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SummaryEnvironmentally extended multiregional input‐output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental‐Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3—a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply‐use tables (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.

SummaryEnvironmentally extended multiregional input‐output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the System of Environmental‐Economic Accounting (SEEA) with a high sectorial detail matched with multiple social and environmental satellite accounts. In this paper, we present the latest developments realized with EXIOBASE 3—a time series of EE MRIO tables ranging from 1995 to 2011 for 44 countries (28 EU member plus 16 major economies) and five rest of the world regions. EXIOBASE 3 builds upon the previous versions of EXIOBASE by using rectangular supply‐use tables (SUTs) in a 163 industry by 200 products classification as the main building blocks. In order to capture structural changes, economic developments, as reported by national statistical agencies, were imposed on the available, disaggregated SUTs from EXIOBASE 2. These initial estimates were further refined by incorporating detailed data on energy, agricultural production, resource extraction, and bilateral trade. EXIOBASE 3 inherits the high level of environmental stressor detail from its precursor, with further improvement in the level of detail for resource extraction. To account for the expansion of the European Union (EU), EXIOBASE 3 was developed with the full EU28 country set (including the new member state Croatia). EXIOBASE 3 provides a unique tool for analyzing the dynamics of environmental pressures of economic activities over time.

AbstractRoughly 97% of the European Union (EU) building stock is not considered energy efficient, and 75–85% of it will still be in use in 2050 (Artola et al., Boosting building renovation: What potential and value for Europe? 2016). Residential buildings account for around two thirds of final energy consumption in European buildings. The rate at which new buildings either replace the old stock or expand the total stock is about 1% per year. Similarly, the current renovation rate of existing buildings in the EU is about 1–2% of the building stock renovated each year. Renovation strategies on building levels need to be derived from a combination of energy efficiency upgrades to buildings and the use of renewable energy to decarbonize the energy supply, on a district or city scale. IEA EBC Annex 75 subtask D2 focuses on promoting cost-effective building renovation at district level combining energy efficiency and renewable energy systems, by focusing on the business models that can make implementation possible. This paper intends to provide an overview of the business model archetypes that can support the development of district demand and/or supply of energy-efficient building renovations and/or renewable energy solutions by targeting various types of stakeholders. It builds upon existing literature to gain insights into the current distributed energy business model landscape. Further, implementation strategies are identified that focus on a holistic evaluation of the expected energy and CO2 performance of the site and optimized infrastructure investment pathways.

AbstractRoughly 97% of the European Union (EU) building stock is not considered energy efficient, and 75–85% of it will still be in use in 2050 (Artola et al., Boosting building renovation: What potential and value for Europe? 2016). Residential buildings account for around two thirds of final energy consumption in European buildings. The rate at which new buildings either replace the old stock or expand the total stock is about 1% per year. Similarly, the current renovation rate of existing buildings in the EU is about 1–2% of the building stock renovated each year. Renovation strategies on building levels need to be derived from a combination of energy efficiency upgrades to buildings and the use of renewable energy to decarbonize the energy supply, on a district or city scale. IEA EBC Annex 75 subtask D2 focuses on promoting cost-effective building renovation at district level combining energy efficiency and renewable energy systems, by focusing on the business models that can make implementation possible. This paper intends to provide an overview of the business model archetypes that can support the development of district demand and/or supply of energy-efficient building renovations and/or renewable energy solutions by targeting various types of stakeholders. It builds upon existing literature to gain insights into the current distributed energy business model landscape. Further, implementation strategies are identified that focus on a holistic evaluation of the expected energy and CO2 performance of the site and optimized infrastructure investment pathways.

This paper introduces an integrative approach to hedonic house price modeling which utilizes high density 3D airborne laser scanning (ALS) data. In general, it is shown that extracting exploratory variables using 3D analysis – thus explicitly considering high-rise buildings, shadowing effects, etc. – is crucial in complex urban environments and is limited in well-established raster-based modeling. This is fundamental in large-scale urban analyses where essential determinants influencing real estate prices are constantly missing and are not accessible in official and mass appraiser databases. More specifically, the advantages of this methodology are demonstrated by means of a novel and economically important externality, namely incoming solar radiation, derived separately for each flat. Findings from an empirical case study in Vienna, Austria, applying a non-linear generalized additive hedonic model, suggest that solar radiation is significantly capitalized in flat prices. A model comparison clearly proves that the hedonic model accounting for ALS-based solar radiation performs significantly superior. Compared to a model without this externality, it increases the model’s explanatory power by approximately 13% and additionally reduces the prediction error by around 15%. The results provide strong evidence that explanatory variables originating from ALS, explicitly regarding the immediate 3D surroundings, enhance traditional hedonic models in urban environments.

This paper introduces an integrative approach to hedonic house price modeling which utilizes high density 3D airborne laser scanning (ALS) data. In general, it is shown that extracting exploratory variables using 3D analysis – thus explicitly considering high-rise buildings, shadowing effects, etc. – is crucial in complex urban environments and is limited in well-established raster-based modeling. This is fundamental in large-scale urban analyses where essential determinants influencing real estate prices are constantly missing and are not accessible in official and mass appraiser databases. More specifically, the advantages of this methodology are demonstrated by means of a novel and economically important externality, namely incoming solar radiation, derived separately for each flat. Findings from an empirical case study in Vienna, Austria, applying a non-linear generalized additive hedonic model, suggest that solar radiation is significantly capitalized in flat prices. A model comparison clearly proves that the hedonic model accounting for ALS-based solar radiation performs significantly superior. Compared to a model without this externality, it increases the model’s explanatory power by approximately 13% and additionally reduces the prediction error by around 15%. The results provide strong evidence that explanatory variables originating from ALS, explicitly regarding the immediate 3D surroundings, enhance traditional hedonic models in urban environments.