Resources, Conservation & Recycling Advances 30 (2026) 200334

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Bi-objective optimization of low-carbon, low-cost scaffolding design using
bamboo and steel with a study in China
Xi Wei a , Fan Xue a,* , Jiajia Wang a , Dong Liang b
a
b

Department of Real Estate and Construction, The University of Hong Kong, Hong Kong Special Administrative Region of China
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region of China

A R T I C L E I N F O

A B S T R A C T

Keywords:
Bamboo-steel hybrid scaffolding
Bi-objective optimization
Net-zero energy building
Sustainable construction
Life cycle analysis

Sustainable structures in construction are increasingly promoted, yet sustainable temporary structures such as
scaffolding remain underexamined. Conventional scaffolding is predominantly constructed with either bamboo
or steel. Bamboo has low carbon emissions but raises regulatory and safety challenges sometimes. Steel ensures
high strength but produces high emissions. This paper proposes a low-carbon, low-cost bamboo-steel hybrid
scaffolding (BSHS) that leverages the environmental benefits of bamboo with the safety advantages of steel. A biobjective optimization model is formulated to minimize life cycle carbon emissions and total cost subjecting to
constraints of overweighted safety regulations; the baseline solver is Non-Dominated Sorting Genetic Algorithm
II (NSGA-II). A case study in Shenzhen, China, demonstrated that BSHS can reduce scaffolding-related carbon
emissions by up to 99.6 % compared to the baseline steelwork solution at a 4.7 % cost increase, while confidently
satisfying all safety requirements. Our findings also confirmed that the slight cost overrun will be offset and
eventually result in cost savings through the scale effect and easier learning curves, once the technology is widely
adopted. The contribution of this paper is two-fold. First, it formulates a bi-objective optimization framework for
sustainable scaffolding design. Secondly, the findings provided empirical evidence that BSHS reduces life cycle
carbon footprint while maintaining cost-effectiveness and regulatory compliance.

1. Introduction
Sustainable development is defined as “development that meets the
needs of the present without compromising the ability of future gener­
ations to meet their own needs” (Brundtland, 1987). Rapid urbanization
has created multiple challenges in the built environment, such as
increased construction waste, carbon emissions, and resource depletion.
The United Nations proposed 17 Sustainable Development Goals (SDGs),
comprising 169 specific targets (UN 2015). Goal 11 “Sustainable Cities
and Communities” issues an urgent call to action in the construction
industry to advance sustainable development.
The energy consumption and associated carbon footprint throughout
a building’s life cycle are central to sustainable development in the
construction industry (Sizirici et al., 2021). The built environment
contributes over 37 % of global energy-related carbon emissions (UNEP
2023). Buildings emit carbon across all stages, from construction,
operation, maintenance, to demolition (Chen et al., 2022). Some
buildings achieve carbon neutrality in operation and maintenance
through optimized designs (Lu et al., 2024), energy models (Meng et al.,

2026), advanced technologies, and green retrofitting (Rayegan et al.,
2024). Yet, other stages still produce a heavy carbon footprint.
Scaffolding is a critical yet often overlooked component of sustain­
able construction. Scaffolding contributes about 10–25 % of total con­
struction costs and 18–30 % of on-site labor (Yin and Caldas, 2022),
while the global scaffolding market was projected to reach USD 75
billion by 2030 (Tejas, 2025). However, carbon footprint of scaffolding
receives less attention than permanent structures in both practice and
literature. One possible reason is that scaffold designs were often
excluded from architectural and tender drawings (Kim and Teizer,
2014). Another possible reason was outsourcing of scaffolding to
specialized small firms relying on single-material systems, regardless of
site-specific conditions, scaffolding efficiency, and carbon emissions.
Sustainable scaffolding systems, thus, will be meaningful for achieving
net-zero energy building targets (Ibrahim et al., 2024).
Steel and bamboo are the two predominant scaffolding materials.
Bamboo scaffolds have prevailed in South and East Asia and Africa
(Sanni-Anibire et al., 2022), while steel dominates in the rest of the
world (Amede et al., 2022). Fig. 1 shows that bamboo’s sustainability

* Corresponding author.
E-mail addresses: weixi@connect.hku.hk (X. Wei), xuef@hku.hk (F. Xue), wjiajia@connect.hku.hk (J. Wang), leodong@connect.hku.hk (D. Liang).
https://doi.org/10.1016/j.rcradv.2026.200334
Available online 1 April 2026
2667-3789/© 2026 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Resources, Conservation & Recycling Advances 30 (2026) 200334

advantages, as it grows rapidly in 3–5 years and sequesters carbon as
about 50 % of dry weight (Sujarwo, 2016). After service life in site, reuse
in wastewater treatment or gardening applications can further reduce
the carbon footprint (Chang et al., 2018; Choy et al., 2005). In contrast,
steelwork generates notably more carbon emissions across stages: min­
ing, smelting, manufacturing, transportation, and recycling. Therefore,
in Hong Kong, bamboo scaffolding temporarily remains dominant under
local codes (HKLD 2024). While its use is declining due to safety con­
cerns, new regulations, and insufficient training programs for bamboo
scaffolders (HKDevB 2025).
Multi-objective optimization (MOO) methods optimize conflicting
goals simultaneously (Gunantara, 2018). MOO/BOO can provide theo­
retical computational approaches for studying bamboo-steel hybrid
scaffolding (BSHS), in order to integrate the advantages with regard to
structural safety and environmental sustainability.
This paper presents a modular, low-carbon BSHS design and its BOO
formulation. The objectives to minimize are life cycle carbon footprint
and total cost with constraints of minimum structural strength and given
site conditions, whereas the variables to determine include framework
configuration and material properties. Typical MOO algorithms, such as
Non-dominated Sorting Genetic Algorithm II (NSGA-II), can solve this
BOO problem for each site.
Contribution of this paper is two-fold. First, the BOO formulation of
BSHS quantifies sustainability and cost goals of bi-material scaffolding.
Second, the BOO results confirmed that BSHS considerably reduces life
cycle carbon footprint and maintains cost efficiency and safety
compliance.

for projects exceeding CNY 600,000 (approximately USD 84,000).
However, increased reliance on steel accelerates carbon emissions
throughout construction. For instance, China produced 1.005 billion
tons of crude steel in 2024, which is more than half of the world (Cai and
Zhu, 2025).
On the contrary, bamboo scaffolding was used in over 95 % of
Buildings Department-registered projects in Hong Kong in 1990s,
including large developments such as the Hong Kong Convention and
Exhibition Centre (Chang and Yu, 2002). Even though part of the
large-scale public projects has been shifted to steelworks in recent years,
bamboo remains a main scaffolding material in Hong Kong, India,
Nigeria, and several other regions. The Hong Kong Buildings Depart­
ment possesses detailed regulatory codes regarding the installation, use,
maintenance, and dismantling of bamboo scaffolding.
Bamboo scaffolding has several key advantages in Hong Kong. First,
Hong Kong is adjacent to bamboo sources of Guangdong and Guangxi
provinces (Fang et al., 2004). Bamboo’s light weight also reduces
transportation, installation, and dismantling costs compared with
steelwork (Amede et al., 2021). Additionally, its flexibility also suits
Hong Kong’s dense urban environment. Licensed scaffolders can do
on-site adjustments in length and positioning (Crolla, 2018). Bamboo
scaffolding is also time-saving due to its rapid assembly, requiring only
one-sixth the time of steelwork (Gebremariam et al., 2024).
2.2. Bamboo-steel hybrid applications in construction
Bamboo-steel hybrid materials have been applied to the construction
field to enhance sustainability. Bamboo’s carbon sequestration rate is
6–13 mg/ha/yr (Nath et al., 2015), which sheds light for a
carbon-efficient bamboo-steel hybrid structure (Zhang et al., 2021).
Although natural bamboo has a limited and varied service life in scaf­
folds, some processed bamboo building components, such as floor tiles,
can achieve a lifespan of 30–40 years (Gichohi, 2014).
The bamboo-steel hybrid composition can also provide considerable
structural strength. These hybrids can withstand compressive stresses of
up to 3656 kg/cm² (358.53 MPa) (Paudel, 2008). Bamboo’s tensile
strength reaches approximately 28,000 N/m² (0.028 MPa) (Nurdiah,
2016). Bamboo provides significant weight reduction while maintains
high structural strength for lightweight construction projects (Adier
et al., 2023).

2. Literature review
2.1. Bamboo scaffolding
Bamboo scaffolding has been widely used across South and East Asia
and parts of Africa, particularly in China and India, with abundant
bamboo resources. Fig. 2. shows historical records of bamboo protoscaffolding in China’s Sui and Tang dynasties (581–907 CE) (Li and
Kobayashi, 2004; Shi et al., 2013). The Northern Song dynasty
(960–1127 CE) marked systematic use of bamboo poles and wooden
rods for temporary architectural elements (Dlamini et al., 2022).
The use of bamboo in construction has decreased due to industrial­
ization. China’s governments have restricted bamboo scaffolding since
2000s due to its limitations, including insufficient material strength,
lack of standardization, decay, and flammability (Liu et al., 2022;
Ramanathan, 2008). The Ministry of Housing and Urban-Rural Devel­
opment (MOHURD) (2021) prohibited bamboo and timber scaffolding

2.3. Optimization in scaffolding design
Optimization algorithms, along with deep learning technologies
driven by optimization, have been applied in scaffolding engineering to

Fig. 1. Life cycle comparison of bamboo and steel scaffolding.
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Fig. 2. The history of bamboo scaffolding in China and Japan.

improve construction safety and management efficiency. Dzeng et al.
(2024) developed an automated system that leverages the YOLO algo­
rithm and augmented reality devices to detect defects in scaffolding
installations. Johansson and Jernek (2022) incorporated a
multi-objective genetic algorithm and linear programming to solve
constrained optimization problems in the scaffolding industry against
various building shapes and plot sizes. Takva et al. (2023) conducted a
cost analysis of H-frame façade scaffolding configurations about hori­
zontal and vertical dimensions. Blockchain technology has also been
applied in scaffolding project management (Yang et al., 2022; Kong
et al., 2025).

parameterized. The NSGA-II algorithm, together with Grasshopper and
Wallacei X software, was used for iterative computation to generate the
pareto frontier.
3.1. Site selection and analysis
The selected case site was an office building developed by China
Vanke Co., Ltd., as shown in Fig. 4. The site was located in Bao’an
District, Shenzhen, Guangdong Province. For this site, steel scaffolding
served as the primary type. The selected steel pipe type is Ф48 × 3, with
an outer diameter of 48 mm and a wall thickness of 3 mm. The weight of
this pipe type was approximately 3.329 kg/m. The bamboo pipes used
on this site followed the local technical code (MOHURD 2012), and
employed Moso bamboo (Phyllostachys edulis) with an average weight of
approximately 1.5 kg/m.

3. Research methods
Fig. 3 illustrates the four phases of the BSHS approach proposed in
this paper. Section 3.1 describes the site analysis phase. A construction
site in Shenzhen was selected, and the regional scaffolding codes under
the China’s National Standards (GB) were reviewed.
Section 3.2 defines the formulation phase. Structural safety clauses
from relevant regulations were quantified as material ratio constraints
(steel-to-bamboo) for the BSHS system. The life cycle carbon footprint
and total cost were modeled as the two optimization objectives.
Section 3.3 presents the optimization phase. Key variables—such as
structural framework configuration and material properties—were

3.2. BOO formulation definition
For all the pipes within the original scaffolding, define set U = {u1,
u2, …, uk}, k = | U |, ui is a single pipe position within the original
scaffolding design. For all the possible positions of pipe that can be
replaced by bamboo poles, define set X = {x1 , x2 ,...,xn },n = |X|, and xi
is one pole.
The BOO formulation consists of two objectives, as shown in Eq. (1).

Fig. 3. Research method.
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Fig. 4. Case site information (a) Building plan with scaffolding scheme. (b) Module of the scaffolding scheme.

optimized F(X){= min CE(X),}TC(X)
subject to X = x1 , x2 , …, xy , xi ∈ X, and 1 ≤ i ≤ y ≤ n,
C(X) ≥ 0

where esp2 is the carbon sink factor (CSF) of bamboo.
esp2 can be inferred from (Lv et al., 2025). In the transportation stage,
carbon emissions are primarily determined by vehicle energy con­
sumption, which includes direct emissions from the combustion of
gasoline and diesel, as well as indirect emissions from fuel production.
These two components of emissions are typically combined into emis­
sion factors. The carbon emission of BSHS from transportation stage Ct
is:

(1)

where X ⊆ X is a subset of bamboo poles; x ∈ X represents a bamboo
pole; CE(X) and TC(X) are the two objective functions regarding carbon
emissions and total cost, respectively; and y = | X | is the quantity of
bamboo poles in the design. The generalized constraints, C(X), represent
a series of mandatory requirements that must be satisfied. Define that
the distances from the case site to the steel scaffolding factory and the
bamboo scaffolding factory are d1 and d2, respectively. The weight of all
the bamboo poles in X is w1, and the weight of all steel pipes in U-X is w2,
respectively. To calculate the total weight of the two materials based on
the member lengths, overlapping factors (OFs) are necessary due to the
overlapping lengths requirement at the lashing nodes of components
intersections. According to the report from the Occupational safety and
Health Council of Hong Kong (2016), the OF for bamboo members is 1.5,
which means the effective length of a bamboo pole per unit length re­
quires 1.5 times the actual bamboo poles length. Similarly, the OF for
steel pipes is 1.16. Due to the different frame densities of bamboo
scaffolding and steel scaffolding, after replacing the steel pipes, the
density of bamboo needs to be increased at the replacement location to
ensure the rigidity of the structural strength.

Ct = et ⋅(d1 ⋅w1 + d2 ⋅w2 )

where et is the transport carbon emission factor per unit weightdistance, d1 the distance from case site to steel scaffolding factory, and
d2 the distance from case site to bamboo scaffolding factory.
et is mainly determined by the types of different transport vehicles
according to the standard GB-T51366–2019. Within this case site
context, the value of et is 0.179 kgCO2e /(t*km). At disposal phase,
common practices for steelwork involve smelting and recycling, which
saves carbon emissions from raw material extraction and processing.
Therefore, the carbon reduction benefits of steel recycling can be
quantified as Sp1:
Sp1 = esp1 ⋅w1

(2)

where ep1 is the carbon emission factor (CEF) of steel, and w1 is the
weight of all the bamboo poles in X.
As the steel pipe type is Ф48 × 3 carbon steel, the value of ep1 should
be 2310kgCO2e/t according to the standard GB-T51366–2019
(MOHURD 2019). The carbon emissions of bamboo material Cp2 is:
Cp2 = ep2 ⋅w2

(3)

where ep2 is the CEF of bamboo scaffolding, w2 is the weight of all steel
pipes in U-X.
The value of ep2 is 327 kgCO2e/t (Zhang et al., 2023). Meanwhile,
during the growth phase of bamboo, the carbon sequestration process
must also be accounted for alongside carbon emissions. The carbon
sequestration of bamboo material Sp2 is:
Sp2 = esp2 ⋅w2

(6)

where esp1 is the carbon sink factor (CSF) of steel material.
esp1 of steel is about 1280 kg CO2e/t (Wang et al., 2024). Common
disposal methods for bamboo include landfill, incineration for power
generation, recycling and reuse, and composting. When bamboo is
landfilled, it produces methane as a by-product. According to the IPCC
model, the carbon emissions from bamboo landfill (el) are about 0.75 kg
CO2e/kg (Ximenes et al., 2018). Incineration for power generation can
substitute coal combustion, resulting in net emission reduction for the
whole process. The carbon emissions (er) for this disposal method is
about − 0.4 kg CO2e/kg (Phuangchik et al., 2023). Recycling contains
sorting bamboo for reuse in construction or processing into furniture or
handicrafts, etc., which can extend the carbon storage duration. Carbon
emissions from composting are similar to landfill because of the reduc­
tion in emissions from chemical fertilizer production.
Bamboo scaffolding currently only accounts for a low proportion in
Shenzhen’s construction industry. The specialized statistics on bamboo
disposal are thus lacking. This paper adopts a simplified calculation
model based on Hong Kong’s patterns (Hossain et al., 2016) and
Shenzhen’s current construction waste classification and incineration
(Zhang et al., 2024; Yi et al., 2024). The disposal proportions are: 60 %
incineration for power generation, 20 % recycling and reuse, and 20 %
landfill treatment (Liang, 2022; Yu et al., 2020). Therefore, the carbon
emissions of BSHS from disposal stage Cd is:

3.2.1. Formulation for sustainability
The primary objective of this paper is to optimize the carbon foot­
print across the life cycle of scaffolding. A cradle-to-grave Life Cycle
Assessment (LCA) typically consists of four stages: production, trans­
portation, use, and disposal (Asdrubali et al., 2024; Laleicke et al.,
2015). In calculating carbon emissions, only those generated from
resource and energy consumption are considered, while human factors
are excluded. During the production stage, the carbon emission of steel
material Cp1 is:
Cp1 = ep1 ⋅w1

(5)

Cd = w2 ⋅(0.2⋅el + 0.6⋅er )

(7)

Where: el is the unit carbon emissions from bamboo landfill, and er is the
unit carbon emissions from bamboo recycling.
Finally, during the service phase of scaffolding, different materials

(4)

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Resources, Conservation & Recycling Advances 30 (2026) 200334

exhibit distinct usage cycles. Define the service life of steel scaffolding as
l1, and that of bamboo scaffolding as l2, while the actual usage duration
at the case site is denoted as P. Since scaffolding components are reus­
able, their utilization period at the case site constitutes only a portion of
their full life cycle. Therefore, for calculating carbon emissions during
the production and disposal phases of steel and bamboo components,
proportionality coefficients of P/l1 and P/l2 should be applied
respectively.
The total carbon emissions of BSHS CE(X) are thus as follows:
)
)
(
(
CE(X) = P/l1 ⋅ Cp1 − Sp1 + P/l2 ⋅ Cp2 − Sp2 + Cd + Ct
(8)

around 692 CNY. Considering that the BSHS is in the initial stage of
promotion, the bamboo scaffolders require extra training to be licensed
(SCMP 2025), the daily salary of bamboo scaffolders will be calculated
with a training cost coefficient f of 1.2. In the BSHS, both
bamboo-bamboo joint and bamboo-steel joint must be executed by
licensed scaffolders. Therefore, the total cost is the sum of rental cost and
labor cost:
TC(X) = RC + LC

3.2.3. Constraint
The constraint of this optimization is to fulfill the mandatory struc­
tural requirement of Shenzhen’s scaffolding regulation. According to the
safety and technical standard (HCBSM 2023) issued by the Shenzhen
Government, the Comprehensive Safety Factor β for normal working
scaffolding should meet the condition that β≥2.0, and the newly
developed scaffolding should fulfill the requirement that β≥2.2. In this
paper, β≥2.2 is taken as the safety constraint. The Comprehensive Safety
Factor β is defined as:

where P is the actual usage duration at the case site, l1 is the service life
of steel scaffolding, and l2 is the service life of bamboo scaffolding.
For this project, installation of the tower’s exterior scaffolding
commenced on September 5, 2018, and its dismantlement was
completed on October 20, 2019, resulting in a total service period of
13.5 months. This paper adopts 120 months as the service life for steel
fastener-type scaffolding and 30 months for bamboo scaffolding
(Gebremariam et al., 2024; Zhang et al., 2010).

β = γ 0 ⋅γu ⋅γm ⋅γʹm

3.2.2. Formulation for cost
For the rental cost part, the total rental cost RC of the two materials
is:
RC = w1 ⋅p1 + w2 ⋅p2

(12)

where γ 0 is the coefficient for importance of a structure, γ u is the
weighted average of load factor coefficients, γ m is the partial safety factor
for resistance of material, and γʹm is the material strength adjustment
coefficient.
For the coefficient for importance of a structure γ0 , the value of which
should be determined by the safety level. Within the context of the case
site, the building height exceeds 40 m, and the type of scaffolding is
landing working scaffolding, the safety level thus should be type II,
which means γ0 =1.0, on the basis of the standard.
For the weighted average of load factor coefficients γu , the value of this
variable is 1.395 for working scaffolding and 1.318 for shoring scaf­
folding in the light of the standard, γu =1.395 in the context of the case
site.
For the partial safety factor for resistance of material γ m , the value
should be 1.165 according to relevant provisions of the current national
standard Technical code of cold-formed thin-wall steel structures GB
50018–2002 (MOHURD 2002) for steel-pipe scaffolding. For the
bamboo scaffolding, the Standard for design of engineered bamboo struc­
tures T/CECS 1101–2022 (CECS 2022) set the lowest partial safety factor
for resistance of material of each grade of bamboo to 1.03. For the newly
developed scaffolding:

(9)

where p1 is the unit rental price of steel pipe, p2 is the unit rental price of
bamboo pole. According to the estimated market prices for scaffolding
rentals. The ratio of p1 to p2 is around 2.5, p1 equals to CNY184/t, thus p2
equals CNY73.6/t.
For the labor cost part, the joints between components are the pri­
mary consideration. The labor cost of the case site LC is:
LC = f(n1 + n3 )⋅(1/te1 + 1/td1 )⋅s1 + n2 ⋅(1/te2 + 1/td2 )⋅s2

(11)

(10)

Where: n1 is the number of bamboo-bamboo joints;
• n2 is the number of steel-steel joints;
• n3 is the number of bamboo-steel joints;
• te1 is the average number of bamboo joint erection per worker per
day;
• te2 is the average number of steel joint erection per worker per day;
• td1 is the average number of bamboo joint dismantled per worker per
day;
• td2 is the average number of steel joint dismantled per worker per
day;
• s1 is the average daily salary of metal scaffolders; and
• s2 is the average daily salary of bamboo scaffolders.

γ m = 1.165a + 1.03(1 − a)

(13)

Where: a is the ratio of steel-pipe to the BSHS.
For the material strength adjustment coefficient γʹm , the value of this
variable for the stability bearing capacity of newly developed working
scaffolding should be 1.433.
Therefore, in the context of the case site, the Comprehensive Safety
Factor should meet the conditions below:

According to the statistics from Hong Kong Occupational Safety and
Health Council (HKOSHC 2016), bamboo scaffolding demonstrates
significantly shorter erection and dismantling times than steel scaf­
folding due to its lightweight nature and band strapping assembly
method. Using average values, a bamboo scaffolder can erect 247 joints
per day (te1), while metal scaffolders can erect 133 joints per day (te2).
And the number of dismantling joints is 702 (td1) and 213 (td2) for
bamboo and metal scaffolders, respectively. To simplify the calculation
process, for the bamboo-steel joints, the erection and dismantling speed
is the average of those of bamboo-bamboo joint and steel-steel joint.
Only licensed scaffolders can take the job of erecting and dismantling
bamboo scaffolding. According to the report of Hong Kong media (HK01
2025), the daily salary of bamboo scaffolders is around 3000 HKD, while
the daily salary of normal metal scaffolders is about 1300 HKD, the ratio
is around 2.3:1. Taken this ratio as reference, the average daily salary of
metal scaffolders (s1) in Shenzhen region is 300 CNY. Thus, the daily
salary of bamboo scaffolders (s2) in Shenzhen region can be inferred

C(X) = β − 2.2 ≥ 0⇒a ≥ 0.52

(14)

This means that the ratio of steel pipes to the BSHS should be no less
than 52 %.
3.3. Optimization algorithm and analysis
This paper applies NSGA-II algorithm (Deb et al., 2002) to solve the
BOO problem. Alternatively, there are some other algorithms that can be
applied in BOO/MOO problems including Tree-structured Parzen esti­
mator (TPE) (Bergstra et al., 2011), Ant Colony Optimization (ACO)
(Dorigo et al., 1996), and Strength Pareto Evolutionary Algorithm 2
(SPEA-2) (Zitzler et al., 2001). NSGA-II is an algorithm with more
balanced performance in all aspects among the above algorithms.
Fig. 5 illustrates characteristic points typically observed in BOO
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Fig. 6. Examples of Pareto solutions for the scaffolding module.
Fig. 5. Characteristic points in the result of solving typical BOO problems.

4.2.2. Pareto frontier and the knee point
Each pink or blue point in Fig. 7 represents a BOO solution, where
the x- and y-coordinates correspond to the two objective function values.
Pink points denote Pareto-optimal solutions. The results indicate a
curved pareto frontier, demonstrating a negative correlation between
the two objectives.
The knee point on the pareto frontier was selected as follows. First,
we normalized the two objectives based on the maximum and minimum
values in
Fig. 7; Then, the point (113,323, 32) closest to the Utopia point was
identified as the knee point. The reference steelwork baseline at the
point of (108,245, 9957) is also marked in the figure, which represents
the total cost and carbon emissions of the steelwork scaffolding,
respectively. Compared to the steelwork baseline, the knee point ach­
ieved a 99.6 % reduction in life cycle carbon emissions with only a 4.7 %
increase in total cost. Fig. 8 shows the schematic rendering of the knee
point. Green pipes represent bamboo elements, while silver pipes indi­
cate steel components.

solutions. The two Anker points in orange represent the solutions where
the minimum values of the two objectives are achieved. These two
minima collectively define the ‘Utopia point’, which represents the ideal
but unattainable solution for this BOO problem (Zhou and Xue, 2023).
The Nadir point, by contrast, represents the least desirable solution. The
Pareto solutions in pink indicate solutions for which no other alternative
is superior in both objectives simultaneously. Collectively, all Pareto
solutions form the pareto frontier. Solutions excluded from the Pareto set
are dominated solutions, as they are inferior on one or both objectives
compared to Pareto solutions. The Knee point is the point on the pareto
frontier closest to the Utopia point, and it can theoretically be taken as
the final solution.
However, in real construction projects, the decision-maker can select
the final solution that best matches the site conditions from the Pareto
Frontier based on different weights of the two optimization objectives.
Furthermore, across different deployment stages, cities, and site condi­
tions, the coefficients in the formulations can be changed, to deliver
scenario-based design and analyses.
4. Experimental result and analysis
4.1. Experimental settings
The experiments were performed on a desktop computer equipped
with a 13th-generation Intel® Core™ i7–13,700 K (3.40 GHz) processor
and 128 GB of memory. The optimization process employed the NSGA-II
algorithm (Hamdy et al., 2016) through the Wallacei X plugin (ver. 2.7)
(Makki, 2025) on the Grasshopper platform (ver. 1.0), which is a
graphical algorithm editor tightly integrated with Rhino (ver. 7)’s 3D
modeling tools (McNeel, 2025). The NSGA-II parameters were set to
default values after preliminary testing: crossover probability = 0.9,
mutation distribution index = 20, and crossover distribution index = 20.
Remainders of NSGA-II parameters followed established guidelines in
the literature (Yusoff et al., 2011; Verma et al., 2021). Each generation
included 100 individuals, and 100 generations were executed, resulting
in 10,000 evaluated solutions.
4.2. Experimental results of the BOO problem
4.2.1. Experimental results
The total computation time was 92 min and 11 s to solve the BOO
problem using NSGA-II using Wallacei X on Grasshopper. A total of 537
Pareto-optimal solutions were obtained from 100 generations. Fig. 6
presents three example scaffolding modules derived from the Pareto
solutions.

Fig. 7. Pareto frontier and solution analysis.
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Fig. 8. Schematic rendering of the solution located at (113,323, 32).

4.3. Scenarios-based analysis
4.3.1. Structural reduction factor analysis
The final solution may vary depending on the applied partial safety
factor. In the early stage of BSHS adoption, data on material strength are
limited, and practical experience remains inadequate. To reflect such
constraints in the formulation, we moderate the structural reduction
factor to γm (the partial safety factor for resistance of material) of BSHS. For
example, when the reduction factors were 0.9 and 0.8, the corre­
sponding constraints became a ≥ 0.72 and a ≥ 0.81, respectively. The
results are shown in Table 1 and Fig. 9. The results indicate that varying
the reduction factor primarily affects the overall steel proportion in the
BSHS, ranging from 52 % to 81 %. Nevertheless, all selected optima
denotes that a modest increase in total cost results in a substantial
reduction in life cycle carbon emissions.
In practice, the final BSHS solution could be altered from the knee
point by decision-makers. For example, factors such as the national
Emissions Trading System (ETS), technological and workforce readiness,
and government incentives must be considered. Depending on the spe­
cific situations, the weights of the two objectives should be adjusted, and
the most suitable solution on the pareto frontier will be selected as the
final solution.

Fig. 9. Pareto solutions under different constraint requirements.

regression process, with the results shown in Fig. 10 and Table 2.
When f value decreases, the relationship between the two optimi­
zation objectives BOO simulation output gradually changes from nega­
tive correlation to positive correlation. The light blue area in Fig. 10
represents the range of feasible solutions under the constraint. When f =
1.15 and 1.1, certain regions of the solution distribution (light pink area)
exhibit a near-linear positive correlation trend. However, many feasible
solutions still show a near-linear negative correlation, and no solution
can completely dominate the original solution. The carbon reduction
costs of the optimal solutions selected at these points are 246.6 % and
327.6 % of the current carbon trading price, respectively.
When f = 1.05, solutions in the pink area show a trend of near-linear
positive correlation. In addition, most solutions in this area dominate
the original solution. However, due to the existence of constraints, there
is still no solution within the feasible range that can completely domi­
nate the original solution. At this point, the carbon reduction cost of the
optimal solution within the feasible range is only 33.7 % of the current
carbon trading price. This also means the promotion and application of
bamboo-steel hybrid scaffolding begin to yield practical benefits at this
point.
When f = 1, that is the ideal situation, the distribution of all solutions
approaches a near-linear positive correlation, meaning the minimum
values that simultaneously satisfy both the carbon emissions and total
cost optimization objectives can be achieved. Within the feasible range,
solutions that can completely dominate the original solution have
emerged. Compared to the all-steel solution, the BSHS can reduce both
the life cycle carbon footprint and total cost simultaneously at this point.
Overall, the training cost coefficient f will gradually decrease as the
BSHS becomes more widespread in real projects. Although a high f value
in the early stages of promoting BSHS will cause the carbon reduction
cost to be much higher than the average carbon trading price, once f falls
back to a reasonable range (around 1.05), the carbon reduction cost of

4.3.2. Comparison to the carbon trading price
The carbon trading price in China has been trending upward in
recent years (Wang et al., 2024). The current average secondary market
price in China is CNY 95.96 per t/CO2e (ICAP 2024). The selected
optimal solution to the BOO problem is (113,323, 32), indicating a
carbon reduction cost of CNY 511.63 per tCO2e compared with the
original all-steel solution (108,245, 9957). As mentioned in Section
3.2.2, at the very initial stage of promoting the BSHS, the training cost
for the bamboo scaffolders should be considered in the total labor cost.
In the above experiment, the training cost coefficient f in Eq. (10) was set
to 1.2 to reflect this concern. However, the training cost coefficient will
gradually decrease as the BSHS becomes more widespread in real pro­
jects, eventually returning to f = 1. This paper also conducted BOO
experiments for f values of 1.0, 1.05, 1.1, and 1.15 to simulate the

Table 1
Pareto solution analysis of three reduction factor values.
Reduction factor

Constraint

min CE(X)

min TC(X)

Selected solution

Improvement in CE(X)

Improvement in TC(X)

1
0.9
0.8

a ≥ 0.52
a ≥ 0.72
a ≥ 0.81

− 3420
1770
4300

108,245
108,245
108,245

(113,323, 32)
(112,550, 1929)
(111,425, 4389)

99.6 %
80.6 %
55.9 %

− 4.7 %
− 4.0 %
− 2.9 %

7

X. Wei et al.

Resources, Conservation & Recycling Advances 30 (2026) 200334

Fig. 10. Solutions for different f values.

should be taken into the grading criteria.
Secondly, government and regulators can leverage carbon marketassisted mechanisms to promote BSHS. Carbon sequestration benefit
achieved by substituting steel with bamboo can be traded in commercial
programs such as Emission Trading Schemes (ETS). The initial cost
premium of BSHS can thus be offset.
Last but not least, government and regulators should include hybrid
configurations into the temporary structure code. Moreover, a certifi­
cation category for "hybrid scaffolders" should also be established to
ensure workforce competency in assembly of mixed materials.

Table 2
Carbon reduction cost for different f values.
f
value

Final solution

Carbon reduction cost
per t/CO2e

Percentage to current carbon
trading price

1.20
1.15

(113,323, 32)
(111,023,
1121)
(109,675,
3916)
(108,664,
− 2981)
(105,639,
− 2981)

511.63
314.39

533.1 %
327.6 %

236.71

246.6 %

32.38

33.7 %

− 201.42

− 209.8 %

1.10
1.05
1.00

5.3. Limitations and future works
Nevertheless, this study has three major limitations. First, the anal­
ysis focuses only on the two dominant material choices in current
scaffolding markets. With ongoing advances in material science,
emerging sustainable materials, such as recycled plastic composites
(Acuña-Pizano et al., 2022), bio-based polymers (Skoczinski et al.,
2024), recycled aluminum (Thalmaier et al., 2025), and 3D-Printed
biodegradable materials (Alkhalidi and Hatuqay, 2020) are gradually
introduced to the market. Second, the discussion addresses only sus­
tainability and cost issues during the initial stage. Additional aspects
could be incorporated as further optimization objectives. Third, in
defining the formulations, various standards and documents related to
bamboo materials are involved. However, calculations may contain
deviations since that some references are outdated, and regulations
differ between Hong Kong and mainland China.
Therefore, future work is suggested in four aspects. First is about
material selection. Future studies will examine different hybrid mate­
rials, including newly developed ones. And for optimization objectives,
practical considerations such as construction time, overall weight, wind
resistance, fire resistance, moisture, and corrosion performance will be
included. Thus, the BOO model can be extended into a more compre­
hensive MOO framework (Jin et al., 2020). Moreover, alternative al­
gorithms of BOO problems can be tested to identify the most efficient
ones in the context of BSHS. Lastly, emerging technologies such as
Generative Artificial Intelligence (GenAI) and information
entropy-enhancement for NSGA-II (Zhou and Xue, 2025) can be adopted
into the MOO/BOO framework.

BSHS projects will be lower than the market carbon trading price. In the
ideal case where f = 1, it is even possible to achieve a win-win situation
of both cost savings and carbon emission reduction.
5. Discussion
5.1. Practical considerations and underlying mechanisms
To promote BSHS, the licensed bamboo scaffolder is a decisive factor.
Thus, the certification programs are required. Currently, limited engi­
neering experience with the hybrid scaffolding and the need to license
bamboo scaffolders from scratch increase short-term adjustment costs,
making BSHS slightly more expensive in terms of carbon reduction than
the current average carbon trading price. However, as the new scaf­
folding is scaled up and widely adopted, the cost premium will gradually
decline. An optimized BSHS can achieve significant reductions in carbon
footprint with only a minimal cost increase—or potentially no increase
at all. The main contributor to the carbon reduction is bamboo’s carbon
sequestration capability. Another considerable contributor is the reuse
and recycling of disposed bamboo poles.
The optimized BSHS integrates two building materials with distinct
mechanical properties. To mitigate potential safety risks brought by this
integration, this paper suggests two approaches. One is localizing the
structural reduction factor in Eq. (13). Decision-makers can adjust this
reduction factor for strength redundancy with reference to the analysis
in Section 4.3.1. The other is rigorous on-site protocols in practice.
Licensed scaffolders and multi-stage on-site safety inspections are the
two key levers in practical construction safety.

6. Conclusion
Scaffolding is a primary type of temporary structure, which accounts
for 10–25 % of total construction costs and 18–30 % of on-site labor
requirements. It is urgently needed for sustainable transformation to
fulfill the requirements of SDGs. Bamboo is an ideal scaffolding material
due to its sustainability, strength, flexibility, and long history of use.
This paper proposes a BOO approach for BSHS, with carbon emission
and total cost defined as two optimization objectives. A case site in
Shenzhen, China, was introduced to evaluate the BOO-BSHS framework.
After the selection among 91 Pareto-optimal solutions, the final design
achieved a 99.6 % reduction in life cycle carbon emissions with only a

5.2. Policy implications
Government and regulators always play a key role in the local econotechnological evaluation and adoption of BSHS. Standardization
regarding local materials and building standards is the first thing should
be established in parallel with a few exemplar pilot projects. Strict
criteria for scaffolding bamboo processing are crucial to ensure uniform
structural integrity. Key features about bamboo poles, such as the har­
vesting age, diameter variations, moisture, and chemical treatments,
8

Resources, Conservation & Recycling Advances 30 (2026) 200334

X. Wei et al.

4.7 % increase in total cost compared to the steelwork. Further analysis
suggests that BSHS is potential to achieve simultaneous reductions in
both carbon emissions and cost when it is widely adopted and worker
training costs decline. This represents a possible win-win scenario for
the scaffolding industry.
The contributions of this study are two-fold. First, the BOO formu­
lation of BSHS quantifies sustainability and cost goals of bi-material
scaffolding. Second, the BOO results confirmed that BSHS consider­
ably reduces life cycle carbon footprint and maintains cost efficiency
and safety compliance. The field of temporary construction structures is
always overlooked by mainstream sustainable building research. This
paper expands the application of BOO into the field of scaffolding,
establishing a methodological framework. The framework captures the
trade-offs between the two scaffolding materials regarding environ­
mental impacts and economic costs.
The BOO framework can be applied beyond the pilot case in
Shenzhen. It can be adopted to other urbanizing regions adjacent to
bamboo-producing area such as South and East Asia and Africa. What’s
more, the optimization framework serves as an adaptive template that
can be customized for any hybrid-material scaffolding, not only bamboo
and steel. Nevertheless, this study is limited by its focus on common
scaffolding materials, incomplete project objectives, and the reliance on
outdated regional bamboo codes.
Future research will thus test more materials, integrate additional
objectives into an MOO framework, explore more efficient algorithms
for BOO problems, and apply emerging technologies such as GenAI and
Vision-Language Models (VLMs) to enhance site analysis and hybrid
scaffolding design. These advancements are expected to accelerate the
scaffolding industry’s transition toward sustainable development.

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CRediT authorship contribution statement
Xi Wei: Writing – original draft, Visualization, Methodology,
Investigation, Conceptualization. Fan Xue: Writing – review & editing,
Validation, Supervision, Project administration, Funding acquisition,
Conceptualization. Jiajia Wang: Software, Methodology, Formal anal­
ysis, Data curation. Dong Liang: Resources, Data curation.
Declaration of competing interest
The authors declare the following financial interests/personal re­
lationships which may be considered as potential competing interests:
Fan, XUE reports financial support was provided by University
Grants Committee Research Grants Council. If there are other authors,
they declare that they have no known competing financial interests or
personal relationships that could have appeared to influence the work
reported in this paper.
Acknowledgement
The work presented in this paper was supported by the Hong Kong
Research Grants Council (C7080-22GF).
Data availability
The data used in this work will be available upon reasonable request.
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