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.     

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.     

Effect of 450 MHz Microwave Modulated with 217 Hz on Human EEG in Rest

Summary This study focuses on discrimination of changes, produced by low-level microwave exposure in intensity and time variability of the human EEG at rest. The power spectral density (PSD) method and nonlinear scaling analysis of the length distribution of low variability periods (LDLVP) were selected for analysis of the EEG signal. During the study, 19 healthy volunteers were exposed to a microwave (450 MHz) of 217 Hz frequency on-off modulation. The field power density at the scalp was 0.16 mW/cm². The experimental protocol consisted of ten cycles of repetitive microwave exposure. Signals from frontal, temporal, parietal and occipital EEG channels on EEG theta, alpha and beta rhythms were analysed. Exposure to microwave causes average increase of EEG activity. LDLVP analysis discriminated significant effect in time variability for 2 subjects (11%). PSD method detected significant changes in intensity for 4 subjects (21%). The effect of low-level microwave exposure is stronger on EEG beta rhythm in temporal and parietal regions of the human brain.     

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.     

Estimating the Recreational-Use Value for Hiking in Bellenden Ker National Park, Australia

The recreational-use value of hiking in the Bellenden Ker National Park, Australia has been estimated using a zonal travel cost model. Multiple destination visitors have been accounted for by converting visitors’ own ordinal ranking of the various sites visited to numerical weights, using an expected-value approach. The value of hiking and camping in this national park was found to be $AUS 250,825 per year, or $AUS 144,45 per visitor per year, which is similar to findings from other studies valuing recreational benefits. The management of the park can use these estimates when considering the introduction of a system of user pays fees. In addition, they might be important when decisions need to be made about the allocation of resources for maintenance or upgrade of tracks and facilities.     

Life cycle energy impacts of automotive liftgate inner

This paper compares the life cycle energy use of a cast-aluminum, rear liftgate inner and a conventional, stamped steel liftgate inner used in a minivan. Using the best available aggregate life cycle inventory data and a simple spreadsheet-level analysis, energy comparisons were made at both the single-vehicle and vehicle-fleet levels. Since the product manufacture and use are distributed over long periods of time that, in a fleet, are not simple linear combinations of single product life cycles. Thus, it is all the products in use over a period of time, rather than a single product, that are more appropriate for the life cycle analysis. Using a set of consistent data, analyses also examine sensitivity to the level of analysis and the assumptions to determine the most favorable materials with respect to life cycle energy benefits.As expected, life cycle energy impacts of aluminum are lower than steel at a single-vehicle level – energy savings are determined to be 1.8 GJ/vehicle. Most energy savings occur at the vehicle operation phase due to improved fuel economy from lightweighting. The energy benefits are realized only very close to the average vehicle life of 14 years. With the incremental growth of the vehicle fleet, it takes longer – about 21 years – for aluminum to achieve life cycle equivalence with steel. The number of years aluminum needs to achieve equivalence with steel was found to be quite sensitive to aluminum manufacturing energy and fuel economy. As the steel industry races to compete with other materials for automotive lightweighting, a systems approach, instead of part-to-part comparison, is more appropriate in the determination of viability of aluminum substitution from an energy perspective.     

PREDICTING FECAL COLIFORM BACTERIA LEVELS IN THE CHARLES RIVER,MASSACHUSETTS, USA1

In Massachusetts, the Charles River Watershed Association conducts a regular water quality monitoring and public notification program in the Charles River Basin during the recreational season to inform users of the river's health. This program has relied on laboratory analyses of river samples for fecal coliform bacteria levels, however, results are not available until at least 24 hours after sampling. To avoid the need for laboratory analyses, ordinary least squares (OLS) and logistic regression models were developed to predict fecal coliform bacteria concentrations and the probabilities of exceeding the Massachusetts secondary contact recreation standard for bacteria based on meteorological conditions and streamflow. The OLS models resulted in adjusted R²s ranging from 50 to 60 percent. An uncertainty analysis reveals that of the total variability of fecal coliform bacteria concentrations, 45 percent is explained by the OLS regression model, 15 percent is explained by both measurement and space sampling error, and 40 percent is explained by time sampling error. Higher accuracy in future bacteria forecasting models would likely result from reductions in laboratory measurement errors and improved sampling designs.     

DEVELOPMENT OF EMPIRICAL,GEOGRAPHICALLY SPECIFIC WATER QUALITY CRITERIA: A CONDITIONAL PROBABILITY ANALYSIS APPROACH1

The need for scientifically defensible water quality standards for nonpoint source pollution control continues to be a pressing environmental issue. The probability of impact at differing levels of nonpoint source pollution was determined using the biological response of instream organisms empirically obtained from a statistical survey. A conditional probability analysis was used to calculate a biological threshold of impact as a function of the likelihood of exceeding a given value of pollution metric for a specified geographic area. Uncertainty and natural variability were inherently incorporated into the analysis through the use of data from a probabilistic survey. Data from wadable streams in the mid‐Atlantic area of the U.S. were used to demonstrate the approach. Benthic macroinvertebrate community index values (EPT taxa richness) were used to identify impacted stream communities. Percent fines in substrate (silt/clay fraction, > 0.06 mm) were used as a surrogate indicator for sedimentation. Thresholds of impact due to sedimentation were identified by three different techniques, and were in the range of 12 to 15 percent fines. These values were consistent with existing literature from laboratory and field studies on the impact of sediments on aquatic life in freshwater streams. All results were different from values determined from current regulatory guidance. Finally, it was illustrated how these thresholds could be used to develop criterion for protection of aquatic life in streams.