The increased popularity of building information modeling (BIM) for application in the construction of eco-friendly green buildings has given rise to techniques for evaluating green buildings constructed using BIM features. Existing BIM-based green building evaluation techniques mostly rely on externally provided evaluation tools, which pose problems associated with interoperability, including a lack of data compatibility and the amount of time required for format conversion. To overcome these problems, this study sets out to develop a template (the “green template”) for evaluating the embodied environmental impact of using a BIM design tool as part of BIM-based building life-cycle assessment (LCA) technology development. Firstly, the BIM level of detail (LOD) was determined to evaluate the embodied environmental impact, and constructed a database of the impact factors of the embodied environmental impact of the major building materials, thereby adopting an LCA-based approach. The libraries of major building elements were developed by using the established databases and compiled evaluation table of the embodied environmental impact of the building materials. Finally, the green template was developed as an embodied environmental impact evaluation tool and a case study was performed to test its applicability. The results of the green template-based embodied environmental impact evaluation of a test building were validated against those of its actual quantity takeoff (2D takeoff), and its reliability was confirmed by an effective error rate of ≤5%. This study aims to develop a system for assessing the impact of the substances discharged from concrete production process on six environmental impact categories, i.e., global warming (GWP), acidification (AP), eutrophication (EP), abiotic depletion (ADP), ozone depletion (ODP), and photochemical oxidant creation (POCP), using the life a cycle assessment (LCA) method. To achieve this, we proposed an LCA method specifically applicable to concrete and tailored to the Korean concrete industry by adapting the ISO standards to suit the Korean situations.

Eco-friendly building designs that use building information modeling (BIM) have become popular, and a variety of eco-friendly building assessment technologies that take advantage of BIM are being developed. However, existing building environmental performance assessment technologies that use BIM are linked to external assessment tools, and there exist compatibility issues among programs; it requires a considerable amount of time to address these problems, owing to the lack of experts who can operate the programs. This study aims to develop eco-friendly templates for assessing the embodied environmental impact of buildings using BIM authoring tools as part of the development of BIM-based building life cycle assessment (LCA) technologies. Therefore, an embodied environmental impact unit database was developed, for major building materials during production and operating stages, to perform embodied environmental impact assessments. Moreover, a major structural element library that uses the database was developed and a function was created to produce building environmental performance assessment results tables, making it possible to review the eco-friendliness of buildings. A case study analysis was performed to review the feasibility of the environmental performance assessment technologies. The results showed a less than 5% effective error rate in the assessment results that were obtained using the technology developed in this study compared with the assessment results based on the actual calculation and operating stage energy consumption figures, which proves the reliability of the proposed approach.

Multiple nations have implemented policies for greenhouse gas (GHG) reduction since the 21st Conference of Parties (COP 21) at the United Nations Framework Convention on Climate Change (UNFCCC) in 2015. In this convention, participants voluntarily agreed to a new climate regime that aimed to decrease GHG emissions. Subsequently, a reduction in GHG emissions with specific reduction technologies (renewable energy) to decrease energy consumption has become a necessity and not a choice. With the launch of the Korean Emissions Trading Scheme (K-ETS) in 2015, Korea has certified and financed GHG reduction projects to decrease emissions. To help the user make informed decisions for economic and environmental benefits from the use of renewable energy, an assessment model was developed. This study establishes a simple assessment method (SAM), an assessment database (DB) of 1199 GHG reduction technologies implemented in Korea, and a machine learning-based GHG reduction technology assessment model (GRTM). Additionally, we make suggestions on how to evaluate economic benefits, which can be obtained in conjunction with the environmental benefits of GHG reduction technology. Finally, we validate the applicability of the assessment model on a public building in Korea.

Purpose: Many countries have implemented policies to reduce greenhouse gas (GHG) emissions in public buildings, emphasizing the leading role of the public sector. In Korea, in order to achieve a 30% reduction in GHG emissions by 2030, public agencies must set annual targets or quotas. However, the lack of experts and support are the biggest obstacles to achieving this reduction target. Methods: This study constructed a GHG evaluation database (DB) and Data set based on energy end uses, GHG reduction technology with the aim of decision making about GHG reduction with minimal building information and limited expert knowledge. The GHG evaluation DB was built using data from the Commercial Building Energy Consumption Survey (CBECS), an energy consumption survey of 6,720 public and commercial buildings by the US Department of Energy. In addition, a DB for evaluating the reduction amount of greenhouse gas reduction technology was established with reference to 1,206 greenhouse gas reduction technology application projects by the Korea Energy Survey. The database was used for constructing data set, we developed a machine learning-based GHG reduction decision support model. Result: Additionally, the case study of domestic public buildings, the economic and environmental benefit of applying greenhouse gas reduction technology were evaluated. The evaluated building can reduce about 111 tonCO2-eq and convert it into economic profit of 36 million won, confirming the applicability of the model.