ABR-好氧颗粒污泥处理黄连素废水的启动研究

实验研究了ABR-好氧颗粒污泥组合工艺处理黄连素制药废水的启动运行,通过分析发现,ABR装置在HRT为4 d,黄连素浓度为50 mg/L的运行方式下成功启动,反应器运行稳定后每个格室MLSS平均值分别为25 840、21 560、27 500和11 200 mg/L。以ABR出水为营养物,成功培养出粒径在2～10 mm,沉降速率为104～137 m/h,沉降性能优良的好氧颗粒污泥。该组合工艺在启动实验的末期,进水COD浓度为3 000～4 000 mg/L左右,出水COD浓度到达168.4～271mg/L,系统总的去除率保持在90%～95%之间,表明ABR-好氧颗粒污泥组合工艺能够有效地处理黄连素制药废水。     

烟花爆竹燃放对四川盆地边缘城市环境空气的影响及其污染传输特征研究

为了解四川盆地边缘城市环境空气质量受烟花爆竹燃放影响的特征,选取位于成都平原西南部的乐山市进行研究。研究发现,春节期间乐山市受烟花爆竹燃放影响的环境空气中的颗粒物及其组分的浓度变化趋势一致。相关性分析结果显示：在除夕夜烟花爆竹燃放影响时间段内,乐山市环境空气中的颗粒物(PM₁₀、PM_2.5)浓度与SO₄^2-、F^-、Al、K、Mn、Cu、Zn等组分浓度呈显著正相关,Pearson相关系数达到了0.48～0.73;Al、Si、K、Mn、Cu、Zn等组分浓度之间也表现出显著正相关,Pearson相关系数高达0.78～0.98。其中,K⁺浓度占比从0%上升到7.32%,SO₄^2-浓度占比从18.94%上升到24.73%,Cl^-浓度占比从0.46%上升到4.29%,Cu元素浓度占比从0.05%上升到0.30%,Al元素浓度占比从5.87%上升到7.46%。除夕夜烟花爆竹燃放影响期间,乐山市中部和北部区...     

中国环境基准理论与方法学研究进展及主要科学问题

环境基准是指环境介质中的环境要素对特定保护对象不产生不良或有害效应的最大限值,是环境标准制修订的科学依据。环境基准理论与方法学一直是国际环境科学和环境保护科学研究领域的前沿,也是国家环境管理的重大科技需求。本文在总结国际和我国环境基准研究成果的基础上,较为系统地阐述了环境基准的基本概况、理论方法学及重要进展。同时,结合学科特点和环境基准科技需求,综合分析了与环境基准理论方法学密切相关的系列关键科学问题。     

环境中重金属和有机污染物的物种敏感性分布研究进展

物种敏感性分布法(SSD,Species Sensitivity Distribution)是一种相对于传统评价因子法具有更高置信度的统计学外推方法,在环境质量基准制定及生态风险评价中得到广泛应用。本文对近年来国内外重金属和有机污染物的物种敏感性分布研究成果进行了综述,阐述了在水体、土壤和沉积物等环境介质中应用SSD方法开展生态风险评价的研究现状,从SSD模型选择、毒性数据点筛选等方面对影响SSD模型不确定性的因素进行探讨,并对SSD方法在生态风险评价领域的应用进行了展望。     

Preparation,characterization, and kinetics of nanoscale iron in nitrate nitrogen removal from polluted water

The aim of this study was to examine the production of nanoscale ions via the liquid phase reduction method and the effectiveness of the removal of nitrate nitrogen (NO₃^?–N) as well as measure the products and kinetics of the reactions. The nanoparticles obtained were approximately 50 nm in diameter and the main component was iron (Fe). This custom-made nanoscale Fe was highly positively charged, and reacted rapidly with NO₃^?–N in oxygen-free and neutral conditions at room temperature. A 90% removal rate was achieved when the reaction occurred for 30 min in simulation sample water with vigorous shaking at 250 r/min at NO₃^?–N concentrations of 30, 50, 80 or120 mg N/L. The nanometer Fe dosage was maintained throughout the experiment at 4 g/L. A first-order kinetics equation was applied to the obtained experimental data which followed a pseudo first-order reaction. Data demonstrated that the removal of nitrate nitrogen from polluted groundwater using a nanoscale Fe iron was effective and rapid.     

A pilot study on the effect of Cu,Zn, and Cd on the spectral curves and chlorophyll of wheat canopy at tiller stage

The aim of this study was to investigate canopy spectral reflectance responses to different levels of heavy metals copper (Cu), zinc (Zn), and cadmium (Cd) induced stress. Random blocks design experiment was conducted to simulate Cu, Zn, and Cd at five concentration levels. Chlorophyll and visible and near infrared canopy reflectance were measured for each treatment 56 days after seeding using chlorophyll meter SPAD-502 and spectroradiometer, respectively. New vegetative indices termed ratio of inclination angles (RIA), MERIS (the medium resolution imaging spectrometer) terrestrial chlorophyll index (MTCI), and normalized difference vegetation index (NDVI) were used to assess the response of canopy spectral reflectance to different heavy metal levels. Significant spectral variability especially in blue, red, and near infrared reflectance was observed for different heavy metal treatments. One-sample test showed significant difference for NDVI, MTCI, and RIA among five-level treatments at the 0.01 level. Correlation analysis demonstrated that the two vegetative indices (RIA and MTCI) were significantly correlated with chlorophyll meter values for Cd, Cu, and Zn treatments. However, NDVI was only significantly correlated with chlorophyll meter values for Cu and Zn treatments. Linear regression analysis also illustrated that RIA and MTCI were potential indices for predicting chlorophyll concentration with significant F test under Cu-, Zn-, and Cd-mediated stress.     

Optimization of the food waste water incineration with respect to CO and NO<Subscript>x</Subscript> emission characteristics

The incineration of food waste water in conjunction with the domestic waste is getting attention as a food waste water treatment method, due to its low treatment cost and high efficiency. Many studies verified that the ammonia in the food waste water served as a reducing agent to suppress the generation of NO_x when the food waste water was injected and incinerated. However, they have not revealed the correlation between the change in the concentration of the CO and NO_x by the influence of the solid matters contained in the food waste water on the incineration of the wastes. The purpose of this study is to determine the optimum amount of the food waste water injected through four nozzles in the primary and secondary incineration chambers and to assess the correlation between the concentration of CO and NO_x in accordance with the food waste water injection in each chamber of the incinerator. For the study, four food waste water injection nozzles were installed; two (A and B) at the top of the primary incineration chamber and the other two (C and D) in the secondary incineration chamber. The correlation between the change in the concentration of CO and NO_x was studied adjusting the amount of the food waste water injected through the nozzles. From the result, Case II showed the concentration of CO and NO_x as 1.8–10 and 14–26 ppm, respectively, while Case I showed that of CO and NO_x as 15–30 and 9–18 ppm, respectively. Those levels are well below the Korean emission criteria, 50 ppm for CO and 80 ppm for NO_x. Based on the results, it is evident there is a certain trade-off between emission of CO and NO_x, and Case II which has relatively low concentration of CO is easier and cheaper to control.     

Preparation,Characterization, and Rapid Adsorption of Hg<Superscript>2+</Superscript> on Nanoscale Aramid-based Adsorbent

A series of nanaoscale aramid-based adsorbents were prepared by the functionalization of poly (p-phenylene terephthalamide) (PPTA) with different content of ethylenediamine (EDA). Their structures were characterized by field emission scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, and elemental analysis. Metal ions, including Hg²⁺, Pb²⁺, Ag⁺, Cu²⁺, Cd²⁺, and Ni²⁺ were chosen as the models to explore the binding behaviors of PPTA–ECH–EDA in aqueous medium. Results showed that PPTA–ECH–EDA exhibited higher adsorption capacity for Hg²⁺ due to their nanoscale structures. In particular, the adsorption rate was so high that equilibrium was achieved within 15 min for Hg²⁺. The adsorption of Hg²⁺ on PPTA–ECH–EDA followed the pseudo second-order model well. Langmuir and Freundlich models were employed to fit the isothermal adsorption, and the results revealed that Freundlich isotherm was a better model to predict the experimental data. The adsorption mechanism was revealed by X-ray photoelectron spectroscopy. It is preconceived that PPTA–ECH–EDA could be used as an effective adsorbent for fast removal of heavy ions from wastewater.     

Prediction of ultimate bearing capacity of Tubular T-joint under fire using artificial neural networks

An artificial neural network (ANN) model is developed for the prediction of the ultimate bearing capacity of tubular T-joint under fire. The input parameters of the network are composed of the diameter ratio (β), the wall thickness ratio (τ), the diameter–thickness ratio (γ) and the temperature (T). The output parameter is composed of the ultimate bearing capacity. In this paper, the training and testing data of the neural network are obtained using the finite element program ABAQUS. The network is trained by 216 dataset and tested by 27 dataset. In the process of training of the network, the Levenberg-Marquardt back-propagation algorithm is adopted. The ‘tansig’ function is adopted in the hidden layer, and the ‘purelin’ function is adopted in the output layer. The results predicted by ANN are compared with the results simulated by finite element method (FEM). These results show that the prediction of the ultimate bearing capacity using the network model is accurate and effective.     

北京官厅水库特征污染物筛查及其健康风险评价

水源水中存在数以万计的污染物,需要根据不同水源污染特征筛查相应的特征污染物,并确定其对人体产生的健康风险。针对官厅水库及其出入库河流的表层水样,采用气相色谱质谱方法,对77种有机污染物进行了目标筛查和定量分析;采用非目标筛查的方法,对1 655种有机污染物进行了定性筛查。定量分析检出43种挥发性有机物(VOCs),浓度为nd～8.17 μg·L^-1;8种羰基化合物,浓度为nd～5.04 μg·L^-1;7种嗅味物质,浓度为nd～1 421.58 ng·L^-1。在检出的58种污染物中,有国家生活饮用水卫生标准(GB5749-2006)的共有23种,有国家地表水环境质量标准(GB3838-2002)的22种,浓度均未超过相关标准。对所检出的污染物进行了危害识别,发现5种嗅味物质浓度均超过了其嗅阈值。对其中有基础毒性数据的17种污染物进行了致癌风险评价,对37种污染物进行了非致癌风险评价。研究表明,17种污染物致癌风险处于10^-6～10^-5水平,而37种污染物的非致癌风险处于10^-2水平,均低于国际认同的风险控制阈值。定性筛查出80种具有潜在健康风险的有机污染物,作为进一步深入研究的目标污染物。据此,2012年调查中官厅水库水中的有机微污染对人体健康的风险总体上处于较低水平。其中,苯系物在官厅水库中普遍存在,六氯丁二烯和巴豆醛是主要的风险特征污染物,2-异丙基-3-甲氧基吡嗪(IPMP)、2-异丁基-3-甲氧基吡嗪(IBMP)和2,4,6-三氯茴香醚(TCA)是主要的致嗅特征污染物。