Assessing groundwater quality and its sustainability in Joypurhat district of Bangladesh using GIS and multivariate statistical approaches

Sustainable groundwater quality is a key global concern and has become a major issue of disquiets in most parts of the world including Bangladesh. Hence, the assessment of groundwater quality is an important study to ensure its sustainability for various uses. In this study, a combination of multivariate statistics, geographical information system (GIS) and geochemical approaches was employed to evaluate the groundwater quality and its sustainability in Joypurhat district of Bangladesh. The results showed that the groundwater samples are mainly Ca–Mg–HCO₃ type. Principal component analysis (PCA) results revealed that geogenic sources (rock weathering and cation exchange) followed by anthropogenic activities (domestic sewage and agro-chemicals) were the major factors governing the groundwater quality of the study area. Furthermore, the results of PCA are validated using the cluster analysis and correlation matrix analysis. Based on the groundwater quality index (GWQI), it is found that all the groundwater samples belong to excellent to good water quality domains for human consumption, although iron, fluoride and iodide contaminated to the groundwater, which do not pose any significant health hazard according to World Health Organization’s and Bangladesh’s guideline values. The results of irrigation water quality index including sodium adsorption ratio (SAR), permeability index and sodium percentage (Na %) suggested that most of the groundwater samples are good quality water for agricultural uses. The spatial distribution of the measured values of GWQI, SAR, Fe (iron), EC (electrical conductivity) and TH (total hardness) were spatially mapped using the GIS tool in the study area.     

Treibhausgasemissionen zukünftiger Erdgasbereitstellung für Deutschland

Ohne Zusammenfassung Original erschienen in UWSF – Z Umweltchem ?kotox 20(2):133–144 (2008) DOI: Herausgeber: Martin Pehnt und Eckard Helmers     

Development of a test method against hot alkaline chemical splashes.

High temperature alkaline chemical liquids have caused injuries and hazardous situations in Finnish pulp manufacturing mills. There are no requirements and/or test method standards concerning protection against high temperature alkaline chemical splashes. This paper describes the test method development process to test and identify materials appropriate for hot liquid chemical hazard protection. In the first phase, the liquid was spilled through a stainless steel funnel and the protection performance was evaluated using a polyvinyl chloride (PVC) film under the test material. After several tentative improvements, a graphite crucible was used for heating and spilling the chemical, and a copper-coated K-type thermometer with 4 independent measuring areas was designed to measure the temperature under the material samples. The thermometer was designed to respond quickly so that peak temperatures could be measured. The main problem was to keep the spilled amount of chemical constant, which unfortunately resulted in significant variability in data.     

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.     

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.     

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.     

Seasonal variations in nickel and vanadium in Mont Blanc snow and ice dated from the 1960s and 1990s

Ni and V have been determined in snow and ice collected at a high altitude location (Col du D?me) near the summit of Mont Blanc on the French-Italian border; dated from the 1960s and 1990s. Ni and V were simultaneously determined by inductively coupled plasma sector field mass spectrometry. Measured concentrations range from 6 to 700 pg g(-1) and 4 to 1,100 pg g(-1) for Ni and V, respectively. The results show pronounced seasonal variations in the concentrations of both metals, with high concentration values in summer layers and much lower values for winter layers. These seasonal variations are linked especially with the existence of inversion layers during winter months. Ni and V concentrations in excess of the contributions from rock and soil dust (Ni(excess), V(excess)) appear to be mainly associated with anthropogenic inputs, with pronounced seasonal variations. Large variations in the V(excess)/Ni(excess) ratio are observed, with a higher ratio in summer than in winter. This shows differences in anthropogenic inputs at Col du D?me during the different parts of the year. The above ratio was compared with the corresponding ratios for oil combustion from stationary sources and the exhaust from gasoline and diesel engines. It appears that Ni and V concentrations at Col du D?me are probably the result of changing combinations of contributions from oil combustion for power generation, industrial and residential uses, on one side, and automobile and truck traffic, on the other side, with possibly a significant contribution from Ni smelters in Russia during winter months.     

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less time.