Carbon Footprint and Uncertainties of Geopolymer Concrete Production: A Comprehensive Life Cycle Assessment (LCA)

Abstract

This study aims to estimate the carbon footprint and relative uncertainties for design components of conventional and geopolymer concrete. All the design components of alkaline-activated geopolymer concrete, such as fly ash, ground granulated blast furnace slag, sodium hydroxide (NaOH), sodium silicate (Na₂SiO₃), superplasticizer, and others, are assessed to reflect the actual scenarios of the carbon footprint. The conjugate application of the life cycle assessment (LCA) tool SimPro 9.4 and @RISK Monte Carlo simulation justifies the variations in carbon emissions rather than a specific determined value for concrete binders, precursors, and filler materials. A reduction of 43% in carbon emissions has been observed by replacing cement with alkali-activated binders. However, the associative uncertainties of chemical admixtures reveal that even a slight increase may cause significant environmental damage rather than its benefit. Pearson correlations of carbon footprint with three admixtures, namely sodium silicate (r = 0.80), sodium hydroxide (r = 0.52), and superplasticizer (r = 0.19), indicate that the shift from cement to alkaline activation needs additional precaution for excessive use. Therefore, a suitable method of manufacturing chemical activators utilizing renewable energy sources may ensure long-term sustainability.

1. Introduction

The construction industry is considered the third-largest contributing sector to carbon emissions, following electricity generation and transportation [1]. The primary reason for higher carbon emissions is the manufacturing of cement by burning fossil fuels and using electricity. Combustion of limestone (CaCO₃) to convert into lime (CaO), the prime component of cement clinker, causes a significant contribution of carbon dioxide (CO₂) emissions to the atmosphere [2]. Around 1.5 million tons of CO₂ are generated globally each year due to the manufacturing process of cement [3]. The production of cement clinker results in a range of 0.8–1.2 kg CO₂ equivalent per kg of Ordinary Portland Cement (OPC) at the embodied phase [4].

The alternative solution to reducing conventional concrete’s carbon footprint is replacing cement with industrial by-products. Moreover, the transition of electricity generation from fossil fuel-based sources (coal, oil, and gas) to renewable ones (solar, wind, hydro, and others) and alternative fuel for transportation will lead to a sustainable solution [5]. The innovative way of minimizing OPC in concrete is to transform industrial by-products or waste, such as fly ash and slag, into cementitious materials. Transforming industrial waste into concrete requires an alkali solution as the activator to enhance bonding and strength, which is known as geopolymer concrete [6]. This study evaluates the environmental assessment of alkali-activated geopolymer concrete based on design components, fly ash, and slag. Although the transition to green energy will diminish fly ash availability over time, the conceptual methodology of geopolymer concrete remains adaptable [7]. In this case, an alternative aluminosilicate-rich material, such as glass powder, rice husk, fine demolition, calcined clay, and others, will substitute for fly ash [8]. Hence, this research reinforces assessing environmental impacts for low-carbon infrastructure and a long-term decarbonization strategy.

The strength-gaining mechanism of geopolymers depends on the polymerization process between aluminum silicate-enriched materials (e.g., fly ash, slag) and alkali-activated solution (e.g., NaOH, Na₂SiO₃, and others) [9]. A higher concentration of hydrogen ions (pH) in sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) dissolves the silicate (Si-O) and aluminum (Al-O) bond of the precursors, i.e., fly ash or slag, as shown in Equation (1). Formed monomers in the dissolution process begin to react with alkali cations to generate geopolymer gel and ultimately result in three-dimensional gel sodium aluminosilicate hydrate (N-A-S-H), as in Equation (2). Additionally, blended ground granulated blast furnace slag (GGBFS) enhances the calcination process to gain early strength and form gel calcium aluminosilicate hydrate (C-A-S-H), as in Equation (3). Hydration is the main mechanism for gaining strength of cement, reacting with water to produce calcium silicate hydrate (C-S-H), as in Equation (4). Therefore, the formation of a sustainable geopolymer concrete requires the integrated application of alkaline-activated fly ash and slag to comply with the desired strength [10].

$${Al}_2{O}_3\backslash {SiO}_2+{OH}^{-}\to {SiO}_4^{4-} , {AlO}_4^{5-} \left(Dissolution\right)$$

(1)

$${n\left[{SiO}_4\right]}^{4-}+{m\left[{AlO}_4\right]}^{5-}+alk\to {\left(Na,K\right)}^{+}.{\left[{{(-SiO}_2)}_z-{AlO}_2\right]}_n.w{H}_{2}O \left(Gel formation\right)$$

(2)

$${Ca}^{2+}+{n\left[{SiO}_4\right]}^{4-}+{m\left[{AlO}_4\right]}^{5-}\to C-A-S-H gel \left(Calcination\right)$$

(3)

$$2C_{3}S+6H\to C_3{S}_2{H}_3\left(C-S-H\right)+3CH \left(Hydration\right)$$

(4)

Over the past decade, a growing interest in research has been observed in relation to substituting cement with alternative alkali-activated binders [11,12]. Aluminosilicate-enriched industrial by-products, namely fly ash and slag, show potential as alternative binders [13]. However, the associated environmental trade-offs of alkali-activated geopolymer concrete need further investigation to optimize it from a sustainability perspective. Therefore, life cycle assessment (LCA) has been considered as a systematic methodology to calculate the carbon footprint and other impact categories for all design components [14].

LCA consists of different phases of the life cycle, such as extraction, manufacturing, construction, operation, maintenance, disposal, and recycling [15]. This study compares raw materials composition, extraction, and the manufacturing process to evaluate the environmental impacts of one cubic meter (1 m³) of conventional and geopolymer concrete. A detailed Monte Carlo simulation has been adopted in this assessment, not only to quantify specific emissions but also the variability of input design parameters. The relevant uncertainties of this analysis provide a transparent framework to identify influential parameters and guidelines to optimize design. The feasible outcomes of the uncertainty analysis address the data gap, model variability, and ensure transparent decision making in adopting sustainability.

2. Materials and Methods

The study conducts a comparative LCA of geopolymer concrete components compared to conventional concrete, as shown in Figure 1. Relative uncertainties in the production system have been justified in this study to prioritize the design parameters in geopolymer concrete. An exhaustive Monte Carlo simulation has been performed to identify the association of individual impact with relative design parameters. M20 (20 MPa) concrete design mix has been considered in this study with the proportion of cement, fine aggregate, and coarse aggregate as 1:1.5:3, with a water–cement ratio of 0.5 [16]. Alkali-activated fly ash, slag, and plasticizer have replaced the cement to form 1 m³ of geopolymer concrete as per the experimental study. The conventional and geopolymer concrete are designed based on the optimal use of materials for 1 m³ of concrete, as shown in

Table 1. Design and proportions of conventional and geopolymer concrete for 1 m³ of concrete.

No	Design Components	Density (kg/m3)	Quantity (kg)	Percentage of Total Mass (%)
Conventional concrete
1	Cement	1440	418	15.05%
2	Fine aggregate (sand)	1600	688	24.77%
3	Coarse aggregate (gravel)	1700	1462	52.64%
4	Water	1000	209	7.52%
	Total mass		2777	100%
Geopolymer concrete
1	Fly ash (Class F)	1050	389	12.56%
2	Slag (GGBFS)	1100	167	5.39%
3	Fine aggregate (sand)	1600	688	22.22%
4	Coarse aggregate (gravel)	1700	1462	47.23%
5	Water	1000	229	7.39%
6	Sodium hydroxide (NaOH)	480	41	1.32% (12 M solution)
7	Sodium silicate (Na2SiO3)	1400	111	3.58 %
8	Superplasticizer	1130	8.34	1.5% of the binder
	Total mass		3087	100%

.

The formulation of geopolymer concrete is derived from experimental studies and well-practiced within the research community. The primary concept of geopolymer development is the activation of aluminosilicate using an alkali solution [17]. This innovative design employs aluminosilicate-enriched materials, such as fly ash and slag, as the binders, activated with the combination of sodium hydroxide and sodium silicate [18,19]. The addition of slag enhances calcination to form both C-A-S-H and N-A-S-H gels [20]. Additionally, the adoption of superplasticizer enhances the workability of geopolymer concrete against the high viscosity resulting from activators [21]. The composition of design components is validated by experimental research to achieve sustainable concrete solutions.

A composition of fly ash (Class F), around 75% to 100% of the total binder, is suitable for the replacement of cement [22,23]. The presence of alumino-silicate initiates a reaction with the alkali solution and forms a geopolymer gel. However, the lower content of calcination results in slower setting of concrete and requires the necessity of adding slag. To accelerate the setting and hardening of concrete, a certain proportion of ground granulated blast furnace slag (GGBFS) up to 40% is recommended to replace fly ash [24,25]. The calcium content of slag enhances the gain of early strength and acts as a partial hydraulic binder. Typically, sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) are applied together as an alkali activator solution within the range of 35–45% of the binder. A ratio of Na₂SiO₃–NaOH between 1.5–2.5 has been found effective to initiate geopolymer reaction by activating fly ash and slag particles [26]. Higher NaOH molarity has been observed to be effective in the dissolution of alumino-silicates. Generally, 12 M NaOH is used as a balanced solution due to its safety of handling and to avoid brittleness. Additionally, the use of superplasticizer (0.5–2% of binder) reduces the water content and improves the concrete workability [27]. Fine and coarse aggregates are used as fillers of concrete, not as reactive components in concrete, as in a conventional concrete mixture [28]. The compositions and proportions of required materials to perform LCA are shown in Table 1.

2.1. Goal and Scope Definition

This study quantifies the design components of geopolymer concrete to comply with the compressive strength of conventional concrete of 20 MPa, as mentioned in Section 2. The goal of this study is to assess the environmental impacts and relevant uncertainties of geopolymer concrete components compared to conventional concrete. The comparative study will set the benchmark for alkali-activated fly ash- or slag-based geopolymer concrete and prioritize influential variables in contributing to the carbon footprint. The ISO 14040/44 standard has been followed in this study to perform the LCA, and relative uncertainties have been identified by applying the pedigree matrix of uncertainty [29,30].

2.2. Functional Unit and System Boundary

The functional unit of this study is one cubic meter (1 m³) of conventional and geopolymer concrete. It is the reference unit to quantify the comparative performance of environmental impacts across different categories of products or processes [31]. All the components have been selected as per the design standard of a 20 MPa design mix. Climate change (kg CO₂ equivalent) has been selected as the potential environmental impact for in-depth analysis due to its contribution to global warming [32]. Other impact categories, such as ozone depletion, acidification, eutrophication, and others, are also expressed to show the relevant changes.

The upstream chain of the production process, cradle-to-gate, has been selected as the system boundary of the materials [33]. The boundary includes the process of raw materials extraction, transportation, and manufacturing of the products, whereas cradle-to-grave includes the complete life cycle of extraction, transportation, manufacturing, operation, and disposal or recycling [34].

2.3. Life Cycle Inventory

The Australian life cycle inventory (AusLCI) has been used to quantify the associated production processes of the materials [35]. Primary data of the concrete design mix have been assessed from the batching plant and laboratory mix design, as mentioned in the methodology section. Secondary data on assessing the environmental impacts have been collected from the sequential production process of the Australian industry facilities. In some cases, the Ecoinvent version 2.2 database has been adopted in the AusLCI by substituting the input flows of the industrial production process [36]. The manufacturing process includes several steps of production, such as raw materials extraction, transportation, energy, and diesel consumption by machinery for production [37]. Occupation of land, transformation area, and use of roads and buildings are also included in the inventory. The LCA tool Simapro 9.4 shows the network of product manufacturing, including the variable steps of production. Some of the clearly visible network of the life cycle inventory for manufacturing a product has been shown in

Table 2. Life cycle inventory for design components.

Inputs for Emissions Factors	Quantity	Unit
Ordinary Portland Cement (OPC)	1 kg	Kilogram
Limestone-milled	1.4 kg	Kilogram
Transport truck—28 t fleet	0.429 tkm	Ton–kilometer
Electricity—low voltage	0.633 MJ	Megajoule
Energy from coal	1.34 MJ	Megajoule
Energy from natural gas	2.54 MJ	Megajoule
Gravel, crushed at the mine	1 kg	Kilogram
Diesel is burned in the machine	0.0161 MJ	Megajoule
Building hall—steel construction	3 × 10−6 m2	Square meter
Electricity—medium voltage	0.0332 MJ	Megajoule
Heat—light fuel oil	0.00492 MJ	Megajoule
Sand, at mine	1 kg	Kilogram
Energy from diesel	0.025 MJ	Megajoule
Energy from natural gas	0.018 MJ	Megajoule
Fly ash from the stove	1 kg	Kilogram
Transport lorry—20-to-28 ton	0.0683 tkm	Ton–kilometer
Natural gas is burned in a furnace	0.05 MJ	Megajoule
Low-voltage electricity at grid	0.000606 MJ	Megajoule
Ground granulated blast furnace slag	1 kg	Kilogram
Aluminum primary ingot	0.000566 kg	Kilogram
Steel unalloyed market	0.00386 kg	Kilogram
Sinter iron market	0.0174 kg	Kilogram
Electricity—medium voltage	0.0393 MJ	Megajoule
Sodium hydroxide 12 M (membrane cell)	1 kg	Kilogram
Sodium chloride—powder	0.854 kg	Kilogram
Electricity—medium voltage	6.13 MJ	Megajoule
Sodium silicate (furnace process)	1 kg	Kilogram
Soda powder	0.403 kg	Kilogram
Electricity—medium voltage	0.551 MJ	Megajoule
Heat—heavy fuel oil in the furnace	2.25 MJ	Megajoule
Heat—natural gas	2.22 MJ	Megajoule
Superplasticizer	1 kg	Kilogram
Chemical (organic)	0.649 kg	Kilogram
Sodium hydroxide without water	0.125 kg	Kilogram
Electricity—medium voltage	2.05 MJ	Megajoule
Water use	1 kg	Kilogram
Electricity—low voltage	0.00313 MJ	Megajoule
Ozone—liquid at plant	3.33 × 10−6 kg	Kilogram
Water works	1.19 × 10−11 p	Process

Note: Gray colour indicates the production of 1 kg (Kilogram) main design components such as Ordinary Portland Cement (OPC), Gravel, Fly ash, Ground granulated blast furnace slag, Sodium hydroxide, Sodium silicate, Superplasticizer, and Water. Required components and energy consumption have been added below to produce the main design component.

.

2.4. Sensitivity Analysis

A sensitivity analysis defines the uncertainties of the production system and identifies the feasible ranges of the possible outcomes [38]. The probabilistic outcomes of the production system identify how the allocation of a particular product influences the decision-making process [39]. Important parameters can be prioritized based on the uncertainty analysis. To address the associated uncertainties of the carbon footprint, the Monte Carlo simulation is a suitable tool to see the variations in outcome and correlation with individual inputs. The conjugated approach of applying Monte Carlo with the @RISK (Palisade Decision Tools, version 8.9.0) and SimaPro 9.4 identifies the possible input variations, correlations, and desirable outcomes for conventional and geopolymer concrete [40]. The simulation is performed over thousands of input iterations to obtain the probabilistic outcome for the carbon footprint. In this analysis, variations in data have resulted from a normal distribution of each design component, such as cement, fly ash, slag, alkaline solutions, and others. Primarily, the LCA tool SimaPro 9.4 defines the statistical indicators of these parameters, including the mean, standard deviation, coefficient of variation, and confidence interval, as shown in

Table 3. Sensitivity indicators (kg CO₂ eq) per unit of individual design components.

Design Components	Impact Unit	Statistical Indicators for Per Unit (kg)				95% Confidence Interval
		Mean	Median	SD	CV (%)	2.5%	97.5%
Cement	kg CO2 eq	0.9010	0.8969	0.0382	4.2441	0.8324	0.9839
Sand	kg CO2 eq	0.0031	0.0031	0.0003	10.3986	0.0025	0.0038
Gravel	kg CO2 eq	0.0127	0.0127	0.0011	8.9070	0.0107	0.0150
Water	kg CO2 eq	0.0010	0.0009	0.0003	31.8765	0.0005	0.0017
Fly ash	kg CO2 eq	0.0277	0.0275	0.0033	11.7802	0.0222	0.0354
Slag	kg CO2 eq	0.0613	0.0610	0.0045	7.3772	0.0540	0.0714
NaOH	kg CO2 eq	1.8224	1.8170	0.1603	8.7956	1.5120	2.1630
Na2SiO3	kg CO2 eq	0.9068	0.8894	0.0921	10.1559	0.7806	1.1589
Superplasticiser	kg CO2 eq	1.3178	1.2711	0.2976	22.5871	0.8601	2.0422

. Then, the @RISK Palisade decision tool further investigates the influential input by ranking and the Pearson correlation coefficient of the influential input.

Impact categories of the designed materials have been obtained by performing a simulation in SimaPro 9.4, as adopted by the AusLCI. The pedigree matrix determines the geological uncertainty of the products based on materials sourcing, regional production, temporal production, and others (the six criteria are outlined in ISO 14044) [41,42]. The main six criteria that are outlined in the ISO 14044 include the following: (1) Data reliability by experts (e.g., estimated vs. measured), (2) data completeness from sites (e.g., site-specific data), (3) temporal corrections between 3–15 years (e.g., age of obtaining data for relative operations), (4) geographical correlations from different areas (e.g., regional relevance of data source), (5) technological correlations from lab processes (e.g., maintain consistency with other established production system), and (6) uncertainty focusing on carbon and fine particle (PM10, PM2.5) emissions. The uncertainty (σ²) of these six identical factors was calculated by summing up all the variations, as shown in Equation (5).

$${\mathsf{\sigma }}^2=\sum _{n=1}^6{\sigma }_n^2$$

(5)

Statistical indicators and ranges of all possible outcomes, including a 95% confidence interval, are outlined in Table 3. It clearly indicates that sodium hydroxide (NaOH), superplasticizer, sodium silicate (Na₂SiO₃), and cement are the dominant factors for emissions with a higher mean and 95% confidence interval, whereas water has the lowest carbon footprint (e.g., 0.0010 kg CO₂ eq per kg), with a higher CV of 31.88%. Even a minor variation in water treatment, distribution, and sourcing, such as municipal and groundwater, leads to a larger deviation in the smallest mean value. However, the higher CV does not reflect the higher uncertainty; rather, it is more variable and is an indicator of dividing the standard deviation (SD) by the mean.

3. Results

A life cycle impact assessment for the designed components was estimated using the most up-to-date version of ReCiPe 2016. Pré Consultants, RIVM, Leiden University, and Radboud University Nijmegen developed this impact assessment methodology for the design inputs of the products [43]. The eighteen (18) midpoint impact categories are as follows: (1) climate change, (2) ozone depletion, (3) terrestrial acidification, (4) freshwater eutrophication, (5) marine eutrophication, (6) human toxicity, (7) photochemical oxidant formation, (8) particulate matter formation, (9) terrestrial ecotoxicity, (10) freshwater ecotoxicity, (11) marine ecotoxicity, (12) ionizing radiation, (13) agricultural land occupation, (14) urban land occupation, (15) natural land transformation, (16) water depletion, (17) metal depletion, and (18) fossil depletion. This study considers the midpoint impact for these two types of concrete. Global warming potential (kg CO₂ eq) has been prioritized for relevant uncertainties of concrete components.

3.1. Impact Assessment of Conventional Concrete

Life cycle assessment of 1 m³ of conventional concrete shows that cement is the primary contributor in the mix design, which accounts for 95% of the carbon footprint, which is 376.7 out of 397.6 kg CO₂ eq, as shown in

Table 4. Impact assessment of one cubic meter (1 m³) of conventional concrete.

Impact Category	Unit	Cement	Sand	Gravel	Water	Total
Climate change	kg CO2 eq	376.637	2.146	18.587	0.202	397.570
Ozone. D	kg CFC-11 eq	2.5 × 10−6	2.3 × 10−10	4.7 × 10−7	1.0 × 10−9	3.0 × 10−6
T. acidification	kg SO2 eq	1.214	0.013	0.108	0.001	1.335
F. eutrophication	kg P eq	1.2 × 10−3	4.2 × 10−7	3.3 × 10−4	2.7 × 10−6	1.5 × 10−3
M. eutrophication	kg N eq	4.3 × 10−2	8.0 × 10−4	3.1 × 10−3	2.4 × 10−5	4.7 × 10−2
Human toxicity	kg 1,4-DB eq	8.089	0.810	0.920	0.011	9.830
Photochem. OF	kg NMVOC	1.163	0.022	0.078	0.001	1.263
Particulate. MF	kg PM10 eq	4.4 × 10−1	4.8 × 10−3	3.7 × 10−2	3.2 × 10−4	4.8 × 10−1
T. ecotoxicity	kg 1,4-DB eq	3.1 × 10−3	2.5 × 10−6	6.5 × 10−4	1.2 × 10−5	3.7 × 10−3
F. ecotoxicity	kg 1,4-DB eq	4.1 × 10−2	6.7 × 10−3	6.7 × 10−3	4.1 × 10−4	5.5 × 10−2
M. ecotoxicity	kg 1,4-DB eq	6.3 × 10−2	6.7 × 10−3	9.7 × 10−3	1.2 × 10−4	8.0 × 10−2
Ionizing radiation	kBq U235 eq	9.0 × 10−3	3.9 × 10−6	6.4 × 10−3	1.8 × 10−5	1.5 × 10−2
Agricultural. LO	m2a	1.761	0.001	0.575	0.051	2.388
Urban. LO	m2a	3.399	0.001	1.270	0.011	4.681
Natural land. T	m2	9.3 × 10−3	2.9 × 10−6	2.2 × 10−2	1.8 × 10−5	3.1 × 10−2
Water depletion	m3	7.683	1.376	2.061	0.237	11.357
Metal depletion	kg Fe eq	5.226	0.001	1.825	0.007	7.059
Fossil depletion	kg oil eq	65.844	0.793	5.053	0.050	71.740

. Similarly, in the case of other impact categories, namely ozone depletion, acidification, eutrophication, human toxicity, ecotoxicity, and depletion of metals and fuel, the ranges of cement contribution lie between 80% and 90% of the total impacts. The primary cause lies in the cement industry’s impact, which involves the energy-intensive production of clinker and raw materials extraction. Compared to cement, minor environmental impacts are observed for gravel, sand, and water, respectively. The finding of this LCA highlights the importance of substituting cement with industrial by-products to reduce emissions. Geopolymer concrete provides this opportunity to reduce impacts. However, all the design components of geopolymer concrete need to be considered, reflecting real scenarios.

3.2. Comparative Assessment of Conventional and Geopolymer Concrete

A comparative analysis of the carbon footprint for two types of concrete reveals a significant advantage of geopolymer concrete over conventional concrete (397.57 kg CO₂ eq) per cubic meter. Around a 43% reduction in carbon emissions is observed for manufacturing geopolymer concrete (228.34 kg CO₂ eq), as shown in

Table 5. Uncertainty analysis of carbon footprint for conventional and geopolymer concrete components.

Design Components			Statistical Indicators (kg CO2 eq)				95% Confidence Interval
		Quantity	Mean	Median	SD	CV	2.5%	97.5%
1	Cement	418	376.637	374.914	15.985	4.264	347.962	411.265
2	Sand	688	2.146	2.139	0.223	10.433	1.727	2.647
3	Gravel	1462	18.587	18.506	1.655	8.946	15.600	21.958
4	Water	209	0.202	0.192	0.064	33.511	0.108	0.359
Conventional concrete (Output)			397.570	395.750	16.03	4.031	365.9	428.5
1	Fly ash	389	10.780	10.682	1.270	11.888	8.652	13.788
2	Slag	167	10.243	10.181	0.756	7.423	9.013	11.925
3	Sand	688	2.146	2.139	0.223	10.433	1.727	2.647
4	Gravel	1462	18.587	18.506	1.655	8.946	15.600	21.958
5	Water	229	0.221	0.210	0.070	33.511	0.119	0.394
6	NaOH	41	74.718	74.498	6.572	8.822	61.994	88.681
7	Na2SiO3	111	100.66	98.73	10.22	10.15	86.65	128.64
8	Superplasticizer	8.34	10.990	10.601	2.482	23.417	7.173	17.032
Geopolymer concrete (Output)			228.34	228.21	12.64	5.535	203.3	253.2

. Aligning with the findings of earlier conducted studies, a feasible range of carbon reduction between 30–60% has been observed for other studies [44,45,46]. However, the consecutive carbon footprint of NaOH and Na₂SiO₃ represents 74.71 and 100.66 kg CO₂ eq, respectively, which is almost 77% of geopolymer emissions. The alternative binders, like fly ash and slag, combinedly generate 21.02 kg of carbon emissions, which is very low compared to the other chemicals. The 95% confidence interval of the traditional concrete represents a variation between 365.9–428.5 kg CO₂ eq with a standard deviation (SD) of 16.03 and a small coefficient of variation (CV) of 4.03%. However, in the case of geopolymer concrete, it lies between 203.3 and 253.3 kg CO₂ eq, even in the worst-case scenario. The results highlight the potential of geopolymer concrete as a sustainable solution over conventional concrete. However, it also emphasizes the environmental trade-off, focusing on the relevant uncertainty of applying the alkali solution as a chemical activator.

3.3. Impact Categories for Design Components

Chemical activators, like sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃), are the primary contributors to the carbon emissions in geopolymer concrete, as shown in Figure 2. The successive contributions of cement, NaOH, and Na₂SiO₃ represent carbon footprints of 376.6, 74.7, and 100.7 kg CO₂ eq, respectively. Moreover, the ozone depletion potentials of Na₂SiO₃ (111 kg) and superplasticizer (8.34 kg) represent a higher amount of CFC emissions, namely 4.09 × 10⁻⁶ and 1.78 × 10⁻⁶, respectively. Similarly, NaOH and Na₂SiO₃ are significant contributors to acidification, representing 0.404 and 0.476 kg SO₂ eq, respectively. Surprisingly, combinedly, they possess nearly the impacts of cement (1.21 kg SO₂ eq), even with small amounts of 41 and 111 kg. The comprehensive LCA reveals that a notable amount of alkali activators may cause environmental degradation instead of bringing environmental benefits. These findings support earlier studies by highlighting the need for the careful management of chemical application for traditional concrete decarbonization [47,48]. Hence, the correlations and individual component distribution have been elaborated in terms of the environmental impacts and uncertainties associated with alternative binders and chemical activators.

3.4. Ranking of Inputs by Their Effect on the Probabilistic Distribution

Probabilistic distribution has been performed for conventional and geopolymer concrete to identify the influence of individual input parameters and to rank them according to their impacts, as shown in Figure 3. The sensitivity of chemical production shows that sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) have a wider variation in carbon emissions, ranging from 210.28–246.48 and 216.93–240.28 kg CO₂ eq, respectively. On the contrary, the deviation in carbon footprint is mostly related to the cement production, varying between 369.42–425.57 kg CO₂ eq. A representation of the tornado plot reveals that all the chemical activators are on top of the carbon emissions, sequentially sodium silicate, sodium hydroxide, and superplasticizer. Hence, the findings emphasize the sensitivity of chemical activators in terms of quantities and emissions. A sustainable method of chemical production can be prioritized by using a source of renewable energy to minimize the impacts.

3.5. Correlation Coefficient of the Design Variable with the Carbon Footprint

Pearson’s correlation coefficient is an important statistical indicator to identify the possible association of individual design components with the estimated carbon footprint [49]. For conventional concrete, cement almost aligns with carbon emissions, indicating that a value of 0.99 means that substitute cement is the only feasible way of minimizing impacts. During their transformation into geopolymer concrete, sodium silicate (r = 0.80) followed by sodium hydroxide (r = 0.52) represent strong and moderate relationships with carbon footprint, as shown in Figure 4. However, a lower correlation value (r = 0.19) has been observed when using superplasticizer. The correlation analysis indicates that the shift from cement to the alkaline solution of NaOH and Na₂SiO₃ is very sensitive in the case of excessive use.

4. Discussion and Conclusions

This study conducts a comparative life cycle assessment to estimate the carbon footprint for conventional and geopolymer concrete. The findings of the LCA suggest replacing cement with industrial by-products, such as fly ash and slag, to minimize the carbon footprint of conventional concrete. Considering all the design components of geopolymer concrete, the assessment reveals that a reduction of 43% in carbon emissions is feasible when compared to the traditional approach. The substitution of cement with fly ash or slag is the key component of this significant reduction, where cement accounts for 95% carbon emissions. Therefore, the promising aspects of reducing the carbon footprint have been in alkali-activated geopolymer concrete without compromising the design strength have been considered.

However, the alkaline solution of sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) combinedly contributes 77% of the total geopolymer carbon footprint. The impact categories of the individual design components show the successive contribution of cement, NaOH, and Na₂SiO₃, representing carbon footprint values of 376.6, 74.7, and 100.7 kg CO₂ eq, respectively. Moreover, acidification (kg SO₂ eq) and ozone depletion potential (CFC-11 eq) are relatively higher as per the weight of sodium hydroxide (41 kg) and sodium silicate (111 kg). For example, the acidification potential impacts of NaOH and Na₂SiO₃ have been noted as 0.404 and 0.476 kg SO₂, respectively, close to the cement impact of 1.21 kg SO₂. Despite being used in smaller quantities, substantial impacts have been observed across all categories. Hence, notable variations in chemical admixture may cause considerable environmental damage in addition to global warming. Therefore, the relative uncertainty of alkaline solutions is important when considering the possible variations in environmental impacts due to their excessive use.

The uncertainty analysis justifies the sensitivity of the individual chemical activators in geopolymer concrete using probabilistic distribution and correlation coefficients. Probabilistic distribution of ranked inputs shows a variation in the carbon footprint ranges from 210.28–246.48, 216.93–240.28, and 223.82–233.20 kg CO₂ eq for Na₂SiO₃, NaOH, and superplasticizer, respectively. The distribution suggests the requirement for sustainable chemical manufacturing, and its small fluctuation in dosage may increase the impact categories significantly.

The Pearson correlation coefficient (r) emphasizes the relationship between carbon footprint and chemical activators. Alkaline solutions show a moderate and strong relationship with the alkaline solutions NaOH (r = 0.52) and Na₂SiO₃ (r = 0.80). The results highlight the dual challenges in designing sustainable concrete, where the formation of geopolymer concrete replaces cement, but the required alkaline solution is highly sensitive to environmental degradation. The full potential of geopolymer concrete can be unlocked through the decarbonization of alkaline production and shifting it to renewable energy-based sources.

Regional-specific environmental impact assessment using the AusLCI (Australian Life Cycle Inventory) ensures its relevance in the decision-making process. Australian energy mixes, industrial processes, and transportation are the basis of this calculation. However, the associated uncertainty factors of calculated emissions enhance their global acceptability and the overall generalization of the findings.