Introduction

To remedy the problem of global warming that has been an international issue since the 1980s, United Nations Framework Convention on Climate Change (UNFCC) was announced in 1992 and lots of environmental regulations have been established since then. According to World Energy Outlook reported by International Energy Agency, Korea was ranked ninth in the amount of CO₂ emission (500,009 thousand tons) and ranked second in the yearly rate of increase as 198.7%, which was such disgraceful as the second largest after China. In addition, the emission of greenhouse gases increased by 80.7% in the construction business of Korea while it decreased by 3% in that of the developed countries. The recent situation has shown that changing the domestic industry of construction is the most urgent matter [1, 2]. 2030 NDC(2030 Nationally Determined Contribution) are intermediate goals for the realization of carbon neutrality by 2050, determined by the participating nations themselves, based on the Paris Agreement. The Republic of Korea plans to reduce its GHG emissions by 40%, by 2030, compared to the levels in 2018 [3, 4, 5]. The government, as a measure to overcome the situation, has implemented a project of “2050 Carbon Neutrality of the Republic of Korea” through the green growth national strategies and plan and has declared solemn pledge for green growth by setting up a 2050 national goal for greenhouse gas reduction [6, 7, 8]. Carbon Neutrality is our nation-wide vision and new global paradigm. Preparing for the transition into a carbon-neutral society is of the utmost importance. We need an implementation system to promote the transition into a carbon-neutral society in all fields, not only the economy and industry, but across the entire society. However, most of the environmental regulations are still recommendatory and such measures as criteria for CO₂ reduction and methods to quantify the emission are incomplete even though CO₂ has been given much attention as the main culprit of global warming [9, 10, 11].

This study aimed to make quantitative assessment of the amount of CO₂ emission in the construction industry, through the regulations on construction environment being currently enforced in Korea. For that, it made research into the relationship between the amount of CO₂ reduction and Energy Performance Index (EPI) provided in Standards for energy conservation and derived a regression equation. The method of research is as follows.

Of the regulations on construction environment being enforced in Korea, those strictly observed and applied to a wide range were found. Standards for energy conservation and methods to calculate EPI points were reviewed and a reference building was selected. A building energy interpretation program was used in simulating the amount of CO₂ emission from the building selected as an object of assessment. Based on the assessment results, regression analysis was carried out on the relationship between the amount of CO₂ reduction and the rise in the EPI score, and then a relational expression was drawn.

Theoretical Consideration on Building Energy Assessment

Standards for Energy Conservation

The standards for energy saving of domestic buildings are based on Building Code, Law for Rationalization of Energy Use and so on, and ‘Energy Consumption of Buildings and Usage of Waste Materials’ (Article 59 of Building Code) and ‘Prevention of Thermal Loss of Buildings’ (Article 21 of Regulations for Facility Standards of Buildings, Etc.) have been implemented. Of measures to regulate the energy performance of buildings to a specific level for the sake of energy saving, Standards for energy conservation control an overall energy performance of a structure at the stage of designing and allows a flexible design of the structure, whatever techniques a designer use, if a specific level of energy performance is secured. The system of submitting a ‘Plan for Energy Saving’ has been implemented to buildings that consume a considerable amount of energy since 1985. EPI, which is to regulate the aggregate amount of energy consumption, was put into effect in 1995, and Standards for energy conservation were revised at the time. ‘Standards for energy conservation in Buildings’ revised and announced in 2001 include general provisions, compulsory matters on Standards for energy conservation and an EPI review report. In particular, when the total score on the EPI review report is larger than 60 points, the design of a building is judged to be suitable. Submitted design plans and other documents are reviewed when a design is scored per item of the EPI review report [12].

Energy Performance Index

Energy Performance Index (EPI) is a measure to regulate energy performance of a building to a specific level for the purpose of energy saving. Energy performance of a building is scored according to EPI on a plan for energy saving. The amount of energy consumption of a building is set up simply as ‘100’ and the energy performance of the building is regulated against the amount of consumption, so that the system is easy to understand by whoever interested. In other words, it is just to select on a chart some of the items provided by Standards for energy conservation and to apply them in a design. In case all of the items are applied, the EPI score of the building becomes 100 points. The index helps a designer to decide what to select among techniques of energy saving in order to get more than the base score, i.e., 60 points. The systems to assess buildings with EPI that are being enforced are ‘Building Energy Rating System, 2002’, ‘Housing Performance Grading indication system, 2006’, ‘Green Building Certification System, 2006 ’ ‘Seoul City Green Building, 2007 ’ and so on [12, 13]. Also, Seoul city amended the regulations in 2008 so that it is obligatory public buildings of smaller than 3,000 m² obtain more than 67 points in the EPI score and those of larger than 10,000 m² achieve more than 81 points. EPI is, thus, thought to be suitable for regulating the energy performance of buildings, for it enables an assessment of major energy factors in the spheres of architecture, facilities and electricity and applies to a wide range of buildings. Table 1 shows the relations between EPI and the energy saving system.

Analysis on Relationship Between EPI and CO₂

Overview

To analyze the relationship between the rise in the EPI score of a building and the amounts of reduction of energy consumption and CO₂ emission, the amount of energy consumption was derived through a building energy simulation per item and a simulation was carried on. Then, through the simulation with the visual-DOE, the amount of reduction of CO₂ emission was analyzed. The amount of CO₂ emission was measured according to the change in the amount of energy that occurred due to change in the conditions of the building. As for the unit amounts of CO₂ emission per energy source, the data provided in the guideline (proposal) for reducing CO₂ emission for Sejong city buildings were referred to. The weather data reported by Korean Solar Energy Society were converted to those fit for files of DOE-2 weather data for simulation.

Based on the assessment results, regression analysis was done on relations between the rise in the EPI score per item and the reduced amount of CO₂ emission and a relational expression was derived.

Method

The energy simulation of buildings is to calculate the amount of energy consumed by machines and electric facilities in a building and, furthermore, to estimate energy costs. Since many variables like characteristics of a building structure should be considered in the calculation, it is general to use a computer. European countries and the United States have analyzed and assessed the energy performance of buildings for efficient management of energy saving. The European Union published a memorandum on ‘Directive on the Energy Performance of Buildings on a purpose that the energy performance certification system applies to all of the structures; in the United States, the guideline for energy simulation (90.1.1- 2004 Appendix G Modeling Guideline) designated by American Society of Heating, Refrigerating and Air- Conditioning Engineers (ASHRAE) is recommended for the stages of architecture design and construction. Simulation techniques and building modeling also have been given increasing attention through the USGBC LEED (Leadership in Energy and Environmental Design) certification system. And, lots of programs on practices have been developed according to the simulation guideline and to the environment- friendly certification systems [14].

In this study, Visual DOE was used, which is often employed in research in Korea for its fast calculation. Visual DOE is one of the commercial DOE-2 programs that are developed on the basis of the essential energy interpretation algorithm, DOE-2. Since the 1960s when DOE started to be developed by the support from the Department of Energy, there has been a constant research lasting for more than 30 years, with Lawrence Berkley National Laboratory as the center of research. Visual DOE, based on such a DOE engine, is a typical dynamic energy simulation program that is able to perform energy interpretation for residential or commercial buildings in Figure 1[14, 15].

Figure 1.

Energy Simulation Assessment Process.

simulation was conducted with a 25-storied building as its object which was estimated to be a general type, for the purpose for analyzing the relationship mentioned above. The building is depicted briefly in Table 2.

A building that meets the base score, 60 points, stipulated in the Standards for energy conservation was modeled with Visual DOE. As for the number of occupants per floor area, the values used in designing air-conditioning facilities were used. ASHRAE STANDARD 90.1 “Energy Efficient Design of New Building Except Low-Rise Residential Building” was referred to for schedule, caloric value of the human body, lighting power density (LPD) and other electric power densities (EPD). ASHRAE STANDARD 62.1 was referred to for amount of ventilation. Table 3 shows the constitution of the object building. The amount of CO₂ emission was measured according to change in the amount of energy that occurred due to change in the conditions per EPI item.

Analysis of Assessment Results

The unit CO₂ emission of the target building was computed to be 177.8 kg-CO₂/㎡, which was found with the criteria consisting of 9 items of energy performance and 7 items of element technologies. As a result of the analysis of how much CO₂ is reduced as the EPI score increases by 1 point from the reference score (60 points), the mean reduction of CO₂ was found to be 3.686 kg- CO₂/㎡ per unit point. Table 4 shows the results of the energy simulation with the 16 EPI items. Of the 7 items that allow the assessor to check change in performance, except those to check whether there is application or not, 3 items were found out to have great effects on the reduction of CO₂.

Analysis of Relationship

To find out the relationship, regression analysis was conducted with analysis data. The analysis was made on the 3 items of performance assessment that were found to have noted effects on the reduction of CO₂.

Before the regression analysis, the correlation between the individual factors was examined by correlation analysis. SigmaStat 3.5 of Jandel Scientific Software was used as an analysis program. As a result of the analysis, the mean heat transmission coefficient of the outer wall, the coefficient of performance (COP) of the air-conditioning facility, and the efficiency of the ventilator were found to be the variables having a significant correlation with CO₂ within the significance level of 5%. The mean heat transmission coefficient of the outer wall (Ue) had a strong positive correlation as 0.972; and the coefficient of performance (COP) of the air-conditioning facility and the efficiency of the ventilator had a strong negative correlation as 0.947 and 0.816 in Figure 2, respectively. A multiple regression analysis was carried out on the relationship between the 3 EPI items and CO₂.

Figure 2.

EPI & CO₂ Factor Scatter matrix.

Analysis of CO₂ - EPI Credit

Regression analysis was done with the 3 credits affecting the amount of CO₂ (yCO₂) emission: the heat transmission coefficient (α), the COP of the air- conditioning facility (β), and the efficiency of the ventilator (γ). The adjusted coefficient of determination (R²) of the model was 86.3%. All the variables were found to be significant as the p-value was less than 0.05 and the t value was more than 2 in all of the variables. And, there was no multi-collinearity as Tol>0.1 and VIF<10.

Analysis of CO₂ EPI Score

A regression equation of a EPI score was derived with the major items, but multi-collinearity was found as VIF > 10. To make up for it, the items showing the multi-collinearity were excluded and only EPI(x) and CO₂ (yCO₂) were analyzed. The coefficient of determination (R²) was 60.4%.

Conclusions

In this study, a simulation was carried out to derive a relational expression on the amount of CO₂ reduction after the rise of an EPI score, and the results of the simulation are as follows:

1.A multiple regression analysis on EPI and CO₂ was conducted to have a relational expression.

2.Those having a close relationship with CO₂ emission among the EPI items were found to be the mean heat transmission coefficient of the outer wall, the coefficient of performance (COP) of the air- conditioning facility, and the efficiency of the ventilator.

3.The unit CO₂ emission of the target building was analyzed to be 177.8 kg- CO₂/㎡. The amount of CO₂ reduction when the EPI score increases by 1 point from the base score (60 points) was averagely 3.686 kg- CO₂/㎡ per unit point.

Since the above is the results of a simulation with a virtual building, there might be difference in the amount of CO₂ reduction according to the scale of a building, purpose of a facility or characteristics of operation. It is, thus, judged that further complementary research needs to be made.