A novel state-of-charge-based method for plug-in hybrid vehicle electric distance analysis validated with actual driving data

Mitigation and Adaptation Strategies for Global Change - Promoting Plug-In Hybrid Vehicles (PHEVs) is viewed as a promising strategy to mitigate the energy consumption and greenhouse gas...     

昆明市地下水污染防治现状与对策

文章以昆明市为例,分析了昆明市地下水水质现状及变化趋势,总结了地下水污染防治工作成效和存在问题。分析表明,由于长期未受到充分重视,昆明市地下水已呈现出污染加重的趋势。近年来,昆明市地下水污染防治取得了一定的成绩,但仍然存在监管能力不足、监测网络覆盖不全的问题。在此基础上提出了开展地下水环境状况调查评估、磷石膏堆场地下水污染防控与修复试点和进一步完善地下水环境监测网络的对策建议,为昆明市和其他南方城市做好地下水污染防治工作提供借鉴。     

模拟盐水入侵及Fe(III)浓度增强对河口感潮淡水沼泽湿地土壤反硝化速率及理化特征的影响

以闽江河口塔礁洲感潮淡水野慈姑(Sagittaria trifolia Linn.)湿地为研究对象,于2016年2、4、7和9月每月均在连续2个小潮日内向研究样地施加人造海水和Fe(OH)_3溶液,研究短期的盐水入侵及Fe(III)浓度增强对河口感潮淡水湿地土壤反硝化速率及理化特征的影响.结果表明,短期的盐水入侵、Fe(III)浓度增强对河口感潮淡水沼泽湿地土壤反硝化速率的影响不显著,然而,盐水和Fe(III)共同施加会显著提高湿地土壤反硝化速率,与对照(CK)相比,盐水和Fe(III)共同施加可使土壤反硝化速率提高270.9%.盐水入侵、盐水和Fe(III)共同施加均可显著提高湿地土壤、间隙水的电导率及Cl~-、SO_4~(2-)的含量;Fe(III)浓度增强可显著降低土壤和间隙水pH值,同时显著提高土壤三价铁含量.     

旅游目的地网络空间结构及其复杂性研究——野三坡旅游地案例实证

复杂性是旅游目的地网络化发展的必然趋势,是认识旅游地网络空间结构与组织特征的重要研究手段。论文以河北省野三坡旅游地为例,通过构建旅游联系强度模型,建立旅游地空间网络,并运用TOP网络空间分析以及复杂网络理论,揭示旅游地网络空间结构与组织的复杂性特征。研究发现：1）旅游地网络具有空间集聚性,形成了以核心景区为中心,由中心城镇、乡村社区和特色园区共同构成的空间集聚单元,并体现出“邻近连接”与“择优连接”的双重特性;2）旅游地网络服从幂律分布,具有无标度网络特性;3）每个节点的前三名和前五名旅游联系强度网络（Top3和Top5网络）具有较小的平均路径长度、较大的集聚系数,呈现出典型的“小世界网络”特征;4）旅游地网络是典型的异配型网络,度-度呈负相关,而网络节点的集聚系数与其度值之间存在近似的倒数关系,因此具有层次性。     

Long-term effects of sliver nanoparticles on the abundance and activity of soil microbiome

正Silver nanoparticles(Ag NPs)are among the most extensively used engineered nanomaterials because of their wellestablished antimicrobial and unique physicochemical properties(Yin et al.,2015).Applications of AgNPs have now been     

环境因素对建筑工程造价的影响模型研究

现代建筑材料多数使用钢材、混凝土、木材等高能耗产品,这些材料在生产和运输的过程中会消耗较大的能量,对建筑绿色度和的影响非常大,同时也不利于降低工程预算。通过对建筑资源能源消耗和造价进行调查分析,并对建筑材料对建筑环境负荷影响和建筑工程造价进行了研究,提出基于环境因素设置的工程造价模型。通过实际操作发现,相对于传统的工程造价模型,该模型对工程造价的变化趋势反应的更为直观准确,可以大幅度提高工程造价工作的效率。     

8-氨基喹啉-5-偶氮-对苯酚荧光光度法测定微量铬(Ⅵ)

在盐酸介质中,铬(Ⅵ)与AQAPOH形成可被氯仿萃取的荧光化合物,其λex/λem=295nm/400nm.线性范围为0-1.0μg Cr(Ⅵ)/25ml(水相),检测限为0.7μg/L.除Mn(Ⅶ)外,常见金属离子无干扰,可在数千倍Cr(Ⅲ)存在下测定废水中微量铬(Ⅵ).初步探讨了荧光反应的机理.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Determination of organophosphorus pesticides and related compounds in water samples by membrane extraction and gas chromatography

A membrane extraction-gas chromatography method was developed fordetermination of organophosphorus pesticides and related compounds including methamidophos, DDVP, dimethoate, methyl parathion, parathion, thiophosphoric acid trimethyl ester, and thiophosphoramidic acid dimethyl ester in water samples. In thismethod, surface-modified acetic cellulose membranes were used to extract the target analytes in water samples, the extracted analytes were back-extracted into a small amount of methanol, andgas chromatography with pulsed flame photometric detector (GC-PFPD) was used to determine the concentrations of targetanalytes in the extracts. The recoveries obtained for thetarget analytes spiked into the water samples ranged from 66to 94%. The method detection limit for each target analyte was 0.05 g L^-1. The method developed in this study had shown the advantages of being cheap, simple, fast, and reliable. It had been used successfully to determine the concentrations of target analytes in river water samples.