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.

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.

A novel time-span input neural network for accurate municipal solid waste incineration boiler steam temperature prediction

A novel time-span input neural network was developed to accurately predict the trend of the main steam temperature of a 750-t/d waste incineration boiler.Its historical operating data were used to retrieve sensitive parameters for the boiler output steam temperature by correlation analysis.Then,the 15 most sensitive parameters with specified time spans were selected as neural network inputs.An external testing set was introduced to objectively evaluate the neural network prediction capability.The results show that,compared with the traditional prediction method,the time-span input framework model can achieve better prediction performance and has a greater capability for generalization.The maximum average prediction error can be controlled below 0.2°C and 1.5°C in the next 60 s and 5 min,respectively.In addition,setting a reasonable terminal training threshold can effectively avoid overfitting.An importance analysis of the parameters indicates that the main steam temperature and the average temperature around the high-temperature superheater are the two most important variables of the input parameters;the former affects the overall prediction and the latter affects the long-term prediction performance.

微生物电解池耦合厌氧膜生物反应器运行性能及微生物学机理研究（英文）

目的:将微生物电解池(MEC)与厌氧膜生物反应器(AnMBR)耦合,构建MEC-AnMBR系统,以期同步实现污水高效处理和膜污染缓解,推动膜生物反应器的理论创新和技术创新.创新点:1.将MEC与AnMBR耦合,构建MEC-AnMBR系统用于高浓度有机废水的处理;2.研究反应器运行和微生物群落之间的关系;3.探究膜污染运行周期中各膜污染阶段微生物代谢产物与自身代谢活性的变化规律.方法:1.启动和运行MEC-AnMBR反应器,并与传统AnMBR对照,综合考察MEC-AnMBR反应器的运行性能;2.利用高通量测序技术对传统AnMBR和MEC-AnMBR各膜污染阶段的阴极膜表面微生物群落结构及多样性进行研究,并综合分析MEC-AnMBR反应器的运行特性与微生物群落间的相互关系;3.对MEC-AnMBR反应器阴极膜组件及微生物分泌物进行原位观察,并研究其在膜污染运行周期中各膜污染阶段微生物代谢产物与自身代谢活性的变化规律.结论:1.成功构建微生物电解池MEC-AnMBR生物系统;2.与AnMBR相比,MEC-AnMBR中的化学需氧量(COD)去除效率和甲烷产量分别增加6.7%和77.1%;3.与AnMBR相比,MEC-AnMBR的膜污染因细胞外聚合物和可溶性微生物产物增长缓慢而大大减少;4.高通量测序分析表明MEC-AnMBR富含互养菌属(Synergistaceae-uncultured)和互营热菌属(Thermovirga),而Thermovirga是关键的功能性微生物;5.这些结果表明MEC-AnMBR可同时提高反应器效率并减轻膜污染.

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.

The acceleration degradation processes of different aged refuses with the forced aeration for landfill reclamation

Forced aeration is one of the promising ways to accelerate landfill reclamation,and understanding the relation between aeration rates and waste properties is the prerequisite to implementing forced aeration under the target of energy saving and carbon reduction.In this work,landfill reclamation processes with forced aeration were simulated using aged refuses(ARs)of 1,4,7,10,and 13 disposal years,and the potential of field application was also investigated based on a field project,to identify the degradation rate of organic components,the O_(2)consumption efficiency and their correlations to microbes.It was found that the removal rate of organic matter declined from 20.3%(AR_(1))to 12.6%(AR_(13)),and that biodegradable matter(BDM)decreased from 5.2%to 2.4%at the set aeration rate of 0.12 L O_(2)/kg waste(Dry Matter,DM)/day.A linear relationship between the degradation rate constant(K)of BDM and disposal age(x)was established:K=−0.0002193x+0.0091(R^(2)=0.854),suggesting that BDM might be a suitable indicator to reflect the stabilization of ARs.The cellulose/lignin ratio decrease rate for AR1(18.3%)was much higher than that for AR13(3.1%),while the corresponding humic-acid/fulvic-acid ratio increased from 1.44 to 2.16.The dominant bacteria shifted from Corynebacterium(9.2%),Acinetobacter(6.6%),and Fermentimonas(6.5%),genes related to the decompose of biodegradable organics,to Stenotrophomonas(10.2%)and Clostridiales(3.7%),which were associated with humification.The aeration efficiencies of lab-scale tests were in the range of 5.4–11.8 g BDM/L O_(2)for ARs with disposal ages of 1–13 years,and in situ landfill reclamation,ARs with disposal ages of 10–18 years were around 1.9–8.8 g BDM/L O_(2),as the disposal age decreased.The increased discrepancy was observed in ARs at the lab-scale and field scale,indicating that the forced aeration rate should be adjusted based on ARs and the unit compartment combined,to reduce the operation cost.