Propose of Mix Design Method for CO 2 Reduction Concrete Using the Regression Analysis

As argued by ‘Declaration of Concrete Environment (2010)’ of Korea and ‘Declaration of Asian Concrete Environment (2011)’ of six Asian countries, concrete as a single material has lately shown extremely large impact on environmental issues such as climate change. Assessment of environmental impact from concrete material and production has considerable importance. Concrete is a major material used in the construction industry that emits a large amount of substances with environmental impacts during its life cycle. Accordingly, technologies for the reduction in and assessment of the environmental impact of concrete from the perspective of Life Cycle Assessment must be developed. At present, the studies in relation to greenhouse gas emission from concrete are being carried out globally as a countermeasure against climate change. In this study, CO2 reduction concrete mix design algorithm was designed using correlation analyses, and its carbon emission and cost reduction performances were assessed. Using correlation analyses, the concrete strength, water/cement (w/c) ratio and fine aggregate/total aggregate (s/a) ratio, and CO2 emissions were identified as major variables of concrete mix design that influenced other variables. Also, this study aims to evaluate the CO2 emission reduction performance of the algorithm-deduced CO2 reduction concrete mix design, and therefore, the CO2 emissions of the CO2 reduction concrete mix design are compared with those of the actual concrete mix design applied to the construction of the office building A in South Korea.


Introduction
With the increasing interest in climate changes worldwide, however, the development of concrete mix designs that consider the reduction of CO2 emissions, in addition to the physical properties such as strength and durability, has become necessary [1].
The major construction materials accounting for more than 90% of building greenhouse gas (GHG) emissions include concrete, rebar, insulation, concrete brick, glass and gypsum board [2].Among the CO2 emissions generated by these major construction materials, concrete accounts for 70% [3].
Several studies have been conducted to determine concrete mix designs through optimization methods.Majority of these studies are concerned with the estimation of target strength or the determination of high-strength and lightweight concrete mix designs [4].In Korea, standard specifications for ready-mixed concrete (RMC) consider the criteria of strength, durability, water tightness, workability, water/cement (w/c) ratio, slump, and fine aggregate/total aggregate (s/a) ratio [5].However, a standard for carbon-dioxide (CO2) emission by RMC has not yet been set.A CO2 emission standard is difficult to establish, mainly because there are numerous variables of the concrete mix influencing CO2 emissions, and the physicochemical compositions of materials used to prepare the mix vary depending on their source and their proportions in the mix.Consequently, a large number of variables must be considered in order to determine concrete mix designs that reflect the environmental load of CO2 emissions, and it is practically impossible to derive a mathematical model that can accurately define the outcome of the interactions of all these variables.To overcome these limitations, this study proposed a CO2 reduction concrete mix design algorithm by performing correlation analyses to rationally minimize CO2 emissions.This study aims to evaluate the CO2 emission reduction performance of the algorithm-deduced CO2 reduction concrete mix design, and therefore, CO2 emissions of the concrete mix design are compared with those of the actual concrete mix design applied to the office building in South Korea.

Literature review
To develop a mix design method for concrete to reduction CO2 emission, this chapter presented methodologies about mix design technique and life cycle CO2 emission assessment etc.
Trend of research was analyzed as below.
The goal that expected from Raharjo et al. research is to obtain the optimal material composition of the mixture that produce the maximum compressive strength but cheaper and competitive in price [6].Berndt et al. has shown that selection of concrete constituents and appropriate mix design can be used to minimize CO2 emissions associated with large wind turbine foundations without compromising strength and performance requirements [7].Andreas et al. aimed at empirically identifying a material parameter (or a number of parameters) that defines the carbonation resistance of mortar and concrete produced with cements containing mineral additions [8].
Peter et al. introduced the commonly used methods of mix design (mixture proportioning) from the United States, and the United Kingdom.The basic principles that are common to all systems are discussed, and then the two methods are considered in detail, stage by stage [9].Talha et al. presented a systematic approach for selecting mix proportions for alkali activated fly ash-based geopolymer concrete (GPC).The proposed mix design process is developed for low calcium Class F fly ash activated geopolymers using sodium silicates and sodium hydroxide as activator solutions [10].Kim et al. evaluated the appropriateness and the reduction performance of the low-carbon-emission concrete mix design system and the deduced mix design results using an evolutionary algorithm (EA), the optimal mix design method, which minimizes the CO2 emission of the concrete mix design [11].Ramin et al. presented the experimental results of an on-going research project to produce geopolymer lightweight concrete using two locally available waste materials -low calcium fly ash (FA) and oil palm shell (OPS) -as the binder and lightweight coarse aggregate, respectively [12].Linoshka et al. investigated a cleaner production of pervious concrete containing waste FA, a solid waste unless otherwise utilized, in combination with other admixtures of nano-iron oxide (NI) and WR.The mix design with the percentages of water-to-binder (w/b), FA/B, NI/B and WR/B was optimized for the desired permeability and compressive strength [13].Hong et al. proposed an integrated model for assessing the cost and CO2 emission (IMACC) at the same time.IMACC is a model that assesses the cost and CO2 emission of the various structural-design alternatives proposed in the structural-design process.To develop the IMACC, a standard on assessing the cost and CO2 emission generated in the construction stage was proposed, along with the CO2 emission factors in the structural materials, based on such materials' strengths [14].

Algorithm process
The major features of the CO2 reduction concrete mix design algorithm are its inputs: strength, water/binder (w/b) ratio, sand aggregate/total aggregate (s/a) ratio, and the proportion of admixture (%), and the resulting concrete mix design, which exhibits the intended physical properties and required reduction in CO2 emission.To develop the algorithm, we first compiled a database of different concrete mix designs provided by Korean RMC suppliers.Key influential factors -CO2 emissions and cost-effectiveness -were then extracted from the correlation analyses of the different concrete mix designs.Finally, regression analyses were performed on the derived influential factors to deduce equations expressing the relationship between CO2 emissions, binder, and fine aggregates.
The regression equations were derived using four different concrete mix designs: plain, with fly ash (FA), ground granulated blast furnace slag (GGBS), and both FA and GGBS.

Establishment of a concrete mix design database
A total of 800 concrete mix designs supplied by 10 RMC suppliers in Korea were investigated as shown in Table 1.The concrete mix designs had varying strength levels (18,21,24,27,30,35,40,50, and 60 MPa) with variables such as plain cement, mixing water, coarse and fine aggregates, and admixtures.Further, the size of coarse aggregate, strength, and w/b and s/a ratios were investigated.Approximately 800 combinations of concrete strength and admixture type (GGBS/FA/GGBS+FA) were included in the database.

CO2 emissions assessment
A system boundary was established for the life cycle CO2 emission evaluation of concrete.The system boundary was selected as the product stage of concrete (cradle to gate) based on ISO 14044 [20] and ISO 21930 [21].The product stage of concrete is divided into the raw material stage, the transportation stage, and the manufacturing stage [22].The raw material stage refers to CO2 emission during the production of major components of concrete such as cement, aggregate, and water.The transportation stage's CO2 emission occurs during the transportation of raw materials to the readymixed concrete manufacturing plant.The manufacturing stage's CO2 emission comes from electricity and oil used in the concrete batch plant.The system boundary for life cycle CO2 emission of concrete is shown in Figure 1.Also, Figure 2 is the production process of concrete.CO2 emissions of concrete mix designs were evaluated by calculating the cumulative product of the amount of each material in the concrete mix and the intensity of CO2 emission from the respective materials.The intensities of CO2 emissions were drawn from the life cycle inventory (LCI) databases used in Korea [15] and other countries [16].Intensities of CO2 emissions from plain cement, mixing water, and coarse and fine aggregates were drawn from the Korean LCI database, whereas the intensities for admixtures (GGBS, FA, and chemical admixtures), for which no Korean LCI databases were available, international LCI databases were used as shown in Table 2 [17,18].

Correlation analysis
Correlation analyses [19] were performed considering 13 variables, including target strength (MPa) of the concrete mix design, w/b and s/a ratios (%), slump (mm), plain cement, mixing water, fine aggregate, and admixture contents (kg/m 3 ), as well as CO2 emissions (kg-CO2/m 3 )' and cost (KRW/m 3 ) [20].Variables w/b and s/a ratios, slump, CO2 emissions, and cost were found to be highly correlated with concrete strength as shown in Table 3.For instance, with increase in concrete strength, the w/b ratio decreased, whereas aggregate content, CO2 emissions, and cost increased.Variables highly correlated with the w/b ratio were concrete strength, plain cement content, slump, s/a ratio, CO2 emissions, and cost.Variables highly correlated with plain cement content were concrete strength, w/b and s/a ratios, fine aggregate content, slump, CO2 emissions, and cost.Variables highly correlated with fine aggregate content were strength, w/b and s/a ratios, plain cement content, CO2 emissions, and cost.Variables highly correlated with CO2 emissions were strength, the w/b and s/a ratios, plain cement and fine aggregate contents, slump, and cost.For instance, with increase in CO2 emissions, concrete strength, and plain cement and fine aggregate contents increased, whereas cost and the w/b ratio decreased.Variables highly correlated with cost were concrete strength, w/b and s/a ratios, plain cement and fine aggregate contents, slump, and CO2 emissions.The unit prices of concrete materials were excluded from the analyses because they significantly varied from one company to another.Thus, from the 12 different variables that were subject to correlation analyses, four variables were found to be most highly correlated: concrete strength (MPa), w/b (%), s/a (%), and CO2 emissions.Regression equations were then deduced from these four key variables as shown in Figure 2.

Derivation of concrete mix design regression equations
The key variables that were found to have high degrees of correlation were subjected to regression analyses.Regression equations expressing relationships between the amounts of CO2 emissions, binder, and the fine aggregate were derived based on the presence of admixture in the concrete mix design, i.e., in four variations: without admixture, with FA or GGBS only, and with both FA and GGBS [21].

Equation for CO2 emission
A regression equation was derived to deduce the CO2 emission depending on the target strength (MPa), w/b(water/binder ratio), s/a(sand aggregate/total aggregate ratio), admixture mix ratio(%).To this end, we derived a regression equation, thereby setting the w/b ratio as the dependent variable and the concrete strength, w/b(%), s/a(%) and admixture mixing ratio(%) as independent variables.Using the amount of CO2 emission calculated from this equation, the binder amount can be deduced.

Equation for binder amount (B)
A regression equation was derived to deduce the binder amount based on the target strength (MPa), w/b ratio, S/a ratio and CO2 emission.To this end, we derived a regression equation, thereby setting the content of binder as the dependent variable and the concrete strength, w/b, s/a, admixture mixing ratio and CO2 emission as independent variables.Using the binder amount calculated from this equation and the CO2 emission calculated from the previous equation and the input information, mixing water content can be deduced.A regression equation was derived to deduce fine aggregate content based on the target strength (MPa), w/b ratio, s/a ratio and admixture mixing ratio.To this end, we derived a regression equation, thereby setting the fine aggregate content as the dependent variable and the concrete strength, w/b, s/a, binder and CO2 emission as independent variables.Using the fine aggregate content calculated from this equation and the s/a ratio calculated from the previous equation and the input information, the coarse aggregate content can be deduced.
[Plain] The amount of chemical admixtures (kg/m 3 ) was generally applied as 0.5 ~ 1% of the amount of ordinary normal cement.

Input of assessment information
As shown in Fig. 3, assessment information is input first to derive a CO2 reduction concrete mix design via correlation analyses.Inputs include concrete strength, w/b and s/a ratios, and admixture type and rate (%).The assessment information input is directly transferred to the matching regression equation embedded into the system [22].

Binder deduction (kg/m 3 )
The assessment information input is transferred to the regression equation for CO2 emissions, which significantly vary with admixture content or its absence.The amount of CO2 emissions thus deduced is transferred to the regression equation for deducing binder content, and the admixture type and rate yield the plain cement and admixture contents.

Water deduction (kg/m 3 )
From the binder content derived in 4.2 and the w/b ratio input in 4.1, the mixing water content of the concrete mix design is automatically deduced.

Fine aggregate deduction (kg/m 3 )
The values deduced from the assessment information input in 4.1, and those deduced from the regression equation relating CO2 emissions and binder content are transferred to the regression equation for deducing fine aggregate content of the target concrete mix design.

Coarse aggregate deduction (kg/m 3 )
Fine aggregate contents deduced from 4.4 and the s/a ratio input in 4.1 serve as the basis for deducing coarse aggregate content of the target concrete mix design.

Chemical admixture deduction (kg/m 3 )
Chemical admixture content is deduced using the regression equation that relates binder and mixing water contents in the range of 0.6-1.4%.This is because an adequate range was set via correlation analysis of the concrete mix design determined.Figure 4 outlines the results of the reliability test of the concrete mix design derived using the CO2 reduction algorithm.The test was performed by feeding the concrete strength, w/b and s/a ratios, and admixture type and rate of approximately 800 mix designs as inputs to the proposed algorithm, followed by the analysis of the average values of CO2 emissions, and the w/b and s/a ratios of the plain cement mix design.These average values were then compared with those of the model mix design constructed using the CO2 reduction mix design system.Analyses were conducted on plain (N = 108), FA (N = 558), GGBS (N = 17), and FA + GGBS (N = 103) algorithm-deduced CO2 reduction mix designs.
As shown in Fig. 4(a), the reliability test revealed that 98 out of 108 plain cement mix designs had deviations of ≤ 10% from the model mix design in terms of CO2 emissions.The deviations for the w/b and s/a ratios were ≤ 10% in 103 plain cement mix designs.Of these, 70 mix designs showed deviations of ≤ 5% for the w/b ratio and 92 mix designs showed the same deviation for the s/a ratio.As shown in Fig. 4(b), the reliability test results for FA mix designs revealed that 522 out of 558 mix designs had deviations of ≤ 10% for CO2 emissions.In particular, deviations of ≤ 5% were observed for the w/b ratio of 435 mix designs and for the s/a ratio of 544 mix designs.This demonstrated high reliability.Fig. 4(c) shows the reliability test results of GGBS mix designs; 15 out of 17 mix designs showed deviations of ≤ 10% for CO2 emissions, and 15 and 17 mix designs showed deviations of ≤ 10% in the w/b and s/a ratios, respectively.High reliability was demonstrated as all 17 mix designs showed a deviation of ≤ 10% for the s/a ratio.Fig. 4(d) shows the reliability test results of FA+GGBS mix designs; 96 out of 103 mix designs showed deviations of ≤ 10% for CO2 emissions, and 97 and 103 mix designs showed deviations of ≤ 10% for w/b and s/a ratios, respectively.With all 103 mix designs showing deviations of ≤ 10% for s/a ratios, FA+GGBS mix designs demonstrated very high reliability.
The results of the overall analysis revealed that CO2 emissions, and the w/b and s/a ratios of the algorithm-deduced v mix designs showed low error rates (%), compared with those of the model mix design.Although there were cases where the average CO2 emissions, and the w/b and s/a ratios of the CO2 reduction mix designs showed deviations of ≥ 10%, compared with those of the model mix design, yet the former accounted for ≤ 7% of all cases.The reliability of the concrete mix design deduced by the CO2 reduction concrete mix design algorithm was thus verified.

Case study
It is a 12-storey building with five underground floors and has a gross floor area of 462,000 m 2 .Information was collected on material amounts for all of the seven standard concrete types, which were used in the construction of the building and were supplied by eight RMC producers in Korea.Based on this information, CO2 emissions and cost-effectiveness were evaluated.Furthermore, a CO2 reduction concrete mix design was deduced under the same conditions, and the analysis and comparison of CO2 emissions and cost-effectiveness of the CO2 reduction mix design and the actual mix design were performed.

Method
Table 6 outlines the results of the assessment of CO2 emissions and cost-effectiveness of the actual mix design for the material amounts of each standard concrete used in the construction of the example building.

Analyses of CO2 emissions and cost-effectiveness
As shown in Table 7, the concrete used for the construction of the example building were analyzed and assessed.The assessment revealed that 35,013,372 and 32,395,708 kg of CO2 were emitted from the actual mix design and the CO2 reduction mix design, respectively.CO2 emitted from the CO2 reduction mix design was 7.48% less than that emitted from the actual mix design as indicated in Table 8.In particular, the standard types 25-18MPa-150 and 25-24MPa-210 demonstrated reductions of 11% and 8%, respectively, in case of the CO2 reduction mix design, whereas the standard types 25-45MPa-600 and 25-48MPa-600 showed similar CO2 emissions in case of both the actual and CO2 reduction mix designs.Furthermore, the analysis of cost-effectiveness revealed that it was possible to reduce the material costs by approximately 1.5% when the CO2 reduction mix design was applied against the total material cost of 9,567,240,410 KRW for the actual mix design as indicated in Table 9.For standard types 25-24MPa-210 and 25-30MPa-150, which are in high demand, cost reductions of 50,982,102 and 56,058,408, respectively, were assessed to be possible.As shown in Figs. 5 and 6, the main factors influencing CO2 emissions of the actual and lowcarbon mix designs were identified to be the mix amounts of plain cement, GGBS, FA, and fine aggregate.In the case of the actual mix design, an increase in strength level tended to increase the mix amounts of plain cement and admixture (GGBS and FA) and the decrease in that of the fine aggregate.However, in the case of the concrete mix design to reduction CO2 emission, an increase in strength level did not affect the mix amounts of plain cement and admixtures, but slightly increased the mix amount of fine aggregate.In addition, as shown in Table 11, the low-carbon mix design outperformed the actual mix design in terms of cost-effectiveness, by demonstrating reduction rates ranging between 0.9% and 2.1%.In the actual mix design, an increase in the strength level tended to increase the mix amounts of plain cement and admixture, while that of fine aggregate tended to decrease.This resulted in increased costs because of the increased amount of plain cement and admixture.However, the lowcarbon mix design did not incur such increase in costs because the mix amounts of materials were maintained at the minimum level at which they satisfied the targeted physical properties.

Discussion and limitations
The significance and limitations of the findings in this study are presented, and possible future directions are discussed.
The importance of reducing the CO2 emission of concrete is being recognized.The findings of this study are significant in that can be applied to concrete industry in South Korea.Moreover, method reducing CO2 emission of concrete can be conducted, and the strategy for reducing the embodied environmental impact can be sought.
Limitations of this study include 1. Consideration of assessment factors for durability (service life), 2. Experimental verification of the alternative concrete mix design to reduction CO2 emission.
1. Consideration of assessment factors for durability (service life), In this study, deterioration phenomena was not considered as an assessment factor for durability of concrete in order to develop a CO2 reduction mix design algorithm.Since durability (service life) of concrete differs according to deterioration phenomenon, differences may arise by admixture (Ground granulated blast slag, GGBS) mixing on the same type of concrete.For example, when durability assessment is done only based on carbonation, durability (service life) of concrete is slightly reduced by mixing of admixtures (GGBS).On the contrary, chloride damage can show increase in durability (service life) of concrete from mixing of admixtures according to previous research.
Therefore, durability (service life) can be changed by admixture ratio (%) of concrete with the same mix design depending on the type of deterioration phenomenon.Through future study, durability (service life) of concrete will be assessed by considering various deterioration phenomena such as carbonation and chloride damage at the same time.
2. Experimental verification of the mix design method to reduction CO2 emission.The mix design method to reduction CO2 emission was proposed in this study.However, it would be necessary to verify, through experiment, physical durability performance (compressive strength, carbonation and chloride etc.) of the mix design.In the future, mix design of concrete derived using the method reducing CO2 emission will be conducted the compressive strength and carbonation etc. experiments.In this study, a CO2 reduction concrete mix design algorithm was designed using correlation analyses, and its carbon emission and cost reduction performances were assessed.

Conclusion
Using correlation analyses, the concrete strength, w/b and s/a ratios, and CO2 emissions were identified as major variables of concrete mix design that influenced other variables.The key variables were then subjected to regression analyses, and the regression equations for CO2 emissions and binder and fine aggregate amounts were derived.
Using the derived regression equations, we developed the CO2 reduction concrete mix design algorithm and system.The reliability of the proposed algorithm was verified by demonstrating that the CO2 reduction mix design exhibited a very low error rate compared with the model mix design constructed previously.
It was discovered that the actual mix design applied to the construction of the example building emitted 35,013,372 kg of CO2, while CO2 emitted by the CO2 reduction mix design was only 32,395,708.Thus, the CO2 emitted in the case of the CO2 reduction mix design was approximately 7.48% less than that emitted in case of the actual mix design.It was also discovered that it was possible to reduce material costs by approximately 1.5% when the CO2 reduction mix design was applied, as opposed to the total material costs of 9,567,240,410 KRW in the case of the actual mix design.

Figure 1 .Figure 2 .
Figure 1.System boundary of the life cycle assessment (LCA) for concrete.
(a) Analysis of the concrete strength, CO2 emissions, and plain cement content (b) Analysis of the w/b ratio, CO2 emissions, and concrete strength (c) Analysis of the w/b and s/a ratios, and plain cement content (d) Analysis of CO2 emissions, plain cement content, and the s/a ratio

Figure 3 .
Figure 3. Process flowchart of CO2 reduction concrete mix design algorithm (a) Plain mix design (b) FA mixing design (c) GGBS mixing design (d) FA+GGBS mixing design

Figure 4 .
Figure 4. Reliability test of CO2 reduction Concrete mix design

Figure 5 .Figure 6 .
Figure 5. Amount of cement and admixture by actual and CO2 reduction mix design

Table 1 .
Example of concrete mix design Database

Table 2 .
CO2 emission factor and reference

Table 3 .
Results of correlation analyses of concrete mix designs

Table 6 .
Assessment method

Table 7 .
Assessment result of CO2 emission and Cost for concrete mix design

Table 8 .
Analyses of CO2 emissions and reduction ratio

Table 9 .
Analyses of cost and reduction ratio Analyses of CO2 emissions and cost-effectiveness by strength level CO2 emissions and the cost-effectiveness of the actual and CO2 reduction mix designs were analyzed and compared based on strength level.As indicated in Table10, the average reductions achieved by the mix design to reduction CO2 were 0.3-11% more than that achieved by the actual mix design.

Table 10 .
CO2 emissions and reduction rates by strength level of concrete mix designs

Table 11 .
Cost-effectiveness and reduction rates by strength level of concrete mix designs