Metal distribution characteristic of MSWI bottom ash in view of metal recovery

Bottom ash is the major by-product of municipal solid waste incineration(MSWI), and is often reused as an engineering material, such as road-base aggregate. However, some metals(especially aluminum) in bottom ash can react with water and generate gas that could cause expansion and failure of products containing the ash; these metals must be removed before the ash is utilized. The size distribution and the chemical speciation of metals in the bottom ash from two Chinese MSWI plants were examined in this study, and the recovery potential of metals from the ash was evaluated. The metal concentrations in these bottom ashes were lower than that generated in other developed countries. Specifically, the contents of Al,Fe, Cu and Zn were 18.9–29.2, 25.5–32.3, 0.7–1.0 and 1.6–2.5 g/kg, respectively. Moreover,44.9–57.0 wt.% of Al and 55.6–75.4 wt.% of Fe were distributed in bottom ash particles smaller than 5 mm. Similarly, 46.6–79.7 wt.% of Cu and 42.9–74.2 wt.% of Zn were concentrated in particles smaller than 3 mm. The Fe in the bottom ash mainly existed as hematite, and its chemical speciation was considered to limit the recovery efficiency of magnetic separation.     

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.     

Shifts in microbial community structure and diversity in a MBR combined with worm reactors treating synthetic wastewater

The chemical oxygen demand (COD) and NH₃-N removal, membrane fouling, sludge characteristics and microbial community structure in a membrane bioreactor (MBR) coupled with worm reactors (SSBWR) were evaluated for 210 days. The obtained results were compared to those from a conventional MBR (C-MBR) operated in parallel. The results indicated that the combined MBR (S-MBR) achieved higher COD and NH₃-N removal efficiency, slower increase in membrane fouling, better sludge settleability and higher activities of the related enzymes in the activated sludge. Denaturing gradient gel electrophoresis was used to analyze the microbial community structures in the C-MBR and the S-MBR. The microbial community structure in the S-MBR was more diverse than that in the C-MBR. Additionally, the slow-growing microbes such as Saprospiraceae, Actinomyces, Frankia, Clostridium, Comamonas, Pseudomonas, Dechloromonas and Flavobacterium were enriched in the S-MBR, further accounting for the sludge reduction, membrane fouling alleviation and wastewater treatment.     

北京市郊区夏季臭氧重污染特征及生成效率

为研究北京郊区夏季O₃(臭氧)重污染过程特征及O₃生成的光化学敏感性,基于2016年夏季在北京郊区开展的针对O₃及其相关污染物的强化观测试验(7月23日—8月31日,共计40 d),分析了观测期间O₃浓度[以φ(O₃)计]变化特征、O₃重污染过程主控因素与O₃敏感性化学特征.结果表明:观测期间φ(O₃)超标时有发生,最大小时φ(O₃)为151.1×10-9,其中有15 d的φ(O₃)最大8 h滑动平均值(O₃-max-8h)超过了GB 3095—2012《环境空气质量标准》二级标准限值,占观测天数的37.5%;不同O₃重污染过程成因有所不同,城市烟羽传输的污染物对郊区O₃重污染过程影响显著(观测期间臭氧重污染过程:过程1,7月27—29日;过程3,8月9—11日;过程4,8月16日;过程5,8月21—24日),区域光化学污染对郊区O₃重污染过程也有贡献(观测期间O₃重污染过程2:8月4—6日);结合后向气流轨迹进一步辅助说明了不同重污染过程中O₃的来源不同.研究还发现,观测区域存在反“周末效应”现象,说明观测区域周末受人为影响较为明显;基于观测数据计算的OPE(O₃生成效率)分析了O₃光化学敏感性表明,在有OPE值的22 d内NO_x控制区和VOCs控制区出现的概率(41%)相等,即观测区域O₃对NO_x和VOCs均敏感;此外还发现,在O₃重污染过程中光化学敏感性会随其反应进程发生改变,由NO_x控制区逐渐转变为VOCs控制区.      

重庆市夏秋季VOCs对臭氧和二次有机气溶胶生成潜势的估算

为估算重庆市夏秋季VOCs（挥发性有机物）对O₃和SOA（二次有机气溶胶）的生成潜势,利用在线GC-MS/FID在2015年8月22日-9月23日对重庆市区点和郊区点VOCs开展了为期一个月的实时观测,获得市区点和郊区点$ \varphi $（TVOCs）（总挥发性有机物）分别为41.35×10-9和22.72×10-9,其中市区点以烷烃（35.2%）和烯炔烃（25.2%）为主,郊区点以含氧挥发性有机物（oxygenated volatile organic compounds,OVOCs）（30.6%）和烷烃（26.0%）为主.结合最大增量反应活性量化市区点和郊区点VOCs的OFPs（臭氧生成潜势）分别为149.11×10-9和71.09×10-9,市区点OFPs最大的是乙烯、丙烯、甲苯、C8和C9的芳香烃等,郊区点OFPs最大的VOCs是丙烯醛、异戊二烯和甲基乙烯基酮.结合气溶胶生成系数量化郊区点和市区点VOCs对SOA的生成贡献分别为0.36和1.26 μg/m3,相比国内其余城市VOCs的SOAP（二次有机气溶胶生成潜势）较小,主要以甲基环己烷、正壬烷、正葵烷和十一烷等高碳烷烃,以及甲苯、苯、二甲苯和乙苯等芳香烃的SOAP为主.研究显示,控制烯炔烃和芳香烃的浓度有助于控制重庆市O₃的生成,控制高碳烷烃和芳香烃则有助于控制重庆市SOA的生成.      

北京市铺装道路降尘污染特征及来源

为研究北京市道路降尘在不同季节的污染特征及来源,选取北京市4条典型道路得到64个采样点的道路尘样品,采集的道路尘样品经过预处理得到75 μm以下的颗粒物,经过再悬浮及实验室分析得到PM_2.5的粒径分布和化学成分谱.结果表明:不同采样高度及不同道路类型的颗粒物粒径大体分布规律一致,颗粒物质量频率存在三个峰值,分别为0.75 μm（微粒径）、2.50 μm（小粒径）、4.50 μm（大粒径）;各季节的降尘颗粒物的化学组分中质量分数最大的是元素,主要元素（含量>1%）季节变化为冬季>春季>秋季>夏季,元素富集因子法得到污染元素为Cr、Cd、Sn、Cu、Zn、Pb、As,双重元素为Bi、Ti、Ni、W、Mg、Ca、TI、Mo、V、Fe、Zr、Ba,其余16种为非富集元素;颗粒物中离子质量分数在夏季最大为9.31%,春季、秋季、冬季的离子质量分数相差不大,其中Ca2+、NO₃-、Cl-、SO₄2-占总离子质量的80%左右;碳素中w（OC）和w（EC）的季节变化均为夏季>秋季>春季>冬季,OC/EC[w（OC）/w（EC）]的季节变化规律为冬季>春季>秋季>夏季.不同季节w（OC）和w（EC）的相关性大小为夏季>秋季>春季>冬季.对PM_2.5中化学组分来源分析表明,污染元素受机动车和建筑尘影响较大,与机动车尾气相比,机动车磨损造成的污染也不容小视;燃煤影响一直存在,但供暖期污染有所改善.机动车尾气、建筑尘及土壤尘对离子均有贡献,在夏季土壤尘、建筑尘、二次反应的综合影响较大,春季土壤尘影响更为突出.碳在夏秋季节受汽车尾气和建筑尘的影响较大,夏季二次反应影响不大;冬季除气象因素外,燃煤和生物质燃烧也不可忽视;春季土壤尘影响较为突出.      

Control of aliphatic halogenated DBP precursors with multiple drinking water treatment processes: Formation potential and integrated toxicity

The comprehensive control efficiency for the formation potentials(FPs) of a range of regulated and unregulated halogenated disinfection by-products(DBPs)(including carbonaceous DBPs(C-DBPs), nitrogenous DBPs(N-DBPs), and iodinated DBPs(I-DBPs)) with the multiple drinking water treatment processes, including pre-ozonation, conventional treatment(coagulation–sedimentation, pre-sand filtration), ozone-biological activated carbon(O_3-BAC) advanced treatment, and post-sand filtration, was investigated. The potential toxic risks of DBPs by combing their FPs and toxicity values were also evaluated.The results showed that the multiple drinking water treatment processes had superior performance in removing organic/inorganic precursors and reducing the formation of a range of halogenated DBPs. Therein, ozonation significantly removed bromide and iodide,and thus reduced the formation of brominated and iodinated DBPs. The removal of organic carbon and nitrogen precursors by the conventional treatment processes was substantially improved by O_3-BAC advanced treatment, and thus prevented the formation of chlorinated C-DBPs and N-DBPs. However, BAC filtration leads to the increased formation of brominated C-DBPs and N-DBPs due to the increase of bromide/DOC and bromide/DON.After the whole multiple treatment processes, the rank order for integrated toxic risk values caused by these halogenated DBPs was haloacetonitriles(HANs)》haloacetamides(HAMs) haloacetic acids(HAAs) trihalomethanes(THMs) halonitromethanes(HNMs) 》I-DBPs(I-HAMs and I-THMs). I-DBPs failed to cause high integrated toxic risk because of their very low FPs. The significant higher integrated toxic risk value caused by HANs than other halogenated DBPs cannot be ignored.     

Nano-sized Fe2O3/Fe3O4 facilitate anaerobic transformation of hexavalent chromium in soil–water systems

The purpose of this study is to investigate the effects of nano-sized or submicro Fe_2O_3/Fe_3O_4 on the bioreduction of hexavalent chromium(Cr(VI)) and to evaluate the effects of nano-sized Fe_2O_3/Fe_3O_4 on the microbial communities from the anaerobic flooding soil.The results indicated that the net decreases upon Cr(VI) concentration from biotic soil samples amended with nano-sized Fe_2O_3(317.1 ± 2.1 mg/L) and Fe_3O_4(324.0 ± 22.2 mg/L) within21 days,which were approximately 2-fold of Cr(VI) concentration released from blank control assays(117.1 ± 5.6 mg/L).Furthermore,the results of denaturing gradient gel electrophoresis(DGGE) and high-throughput sequencing indicated a greater variety of microbes within the microbial community in amendments with nano-sized Fe_2O_3/Fe_3O_4 than the control assays.Especially,Proteobacteria occupied a predominant status on the phylum level within the indigenous microbial communities from chromium-contaminated soils.Besides,some partial decrease of soluble Cr(VI) in abiotic nano-sized Fe_2O_3/Fe_3O_4 amendments was responsible for the adsorption of nano-sized Fe_2O_3/Fe_3O_4 to soluble Cr(VI).Hence,the presence of nano-sized Fe_2O_3/Fe_3O_4 could largely facilitate the mobilization and biotransformation of Cr(VI) from flooding soils by adsorption and bio-mediated processes.     

结合WRF/Chem和PMF方法的邯郸市PM_(2.5)源解析

<正>向源模型法和反向受体模型法是进行城市PM_(2.5)源解析的2种方法,两者各有所长。该研究应用三维空气质量模型Weather Research and Forecasting Model with Chemistry(WRF-Chem)模型和受体模型Positive Matrix Factorization(PMF),以2014年10月为研究时段,分别对邯郸市的细微颗粒物(PM_(2.5))进行源解析。PMF模型的解析结果表明,邯郸市PM_(2.5)来源为二次源30.2%,燃煤源25.4%、金属冶炼源15.1%、机动车源14.4%、扬尘源9.8%,生物质燃烧源5.2%。应用WRF-Chem模型,Brute-Force方法解析出的结果为,在本地源贡献中,工业源贡献了49.0%,民用源11.9%、农业源9.6%、交通源3.8%和电厂源-1.5%(负值由于PM_(2.5)前体物之间的非线性反应所致)。应用源模型对二次成分(SO_4~(2-)、NO_3~-和NH_4~+)进行再解析,结果显示,燃煤源源贡献率最大,达到25.7%,其次分别为农业源(24.0%)、工业源(6.5%)、生物质源(1.8%)和机动车(0.03%)。结合2种方法得出,邯郸市的PM_(2.5)中,本地燃煤源贡献了37.1%,其次分别为金属冶炼源(18.4%)、机动车源(15.1%)、扬尘源(13.3%)、生物质燃烧源(6.2%)。     

大冶湖表层水和沉积物中重金属污染特征与风险评价

于2014年4月采集大冶湖表层水和表层沉积物,用原子吸收分光光度法测定其重金属含量,并基于健康风险评价模型和潜在生态风险指数法开展表层水和沉积物重金属污染的潜在健康风险和生态风险评价.结果表明,表层水和沉积物重金属(Ni、Cd、Cu和Pb)含量平均值分别为49.27、2.19、12.18、12.13μg·L~(-1)和78.46、77.13、650.13、134.22 mg·kg~(-1).富集系数显示,Cd、Cu和Pb均为重度富集,尤其是Cd累积最为明显.与国内典型湖泊重金属污染相比,表层水和沉积物中重金属元素含量均相对较高.表层水和沉积物重金属元素均表现为湖湾处含量较高,中部含量较均匀的分布规律,其来源主要受多种人为活动污染.环境风险评价显示,重金属类化学物质通过饮水途径产生健康风险范围为9.77E-08~1.63E-05 a-1,Ni和Cd是水环境健康风险的优先管理对象.沉积物重金属的潜在生态风险高低为CdCuPbNi,其中Cd是生态风险的贡献元素.