Impacts of natural weathering on the transformation/neoformation processes in landfilled MSWI bottom ash: a geoenvironmental perspective

Natural weathering processes are significant mechanisms that noticeably affect the fundamental nature of incineration ash residues. To provide a greater understanding of these processes, a MSWI (mono)landfill site in the north east of the US was selected as the target for systematic investigation of the natural weathering of bottom ash residues. Samples of various ages were collected from locations A (1 yr), B (10 yrs), C (13-14 yrs) and D (20 yrs) of the landfill in 2009. We investigated the phase transformation of the collected bottom ash particles, neoformation processes as well as the behavior and distribution of certain heavy metals (Cu, Pb, Zn, Ni, and Cr) in the neoformed phases using optical microscopy, SEM-EDX, and bulk examinations. Key findings: at the preliminary stage, the waste metallic particles (Al, Fe, and Cu) and unstable minerals such as lime, portlandite, ettringite and hydrocalumite convert to oxide and hydroxide (hydrate) phases, calcite, alumina gel and gypsum. At the intermediate stage, the decomposition of melt products including magnetite spinels and metallic inclusions is triggered due to the partial dissolution of the melt glass. At the longer time horizon it is possible to track the breakdown of the glass phase, the extensive formation of calcite and anhydrite, Al-hydrates and more stable Fe-hydrates all through the older ash deposits. Among the dominant secondary phases, we propose the following order based on their direct metal uptake capacity: Fe-hydrates>Al-hydrates>calcite. Calcite was found to be the least effective phase for the direct sorption of heavy metals. Based on overall findings, a model is proposed that demonstrates the general trend of ash weathering in the landfill.     

Electrochemical Detection of Pathogen Infection Using Cell Chip

The immobilized cell using self-assembled synthetic oligopeptide was applied to the electrochemical detection of pathogen infection. Thin films based on cysteine-terminated synthetic oligopeptides were fabricated for the immobilization of HeLa cell on gold (Au) substrate. Layer formation and immobilization of the cell were investigated with surface plasmon resonance (SPR) and electrochemical impedance spectroscopy (EIS). Experimental results showed that the thin film of cysteine-terminated synthetic oligopeptide was successfully fabricated and it could be applied for the immobilization of HeLa cells. The adhered living cell was exposed to E. coli O157:H7, which induced the change of SPR angle and electrochemical impedance signal. The proposed cell immobilization method using self-assembly technique can be applied to construct the cell microarray for on-site pathogen monitoring.     

太赫兹时域光谱法测定水中重金属离子

采用太赫兹时域光谱法采集溶液时域数据,经过去噪和时域分析,汞、镉、铜离子溶液分别在频率为1.7THz、0.7THz、1.2THz位置上建立线性模型,得到拟合效果最佳的决定系数,分别为0.969、0.896、0.932。该方法检出限为0.001mg/L~0.002mg/L,空白加标样6次测定结果的RSD为2.0%,加标回收率为94.0%～102%。将该方法用于测定某污水处理厂两个进口的实际水样,结果汞离子未检出。     

石墨炉原子吸收法测定土壤中的锡

研究了硝酸－高氯酸体系消解、石墨炉原子吸收法测定土壤中锡的方法。采用酒石酸－锆复合溶液作基体改进剂,锆涂层热解石墨管为原子化器。方法的检出限为3μg/L(样品消解溶液)。实际样品测定的相对标准偏差小于7.5%,加标回收率为90%～97%。      

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

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste. ● Feature selection methods were used to improve models’ prediction accuracy. ● The best model predicted C, H, and N contents with accuracy R ² ≥ 0.93, 0.87, 0.97. ● Some suitable models showed insensitivity to spectral noise. ● Under moisture interference, the models still had good prediction performance. 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.     

盐酸胍诱导的apo-CP43去折叠过程

膜蛋白生物合成与色素组装中蛋白的稳定性可以通过去折叠条件与过程分析得到.利用色氨酸荧光光谱和ANS荧光光谱研究了apo-CP43在盐酸胍条件下的稳定性.色氨酸荧光光谱观测到apo-CP43在盐酸胍作用下去折叠进程的主要特征:荧光强度先是逐渐降低,之后再逐渐升高,而最大荧光发射峰位置则一直持续红移.盐酸胍处理后apo-CP43的F360 nm/F335 nm比值逐渐增大,表明荧光最大发射峰逐步红移.当盐酸胍浓度约为5.5 mol/L时,去折叠比例趋于相对稳定状态,说明此时apo-CP43已经基本完成去折叠.荧光相图法结果显示盐酸胍诱导apo-CP43变性的过程符合三态模型.ANS荧光测定数据显示盐酸胍处理之后最大ANS荧光发射峰位置红移,并且荧光强度逐渐降低.以上数据表明在盐酸胍条件下apo-CP43是一个相对比较稳定的蛋白.     

水体冻结过程中卤乙酸前体物在水-冰体系中的分配研究

通过室内模拟试验,研究了水体冻结过程中,水体中溶解性有机物(DOM)和卤乙酸前体物在水-冰体系中的分配规律.按照DOM在XAD树脂上的吸附特性将其分为5个部分:疏水性有机酸(HPO-A),疏水性中性有机物(HPO-N),过渡亲水性有机酸(TPI-A),过渡亲水性中性有机物(TPI-N)和亲水性有机物(HPI).结果表明:在水体冻结过程中,5种DOM组分在水相中的DOC浓度均随冷冻时间的增长而增加,呈现冷冻浓缩效应.与溶解性有机碳(DOC)所表征的整体有机物相比,5种DOM组分中的卤乙酸(HAAs)前体物更倾向于停留在水相中浓缩.在5种DOM组分中,HPI是主要的HAAs前体物.5种DOM组分在未冻结水中的UV-254与HAAFP均表现出一定相关性,其中HPO-A, TPI-A和HPI的UV-254与HAAFP达到极显著水平.然而在融冰水中,这5种DOM组分的UV-254与HAAFP的相关性均不显著.     

盐度冲击下MBR污泥SMP和EPS的三维荧光光谱解析

利用三维荧光(EEM)技术研究了不同盐度冲击下膜-生物反应器(MBR)污泥微生物溶解性产物(SMP)和胞外聚合物(EPS)的变化规律,分析不同盐度冲击下MBR污泥SMP和EPS的EEM图谱.结果表明,当冲击盐度大于2.5g/L时,SMP的EEM图谱中色氨酸荧光峰B(270nm,350nm)、类胡敏酸荧光峰C(375,475nm)、类富里酸荧光峰D(260,460nm)以及EPS的EEM图谱中色氨酸荧光峰B的荧光强度随冲击盐度的提升而增加,EPS的EEM图谱中类胡敏酸C峰的荧光强度则随冲击盐度的提升而下降.用平行因子分析(PARAFAC)方法确定EEM图谱中存在的4个组分,分别为类蛋白质组分C1(230/280,350nm),类胡敏酸组分C2(290/310,380nm)、C3(290/360,460nm)和C4(270/340,440nm);当冲击盐度大于2.5g/L时,SMP中C1、C3和C4组分的荧光强度与冲击盐度呈正相关,而EPS中C3和C4组分的荧光强度分别与冲击盐度呈正相关和负相关,其相关系数均≥0.90;SMP中类蛋白质荧光组分和类胡敏酸组分的荧光强度之和分别与测定的蛋白质含量和胡敏酸含量呈明显的正相关性,相关系数均＞0.93,可作为荧光组分强度定量计算的依据,而EPS中此相关性并不明显.     

污水厂二级出水溶解性有机物臭氧化特性研究

采用液相色谱荧光检测器将三维荧光图谱与凝胶色谱分子量分布相结合,对污水处理厂二级出水溶解性有机物(EfOM)的臭氧化反应特性进行了研究.结果表明臭氧会使得二级出水溶解性有机物三维荧光强度明显降低.HPLC-SEC的结果表明臭氧不会改变腐殖质类物质的分子量分布,但臭氧会与小分子蛋白类物质发生反应.根据制备液相的分析结果,小分子蛋白类物质中含有大量苯环及其他共轭结果物质,因此臭氧会优先与小分子蛋白类物质发生反应.同时,XPS分析结果表明臭氧在低投加量下就会与苯环结构反应,提高脂肪类饱和有机物含量,随着投加量进一步升高,含氧官能团(羰基,羧基)数量有所升高.     

融雪期城市河流中溶解性有机物的时空分布特征

以沈阳市新开河为研究对象,考察了河水中溶解性有机物(DOM)含量的月份变化,以及融雪期河水中DOM含量和特性的时空变化规律.利用XAD树脂将DOM分为5个部分:疏水性有机酸(HPO-A),疏水性中性有机物(HPO-N),过渡亲水性有机酸(TPI-A),过渡亲水性中性有机物(TPI-N)和亲水性有机物(HPI).结果表明,融雪期河水中的溶解性有机碳(DOC)浓度较高,HPO-N和TPI-N是融雪期河水中的主要DOM组分,并且DOM中的荧光物质主要为类芳香族蛋白质荧光物质和类腐植酸荧光物质.融雪期水体中的DOC、波长254nm处的紫外吸光度(UV-254)和三卤甲烷生成势(THMFP)呈先降低然后波动最后升高的变化趋势.特征紫外吸光度(SUVA)和三卤甲烷生成活性(STHMFP)与以上三者的变化规律相反.融雪期河水中的DOC受污水排放影响大,有排污口处的DOC含量明显大于其他区域.污水排放也使受纳水体中UV-254对THMFP的指示作用减弱.