DOI: 10.3303/CET2188133 
 

 

 
 

 
 

 
 
 

 
 
 

 
 
 

 

 
 
 

 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 
 

 
 

 

Paper Received: 25 May 2021; Revised: 10 September 2021; Accepted: 13 October 2021 
Please cite this article as: Dollente I.J.R., Tan R.R., Promentilla M.A.B., 2021, Life Cycle Assessment of Precast Geopolymer Products, 
Chemical Engineering Transactions, 88, 799-804  DOI:10.3303/CET2188133 

CHEMICAL ENGINEERING TRANSACTIONS 

VOL. 88, 2021 

A publication of 

The Italian Association 
of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Petar S. Varbanov, Yee Van Fan, Jiří J. Klemeš

Copyright © 2021, AIDIC Servizi S.r.l. 

ISBN 978-88-95608-86-0; ISSN 2283-9216 

Life Cycle Assessment of Precast Geopolymer Products 
Ithan Jessemar R. Dollente, Raymond R. Tan*, Michael Angelo B. Promentilla 
De La Salle University, Philippines 
raymond.tan@dlsu.edu.ph 

Reducing the embodied carbon footprint caused by construction projects is being pushed by many countries. 
One potential solution is the large-scale use of low-carbon building materials like geopolymers (GPs). GPs 
result from the chemical activation of aluminosilicate materials using an alkaline liquid, resulting in an 
inorganic polymeric network; it can also allow repurposing of the waste or by-products of industries. The 
sustainability of this new type of material is assessed here using Life Cycle Assessment (LCA). This study 
quantifies the cradle-to-gate environmental impacts of a localized geopolymer process in the Philippines and 
contrasts the impacts of Ordinary Portland Cement (OPC). The Life Cycle Inventory (LCI) analysis was 
performed using OpenLCA software and Life Cycle Impact Assessment (LCIA) using IPCC 2013 
methodology. LCA results show that GP concrete with an RHA-based activator has a similar Global Warming 
Potential (GWP) as GP made using a commercial activator. The main contributors to the impacts are the 
production of the alkali activators, which indicates that the electricity generation mix has a significant influence 
on the environmental sustainability of GP. 

1. Introduction

Reducing the construction industry's carbon footprint is a goal of many countries to manage the effects of 
greenhouse gases (Van Deventer et al., 2012). The large carbon footprint is caused by the high-temperature 
decomposition of the calcareous materials to make Ordinary Portland Cement (OPC) (Miller, 2018). Lehne 
and Preston (2018) report that OPC accounts for about 8% of global greenhouse gas (GHG) emissions. 
The large-scale use of low-carbon building materials like geopolymers (GPs) became a potential solution to 
reduce this embodied carbon footprint. Conceptualized by Davidovits and Sawyer (1985), geopolymers are 
structured matrices of aluminum and silicon-rich materials, such as coal ash and fly ash, which have been 
chemically activated using an alkaline or acidic medium. The final formed product has a network similar to 
polymers but is compositionally inorganic and is likened to construction products that use OPC as the base 
(Fernández-Jiménez and Palomo, 2009).  
Based on the study of Kumar and Kumar (2013), the economies of production of geopolymer-based products 
are like conventional concrete. However, the commercial adoption of geopolymer technology is still low. 
Acceptance is still short-term and is only driven by a market that is becoming more environmentally aware 
(Van Deventer et al., 2012). Thus, the potential commercialization entry for GPs is with niche products. Non-
structural, non-load-bearing precast products such as pavers, deco panels, and tiles can be initial entry points 
for geopolymer technology. Precast production, as compared to onsite production, has lower embodied 
energies because of the reduced inventories, raw material waste, land use, and additional production cycles 
(Myhr et al., 2019). 
In addition, the sustainability of GPs can be proven by environmental accounting using LCA. However, there is 
still a variation of the literature results versus OPC (Ouellet-Plamondon and Habert, 2015). The differences 
come from disregarding the GHG contributions of the alkali activation components, sodium hydroxide, sodium 
silicate, and the localization of production (Miller, 2018).  
A recent study by Kamseu et al. (2017) shows a potential GHG drop when using a sodium silicate activator 
made from locally available Rice Husk. A study by Longos et al. (2020) has proven that a GP mixture from 
locally sourced coal fly ash and nickel mine waste was seen to have the guideline compressive strength 

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pavements, pavers, and bricks. However, no study has investigated quantifying the cradle-to-gate 
environmental impacts of a precast geopolymer process in the Philippines.  
This study addresses these research gaps in the GP literature by performing process synthesis and LCA of a 
representative GP plant and contrasting the impacts of a precast OPC concrete process. Three types of 
concrete mixes are considered for this study: Ordinary Portland Cement concrete mix (OPC blend); fly ash 
geopolymer with commercial sodium silicate and NaOH activators (GP-Orig); fly ash geopolymer with rice 
husk ash-based sodium silicate and NaOH activators (GP-RHA). The results of this study shall determine how 
feasible and sustainable geopolymers are for local commercial adoption. 

2. Materials and methods

2.1 Case study and site location 

The local availability of fly ash is the main factor in implementing geopolymer-based production, as the 
transportation of the fly ash also contributes a lot to the total emissions (Miller, 2018). The geopolymer facility 
shall be in Alas-Asin, Mariveles, Bataan, Philippines (14°26'17.61"N, 120°31'34.08"E) and is chosen near the 
fly ash source. The facility shall also be proximate to the source of aggregates and the National Capital 
Region as the target primary market. 

2.2 Process network and synthesis 

P-graph Studio (P-graph, 2021) was used to generate the structure of the process network of the local case 
geopolymer facility and solve the synthesis problem. This program presents a bipartite graph of the materials 
(raw, intermediate, and products) and the operating units. The layout is based on stoichiometric inflows and 
outflows of the process and relevant cost information of these materials and operations (Friedler et al., 1992). 
The problem is solved using the accelerated branch and bound (ABB) algorithm (Friedler et al., 1996) 
implemented in P-graph Studio. This procedure gives the process configuration with maximized profit. The 
optimized OPC and geopolymer facilities are presented in Figure 1. 

Figure 1: Optimized structure for the process network synthesis of the localized OPC and GPC facility 

2.3 Goal and Scope of LCA 

This study evaluates the environmental impacts of a synthesized and localized geopolymer process in the 
Philippines and contrasts the impacts of a GP-based scenario to a standard localized OPC process. A cradle-
to-gate LCA of a facility is performed following the guidelines of ISO 14040 (ISO, 2006). The environmental 
aspects are measured based on a 'functional unit' of product or per daily production such that the products 
being compared are of an equitable function. The functional unit applied in this study is 1.0 m3 of concrete to 
produce approximately 609 units of concrete pavers. Three types of concrete mixes are considered for the 
analysis: Ordinary Portland Cement concrete mix (OPC blend), fly ash geopolymer with commercial sodium 
silicate and NaOH activators (GP-Orig), and fly ash geopolymer with Rice husk ash-based sodium silicate and 
NaOH activators (GP-RHA). The system boundaries are shown in Figure 2 for all concrete mixes. The 
volumetric equivalence of the mixes is kept, achieving the three different types of concrete. 

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Figure 2: System boundary and process flow model for OPC Blend, GP-Orig, and GP-RHA blends 

OpenLCA version 1.10.3 (GreenDelta, 2021), an open-source software for LCA, was used to perform the 
assessment calculations. Emission assessments include machine and equipment usage, raw materials, 
utilities, and transportation. 

2.4 Life cycle inventory analysis 

The LCI is based on the procedure specified in the ISO 14040, and the inventory values are acquired through 
the free sets of the Ecoinvent 3.0 database (Wernet et al., 2016). The total GHG emissions were carried out 
using OpenLCA, which catalogs all the component weights, volumes, and transportation distances in the 
synthesized system. The mix design for the GP blends is from first-hand data using locally sourced materials, 
considering the relevant synthesis preferences in the optimization study by Sumabat et al. (2015) and the 
resulting data from P-Graph Studio from Section 2.2. The OPC blend is based on the study by Turner and 
Collins (2013). The inventory data of raw materials and utilities used and the transportation distances from the 
local suppliers are presented in Table 1. 

Table 1: Mix design formulations (kg / m3) and cradle-to-gate inventory data 

Raw Material / Utilities OPC Blend GP-Orig GP-RHA 
Land transport 
distance, km 

Sea transport 
distance 

Cement 328.0 - - 192 - 
Fly ash - 541.8 541.8 10.0 - 
NaOH - 41.68 135.9 100 1,445 
Na2SiO3 - 132.7 - 170 1,498 
Fine aggregates (Sand) 781.0 238.9 238.9 50.0 - 
Coarse aggregates (Gravel) 1,242 1,354 1,354 50.0 - 
Rice Husk - - 297.4 121 - 
Electricity (kWh) 15.18 20.84 51.38 - - 
Diesel (fuel) 18.67 16.02 16.02 - - 
Water 203.4 187.3 491.3 - - 

3. Results and discussion

3.1 Impact assessment results 

The impact assessment was performed using the baseline model of the Intergovernmental Panel on Climate 
Change (IPCC) 2013, indicating the global warming potential (GWP) for a 100-year horizon. The 
environmental impact indicators considered for this study are three-fold climate change categories from a) 
Biogenic carbon sources, b) Fossil sources, and c) Land use and land transformation. The geographic scope 

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of this indicator is on a global scale, and the reference process location is in the Philippines. The results of the 
impact assessments for one functional unit of the concrete mixes are shown in Table 2. 

Table 2: GWP100 impact assessment results for the concrete blends 

Impact Category Unit OPC Blend GP-Orig GP-RHA 

Climate change, Fossil kg CO2 eq. 354.8 241.3 249.8 
Climate change, Biogenic kg CO2 eq. 6.021 17.23 6.193 
Climate change, Land Use, and Transformation kg CO2 eq. 0.121 0.169 0.316 

Figure 4: Impact assessment comparison between localized OPC and GP concrete production 

Table 2 and Figure 4 show that there are varying environmental impacts of the three mixes. For fossil sources, 
OPC has the maximum burden caused by fossil fuel burning for the high-temperature clinkerization process 
(Miller et al., 2016). As a result, carbon savings of 32 % were seen for GP-Orig and 30 % for GP-RHA 
concrete. For biogenic sources, GPC-Orig carries a considerable environmental burden, mainly caused by the 
high-temperature fusion process to melt soda ash and silica sand in sodium silicate production (Passuello et 
al., 2017). Finally, GPC-RHA carries the biggest GWP for land use and Transformation as the land-use 
changes and management of the Chlor-alkali process have considerable emissions. Considering that fossil 
and biogenic sources have the most significant weights in terms of equivalent emissions, it can be inferred 
that the OPC blend has the most undesirable environmental impacts. 

3.2 Contribution analysis 

The contribution of the different components per cubic meter for each impact category is shown in Figure 5. 
For GWP100, Portland cement contributes about 78 to 83 % of carbon emissions in all sources, confirming the 
source of the relatively high carbon footprint of OPC. Diesel, land transport, and coarse aggregates have 
secondary impacts.  

Figure 5: Impact contribution of ingredients and utilities of localized OPC and GPC production 

0.1

1

10

100

1000

Climate change - fossil Climate change - biogenic Climate change - land use
and land transformation

Lo
g 1

0
[k

g 
C

O
2

eq
.]

OPC Blend GP-Orig GP-RHA

0%

20%

40%

60%

80%

100%

OPC Blend GPC-Orig GPC-RHA OPC Blend GPC-Orig GPC-RHA OPC Blend GPC-Orig GPC-RHA

kg
 C

O
2

eq
.

OPC NaOH Sodium Silicate Electricity Fine Aggregates
Coarse Aggregates Diesel Land Transport Sea Transport

Climate Change - BiogenicClimate Change - Fossil Climate Change - Land Use 
and Transformation

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For GP-Orig, the commercial sodium silicate is the dominant contributor for biogenic and fossil sources with 
about 60 % contribution for fossil sources and 85 % contribution for biogenic sources. For the GP-RHA, the 
most significant contribution is from NaOH with 70 to 95 %. Consistent with previous studies, the alkali 
activators are the components that reduce the sustainability of geopolymers (Bajpai et al., 2020). Additional 
carbon savings can be achieved using more waste materials such as ground granulated blast-furnace slag, 
silica fume, and other alummino-silicate materials (Huseien et al., 2018). Electricity use, land transport, and 
coarse aggregates are secondary impacts. The Chlor-alkali process can have additional carbon savings if the 
process is facilitated through renewable energy sources. On the other hand, transportation GHG can be 
minimized by optimizing material routes and the modes of transportation (Miller, 2018). Other components 
have minimal impacts (0.3 to 5 %). Sea transport has the lowest environmental impacts on all categories for 
the GP mixes. 

3.3 Sensitivity analysis 

A sensitivity analysis based on the effects of transportation and local sources of raw materials is seen in 
Figure 6. The raw materials in GP-Orig (option 1) are adjusted to the maximum available distance for the local 
source of fly ash (option 2), sodium hydroxide (option 3), commercial sodium silicate (option 4), and by making 
use of all the maximum distances from the previous options (option 5). There is only a relatively low change in 
emissions, and thus, transportation distance does not significantly alter the impacts of the GP mixes. The 
change of impacts is about -0.39 % to 8.89 %. 

Figure 6: Sensitivity of emissions due to transportation of raw materials  

4. Conclusion

In this study, P-Graph was used to synthesize the product and profit flows of a localized precast GP facility 
based on literature and experimental data. LCA was then applied to compare the cradle-to-gate environmental 
impacts of this facility to an OPC-based facility. Based on the assessment results, the GP concrete with an 
RHA-based sodium silicate fared better than GP concrete made with a commercial sodium silicate in terms of 
biogenic climate change impact but fared poorer on land use and transformation. Overall, GP-RHA has a 
similar Global Warming Potential (GWP) as GP-Orig. In addition, precast products made from geopolymers 
had a global warming reduction of about 28% compared with OPC concrete products. The alkali activators 
were seen to contribute to the impact categories for GPC. Using rice husk as a replacement activator can 
have additional benefits in biogenic CO2 reduction. Although changes in transportation distances had minimal 
impacts, potential savings for fossil fuel CO2 can be improved by minimizing transportation and using more 
sustainable energy sources and precursors. Focus can also be given to improve the chlor-alkali process by 
adopting renewable energy sources and by using emergent technologies in lowering the electricity 
requirements during electrolysis. This study shows that precast geopolymer production has global warming 
reduction potentials, and commercialization entails some sustainability gains. Further development of this 
work could be a study on the social impacts and techno-economic evaluation on the commercial scale 
adoption of this alternative material. 

240

250

260

270

280

Option1 Option2 Option3 Option4 Option 5

kg
 C

O
2 

eq
.

Climate change -
land use and
transformation

Climate change -
biogenic

Climate change -
fossil

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Acknowledgments 

The authors are grateful for the contributions of GreenDelta GmBH in offering OpenLCA as open-source 
software for Life Cycle Assessment and giving us a provisional academic license for the Ecoinvent 3.0 
database and to the University Research Coordination Office (URCO) De La Salle University-Manila for their 
support to the projects of the GAMERS Laboratory. 

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