migration promoted the accumulation of PCDD/Fs in scrubbing water,and the flow entrainment phenomenon played a great role in causing the“memory effect”.The PCDD/F concentrations of fly ash collected from cyclone and fabric filter(FF)were as high as 4.23 and 6.99 ng I-TEQ/g,respectively,which had exceeded the national landfill limitation(3 ng I-TEQ/g)in China.The system balance calculations revealed that APCDs promoted the migration of PCDD/Fs from the gas-phase to the particulate-phase,which caused fly ash to be the main carrier of PCDD/Fs and led to excessive emissions.The results of this study can contribute to the optimized design of combustion conditions and system cleaning for controlling PCDD/F emissions from rotary kiln incinerators.

Novel development of VO_(x)-CeO_(x)-WO_(x)/TiO_(2) catalyst for low-temperature catalytic oxidation of chloroaromatic organics

A novel selective catalytic reduction(SCR)catalyst with high catalytic activity on chloroaromatic organics at lower temperatures(160-180℃)is critical for municipal solid waste incineration(MSWI)plants.This study prepares a series of honeycomb-type VO_(x)/TiO_(2) catalysts and finally develops a new low-temperature catalyst with high catalytic activity in eliminating chloroaromatic organics.Based on the conversion efficiency(CE)of 1,2-dichlorobenzene(1,2-DCB)and CO_(2) selectivity,the optimal VO_(x) content of 4.06%(in weight)in VO_(x)/TiO_(2) catalyst is first confirmed.By modifying CeO_(x) and WO_(x),a novel honeycomb-type catalyst of VO_(x)-CeO_(x)-WO_(x)/TiO_(2) achieves the highest CE(93.1%-93.6%)and CO_(2) selectivity(40.9%-60.7%)at 150-200℃.It was found that the CeO_(x) and WO_(x) can improve the catalytic activity by enriching the surface content of V and O,increasing the proportion of V5+and Osurf,enlarging the supply source of reactive oxygen species and their storage capacity,and accelerating the redox cycle of VO_(x),CeO_(x),WO_(x),and reactive oxygen species.This study can guide the development of monolithic low-temperature catalysts with high catalytic activity in eliminating chloroaromatic organics in MSWI flue gas.