A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

在线自动监测仪与实验室国标方法测定地表水中总氮的比对分析

随着监测技术的发展,地表水中越来越多的污染物可采用自动监测仪器实现实时监测。采用自动监测与实验室国标方法测定地表水中总氮的结果是否可比以及造成差异的原因,文章根据实际样品比对实验对此进行了探讨。     

检验环境影响预测准确度统计方法的研究近况

开展环境影响评价工作近二十年来，国内外对预测结果准确度的检验尚无制定统一标准，而预测结果的准确与否，又直接影响到环境影响报告书的质量。为此，本文将国内外这方面的研究状况作以评论，以供从事环境影响评价和后评估的专业人员参考     

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。     

新疆生态功能区划初探

“新疆生态功能区划”参考了“中国综合生态环境区划方案”，以《生态功能区划暂行规程》为依据，充分考虑新疆独特的地理分布格局，将新疆分为5个生态区，18个生态亚区，79个生态功能区。“新疆生态功能区划”对科学有效地管理新疆生态环境，因地制宜地实施保护和治理策略，保证社会经济可持续发展具有重要意义。     

兰州市功能区大气细菌污染和城市绿地系统杀菌效应分析

在测定兰州市城市不同功能区和不同类型绿地系统空气细菌数量的基础上,分析了各功能区空气细菌污染状况,以及人流量和车流量与空气细菌数量之间的关系;探讨了不同绿地系统的杀菌效应,指出各绿地系统杀菌能力:乔、灌、草>乔、灌>草、灌>草坪。     

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。     

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.