Long-term trends and short-term variability of water quality in Skive Fjord, Denmark – nutrient load and mussels are the primary pressures and drivers that influence water quality

Nineteen years of monitoring data from the eutrophic Skive Fjord, Denmark were examined for linkages to external pressures and drivers, including nutrient inputs, meteorology and stocks of blue mussels. Linkages were examined by: 1) time-series analysis to document effects of nutrient reduction programs, 2) Pearson Rank correlations, 3) multivariate statistical analysis (PLS) to identify water quality variables with high predictability and their linkages to pressures, and 4) regression analysis to quantify relationships between pressures and water quality. Freshwater input, nitrogen load and phosphorus load showed decreasing trends through the period 1984–2002. The load reductions were only partially translated into trends in water quality: phosphorus decreased in most seasons, while total nitrogen decreased during winter and spring only. Phosphorus concentration had the highest predictability (explained by seasonal temperature variation) followed by transparency, silicate, tot-N, chlorophyll-a, primary productivity, phytoplankton diversity and phytoplankton turnover. The variation in pressures other than nutrient input confounded the relations between loads and water quality. High biomass of mussels led to reduced chlorophyll-a and increased transparency, while short-term variability in water column mixing led to changes in chlorophyll-a due to nutrient entrainment and coupling to benthic mussels.     

Comparison of Numerical Street Dispersion Models with Results from Wind Tunnel and Field Measurements

Numerical dispersion models developed and validated in different European countries were applied to data sets from wind tunnel and field measurements. The comparison includes the Danish Operational Street Pollution Model (OSPM) and the microscale flow and dispersion model MISKAM. The latter is recommended for application in built-up areas in the draft of the new German guideline VDI 3782/8. In a first step the models were applied to simplified street configurations. Different parameters as length and height of adjacent buildings and the angle of the incoming flow were varied. The results were compared to recent wind tunnel measurements. In a second step the models were applied to two extensively investigated field data sets from Jagtvej, Copenhagen and G ttinger Straße, Hannover. Intensified and more transparent and accessible validation procedures would be helpful for the thorough user.     

Statistical analyses of coastal water quality for a port and harbour region in India

A long-term study of temperature, pH, turbidity, suspended solid, salinity, dissolved oxygen, biochemical oxygen demand and ammonia nitrogen has been performed in a port and harbour region in India for four years from December 1996 to November 2000. Marine water quality results showed no regular trend. The mean monthly values of temperature, pH, turbidity, suspended solid, salinity, dissolved oxygen, biochemical oxygen demand and ammonia nitrogen were in the range of 22.64 ± 0.4 to 29.05 ± 1.37 °C; 7.65 ± 0.04 to 7.81 ± 0.13; 28.8 ± 14.7 to 64.2 ± 32.0 NTU; 283.5 ± 81.8 to 356.0 ± 159.7 mg/L; 29.78 ± 7.18 to 29.78 ± 1.04 ppt; 4.67 ± 0.50 to 6.01 ± 1.02 mg/L; 5.41 ± 1.92 to 7.56 ± 2.1 mg/L; and 0.25 ± 0.07 to 0.63 ± 0.49 mg/L, respectively. The results of correlation analysis showed that biochemical oxygen demand (BOD) was inversely correlated dissolved oxygen (DO) and poorly correlated with all other parameters. Turbidity and suspended solid were moderately correlated with each other while salinity was moderately correlated with other water quality parameters. In factor analysis, four factors were drawn out of the eight variables, which represented 74% of the variance of the original data. Factor I was related to suspended solid and turbidity. Factor II represented mainly temperature and DO showing inverse relation between these two. Factor III implied the degree of pollution at any monitoring station. Factor IV included pH and salinity. It could be concluded that the factor model represented almost all the variables.     

Assessing alpine plant vulnerability to climate change: a modeling perspective

The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Numerical integration of chemical ODE problems arising in air pollution models

The numerical treatment of a regional air pollution model (such models are, as a rule, described mathematically by systems of partial differential equations) leads to the solution of very large computational problems. The chemical submodel of an air pollution model is normally the most timeconsuming part of the computational work. The application of appropriate discretization and splitting procedures reduces the chemical submodel to a large number of relatively small ODE systems (one such system per gridpoint). In the process of searching for efficient numerical algorithms for the chemical submodels one can carry out experiments by using only one such ODE system in order to facilitate the work. This approach has been used in connection with a particular chemical scheme, the condensed CBM IV scheme, which is used in several large air pollution models. Six integration algorithms have been tested on a set of typical scenarios (consisting of different starting concentrations and/or of different values of the emissions). The advantages and the disadvantages of the algorithms tested are discussed. The final decision about the most efficient algorithm, among the algorithms tested, should be made after a second series of experiments. The coupling of the chemical process with the transport of air pollution (on, at least, a twodimensional domain) together with the application of highspeed computers has to be studied in the second series of experiments, which will be performed in a subsequent paper.     

水上事故溢油运动轨迹与环境归宿预测模型的研究进展

以事故溢油在水面上的运动轨迹和环境归宿为研究对象,重点对溢油水下分散过程、岸边黏附及受水流冲刷下油膜质量衰减过程、水体悬浮物对石油黏附/吸附量的预测模型研究成果,以及目前日益受到关注的河流溢油模型的研究进展进行归纳总结。对比分析了不同预测模型结构功能差异和适用性问题,为不同环境条件下溢油事故的后预警、后预测提供模型选择依据和技术支持。最后就溢油模型尚存的一些问题及未来发展的方向进行了探讨。     

A Stream Network Model for Integrated Watershed Modeling

We describe a flexible, computationally efficient stream network model, which forms the core of a simulation framework that spatially integrates the contributions from point and nonpoint sources in a watershed. The model uses the map and stream topology information in the US Environmental Protection Agency’s Reach File 3 to generate a spatially explicit network of stream reaches. Water and materials are routed through the stream network to the watershed outlet, and the routing process accounts for transit times and for possible nutrient losses in streams. This model can be applied wherever Reach File maps or maps from the newer National Hydrography Dataset are available, and it can be combined with models of other watershed processes to create a complete watershed simulation system. We present an application of the stream network model to two watersheds of different sizes in the Patuxent River watershed of Maryland, USA. Simulated predictions of streamflow and nitrate concentrations are either very good or good according to standards developed for evaluating the widely used Hydrologic Simulation Program – Fortran (HSPF) watershed model.     

Evaluating response surface designs for uncertainty analysis and prescriptive applications of a large-scale water quality model

Environmental models are often too large and cumbersome for effective use in regulatory decision making or in the characterization of uncertainty. This paper describes and compares four response surfaces that could complement a large-scale water quality model, the U.S. National Water Pollution Control Assessment Model (NWPCAM), in simulation and regulatory decision support applications. Results show that a physically based reduced-form model that exploits the mathematical structure of the underlying water quality model is a better predictor of policy-relevant outputs than the polynomial expansions that are frequently used in response surface studies.     

自动监测设备比对监测合格率统计方法的探讨

参照污染源达标率统计方法,得出自动监测设备比对监测的合格率统计方法,并具体介绍了企业单个项目合格率统计方法、区域单个项目合格率统计方法和区域综合合格率统计方法。     

1981～1997年《地震学刊》的发文、引文统计分析

从发文数量,发文地区分布,核心作用,论文作者合作度,引文数量,普赖斯指数,引文期刊等方面,分析了《地震学刊》吸收和传递信息的能力。测定了７种地震期刊为江苏省地震局图书馆的核心期刊。