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The design and assessment of net-zero buildings commonly focus exclusively on the operational phase, ignoring the embodied environmental impacts over the building life cycle. An analysis is presented on the consequences of integrating embodied impacts into the assessment of the environmental advantageousness of net-zero concepts. Fundamental issues needing consideration in the design process - based on the evaluation of primary energy use and related greenhouse gas emissions - are examined by comparing three net-zero building design and assessment cases: (1) no embodied impacts included, net balance limited to the operation stage only; (2) embodied impacts included but evaluated separately from the operation stage; and (3) embodied impacts included with the operation stage in a life cycle approach. A review of recent developments in research, standardization activities and design practice and the presentation of a case study of a residential building in Norway highlight the critical importance of performance indicator definitions and system boundaries. A practical checklist is presented to guide the process of incorporating embodied impacts across the building life cycle phases in net-zero design. Its implications are considered on overall environmental impact assessment of buildings. Research and development challenges, as well as recommendations for designers and other stakeholders, are identified.

In the present study, innovative energy efficiency enhancement methods and cleaner production in conventional waste-fired CHP plants are presented. This includes the medium- and low-grade solar thermal systems and flue gas condensation for feedwater heating in different arrangements. The article presents a thorough thermodynamic, economic, and environmental assessment of all the possible scenarios and then ranks the best solutions in different aspects. For making the results reliable, the solutions are applied to a waste-fired CHP plant in Denmark. For this, a transient simulation of the proposed configurations is performed via TRNSYS software for an entire year. The results indicate that the proposed models can produce more power and heat than the conventional plant but with different effectiveness factors. According to the economic results, a design consisting of a flue gas condensation circuit and parabolic trough collectors for the open and closed feedwater heater form the best configuration. The exergy assessment results indicate that the waste incinerator with annual irreversibility of 128.4 GWh is the most important component exergetically. Finally, the parametric study results show that the increase of incineration temperature significantly affects the power and heat exergy efficiency ratios.

The hypothesis of this paper is that in order to identify least cost solutions of the integration of fluctuating renewable energy sources into current or future 100% renewable energy supplies one has to take a Smart Energy Systems approach. This paper outline why and how to do so. Traditionally, significant focus is put on the electricity sector alone to solve the renewable energy integration puzzle. Smart grid research traditionally focuses on ICT, smart meters, electricity storage technologies, and local (electric) smart grids. In contrast, the Smart Energy System focuses on merging the electricity, heating and transport sectors, in combination with various intra-hour, hourly, daily, seasonal and biannual storage options, to create the flexibility necessary to integrate large penetrations of fluctuating renewable energy. However, in this paper we present the development and design of coherent Smart Energy Systems as an integrated part of achieving future 100% renewable energy and transport solutions. The transition from fossil fuels towards the integration of more and more renewable energy requires rethinking and redesigning the energy system both on the generation and consumption side. To enable this, the Smart Energy System must have a number of appropriate infrastructures for the different sectors of the energy system, which are smart electricity grids, smart thermal grids (district heating and cooling), smart gas grids and other fuel infrastructures. It enables fluctuating renewable energy (such as wind, solar, wave power and low value heat sources) to utilise new sources of flexibility such as solid, gaseous, and liquid fuel storage, thermal storage and heat pumps and battery electric vehicles. Smart Energy Systems also enable a more sustainable and feasible use of bioenergy than the current types allow. It can potentially pave the way to a bioenergy-free 100% renewable energy and transport system.

The concept of Zero Energy Building (ZEB) has gained wide international attention during last few years and is now seen as the future target for the design of buildings. However, before being fully implemented in the national building codes and international standards, the ZEB concept requires clear and consistent definition and a commonly agreed energy calculation methodology. The most important issues that should be given special attention before developing a new ZEB definition are: (1) the metric of the balance, (2) the balancing period, (3) the type of energy use included in the balance, (4) the type of energy balance, (5) the accepted renewable energy supply options, (6) the connection to the energy infrastructure and (7) the requirements for the energy efficiency, the indoor climate and in case of gird connected ZEB for the building–grid interaction. This paper focuses on the review of the most of the existing ZEB definitions and the various approaches towards possible ZEB calculation methodologies. It presents and discusses possible answers to the abovementioned issues in order to facilitate the development of a consistent ZEB definition and a robust energy calculation methodology.

Lignocellulose biorefineries are distinguished by an explicitly integrative, multi-functional concept that transforms biomass into multiple products, using a variety of conversion and separation processes. This study focuses on the technical design and economic evaluation of a lignocellulose biorefinery, that converts 400,000tDM/a (≙250MW) of beech wood into chemicals and fuel. A model was simulated with Aspen Plus® including the process steps pre-treatment, enzymatic hydrolysis, alcoholic fermentation, dehydration and biogas generation and upgrading. Mass and energy balances showed that 61,600t/a polymer-grade ethylene, 58,520tDM/a organosolv lignin, 38,400t/a biomethane and 90,800tDM/a hydrolysis lignin can be produced with a total energy efficiency of 87.1%. A discounted cash flow analysis indicated that the heat integrated biorefinery concept is not yet profitable. However, the economic results are greatly sensitive regarding various assumptions, in particular in terms of the prices for beech wood, ethylene and organosolv lignin.

Purpose: Environmental life cycle assessment (LCA) is today an important methodology to quantify the life cycle based environmental impacts of products, services or organisations. Since the very first LCA studies, the cumulative energy demand CED (also called ‘primary energy consumption’) has been one of the key indicators being addressed. Despite its popularity, there is no harmonised approach yet and the standards and guidelines define the cumulative energy demand differently. In this paper, an overview of existing and applied life cycle based energy indicators and a unifying approach to establish characterisation factors for the cumulative energy demand indicator are provided. The CED approaches are illustrated in a building’s LCA case study. Methods: The five approaches are classified into two main concepts, namely the energy harvested and the energy harvestable concepts. The two concepts differ by the conversion efficiency of the energy collecting facility. A unifying ‘energy harvested’ approach is proposed based on four theses, which ensure consistent accounting among renewable and non renewable energy resources. Results and discussion: The indicator proposed is compared to four other CED indicators, differing in the characterisation factors of fossil and biomass resources (upper or lower heating value), the characterisation factor of uranium and the characterisation factors of renewable energy resources (amount harvested or amount harvestable). The comparison of the five approaches is based on the cumulative energy demand of a newly constructed building of the city of Zürich covering the whole life cycle, including manufacturing and construction, replacement and use phase, and end of life. The cumulative energy demand of the life cycle of the building differs between 336 MJ oil-eq/m2a (‘CED uranium low’) and 836 MJ oil-eq/m2a (‘CED energy statistics’). The main differences occur in the use phase. The main reason for the large differences in the results are the different concepts to determine the characterisation factors for renewable and nuclear energy resources. Conclusions: The energy harvested approach ‘CED standard’ is a consistent approach, which quantifies the energy content of all different (renewable and non-renewable) energy resources. The ‘CED standard’ approach and the impact category indicator results computed with this approach reflect the safeguard subject ‘energy resources’ but not (no other) environmental impacts. The energy harvested approach proposed in this paper can readily be implemented in different contexts and applied to various data sets.

Climate change triggers a wide range of hydrometeorological, glaciological, and geophysical processes that span across vast spatiotemporal scales. With the advances in technology and analytics, a multitude of remote sensing (RS), geodetic, and in situ instruments have been developed to effectively monitor and help comprehend Earth’s system, including its climate variability and the recent anomalies associated with global warming. A huge volume of data is generated by recording these observations, resulting in the need for novel methods to handle and interpret such big datasets. Managing this enormous amount of data extends beyond current computer storage considerations; it also encompasses the complexities of processing, modeling, and analyzing. Big datasets present unique characteristics that set them apart from smaller datasets, thereby posing challenges to traditional approaches. Moreover, computational time plays a crucial role, especially in the context of geohazard warning and response systems, which necessitate low latency requirements.