Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada

Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO₄, and NO₃ concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

长江流域等重污染行业经济和污染贡献率剖析

应用"污染贡献率"这一指标,分析了长江、黄河、珠江和松花江流域COD和氨氮排放的重污染行业以及地区分布,指出了各流域COD和氨氮排放的控制重点.同时分析了各流域重污染行业的经济贡献率,最后结合行业的污染贡献率和经济贡献率以及行业在地区所占的比例,提出了几点重要的结论.     

对室内装饰装修材料检测中甲醛分析方法的研究

目前室内装饰装修材料中甲醛含量的检测有六个类别,分析方法不统一,且没有一定的质量控制措施.文章对分析方法进行了改进,并且研究用水中的甲醛标样来对检测过程进行质量控制,结果较好.     

一次监测值用于水质评价的研究

以2003年长江和淮河水系为例,通过计算各个评价项目的单月监测值分别与季均值和年均值的相对误差及其分布,以及水质类别相同的断面比例,认为对于旬报、月报短期水质评价,采用一次监测的数据评价水质是可靠的;对于季报和年报中、长期水质评价,采用一次监测数据评价的可靠程度较差,应采用2次或2次以上的监测数据平均值进行评价。     

地表水环境质量定性评价

针对目前缺乏统一的地表水环境质量定性评价准则的现状,根据我国主要水体的污染程度,提出了断面、河流、水系水质定性评价方法。     

辽河流域浑河沈阳段地表水重点控制有机污染物的筛选

采用美国环保局工业环境实验室提出的化学物质的“潜在危害指数法”,对辽河流域浑河沈阳段地表水和底质中检出的有机污染物的潜在危害进行了排序,参考国内外有毒化学品优先控制名单的筛选原则和方法,结合本流域的实际情况,制定出重点控制有机污染物的评分标准,提出辽河流域浑河沈阳段重点控制有机污染物名单。考虑到个别有机污染物在水中的浓度很低,但在底质中相对含量较高,所以将底质的检测结果也纳入评分标准。     

The Chemistry of Soils, Rocks and Plant Bioindicators in Three Ecosystems of the Holy Cross Mountains, Poland

In June of 2000, biogeochemical study was carried out in three ecosystems of the Holy Cross Mountains (south-central Poland). This paper presents element concentrations and stable sulfur (and in one site lead) isotope ratios in rocks, detailed soil profiles, and plant bioindicators including epiphytic lichen Hypogymnia physodes (L.) Nyl., mosses (Pleurozium schreberi (Brid.) Mitt., Hypnum cupressiforme Hedw. S. Str., Hylocomium splendens (Hedw.) B.S.G.), Scots pine (Pinus sylvestris L.), common birch (Betula pendula Roth.), aspen (Populus tremula L.) and English oak (Quercus robur L.). Chemical analyses were performed with ICP-AES and AAS methods in the accredited laboratory (Central Chemical Laboratory of the Polish Geological Institute in Warsaw). The principal objective of this study was to compare the chemical composition of rocks, soils and selected plant bioindicators between investigation sites using the same methods of sample collection, preparation and analyses. The results of this study have shown that there is a high variability in concentrations of elements in plant bioindicators from the same sites that can not be explained only by soil properties or anthropogenic influence. This conclusion indicates that for biomonitoring purposes (especially with vascular plants) we cannot neglect individual features of the species examined.     

Application of a systemic approach to the study of pollution of the Tinto and Odiel rivers (Spain)

The province of Huelva in the SW of Spain presents high environmental contrasts: together with the great abundance of natural spaces, it shows the impacts of historical natural resources exploitation processes. In the Ria of Huelva, the effluents of the chemical industries must be added to the contaminating inputs of the Tinto and Odiel rivers, coming from the acid drainage of the mines located in the Iberian Pyrite Belt. This forced the Environmental Agency (AMA) to elaborate in 1987 an Effluent Remediation Plan in order to negate unacceptable environmental impacts. The application of a grey box systemic analysis to the AMD pollution, undergone by the Tinto and Odiel rivers has allowed to set a conclusive explanation of the sampling results observed for a period of 11 years, thus making available an overall view of the polluting process and, above all, an explanation of its partial aspects.