城市生活污水生化出水中有机物的臭氧氧化特性

考察了O3法对城市生活污水生化出水中溶解性有机物的去除效果以及二级出水中各类有机污染物的氧化特性。实验结果表明:O3法对于城市污水二级生化出水的UV254值具有较高的去除效率,20 min内即可达57.1%的去除率,COD去除速率较慢,150 min时去除率为62.5%,而DOC去除效果很差,150 min的去除率仅为36.1%。经氧化处理后,疏水性物质的浓度明显下降,其中非酸疏水物质则基本被氧化完全,而亲水性物质氧化效果很差。水中各类有机物的组成发生明显变化。对不同的有机物而言,其氧化去除速率为疏水性物质>弱疏水物质>亲水性物质。

水中有机物和水处理工艺相关性分析

在介绍水中有机物典型分类方法 (分子量分级、亲水性憎水性分类 )的基础上 ,阐明了不同分类有机物与水处理工艺之间的关系。混凝沉淀主要去除水中大分子、憎水性的有机物 ,活性炭倾向于吸附中间分子量、与自身孔径分布相一致的憎水有机物 ,臭氧氧化出水分子量减小 ,适量臭氧投加量可以增强有机物的可吸附性 ,憎水性的大分子有机物是纳滤膜优先去除的主要对象 ,同时这一部分有机物也是膜污染的主要原因。不同的水处理工艺有不同的特定有机物去除对象 ,不同有机物对不同工艺产生不同的影响。

谈有机化学总复习

有机化学的总复习应当使学生将有机化学知识系统化、网络化。通过对有机化学知识有明确测试目标的讲练,使学生加深和强化对有机化学知识的理解、掌握和运用,提高学生综合和灵活运用所学知识解决实际问题的能力。

城市供水水处理发展趋势——活性炭处理方法

活性炭是一种经特殊处理的炭,具有无数细小孔隙,表面积巨大,活性炭的表面积为500～1 500 m2/g。活性炭由很强的物理吸附和化学吸附功能,而且还具有解毒作用。

APPROACH TO THE REGIONALIZATION OF A GRICULTURAL-PASTURALIZATION AROUND CHANGSHAN ISLANDS IN NORTHERN YELLOW SEA

Based on the data of resources,environment and foundation of productio n,applying principal compo-nents-clustering quantitative analysis,this article divides the maritime space of Changshan Islands into three regions of agricultural-pasturalization,pr oviding a scientific basis for the ra tional distribution of marine culti vation.The three re-gions are as follows:1)The region of an agricultural-pastu ralization in the northern part of ma ritime space.It includes Da Wangjia and Shicheng islands.The ma in production is cultivation of praw n and molluscs in sea beach,float raft culture of mussel in shallow sea and scallop,and breeding of sea cucumber in subma rine.2)The region of agricultur-al-pasturalization in the middle we stern part of maritime space.It includes Da Changshan and Guanglu island s,and west-ern part of Xiao Chengshan Island.The main production is float raft cultu re of mussel and scallop in shallow se a,and breed-ing of sea cucumber in submarine.3)The region of agricultural-pastura lization of the southeastern part of maritime space.It includes the eastern part of Xiao ChangShan Island,Haiyang and Zhangzi islands.The main production is bre eding of abalone,sea cucumber,algaes and fish.

Decomposition of algal lipids in clay-enriched marine sediment under oxic and anoxic conditions

A series of laboratory incubation experiments were conducted to examine the decomposition of algal organic matter in clay-enriched marine sediment under oxic and anoxic conditions. During the 245-day incubation period, changes in the concentrations of TOC, major algal fatty acid components （14：0, 16：0, 16：1, 18：1 and 20：5）, and n-alkanes （C16-C23） were quantified in the samples. Our results indicate that the organic matters were degraded more rapidly in oxic than anoxic conditions. Adsorption of fatty acids onto clay minerals was a rapid and reversible process. Using a simple G model, we calculated the decomposition rate constants for TOC, n-alkanes and fatty acids which ranged from 0.017-0.024 d^-1, 0.049-0.103 d^-1 and 0.011 to 0.069 d-l, respectively. Algal organic matter degraded in two stages characterized by a fast and a slow degradation processes. The addition of clay minerals montmorillonite and kaolinite to the sediments showed significant influence affecting the decomposition processes of algal TOC and fatty acids by adsorption and incorporation of the compounds with clay particles. Adsorption/association of fatty acids by clay minerals was rapid but appeared to be a slow reversible process. In addition to the sediment redox and clay influence, the structure of the compounds also played important roles in affecting their degradation dynamic in sediments.

Organic composition of gasoline and its potential effects on air pollution in North China

When gasoline is burned to power an automotive engine, a portion of the fuel remains unburned or is partially burned and leaves the engine as hydrocarbon and oxygenated compounds. In addition, a small portion of the fuel can escape the vehicle through evaporation. Changes in alkanes, olefins and aromatics each affect emissions differently, which could complicate control strategies for air pollution. In this study, we collected 31 gasoline samples over five provinces and cities(Beijing, Tianjin, Hebei, Shandong, and Shaanxi) in North China between 2012 and 2013. The organic composition of the gasoline samples was analyzed using the gas chromatography-mass spectrometry(GC-MS) method, and the aniline compounds were analyzed by solvent extraction and the GC-MS method. The ratios of alkanes, aromatics, olefins and other organic compounds in gasoline were 40.6%, 38.1%, 12.9% and 8.4%, respectively. The aromatic and benzene exceedances were 15 and 8 based on the China's gasoline standards(III), and they accounted for 48.4% and 25.8% of all the gasoline samples, respectively. Strong carcinogen aniline compounds were detected in all 31 samples, and the content of aniline compounds in 3 samples exceeded 1%. The high proportion of aromatics and olefins in the gasoline increased the emissions of carbon monoxide(CO) and toxics, as well as the atmospheric photochemical reactivity of exhaust emissions, which could hasten the formation of secondary pollutants. Our results are helpful for redefining government strategies to control air pollution in North China and relevant for developing new refining technology throughout China.

Development of a national VNIR soil-spectral library for soil classification and prediction of organic matter concentrations

Soil visible-near infrared diffuse reflectance spectroscopy(vis-NIR DRS)has become an important area of research in the fields of remote and proximal soil sensing.The technique is considered to be particularly useful for acquiring data for soil digital mapping,precision agriculture and soil survey.In this study,1581 soil samples were collected from 14 provinces in China,including Tibet,Xinjiang,Heilongjiang,and Hainan.The samples represent 16 soil groups of the Genetic Soil Classification of China.After air-drying and sieving,the diffuse reflectance spectra of the samples were measured under laboratory conditions in the range between 350 and 2500 nm using a portable vis-NIR spectrometer.All the soil spectra were smoothed using the Savitzky-Golay method with first derivatives before performing multivariate data analyses.The spectra were compressed using principal components analysis and the fuzzy k-means method was used to calculate the optimal soil spectral classification.The scores of the principal component analyses were classified into five clusters that describe the mineral and organic composition of the soils.The results on the classification of the spectra are comparable to the results of other similar research.Spectroscopic predictions of soil organic matter concentrations used a combination of the soil spectral classification with multivariate calibration using partial least squares regression(PLSR).This combination significantly improved the predictions of soil organic matter(R2=0.899;RPD=3.158)compared with using PLSR alone(R2=0.697;RPD=1.817).