铁屑对低浓度含铬地下水的处理研究

以某铬渣污染场地上抽提上来的低浓度含铬地下水作为实验研究对象。选用铁屑对含铬废水进行处理。通过静态试验考察了影响六价铬去除率的因素:pH、铁屑用量、反应时间,得到了较好的反应工艺参数。并在静态试验的基础上,用铁屑填充自制的反应柱研究了动态试验的效果。结果表明:六价铬的出水浓度低于0.05 mg/L,达到GB/T 14848-93《地下水质量标准》Ⅲ类排放标准。     

Discrete-choice experiments valuing local environmental impacts of renewables: two approaches to a case study in Portugal

Despite the often mentioned environmental benefits associated with transition from fossil fuels to renewable energy sources, their use for electricity production has non-negligible negative environmental impacts. The most commonly mentioned in surveys concern different types of landscape impacts, impacts on the fauna and flora, and noise. These impacts differ by size and location of plants, and by source of energy, rendering the policy decision complex. In addition, there are other welfare issues to take into consideration, as positive and negative environmental impacts are not evenly distributed among population groups. This paper proposes to compare the welfare impacts of renewable energy sources controlling for the type of renewable as well as the specific environmental impact by source. To this end, two discrete-choice experiments are designed and applied to a national sample of the Portuguese population. In one case, only individual negative impacts of renewables are used, and in another case, the negative impacts interact with a specific source. Results show the robustness of discrete-choice experiments as a method to estimate the welfare change induced by the impacts of renewable energy sources. Overall, respondents are willing to pay to reduce the environmental impacts, thus making compensation for local impacts feasible. Moreover, the estimations reveal that respondents are significantly sensitive to the detrimental environmental effects of specific renewable energy sources, being willing to pay more to use these sources of energy relative to others.     

正交实验在气浮法条件筛选中的应用研究

正交试验是研究多因素多水平的一种设计方法,它是根据正交性从全面试验中挑选出部分有代表性的点进行试验,这些有代表性的点具备了“均匀分散,齐整可比”的特点,正交试验设计是分析因式设计的主要方法。是一种高效率、快速、经济的实验设计方法。将正交试验选择的水平组合列成表格,称为正交表。本文选择对溶气气浮法为研究对象,通过PAC的加入量、沉降时间、搅拌强度和搅拌时间等因素对废水的混凝处理效果有较大影响,为确定各因素的最佳值和影响效果的主次关系,选择影响较大的因素,采用正交实验确定设备最佳的运行条件。     

高密度沉淀池技术概述

高密度沉淀池(Densadeg)以其结构紧凑、处理效率高、出水水质稳定等特点,越来越多地被应用于城市污水一级强化处理和深度处理。本文主要介绍了高密度沉淀池的三种基本类型,重点阐述了RL型高密度沉淀池的工作原理及组成,以及污泥外部循环系统、高效斜板设置的特点;同时介绍了Densadeg的另一种运行方式:超高速沉淀池(ACTIFLO工艺),展望了高密度沉淀池的应用前景。     

武当山夏季颗粒物数浓度谱分布特征及气团来源影响研究

为研究大气边界层中上层大气颗粒物的数浓度谱分布特征及气团来源的影响,于2018年6月利用3080型SMPS粒径谱仪对武当山14.6~660 nm颗粒物数浓度谱进行观测,分析和探讨了其数浓度谱分布及日变化特征,并结合后向轨迹、潜在源贡献因子法（PSCF）与浓度权重轨迹分析法（CWT）探讨对武当山颗粒物数浓度影响较大的外源输送路径和贡献源区.结果表明:①武当山大气颗粒物主要以爱根模态为主,平均数浓度为2 500个/cm3,积聚模态、核膜态平均数浓度分别为2 265、359个/cm3,3种模态数浓度分别占总数浓度的48.79%、44.21%、7.01%.②在新粒子生成日,核膜态数浓度于10:00开始上升,11:00—17:00的核膜态数浓度相对较高,约2 000个/cm3.新粒子生成日ρ（SO₂）与ρ（O₃）的日变化趋势均与核模态数浓度较为相似,表明SO₂和O₃参与光化学反应后的产物（硫酸及有机物）有利于新粒子的生成与增长.新粒子生成日风速、温度均大于非新粒子生成日,但相对湿度较低.③在东部及局地气团影响下大气颗粒物主要以积聚模态为主,数浓度分别为2 311和2 596个/cm3;核模态、爱根模态数浓度在受西北气团影响时最大,数浓度分别为806和3 078个/cm3.④潜在源区分析表明,影响武当山积聚模态数浓度的主要源区为十堰市本地及襄阳市,二者贡献值在840个/cm3以上.研究显示,武当山颗粒物主要以爱根模态为主,颗粒物数浓度日变化主要受大气边界层发展及山谷风的影响,较高的ρ（SO₂）与ρ（O₃）以及高温、低湿及较大的风速均有利于新粒子的生成,周边城市的区域性传输对武当山颗粒物的影响较大.      

Monitoring and reporting attacks on education in the Democratic Republic of the Congo and Somalia

The United Nations' Monitoring and Reporting Mechanism is charged with documenting six grave violations against children in a time of conflict, including attacks on schools. Many of these incidents, however, remain unreported across the globe. This study explores whether or not a local knowledge base of education and child protection actors in North and South Kivu Provinces, Democratic Republic of the Congo, and in Mogadishu, Somalia, could contribute to a more complete record of attacks on education in those areas. Hundreds of semi‐structured interviews were conducted with key informants across the three settings, and in total 432 attacks on education were documented. Purposive samples of these reports were verified and a large majority was confirmed. Local non‐governmental organisations and education institutions were most knowledgeable about these incidents, but most never reported them to a monitoring authority. The study concludes that attack surveillance and response were largely insufficient, and recommends investing in mechanisms that utilise local knowledge to address these shortcomings.     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

Chemometrics methods for the investigation of methylmercury and total mercury contamination in mollusks samples collected from coastal sites along the Chinese Bohai Sea

The development and application of chemometrics methods, principal component analysis (PCA), cluster analysis and correlation analysis for the determination of methylmercury (MeHg) and total mecury (HgT) in gastropod and bivalve species collected from eight coastal sites along the Chinese Bohai Sea are described. HgT is directly determined by atomic fluorescence spectrometry (AFS), while MeHg is measured by a laboratory established high performance liquid chromatography-atomic fluorescence spectrometry system (HPLC-AFS). One-way ANOVA and cluster analysis indicated that the bioaccumulation of Rap to accumulate Hg was significantly (P<0.05) different from other mollusks. Correlation analysis shows that there is linear relationship between MeHg and HgT in mollusks samples collected from coastal sites along the Chinese Bohai Sea, while in mollusks samples collected from Hongqiao market in Beijing City, there is not any linear relationship.     

雾化电晕净化烹调油烟技术

对雾化电晕放电极雾化过程、荷电液滴的捕集原理、自清洗作用进行探讨,在相同电压下雾化负电晕放电电流高于干式负电晕放电电流,极间大量荷电液滴具有很高的荷质比,并高速向极板驱进,对烟尘具有静电凝并和动力凝并除尘作用,具有高效净化油烟、自清洗极板的功能,此项净化烹调油烟的新技术,优于传统油烟净化技术,具有很好的应用价值和前景。     

双农杆菌共转化获得无标记转pepc基因的水稻植株

利用双农杆菌/双质粒的共转化系统获得了无选择标记转pepc基因的水稻植株.采用两个农杆菌EHA105转化粳稻品种台粳9号幼胚诱导的胚性愈伤组织,其中一个农杆菌内的质粒表达载体的T-DNA区仅含有目的基因pepc,另一个的T-DNA区含有选择标记基因hpt和GUS报告基因.获得抗性愈伤的转化率为9.2%.85.3%的抗性愈伤分化成T0代株系,其中78.8%的T0代植株为GUS阳性转基因植株.PCR分析表明,在78个T0代GUS阳性植株(来源于23个抗性愈伤组织)中共有35个植株(来源于7个抗性愈伤组织)含有pepc基因,即在23个GUS阳性株系中发生共转化株系的频率为30.4%.7个共转化的株系中有5个株系自交产生后代植株中含有无标记转pepc基因植株,其比例为71.4%.无标记的转pepc基因水稻植株中PEPC活性平均比对照提高8.8倍;与非转基因对照植株相比,转pepc基因水稻植株表现出更强的光合能力.图5表3参26