我国水业市场化模式

本文就我国水业的特许经营模式和市场监管等问题进行了重点讨论。     

Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).     

Effectiveness of resistivity monitoring for interpreting temporal changes in landfill properties

It is always possible for impermeable layers to exist in landfills. When they do, the properties of the solution at the exit of the leachate-collection system might not accurately reflect the overall properties of the landfill. This study examines whether resistivity monitoring is effective for determining the influence of impermeable layers on the leachate. The test cell used in this study was filled with waste made up mainly of incinerator ash and shredded incombustible material. Three lines of resistivity sensors were laid in the uppermost layer of the fill. A resistivity profile was recorded periodically from each of these lines. The water-table level and leachate properties were measured concurrently. Leachate conductivity was mainly controlled by concentrations of the main ions, and it correlated inversely to variations in resistivity. Temporal changes in the resistivity of the fills are an excellent means of assessing the leaching in fills. Monitoring the properties of leachate, combined with resistivity profiling, is extremely useful for interpreting the temporal changes of properties in landfills containing impermeable layers.     

稠油污水生化性处理技术研究

为了探讨稠油污水能否使用生物法处理,以生活污水和农药厂生化池原菌种经过诱导驯化,分别培养了可以在稠油污水中生长的好氧菌种革兰氏阴性菌G-1和厌氧菌种革兰氏阴性菌G-2.以G-2和G-1对稠油污水进行顺序处理,可使其BOD5/CODCr达到0.26;采用SBR法对新疆稠油污水放大处理试验的结果：COD降至150 mg/L以下,各项指标达到GB8978-1998二级排放标准.     

污染物排放相关指标计算方法的研究

针对传统的污染排放数据指标计算方法存在的问题,提出污染物排放指标应根据排污强度和经济指标确定的新思路,同时提出污染物排放指标数据的快速测算模型设计.建议通过环境监测数据或物料衡算数据确定每个排污单位的平均排污强度,作为计算机处理的参数,再由该排污单位申报每月的经济指标(产量或产值),输入计算机计算其产污量、排污量和去除量.实施计算机管理的关键是选取适当的数据计算模型.新思路应该能够规范计算程序,建立污染源动态数据库,对排污数据实行有效的统计分析.     

大气环境影响评价工作分级要求要点

根据大气环境影响评价工作的分级要求,提出了针对性的工作要点,以满足大气环境评价工作的需要.     

Non-native Species <Emphasis Type="Italic">DO</Emphasis> Threaten the Natural Environment!

Sagoff [Journal of Agricultural and Environmental Ethics 18 (2005), 215–236] argues, against growing empirical evidence, that major environmental impacts of non-native species are unproven. However, many such impacts, including extinctions of both island and continental species, have both been demonstrated and judged by the public to be harmful. Although more public attention has been focused on non-native animals than non-native plants, the latter more often cause ecosystem-wide impacts. Increased regulation of introduction of non-native species is, therefore, warranted, and, contra Sagoff’s assertions, invasion biologists have recently developed methods that greatly aid prediction of which introduced species will harm the environment and thus enable more efficient regulation. The fact that introduced species may increase local biodiversity in certain instances has not been shown to result in desired changes in ecosystem function. In other locales, they decrease biodiversity, as they do globally.     

Impact of Human Activities on Carbon Dioxide (CO<Subscript>2</Subscript>) Emissions: A Statistical Analysis

Summary The balance of evidence suggests a perceptible human influence on global ecosystems. Human activities are affecting the global ecosystem, some directly and some indirectly. If researchers could clarify the extent to which specific human activities affect global ecosystems, they would be in a much better position to suggest strategies for mitigating against the worst disturbances. Sophisticated statistical analysis can help in interpreting the influence of specific human activities on global ecosystems more carefully. This study aims at identifying significant or influential human activities (i.e. factors) on CO₂ emissions using statistical analyses. The study was conducted for two cases: (i) developed countries and (ii) developing countries. In developed countries, this study identified three influential human activities for CO₂ emissions: (i) combustion of fossil fuels, (ii) population pressure on natural and terrestrial ecosystems, and (iii) land use change. In developing countries, the significant human activities causing an upsurge of CO₂ emissions are: (i) combustion of fossil fuels, (ii) terrestrial ecosystem strength and (iii) land use change. Among these factors, combustion of fossil fuels is the most influential human activity for CO₂ emissions both in developed and developing countries. Regression analysis based on the factor scores indicated that combustion of fossil fuels has significant positive influence on CO₂ emissions in both developed and developing countries. Terrestrial ecosystem strength has a significant negative influence on CO₂ emissions. Land use change and CO₂ emissions are positively related, although regression analysis showed that the influence of land use change on CO₂ emissions was still insignificant. It is anticipated, from the findings of this study, that CO₂ emissions can be reduced by reducing fossil-fuel consumption and switching to alternative energy sources, preserving exiting forests, planting trees on abandoned and degraded forest lands, or by planting trees by social/agroforestry on agricultural lands.     

不同环境体系下锂离子电池热失控特性实验研究

针对锂离子电池热失控引发的航空运输安全问题,自主设计并搭建锂离子电池热失控灾害演化及危险性分析实验平台。在敞开和密封环境体系下,对电加热触发荷电量(State of Charge,SOC)为0%、50%和100%的18650型锂离子电池热失控规律进行了实验研究。观察单体锂离子电池在敞开和密封体系中的热失控现象,并记录单体锂离子电池热失控时间、温度峰值及相应的温度变化。数据结果显示,相比敞开体系,密封体系有效的延缓了锂离子电池发生热失控的时间,并降低了锂离子热失控时释放的能量,为锂离子电池的航空运输安全性研究提供了理论依据和工程技术参考。     

西部复杂性地貌地区消防规划评估与建设研究 ——以凉山州区域为例

城市消防规划作为城市消防安全体系建设的重要依据,是助力城市现代化进程、推动城市综合安全智慧网络形成的重要基石。通过对凉山州各地貌地区消防现状存在问题的分析,结合凉山州的实际情况及全州建设发展多种形式综合性消防应急救援队伍的需要,提出了能满足全州消防安全需求且能够有效指导城市消防建设的相应对策。