湿地营养物基准制定方法研究

湿地是自然界最具生物多样性和较高生产力的生态系统,对维持地球生态系统健康和调节气候、保持生物多样性等具有重要作用。然而由于受到不合理开发和人类活动的影响,湿地及其周边氮磷营养盐过量富集,导致湿地物种组成退化、生物多样性降低、湿地萎缩、湿地结构和功能受损等问题。目前,世界各国都高度重视湿地的生态保育和建设项目控制,由于我国在该领域起步相对较晚,生态保育和调控的理论及技术手段急需提升。湿地营养物基准是营养物在湿地中产生的生态效应不危及湿地水生态系统和或下游水体功能和用途的最大可接受浓度或限值,基准指标包括原因变量（水体和沉积物中的氮磷浓度）、生物反应变量（生物量）和支持变量（水文、传导率和粒度等）。湿地营养物基准是湿地富营养化识别、评价、管理以及湿地生态系统恢复的重要依据,也是控制下游水体营养物负荷,保护下游水体的重要支撑。     

环境保护社会团体健康有序发展策略研究

随着经济社会的不断发展,人民群众的环境意识在不断提高,环境质量改善等逐渐成为公众关注的热点,国内环保社团也随之不断发展和日趋活跃,成为环境保护方面的一股重要社会力量,发挥着愈来愈重要的作用。当前应该为环保社团的生存和发展提供良好的空间,以满足人民群众渴望不断改善环境质量的内在需求,更好地发挥环保社团对企业和个人不良环境行为的监督作用,为建设好美丽中国做出贡献。本文旨在对国内环保社团的发展现状和未来发展策略进行研究,文章既分析了当前环保社团发展的一些制约因素,也从管理体制改革,制度建设,具体实施办法等方面对中国环保社团未来发展策略提出了一些有益建议,以达到引导和促进国内环境保护社会团体健康有序发展之目的。     

Adsorption of 2-mercaptobenzothiazole from aqueous solution by organo-bentonite

The adsorption behavior of 2-mercaptobenzothiazole onto organo-bentonite was investigated.Natural bentonite from Gaozhou in Guangdong Province,China was collected.Organo-bentonite was prepared by intercalation of cetyltrimethyl ammonium bromide into the natural bentonite.The physicochemical properties of the prepared organo-bentonite were characterized by X-ray diffraction,N2 adsorption-desorption isotherm and Fourier transform infrared spectroscopy.The results showed that montmorillonite is the main component of the natural bentonite.The basal spacing of the natural bentonite is 1.47 nm,which increased to 1.98 nm on intercalation with cetyltrimethyl ammonium bromide.Moreover,both the surface area and pore volume increased with intercalation.Clear CH2 stretching(3000-2800 cm-1) and scissoring(1480-1450 cm-1) modes of the intercalated surfactants were observed for organobentonite.Compared with the pseudo first-order kinetic model,the pseudo second-order kinetic model is more suitable to describe the adsorption kinetics of 2-mercaptobenzothiazole onto organo-bentonite.The adsorption capacity of 2-mercaptobenzothiazole onto organo-bentonite increased with increasing initial concentration of 2-mercaptobenzothiazole,but decreased with increasing adsorbent dosage.The adsorption isotherm of 2-mercaptobenzothiazole onto organo-bentonite fits well with the Langmuir model.The maximum adsorption capacity of organo-bentonite for 2-mercaptobenzothiazole was 33.61 mg/g,indicating that organo-bentonite is a promising adsorbent for 2-mercaptobenzothiazole.     

二氯苯在土壤中的迁移行为和生物降解

主要从挥发、吸附与解吸、渗滤三个方面介绍了二氯苯在土壤中的迁移行为以及生物降解过程。探讨了二氯苯的物化性质、三种同分异构体的构型、土壤特性、外界环境条件等因素对二氯苯迁移行为的影响,以及迁移行为与生物降解的相互关系;同时介绍了可降解二氯苯的微生物种类、二氯苯好氧生物降解机理、共代谢现象,以及实验室研究方法。这些研究对于受二氯苯污染的土壤的修复具有理论指导意义。     

Photocatalytic oxidation of heptane in the gas-phase over TiO2.

In this paper, gas-phase photocatalytic oxidation (PCO) of heptane over UV-illuminated TiO2 was carried out at ambient temperature in a batch reactor. Complete oxidation of heptane with almost stoichiometric production of CO2 and H2O was observed. The intermediates detected were propanal, butanal, 3-heptanone, 4-heptanone and carbon monoxide. A scheme of the possible mechanism for PCO of heptane over TiO2 was suggested. Langmuir-Hinshelwood kinetics equation was obtained from the results at different initial concentrations of heptane, oxygen, moisture and light intensity. The photocatalytic activity of TiO2 can be sustained indefinitely. This can be attributed to the production of water in the system, which can replenish the consumed hydroxyl radicals.     

污染土壤毒性研究方法进展

综述了国内外有关污染土壤毒性研究方法 ,包括传统的方法如植物法、动物法和微生物法等和生态毒理学方法 ,并从生物、非生物和环境等方面论述了影响土壤毒性的因素 ,提出了当前土壤污染毒性研究方法中存在的问题 ,认为随着环境科学技术的发展 ,污染土壤毒性研究方法在环境保护中必将发挥越来越重要的作用     

Comparative study of extraction methods for the determination of PAHs from contaminated soils and sediments

The following four methods were compared on the extraction efficiency of 16 EPA (US Environmental Protection Agency) polycyclic aromatic hydrocarbons (PAHs): German method of the Verband Deutscher Landwirtschaftlicher Untersuchungs und Forschungsanstalten (VDLUFA), two methods of the International Organization for Standardization using shaking (ISO A) and Soxhlet extraction (ISO B) and an ultrasonic method. Recovery rates of 16 PAHs were determined in two soils. Extraction efficiency was evaluated in five soils and three sediments. Effect of drying soils and sediments on extraction efficiency was tested using the VDLUFA and the ultrasonic methods. Our study shows that the number of aromatic rings, rather than extraction procedures, significantly influenced recovery rates of individual PAHs. No significant differences in extraction efficiency of the four methods were observed for less polluted samples. For highly polluted soils, extraction efficiency decreased in the following order: VDLUFA method > ISO A > ultrasonic method > ISO B. Influence of soil moisture on extraction efficiency depended to some extent on both solvent used and content of PAHs in samples. A mixture of dichloromethane/acetone (5:1) is recommended for PAH extraction from moist samples when the ultrasonic method is used.     

团花锦蛇、绿锦蛇和三索锦蛇的核型及Ag-NORs

报道了锦蛇属团花锦蛇（Ｅ．ｄａｖｉｄｉ）、绿锦蛇（Ｅ．ｐｒｖｓｉｎａ）和三索锦蛇（Ｅ．ｒａｄｉａｔａ）３个种的核型和Ａｇ－ＮＯＲｓ,团花锦蛇的型２ｎ＝３６（８Ｖ＋６ｓＶ＋２Ｉ＋２０Ｍ）,绿锦蛇的核型２ｎ＝３６（７Ｖ＋７ｓＶ＋２Ｉ＋２０ｍ）,三索锦蛇的核型２ｎ＝４０（６Ｖ＋３ｓＶ＋２ｓＩ＋５Ｉ＋２４ｍ）;①团花锦蛇和绿锦蛇的染色体数目和结构与此属大多数咱的相似,;②此种为雄性,未见染色体异型。③Ａｇ     

巢湖蓝藻酸提取液提高玉米秸秆的酶解效率

资源化利用是避免富营养化水体打捞得到的蓝藻二次污染的有效方法途径。本研究以巢湖蓝藻为例,利用稀硫酸处理得到酸提取液并将其用于玉米秸秆的酶解过程。以主要成分还原糖和蛋白质的提取量为目标,优化了稀硫酸处理条件(处理时间、温度和硫酸浓度)。结果表明,从巢湖蓝藻提取还原糖的效率随着处理温度和硫酸浓度的升高而升高。在处理温度为125℃,处理时间为2 h,稀硫酸浓度为5%时,提取的还原糖最多为(152.8±12.6)mg/g。稀硫酸处理条件对蛋白质的提取效果影响并不显著。在处理温度为105℃,处理时间为1 h,稀硫酸浓度为5%时,最大提取量为(1.55±0.00)mg/g。提取的藻液中和后可以用于玉米秸秆的酶解过程,同对照相比酶解效率能够提升10%左右。结果表明,藻液中的小分子物质和钙离子是主要的作用组分,推测其和木质素表面官能团结合,从而降低了木质素对纤维素酶的非再生吸附。     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.