顶空气相色谱法测定食品中甜蜜素含量

采用顶空气相色谱法测定食品中甜蜜素含量,探讨了气液相平衡条件及色谱条件的选择,实验结果表明甜蜜素的标准溶液在0.1-0.4μg/l范围内具有良好的线性关系,回收率为87.5%-101.8%,相对标准偏差为2.6%.     

对实验室污染问题的思考和建议

分析了目前实验室存在的污染种类及危害,阐明实验室是一种不容忽视的污染源,且污染种类复杂,毒害较大.提出实验室污染防治措施.     

浅谈高职高专院校中的语文素质教育

一方面阐释语文素质教育在高职高专教育中的重要性及其作用;另一方面阐释了作为一名大学语文教师应如何在教学中体现"素质教育",培养出具有较高综合素质的职业技术人才.     

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.     

Analysis of Roadside Inhalable Particulate Matter (PM10) in Major Korean Cities

A data analysis of three major Korean cities was conducted to assess roadside inhalable particulate matter 10 μm or smaller in aerodynamic diameter (PM₁₀), including temporal and meteorological variations, over a recent period of 4 to 6 years. The yearly roadside PM₁₀ concentrations presented a well-defined increasing trend or no trend depending on the roadside monitoring station. Most mean values exceeded or approximated the Korean standard of 70 μg/m³ per year for PM₁₀. A representative roadside diurnal trend was characterized by a distinct morning maximum. In most cases, the Sunday roadside concentrations were similar to or somewhat lower than the weekday concentrations, and the PM₁₀ concentrations presented a well-defined seasonal variation, with the maximum concentration in March. The monthly maximum concentrations observed in March were most likely attributable to Asian dust storms. In two metropolitan cities (Seoul and Busan), the frequency of days with roadside PM₁₀ concentrations exceeding the standard of 150μg/m³ per 24 h was much lower for the roadside monitoring stations than for the residential monitoring station, whereas in the third city (Daegu), this result was reversed. Interestingly, the average maximum concentrations observed for the roadside sites in Seoul and Busan during March were higher than those for the residential sites, suggesting that the roadside concentrations responded more to the dust storms than the residential areas. The relationship between the pollutant concentrations and five important meteorological parameters (solar radiation, wind speed, air temperature, relative humidity, and precipitation) showed that the number and type of meteorological variables included in the equations varied according to the monitoring station or season. Finally, the current results confirmed that attention should be given to the PM₁₀ exposure of residents living near roadways.     

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.     

Indicators for sustainable energy development in Lithuania

This article summarizes some of the results from the application of the indicators for sustainable energy development (ISED) tool for analyzing Lithuania's energy sector, in terms of trends, setting energy policy goals and monitoring progress towards these goals. This experience illustrates the potential applicability of the ISED methodology for energy policy development in economies in transition, using Lithuania as an example. The article presents a summary of the results achieved and conclusions arrived at from the analysis of six priority areas in the context of the research project coordinated by the International Atomic Energy Agency, and provides recommendations for the development of sustainable energy policy using the ISED approach.     

BIOECONOMIC ANALYSIS OF SELECTED CONSERVATION PRACTICES ON SOIL EROSION AND FRESHWATER FISHERIES1

ABSTRACT: Farmers can generate environmental benefits (improved water quality and fisheries and wildlife habitat), but they may not be able to quantify them. Furthermore, farmers may reduce their incomes from managing lands to produce these positive externalities but receive little monetary compensation in return. This study simulated the relationship between agricultural practices, water quality, fish responses to suspended sediment and farm income within two small watersheds, one of a cool water stream and one of a warm water stream. Using the Agricultural Drainage and Pesticide Transport (ADAPT) model, this study related best management practices (BMPs) to calculated instream suspended sediment concentrations by estimating sediment delivery, runoff, base flow, and streambank erosion to quantify the effects of suspended sediment exposure on fish communities. By implementing selected BMPs in each watershed, annual net farm income declined $18,000 to $28,000 (1 to 3 percent) from previous levels. “Lethal” fish events from suspended sediments in the cool water watershed decreased by 60 percent as conservation tillage and riparian buffers increased. Despite reducing suspended sediments by 25 percent, BMPs in the warm water watershed did not reduce the negative response of the fisheries. Differences in responses (physical and biological) between watersheds highlight potential gains in economic efficiency by targeting BMPs or by offering performance based “green payments.”     

SUMMER LOW FLOWS IN NEW ENGLAND DURING THE 20TH CENTURY1

ABSTRACT: High springtime river flows came earlier by one to two weeks in large parts of northern New England during the 20th Century. In this study it was hypothesized that late spring/early summer recessional flows and late summer/early fall low flows could also be occurring earlier. This could result in a longer period of low flow recession and a decrease in the magnitude of low flows. To test this hypothesis, variations over time in the magnitude and timing of low flows were analyzed. To help understand the relation between low flows and climatic variables in New England, low flows were correlated with air temperatures and precipitation. Analysis of data from 23 rural, unregulated rivers across New England indicated little evidence of consistent changes in the timing or magnitude of late summer/early fall low flows during the 20th Century. The interannual variability in the timing and magnitude of the low flows in northern New England was explained much more by the interannual variability in precipitation than by the interannual variability of air temperatures. The highest correlation between the magnitude of the low flows and air temperatures was with May through November temperatures (r =?0.37, p= 0.0017), while the highest correlation with precipitation was with July through August precipitation (r = 0.67, p > 0.0001).