Uncertainty characterization of building emergy analysis (BEmA)

Yi, Hangmo; Braham, William W.

doi:10.1016/j.buildenv.2015.05.007

Cited by 36 publications

(11 citation statements)

References 25 publications

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“…A sensitivity analysis can reveal the margins of uncertainty related to the emergy assessment at issue. This complies with the currently open debate within the emergist community (Ingwersen, 2010;Li et al, 2011;Yi & Braham, 2015;Reza et al, 2013;Hudson & Tilley, 2014), although not all authors include its assessment. In particular, sensitivity analyses are performed by changing the quantities of the driving inputs (raw amounts or UEVs) -typically, 10% and 20% -and evaluating the resulting effects on the total flows and indicators.…”

Section: Sensitivity Analysissupporting

confidence: 64%

Organic vegetables from community-supported agriculture in Italy: Emergy assessment and potential for sustainable, just, and resilient urban-rural local food production

Cristiano

2021

Journal of Cleaner Production

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Global crises such as the COVID-19 pandemic highlight the interconnectedness and vulnerability of human systems, requiring integrated interdisciplinary studies aimed at breaking unsustainable and unjust practices. In this work, a horticultural collaborative production system is addressed, inspired by the community-supported agriculture (CSA) model. In a highly industrialised area of Northern Italy, with significant wild land consumption, an alternative bottom-up experience is described for the provision of vegetables in a short and cooperative not-for-sale supply chain. Local organic farming and just labour conditions seek ecological sustainability and social equity beyond market dynamics. This CSA project contributes to the resilience of a territory currently affected by health and economic plights. Its claims, limits, and potentials of a project of this kind are investigated for the first time by means of the Emergy Assessment (EMA). The socio-ecological and economic inputs in the system at issue are identified and quantified, partly eased by the transparent process of the target community, and some key indicators are calculated. This EMA provides fruitful insights of a single replicable and/or scalable project, thus offering current barrier and future opportunities for local improvement and exportability to crisis and post-crisis scenarios, and anyway for pursuing sustainability goals.

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Section: Sensitivity Analysissupporting

confidence: 64%

Organic vegetables from community-supported agriculture in Italy: Emergy assessment and potential for sustainable, just, and resilient urban-rural local food production

Cristiano

2021

Journal of Cleaner Production

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“…Monte Carlo-based simulation is the most widely used uncertainty propagation method in the area of building energy assessment [107][108][109]. This is because this method is very intuitive and easy to implement compared to other uncertainty propagation approaches (such as full factorial numerical integration, stochastic Galerkin, and discrete projection).…”

Section: Monte Carlo Sampling-based Simulationmentioning

confidence: 99%

A review of uncertainty analysis in building energy assessment

Tian

Heo

Wilde

et al. 2018

Renewable and Sustainable Energy Reviews

324

122

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Uncertainty analysis in building energy assessment has become an active research field because a number of factors influencing energy use in buildings are inherently uncertain. This paper provides a systematic review on the latest research progress of uncertainty analysis in building energy assessment from four perspectives: uncertainty data sources, forward and inverse methods, application of uncertainty analysis, and available software. First, this paper describes the data sources of uncertainty in building performance analysis to provide a firm foundation for specifying variations of uncertainty factors affecting building energy. The next two sections focus on the forward and inverse methods. Forward uncertainty analysis propagates input uncertainty through building energy models to obtain variations of energy use, whereas inverse uncertainty analysis infers unknown input factors through building energy models based on energy data and prior information. For forward analysis, three types of approaches (Monte Carlo, non-sampling, and non-probabilistic) are discussed to provide sufficient choices of uncertainty methods depending on the purpose and specific application of a building project. For inverse analysis, recent research has concentrated more on Bayesian computation because Bayesian inverse methods can make full use of prior information on unknown variables. Fourth, several applications of uncertainty analysis in building energy assessment are discussed, including building stock analysis, HVAC system sizing, variations of sensitivity indicators, and optimization under uncertainty. Moreover, the software for uncertainty analysis is described to provide flexible computational environments for implementing uncertainty methods described in this review. This paper concludes with the trends and recommendations for further research to provide more convenient and robust uncertainty analysis of building energy. Uncertainty analysis has been ready to become the mainstream approach in building energy assessment although a number of issues still need to be addressed.

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“…The most recent building emergy studies focus on extending the EmS for analyzing different building types/components [6,78,[85][86][87][88][89][90][91][92][93]. Meanwhile, methodological advancements [78,80,[94][95][96] and the suggestion of new indicators [5,78] have also been explored. In particular, Srinivasan et al [5] proposed a new building performance indicator based on the balance of renewable and non-renewable energy.…”

Section: Emergy Approach To Building Applicationmentioning

confidence: 99%

Beyond Energy Efficiency in Building Sustainability: A Review of Emergy and Information for Systemically Characterizing Building Performance

Yi¹,

Mehrotra²

2022

Highlights Sustain.

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Sustainable buildings tend to maximize power and information rather than efficiency. The multidimensional concepts and tools provided by systems ecology and thermodynamics aid the understanding of building performance and sustainability as part of the global and complex thermodynamic phenomena in living systems—energy is not concentrated, but it flows, increasing the flow rate of useful energy. From such an extended macroscopic perspective, this paper addresses holistic eco-systemic criteria of building performance evaluation, focusing on emergy (spelled with an "m") and information—the two critical indices of extensive and intensive analysis. Emergy aggregates the utmost and upstream energetic impacts, whereas information evaluates the structural pattern of the energy-flow distribution. These indices are theoretically correlated under the principles of ecological energy transformation and are often practically compatible. To clarify the definitions and appropriate scientific contexts of the new indices for environmental building studies, we review information theory, ecological theorems, and a few pioneering studies. Emergy and information have a great potential for advanced environmental building analysis, but building-scale implementation of emergy, information, and system principles remains a scientific challenge. The findings call for further research into the improvement of building-specific emergy/information data and reliable evidence of the analogy between building and open living systems.

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Uncertainty characterization of building emergy analysis (BEmA)

Cited by 36 publications

References 25 publications

Organic vegetables from community-supported agriculture in Italy: Emergy assessment and potential for sustainable, just, and resilient urban-rural local food production

Organic vegetables from community-supported agriculture in Italy: Emergy assessment and potential for sustainable, just, and resilient urban-rural local food production

A review of uncertainty analysis in building energy assessment

Beyond Energy Efficiency in Building Sustainability: A Review of Emergy and Information for Systemically Characterizing Building Performance

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