Effects of calcium hydroxide and calcium chloride addition to bentonite in iron ore pelletization.

Pyrite ash is created as waste from the roasting of pyrite ores during the production of sulphuric acid. These processes generate great amounts of pyrite ash waste that is generally land filled. This creates serious environmental pollution due to the release of acids and toxic substances. Pyrite ash waste can be utilized in the iron production industry as a blast furnace feed to process this waste and prevent environmental pollution. The essential parameters affecting the pelletization process of pyrite ash were studied using bentonite as a binder. Experiments were then carried out using bentonite and a mixture of bentonite with calcium hydroxide and calcium chloride in order to make the bentonite more effective. The metallurgical properties of pyrite ash, bentonite, calcium hydroxide, calcium chloride, a mixture of these and sintered pellets were studied using X-ray analysis. The crushing strength tests were carried out to investigate the strength of pyrite ash waste pellets. The results of these analyses showed that pyrite ash can be agglomerated to pellets and used in the iron production industry as a blast furnace feed. The crushing strength of the pellets containing calcium hydroxide and calcium chloride in addition to bentonite was better than the strength of pellets prepared using only bentonite binder.     

Estimates of animal methane emissions

The enteric methane emissions into the atmospheric annually from domestic animals total about 77 Tg. Another 10 to 14 Tg are likely released from animal manure disposal systems. About 95% of global animal enteric methane is from ruminants, a consequence of their large populations, body size and appetites combined with the extensive degree of anaerobic microbial fermentation occurring in their gut. Accurate methane estimates are particularly sensitive to cattle and buffalo census numbers and estimated diet consumption. Since consumption is largely unknown and must be predicted, accuracy is limited often by the information required, i.e., distribution of animals by class, weight and productivity. Fraction of the diet lost as enteric methane mostly falls into the range of 5.5–6.5% of gross energy intake for the world's cattle, sheep and goats. Manure methane emissions are heavily influenced by fraction of disposal by anaerobic lagoon. Non-ruminants, i.e., swine, become major contributors to these emissions.     

Reversibility of stemflow-induced soil acidification in Swedish beech forest

Stemwater running down the trunks of beech (Fagus sylvatica L.) has an acidifying effect on soil near the stem. The deposition of acidifying substances may be two to four times higher close to the stem compared to in the stand in general. To study reversibility of soil acidification, 72 stumps of beech trees were chosen from five different year classes of felling (3, 6, 9, 14-15, 25-30), representing the years when stemflow ceased to affect the soil. The H(+) concentration (pH KCl) in the topsoil (0-5 cm) differed between the distances 10-30 cm and 230-250 cm from the stumps, the soil close to the stem being more acid. The longer the time since felling the smaller the differences in H(+) concentration became. This reduction in soil acidity amounted to ca. 50% after 15 years, and only small further changes occurred over the next ten years. This indicates that soil may not recover fully from acidification, or does so at a rather slow rate after the initial 15 years of recovery.     

Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection

In this paper we apply graph theory in a reserve selection exercise to explore the tradeoffs between maintaining connectivity and minimizing the total area of a protected area network. Rather than focus on a single organism, we used a multi-species approach and looked at the tradeoff curves for organisms with varying dispersal abilities. We first generated the tradeoff curves using a graph-based metric to determine the importance of individual patches for maintaining connectivity. We then performed an analogous set of analyses using patch size as a surrogate measure of importance.     

Evaluation of a real-time monitoring system for river quality — a trade-off between risk attitudes,costs, and uncertainty

Uncertainty is definitely one of the key topics in environmental assessment and management. Typically, attempts to reduce uncertainty are subject to expenses. But how to compare and trade-off expenses and the reduced uncertainty? They only seldom allow the use of a single unit. Instead, the whole analysis and decision procedure is very subjective. This paper presents one approach to handle such problems, namely the combined use of Bayesian influence diagrams, and probabilistic risk attitude analysis. The approach was used in the evaluation of three alternatives for a real time river water quality forecasting system. A trade-off analysis of risk attitudes, costs and uncertainty indicated the levels of socioeconomic utility required for investments in the respective systems, and accordingly illuminated the impact of the uncertainties involved on inference and decision-making with various risk attitudes and discount rates.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.