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.     

发展旅游对海岛环境的影响及应对策略研究

海岛作为一个独特的地理单元，旅游资源丰富，发展前景广阔，但在海岛旅游迅速发展的同时，海岛环境也受到极大的影响。而海岛又是环境敏感地区，生态环境脆弱，一旦破坏就难以恢复，所以重视海岛旅游出现的环境问题，加强对海岛环境的保护，促进海岛经济的可持续发展应引起广泛的关注和重视。     

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.     

地下水水质评价的多元线性回归分析模型研究

运用回归分析理论和方法,建立了一个基于多元线性回归分析法的地下水水质评价模型,并将该模型用于遵义市海龙坝地下水水质评价.结果表明,建立的模型较符合本研究区的实际情况.     

企业可持续发展评价指标体系的选定原则及构建框架

为了制定企业可持续发展的战略决策,须制定可持续发展的指标体系,并依据这一体系对数据和资料进行收集、整理和分析,从而确定可靠而有效的政策方针。文中论述了可持续发展指标体系的定义、选定标准、原则和可持续发展的评价指标体系,提出了压力-状态-响应框架模型以及不同层次的指标体系框架。该指标体系分为总体层、系统层、状态层、变量层和要素层五个等级。对于持续发展的表征指标及对目前发展的可持续性评估,还需要长时间和切合实际的探讨。     

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.     

The Water Fluxes of the Yellow River to the Sea in the Past 50 Years, in Response to Climate Change and Human Activities

Since the 1970s, the water fluxes to the sea of the Yellow River have declined significantly. Based on data of precipitation, air temperature, the measured and “natural” river flow, the water diversion and consumption, and the areas of erosion and sediment control measures over the drainage basin, water fluxes to the sea of the Yellow River are studied in relation with the influences of changing climate and human activities. The Yellow River basin can be divided into different water source areas; multiple regression indicates that the variation in precipitation over different water source areas has different effect on water fluxes to the sea. In the period between 1970 and 1997, averaged air temperature over the whole Yellow River increased by about 1.0°C, from 16.5°C to 17.5°C, a factor that is negatively correlated with the water yield of the Yellow River. Water diversion and consumption has sharply increased and resulted in a significant decline in the water fluxes to the sea. Since the 1960s, erosion and sediment control measures have been practiced over the drainage basin. This factor, to a lesser degree, is also responsible for the decrease in water fluxes to the sea. A multiple regression equation has been established to estimate the change in water fluxes to the sea caused by the changes in precipitation, air temperature, water diversion and consumption, erosion, and sediment control measures, indicating that the contribution of water diversion and consumption to the variation in annual water flux to the sea is 41.3%, that of precipitation is 40.8%, that of temperature is 11.4%, and that of erosion and sediment control measures is 6.5%.     

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.     

ACCURACY OF LAKE AND STREAM TEMPERATURES ESTIMATED FROM THERMAL INFRARED IMAGES1

Emitted thermal infrared radiation (TIR, λ= 8 to 14 μm) can be used to measure surface water temperatures (top approximately 100 μm). This study evaluates the accuracy of stream (50 to 500 m wide) and lake (300 to 5,000 m wide) radiant temperatures (15 to 22°C) derived from airborne (MASTER, 5 to 15 m) and satellite (ASTER 90 m, Landsat ETM+ 60 m) TIR images. Applied atmospheric compensations changed water temperatures by ?0.2 to +2.0°C. Atmospheric compensation depended primarily on atmospheric water vapor and temperature, sensor viewing geometry, and water temperature. Agreement between multiple TIR bands (MASTER ‐ 10 bands, ASTER ‐ 5 bands) provided an independent check on recovered temperatures. Compensations improved agreement between image and in situ surface temperatures (from 2.0 to 1.1°C average deviation); however, compensations did not improve agreement between river image temperatures and loggers installed at the stream bed (from 0.6 to 1.6°C average deviation). Analysis of field temperatures suggests that vertical thermal stratification may have caused a systematic difference between instream gage temperatures and corrected image temperatures. As a result, agreement between image temperatures and instream temperatures did not imply that accurate TIR temperatures were recovered. Based on these analyses, practical accuracies for corrected TIR lake and stream surface temperatures are around 1°C.