Dynamic nano-Ag colloids cytotoxicity to and accumulation by Escherichia coli: Effects of Fe3+, ionic strength and humic acid

Released Ag ions or/and Ag particles are believed to contribute to the cytotoxicity of Ag nanomaterials, and thus, the cytotoxicity and mechanism of Ag nanomaterials should be dynamic in water due to unfixed Ag particle:Ag⁺ ratios. Our recent research found that the cytotoxicity of PVP-Ag nanoparticles is attributable to Ag particles alone in 3 hr bioassays, and shifts to both Ag particles and released Ag⁺ in 48 hr bioassays. Herein, as a continued study, the cytotoxicity and accumulation of 50 and 100 nm Ag colloids in Escherichia coli were determined dynamically. The cytotoxicity and mechanisms of nano-Ag colloids are dynamic throughout exposure and are derived from both Ag ions and particles. Ag accumulation by E. coli is derived mainly from extracellular Ag particles during the initial 12 hr of exposure, and thereafter mainly from intracellular Ag ions. Fe³⁺ accelerates the oxidative dissolution of nano-Ag colloids, which results in decreasing amounts of Ag particles and particle-related toxicity. Na⁺ stabilizes nano-Ag colloids, thereby decreasing the bioavailability of Ag particles and particle-related toxicity. Humic acid (HA) binds Ag⁺ to form Ag⁺-HA, decreasing ion-related toxicity and binding to the E. coli surface, decreasing particle-related toxicity. HA in complex conditions showed a stronger relative contribution to toxicity and accumulation than Na⁺ or Fe³⁺. The results highlighted the cytotoxicity and mechanism of nano-Ag colloids are dynamic and affected by environmental factors, and therefore exposure duration and water chemistry should be seriously considered in environmental and health risk assessments.     

Mechanism and catalytic performance for direct dimethyl ether synthesis by CO2 hydrogenation over CuZnZr/ferrierite hybrid catalyst

Direct synthesis of dimethyl ether(DME) by CO_2 hydrogenation has been investigated over three hybrid catalysts prepared by different methods:co-precipitation,sol-gel,and solid grinding to produce mixed Cu,ZnO,ZrO_2 catalysts that were physically mixed with a commercial ferrierite(FER) zeolite.The catalysts were characterized by N_2 physisorption,X-ray diffraction(XRD),transmission electron microscopy(TEM),X-ray photoelectron spectroscopy(XPS),temperature programmed desorption of CO_2(CO_2-TPD),temperature programmed desorption of NH_3(NH_3-TPD),and temperature programmed H2 reduction(H_2-TPR).The results demonstrate that smaller CuO and Cu crystallite sizes resulting in better dispersion of the active phases,higher surface area,and lower reduction temperature are all favorable for catalytic activity.The reaction mechanism has been studied using in situ diffuse reflectance infrared Fourier transform spectroscopy(DRIFTS).Methanol appears to be formed via the bidentate-formate(b-HCOO) species undergoing stepwise hydrogenation,while DME formation occurs from methanol dehydration and reaction of two surface methoxy groups.     

Effect of NOx and SO2 on the photooxidation of methylglyoxal: Implications in secondary aerosol formation

Methylglyoxal(CH_3COCHO,MG),which is one of the most abundant α-dicarbonyl compounds in the atmosphere,has been reported as a major source of secondary organic aerosol(SOA).In this work,the reaction of MG with hydroxyl radicals was studied in a 500 L smog chamber at(293±3) K,atmospheric pressure,(18±2)% relative humidity,and under different NOx and SO_2.Particle size distribution was measured by using a scanning mobility particle sizer(SMPS) and the results showed that the addition of SO_2 can promote SOA formation,while different NOx concentrations have different influences on SOA production.High NOx suppressed the SOA formation,whereas the particle mass concentration,particle number concentration and particle geometric mean diameter increased with the increasing NOx concentration at low NOx concentration in the presence of SO_2.In addition,the products of the OH-initiated oxidation of MG and the functional groups of the particle phase in the MG/OH/SO_2 and MG/OH/NOx/SO_2 reaction systems were detected by gas chromatography mass spectrometry(GC-MS) and attenuated total reflection fourier transformed infrared spectroscopy(ATR-FTIR) analysis.Two products,glyoxylic acid and oxalic acid,were detected by GC-MS.The mechanism of the reaction of MG and OH radicals that follows two main pathways,H atom abstraction and hydration,is proposed.Evidence is provided for the formation of organic nitrates and organic sulfate in particle phase from IR spectra.Incorporation of NOx and SO_2 influence suggested that SOA formation from anthropogenic hydrocarbons may be more efficient in polluted environment.     

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.      

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...     

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.