Assessment of the phytoextraction potential of high biomass crop plants

A hydroponic screening method was used to identify high biomass crop plants with the ability to accumulate metals. Highest values of shoot accumulation were found in maize cv. Ranchero, rapeseed cv. Karat, and cardoon cv. Peralta for Pb (18 753 mg kg(-1)), Zn (10 916 mg kg(-1)), and Cd (242 mg kg(-1)), respectively. Subsequently, we tested the potential of these three cultivars for the phytoextraction of a metal spiked compost, finding out that, in cardoon and maize plants, increasing Zn and Cd concentrations led to lower values of root and shoot DW. By contrast, rapeseed shoot growth was not significantly affected by Cd concentration. Finally, a metal polluted soil was used to check these cultivars' phytoextraction capacity. Although the soil was phytotoxic enough to prevent the growth of cardoon and rapeseed plants, maize plants phytoextracted 3.7 mg Zn pot(-1). We concluded that the phytoextraction performance of cultivars varies depending on the screening method used.     

5种沉水植物对重金属富集能力的对比研究

为了探求不同的沉水植物对水体中重金属吸收富集能力的差异,采用原子吸收光谱法,对淮河支流东风渠水体及水体中常见的5种沉水植物:菹草、黑藻、龙须眼子菜、穗花狐尾藻及小茨藻进行了铅(Pb)、镉(Cd)、锌(Zn)、铜(Cu)含量分析。结果表明:5种沉水植物样品中重金属含量远远高于水体重金属背景值,对重金属Cu、Pb、Cd、Zn的富集系数为58~1 515,对Zn富集最强,最大富集量达到242.42 mg/kg,富集系数为1 515。不同的沉水植物对重金属的吸收富集优势存在明显差异,利用沉水植物来修复水体重金属污染时,须依据不同的污染元素来选择合适的沉水植物。     

负载金属活性碳纤维对NO催化分解性能的研究

碳纤维用于环境保护,污染治理是个重要课题,采用浸渍法研制系列钯负载活性碳纤维,研究了它们对NO的歧化分解性能,并与其它载体催化剂进行比较,实验结果表明负载钯活性碳纤维在300℃以上能催化NO的歧化分解。负载钯活性炭和负载钯炭黑分解NO的能力明显比前者弱,石墨和分子筛载体负载钯催化剂在400℃仍没有催化分解NO的作用。催化反应温度升高,NO流量降低,钯负载量增加有利于NO分解率提高,采用钯－铜混合物负载活性碳纤维可以减少钯的使用量。     

负载型金属氧化物催化剂分解臭氧的研究

用浸渍法制备了活性炭、γ-氧化铝和分子筛负载的MnO2,CuO,Fe2O3催化剂,并考察了它们对臭氧分解的催化性能。结果表明,MnO2催化剂优于CuO,Fe2O3,催化剂,活性炭为载体的催化剂优于γ-氧化铝和分子筛为载体的催化剂。温度对臭氧催化分解影响很大,在90℃时,MnO2／AC催化剂对臭氧的去除率可达80％以上。当存在一定浓度的水蒸气时,湿度越大,催化性能越差。当臭氧初始质量浓度低于50mg／L时,随着臭氧初始浓度的增加,催化性能有一定的下降。     

Optical and Chemical Methods of Metal Ash Analysis and Tin Recovery

‘Metal ash’ presents a waste disposal problem in most of the developing countries as the industries employ obsolete technologies. In this paper we describe analysis of tin ash, zinc ash and aluminium ash by means of optical methods, such as X-ray diffraction (XRD), inductively coupled plasma mass spectrometry (ICP-MS), electron probe micro analysis (EPMA), scanning electron microscopy (SEM) and chemical methods. The results of tin ash obtained by XRD method matched well with the cassiterite, a naturally occurring mineral of tin. ICP-MS studies reveal the presence of a large number of tracer metals, which may cause pollution by tertiary dispersion and this aspect is discussed. Conversely, the data generated by chemical methods are limited. However, the methods are simple and cost-effective. Then, they can easily be adopted by low-budget industries. Simple and cost-effective process to recover tin from tin ash is described. It is based on heating tin ash with sodium cyanide to about 900°C to separate tin component from the metal ash. The process recovers good quality tin and offers a very high yield. The process can be scaled up to small pilot plant.     

进口含金属物料的固体废物鉴别方法研究

基于已完成的112例进口含金属物料的固体废物鉴别实践,系统地介绍了进口含金属物料的申报品名及各品名所占比例,种类及各种类的特征、固体废物鉴别关键方法和每种鉴别结果所占比例,其中申报品名主要为矿石(砂),所占比例为51.8%;鉴别结果主要为冶炼渣,所占比例为37.5%。提出对于进口的含金属物料,通过测量主要成分和含量、最主要金属元素及典型重金属元素的含量、物相组成、矿相组成,对于极细的粉末等特殊物料,还需要粒度分析等辅助试验,确定其产生来源。如果确定属于金属冶炼过程中产生的副产物、污染控制设施或环境治理过程中产生的物料、含金属废料简单加工处理产物、矿物采选过程中产生的废弃物,那么鉴别物料属于固体废物。     

基于机器学习的大气PM2.5中金属浓度预测模型的研究

基于2013—2018年哈尔滨市气象数据、大气污染物数据和细颗粒物（PM_2.5）中金属成分数据,采用机器学习方法探索大气PM_2.5中金属浓度预测模型,并选择最优模型进行污染物浓度预测。结果表明,多元线性回归（MLR）、人工神经网络（BP-ANN）、支持向量机（SVM）和随机森林（RF）4种模型中,RF对大气PM_2.5中5种金属［锑（Sb）、砷（As）、铅（Pb）、镉（Cd）、铊（Tl）］的浓度预测效果最佳,在训练集和测试集中表现均较稳定,其中相关系数（r）均＞0.7, 平均绝对误差（MAE）和均方根误差（RMSE）数值较小。RF在大气PM_2.5中金属浓度预测上具有较好的表现,可在缺乏监测和实验数据的情况下,实现对大气颗粒物中金属浓度的快速预测,为全面了解颗粒物中金属污染特征提供数据基础。     

螯合树脂在线富集——火焰原子吸收光度法测定水中微量Cu,Pb,Zn,Cd

对螯合树脂在线富集，火焰原子吸收光度法进行了条件试验。试验证实方法对Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ４个元素检出浓度可达μｇ／Ｌ级，校准曲线性、样品重现性及准确度可满足测定要求。     

ICP-MS法同时测定地表水中18种金属元素

以115In-103Rh为双内标校正系统,采用电感耦合等离子体质谱法同时测定地表水中铜、锌、硒、砷、汞、镉、铅、铁、锰、钼、钴、铍、锑、镍、钡、钒、钛、铊等18种金属元素,优化了测量同位素、内标元素等试验条件。18种金属元素在0μg/L～100μg/L范围内线性良好,检出限为0.006μg/L～0.123μg/L,标准样品的测定值均在保证值范围内,平行测定的RSD为1.7%～4.2%,实际水样加标回收率为89.0%～100%。     

Heavy metal contamination from mining sites in South Morocco: Monitoring metal content and toxicity of soil runoff and groundwater

The aim of the present work is the assessment of metal toxicity in runoff, in their contaminated soils and in the groundwater sampled from two mining areas in the region of Marrakech using a microbial bioassay MetPLATE™. This bioassay is based on the specific inhibition of the β-galactosidase enzyme of a mutant strain of Escherichia coli, by the metallic pollutants. The stream waters from all sampling stations in the two mines were all very toxic and displayed percent enzyme inhibition exceeding 87% except SWA₄ and SWB₁ stations in mine C. Their high concentrations of copper (Cu) and zinc (Zn) confirm the acute toxicity shown by MetPLATE. The pH of stream waters from mine B and C varied between 2.1 and 6.2 and was probably responsible for metal mobilization, suggesting a problem of acid mine drainage in these mining areas. The bioassay MetPLATE™ was also applied to mine tailings and to soils contaminated by the acidic waters. The results show that the high toxicity of these soils and tailings was mainly due to the relatively concentration of soluble Zn and Cu. The use of MetPLATE™ in groundwater toxicity testing shows that, most of the samples exhibited low metal toxicity (2.7–45.5% inhibition) except GW3 of the mine B (95.3% inhibition during the wet season and 82.9% inhibition during the dry season). This high toxicity is attributed to the higher than usual concentrations of Cu (189 μg Cu l⁻¹) and Zn (1505 μg Zn l⁻¹). These results show the potential risk of the contamination of different ecosystems situated to the vicinity of these two metalliferous sites. The general trend observed was an increase in metal toxicity measured by the MetPLATE with increasing total and mobile metal concentrations in the studied matrices. Therefore, the MetPLATE bioassay is a reliable and fast bioassay to estimate the metals toxicity in the aquatic and solids samples.