水中氮类污染物的联系与区别

叙述了水体中含氮类污染物的来源，种类，相互转化方式和条件，表征意义等，以便对水中氮类污染物有一个全面，系统的认识。     

氨氮测定过程中有关问题的探讨

针对纳氏比色法测定氨氮过程中存在的问题，提出了相应的解决办法。消除了混浊和泡沫干扰问题，降低了空白吸光度，提高了测定的准确度。     

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.     

同时分解法测定水中总氮和总磷

通过实验找到了同时测定水中总氮和总磷的条件,实现了总氮和总磷的同时测定。     

天然石材产品放射性水平及其防护管理

简介了我国天然石材产品中放射水平、分类控制使用的现状以及应用天然石材装饰室内所致辐射对人体健康产生的不良影响，提出了加强对天然石材产品使用过程中的监督、监测和管理的建议。     

Aerosol Scavenging: Model Application and Sensitivity Analysis in the Indian Context

Sulfate aerosols have been found to bethe major contributors to precipitation acidity. Thus,in view of the long-term ecological repercussions theyhave on aquatic ecosystems and their acidity-potential,the present analysis focuses on a case study applicationof the layer-averaged aerosol-scavenging model (Okita et al., 1996) for predicting values of the wet scavengingcoefficient and sulfate concentrations in precipitationsamples on the basis of the information available forsome selected Indian cities. Through sensitivityanalysis (Pandey et al., 1997) the scavengingcoefficient has been found to be very strongly dependenton precipitation intensity. Comparison of modelpredictions has been done with the measured values forDelhi, Mumbai, Calcutta and Chennai in India.     

Prediction of Leachate Level in Kimpo Metropolitan Landfill Site by Total Water Balance

Kimpo metropolitan landfill has received various kinds of wastessince January 1992. The leachate level was measured to be 10.3 m in May 1995 and the level increased to 12.2 m in August 1996. Therefore, to prove the reason for the increasing leachate level, we calibrated hydraulic conductivity of each waste andintermediate layer using the HELP (Hydrologic Evaluation ofLandfill Performance) model. The leachate generation data measured from February 1993 to October 1995 was used in the model calibration. As a result of a model calibration, we obtained anaverage infiltration ratio and used this in analysis of the total water balance to predict elevation of leachate level. Main causes of the elevation of the leachate level were the high water content of the waste and the degradation of the leachate-drainage system caused by the subsidence of a naturalbarrier layer.     

Nitrogen isotope ratios in pine bark as an indicator of N emissions from anthropogenic sources

The article describes the use of Scots pine bark to identifynitrogen sources in eastern Germany, as well as background areas in Russia and Bulgaria, by using natural isotope ratios of total nitrogen (N_t) and individual N compoundssuch as ammonium (NH₄ ⁺), nitrate (NO₃ ^-)and amid nitrogen (amide-N). The samples collected were analysed using an elemental analyser in connection with a gas isotope mass spectrometer (EA-IRMS). Natural ¹⁵N abundances in pine bark from impact areas suggest that the ammonium accumulated on the surface of the bark is releasedfrom livestock management. Bark of Scots pines growing near agricultural land had highly depleted ¹⁵N_t values (between –8 and –12), while bark from background areas (unpolluted areas) displayed slightly negative ¹⁵N_t values (mean ¹⁵N_t = –3.8). It is assumed that part of the N adsorbed on the bark surface is mainly derived from ammonia(mean ¹⁵N_t = –40.3) escaping from livestock housing and during the application of manure. This assumption is confirmed by experiments under controlled conditions in which manure samples were spread on soil. In addition, temporal and spatial variations of ¹⁵N_t abundances in pine bark from various locations in eastern Germany as wellas pine stands in Nature Park Dübener Heath are discussed.     

测定总氮的影响因素探讨

针对水质中总氮测定时蒸馏水、消解剂和消化过程等影响因素进行了讨论,并提出了减小空白值的对策。     

消泡剂硅油I在工业废水氨氮测定中的应用

对色泽较深，含杂质量较高的废水加硅油I以抑制测定中蒸馏产生的泡沫．结果表明，在250ml水样中加硅油IO．10～1．25ml，即可收到理想效果．硅油I性质稳定，不随水蒸汽蒸出，对测定无干扰．