Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

Assessment of the Water Quality of the River Arno in the Area of Florence, Italy

The quality of the waters collected from R. Arno was examined in the period September 1988 to December 1989. A first campaign in September/October 1988, during a period of low water, gives a general picture of pollution conditions along the river from the source to the mouth. the river appears to be heavily polluted immediately downstream of Florence and in the area of the textile industry.

In the second campaign, through the whole year 1989, particular attention has been given to the Florence area; the most significant results, compared with those from a previous investigation carried out in 1971, show only a small reduction of the pollution load, due to the shortage and inadequacy of wastewater depuration. Some considerations are reported on pollution drop with full spate.     

Long Term Trends in Concentration of Major Pollutants (SO<Subscript>2</Subscript>, CO,NO, NO<Subscript>2</Subscript>, O<Subscript>3</Subscript> and PM<Subscript>10</Subscript>) in Prague – Czech Republic (Analysis of Data Between 1992 and 2005)

To assess the effect of changes in traffic density and fuels used for heating at the beginning of the 1990s, 1992–2005 monthly averages of PM₁₀, SO₂, NO₂, NO, CO and O₃ from Prague, the Czech capital, were analyzed together with long term trends in emissions of major pollutants, fuel consumption and number of vehicles registered in Prague. The data from all monitoring stations were retrieved from the database of the state automated monitoring system. Correlation coefficients between ambient monthly averaged temperature and all pollutants of concern showed distinct seasonal trends. The results showed that while SO₂ and to some extent also CO concentrations dropped namely in the first half of the analyzed period (1992–1997) as a result decreased fossil fuel consumption for local heating, the behaviour of other pollutant concentrations followed a different pattern. PM₁₀ concentrations decreased during the beginning of the 1990s but showed a sign of increase after 2000. Concentrations of ozone and NO₂ did not reveal any significant change throughout the whole studied period. It can be concluded that during the studied period traditional urban sources of pollution, such as coal and oil combustion, lost their importance but were simultaneously substituted by pollutants from automotive transport (namely PM and NO₂) making the problem of air quality even worse.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

基于高程的环境库兹涅茨曲线实证分析

本文利用GIS的空间分析技术。以高程带为取样单元。研究在高程带上三种主要的大气污染物与经济发展之间的定量关系。以重庆市为例,验证环境库兹涅茨在高程上是否存在。研究结果发现。污染物浓度随高程的增加呈非单调下降的趋势。人均GDP随高程的增加先增大后减小。在高程上。污染物浓度与经济发展之间的关系和两者在时间序列和国别（或地区）序列上环境库兹涅茨曲线研究的结论相似。其中。TSP和NOx分别与人均GDP之间呈较稳定的呈“N”形和饲“U”形关系。受人口密度和高程影响较大；而SO2与人均GDP之间关系不稳定。     

Atmospheric pollutants monitoring by analysis of epiphytic lichens

The Canoparmelia texana epiphytic lichenized fungi was used to monitor atmospheric pollution in the S?o Paulo metropolitan region, SP, Brazil. The cluster analysis applied to the element concentration values confirmed the site groups of different levels of pollution due to industrial and vehicular emissions. In the distribution maps of element concentrations, higher concentrations of Ba and Mn were observed in the vicinity of industries and of a petrochemical complex. The highest concentration of Co found in lichens from the S?o Miguel Paulista site is due to the emissions from a metallurgical processing plant that produces this element. For Br and Zn, the highest concentrations could be associated both to vehicular and industrial emissions. Exploratory analyses revealed that the accumulation of toxic elements in C. texana may be of use in evaluating the human risk of cardiopulmonary mortality due to prolonged exposure to ambient levels of air pollution.     

长江干流江苏段水质评价

利用长江干流江苏段16个断面的水质监测资料，采用最差因子评价法，对长江干流江苏段的16个断面水质状况进行了分析评价。结果表明，长江干流江苏段的水质以Ⅱ、Ⅲ类为主，夏半年的水质优于冬半年，部分断面水质较差，各断面的主要污染物以氨氮为主。