微波消解-原子吸收光度法测定土壤中铜锌铅镉镍铬

用微波消解－原子吸收光度法测定土壤中铜，锌，铅，镉，镍和铬。通过硝酸－氢氟酸－过氧化氢体系消解液对土壤样品消解，选择出微波最佳消解条件。对硝酸－盐酸－过氧化氢体系消解液和硝酸－氢氟酸－过氧化氢体系消解液进行消解对比试验，发现前者不能将土壤样品完全消解，后者能将样品消解完全，但需将消解液中剩余的酸赶尽，否则测定结果将明显偏低。微波消解土壤与传统电热消解相比，操作简便快速，可提高工作效率。     

水体重金属污染生物监测的研究进展

综述了重金属的毒性效应和水体重金属污染的现状,介绍了利用水生藻类、浮游动物群落和底栖动物监测水体重金属污染的研究进展及发展趋势。     

外源废水输入对福州东湖湿地水体污染元素浓度和分布特征的影响

滨海湿地作为一种特殊的湿地类型,对人类活动和环境污染响应十分敏感。近年来,外源废水输入导致滨海湿地水体污染严重,对生态环境和人类健康产生威胁。该研究以福州东湖湿地为研究对象,分析上游径流、生活污水、工业废水、养殖塘废水、退塘还湿以及天然湿地等外源水输入对福州东湖水体Cr、Cu、Zn、As、Pb和Mn浓度及分布特征的影响,并对养殖塘水体与沉积物中污染元素浓度进行分析和生态风险评估。研究结果表明,福州东湖湿地水体中Cr、Cu、Zn、As、Pb、Mn的质量浓度分别为(0.50±0.20)、(3.87±1.54)、(34.48±1.71)、(4.72±0.48)、(0.77±0.38)、(151.96±58.81)μg/L,各污染元素浓度符合地表水Ⅱ类水标准。工业废水和养殖塘废水输入是福州东湖水体中污染元素的主要来源,其中工业废水的Mn浓度、养殖塘废水的Cr、Cu、Pb和Mn浓度较高。由于养殖饵料与消毒剂的添加,部分养殖塘沉积物Cr和Mn存在轻度或偏中度污染,呈现轻度生态风险。为防止水质进一步恶化,应改良工业废水处理设施,优化农业养殖模式,控制周边地区污染源。     

合肥市臭氧及其前体物污染特征及源解析

利用合肥市臭氧和VOCs连续观测数据分析了合肥市臭氧及其前体物污染特征,并使用NAQPMS模型研究了合肥市不同季节臭氧来源情况。结果表明:O₃已经成为影响合肥市环境质量的主要污染因子,O₃高值区主要集中在5—6月和9月。合肥市大气VOCs中烷烃含量最丰富,其次是烯烃、芳香烃和炔烃;主要物种为乙烷、丙烷、乙炔、正戊烷、乙烯、环戊烷、异戊烷、正丁烷、异丁烷和甲苯。合肥市O₃生成主要受VOCs控制,其中,烯烃是合肥市O₃生成贡献最大的关键活性组分,乙烯的OFP贡献率居首位。合肥市不同季节O₃来源差异较大,其中,本地排放是主要来源,夏季占比为50%,其余季节占比为30%~45%,O₃存在跨省长距离输送特征,主导风向的变化是造成合肥市臭氧来源季节性变化的重要因素。     

场地污染监测预警与决策一体化系统的设计与实现

通过分析我国相关场地污染现状和需求,设计了场地污染监测预警与决策一体化系统,利用物联网设备实时监测采集污染数据,并通过数据传输技术SignalR进行数据传输,再使用三维地理框架Cesium反映监测区域的污染情况,保证对污染处理响应的实时性和高效性,指出三维虚拟地理技术与大数据、物联网技术结合是系统的发展方向。     

贵州煤矿区表层水-沉积物重金属分布特征及来源分析——以新寨河为例

为探索贵州煤矿区表层水-沉积物中重金属的分布特征及来源,科学制定环境保护与污染治理措施,以新寨河为研究对象,在11个样点共采集66个表层水体和沉积物样品,通过对Cd、Pb、Cr、Zn、Cu、As、Hg、Fe、Mn等9种重金属元素进行分析,揭示其在新寨河的空间分布特征。同时,利用多指数法开展了有毒重金属元素污染状况评价,通过相关性分析和主成分分析解析了重金属的来源。结果表明,新寨河流域表层水体中,Fe、Mn点位超标率达100%。表层水中重金属元素的平均含量排序为Fe＞Mn＞Zn＞Cu＞Cr＞As＞Cd＞Pb＞Hg,而沉积物中重金属元素的平均含量排序则是Fe＞Mn＞Zn＞Cr＞Cu＞As＞Pb＞Cd＞Hg,表明新寨河表层水体和沉积物中重金属元素的空间分布存在一定差异。各重金属元素的内梅罗综合污染指数介于0.59~1.13之间,表明新寨河表层水体中重金属的污染程度达到轻微污染水平。单种重金属元素的潜在生态危害系数计算结果显示,90.91%和9.09%的沉积物样点分别被归类为轻微风险和中等风险。所有样点沉积物的潜在生态危害指数介于14.57~120.55之间(均值为72.08),表明新寨河沉积物的潜在生态风险较低。Cu、As在多个样点存在污染现象,需予以重点监控管理。新寨河流域重金属的来源可分为三大类:Cd、Pb、Cr、Zn、Cu为第一类,对应地表径流源;As、Fe、Mn为第二类,对应煤矿开采源;Hg为第三类,对应复合源。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Trace Metal Concentration in Roadside Surface Soil and Tree Back: A Measurement of Local Atmospheric Pollution in Abuja, Nigeria

Cadmium, copper, lead, nickel and zinc concentrations were analysed by atomic absorption spectrophotometry in surface soil and tree bark from different districts of Abuja, Nigeria, in order to determine the atmospheric trace metal input in the area.Elevated concentrations of some of the studied metals were observed in the soil and tree bark samples from the commercial/high traffic areas of the city compared to backgroundvalues. In soil samples, the average concentration of the metals were 0.6±0.4, 18.0±4.0, 281±39, 16±4 and66±23 g g^-1 dry weight for Cd, Cu, Pb, Ni and Zn, respectively, whilst the average concentrations in tree bark were 0.3±0.2, 12±4, 133±32, 13±3 and 61±10 g g^-1 dry weight for Cd, Cu, Pb, Ni and Zn, respectively. The trend in trace metal levels suggested that automobile emissions are a major source of these metals as the highest concentrations of Pb and Zn were recorded in the commercial areas of the city known for their high traffic densities. The levels of metal in the study area were relativelylow compared to levels found in some larger and older cities in various countries worldwide.     

Flue gas treatability studies: a tool for techno-economic control of industrial air pollution

Air pollution problems in developing countries have gained larger fraction in the last decade especially due to non functioning and non implementation of effective air pollutioncontrol devices in industries. In industrial wastewater management, adequate treatability studies are conducted to arrive at a techno-economic treatment option. However no suchstudies were done for reducing air pollution or emission fromindustries until now in India. Little information was availableabout such studies in other countries. This article provides information about a novel technique known asflue gas treatability studies and to undertake such studies, a pilot scale system is installed in Air Pollution Control Divisionof M/s National Environmental Engineering research Institute, NEERI, Nagpur-20, India. This study is a tool for techno-economicselection of air pollution control systems specially for small/medium scale industrial emissions.     

“十一五”期间重点流域化学需氧量排放及减排潜力分析

根据"十一五"期间七大流域化学需氧量(COD)排放总量、工业COD排放量及生活COD排放量的变化情况对各流域的减排幅度进行了综合评价,根据单位水资源COD负荷、单位工业产值COD排放强度及人均生活COD排放强度对各流域的污染压力进行了综合评价,以七大流域的减排幅度和污染压力为基础分析了各流域COD的减排潜力,并对各流域的重点防控领域和配套减排措施等方面提出了政策建议。