江苏省太湖流域水生态健康评估的初步实践及展望

阐述了水生态健康的内涵与意义,从江苏省率先在太湖流域开展水生态环境功能分区管理的顶层设计,构建以水生态健康指标为核心的水生态健康评估技术体系,地方对照水生态环境功能区划的水生态分级管控目标开展的应用与实践结果等3个方面,回顾了江苏省太湖流域水生态健康评估工作的主要进展,提出了完善水生态健康评估技术体系和推进流域水生态健康评估工作的建议。     

基于EFDC的长江常州段污水排江浓度场数值模拟

长江感潮河段水流与污染排放引起的浓度场复杂多变,基于EFDC(Environmental Fluid Dynamic Code)模型,采用正交曲线网格拟合自然河道边界,建立了长江常州段的水动力和水质模型。采用现场同步实测资料,与计算结果比对,证明该模型在水动力和水质两个方面都与实测数据吻合较好,满足了实际工程的需要;同时由于长江水流运动较快,一阶降解动力学已经满足了化学需氧量(COD)、氨氮(NH3-N)和总磷(TP)浓度计算要求,可以不考虑它们复杂的生化反应过程。     

遥感技术在水生态环境管理的应用与前景

随着遥感数据源的不断丰富,遥感技术不断提高,可以解决越来越多的水环境问题。指出了当前水生态环境管理方面的主要需求,结合目前遥感技术的发展,对国内外的水环境遥感研究进展进行综述。以湖泊富营养化监测与评估、核电站温排水遥感监测及城市黑臭水体遥感监测为案例,具体阐述遥感在水环境管理中的应用方法及成效。未来水生态环境管理发展趋势将以水污染防治为主向水污染防治和水生态修复与保护并重发展。基于此趋势,提出遥感在水生态修复的应用潜力,利于更多地方部门积极有效应用遥感技术,解决水生态环境问题。     

水处理中微生物絮凝剂产生菌的选育及应用

综述了微生物絮凝剂产生菌筛选和培育方面的研究进展,介绍了微生物絮凝剂在给水和饮用水、乳化液的油水分离、污水处理等领域的应用,以及廉价培养基的探索实践。提出针对影响微生物絮凝剂产生菌生长代谢的环境条件开展深入研究,同时寻找或设计廉价培养基,降低生产成本,推动其工业化应用。     

水中藻类对连续流动法测定总氮结果的影响

以天津市河道、水库为研究对象,在藻类增殖期采用连续流动法与碱性过硫酸钾消解法对水体中总氮进行比对监测,同时分析水中藻类分类和藻细胞密度。试验表明:虽然两种方法测定总氮的结果精密度基本相同,但二者之间的系统误差存在显著差异,连续流动法较碱性过硫酸钾消解法的测定结果低5.4%。两种方法测定总氮结果的相对偏差与水体中藻细胞密度呈正相关性,当水体中藻细胞密度﹥2.41×108L-1时,对连续流动法测定总氮的结果产生显著影响,相对偏差超过标准规范要求。     

太原汾河景区跨桥断面水体污染的时空变化模式研究

选取太原汾河景区跨桥断面8个监测点,在2012年3月—2013年10月期间对河流8项水质参数进行监测,并结合派生的水体综合污染指数及主成分分析方法分析和评价景区水污染时空变化特征。结果表明,景区水质污染变化时空差异明显,上游污染相对较小,下游污染较重;春季溶解氧和p H值变化幅度最大,夏季除总氮和氨氮外,其他各污染物均有显著变化特征,秋季则以氨氮、总氮和总磷变化最为显著。主成分分析结果显示,虽然各监测点水体污染的关键影响因子不同,但总磷是太原市河流水体污染的共同解释因子。     

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.     

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