色基生产废水的三级处理工艺试验

在染料中间体红色基Ｂ，紫酱色基ＧＰ的生产过程中，全产生降解处理的废水，采用中和隔油－生物接触氧化－电解脱色工艺处理可达标准排放。试验结果表明，硝化废酸液和水解母液的混合废水经过中和隔油处理后，ＣＯＤｃｒ的去除率可达到５６％以上，而ＢＯＤ５／ＣＤＯｃｒ的比值可在从０．２２提高到０．５以上；再经生物接触氧化处理后，ＣＯＤｃｒ的去除率在８８％以上，ＢＯＤ５的去除率在９２％以上；最后，电解处理能使ＣＯＤｃ     

豫北典型农田作物中重金属污染状况及健康风险评价

农产品污染引发的食品安全问题目前已经成为全社会关注的焦点,为了研究和评价农作物中重金属污染和健康风险状况,采集了焦作市武陟县玉米、水稻和花生三种大田作物样品,共计47个样品,其中玉米样品16个,花生样品4个,水稻样品27个。在测定作物籽粒中重金属Cr、Ni、As、Cd和Pb含量的基础上,分别采用单因子污染指数和综合污染指数法评价了作物籽粒中重金属的污染状况,并运用危险商（HQ）法评价了这些作物中的重金属对人体健康可能造成的风险,进而应用相关分析法、聚类分析法及主成分分析法,探讨了作物籽粒中重金属含量的分布特征及其污染来源。结果表明：武陟县农田作物籽粒中的Cr、Ni、As、Cd和Pb的平均含量分别为0.26±0.42、0.31±0.29、0.04±0.03、0.01±0.04和0.03±0.03 mg·kg^-1。其中,玉米籽粒中的Cr、Ni、As、Cd和Pb的平均含量分别为8.86×10^-2±0.21、9.41×10^-2±0.12、8.10×10^-3±5.29×10^-3、1.20×10^-5±4.92×10^-5和0.04±0.02 mg·kg^-1;水稻籽粒中的Cr、Ni、As、Cd和Pb的平均含量分别为0.38±0.49、0.44±0.31、0.07±0.02、4.60×10^-3±7.42×10^-3和0.03±0.03 mg·kg^-1;花生籽粒中的Cr、Ni、As、Cd和Pb的平均含量分别为0.13±0.22、0.32±0.16、0.02±3.05×10^-3、0.11±0.07和1.32×10^-2±1.70×10^-2 mg·kg^-1。农作物籽粒中各重金属元素的单因子污染指数评价结果显示,从总体上看,3种农作物籽粒中5种重金属的单因子污染指数均值均小于1,单因子污染指数均值大小顺序为：Ni＞As＞Cr＞Pb＞Cd;从作物类型来看,玉米和水稻中Ni超标的样品比率分别为6.67%和51.85%,水稻中Cr超标的样品比率为12%。农作物籽粒中各重金属元素的综合污染指数评价结果显示,重金属的平均综合污染指数为0.59,整体上处于安全等级。总体来看,14.89%的农作物受到不同程度的污染,其中轻度污染的农?     

Indicating landfill stabilization state by using leachate property from Laogang Refuse Landfill

Variation and evolution process of leachate can be applied as a reference for landfill stabilization phase. In this work, leachates with different ages were collected from Laogang Refuse Landfill, and characterized with 14 key parameters. Simultaneously, principal component analysis （PCA） was applied to develop a synthetic parameter-F based on these 14 parameters, and a logarithm equation was simulated for the landfill stabilization process finally. It was predicted that leachates would meet Class I and Class II in standard for pollution control on the landfill site of municipal solid waste （GB 16889-1997） after 32 years and 22 years disposal under the natural attenuation in the humid and warm southern areas of China, respectively. The predication of landfill state would be more accurate and useful according to the synthetic parameter F of leachate from a working landfill.     

Source apportionment and ozone formation potential of volatile organic compounds in Lagos (Nigeria)

Concentrations of volatile organic compounds (VOCs) of the city air in Oba Akran road, Lagos were investigated. The chlorinated VOCs and xylene in Oba Akran were high. The average benzene/toluene ratio in Oba Akran was 1.7 suggesting that vehicular emission was a possible VOC source in most areas of Oba Akran. The toluene/(m+p-xylene) ratio also suggests a common source of toluene and xylene at these sites, presumably organic solvent used by industries located at Oba Akran. Our results showed that 7.10 tons of CO ₂ equivalents of VOCs are being emitted per year from Oba Akran. Xylenes were found to be the largest contributor to the ozone formation followed by trichloroethylene. A multivariate statistical analysis (Factor analysis extracted with Principal Component Analysis) has been applied to a set of data, and it was found that the main principal components, extracted from the air VOC pollution data, were related to gasoline and oil combustion/industrial activities.     

济南市夏、冬季PM2.5中化学组分的季节变化特征及来源解析

为探究济南市大气气溶胶中化学组分的季节变化特征,于2015年夏季、冬季分别连续进行1个月的PM_(2.5)样品采集,并分析无机离子、碳质组分与水溶性二次有机碳(WSOC)的组成、浓度水平及来源.结果表明,济南市冬季PM_(2.5)的质量浓度[(158.3±95.3)μg·m~(-3)]约为夏季[(75.3±25.9)μg·m~(-3)]的2倍,在我国其浓度处于中上等水平.无机离子的总浓度呈夏低冬高的季节变化特征,其中SO_4~(2-)、NO_3~-、NH_4~+是浓度最高的3种离子,且这3种离子的相关性均较好,NH_4~+在夏季和冬季均以(NH_4)_2SO_4和NH_4NO_3的形式存在.大气中存在较高程度的SO_2和NO_2的二次氧化,其中硫氧化率(SOR)呈夏高冬低的变化特征,而氮氧化率(NOR)呈相反的季节变化特征.通过分析PM_(2.5)中阴、阳离子电荷平衡可知,PM_(2.5)呈弱碱性.基于热力学模型ISORROPIA-Ⅱ,结果表明冬季PM_(2.5)的酸性比夏季强.OC与EC浓度均呈夏低冬高的变化特征,由OC/EC的比值、WSOC/OC的比值和估算的二次有机碳(SOC)的浓度可知,夏季二次污染的程度比冬季更为严重.主成分分析(PCA)结果表明,济南市夏季无机离子主要来自二次氧化及生物质燃烧,而冬季无机离子主要来自煤炭燃烧及其产生的前体物经光化学氧化形成的二次污染物.     

中国省际资源节约指数的空间差异研究

论文首次利用改进的"节约指数"并结合图形数据,对中国各省区资源消耗现状进行定量分析。结果表明:中国资源节约指数空间差异明显,总体上东部比西部节约、中部过渡(除山西外);低于全国平均节约水平的省域约占2/3,其中大部分在西部地区;此外,经济发展水平越高的省域,资源环境绩效水平相对越好。研究结果揭示了中国不同省域建设节约型社会的节约水平和资源利用效率差异,同时也为促进区域协调发展以及经济社会的可持续发展提供依据。     

主成分和聚类分析应用于淮南矿区地下水水质评价

运用主成分方法分析淮南矿区23个地下水样的7个水样指标,提取出4个主成分,应用聚类分析对该4个主成分的得分进行聚类。在此基础上,将主成分得分与其对应的特征值相乘,得到水质综合评价指数。聚类分析后水样划分为5类,对每一类的水质综合评价指数取平均值,从而确定水质等级。     

基于多种方法的长江上游小流域水质综合评价

选取大河和巴关河流域2018—2022年水质监测数据,运用单因子评价法、Spearman秩相关系数法、综合污染指数法和主成分分析法,对流域水质状况、变化趋势及主要污染物特征进行综合评价分析。结果表明:2018—2022年,大河流域水质未达到地表水Ⅲ类标准;流域整体综合污染指数超过了1,为重污染,下游污染程度较重;营养指标和有机污染物指标存在显著正相关。巴关河流域水质达到了地表水Ⅲ类标准;流域整体综合污染指数未超过1,为中污染,上游污染程度较重;营养指标、有机污染物指标和重金属指标等均呈现出不同程度的相关性。巴关河流域水质总体优于大河流域。TP、NH₃-N、COD_Mn、COD_Cr和BOD₅是影响大河流域和巴关河流域水质的主要因子,均属于有机型及富营养化污染指标,主要来自生活源和农业源。建议选择适宜的评价方法开展系统性小流域污染溯源,分河段有针对性地开展小流域水环境治理。     

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.     

黄河干流水质评价与时空变化分析

在黄河流域生态保护的实施中,分析流域的水质污染状况以及时空变化规律,成为保证流域水安全的首要任务.为了全面了解黄河流域近年来的水环境状况,基于流域8个监测断面2004～2018年的水质数据,使用Mann-Kendall(M-K)趋势检验、层次聚类分析和主成分分析等多元数据分析方法,结合改进的综合水质标识指数(WQI),...