专家笔谈：资源环境热点问题

重大的资源开发利用工程建设设想或实施往往容易引起社会各界的广泛关注。如何正确认识和科学评价各种资源环境热点问题是大家讨论的重点。文章认为任何重大资源开发工程必须遵循自然规律、生态规律、资源规律和经济规律,必须结合国家战略需求和地缘政治关系,开展前期深入的系统性综合调查,进行生态安全与资源工程安全评价和交叉学科论证,并对其科学价值、社会价值和经济价值等做出正确的判断。建议：未来的资源环境工程建设要谨防“大跃进”,要科学认识自然资源系统规律,守护好美丽的地球家园;要切实履行资源科学家的社会责任,提倡基于科学研究和科学态度的学术争鸣,科学问题最好还是由科学家去讨论;一些争议大的科研课题慎用公益性研发经费来支持。     

气候变化和人类活动对武江流域年径流及最大日流量影响的定量分析

针对气候变化与人类活动对流域年径流及最大日流量变化影响的定量识别问题,以华南湿润区武江流域为例,分别采用HIMS（Hydro-Informatic Modeling System）模型和敏感性系数法,从日和年尺度定量模拟和评估气候变化与人类活动对流域年最大日流量和径流变化的影响过程及贡献率。结果表明：HIMS模型在武江流域适用性良好,日尺度模型率定期和验证期的纳西效率系数分别为0.85和0.77,水量平衡误差绝对值分别为3.1%和3.3%;两种方法均表明气候变化是引起流域年径流量增加的主要因素,人类活动导致了流域径流量的减少,但贡献率较小。气候变化与人类活动导致了流域年最大日流量的增加,气候变化对年最大日流量增加的贡献率为94%,而人类活动的贡献率则为6%。相较于年均径流量,气候变化对年最大日流量的影响更为显著。     

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     

可靠性强化试验技术在某型伺服作动器研制中的适用性探索

目的探索可靠性强化试验技术在典型机电液一体化产品伺服作动器研制过程中的适用性。方法以某型伺服作动器为研究对象,从故障激发的角度对可靠性强化试验技术的应用进行可行性分析,在响应调查和应力分析的基础上,结合产品的工作特点设计适用于该类伺服作动器的可靠性强化试验方案,包含低温步进应力试验、高温步进应力试验、快速温度循环试验10个循环、振动步进应力试验(包含气锤式三轴向六自由度超高斯随机振动方式及电磁振动台随机振动方式)及综合环境应力试验5个循环,并依此进行试验。结果在快速温度循环试验及综合环境应力试验过程中,均有效地激发出了产品的漏油故障,与相似产品外场暴露的漏油故障模式相吻合。结论可靠性强化试验技术可有效地应用于典型机电液一体化产品伺服作动器的研制过程,设计的可靠性强化试验方案可有效地激发外场出现频率较高的故障,可作为该类产品研制的试验手段之一。     

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.     

浅谈烟道气现场监测的工作管理

烟道气现场监测，易出差错。监测人员必须有良好的专业理论水平、丰富的工作经验、高度的敬业精神。本文就现场监测工作易出现问题进行了分析，列举了解决问题的方法     

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.     

中国水环境的NPSP问题及对策

介绍了我国水环境中的非点源污染（ＮｏｎｐｏｉｎｔＳｏｕｒｃｅｐｏｌｌｕｔｉｏｎ，缩写为ＮＰＳＰ）的情况，强调农业生产是最主要的非点源污染。同时，针对我国水污染防治的政策目标，提出一些建议。