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The purpose of this paper is to compare well‐known technologies of sludge utilization on the basis of energy and economical balances of real processes. The calculations are based on pilot tests in the Central Waste Water Treatment Plant (CWWTP) in Prague, the biggest waste water treatment plant in the Czech Republic.

A key issue for the comparison of mass and energy flow of sludge management is the attainable level of sludge dewaterability. Results of dewatering of anaerobic digested sludge are available from real applications since most sewage plants use digesters. The existing limited knowledge about mixed raw sludge (MRS) dewaterability have driven authors to make pilot tests targeted to establishment of an attainable level of MRS dewaterability. To get as close results as possible even anaerobic stabilized sludge was dewatered and various other data were collected to obtain a comprehensive data set for energy balance of the sludge management calculation. The pilot tests took place at CWWTP in 2005. Measured data were used to calculate energy balance of a number of different sludge managements.

To produce self‐reliant combusting sludge, a dry matter content of 35‐45 per cent for MRS and 45‐55 per cent for digested sludge has to be achieved by means of dewatering and potentially drying. In recent measurements at CWWTP a dry matter content of about 33 per cent was achieved by dewatering of MRS. This value is very close to the range of the dry matter content at which a self reliant combustion can be expected.

This comparison together with investment cost analysis should be one of the most important parameters in case of design a new or revamp an old waste water treatment plant.

The paper provides results from pilot tests at CWWTP together with three different energy balances comparison.

To study the impact of River Nestos (North Greece) dams construction on coastal morphology.

In order to study the evolution of the coastal morphology in the area, an “one‐line shoreline change model” was developed (PELNCON). The model's input comprises the field characteristics, the wave characteristics at the breaker line and a “source” term for the sediment supply rate by River Nestos. The model calculates the shoreline change over a given period of time. The annually transported sediment quantity by the river is estimated using filed measurements and other models' results for various sites along the Greek part of the hydrologic basin of Nestos (Nestos is a transboundary river extending along Greece and Bulgaria).

The “PELNCON” results demonstrate a serious erosion threat for the coastal area due to the sediment budget deficit of about 1.8 × 10⁶m³/year.

The developed model is subject to common structural weaknesses of computational modelling based on the one‐line shoreline change theory.

The developed model is user‐friendly and can be applied to any coastal area of known characteristics, providing realistic results.

This paper is an attempt to model the correlation between two large‐scale phenomena, namely coastal erosion and water/sediment management in river basins, setting at the same time the basis for further study on this particular scientific field.

The paper attempts to address both resource consumption and recycling effectiveness, using concepts from thermodynamics: entropy production for evaluating the costs (resource consumption) and statistical entropy for evaluating the benefits (separation of materials) of recycling processes.

Resource consumption, in this context, is to be understood as the overall thermodynamic devaluation of matter and energy flows. The recycling effectiveness, on the other hand, can be measured by the process's ability to reduce the “mixedness” of the material flows, using statistical entropy (entropy of mixing) as an indicator. Statistical entropy has been used by others as an indicator for the performance of waste separation processes, and its application to metal recycling seems straightforward. Entropy production has been applied as a measure for resource consumption in copper production. Here, the two concepts are combined to reach an expression describing the resource efficiency of recycling.

The theoretical description of the approach is supported by an example calculation for copper recycling. The findings suggest a near perfect effectiveness of the copper separation when processing medium grade copper scrap in a primary copper smelter. The resource consumption, on the other hand, is quite large when compared to the service of the process, giving rise to a rather small thermodynamic efficiency (in terms of the definition of efficiency as applied in this paper).

Both measures used here, recycling efficiency and recycling effectiveness, are very demanding concerning the data basis, making applications time consuming. These drawbacks can be overcome by linking material flow tools (e.g. LCA software) with thermodynamic databases. More examples have to be considered to show the practical relevance of the approach.

The paper addresses effectiveness and efficiency using a common denominator, thermodynamic entropy. This unification helps in ranking different recycling options regarding their performance in terms of technical effectiveness and resource consumption.

The purpose of this investigation is the modeling of rapid climate changes (RCC) and analysis of their impacts in ecological and economic systems, in particular, their responses on the rate of RCC and assessment of the considered factors most influenced by RCC.

For modeling impacts of the RCC, the model WORLD3 has been used. Since it is expected that the greatest impacts of RCC be in energy, in this case, the WORLD3 model has been used under the assumption that RCC influences the rapid decrease of energy during a time period of one year. Therefore, the results will be more explicit than in the case when the change occurs gradually during a longer time period.

The results obtained in this work show that increasing the rate of RCC can be associated also with nonlinear responses of economic and ecological factors. It is seen from the analysis that the later the RCC occurs in the time scale considered, the lesser the consequences for ecological and economic systems affected by the RCC.

From these results, it can be concluded that adaptability and resilience of ecosystems and economies is needed, especially for the factors that are most affected by RCC – in this case, the population and energy, exert efforts for reducing the causes of RCC, and prompt action to mitigate global warming as the main cause of RCC. Also, these results show the possibility of early development of potential mitigation and adaptation strategies and allow for a better evaluation of risk exposure.

This work is original, as no such analysis has been carried out about impacts of RCC in economic and ecological systems. The paper provides data and results upon which further research could be carried out.

Renewable energy sources are likely to play a major role in meeting the future energy requirement of a developing country like India. Among the various renewable energy sources, the bio‐energy plays a key role for the power generation. In this paper, an attempt is made to develop a fuzzy based linear programming optimal electricity allocation model (OEAM) that minimizes the cost and determines the optimum allocation of different energy sources for the centralized and decentralized power generation in India with special emphasis to bio‐energy.

The OEAM model optimizes and selects the appropriate energy options for the power generation on the factors such as cost, potential, demand, efficiency, emission and carbon tax. The objective function of the model is minimizing the cost of power generation. The other factors are used as constraints in the model. The fuzzy linear programming optimization approach is used in the model.

The extents of energy sources distribution for the power generation in the year 2020 would be 15,800 GWh (4 per cent) from the coal based plants, 85,400 GWh (20 per cent) from the nuclear plants, 191,100 GWh (44 per cent) from the hydro plants, 22,400 GWh (5 per cent) from the wind mills, 45,520 GWh (11 per cent) from the biomass gasifier plants, 14,112 GWh (3 per cent) from the biogas plants, 8,400 GWh (2 per cent) from the solid waste, 33,600 GWh (8 per cent) from the cogeneration plants and 11,970 GWh (3 per cent) from the mini hydel plants, respectively.

The OEAM has been developed for the electricity demand allocation for the year 2020. An extensive literature survey revealed that carbon tax and emission constraints were never used in the previous models and they are considered in the present model.

The objective is to describe and evaluate the development of a novel planning tool for end‐use efficiency in the built environment and for infrastructural changes in the energy system.

After describing problems related to further reduce heat demand in the Danish built environment, the geographical nature of the planning task is discussed. The requirements are then translated into concepts for the development of a general method, which is implemented in a practical design of a heat atlas. Typical applications are described and discussed.

It was found that the availability of the extensive public databases in Denmark make feasible the development and application of a highly detailed geographical information base for end use and infrastructure planning and analysis. It was also realised that the development has much higher potentials than explored in this paper. On the other hand, the complex geography of the urban/rural boundaries of cities requires extra care when using this approach.

Unfortunately, the results of this report are only directly applicable for Denmark, which maintains public databases on the built environment and socio‐demography with a very high standard of detail and coverage. The research presented here may require further development of empirical methods of the relation between energy demand and physically and socially mapped data. On the other hand, the research may contribute to better data for analyses in the techno‐economic analyses of future energy systems, which now can be carried out for arbitrary geographical units, independent of administrative boundaries.

The method presented here may be further developed as a practical tool to be used to revive the municipal and regional energy planning, either by technical consultants or by local governments. Even a publicly accessible, web‐based tool is feasible.

The paper describes how existing data in society can be assembled to a novel method to be used within energy planning, and environmental management as a whole. A system of the one developed does not exist as yet. On the other hand it builds upon existing traditions in energy planning and local governance.

The high costs of collection and transportation of municipal solid waste (MSW) on the overall waste management budget (sometimes more than 75 per cent) makes it an issue to be urgently addressed for improvement. The paper aims to focus on the optimisation of routing networks for waste collection/transportation.

The paper proposes herein the application of geographic information system (GIS) 3D route modelling for waste collection/transportation to optimise the route according to the minimum fuel consumption criterion to different municipalities of the island of Santo Antao of Cape Verde.

The optimisation for the lowest fuel consumption yields 52 per cent savings in fuel, when compared to that for the shortest distance, even travelling a 34 percent longer distance, which shows the importance of considering simultaneously the relief of the territory and the lowest fuel consumption criterion when optimising vehicle routes.

With such a supporting decision tool savings in fuel are huge, the efficiency of management systems is improved and the environmental impact during daily operation is reduced. The GIS 3D route modelling takes into account the effects of both the road inclination and the vehicle load.

The originality of the work lies in the chosen approach. To optimise vehicle routes the criterion of minimum fuel consumption rather than the commonly used shortest distance is used, since fuel consumption is the factor reflecting actual costs relative to MSW management.