High-performance permanent magnets

 High-performance permanent magnets (pms) are based on compounds with outstanding intrinsic magnetic properties as well as on optimized microstructures and alloy compositions. The most powerful pm materials at present are RE–TM intermetallic alloys which derive their exceptional magnetic properties from the favourable combination of rare earth metals (RE=Nd, Pr, Sm) with transition metals (TM=Fe, Co), in particular magnets based on (Nd,Pr)₂Fe₁₄B and Sm₂(Co,Cu,Fe,Zr)₁₇. Their development during the last 20 years has involved a dramatic improvement in their performance by a factor of >15 compared with conventional ferrite pms therefore contributing positively to the ever-increasing demand for pms in many (including new) application fields, to the extent that RE–TM pms now account for nearly half of the worldwide market. This review article first gives a brief introduction to the basics of ferromagnetism to confer an insight into the variety of (permanent) magnets, their manufacture and application fields. We then examine the rather complex relationship between the microstructure and the magnetic properties for the two highest-performance and most promising pm materials mentioned. By using numerical micromagnetic simulations on the basis of the Finite Element technique the correlation can be quantitatively predicted, thus providing a powerful tool for the further development of optimized high-performance pms.     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

A Recourse‐Based Interval Fuzzy Programming Model for Point‐Nonpoint Source Effluent Trading under Uncertainty

In this study, a recourse‐based interval fuzzy programming (RIFP) model is developed for tackling uncertainties expressed as fuzzy, interval, and/or probabilistic forms in an effluent trading program. It can incorporate preregulated water‐pollution control policies directly into its optimization process, such that an effective linkage between environmental regulations and economic implications (i.e., penalties) caused by improper policies due to uncertainty existence can be provided. The RIFP model is applied to point‐nonpoint source effluent trading of the Xiangxi River in China. The efficiency of trading efforts between water quality improvement and net system benefit under different degrees of satisfying discharge limits is analyzed. The results are able to help support (1) formulation of water‐pollution control strategies under various economic objectives and system‐reliability constraints, (2) selection of the desired effluent trading pattern for point and nonpoint sources, and (3) generation of tradeoffs among system benefit, satisfaction degree, and pollutant mitigation under multiple uncertainties. Compared with the traditional regulatory approaches, the results demonstrate that the water‐pollution control program can be performed more cost‐effectively through trading than nontrading.     

Analyzing the Impacts of Dams on Riparian Ecosystems: A Review of Research Strategies and Their Relevance to the Snake River Through Hells Canyon

River damming provides a dominant human impact on river environments worldwide, and while local impacts of reservoir flooding are immediate, subsequent ecological impacts downstream can be extensive. In this article, we assess seven research strategies for analyzing the impacts of dams and river flow regulation on riparian ecosystems. These include spatial comparisons of (1) upstream versus downstream reaches, (2) progressive downstream patterns, or (3) the dammed river versus an adjacent free-flowing or differently regulated river(s). Temporal comparisons consider (4) pre- versus post-dam, or (5) sequential post-dam conditions. However, spatial comparisons are complicated by the fact that dams are not randomly located, and temporal comparisons are commonly limited by sparse historic information. As a result, comparative approaches are often correlative and vulnerable to confounding factors. To complement these analyses, (6) flow or sediment modifications can be implemented to test causal associations. Finally, (7) process-based modeling represents a predictive approach incorporating hydrogeomorphic processes and their biological consequences. In a case study of Hells Canyon, the upstream versus downstream comparison is confounded by a dramatic geomorphic transition. Comparison of the multiple reaches below the dams should be useful, and the comparison of Snake River with the adjacent free-flowing Salmon River may provide the strongest spatial comparison. A pre- versus post-dam comparison would provide the most direct study approach, but pre-dam information is limited to historic reports and archival photographs. We conclude that multiple study approaches are essential to provide confident interpretations of ecological impacts downstream from dams, and propose a comprehensive study for Hells Canyon that integrates multiple research strategies.     

Goals and remedial strategies for water quality and wildlife management in a coastal lagoon--a case-study of Ringkøbing Fjord, Denmark

The aim of this work is (1) to discuss approaches and tools to set management goals using operational indicators for coastal management (i.e., indicators that are easy to measure, understand and predict) and validated predictive models and (2) to discuss remedial strategies for sustainable coastal management regarding water quality and the abundance of fish, waterfowl and large aquatic plants. These approaches are exemplified using data from Ringkøbing Fjord, Denmark, which has undergone two major regime shifts during the last decades. This work discusses the changes taken place during the period from 1980 to 2004 (when there are good empirical data). For Ringkøbing Fjord, which is a very shallow, well-oxygenated lagoon dominated by resuspension processes, we have targeted on the following operational indicators, which are meant to reflect seasonal median values for the entire defined coastal area (the ecosystem scale) and not conditions at individual sites or data from shorter time periods: Secchi depth (as a standard measure of water clarity) and chlorophyll-a concentrations (as a key measure of algal biomass). The operational indicators are regulated by a set of standard abiotic factors, such as salinity, suspended particulate matter (SPM), nutrient concentrations (N and P), coastal morphometry and water exchange. Such relationships are quantified using well-tested, general quantitative models, which illustrate how these indicators are interrelated and how they reflect fundamental aspects of coastal ecosystems. We demonstrate that the regime shift in the lagoon can be modelled and quantitatively explained and is related to changes in salinity and nutrient inflow. A very important threshold is linked to increased salinities in the lagoon. For example, when the mean annual salinity is higher than about 9.5‰, large numbers of saltwater species of clams can survive and influence the structure and function of the ecosystem in profound ways. The model also illustrates the dynamic response to changes in nutrient loading. We have presented several management strategies with the goal of keeping the Secchi depth at 2 m, which would stimulate the growth of higher aquatic plants, which are fundamental for fish production and bird abundance in the lagoon. Given the fact that the Secchi depth depends on many variable factors (temperature, TP-inflow from land, salinity, changes in biomasses of macrophytes and clams, which are accounted for in these simulations), our results indicate that in practice it will likely be very difficult to reach that goal. However, it would be realistic to maintain a Secchi depth of 1.5 m if the variability in salinity is minimized and the mean salinity is kept at about 10.2‰.     

Validation of a hybrid life-cycle inventory analysis method

The life-cycle inventory analysis step of a life-cycle assessment (LCA) may currently suffer from several limitations, mainly concerned with the use of incomplete and unreliable data sources and methods of assessment. Many past LCA studies have used traditional inventory analysis methods, namely process analysis and input-output analysis. More recently, hybrid inventory analysis methods have been developed, combining these two traditional methods in an attempt to minimise their limitations. In light of recent improvements, these hybrid methods need to be compared and validated, as these too have been considered to have several limitations. This paper evaluates a recently developed hybrid inventory analysis method which aims to improve the limitations of previous methods. It was found that the truncation associated with process analysis can be up to 87%, reflecting the considerable shortcomings in the quantity of process data currently available. Capital inputs were found to account for up to 22% of the total inputs to a particular product. These findings suggest that current best-practice methods are sufficiently accurate for most typical applications, but this is heavily dependent upon data quality and availability. The use of input-output data assists in improving the system boundary completeness of life-cycle inventories. However, the use of input-output analysis alone does not always provide an accurate model for replacing process data. Further improvements in the quantity of process data currently available are needed to increase the reliability of life-cycle inventories.     

Variability of soil-water quality due to Tsunami-2004 in the coastal belt of Nagapattinam district, Tamilnadu

In this study, the Tsunami-caused deterioration of soil and groundwater quality in the agricultural fields of coastal Nagapattinam district of Tamilnadu state in India is presented by analyzing their salinity and sodicity parameters. To accomplish this, three sets of soil samples up to a depth of 30cm from the land surface were collected for the first six months of the year 2005 from 28 locations and the ground water samples were monitored from seven existing dug wells and hand pumps covering the study region at intervals of 3 months. The EC and pH values of both the soil and ground water samples were estimated and the spatial and temporal variability mappings of these parameters were performed using the geostatistical analysis module of ArcGIS((R)). It was observed that the spherical semivariogram fitted well with the data set of both EC and pH and the generated kriged maps explained the spatial and temporal variability under different ranges of EC and pH values. Further, the recorded EC and pH data of soil and ground water during pre-Tsunami periods were compared with the collected data and generated variability soil maps of EC and pH of the post-Tsunami period. It was revealed from this analysis that the soil quality six months after the Tsunami was nearing the pre-Tsunami scenario (EC< 1.5dSm(-1); pH<8), whereas the quality of ground water remained highly saline and unfit for irrigation and drinking. These observations were compared with the ground scenarios of the study region and possible causes for such changes and the remedial measures for taking up regular agricultural practices are also discussed.     

Analysis of the nitrifying bacterial community in BioCube sponge media using fluorescent in situ hybridization (FISH) and microelectrodes

There is growing interest in the development of more cost-effective and retrofit technologies for the upgrade and expansion of existing wastewater treatment plants with extreme space constraints. A free-floating sponge media (BioCube) process, using a 24L lab scale reactor, was operated to study the nitrification profiles and microbial community. The COD removal efficiencies were maintained, at an average of 95%, with the mixed liquor suspended solids (MLSS) inside the BioCube sponge media maintained at 12,688mg/L. The nitrification removal efficiencies were between 92% and 100%, with an average value of 99%. From the results of microelectrode measurements, the ammonium ion concentration was found to rapidly decrease from the surface of the BioCube sponge media to a depth of 2mm due to chemical reactions carried out by ammonia oxidizing bacteria (AOB) species. Multi-fluorescence in situ hybridization (FISH) has been used to investigate the spatial distributions of various microbial activities within reactors. Microbial communities were targeted using different oligonucleotide probes specific to AOB and nitrite oxidizing bacteria (NOB). There were a large number of AOB populations, but these were not uniformly distributed in the biofilm compared to the NOB populations.     

Detecting Temporal Change in Watershed Nutrient Yields

Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.     

The Contribution of Marsh Zones to Water Quality in Dutch Shallow Lakes: A Modeling Study

Many lakes have experienced a transition from a clear into a turbid state without macrophyte growth due to eutrophication. There are several measures by which nitrogen (N) and phosphorus (P) concentrations in the surface water can be reduced. We used the shallow lake model PCLake to evaluate the effects of three measures (reducing external nutrient loading, increasing relative marsh area, and increasing exchange rate between open water and marsh) on water quality improvement. Furthermore, the contribution of different retention processes was calculated. Settling and burial contributed more to nutrient retention than denitrification. The model runs for a typical shallow lake in The Netherlands showed that after increasing relative marsh area to 50%, total phosphorous (TP) concentration in the surface water was lower than the Maximum Admissible Risk (MAR, a Dutch government water quality standard) level, in contrast to total nitrogen (TN) concentration. The MAR levels could also be achieved by reducing N and P load. However, reduction of nutrient concentrations to MAR levels did not result in a clear lake state with submerged vegetation. Only a combination of a more drastic reduction of the present nutrient loading, in combination with a relatively large marsh cover (approximately 50%) would lead to such a clear state. We therefore concluded that littoral marsh areas can make a small but significant contribution to lake recovery.