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.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Determination of organophosphorus pesticides and related compounds in water samples by membrane extraction and gas chromatography

A membrane extraction-gas chromatography method was developed fordetermination of organophosphorus pesticides and related compounds including methamidophos, DDVP, dimethoate, methyl parathion, parathion, thiophosphoric acid trimethyl ester, and thiophosphoramidic acid dimethyl ester in water samples. In thismethod, surface-modified acetic cellulose membranes were used to extract the target analytes in water samples, the extracted analytes were back-extracted into a small amount of methanol, andgas chromatography with pulsed flame photometric detector (GC-PFPD) was used to determine the concentrations of targetanalytes in the extracts. The recoveries obtained for thetarget analytes spiked into the water samples ranged from 66to 94%. The method detection limit for each target analyte was 0.05 g L^-1. The method developed in this study had shown the advantages of being cheap, simple, fast, and reliable. It had been used successfully to determine the concentrations of target analytes in river water samples.     

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.     

地表水样品自然沉降时间对总磷测定结果的影响分析

地表水中总磷含量高低是评定水质优劣的一项重要指标,分析数据表明丰水期中总磷主要来源于泥沙中吸附的有机磷和无机磷,而溶解态磷含量较少;水样中总磷含量随着自然沉降时间的延长而逐渐降低.因此样品采集回来后样品的自然沉降时间是影响地表水中总磷测定结果的一个主要原因之一.     

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.