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.     

基于复杂系统建模的水管理政策研究进展

基于Agent的建模方法（ABSS）通过自下而上的方式，考察系统中主体的不同状态和行为特征、主体与环境的作用、主体之间的作用，来表征系统的宏观特征，是进行复杂社会环境系统分析和政策研究的重要手段，在水资源、水环境管理系统中得到了有效的应用。本文在大量文献调研的基础上，讨论了ABSS建模方法的基本原理、主要特征、系统构成、分类方法和开发工具等特征，总结了其供水系统发展、水资源分配和流域水资源管理、农业土地和水资源利用、居民用水行为、农业污染控制及人类活动的水环境影响等方面的应用，分析了其在研究内容、研究方法、研究结果等方面的发展趋势，讨论了利用该方法研究我国水资源管理和水污染控制政策的必要性和重要性。     

Effects of Coastal Lighting on Foraging Behaviorof Beach Mice

Abstract:  Introduction of artificial light into wildlife habitat represents a rapidly expanding form of human encroachment, particularly in coastal systems. Light pollution alters the behavior of sea turtles during nesting; therefore, long-wavelength lights—low-pressure sodium vapor and bug lights—that minimize impacts on turtles are required for beach lighting in Florida (U.S.A.). We investigated the effects of these two kinds of lights on the foraging behavior of Santa Rosa beach mice (  Peromyscus polionotus leucocephalus ). We compared patch use and giving-up densities of mice for experimental food patches established along a gradient of artificial light in the field. Mice exploited fewer food patches near both types of artificial light than in areas with little light and harvested fewer seeds within patches near bug lights. Our results show that artificial light affects the behavior of terrestrial species in coastal areas and that light pollution deserves greater consideration in conservation planning.     

日照市畜牧业生产对环境的污染及其防治措施研究

畜禽粪便中大量有机污染物污染着人们赖以生存的土壤和水体，粪尿分解产生的大量有害气体污染了大气。本文结合日照市畜牧业生产的实际，对日照市畜牧业生产对环境的污染现状进行了分析，找出了日照市畜牧业生产对环境污染产生的主要原因和存在问题，提出畜牧业生产对环境污染的防治对策。     

张家界国家森林公园地表水污染综合分析

随着旅游业的快速发展,张家界国家森林公园水环境保护、水污染治理及水资源利用问题已成为张家界旅游可持续发展中突出的问题.文章利用大量监测数据,对公园地表水污染状况进行模糊数学法综合评价,进行污染特征与污染规律分析,从而提出严格控制排污,科学规划水资源、严格控制景区客流量等对策及建议,以期为张家界国家森林公园水环境保护及张家界旅游业的持续健康发展提供决策参考.     

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.     

基于GIS的南京市典型蔬菜基地土壤重金属污染现状与评价

对南京市八卦洲蔬菜基地土壤中的铅、铬、铜和镉进行测定分析,利用不同的评价标准来评价其环境质量状况,同时借助GIS软件研究了污染指数的空间分布状况,并解析了其重金属污染的来源.结果表明,以自然背景值为评价标准,则蔬菜地土壤中的重金属都超过污染指标,其中镉为首要污染因子;以国标二级为评价标准,则除镉以外的三种重金属的单项污染指数值全都小于1,但其综合污染指数迭1.50,总体上属轻污染状况.南京化工因区、南京长江二桥和各种农业生产活动等可能是主要污染源.     

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