Dynamic type-cohort-time approach for the analysis of energy reductions strategies in the building stock

Vásquez, Felipe; Løvik, Amund N.; Sandberg, Nina Holck; Müller, Daniel B.

doi:10.1016/j.enbuild.2015.11.018

Cited by 65 publications

(49 citation statements)

References 49 publications

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“…System boundary According to the literature [14], three aspects are emphasized in TCT analysis: (i) types of CPGs, (ii) cohorts, and (iii) time. Types and groups correspond to the structure (typology) of CPGs.…”

Section: Legendmentioning

confidence: 99%

“…Types and groups correspond to the structure (typology) of CPGs. Time refers to the modeling time range-one year or several years-and whether this corresponds to According to the literature [14], three aspects are emphasized in TCT analysis: (i) types of CPGs, (ii) cohorts, and (iii) time. Types and groups correspond to the structure (typology) of CPGs.…”

Section: Legendmentioning

confidence: 99%

“…Besides, the increasing installed capacity of renewable energy squeezed the development space of thermal power and generated environmental benefits [12,13], which should be involved in such studies. In the paper, we analyze the structure evolution of China's CPG stock from 1980 to 2018 with Type-Cohort-Time (TCT) approach, and estimate the environmental benefits of structure evolution in history and future with the Logarithmic Mean Divisia Index (LMDI) method.The TCT model is able to handle the complexity and heterogeneity of stock evolution by breaking down the inventory into its basic dimensions, which are characterized by the different sizes, driving forces, and techniques [14]. Environmental impacts of stock evolution are of concern for strategy and policy-making as important references.…”

mentioning

confidence: 99%

“…The TCT model is able to handle the complexity and heterogeneity of stock evolution by breaking down the inventory into its basic dimensions, which are characterized by the different sizes, driving forces, and techniques [14]. Environmental impacts of stock evolution are of concern for strategy and policy-making as important references.…”

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confidence: 99%

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Environmental Benefits of Stock Evolution of Coal-Fired Power Generators in China

Xiao

et al. 2019

Sustainability

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The evolution of in-use coal-fired power generators (CPGs) in China has been impelled by a series of policies called Developing Large Units and Suppressing Small Ones in recent decades. However, it remains highly uncertain about the contribution of the evolution on air pollution reductions at different stages. Models used to assess the effects of CPGs’ evolution often do not account for the different boundary conditions related to units composition and age structure of the existing CPGs, and lifetime expectancy, which hinders effective strategy development and realistic target setting. This study employs a dynamic Type-Cohort-Time (TCT) stock-driven model and Logarithmic Mean Divisia Index (LMDI) technique, to investigate the structural evolution of China’s CPGs as well as its environmental effects from 1980 to 2050. We consider generator-specific characteristics, lifetime-related issues and alternative techniques in the historical and scenario analysis. The main results are as follows: the environmental benefits of structural evolution were limited, compared with the changes in emission coefficient due to technical renovation. However, scenario analysis indicates that structural adjustment by elimination of outdated CPGs and construction of new ones in future will undertake emission reduction commitments, since the potentials of other approaches decrease. Uncertainty analysis further demonstrates that promoting elimination of small CPGs and substituting them with renewable energy will bring more emission reductions. The key findings can support policy-making on elimination, construction, and emissions abatement of CPGs.

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Section: Legendmentioning

confidence: 99%

Section: Legendmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Environmental Benefits of Stock Evolution of Coal-Fired Power Generators in China

Xiao

et al. 2019

Sustainability

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“…This dynamic segmented model has been further applied to simulate the development of dwelling stocks in 11 European countries (Sandberg et al 2016a). Additionally, a dynamic stock-driven material model has been widely exploited to simulate and forecast the evolution of building stocks in several other countries, such as the United States (Moura et al 2015), Chile (Gallardo et al 2014), Germany and Czech Republic (Vásquez et al 2016), and Japan (Hatayama and Tahara 2016).…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Dynamic Material Flow Analysis Model for Chinese Urban Housing Stock

Cao

Shen

Zhong

et al. 2017

J of Industrial Ecology

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Summary The stock‐driven dynamic material flow analysis (MFA) model is one of the prevalent tools to investigate the evolution and related material metabolism of the building stock. There exists substantial uncertainty inherent to input parameters of the stock‐driven dynamic building stock MFA model, which has not been comprehensively evaluated yet. In this study, a probabilistic, stock‐driven dynamic MFA model is established and China's urban housing stock is selected as the empirical case. This probabilistic dynamic MFA model has the ability to depict the future evolution pathway of China's housing stock and capture uncertainties in its material stock, inflow, and outflow. By means of probabilistic methods, a detailed and transparent estimation of China's housing stock and its material metabolism behavior is presented. Under a scenario with a saturation level of the population, urbanization, and living space, the median value of the urban housing stock area, newly completed area, and demolished area would peak at around 49, 2.2, and 2.2 billion square meters, respectively. The corresponding material stock and flows are 79, 3.5, and 3.3 billion tonnes, respectively. Uncertainties regarding housing stock and its material stock and flows are non‐negligible. Relative uncertainties of the material stock and flows are above 50%. The uncertainty importance analysis demonstrates that the material intensity and the total population are major contributions to the uncertainty. Policy makers in the housing sector should consider the material efficiency as an essential policy to mitigate material flows of the urban building stock and to lower the risk of policy failures.

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Energy simulation and LCA for macro-scale analysis of eco-innovations in the housing stock

Allacker

Castellani

Baldinelli

et al. 2018

Int J Life Cycle Assess

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Purpose Energy consumption of buildings is one of the major drivers of environmental impacts. Life cycle assessment (LCA) may support the assessment of burdens and benefits associated to eco-innovations aiming at reducing these environmental impacts. Energy efficiency policies however typically focus on the meso-or macro-scale, while interventions are typically taken at the micro-scale. This paper presents an approach that bridges this gap by using the results of energy simulations and LCA studies at the building level to estimate the effect of micro-scale eco-innovations on the macro-scale, i.e. the housing stock in Europe. Methods LCA and dynamic energy simulations are integrated to accurately assess the life cycle environmental burdens and benefits of eco-innovation measures at the building level. This allows quantitatively assessing the effectiveness of these measures to lower the energy use and environmental impact of buildings. The analysis at this micro-scale focuses on 24 representative residential buildings within the EU. For the upscaling to the EU housing stock, a hybrid approach is used. The results of the micro-scale analysis are upscaled to the EU housing stock scale by adopting the eco-innovation measures to (part of) the EU building stock (bottom-up approach) and extrapolating the relative impact reduction obtained for the reference buildings to the baseline stock model. The reference buildings in the baseline stock model have been developed by European Commission-Joint Research Centre based on a statistical analysis (top-down approach) of the European housing stock. The method is used to evaluate five scenarios covering various aspects: building components (building envelope insulation), technical installations (renewable energy), user behaviour (night setback of the setpoint temperature), and a combined scenario. Results and discussion Results show that the proposed combination of bottom-up and top-down approaches allow accurately assessing the impact of eco-innovation measures at the macro-scale. The results indicate that a combination of policy measures is necessary to lower the environmental impacts of the building stock to a significative extent. Conclusions Interventions addressing energy efficiency at building level may lead to the need of a trade-off between resource efficiency and environmental impacts. LCA integrated with dynamic energy simulation may help unveiling the potential improvements and burdens associated to eco-innovations.

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Dynamic type-cohort-time approach for the analysis of energy reductions strategies in the building stock

Cited by 65 publications

References 49 publications

Environmental Benefits of Stock Evolution of Coal-Fired Power Generators in China

Environmental Benefits of Stock Evolution of Coal-Fired Power Generators in China

A Probabilistic Dynamic Material Flow Analysis Model for Chinese Urban Housing Stock

Energy simulation and LCA for macro-scale analysis of eco-innovations in the housing stock

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