Strontium-90 in Canada goose eggshells and reed canary grass from the Columbia River,Washington

Strontium-90 (⁹⁰SR) released to the ground near the N Reactor at the U.S. Department of Energy's Hanford Site enters the Columbia River through shoreline seeps. The ⁹⁰Sr is then potentially available for uptake by plants and animals. The life history and foraging behavior of nesting Canada geese is such that female geese could ingest ⁹⁰Sr while foraging on shoreline plants. Radichemical analyses showed that goose eggshells taken from an island, downstream from the N Reactor, contained more ⁹⁰Sr than did eggshells collected from other downstream islands. Reed canary grass samples taken from shoreline areas immediately downstream from the N Reactor contained higher concentrations of ⁹⁰Sr than samples from other downstream areas. All goose eggshells did not contain enhanced levels of ⁹⁰Sr, and all reed canary grass samples did not contain enhanced levels of ⁹⁰Sr, but a relationship exists between the releases of ⁹⁰Sr to the Columbia River and the enhanced levels of ⁹⁰Sr in some of the environmental samples analyzed.Pacific Northwest Laboratory is operated by Battelle Memorial Institute for the U.S. Department of Energy under contract DE-ACO6-76RLO 1830.     

Evaluation of spatial and temporal variations in marine sediments quality using multivariate statistical techniques

Spatial and temporal variations of sediment quality in Matanzas Bay (Cuba) were studied by determining a total of 12 variables (Zn, Cu, Pb, As, Ni, Co, Al, Fe, Mn, V, CO₃ ^2?, and total hydrocarbons (THC). Surface sediments were collected, annually, at eight stations during 2005–2008. Multivariate statistical techniques, such as principal component (PCA), cluster (CA), and lineal discriminant (LDA) analyses were applied for identification of the most significant variables influencing the environmental quality of sediments. Heavy metals (Zn, Cu, Pb, V, and As) and THC were the most significant species contributing to sediment quality variations during the sampling period. Concentrations of V and As were determined in sediments of this ecosystem for the first time. The variation of sediment environmental quality with the sampling period and the differentiation of samples in three groups along the bay were obtained. The usefulness of the multivariate statistical techniques employed for the environmental interpretation of a limited dataset was confirmed.     

Prediction of stream fish assemblages from land use characteristics: implications for cost-effective design of monitoring programmes

Increasing human impact on stream ecosystems has resulted in a growing need for tools helping managers to develop conservations strategies, and environmental monitoring is crucial for this development. This paper describes the development of models predicting the presence of fish assemblages in lowland streams using solely cost-effective GIS-derived land use variables. Three hundred thirty-five stream sites were separated into two groups based on size. Within each group, fish abundance data and cluster analysis were used to determine the composition of fish assemblages. The occurrence of assemblages was predicted using a dataset containing land use variables at three spatial scales (50 m riparian corridor, 500 m riparian corridor and the entire catchment) supplemented by a dataset on in-stream variables. The overall classification success varied between 66.1–81.1% and was only marginally better when using in-stream variables than when applying only GIS variables. Also, the prediction power of a model combining GIS and in-stream variables was only slightly better than prediction based solely on GIS variables. The possibility of obtaining precise predictions without using costly in-stream variables offers great potential in the design of monitoring programmes as the distribution of monitoring sites along a gradient in ecological quality can be done at a low cost.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

人体接触挥发性有机化合物的生物标志物

生物标志物是阐明接触与健康损害之间关系的工具。综述了３７ 篇文献,简单论述了挥发性有机化合物的各种生物标志物,这些生物标志物包括暴露生物标志物,效应生物标志物和易感性生物标志物。还简述了各种生物标志物之间的相互关系,并介绍了各种生物标志物的研究现状和发展前景,以及应用它们来评价ＶＯＣｓ对人体健康的影响。     

Fuzzy Logic Model to Estimate Seasonal Pseudo Steady State Chlorophyll-A Concentrations in Reservoirs

A fuzzy logic model is developed to estimate pseudo steady state chlorophyll-a concentrations in a very large and deep dam reservoir, namely Keban Dam Reservoir, which is also highly spatial and temporal variable. The estimation power of the developed fuzzy logic model was tested by comparing its performance with that from the classical multiple regression model. The data include chlorophyll-a concentrations in Keban lake as a response variable, as well as several water quality variables such as PO₄ phosphorus, NO₃ nitrogen, alkalinity, suspended solids concentration, pH, water temperature, electrical conductivity, dissolved oxygen concentration and Secchi depth as independent environmental variables. Because of the complex nature of the studied water body, as well as non-significant functional relationships among the water quality variables to the chlorophyll-a concentration, an initial analysis is conducted to select the most important variables that can be used in estimating the chlorophyll-a concentrations within the studied water body. Following the outcomes from this initial analysis, the fuzzy logic model is developed to estimate the chlorophyll-a concentrations and the advantages of this new model is demonstrated in model fitting over the traditional multiple regression method.     

Effects of geomorphology, habitat, and spatial location on fish assemblages in a watershed in Ohio, USA

In this paper, we evaluate relationships between in-stream habitat, water chemistry, spatial distribution within a predominantly agricultural Midwestern watershed and geomorphic features and fish assemblage attributes and abundances. Our specific objectives were to: (1) identify and quantify key environmental variables at reach and system wide (watershed) scales; and (2) evaluate the relative influence of those environmental factors in structuring and explaining fish assemblage attributes at reach scales to help prioritize stream monitoring efforts and better incorporate all factors that influence aquatic biology in watershed management programs. The original combined data set consisted of 31 variables measured at 32 sites, which was reduced to 9 variables through correlation and linear regression analysis: stream order, percent wooded riparian zone, drainage area, in-stream cover quality, substrate quality, gradient, cross-sectional area, width of the flood prone area, and average substrate size. Canonical correspondence analysis (CCA) and variance partitioning were used to relate environmental variables to fish species abundance and assemblage attributes. Fish assemblages and abundances were explained best by stream size, gradient, substrate size and quality, and percent wooded riparian zone. Further data are needed to investigate why water chemistry variables had insignificant relationships with IBI scores. Results suggest that more quantifiable variables and consideration of spatial location of a stream reach within a watershed system should be standard data incorporated into stream monitoring programs to identify impairments that, while biologically limiting, are not fully captured or elucidated using current bioassessment methods.     

Has central environmental protection inspection improved air quality? Evidence from 291 Chinese cities

In recent years, central environmental protection inspection (CEPI) has been a major policy innovation in the field of Chinese environmental governance. Based on panel data on the daily air quality of Chinese cities, this paper mainly uses a difference-in-differences (DID) approach to conduct an empirical analysis of the relationship between CEPI and the air quality governance performance of Chinese local governments. There are large differences in the impact of CEPI on different air quality indicators. Controlling for a series of variables, we found that CEPI significantly reduced the air quality index (AQI) and concentrations of pollutants including PM_2.5, PM₁₀, SO₂ and NO₂ and that it significantly increased the concentration of O₃; however, it had no significant effect on the concentration of CO. Furthermore, we complemented the quantitative analyses with qualitative evidence gathered from an in-depth interview. Based on the qualitative evidence collected, CEPI indeed plays a role in improving the environmental protection performance of regular environmental governance. Notably, CEPI achieved better and sustainable results in improving air quality through the underlying mechanism of promoting regular governance by campaign-oriented governance in the internal hierarchical system. This article not only provides a marginal empirical contribution by providing new quantitative evidence but also helps reveal the underlying mechanism of promoting regular governance.     

Environmental quality assessment combining sediment metal levels, biomarkers and macrobenthic communities: application to the óbidos coastal lagoon (Portugal)

Macroinvertebrate benthic communities are one of the key biological components considered for the assessment of benthic integrity in the context of the Water Framework Directive (WFD). However, under moderate contamination scenarios, the assessment of macrobenthic alterations at community level alone could be insufficient to discriminate the environmental quality of coastal and transitional waters. Keeping this in view, sediment quality of moderately contaminated sites in a coastal lagoon (óbidos lagoon, Portugal) was assessed by the combination of sediment metal levels, Carcinus maenas biomarkers (accumulated metals and oxidative stress responses) and macrobenthic communities. Two sites were selected in confined inner branches (BS and BB) and a third one in the middle lagoon (ML). The site BB presented slightly higher levels of metals in sediment but biological variables calculated for macrobenthic data were not significantly different between sites. The biotic index M-AMBI that is being applied to assess environmental quality of transitional waters in the scope of the WFD pointed either to high (site ML) or good quality status (BS and BB) in the selected sites. However, crabs from BB site presented significantly higher levels of Ni in hepatopancreas than those from ML and macrobenthic community structure was significantly different between BB and ML. Additionally, spatial differences were obtained for oxidative stress parameters suggesting that BB site presented stressors for crabs (higher GST and lower GSH_t at BB site). Factor analysis (PCA) integrating sediment contamination, biomarkers in crabs and macrobenthic data also distinguished BB site as the most environmentally disturbed. On the other hand, at ML site, some macrobenthic variables (equitability and polychaetes’ diversity) were found to be enhanced by current environmental conditions, suggesting the existence of a better sediment quality. Current results pointed to the usefulness of integrating macrobenthic community alterations with responses at organism level (bioaccumulation and biochemical endpoints) in order to increase the accuracy of environmental quality assessment in lagoon systems. Moreover, the application of different statistical methods was also found to be recommendable.     

Simulation of PM<Subscript>10</Subscript> concentration patterns for a 2010 traffic scenario in Bologna,Italy

Three state of the art traffic–emission–dispersion models dealing with particulate matter have been tested and validated over the Bologna metropolitan area with 2001 data and a future scenario has been developed in order to estimate expected PM concentrations in 2010. The modelling system is composed by a traffic model (VISUM) evaluating vehicle fluxes as a function of mobility demand and road network in the area, an emission model (Trefic) estimating pollutants emitted in atmosphere as a function of vehicle fluxes amount and composition and of environmental conditions and a dispersion model (ADMS) evaluating PM concentrations on the area, given the meteorological variables. The three models compose a cascade sequence and results of the previous one feed the next one. PM concentrations computed by the model suite for the town of Bologna, in northern Italy, for the reference period (January 2001) have been compared with air quality stations measurements suggesting the modelling system being especially suitable for evaluating traffic induced PM. Qualitative and quantitative changes in the circulating vehicle fleet have been supposed in order to obtain a realistic scenario for year 2010. Forecasted concentrations have been then compared with limits fixed by current EU legislation for particulate matter.     

动态因子分析在环境监测数据综合处理中的应用

动态因子分析(DFA)作为降维度的多元统计方法,被设计用于时间序列分析,以揭示多元变量中解释变量与共同趋势对响应变量的影响程度。相较传统多元统计方法,DFA显性考虑时间因素,并量化影响响应变量的潜在因素。该方法可以忽略内在理化过程,具有良好的模拟效果,且在国外已广泛应用于地表水及地下水生态环境、空气污染等领域,但在国内尚未被应用。DFA在自身完善、应用范围、信息挖掘、数据预处理、预测分析、空间分析方面仍有巨大发展前景。     

灰色理论及其模型在北京典型城市区域声环境研究中的应用

以北京市某典型区域作为研究对象,在收集大量相关资料与实测历史噪声数据的基础上,对研究区域内的声环境质量影响因素进行灰色关联度分析,并运用灰色理论建立GM（1,1）模型进行预测。结果表明,影响城市区域声环境质量因素从大到小的排序依次为：机动车辆﹥常住人口数量﹥平均车流量﹥地区生产总值﹥城市道路桥梁﹥基础设施投资﹥治理噪声环保投资;以研究区域内噪声污染实测历史数据建立的GM（1,1）模型精度符合要求标准,根据GM（1,1）模型预测北京市“十二五”期间声环境质量达标且有轻微下降趋势。     

Atmospheric influences on water quality: a simulation of nutrient loading for the Pearl River Basin, USA

Knowledge of water quality conditions is essential in assessing the health of riverine ecosystems. The goal of this study is to determine the degree to which water quality variables are related to precipitation and air temperature conditions for a segment of the Pearl River Basin near Bogalusa, LA, USA. The AQUATOX ecological fate simulation model is used to estimate daily total nitrogen, total phosphorus, and dissolved oxygen concentrations over a 2-year period. Daily modeled output for each variable was calibrated against reliably measured data to assess the accuracy. Observed data were plotted against simulated data for controlled and perturbed models for validation, and stepwise multiple regression analysis was used to quantify the relationships between the water quality and meteorological variables. Results suggest that daily dissolved oxygen is significantly negatively correlated to concurrent daily mean air temperature with a total explained variance of 0.679 (p?<?0.01), and monthly dissolved oxygen is significantly negatively correlated to monthly mean air temperature with a total explained variance of 0.567 (p?<?0.01). Total mean monthly phosphorus concentration is significantly positively related to the previous month's precipitation with a total explained variance of 0.302 (p?<?0.01). These relationships suggest that atmospheric conditions have a strong influence on water quality in the Pearl Basin. Therefore, environmental planners should expect that future climatic changes are likely to alter water quality.     

Assessment of water quality of Rawal Lake by long-time monitoring

Water quality of rivers, natural lakes, and reservoirs in developing countries is being degraded because of the contaminated inflows. There is a serious need for appropriate water quality monitoring for future planning and management of clean water resources. Quality of water in Rawal Lake Pakistan has been investigated in this paper. Flows from the upstream of Rawal Lake and its surrounding villages are highly polluted. Lake water quality parameters like pH, turbidity, alkalinity, calcium, nitrite, sulfate, biological oxygen dissolved, dissolved oxygen, chloride, total dissolved solids (TDS), and coliforms were investigated. Samples of water from different locations of Korang River were collected and tested. Most of the data was collected by field sampling and field visits. However, long-term information was taken from different departments. Statistical parameters (standard deviation, maximum, minimum, mean, mode, kurtosis, skew, and Euclidean distance) of variables were determined. A distinct parameter based on the difference of the maximum value the variable and maximum allowable value of that variable defined by World Health Organization was used for analysis. Grouping and clustering of elements was made on the basis of this parameter. Trend of increasing or decreasing of values of variables over a long time was also taken into account for grouping the variables. It was concluded that the concentration of seven contaminants was higher as compared to the permissible limits under environmental standards. These variables need immediate attention. The environmentally bad conditions of Rawal Lake can only be rectified by appropriate lake environmental supervision, watershed management, and implementation of environmental legislation.     

太湖蓝藻水华暴发程度年度预测

近年来,尽管太湖主要水质指标有所改善,但蓝藻水华暴发的频次和面积并未明显减少.为了探讨太湖蓝藻水华暴发的环境驱动因子,统计了2012—2020年历年4—10月预警期间的太湖蓝藻水华发生规模与频次,结合同步浮标自动监测数据和实验室分析数据,构建了蓝藻水华预测模型.以太湖蓝藻水华综合指数(Ic)表征蓝藻水华强度,并通过Ic...     

How does trade development affect environmental performance? New assessment from partially linear additive panel analysis

Assessing the linkage between trade development and environmental quality has recently attracted increasing attention because of the rapid advancement of trade globalization along with the severe degradation of the environment. However, neglecting the possible nonlinear relationship between the variables, the existing studies mainly use linear models to explore the trade-environment linkage. To fill this gap, this paper introduces a novel partially linear additive panel model that highlights nonlinear and heterogeneous features to investigate the direct and indirect influences of trade development on environmental performance over the period 2005–2017 in China. The results show that trade has an inverse “U-shaped” direct effect on the environment. In contrast, trade development can indirectly improve environmental quality through economic growth. Nonlinear marginal analysis demonstrates that such an impact not only presents individual differences but also embodies the trait of temporal dynamics. Empirical results further reveal the importance of our model, which can automatically identify the variable nexus and thus reduce the setting error of the parametric models. Model evaluation also confirms the superiority of the used model over existing parametric and nonparametric models. The partially linear additive panel model provides a new evaluation method for environmental impact regarding trade development, and can be applied to other fields where an assessment of the effect of socio-economic factors on the environment is needed.     

A systems approach to modeling Community-Based Environmental Monitoring: a case of participatory water quality monitoring in rural Mexico

Community-Based Environmental Monitoring (CBM) is a social practice that makes a valuable contribution to environmental management and construction of active societies for sustainable future. However, its documentation and analysis show deficiencies that hinder contrast and comparison of processes and effects. Based on systems approach, this article presents a model of CBM to orient assessment of programs, with heuristic or practical goals. In a focal level, the model comprises three components, the social subject, the object of monitoring, and the means of action, and five processes, data management, social learning, assimilation/decision making, direct action, and linking. Emergent properties were also identified in the focal and suprafocal levels considering community self-organization, response capacity, and autonomy for environmental management. The model was applied to the assessment of a CBM program of water quality implemented in rural areas in Mexico. Attributes and variables (indicators) for components, processes, and emergent properties were selected to measure changes that emerged since the program implementation. The assessment of the first 3 years (2010–2012) detected changes that indicated movement towards the expected results, but it revealed also the need to adjust the intervention strategy and procedures. Components and processes of the model reflected relevant aspects of the CBM in real world. The component called means of action as a key element to transit “from the data to the action.” The CBM model offered a conceptual framework with advantages to understand CBM as a socioecological event and to strengthen its implementation under different conditions and contexts.     

Is Globalization Detrimental to CO<Subscript>2</Subscript> Emissions in Japan? New Threshold Analysis

Using annual data from 1970 to 2014, this paper examines the effects of globalization on CO₂ emissions in Japan while accounting for economic growth and energy consumption as potential determinants of carbon emissions. The structural breaks and asymmetries arising due to policy shifts require attention, and hence, an asymmetric threshold version of the ARDL model is utilized. The results show the presence of threshold asymmetric cointegration between variables. Threshold-based positive and negative shocks arising from globalization increase carbon emissions, while the impact of the latter is more profound. Energy consumption (economic growth) also has a significant positive effect on carbon emissions. Globalization, economic growth, and energy consumption significantly increase carbon emissions in the short run. We suggest that policy makers in Japan consider globalization and energy consumption as policy tools in formulating their policies regarding protecting sustainable environmental quality in the long run. Otherwise, the Japanese economy may continue to face environmental consequences such as undesirable climate change and massive warming at the micro and macro levels as a result of potential shocks arising from globalization and energy consumption.     

Multivariate Analysis of Interactions Between Phytoplankton Biomass and Environmental Variables in Taihu Lake, China

Phytoplankton variation in large shallow eutrophic lakes is characterized by high spatial and temporal heterogenity. Understanding the pattern of phytoplankton variation and the relationships between it and environmental variables can contribute to eutrophic lakes management. In this study Taihu Lake, one of the largest eutrophic fresh water lake in China, was taken as study area. The water body of Taihu Lake was divided into five regions viz. Wuli bay (WB), Meilian Bay (MB), West Taihu Lake (WTL), Main Body of Taihu Lake (MBTL) and East Taihu Lake (ETL). Concentrations of chlorophyll-a and the related environmental variables were determined in each region in the period 2000–2003. Factor analysis and multivariate analysis were applied to evaluate the interactions between phytoplankton variation and environmental variables. Results showed that the highest average concentrations of TN, TP and Chl-a were observed in WB, followed in a descending order by MB and WTL, and the lowest concentrations of TN, TP and Chl-a were observed in MBTL and ETL. Chl-a and TP concentrations in most regions (except ETL) declined during the study period. It suggested that to some extent the lake was recovering from eutrophication. However, persistent ascending of TN and NH₄–N in all five regions indicated the deteriorating of water quality in the study period. Results of multivariate showed that the relationships between phytoplankton biomass and environmental variables varied among regions. TP illustrated itself a controlling role on phytoplankton in WB, MB, WTL and MBTL according to the significant positive relations to phytoplankton biomass in these regions. Nitrogen could be identified as a limiting factor to phytoplankton biomass in ETL in view of the positive correlations between TN and phytoplankton and between NH₄–N and phytoplankton. Spatial variation of interactions between phytoplankton and environmental parameters suggested proper eutrophication control measures were needed to restore ecological system in each region of Taihu Lake.     

Optimizing the Monitoring Strategy of Wastewater Treatment Plants by Multiobjective Neural Networks Approach

This paper applies artificial neural network (ANN) to model the observed effluent quality data. The ANN’s structure, involving the number of hidden layer and node and their connection, is determined endogenously by resorting to the compromise of data cost minimization and prediction accuracy maximization. To obtain the best compromise possible, the model introduces an aspiration variable (μ) that represents the level of aspiration achieved in one objective and the conjugate of μ, (1 − μ), represents level of aspiration achieved in the other objective. Because a massive amount of calculation is required, the model applies genetic algorithm (GA) for its computational flexibility and capability to ensure global solution. Feasibility and practicality of the model is tested by a case study with a set of 150 daily observations on 17 operational variables and quality parameters at an industrial wastewater treatment plant (WTP) located in southern Taiwan. Of these 17 variables open to selection, only 6 variables, wastewater flow rate (Q), CN⁻, SS, MLSS, pH and COD are selected by the model to achieve the maximum accuracy of prediction, 0.94, with a total cost of 5,950 NT$. By constraining budget availability, the variables included in the model are reduced in number, causing a concomitant reduction in prediction accuracy, that is, by varying μ (aspiration level of accuracy), a trajectory of cost and accuracy is generated. The calculation results a cost of 3,650 NT$ and 0.54 accuracy for the case with variables including flow rate, SCN⁻ and SS in equalization basin; aeration tank hydraulic retention time (HRT) and percentage of returned sludge (R%) are selected for building the prediction model when the importance of required budget is equal to the accuracy of prediction model. In addition, when required cost for building ANN model is between 3,650 NT$ and 3,900 NT$, the marginal return of budget input is highest in the entire range of calculation.