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[EN] The objective of this article is to compare the behaviour of the most representative domestic hot water systems (DHW) in single-family buildings. The study evaluates the energy consumption, equivalent CO2 emissions and cost for each system over a 15-year life period. This analysis is carried out in four cli- matic zones across Europe to observe the influence of climatic conditions on the results. The four climatic zones are located in the cities of Athens, Madrid, London and Berlin. The analysed systems are: a) natural gas-fired instantaneous water heaters, b) electric storage water heater, c) solar thermal system with gas- fired instantaneous, d) solar thermal system with electric storage water heater, e) air-source heat pump, f) photovoltaic system with electric storage water heater, and g) photovoltaic system with air-source heat pump. This range of technologies covers the most likely solutions to be implemented across domestic buildings in Europe.The heat pump system (HPWH) with PV considering self-consumption shows the lowest environmen- tal impact in all zones, but is not an attractive investment in the coldest zones due to lower natural gas prices. Thermal solar systems have a high purchase and maintenance costs which do not compensate their energy savings. The PV HPWH system has a greater reduction of emissions and a lower cost than HPWH across a 15-year life. The gas boiler system has the lowest cost in a 15-year period in the coldest areas, despite having a greater environmental impact than the heat pump.(c) 2023 Elsevier B.V. All rights reserved.

Thermoacoustic technology emerges as a sustainable and low-carbon method for energy conversion, leveraging environmentally friendly working mediums and independence from electricity. This study presents the development of a multimode heat-driven thermoacoustic system designed to utilize medium/low-grade heat sources for room-temperature cooling and heating. We constructed both a simulation model and an experimental prototype for a single-unit direct-coupled thermoacoustic system, exploring its performance in heating-only, cooling-only, and hybrid heating and cooling modes. Internal characteristic analysis including an examination of internal exergy loss and a distribution analysis of key parameters was first conducted in the hybrid cooling and heating mode. The results indicated a positive-focused traveling-wave-dominant acoustic field within the thermoacoustic core unit, enhancing energy conversion efficiency. The output system performance was subsequently tested under different working conditions in the heating-only and cooling-only modes. A maximum output heating power of 2.3 kW and a maximum COPh of 1.41 were observed in the heating-only mode. Meanwhile, a cooling power of 748 W and a COPc of 0.4 were obtained in the typical cooling condition at 7 °C when operating in cooling-only mode. These findings underscore the promising potential of thermoacoustic systems for efficiently utilizing medium/low-grade heat sources for cooling and/or heating applications in the future.

The lifetime and reliability of power transformers are primarily dependent on the hot-spot temperature in the windings, as temperature is the most important factor determining the insulation degradation rate. Key to removing the heat from the transformer is the radiator which must be carefully designed to keep the temperatures within limits under all operating conditions whilst minimizing the transformer size, weight and cost. This paper compares the analytical method used to predict the radiator performance with computational fluid dynamics (CFD) models in terms of heat dissipation. It is found that the analytical method and CFD models give similar results in the air natural (AN) cooling modes, whereas the analytical method overestimates the heat dissipation in the air forced (AF) cooling modes. Moreover, the thermal conduction effect in the radiator wall is investigated under different operating conditions and for different radiator sizes using the CFD models. The simulation results indicate that the radiator wall contributes to 6%-10% of the total heat dissipation under some circumstances and therefore should not be simply ignored in radiator models.

Environmental tax reform (ETR), a shift from labour to carbon taxes, has been mostly modelled using general equilibrium (GE) analysis. Since a low-carbon transition will require deep transformations, one will also have to address out-of-equilibrium dynamics and increased agent heterogeneity. Unlike GE models, agent-based models (ABMs) are well equipped to deal with this. We therefore replicate a recent GE model for ETR using an agent-based approach. This process, known as "agentization", allows assessing similarities as well as differences in policy impacts between the two modelling approaches, in turn providing a test of the robustness of the GE results. We find that the agent-based model is able to replicate many results of the general equilibrium analysis, while revealing strengths and weaknesses of both model types. We discuss concrete implementation steps and difficulties experienced in the GE-ABM translation process. We illustrate the potential of ABM by extending the model in several directions. We show that heterogeneous subsistence consumption can increase the space for combining a double dividend with an equity goal, and that overall macro-economic results can conceal important distributional impacts when green preferences and labour supply elasticities vary.

Modelling the economics of climate change is daunting. Many existing methodologies from social and physical sciences need to be deployed, and new modelling techniques and ideas still need to be developed. Existing bread-and-butter micro- and macroeconomic tools, such as the expected utility framework, market equilibrium concepts and representative agent assumptions, are far from adequate. Four key issues—along with several others—remain inadequately addressed by economic models of climate change, namely: (1) uncertainty, (2) aggregation, heterogeneity and distributional implications (3) technological change, and most of all, (4) realistic damage functions for the economic impact of the physical consequences of climate change. This paper assesses the main shortcomings of two generations of climate-energy-economic models and proposes that a new wave of models need to be developed to tackle these four challenges. This paper then examines two potential candidate approaches—dynamic stochastic general equilibrium (DSGE) models and agent-based models (ABM). The successful use of agent-based models in other areas, such as in modelling the financial system, housing markets and technological progress suggests its potential applicability to better modelling the economics of climate change.

This paper proposes a novel online and self-learning algorithm to the identification of fuzzy neural networks, which not only learns the structure and parameters online but also learns the threshold parameters by itself and automatically. For structure learning, a self-constructing approach including adding neurons and merging highly similar fuzzy rules is proposed based on the criteria of the system error between actual and model output and the maximum firing strength of neurons. In order to achieve the efficient merging computing, a new calculation method of similarity degree between fuzzy rules is developed. Further and more importantly, the varying width of Gaussian membership functions can be learned by itself according to the underfitting and overfitting criteria. Similarly, different from the existing constant threshold of similarity degree for merging, the varying threshold of similarity degree can be self-learned according to the real-time accuracy of model. The proposed self-learning mechanism significantly improves the model accuracy and greatly enhances the easy usability. Several benchmark examples are implemented to illustrate the effectiveness and feasible of the proposed approach.

In industrialized countries, large amounts of mineral wastes are produced. They are re-used in various ways, particularly in road and earth constructions, substituting primary resources such as gravel. However, they may also contain pollutants, such as heavy metals, which may be leached to the groundwater. The toxic impacts of these emissions are so far often neglected within Life Cycle Assessments (LCA) of products or waste treatment services and thus, potentially large environmental impacts are currently missed. This study aims at closing this gap by assessing the ecotoxic impacts of heavy metal leaching from industrial mineral wastes in road and earth constructions. The flows of metals such as Sb, As, Pb, Cd, Cr, Cu, Mo, Ni, V and Zn originating from three typical constructions to the environment are quantified, their fate in the environment is assessed and potential ecotoxic effects evaluated. For our reference country, Germany, the industrial wastes that are applied as Granular Secondary Construction Material (GSCM) carry more than 45,000 t of diverse heavy metals per year. Depending on the material quality and construction type applied, up to 150 t of heavy metals may leach to the environment within the first 100 years after construction. Heavy metal retardation in subsoil can potentially reduce the fate to groundwater by up to 100%. One major challenge of integrating leaching from constructions into macro-scale LCA frameworks is the high variability in micro-scale technical and geographical factors, such as material qualities, construction types and soil types. In our work, we consider a broad range of parameter values in the modeling of leaching and fate. This allows distinguishing between the impacts of various road constructions, as well as sites with different soil properties. The findings of this study promote the quantitative consideration of environmental impacts of long-term leaching in Life Cycle Assessment, complementing site-specific risk assessment, for the design of waste management strategies, particularly in the construction sector.