优势菌的筛选及其强化活性污泥好氧反硝化的研究

利用含活性污泥提取物的贫培养基筛选SBR系统中的好氧异养优势菌。结合自然温度（15～20℃）、延长培养时间等条件来提高菌群的可培养性。从SBR活性污泥系统中分离出5种细菌。4株去除COD优势菌,1株异养硝化细菌,能在好氧条件下实现对总氮的去除。反应池底采用边缘对称曝气,反应池内细菌在时间顺序和空间位置上循环经历好氧过程及微氧过程。将PVA铝盐法固定的细菌对反应器进行生物强化。结果显示,在好氧工艺的条件下,投加优势菌群后,与未加优势菌群的反应器相比,可以显著改善污泥的沉降性能,COD、NH₃-N和TN降解率显著提高,分别达到98%、97%和90%。生物强化作用明显,反应器内具有良好的好氧反硝化环境。     

地震现场数据共享标准化研究及其标准起草

标准化被普遍认为是保证信息更有效处理、交换、管理以及消除技术壁垒的最有效手段.信息共享标准是为规范信息共享的行为而制订的,是实现信息共享的"软"环境.通过对地震现场信息共享标准化研究,概述了这一标准制定的过程、总体内容框架安排的一些考虑以及存在问题,讨论了地震现场信息共享标准分类与编码体系、数据交换格式、元数据、数据字典及数据质量控制等与信息共享标准相关的一些问题.     

隐伏断裂的地气测量及其意义

传统概念的地气测量是指地下上升到地表并扩散到大气空间的天然状态气体 ,如CO2 、CH4 、Rn、Hg、H2 等。近十多年的研究证实地气还包含着新的内涵 ,即地壳岩石以及地表土壤中还存着痕量的金属与非金属气体 ,通过捕集这些气体 ,可以获得更多的深部地质构造、矿床信息。据报导 ,国内外的研究主要是在已知矿床上做的正演研究。本文是在已知隐伏断层构造上方地表 ,试验金属与非金属地气存在的可能性。     

A biomimetic absorbent for removal of trace level persistent organic pollutants from water

A novel biomimetic absorbent containing the lipid triolein was developed for removing persistent organic pollutants (POPs) from water. The structural characteristics of the absorbent were obtained by SEM and a photoluminescence method. Under optimum preparation conditions, triolein was perfectly embedded in the cellulose acetate (CA) spheres, the absorbent was stable and no triolein leaked into the water. Dieldrin, endrin, aldrin and heptachlor epoxide were effectively removed by the CA--triolein absorbent in laboratory batch experiments. This suggests that CA-triolein absorbent may serve as a good absorbent for those selected POPs. Triolein in the absorbent significantly increased the absorption capacity, and lower residual concentrations of POPs were achieved when compared to the use of cellulose acetate absorbent. The absorption rate for lipophilic pollutants was very fast and exhibited some relationship with the octanol--water partition coefficient of the analyte. The absorption mechanism is discussed in detail.     

上海与伦敦城市绿地的生态功能及管理对策比较研究

在资料收集及实地采样调查的基础上 ,文章对上海与伦敦城市绿地的生态功能及管理对策进行了比较分析 ,指出了上海城市绿地建设及管理中的一些优点及不足之处。     

可持续发展城市规划是迈向新世纪的必然选择

主要论述可持续发展城市规划是人类走向生态文明的必然之理以及它的含概机理与实施途径。     

Pollution characteristics of 23 veterinary antibiotics in livestock manure and manure-amended soils in Jiangsu province,China

The aim of this study was to investigate the pollution characteristics of typical veterinary antibiotics in manure and soil of livestock farms in Jiangsu province. This investigation employed solid-phase extraction (SPE) coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A total of 53 manure and 50 amended soil samples from 16 livestock farms in Jiangsu province were collected for analysis. In the manure samples, the highest detected frequencies and concentrations were those of tetracyclines (TCs, 54.1 ± 5775.6 μgkg^?1), followed by fluoroquinolones (FQs, 8.4 ± 435.6 μgkg^?1), sulphonamides (SAs, 3.2 ± 5.2 μgkg^?1) and macrolides (MACs, 0.4 ± 110.5 μgkg^?1). Statistical analysis was used to illuminate the pollution characteristics of 23 veterinary antibiotics for various animal types and different regions in Jiangsu province. The results showed that the pollution level in cow manure was relatively lower compared with pig and chicken manure due to the relative restriction of medication. Furthermore, contamination was serious in amended soil from chicken farms. The pollution level in manure among different regions was higher to the south and north compared with the centre of the region. The same outcome was found for soil. Antibiotic residues in organic fertilizer were also investigated in this study. We found that although the detected concentration was lower in organic fertilizer than in fresh manure, detection frequencies (10–90%) were high, especially for roxithromycin (90%) in MACs (30–90%). This finding suggests attention should be paid to the pollution levels in organic fertilizer. This study is the first extensive investigation of the occurrence and distribution of many kinds of typical veterinary antibiotics in manure and soil from livestock farms of Jiangsu province. This investigation systematically assesses veterinary antibiotics usage and related emissions in southeast China.     

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.     

Economic dispatch of power system containing wind power and photovoltaic considering carbon trading and spare capacity variation

The drying up of the fossil energy sources and the damage from unchecked carbon emissions demand the development of low carbon economy, which promotes the development of new energy sources, such as wind power and photovoltaic. However, the direct connections of wind/photovoltaic power into power grid bring great impacts on power systems, thus affecting the security and stability of power system operations, which challenges the power system dispatching. In despite of many methods for power system dispatch, lack of the models, for power system containing wind power and photovoltaic considering carbon trading and spare capacity variation (PSCWPCCTSCV), restricts the further optimal operations of power systems. This paper studies the economic dispatch modeling problem of power system containing wind power and photovoltaic, establishes the model of economic dispatch of PSCWPCCTSCV. On this basis, adaptive immune genetic algorithm is applied to conduct the economic operation optimization, which can provide the optimal carbon trading price and the optimal power distribution coefficient. Finally, simulations based on the newly proposed models are made to illustrate the economic dispatch of PSCWPCCTSCV. The results show that optimization with the proposed model can not only weaken the volatility of the new energy effectively, but also reduce carbon emissions and reduce power generation costs.