Nativ-basierte Grundöle für die Produktion von Kühlschmierstoffen

Aims and Scope

Compared to mineral oil products, cooling lubricants based on fatty acid esters have technological advantages. Moreover, they are more environmentally compatible and make a contribution to a sustainable economy. Nevertheless, they are rarely applied in practice, because of their comparably high price, that is based on raw-material and synthesis costs. Alternatives concerning raw-materials and synthesis pathways are considered and properties of resulting ester products are compared.

Methods

The investigations aimed at three fatty acid-2-ethyl-hexylesters that were synthesized in an enzymatic-catalytic routine based on peanut oil, suet, and waste edible fat and at esters that were conventionally produced from animal and plant fats and 2-ethyl-1-hexanol. Physical properties, fatty acid patterns, contents of free fatty acids, as well as oxidative and hydrolytic stabilities were determined. Thermolysis experiments were performed.

Results

The physical properties of the seven esters, density, viscosity, pourpoint, and flash point, were comparable and gave reason for the assumption, that the products could be used as basis oils in lubricant formulations. Hydrolysis stabilities of the esters were high and thermal stress did not point at high potential of hazardous compounds formation. Especially the enzymatic-catalytically produced esters showed deficits concerning oxidation stabilities and free fatty acid contents.

Outlook

For practice it will be necessary to define minimum qualities for raw-materials and resulting ester oils to be used as lubricant basis oils. Moreover, processes have to be developed, that yield high quality ester products from waste edible and animal fats without loosing the advantage of low-cost raw-materials by high production and refinement costs. Surely, one contribution is the further development of the energy-saving enzymtic alcoholysis for ester production.     

Comparing indoor wastewater-fed aquaculture with two conventional wastewater treatment plants using adopted sustainable process indices

Highly aggregating 'Sustainable Process Indices' (SPI) were calculated for an indoor wastewater-fed aquaculture and two conventional wastewater treatment plants to make a direct comparison between the three facilities possible. The goal was to find out which technology would be better suited for use in a sustainable economy. The SPI provides a type of 'ecological footprint' for the three facilities on the basis that, in a sustainable economy, solar energy would be our main energy source and that surface area would become the limiting factor for economic development, because the transformation of solar energy into other forms of energy, products or services requires area. SPI calculations consider the area necessary for the sustainable dissipation of byproducts and wastes of a process into the environment. The SPI thus uses area as its basic unit for comparisons between different technologies, products or services.

Energy consumption, as well as treatment performance (both the quality and quantity of treated effluent), and multi-functionality of facilities were key variables in determining how much area a wastwater treatment plant would need to be embedded sustainably into the environment. The calculated SPIs reveal that the wastewater-fed aquaculture requires the least area to be embedded sustainably into the environment, therefore, it would be better suited for use in a sustainable economy compared to the two conventional wastewater treatment plants.     

Evaluating Spatial Design Techniques for Solving Land-use Allocation Problems

This study examines the use of spatial optimization techniques for multi-site land-use allocation problems (MLUA). 'Multi-site' refers to the problem of allocating more than one land-use type in an area, which are difficult problems as they involve multiple stakeholders with conflicting goals and objectives. Spatial optimization methods consist of (1) an optimization model and (2) an algorithm to solve the model. This study demonstrates a goal-programming model to solve the MLUA problem. The model is solved using both simulated annealing and genetic algorithms. Special attention has been given to introduce a spatial compactness objective in the model. It is shown that the compactness objectives in the optimization model generate compact patches of the same land use for using both the simulated annealing procedure and the genetic algorithm. In addition, it appears that using the proper settings of the compactness objectives, connectivity between patches of land use is promoted. The method is tested for a fictive study and then demonstrated for a real case study, both measuring 20 × 20 cells. The genetic algorithm generally performs better than simulated annealing in terms of solution time and achieving compactness.     

A comparison of predicted and measured levels of runoff-related pesticide concentrations in small lowland streams on a landscape level

Short-term pollution events via runoff are typical of streams in agricultural areas. Existing runoff models that simulate pesticide loss from agricultural fields require extensive input of information. There is thus a need for a simple model that can predict runoff-related pesticide concentrations in many streams on a landscape level when only limited data are available. To validate such a model, the runoff-related pesticide load of 18 small lowland streams was predicted with an extended version of the model "simplified formula for indirect loadings caused by runoff" (available from the Organisation for Economic Cooperation and Development, OECD). The authors suggest that the model presented here is suitable for use in routine exposure assessment of pesticides on a landscape level, as all input data (soil, slope, precipitation, pesticide application) are readily available from public authorities or could be generated by simple regional flood hydrograph curves. The predicted concentrations were compared with measured concentrations obtained by runoff-triggered sampling. Fungicides, insecticides and herbicides were detected in 17 streams, with max. concentrations measuring up to 29.7 microg/l for the fungicide azoxystrobin and 0.3 microg/l for the insecticide parathion-ethyl. Herbicides were detected in 16 streams, with max. concentrations between 13.7 and 1.2 microg/l. The linear regression between the predicted and measured concentrations (log-values) shows significant correlations for the following pesticides: azoxystrobin: r2=0.43; p=0.03; epoxiconazole: r2=0.71; por=0.5 microg/l).     

Giardia and Cryptosporidium in pristine protected catchments in central eastern Australia

We report the first confirmed records of the pathogenic protozoa Giardia lamblia and Cryptosporidium parvum from small remote streams in pristine protected areas in Australia, beyond the reach of urban or agricultural contamination.     

The effect of modelling expert knowledge and uncertainty on multicriteria decision making: a river management case study

To support decision making on complex environmental issues, models are often used to explore the potential impacts of different management alternatives on the environmental system. We explored how different model outcomes affect decision making. Two topics have our particular interest, namely (1) the influence of quantification of qualitative information on decision making, and (2) the influence of reflecting uncertainty in the model outcomes on decision making. We set up a survey, in which we use a case study describing a decision making situation in strategic river management. The survey was disseminated through the Internet. From the results we conclude that the quantification of information in itself does not necessarily change preferences, although the outcomes suggest that preferences converge when based on quantified information. When confronted with uncertainty information, respondents show a preference for the alternative with the smallest chance of negative impacts. The study shows that, whereas the modelling community often strives to provide the policy process with as good, and as detailed information as is possible, their assumption that this will automatically lead to ‘better’ decision making is not self-evident.     

Development of a biotic ligand model (BLM) predicting nickel toxicity to barley (Hordeum vulgare)

A biotic ligand model (BLM) was developed to predict nickel toxicity, affecting root growth of barley (Hordeum vulgare), in nutrient solutions. The extent to which Ca(2+), Mg(2+), Na(+), K(+) ions and pH each influenced nickel toxicity was determined. Higher activities of Mg(2+) linearly increased the 4d EC50 Ni (2+) , while Ca(2+), Na(+), K(+) and H(+) activities did not significantly influence Ni(2+) toxicity. Stability constants for the binding of Ni(2+) and Mg(2+) to the biotic ligand were obtained: logK(NiBL)=5.27 and logK(MgBL)=3.47. Further, it was calculated that on average 57% of the biotic ligand sites needed to be occupied by nickel to induce 50% root growth inhibition. Auto-validation of the BLM indicated that predicted EC50s differed from the observed EC50s by a factor of less than 2, indicating that the BLM concept may also be used to predict metal toxicity to terrestrial plants.