Significance of urinary arsenic speciation in assessment of seafood ingestion as the main source of organic and inorganic arsenic in a population resident near a coastal area

In order to characterize the different sources of exposure to arsenic (As), urinary excretion of total As, the sum of inorganic As+MMA+DMA determined by the hydride generation-atomic absorption spectrophotometry technique, and the species As(3), As(5), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA) and arsenobetaine were determined in 49 workers at a steel foundry, with presumed occupational exposure to As, and 50 subjects from the general population, all males. No evidence of occupational exposure to As resulted from environmental monitoring performed in the foundry, although the analysis of minerals used as raw materials showed the presence of As, particularly in fossils and fine ores. The urinary concentrations of As(3), MMA, DMA, the sum of inorganic As+MMA+DMA and total As were not different in the two groups, while arsenobetaine appeared significantly higher in the controls than in the workers. The different species of urinary As were all significantly correlated. Urinary excretion of As(3) was associated with the consumption of mineral water and with residence in an industrial zone, while MMA, DMA, arsenobetaine, the sum of inorganic As+MMA+DMA and total As urinary excretion were associated with the consumption of crustaceans and/or shellfish 3 days or less before urine collection. Multiple regression analysis confirmed these results. In conclusion, in populations with a high consumption of seafood, living in areas characterized by coastal/marine As pollution, only speciation of As can identify a prevalent role of environmental sources, like the consumption of seafood contaminated by As, in determining urinary As excretion, and exclude an occupational origin of the exposure.     

Progress in developing an ANN model for air pollution index forecast

An air pollution index (API) reporting system is introduced to selected cities of China for public communication on air quality data. Shanghai is the first city in China providing daily average API reports and forecasts. This paper describes the development of an artificial neural network (ANN) model for the API forecasting in Shanghai. It is a multiple layer perceptron (MLP) network, with meteorological forecasting data as the main input, to output the next day average API values. However, the initial version of the MLP model did not work well. To improve the model, a series of tests were conducted with respect to the training method and structure optimization. Based on the test results, the training algorithm was modified and a new model was built. The new model is now being used in Shanghai for API forecasting. Its performance is shown reasonably well in comparison with observation. The application of the old model was only weakly correlated with observation. In 1-year application, the correlation coefficients were 0.2314, 0.1022 and 0.1710 for TSP, SO₂ and NO_x, respectively. But for the new model, for over 8 months application, the correlation coefficients are raised to 0.6056, 0.6993 and 0.6300 for PM₁₀, SO₂, and NO₂. Further, the new algorithm does not rely on manpower intervention so that it is now being applied in several other Chinese cities with quite different meteorological conditions. The structure of the model and the application results are presented in this paper and also the problems to be further studied.     

PEM式臭氧消毒在地上游泳池水处理中的应用

采用臭氧法水处理系统对地上游泳池的循环水进行灭菌消毒,研究了臭氧用量、循环水流量和运行时间等因素对臭氧法灭菌效果的影响。结果表明,3组PEM臭氧发生器应用于21.2 m3的地上游泳池,在4 m3/h的循环水流量下运行12 h后,水中的细菌总数与大肠杆菌群数达到国家标准,去除率均在99%以上。与盐电解法水处理系统相比较,臭氧法水处理系统的优势在于:杀菌快速高效、出水水质的理化指标较好和运行费用低廉。     

基于GCM_CB模型的土壤重金属污染评价

灰色聚类法已经运用于土壤重金属污染评价中,然而此法在确定聚类权重时仅考虑重金属浓度,忽略了衡量重金属毒性强弱的重要指标生物毒性指数。为了更客观和准确地反映土壤重金属的污染程度,将生物毒性指数引入到聚类指标权重中,构建GCM_CB(grey clustering method_concentration and biotoxicity)土壤重金属污染评价模型。通过对华东某地区的10个区域土壤重金属污染进行分析评价,并与常用评价方法对比研究,表明:其多数样点的评价结果基本一致,但针对样品4和样品9中的元素Hg,因其强毒性,使得评价等级由I级定为II级,从而提高了评价方法的灵敏度,更加符合该区域的实际土壤污染情况。     

改性CMC聚合物吸附酸法地浸废水中的铀

在温度为70～80℃、单体质量浓度为30%～35%、羧甲基纤维素∶丙烯酸(质量比)为10∶2.5、反应时间为3.5～4 h条件下对CMC进行改性,接枝率可达68%以上。以改性前后的CMC为吸附剂,对模拟酸法地浸含铀废水进行了对比吸附实验研究。结果表明:改性CMC对铀吸附效果最佳的实验条件为:改性CMC质量浓度为0.10 g/L,温度为25℃,pH为5.0,吸附时间100 min,此时铀去除率达到了97.1%,比CMC改性后对铀的吸附率平均提高了近21%。影响吸附效果程度由强到弱的顺序为:改性CMC投加量、pH、吸附时间、温度。     

外源Cd对不同利用方式红壤脲酶活性的影响

采用室内培养实验,通过将外源Cd添加到同一母质、全镉含量相近的不同利用方式的红壤中(林地、水稻土和菜园土),研究了外源Cd污染对不同利用方式红壤脲酶活性的影响。结果表明:整个培养过程中,Cd污染对3种红壤脲酶活性都有抑制作用,且随重金属浓度的增强而增强。同剂量Cd污染对3种红壤脲酶活性的抑制效应不同,大小为林地>水稻土>菜园土。实验设定的Cd处理水平下,对林地、水稻土和菜园土脲酶活性产生显著抑制作用(p<0.05)的Cd浓度分别为5、30和50 mg/kg土。     

微波修复原油污染土壤的均匀设计实验

采用均匀设计实验方法,研究了微波修复原油污染土壤时原油去除率与微波能耗、含水率和含炭率等因素的关系,并应用MATLAB编程拟合出经验公式。结果分析表明:微波能耗在0～288 kJ范围内,污染土壤的原油去除率随微波能耗线性增加;在含水率为6%、含炭率为4%、微波能耗从0增加到288 kJ时,原油去除率从0%增加至92.3%;含炭率在0%～4%范围内原油去除率与含炭率成线性关系,在微波能耗为288 kJ、含水率为6%、含炭率从0%增加到4%时,原油去除率从12.3%增加至92.3%;原油去除率与含水率成二次曲线关系且开口向下,微波修复原油污染土壤的最佳含水率为6.6%。研究结果对微波修复原油污染土壤技术的优化提供了有价值的参考。     

氨水土壤混合物脱除CO2温室气体的实验研究

为了脱除CO2温室气体,提出了利用氨水土壤混合物去除CO2的新方法.分别考察了土壤颗粒粒径、CO2初始流量、氨水浓度(质量比)和温度对CO2脱除量和脱除率的影响.实验结果表明,该方法去除CO2的量较土壤物理吸附量和氨水化学吸收量的总和提高了大约15%;随着氨水浓度的增大,CO2的脱除率和脱除量都增大;随着土壤颗粒粒径和CO2初始流量的增大,CO2的脱除率和脱除量都减小;当温度由22℃升高到31℃,CO2的脱除率随着温度的升高而增大,但是继续升高温度到40 ℃,CO2的脱除率反而下降.     

某矿区土壤和地下水重金属污染调查与评价

为了解湘南某矿区土壤和地下水重金属污染状况,对该矿区东河流域附近重金属污染源进行了调查,同时,对地下水和土壤样品进行了采样分析,结果表明：（1）该矿区东河流域附近的主要污染源有18个,其中有色金属选厂、尾矿库、采矿场和冶炼厂是排放重金属较多的污染源;（2）20个采样点中土壤重金属Pb、Cd、Zn、As和Hg大部分超过国家土壤环境质量标准（GB15618-1995）,综合污染指数P综〉1,该矿区主要的重金属污染元素为Cd、As和Hg,且土壤中Cd、Zn和As的含量两两之间存在着极显著的正线性相关关系;（3）重金属元素在土壤中的纵向迁移不明显,该矿区附近20个采样点的地下水并未受到污染,综合污染指数P综〈1。20个采样点地下水Pb、Cd、Zn、As、Hg浓度均能达到地下水质量标准（GB／T14848．9）中的Ⅲ类标准。     

基于统计的百花湖表层水中重金属分布特征

以云贵高原深水湖泊百花湖为研究对象,研究其表层水中9种重金属(As,Hg,Cd,Pb,Fe,Cu,Zn,Mn和Cr)的分布特征并开展溯源研究. 结果表明:各采样点之间重金属含量变化较大,变异系数为5.6%～147%,同一采样点水质中重金属元素含量变化顺序为Fe>Mn>Cr>Zn>Cu>As>Pb>Hg>Cd;地统计分析从空间角度表明百花湖不同水域重金属含量分布差异较大;ρ(Ca)与ρ(Cu),ρ(Pb)的相关系数(R2)分别为-0.771(P<0.01)和-0.692(P<0.05);主成分分析揭示了该湖泊水体重金属含量主要受4个因素的影响(分别解释了总因子的33.88%,19.32%,18.02%和11.81%),其中一些重金属同时受2个以上主成分因素的影响;聚类分析将这9种重金属归为4类,Fe单独为一类,Cd,Pb,Hg,As和Cu为一类,Zn,Cr为一类,Mn独自为一类. 地统计分析、相关性分析、主成分分析和聚类分析的应用使得影响因素复杂的水环境问题的研究相对简单化.