广东省"十五"环境统计改革设想

在国家环保总局"十五"环境统计改革基础上,结合各省经验和广东省实际,提出了广东省环境统计改革设想,逐步实行季报、月报,并将环境统计、排污申报合二为一。     

基于GIS环境管理平台聚类分析的实现

高效数字化管理技术是我国环境管理工作的关键和必然趋势。地理信息系统和多元统计方法虽然在环境管理中已经得到一定程度的应用,但这两种高效工具几乎处于"脱节"状态;文章在GIS平台上有效地集成了系统聚类分析方法,有利于区域环境质量管理对空间海量数据的分析,文章重点介绍了系统聚类谱系图的生成算法与绘制中的难点,并用实例验证了该算法的可靠性和实用性。     

高锰酸盐指数测定中校正系数K值的变化验证

运用数理统计方法,验证了高锰酸盐指数测定的校正系数K值在4～5h内不会随时间和水样的变化而变化,K值不必每个样品都测定。     

加强环境统计工作的几点建议

分析了当前环境统计工作中存在的一些问题,提出了对策和建设.     

COMPARISON OF MODELS FOR ESTIMATING FLOOD QUANTILES IN NEW HAMPSHIRE AND VERMONT1

We develop and compare three regression models for estimating flood quantiles at ungaged stream reaches in New Hampshire and Vermont. These models emerge from systematic analysis and validation of relations between flood magnitude and six candidate predictors reflecting basin size, topography, and climate and channel size at 36 gaging stations with record lengths exceeding 20 years. Of the candidate predictors, bank full width is most highly correlated with flood magnitude and the best prediction equation is based on width. Thus channel geometry is closely related to the current hydrologic regime in spite of geologically recent glaciation and apparently non-alluvial bank materials. We also develop models that use information obtainable from maps or GIS. The best of these uses drainage area and drainage-basin elevation as predictors, but it is substantially less precise than the width-based relation. A third relation using only drainage area as a predictor is even less precise but may be useful for some purposes. No other single predictors or combinations yielded useful predictions, although some had been included in previously-established models for the region. Model comparison included examination of residuals generated by regression using one-at-a-time suppression of data points and comparison with precision obtainable with gaging records of varying lengths.     

Trends of air pollution in the Fichtelgebirge Mountains, Bavaria

We analyzed 13 years of hourly measurements of SO₂, NO_x, and O₃, at forest ecosystem research sites in SE Germany. A quasi-continuous data record was obtained by combining data sets from two locations. Before interpreting trends in the combined data set, we analyzed if the change of location introduced a systematic bias. We employed autocorrelation functions, Hurst statistics, complexity analysis, and recurrence quantification and found that the partial data sets exhibited no indication of the presence of any bias. For SO₂, we also compared the data from the forest sites with data obtained in nearby cities and also found no indications for any systematic effects. Applying nonparametric trend statistics we found a significant decrease of the SO₂. Most of the observed decrease is due to the reductions of SO₂ emissions in eastern Germany, but reductions in western Germany and the Czech Republic also played important roles. For O₃, we observed a significant increase, the causes of which are unclear from our data alone. No trend was identified for NO_x.     

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L⁻¹), medium dose (amended at 100 μg U L⁻¹), and high dose (500 μg U L⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

推广工伤保险对我国生产事故统计的影响

我国安全生产统计工作所依托的行政手段还不能完全适应变化中的市场经济环境 ,政府安全生产管理不到位 ,监管不严 ,各类事故的少报、瞒报、不报现象相当普遍 ,极大地影响了伤亡事故统计的准确性。2 0 0 4年我国已实施新的《工伤保险条例》 ,笔者认为 ,会在一个较长的时期内对生产事故统计带来较明显的影响 ,使生产事故造成的伤亡人数统计变得更为全面和科学 ,这种影响必然会对原有统计偏差的修正 ,有利于今后加强和完善对安全生产的宏观决策和管理 ,会从根本上促进安全生产水平的提高。     

CHEMISTRY OF COALBED METHANE DISCHARGE WATER INTERACTING WITH SEMI‐ARID EPHEMERAL STREAM CHANNELS1

ABSTRACT: The objective of this study was to examine the chemistry of Coalbed Methane (CBM) discharge water reacting with semi‐arid ephemeral stream channels in the Powder River Basin, Wyoming. The study area consisted of two ephemeral streams: Burger Draw and Sue Draw. These streams are tributaries to the perennial Powder River. Samples were collected bimonthly from three CBM discharge points and seven channel locations in Burger Draw and Sue Draw. Samples were also collected bimonthly from the Powder River above and below the confluence of Burger Draw. Before sample collection, the pH and electrical conductivity (EC) were measured in the field. Samples were transported to the laboratory and analyzed for alkalinity, major cations, and anions. From the measurement of sodium (Na), calcium (Ca), and magnesium (Mg), practical sodium adsorption ratio (SARp) and true sodium adsorption ratio (SARt) were calculated. Results suggest pH and EC of CBM discharge water was 7.1 and 4.3 dS/m, respectively. The CBM discharge water consisted of higher concentrations of sodium and alkalinity compared to other components. The pH of CBM discharge water increased significantly (p = 0.000) in the downstream channel of Burger Draw from 7.1 to 8.84 before it joined with the Powder River. Dissolved calcium concentration of CBM discharge water decreased significantly (p = 0.000) in the downstream channel water. Subsequently, SARp increased approximately from 24 to 29. The SARt also increased significantly (p = 0.001) in the downstream channel water. For instance, SARt of CBM discharge water increased from 32.93 to 45.5 downstream channels after the confluence of Sue Draw with the Burger Draw. The only significant difference in water chemistry above and below the confluence of Burger Draw with the Powder River was pH, which increased from 8.36 to 8.52. The significant increase in SAR values of CBM discharge water in Burger Draw and Sue Draw tributaries suggest a careful monitoring of salinity and sodicity is needed if CBM discharge water is used for irrigation in semi‐arid environments. Results discussed in this study will be useful to downstream water users who depend on water for irrigation.