郑州市土壤与绿色植物中汞的分布特征

汞污染具有生物积累性,因而得到社会广泛关注。研究监测和评估了郑州市城区土壤和绿色植物叶片中汞浓度、分布、污染水平等。研究发现郑州市主城区土壤总汞浓度为0. 150～0. 958 mg/kg,平均浓度为0. 448 mg/kg;郑州市主城区绿色植物叶片总汞浓度为0. 017～0. 249 mg/kg,平均浓度为0. 107 mg/kg;土壤和叶片中汞浓度按功能区排序为交通枢纽区工业区商业区行政区高教区住宅区。采用地累积指数法对郑州市80个土壤样品的汞污染水平进行评估,结果显示60%受到轻度污染,35%受到偏中度污染,5%受到中度污染。研究较为全面地分析了土壤汞污染的现状及浓度,为郑州市土壤汞污染防治提供参考。     

工作场所职业工效相关因素及其管理初探

为了探讨工作场所职业工效管理的基本策略和方法，在概述职业工效相关因素类别、相互关联及评价方法等基础上，提出基于职业病危害防治要求、风险管理理念和管理体系建设模式的职业工效不良因素干预管理的初步策略及实施要点。研究结果表明:工作场所职业工效相关因素包括个体特征、工艺设备及其布局、工作系统设计、作业环境、作业管理和社会心理因素等，不同因素间存在直接或间接的相互影响，并最终影响到微观层面劳动者职业活动的工效特点及宏观层面工作场所整体的职业工效特征；实施有效的职业工效管理，在于科学辨识、评估不良职业工效因素的基础上，进一步在职业病危害预防控制的不同阶段采取合理可行的管理方法进行干预，并持续改进。     

Simple Model of Dissolved Oxygen Consumption in a Bay within High Organic Loading: An Applied Remediation Tool

San Vicente Bay is a coastal shallow embayment in Central Chile with multiple uses, one of which is receiving wastewater from industrial fisheries, steel mill effluents, and domestic sewage. A simulation model was developed and applied to dissolved oxygen consumption by organic residues released into this embayment. Three compartments were established as function of: depth, circulation and outfall location. The model compartments had different volumes, and their oxygen saturation value was used as baseline. The parameters: (a) BOD₅ of the industrial and urban effluents, (b) oxygen demand by organic sediments, (c) respiration, (d) photosynthesis and (e) re-aeration were included in the model. Iteration results of the model showed severe alterations in Compartment 1, with a decrease of 65% in the oxygen below saturation. Compartment 2 showed a small decline (10%) and compartment 3 did not show apparent changes in oxygen values. Measures recommended for remediation were to decrease the BOD₅ loading by 30% in the affected sector. Iteration of the model for 200 h following recommendations derived from the preceding results produced an increase in saturation of 60% (5 ml O₂ L⁻¹), which suggested an improvement of the environmental conditions.     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

Importance of public information and perception for managing recreational activities in the Peel-Harvey estuary, Western Australia

Surveys of water recreational activities were conducted in the Peel-Harvey estuary. Channels used by recreationists to gain information about water quality, the perception of water quality and resulting behaviour were investigated. This study showed that personal perception, local knowledge and history, absence of warnings and residency were major factors contributing to risk perception and behaviour in this recreational community. Management strategies should take this information into account to achieve maximal outcomes.     

Influence of urbanization and tourist activities on the water quality of the Potrero de los Funes River (San Luis – Argentina)

A study of the water quality of the Potrero de los Funes River (San Luis – Argentina) was carried out in order to evaluate the possible effect of the anthropogenic activities on the river developed in the homonymous town. Samples were collected during the period March 2000–November 2005 at three selected sampling sites (RP₁, RP₂ and RP₃). Different physicochemical and bacteriological parameters (turbidity, pH, conductivity, suspended solids, alkalinity, potassium, sodium, calcium, magnesium, chlorides, nitrates, phosphates, sulphates, chemical oxygen demand (COD), 5-day biological oxygen demand (BOD₅), dissolved oxygen, total coliforms, Escherichia coli and total heterotrophic bacteria) were analysed according to the Standard Method for the Examination of Water and Wastewater. When comparing the values of total coliforms, E. coli, total heterotrophic bacteria, COD, BOD₅ and phosphates from the zone without anthropogenic influence (RP₁) and the urban zones (RP₂ and RP₃) an important variation in the parameters was observed. These results indicate that the urban activity produces a serious and negative effect on the water quality, thus constituting a sanitary risk and may have a major impact on the trophic status of the Potrero de los Funes dam. As case study, we report on the use of General Quality Index (GQI) to evaluate spatial and seasonal changes in the water quality of Potrero de los Funes River. Results revealed a significant degradation of the water quality at RP₂ and RP₃.     

Reflections on the use of Bayesian belief networks for adaptive management

A broad range of tools are available for integrated water resource management (IWRM). In the EU research project NeWater, a hypothesis exists that IWRM cannot be realised unless current management regimes undergo a transition toward adaptive management (AM). This includes a structured process of learning, dealing with complexity, uncertainty etc. We assume that it is no longer enough for managers and tool researchers to understand the complexity and uncertainty of the outer natural system-the environment. It is just as important, to understand what goes on in the complex and uncertain participatory processes between the water managers, different stakeholders, authorities and researchers when a specific tool and process is used for environmental management. The paper revisits a case study carried out 2001-2004 where the tool Bayesian networks (BNs) was tested for groundwater management with full stakeholder involvement. With the participation of two researchers (the authors) and two water managers previously involved in the case study, a qualitative interview was prepared and carried out in June 2006. The aim of this ex-post evaluation was to capture and explore the water managers' experience with Bayesian belief networks when used for integrated and adaptive water management and provide a narrative approach for tool enhancement.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

ARSENIC CONSUMPTION AND HEALTH RISK PERCEPTIONS IN A RURAL WESTERN U.S. AREA1

ABSTRACT: Churchill County, Nevada, has approximately 23,000 residents, among whom an estimated 13,500 relied on private wells for water supply in 2002. This study examined exposure to arsenic in water supplies among residents with private domestic wells and factors related to householder choice to consume tap water. It compared opinions and concerns about water quality with consumption habits and observed concentrations from tap water samples. The results from 351 households indicated that a majority (75 percent) of respondents consumed tap water and that a minority (38 percent) applied treatment. Approximately 66 percent of those who consumed tap water were exposed to concentrations of arsenic that exceeded 10 ppb. Water consumption was related to application of treatment. Among 98 respondents who were not at all concerned about the health effects of aqueous arsenic, 59 (60 percent) reported consuming tap water with concentrations of arsenic exceeding 10 ppb. Conversely, among 86 respondents who were highly concerned about arsenic, 33 (37 percent) consumed tap water with concentrations of arsenic exceeding 10 ppb. Results from a national sampling effort showed that 620 of 5,304 private wells sampled (11.7 percent) had arsenic concentrations above 10 ppb. The paradox of awareness of arsenic in water supplies coupled with consumption of aqueous arsenic in concentrations greater than 10 ppb may be common in other parts of the nation. Enhanced educational efforts, especially related to tap water sampling and explanations of efficacy of available treatment, may be useful means of reducing exposure through private water supplies.     

Risk-evaluation of Hi-tech Enterprise in the Process of Approaching Global Market

In the high technology industry, small and medium sized technology enterprises (SMSTEs) play a pivotal role in advancing the whole industry. To achieve sustainable development, they need to extend their scope of business activities beyond a national view and exploit international market actively to meet international competitions that increase quickly in the form of allocating resources within the scope of the world. However, the SMSTEs are also facing risks associated with themselves during the process of exploiting international market owing to their own restrictions, so what they should do is to consider risk evaluations in exploiting the international market.