二氧化氯对有机染料脱色效果的研究

本文对二氧化氯二两种直接染料和两种活性染料脱色效果的影响因素－ClO2的投加量、染料的初始浓度、pH值、温度以及反应时间等进行了研究。结果表明,在适当的条件下,二氧化氯对这几种有机染料均具有很好的脱色效果。     

蒽醌染料中间体溴氨酸降解酶的特性

从污染地分离筛选出的菌株BX26对蒽醌染料中间体溴氨酸有显著的降解脱色作用,降解过程受降解酶的控制,试验结果表明,降解酶为溴氨酸诱导的胞外酶,该酶在温度高于50℃处理后失活,盐度对该酶失活有影响,盐度高于1%会显著降低该酶活力,酶对溴氨酸的催化脱色要有氧参加,氮气气氛中酶活受抑制。     

1—硝基芘对斜生栅藻的毒性研究

酿要用评价化学品对藻类毒性的标准实验方法,研究了１－硝基芘对斜生栅藻生长的影响,得到了１－ＮＰ抑制斜生栅藻生长的ＥＣ５０（９６ｈ）为０．１８２４ｍｇ．１＾－１,实验结果还表明,１－ＮＰ对藻生长的抑制作用随时间的延长而增加,抑制物性表现为特久且强度大,抑制机理为不可逆性抑制。     

环境气体标准样品量值的计算及不确定度分析

依据《气体分析校准气体混合物的制备重量法》（1SO6142—2001）和《气体分析气体标准样品组成的测定和校验比较法》（ISO6143—2001）,阐述了环境气体标准样品不同定值方法的量值计算及不确定度来源,并比较了同一气体标准样品采用不同定值方法得到的不同量值结果及不确定度：     

Effects of crude oil residuals on soil chemical properties in oil sites, Momoge Wetland, China

Crude oil exploration and production has been the largest anthropogenic factor contributing to the degradation of Momoge Wetland, China. To study the effects of crude oil on wetland soils, we examined the total petroleum hydrocarbon (TPH), total organic carbon (TOC), total nitrogen (TN), and total phosphorus (TP), as well as pH and electricity conductivity (EC) from oil sites and uncontaminated areas in the Momoge Wetland. All contaminated areas had significantly higher (p < 0.05) contents of TPH and TOC, but significantly lower (p < 0.05) TN contents than those of the uncontaminated areas. Contaminated sites also exhibited significantly higher (p < 0.05) pH values, C/N and C/P ratios. For TP contents and EC, no significant changes were detected. The level of soil contamination and impact of oil residuals on soil quality greatly depended on the length of time the oil well was in production. Oil residuals had caused some major changes in the soils’ chemical properties in the Momoge Wetland.     

Estimation of the temporal and spatial distribution of dust concentration over China by combining PM10 and conventional meteorological observations

In this paper, we will present a simple algorithm to estimate the temporal and spatial distribution of dust mass concentration by combining PM10 and conventional meteorological observations. The efficiency of the algorithm has been demonstrated by applying it to analyze the dust source, transport, and dissipation of the dust storm which occurred in the west region of Pa-tan-chi-lin Desert at 0200 BST 27 March, 2004.     

Determination of heavy metals and metals levels in five fish species from I??kl? Dam Lake and Karaca?ren Dam Lake (Turkey)

The concentrations of heavy metals and metals (Zn, Pb, Bi, Cd, Ni, Co, Fe, Mn, Mg, Cu, Cr, Ca, Sr, Na, Li, K) were measured in muscle of five species Cyprinus carpio (from I??kl? dam), Scardinius erythrophthalmus (from I??kl? dam), Tinca tinca (from I??kl? dam), C. carpio (from Karaca?ren dam), Carassius carassius (from Karaca?ren dam) caught from I??kl? and Karaca?ren. The highest metal was Na (466.95 μg/g) in C. carassius, while the lowest levels were Fe (0.37 μg/g) and Cu (0.37 μg/g) in C. carpio from I??kl? dam. The mean concentrations μg/g d.w. some of heavy metals in muscle of C. carpio (from I??kl? dam), S. erythrophthalmus (from I??kl? dam), T. tinca (from I??kl? dam), C. carpio (from Karaca?ren dam), C. carassius (from Karaca?ren dam) were as follows: Cd 2.00-2.10-1.95-2.06-2.27, Zn 4.36-2.64-13.13-13.33-24.47, Pb 1.65-1.24-1.90-2.37-2.41, Co 2.46-2.37-2.48-2.58-2.80, Mg 138.51-154.35-218.59-204.58-202.16, Fe 0.37-2.62-3.17-3.01-12.33, respectively.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.