137Cs示踪技术在滦河源区栗钙土风蚀速率估算中的应用

对采集于滦河源区3个栗钙土剖面中的27个土层样品的pH、有机碳含量、碳酸钙含量、密度及质地进行了化验分析,运用ADCOM100超低本底γ谱仪测定了土壤样品1377Cs的比活度.结果表明,自然栗钙土以及被风蚀土壤剖面中137Cs比活度随深度呈指数递减式分布,其最大渗透深度可达约30cm;利用137Cs示踪技术估算的研究区土壤风蚀速率在0.1842cm·a-1和0.2897cm·a-1之间;栗钙土不同粒径土壤颗粒中137Cs的比活度差异显著,即细粒(粒径≤0.10mm的极细砂、粉粒和黏粒)中137Cs比活度大于细砂(0.10～0.25mm)中137Cs比活度大于粗粒(0.25～2.00mm的中砂、粗砂和极粗砂)中137Cs比活度.可见,运用137Cs示踪法可以定量估算区域土壤风蚀速率,但需综合考虑137s在土壤中的分布、土壤有机质含量和质地等因素,以使其结果将更为准确.     

A sensitive spectrophotometric method for the determination of arsenic in environmental samples

We developed a cost-effective and sensitive spectrophotometric method for the determination of arsenic at trace level using a new reagent, leuco malachite green. Here we show that, arsenic reacts with potassium iodate in acidic conditions to liberate iodine, and the liberated iodine selectively oxidizes leuco malachite green to malachite green dye. We studied the Beer’s law at 617 nm, which showed linearity over the concentration range 0.09–0.9 μg ml⁻¹ of arsenic. We show that the molar absorptivity, Sandell’s sensitivity and detection limit of the method are 6.1 × 10⁴ l mol⁻¹ cm⁻¹, 0.0012 μg cm⁻² and 0.025 μg ml⁻¹, respectively. We applied the developed method for the determination of arsenic in environmental samples.     

长江、嘉陵江(重庆段)源水有机提取物的致突变活性及其季节变化

为了确定并比较重庆主城区段长江、嘉陵江源水有机提取物的致突变性及其季节变化规律，分别于春、夏、冬季采用GDX－120大孔树脂，对位于城区上游、城区中段、城区下游以长江、嘉陵江源水的5个水厂的进厂水进行了有机物的浓缩提取。提取物的致突变活性采用经典的Ames试验平板掺入法评估，测试菌株为TA98及TA100，同时做加与不加S9的比较。结果显示，嘉陵江及长江源水的有机提取物均有不同程度的致突变活性。嘉陵江源水明显大于长江源水，城区中段源水明显大于上游段及下游段源水。多数断面显示平水期致突变活较为显著并且移码型致突变性大于碱基置换型致密变性。研究结果提示，城市污染源已导致长江、嘉陵江源水具备致突变活性，控制两江沿岸的各种水污染源已成为当务之急。     

Profiles of PAH emission from steel and iron industries

In order to characterize the polycyclic aromatic hydrocarbons (PAHs) emission from steel and iron industries, this study measured the stack emission of twelve steel and iron plants in southern Taiwan to construct a set of source fingerprints. The study sampled the emissions by the USEPA's sampling method 5 with the modification of Graseby for the gas and particulate phase PAH and, then, used Hewlett-Packard 5890 gas chromatograph equipped with mass spectrometer detector to analyze the samples. The steel and iron industries are classified into three categories on the basis of auxiliary energy source: Category I uses coal as fuel, Category II uses heavy oil as fuel and Category III uses electric arc furnace. The pollution source profiles are obtained by averaging the ratios of individual PAH concentrations to the total concentration of 21 PAHs and total particulate matter measured in this study. Results of the study show that low molecular weight PAHs are predominant in gas plus particulate phase for all three categories. For particulate phase PAHs, however, the contribution of large molecular weight compounds increases. Two-ring PAHs account for the majority of the mass, varying from 84% to 92% with an average of 89%. The mass fractions of 3-, 4-, 5-, 6-ring PAHs in Category I are found to be more than those of the other two categories. The mass of Category III is dominated by 7-ring PAHs. Large (or heavy) molecular weight PAHs (HMW PAHs) are carcinogenic. Over all categories, these compounds are less than 1% of the total-PAH mass on the average. The indicatory PAHs are benz[a]anthracene, benzo[k]fluoranthene, benzo[ghi]perylene for Category I, benzo[a]pyrene, acenaphthene, acenaphthylene for Category II and coronene, pyrene, benzo[b]chrycene for Category III. The indicatory PAHs among categories are very different. Thus, dividing steel and iron industry into categories by auxiliary fuel is to increase the precision of estimation by a receptor model. Average total-PAH emission factors for coal, heavy oil and electric arc furnace were 4050 μg/kg-coal, 5750 μg/l-oil, 2620 μg/kW h, respectively. Carcinogenic benzo[a]pyrene for gas plus particulate phase was 2.0 g/kg-coal, 2.4 μg/l-oil and 1.4 μg/kW h for Category I, II and III, respectively.     

Assessment of contribution of SO2 and NO2 from different sources in Jamshedpur region, India

Contribution of pollution from different types of sources in Jamshedpur, the steel city of India, has been estimated in winter 1993 using two approaches in order to delineate and prioritize air quality management strategies for the development of region in an environmental friendly manner. The first approach mainly aims at preparation of a comprehensive emission inventory and estimation of spatial distribution of pollution loads in terms of SO₂ and NO₂ from different types of industrial, domestic and vehicular sources in the region. The results indicate that industrial sources account for 77% and 68% of the total emissions of SO₂ and NO₂, respectively, in the region, whereas vehicular emissions contributed to about 28% of the total NO₂ emissions. In the second approach, contribution of these sources to ambient air quality levels to which the people are exposed to, was assessed through air pollution dispersion modelling. Ambient concentration levels of SO₂ and NO₂ have been predicted in winter season using the ISCST3 model. The analysis indicates that emissions from industrial sources are responsible for more than 50% of the total SO₂ and NO₂ concentration levels. Vehicular activities contributed to about 40% of NO₂ pollution and domestic fuel combustion contributed to about 38% of SO₂ pollution. Predicted 24-h concentrations were compared with measured concentrations at 11 ambient air monitoring stations and good agreement was noted between the two values. In-depth zone-wise analysis of the above indicates that for effective air quality management, industrial source emissions should be given highest priority, followed by vehicular and domestic sources in Jamshedpur region.     

大气环境中OH自由基测定

采用自旋捕集技术和电子自旋共振法结合测定大气环境中ＯＨ自由基，首先用自旋捕集剂将ＯＨ自由基捕集，生成比较稳定的自然旋加合物，，然后带回实验室处理测定，该法为开展大气光化学研究提供了一种采样方便，利于实测的方法，据３个采样点的实测结果表明，相对误差约为３５％，比文献所示结果略大。     

Soil heavy metal pollution from Pb/Zn smelting regions in China and the remediation potential of biomineralization

Smelting activities pose serious environmental problems due to the local and regional heavy metal pollution in soils they cause. It is therefore important to understand the pollution situation and its source in the contaminated soils. In this paper, data on heavy metal pollution in soils resulting from Pb/Zn smelting (published in the last 10 years) in China was summarized. The heavy metal pollution was analyzed from a macroscopic point of view. The results indicated that Pb, Zn, As and Cd were common contaminants that were present in soils with extremely high concentrations. Because of the extreme carcinogenicity, genotoxicity and neurotoxicity that heavy metals pose, remediation of the soils contaminated by smelting is urgently required. The primary anthropogenic activities contributing to soil pollution in smelting areas and the progressive development of accurate source identification were performed. Due to the advantages of biominerals, the potential of biomineralization for heavy metal contaminated soils was introduced. Furthermore, the prospects of geochemical fraction analysis, combined source identification methods as well as several optimization methods for biomineralization are presented, to provide a reference for pollution investigation and remediation in smelting contaminated soils in the future.     

大气可吸入颗粒物源解析方法研究进展

综述了国内外用于可吸入颗粒物源解析的受体模型的最新研究进展,详细介绍了粗集理论模型、BP网络权重分析、投影寻踪回归、正定矩阵分解和主成分分析等多种方法。指出了可吸入颗粒物源解析方法的发展趋势和还需做的工作。     

极谱催化波法测定痕量亚硝酸根的研究

在含稀硫氰酸盐的底液中 ,在单扫示波极谱仪上 ,有一灵敏的亚硝酸根催化波。峰电位为 -0 .47V( vs·SCE)。阳极化二阶导数峰高与亚硝酸根浓度在 1× 10 - 7～ 5× 10 - 5mol/L 之间成线性关系。检测限达 5× 10 - 5mol/L( 2 .3ppbNO - 2 )。试验了多种共存离子对测定的影响 ,表明该法具有较好的选择性 ,尤其是大量硝酸根不干扰。应用该法测定了许多样品中的亚硝酸根 ,并对该波的机理进行了研究 ,结果证明该波是 [SCN· NO]催化溶液中的溶解氧还原所致     

An integrated chemical mass balance and source emission inventory model for the source apportionment of PM2.5 in typical coastal areas

The source apportionment of PM_2.5 is essential for pollution prevention. In view of the weaknesses of individual models, we proposed an integrated chemical mass balance-source emission inventory (CMB-SEI) model to acquire more accurate results. First, the SEI of secondary component precursors (SO₂, NO_x, NH₃, and VOCs) was compiled to acquire the emission ratios of these sources for the precursors. Then, a regular CMB simulation was executed to obtain the contributions of primary particle sources and secondary components (SO₄^2?, NO₃^-, NH₄⁺, and SOC). Afterwards, the contributions of secondary components were apportioned into primary sources according to the source emission ratios. The final source apportionment results combined the contributions of primary sources by CMB and SEI. This integrated approach was carried out via a case study of three coastal cities (Zhoushan, Taizhou, and Wenzhou; abbreviated WZ, TZ, and ZS) in Zhejiang Province, China. The regular CMB simulation results showed that PM_2.5 pollution was mainly affected by secondary components and mobile sources. The SEI results indicated that electricity, industrial production and mobile sources were the largest contributors to the emission of PM_2.5 gaseous precursors. The simulation results of the CMB-SEI model showed that PM_2.5 pollution in the coastal areas of Zhejiang Province presented complex pollution characteristics dominated by mobile sources, electricity production sources and industrial production sources. Compared to the results of the CMB and SEI models alone, the CMB-SEI model completely apportioned PM_2.5 to primary sources and simultaneously made the results more accurate and reliable in accordance with local industrial characteristics.