Next Article in Journal
Super-Supportive Corporate Social Responsibility Behaviors in China’s Construction Enterprises
Previous Article in Journal
Robustness as a Design Strategy: Navigating the Social Complexities of Technology in Building Production
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Research on Carbon Footprint Calculation for the Materialisation Phase of Prefabricated Housing

School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013, China
*
Authors to whom correspondence should be addressed.
Buildings 2025, 15(19), 3588; https://doi.org/10.3390/buildings15193588
Submission received: 31 August 2025 / Revised: 29 September 2025 / Accepted: 30 September 2025 / Published: 5 October 2025
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

Abstract

Against the backdrop of accelerating global low-carbon transition, the construction sector has emerged as a critical domain for carbon reduction. This paper establishes a carbon footprint calculation model for the materialisation phase of prefabricated residential buildings, grounded in the theory of whole-life-cycle carbon and the carbon emission factor method. It delineates phase boundaries and carbon source composition, while integrating project data to formulate computational expressions. Using Building 1 of YT Apartments as a case study for phased assessment, results indicate that the building material production phase accounts for the highest proportion of emissions (90.76%), followed by on-site construction (3.83%), material transportation (2.92%), on-site assembly (1.27%), component manufacturing (0.86%), and component transportation (0.36%). This demonstrates that the building material production phase holds the greatest potential for emissions reduction, providing theoretical support for low-carbon strategies in prefabricated housing.

1. Introduction

During the 20th century, the greenhouse effect emerged as a critical issue amid relentless global industrial and technological advancement. Between 1972 and 2011, global carbon emissions (CEs) rose sharply, from 1.48 billion t to 3.13 billion t, significantly influencing climate change [1]; concurrently, the construction sector’s rapid expansion has intensified its environmental pressures, as it is recognised as one of the three largest global energy consumption and greenhouse gas emission sources, with the other two being industry and transport. In China, buildings alone contribute roughly 40–50% of total national emissions [2], but the IPCC Sixth Assessment Report indicates that the building sector has the potential to achieve net-zero emissions by 2050 through measures such as improving energy efficiency, strengthening demand-side management, and expanding the use of renewable energy [3]. To align with the Paris Agreement’s temperature targets and promote the realisation of the United Nations Sustainable Development Goals (SDGs), it is crucial to prioritise emission reduction within the construction sector.
In response, China has prioritised green building development at the policy level. Within the 14th Five-Year Plan for the Construction Industry, clear emphasis is placed on speeding up the adoption of prefabricated construction and encouraging environmentally friendly building practices, with the aim of driving the sector towards a low-carbon transformation [4]. Existing research indicates that prefabricated construction, owing to its industrialised and standardised advantages, possesses significant energy conservation and emission reduction potential [5,6]. Within the field of carbon footprint assessment for prefabricated buildings, while some scholars have explored the topic from various angles, most of their studies suffer from weak data foundations, as a substantial number rely heavily on industry databases (such as Ecoinvent and the China LCA Database), making it difficult to reflect regional variations in energy structures, transport modes, and component manufacturing processes [7]. In some studies, researchers consider only the component production phase, while others incorporate the transportation and construction assembly phases, leading to inconsistent boundaries in carbon footprint calculations [8,9]. Furthermore, existing research predominantly focuses on the construction or operational phases of prefabricated buildings, lacking systematic quantification and factor analysis for embodied phase carbon footprints. Given that residential buildings constitute the largest share of completed floor area (approximately 66%), research into carbon footprint accounting and reduction pathways for prefabricated housing holds significant practical relevance.
Drawing on life cycle carbon theory and the carbon emission factor approach, we conducted this study to develop a calculation model through which to assess the carbon footprint during the embodied stage of prefabricated residential buildings. Our model can be used to specify the boundaries and scope of embodied phase measurement and systematically examine the carbon source composition across different processes; on this basis, a database of carbon emission factors was combined with project-specific baseline data to formulate corresponding calculation expressions for each stage of the materialisation process. In order to verify the model’s applicability, Building 1 of the YT prefabricated apartment project was selected as a case example, and a staged carbon footprint evaluation was carried out for its materialisation phase.

2. Literature Review

2.1. Carbon Footprint Accounting Boundaries

In recent years, many scholars have used the life cycle assessment (LCA) method to analyse carbon footprint sources for buildings throughout their entire life cycles, or at specific stages; by applying quantitative analysis, this method is used to estimate the overall carbon footprint of a building and evaluate its environmental impacts. Regarding the full life cycle, Mei et al. [10] took a single urban building as an example and divided its life cycle into five stages—planning, material preparation, construction, operation and maintenance, and demolition—based on which they constructed a carbon emission calculation model through which to achieve accurate quantification of emissions at each stage. Valeria et al. [11] conducted a full life cycle comparative study of recycled and otherwise prefabricated wall panels, the results of which showed that the use of bio-based materials helps to reduce carbon emissions in circular buildings. Zhang et al. [12] proposed an integrated method, combining building life cycle carbon emissions with cost analysis, leveraging BIM technology to assess carbon intensity throughout a building’s entire life cycle. Xing et al. [13] established a dynamic life cycle assessment model through which to optimise a building’s thermal insulation performance through time series verification of upstream parameters, thereby predicting carbon emissions. Borja et al. [14] established a full life cycle carbon emission baseline for typical Spanish residential buildings, encompassing specific, operational, and total emissions across their entire life cycles. Tavares and Freire [15] conducted a full life cycle assessment for steel-framed lightweight prefabricated single-bedroom dwellings, comparing carbon footprints and environmental impacts across different climate zones, insulation levels, and energy system configurations. Gao et al. [16] proposed an integrated LCA and BIM simulation model for calculating the carbon emissions of prefabricated buildings (PBs) and timber buildings (TBs) throughout their life cycles, systematically evaluating these technologies’ carbon performances through case studies. Regarding the physical–chemical phase, Ma et al. [17] examined the impacts of factory production, logistics transport, and assembly construction on prefabricated building carbon emissions, and comparative results indicated lower overall energy consumption for prefabricated buildings compared to conventional constructions. Luo et al. [18] focused on carbon emission environmental impacts in the building operation stage and predicted and evaluated the carbon footprint through a multi-scenario model. Zhan et al. [19] studied the carbon emissions of residential prefabricated buildings in the materialisation stage, based on the LCA-BIM platform, and used a structural equation model to analyse the impacts of material selection, energy consumption, and material storage on emissions. Li et al. [20] utilised Dynamo parametric modelling and coding, integrated with BIM systems and IoT technology, in order to achieve carbon emission data integration, precise assessment, and real-time tracking during the materialisation phase. Liu et al. [21] used the data quantification DEMATEL-ISM-MICMAC method to conduct an in-depth analysis of the carbon footprint and key influencing factors of the materialisation stage of prefabricated houses, providing theoretical guidance for low-carbon emission reduction strategy formulation.
In recent years, with the rapid development of China’s prefabricated construction industry, academic interest in residential carbon footprint research has significantly increased. When scoping carbon footprint calculations, the authors of most studies still use life cycle assessment (LCA) methods to assess the carbon emissions of prefabricated homes from construction to demolition; however, the results of such methods often underappreciate the representative role of the materialisation phase in overall carbon emissions, as the materialisation phase can largely reflect the total carbon emission level of a building, while significantly reducing computational complexity. Further literature analysis shows that the materialisation phase can be broken down into the following five key components: building material production, building material transportation, component manufacturing, component transportation, and on-site construction operations.

2.2. Carbon Footprint Accounting Methods

Against the backdrop of deepening global urbanisation, traditional construction models render urban development a persistent and substantial carbon source; notably, in most mature cities, new buildings account for merely 1–2% of the existing stock annually, implying that, over the coming decades, more than 95% of carbon emissions will originate from existing structures. Promoting low-carbon new developments and green retrofits of existing buildings has thus become a critical pathway to carbon reduction. Carbon footprint accounting plays a pivotal role in this process, yet currently faces challenges, including inconsistent standards and ambiguous system boundaries. Cang et al. [22] proposed a building embodied carbon accounting method applicable to the schematic design phase, which extracts quantities from BIM models through coding and combines them with pre-constructed BE-level emission factors for rapid calculation. Ouellet et al. [23] analysed discrepancies in biogenic carbon accounting across 16 countries using three LCA methodologies for identical timber structures, revealing significant variations in outcomes based on differing biogenic carbon treatment approaches, despite identical methodologies. Tsay et al. [24] developed a digital carbon footprint calculation tool integrating Building Information Modelling (BIM) with parametric analysis; employing a dynamic life cycle assessment approach, it enables real-time calculation of embodied and operational carbon by inputting building geometric parameters (window-to-wall ratio, shading depth, etc.). Muheeb et al. [25] employed a parametric LCA methodology, utilising One Click LCA software and an Excel platform to conduct 630 iterative calculations across four structural systems (timber, steel, concrete, and composite structures), strictly adhering to ISO 14040 standards for carbon footprint assessment. Sun and Huang [26] employed stochastic frontier analysis to identify key influencing factors, constructing a predictive model integrating factor analysis and extreme learning machines (ELMs) for assessing and forecasting carbon emission intensity. Lu et al. [27] proposed a design process-oriented carbon footprint calculation method enabling rapid emission estimation under incomplete information conditions. Wang et al. [28] constructed a Multi-Region Input–Output (MRIO) model based on 2007 and 2012 input–output data, comparing carbon footprints and inter-regional implicit carbon flows across 30 Chinese provinces under production and consumption accounting principles. Gao et al. [29] systematically analysed building carbon footprint accounting and prediction models. Accounting primarily employs two methodologies, top-down (e.g., economic input–output models) and bottom-up (e.g., physical models), with the former predominantly used at the urban scale, while the latter applies to individual buildings. Liu et al. [30] systematically reviewed the evolution of carbon accounting methodologies; traditional approaches rely mainly on the IPCC emission factor method (bottom-up) and atmospheric concentration inversion (top-down), yielding annual emission inventories; on the other hand, emerging real-time carbon monitoring technologies have successfully reduced the accounting scale to daily, or even hourly, intervals by integrating multi-source high-frequency big data from the electricity, transport, and industry sectors.
Currently, diverse methods exist for calculating building carbon footprints, with field surveys, structural balance approaches, and carbon emission factor methods being the most widely applied and representing the mainstream research methodologies within this field.

3. Model and Methods

3.1. System Boundaries and Methodology for Prefabricated Housing Carbon Footprint Calculation During the Materialisation Phase

(1)
Time Boundaries
As illustrated in Figure 1, the prefabricated housing materialisation stage is divided into four sequential phases for this research. The first phase is building material production and transportation, which accounts for carbon emissions arising from raw material consumption during production, as well as energy used for logistics. The second phase is the factory production stage, during which carbon emissions result from energy consumed by machinery during prefabricated component processing and internal transport. The third phase covers prefabricated component transportation, including the fuel consumption associated with different transport modes. Finally, the on-site assembly stage incorporates carbon emissions from both material usage and mechanical energy during on-site operations such as pouring, hoisting, and installation [31].
(2)
Study Scope
During the building project construction, large quantities of various materials, construction machinery, and equipment are utilised. From raw material production to machinery operation and material and component transportation, each stage involves significant energy use and corresponding CO2 emissions. In this study, we consider carbon footprint contributions from major phases: building material production, energy consumption from mechanical operations, transportation emissions, and manual on-site activities. Minor operations and low-impact consumables are excluded. Since key building materials contribute most significantly to overall emissions, our analysis is focused on concrete, steel, cement, mortar, lime, timber, and water, while materials with smaller usage volumes are omitted due to their limited impacts.
(3)
Carbon Emission Factor Method
The carbon emission factor methodology was first introduced by the United Nations Intergovernmental Panel on Climate Change (IPCC) in 1996, as part of a standardised approach for calculating carbon emissions; since then, the methodology has undergone several updates, and the version currently in use originates from the 2006 IPCC guideline revision, in which carbon emissions are calculated by multiplying activity data from emission sources by standardised carbon emission factors [32].
The above method has a well-established methodological framework and good authority, making it suitable for various carbon emission calculation scenarios related to energy consumption and providing a reliable tool for assessing greenhouse gas emissions. Carbon emission coefficient method application examples include those by Quan [33], Yu [34], and Zhang [35], who used carbon emission coefficients to calculate and analyse the greenhouse gas emissions generated during the prefabricated building materialisation process. The calculation formula is as follows: “Carbon footprint = Carbon footprint factor × Activity data.” The carbon emission coefficient method can be further divided into the three following calculation methods.
The inventory method integrates diverse data resources and combines actual operating parameters from various fields to establish a systematic calculation model. While enabling dynamic carbon emission monitoring, it ensures the temporal and spatial comparability of inventory data, providing a reliable basis for formulating emission reduction strategies; this standardised calculation system covers the entire process from production to consumption, effectively linking emission data across different sectors, and it can meet regional-level greenhouse gas inventory requirements and support carbon footprint tracing in key industries, highlighting the foundational role of inventory compilation technology in environmental management.
The information modelling method is a quantitative assessment model for energy consumption and material flow, integrating multi-dimensional parameters from the design, construction, operation, and demolition stages; this model leverages BIM platforms to integrate multi-source data, forming a carbon footprint monitoring framework covering the entire building life cycle, and its parameterised database provides precise data support for carbon footprint calculations.
The mathematical modelling method uses building material production, transportation, and installation data as input variables for the formula “carbon footprint = carbon footprint factor × activity data”. It relies on engineering construction process inventory data to obtain key indicators, such as fuel consumption and process parameters, at each stage; selects corresponding carbon footprint factors based on industry characteristics; and uses the calculation formula to achieve precise carbon footprint tracing. The resulting scientific calculation system enables both enterprise-level carbon footprint management and regional greenhouse gas inventory compilation, providing a quantitative basis for developing differentiated emission reduction plans.
Based on these considerations, we adopted the carbon emission factor method and implemented mathematical modelling to develop a detailed carbon footprint calculation model for prefabricated housing in this study, enabling precise emission quantification throughout the materialisation stage.

3.2. Carbon Footprint Factor Determination

When determining carbon footprint factors, data selection should follow the principle of hierarchical matching, as follows: prioritise the use of carbon footprint factors provided by domestic data platforms, such as China’s Life Cycle Database (CLCD); if existing domestic data is outdated due to its statistical year being too early, supplementary data should be collected from recent domestic research on carbon footprints in the construction sector over the past five years, or carbon footprint factors should be reconstructed based on current industrial technology levels; when the above conditions cannot be met, international authoritative databases (such as Ecoinvent, ELCD) or peer-reviewed overseas research results may be used as alternative carbon footprint factors across regions, but the applicability of the data sources must simultaneously be explained, and regional adjustments must be made. Following this approach ensures that carbon footprint accounting throughout the building life cycle is based on reliable and regionally relevant data. The carbon footprint factors are detailed in Appendix A.1, Appendix A.2, Appendix A.3. and Appendix A.4.

3.3. Carbon Footprint Calculation Model for Prefabricated Housing During the Materialisation Phase

A carbon footprint calculation framework for the prefabricated housing materialisation phase was developed in this study, employing the carbon emission factor method and defining the system boundary to clarify the calculation scope. As expressed in Equation (1), the total carbon footprint is obtained by summing the carbon emissions across all relevant phases.
C = C 1 + C 2 + C 3 + C 4
In the formula, C denotes the total carbon footprint of the prefabricated residential building during the materialisation stage (kgCO2e), and C1C4 are the carbon footprint values for building material production and transportation, factory production, prefabricated component transportation, and on-site assembly stages, respectively.
The unified functional unit for result analysis is detailed in Equation (2).
C x / s = C x s
In the formula, C x / s denotes the carbon footprint value per unit area (kgCO2e/m2); S represents the building area (m2).

3.3.1. Carbon Footprint Calculation for Building Material Production and Transportation

The carbon footprint assessment for the production and transportation stages covers the complete life cycle flow of primary building materials, including the full manufacturing process, from raw material extraction and industrial processing to finished product dispatch, as well as greenhouse gas emissions arising from the energy consumed during transportation to precast plants and construction sites; this process is formalised in Equation (3).
C 1 = C Z S + C Z Y
In the formula, C Z S indicates the carbon footprint from building material production; and C Z Y is the carbon footprint from material transportation.
(1)
Building Material Production Stage
The carbon footprint for the building material production stage is calculated according to Equation (4).
C Z S = i = 1 n Q i × E c , i
In the formula, Q i denotes the quantity of consumption for the i-th primary building material; and E c , i represents the i-th major building material carbon footprint factor (kgCO2e/building material unit).
(2)
Building Material Transportation Phase
The carbon footprint for the building material transportation phase is calculated according to Equation (5).
C Z Y = n i = 1 Q i × D i × E y s , i + n m = 1 Q m × D m × E y s , m
In the formula, Q i   and   Q m represent material consumption for transportation to the prefabrication plant and material consumption for transportation to the site, respectively; D i and D m denotes the transport distances for materials delivered to the factory and site; and E y s indicates the carbon footprint factor per unit distance for each transportation mode (kgCO2e/Unit·km).

3.3.2. Carbon Footprint Calculation Model for the Factory Production Stage

As a distinctive process unit within the prefabricated construction model, the factory production stage fundamentally transforms the on-site operations characteristic of traditional in situ casting into standardised manufacturing within industrial workshops; this stage focuses on the comprehensive processing system for prefabricated components, specifically encompassing the use of standardised products to manufacture building elements of varying integration levels, alongside the carbon footprint generated by energy consumption during the internal transport of factory-produced goods within the premises.
Since the impacts of raw materials are already accounted for in the material production stage, the factory production stage focuses primarily on the energy usage from equipment operation, and the resulting carbon footprint is influenced by the production line layout, component complexity, and processing technology. Equations (6)–(8) are used for calculating in this stage.
C 2 = C S C + C Y S
In the formula, C S C denotes the carbon footprint value during the factory production stage (kgCO2e); and C Y S indicates the carbon footprint calculation for on-site transportation processes (kgCO2e).
C S C = n i = 1 Q y , i q y , i × P s , i × E e
In the formula, Q y , i is the quantity of the i-th type of prefabricated component (ALC precast wall panel, m2; other components, m3); q y , i denotes the production capacity per shift for each line of the i-th type of prefabricated component; and P s , i represents the shift output for the i-th type of factory-produced product (kWh/shift).
C Y S = n i = 1 Q y , i × T y i , j × R y c , j × E j
In the formula, Q y , i is the total volume of prefabricated components of the i-th type; T y i , j denotes the number of machine hours consumed by the j-th type of transport machinery for delivering the i-th type of prefabricated component on site (machine hours); and R y , j represents the energy consumption per unit shift for the j-th type of conveying machinery (energy consumption per shift).

3.3.3. Carbon Footprint Calculation Model for Prefabricated Component Transportation

Within the industrialised construction system transportation phase, the component transfer process may be analogous to manufacturing supply chain operations, comprising three sub-stages, as follows: firstly, vertical hoisting operations, during which factory crane equipment transfers components onto transport vehicles; secondly, horizontal conveyance processes, matching component characteristics and functional requirements to appropriate transport modes (vertical transport, horizontal transport, or bulk transport); finally, reverse hoisting operations at the construction site, used to achieve precise component stacking. Taking composite slab transportation as an example, the initial vertical hoisting requires a bridge crane for positioning and loading; horizontal transport employs low-loader trailers for long-distance conveyance; and, upon site arrival, truck-mounted cranes complete unloading and stacking, as illustrated in the following equation:
C 3 = C C Z 1 + C S P + C C D = C Z 4
In the formula, C 3 denotes the carbon footprint value during the transport phase (kgCO2e); C C Z 1 and C C Z 2 indicate carbon footprint values for the two vertical hoisting processes (kgCO2e); and C S P represents the carbon footprint value of the horizontal transport process (kgCO2e).
(1)
Vertical Transport Process
In prefabricated construction, secondary vertical hoisting operations are reciprocal in nature, allowing the calculation process to be streamlined and simplified. The vertical lifting machinery operating duration is determined according to the quantity of each type of prefabricated component, which enables an accurate energy use assessment. The carbon footprint associated with vertical transport is computed using Equation (10).
C C Z 1 + C C Z 2 = 2 × n i = 1 Q y , i × T y c i , j × R y c , j × E j
In the formula, Q y , i denotes the quantity of the i-th type of prefabricated component; T y i , j represents the machine hours required by the j-th type of lifting equipment to handle; and R y , j indicates the energy consumption per shift for the j-th lifting machine (kWh/shift).
(2)
Horizontal Transport Process
Horizontal transport energy consumption is influenced by the type of vehicle assigned to the prefabricated components, the load capacity, and the transport distance, and it is directly related to the energy consumption of the transport vehicle. The carbon footprint of the horizontal transport process is calculated according to Equation (11).
C S P = n i = 1 Q M y , i × D y , i × E y s , i
In the formula, Q M y , i denotes the weight (in t) of the i-th type of prefabricated component being transported; D y , i indicates the transportation distance between the factory and the construction site (km); and E y s , i is the carbon footprint factor for the i-th type of prefabricated component transport method (kgCO2e/Unit·km).

3.3.4. Carbon Footprint Calculation Model for the On-Site Assembly Phase

The ‘semi-prefabricated, semi-cast-in-place’ construction method employed in this study for prefabricated housing involves factory-prefabricating certain components, while assembling and finishing the remainder on-site. The assembly rate determines each method’s proportion, allowing flexible adjustment to achieve efficient construction, as illustrated in the following formula:
C 4 = C X S + C Z P
(1)
On-site Construction Phase
The carbon emissions associated with on-site construction mainly arise from two sources: (i) the energy consumed by construction machinery and equipment during operation, and (ii) the energy expenditure resulting from human labour involved in the assembly processes. Together, these two aspects represent the principal contributors to the carbon footprint during on-site construction.
C X S = C S G + C R G
In the formula, C S G indicates the carbon footprint values of machinery and equipment during on-site construction processes (kgCO2e); and C R G denotes the carbon footprint value from human involvement (kgCO2e).
The emissions produced by construction machinery are further quantified using Equations (14) and (15).
C S G = k h Q s , h × E Q h , k × E e , k
C R G = Q r × E e , r
In the formula, Q s , h is the total number of shifts performed by the h-th type of construction equipment; E Q h , k represents the energy consumption of the h-th type of construction machinery per k units of energy (energy consumption per unit shift); and E e , k denotes the carbon footprint factor for energy k (kgCO2e/kg).
(2)
Assembly Phase
On-site precision positioning of building components requires specialised equipment. Field operations primarily comprise three modules: horizontal prefabricated component assembly, vertical cast-in-place joint construction, and enclosure system installation. Carbon measurement during construction focuses on two core processes: component hoisting and positioning (lifting), and joint connection and fixation (installation).
Lifting refers to the process of transferring prefabricated components from storage yards to the construction site using specialised equipment, requiring tower cranes and lifting apparatuses; its carbon footprint primarily stems from lifting machinery diesel or electricity consumption. Installation connections are categorised into two types: removable mechanical connections, and cast-in-place fixed connections. The former encompasses dry construction techniques, such as high-strength bolt anchoring and robotic welding; the latter, involving minimal cast-in-place material usage and emissions already accounted for in the preceding building material production phase, is excluded from the construction phase carbon footprint. The carbon footprint of the assembly process is calculated using Equations (16)–(19).
C Z P = C D Z + C A Z + C R G
C D Z = ( n i = 1 P i × T i × E e ) × N i
C A Z = j R g s , j × T g s , j × E j × Q g s , i
C R G = Q r × E e , r
In the formulae, C D Z represents the carbon footprint value of hoisting machinery and equipment (kgCO2e); C Z P is the carbon footprint value of mechanical equipment installation (kgCO2e); C R G indicates the carbon footprint value of manual operations (kgCO2e); P i denotes the rated power (kw) of the i-th type of lifting machinery; T i is the time required for hoisting the i-th type of precast component (hours); N i represents the quantity of the i-th type of prefabricated component (units); R g s , j denotes the per-shift energy consumption of the j-th construction machine; T g s , j indicates the hourly consumption of the j-th machine under the i-th prefabricated component connection method (hours); and Q g s , i is the quantity of work for the i-th type of prefabricated component to be assembled.

4. Case Study

4.1. Project Overview

In this study, we took the YT Prefabricated Apartment Project in Ganzhou, Jiangxi Province, as our research object. The construction site is rectangular in shape, with a total floor area of 39,314.05 m2, approximately 27,282.7 m2 above ground and 12,031.35 m2 below ground. The primary components comprise one new eight-storey and two nine-storey high-rise residential public buildings, alongside a single-storey public building serving as a duty office. Specifically, Building 1 is an eight-storey residential block with a height of 29.1 m and a gross floor area of 8484.11 m2; Building 3 is a nine-storey block reaching 32.7 m in height and 8935.96 m2 in floor area; and Building 5 is also nine storeys high, with a total height of 33.45 m and a floor area of 9740.32 m2. The project also includes an underground car park and associated outdoor works. The prefabricated building area totals 23,532.16 m2, comprising Buildings 1, 3, and 5, and accounting for 37% of the gross floor area. For this research, we analysed Building 1 as a case study; this prefabricated concrete structure comprises one basement level and seven above-ground storeys, with a total floor area of 8484.11 m2.
For this research, a residential building project was taken as the case study, and our analysis places emphasis on examining the embodied carbon profile of prefabricated housing throughout the materialisation stage. Multiple building materials are utilised during the materialisation stage, some of which have minimal impacts on the overall carbon footprint due to low consumption volumes and the absence of established carbon footprint factors; consequently, calculations primarily focused on materials with substantial cumulative usage, high construction costs, and significant energy consumption, alongside mechanical equipment shifts. Lightweight materials and sporadically used tools were excluded from the assessment.
This residential development incorporated prefabricated staircases, composite slabs, and ALC wall panels, resulting in an assembly ratio of 35.75%, the specific component usage for which is detailed in Table 1.
Data collection for this study was conducted in three phases: Firstly, discussions were held with project partners to systematically gather foundational materials, including structural design drawings, construction bills of quantities, and raw material supply chain data. Building upon this step, field investigations were undertaken at prefabricated component production bases to meticulously record process parameters, equipment energy consumption rates, and on-site component logistics solutions. Finally, through regular thematic interviews, we focused on key carbon footprint nodes within the assembly workflow to systematically identify optimisation opportunities for emission reduction during technical implementation.

4.2. Prefabricated Building Carbon Footprint Assessment

4.2.1. Carbon Emissions from Material Production and Transportation

(1)
Material Production Stage
The dataset on material consumption used in this research was derived from the bill of quantities supplied by the construction enterprise. To address material diversity, a functional attribute classification method was employed for systematic integration. The building material production stage was divided into two distinct components for independent calculation: in situ construction and prefabricated processing. The respective results are presented in Table 2 and Table 3.
(a)
Carbon Emissions from Material Production in Cast-in-Place Construction
Based on the aforementioned calculations, an analysis of the carbon footprint distribution among primary building materials during the production phase for in situ construction is presented in Figure 2 and Figure 3.
Data analysis shows that, during the manufacturing stage, the carbon emissions of materials used in cast-in-place construction are largely concentrated in concrete (34.22%), steel (23.99%), and bricks and blocks (17.65%); this distribution pattern exhibits a significant positive correlation with the proportion of material usage in the project. For these high-carbon-footprint materials, environmental benefits should be maximised by optimising material mix ratios and usage based on physical and mechanical properties while ensuring structural integrity; refining aggregate grading design; enhancing steel recycling rates; and optimising masonry construction methods.
(b)
Carbon Emissions Associated with Prefabricated Materials Throughout The Manufacturing Stage
According to the data presented in Table 3, concrete components and steel reinforcement products generate the most significant greenhouse gas emissions throughout their entire life cycles, while steel moulds produce the lowest emissions. Within standardised construction systems, metal moulds function as reusable components, and the standardised specifications of these moulds significantly reduce the overall demand for moulding equipment; specifically, the area of standardised metal moulds used for prefabricated staircases is 57.1 m2, while the lateral surface area utilised for composite slab production is 30.8 m2.
Based on the aforementioned calculations, an analysis of the carbon footprint distribution across various materials for prefabricated components (precast composite slabs, precast staircases, ALC precast wall panels) is presented in Figure 4 and Figure 5.
It is estimated that the total greenhouse gas emissions produced in the raw material preparation stage of prefabricated components amount to 344,328.42 kgCO2e. Analysing emission composition revealed that ALC partition walls contribute the largest carbon footprint, at 164,662.6 kgCO2e (47.82% share) (in this case study, all internal partition walls were prefabricated wall panels); composite floor slabs followed, with a carbon footprint of 158,606.66 kgCO2e (46.06%); stair components had the lowest footprint, at 20,917.33 kgCO2e (6.07%); steel formwork, possessing reusable properties, was calculated separately, at 144.83 kgCO2e.
(2)
Building Material Transport Phase
The distance required for transporting building materials was calculated through electronic map tools, selecting the most suitable route from the supplier’s location to either the construction site or the prefabrication plant. Road freight was employed as the exclusive transport mode, with trucks delivering goods at full capacity, and then returning without load. To better capture the imbalance between outbound and return trips, we made adjustments to the emission factors assigned to transport vehicles, and the corresponding outcomes are illustrated in Table 4 and Table 5, as well as Figure 6 and Figure 7.
(a)
Carbon Emissions from Transporting Major Building Materials to the Construction Site
Table 4. Carbon emissions of building materials from the transportation stage to the construction site.
Table 4. Carbon emissions of building materials from the transportation stage to the construction site.
ProcessMaterial TypeWeight
(t)
Distance (km)Transport VehicleEmission Factor (kgCO2e/t·km)Carbon Emissions
(kgCO2e)
Delivery of building materialsCrushed stone601.9524Diesel lorry (heavy-duty 10 t)0.2713915.05
Sand213.7024Diesel lorry (heavy-duty 10 t)0.2711389.90
Timber62.0214.9Diesel lorry (heavy-duty 18 t)0.215198.68
Cement105.2130Diesel lorry (heavy-duty 30 t)0.13410.32
Mortar1493.8532.4Diesel lorry (heavy-duty 18 t)0.21510,277.69
Concrete8224.755.6Diesel lorry (heavy-duty 18 t)0.21510,609.93
Reinforcing steel230.50404Diesel lorry (heavy-duty 30 t)0.1312,105.91
Other steel products34.84232Diesel lorry (heavy-duty 30 t)0.131050.77
Other metals29.60232Diesel lorry (heavy-duty 18 t)0.2151476.30
Bricks6298.4230Diesel lorry (heavy-duty 10 t)0.27151,206.15
Thermal insulation10.5018Diesel lorry (heavy-duty 10 t)0.27151.22
Waterproofing41.4524Diesel lorry (heavy-duty 10 t)0.271269.56
Glass40.1535Diesel lorry (heavy-duty 30 t)0.13182.66
Paints and coatings21.4450Diesel lorry (heavy-duty 10 t)0.271290.51
(b)
Transportation of construction materials to the prefabrication plant
Table 5. Carbon emissions generated during the delivery of building materials to the prefabrication site.
Table 5. Carbon emissions generated during the delivery of building materials to the prefabrication site.
Transport processMaterial TypeWeight (t)Distance
(km)
Vehicle CategoryEmission Factor (kgCO2e/t·km)Carbon Emissions
(kgCO2e)
Delivery of raw materialsConcrete674.6360Diesel lorry (heavy-duty 18 t)0.2158702.73
Reinforcing steel42.16380Diesel lorry (heavy-duty 30 t)0.132082.70
Autoclaved aerated concrete495.9154Diesel lorry (heavy-duty 30 t)0.133481.29
Our analysis showed that the total transportation-related carbon emissions for major construction materials and prefabricated elements reached 107,701.38 kgCO2e; among them, masonry blocks accounted for the largest proportion, at 47.54%, with a carbon footprint of 51,206.15 kgCO2e, making them the primary carbon emission source. Concrete followed, at 22,793.95 kgCO2e; then steel, at 15,239.38 kgCO2e; and mortar, at 10,277.69 kgCO2e, accounting for 21.16%, 14.15%, and 9.54% respectively. By contrast, the emissions associated with the transportation of other materials were relatively insignificant.
Figure 6. Carbon footprint values of major construction materials and prefabricated components during the transport phase (kgCO2e).
Figure 6. Carbon footprint values of major construction materials and prefabricated components during the transport phase (kgCO2e).
Buildings 15 03588 g006
Figure 7. Share of carbon emissions during the transportation of key building materials and prefabricated components (%).
Figure 7. Share of carbon emissions during the transportation of key building materials and prefabricated components (%).
Buildings 15 03588 g007

4.2.2. Emissions from the Factory Production Stage

In this study, we examined three categories of prefabricated components—precast staircases, precast composite floor slabs, and ALC precast wall panels—among which staircases and precast composite slab components were manufactured via semi-automated production lines within the factory. Their standardised production sequence was as follows: form work surface preparation → mould assembly → embedded component positioning → reinforcement mesh fabrication → concrete placement → compaction → surface texturing → temperature-controlled curing. During prefabrication, concrete placement, compaction, and on-site transportation, automated equipment was utilised; meanwhile, mould assembly, embedded component positioning, and reinforcement tying required manual intervention. ALC panels were formed using specialised moulds on fully automated production lines, with process parameters and product performance meeting industrialised construction standards.
Through on-site inspection of the prefabricated component production base, capacity data for various component production lines and equipment energy consumption parameters were obtained. Research indicates that, after production and curing, components must be transported to temporary storage yards before being delivered to construction sites via specialised transport; this series of transport operations generates corresponding greenhouse gas emissions. The methodology for calculating emissions and the corresponding results are summarised in Table 6.

4.2.3. Carbon Footprint During Precast Component Transportation

During component transportation, both vertical and horizontal transport methods must be considered.
(1)
Vertical Transport
Vertical transport is employed to prevent damage and reduce subsequent construction difficulties. Prior to loading, hoisting frames should be assembled, components properly positioned and secured within the frames, and stabilised using flexible cushioning materials to ensure components remain undamaged during transit, when vehicles must start smoothly and maintain a steady speed. Particular care is required when manoeuvring turns or changing lanes, necessitating a reduction in speed well in advance and adopting a slow-speed approach to ensure the stability of precast elements, such as wall panels, and prevent overturning incidents. The carbon footprint results of the vertical transportation process are shown in Table 7.
(2)
Horizontal Transport
The prefabricated staircases and composite slabs were supplied locally by the same manufacturer, with a reasonable transport distance. The resulting emissions for the horizontal transportation stage are summarised in Table 8 and Table 9.
As shown in Figure 8, during prefabricated component transport, vertical lifting generated the largest emissions, totalling 7851.53 kgCO2e, whereas horizontal transport contributed 5400.90 kgCO2e. Examining component types, ALC precast wall panels exhibited the highest carbon footprint, at 7694.04 kgCO2e, primarily due to the exclusive use of ALC panels for all internal walls in this case study, as their high material density necessitated greater energy consumption during transport, while their fragility required specialised packaging and handling methods. Furthermore, the vertical hoisting operations involved were particularly demanding.

4.2.4. Emissions During the On-Site Assembly Phase

(1)
Cast-in-Place Construction Section
The carbon emissions associated with cast-in-place construction are mainly derived from construction machinery operation and manual labour. By analysing energy consumption data, the energy use for equipment and labour for each task can be calculated, with the results summarised in Table 9.
(2)
Precast Component Assembly Process
The assembly procedure for precast components comprises two stages: hoisting and positioning. Hoisting operations are executed using tower cranes and specialised lifting equipment, with lifting durations determined based on the contractor’s prior operational experience. The method for calculating associated emissions and the corresponding results are presented in Table 10.
Following the principle of clearly defining system boundaries, we examined the energy consumption associated with mechanical connection processes during prefabricated component installation. Fully threaded sleeve connections were used for stair elements and composite floor slabs, whereas clamp-type dry connection techniques were utilised for lightweight enclosure panels. The corresponding carbon emission results are summarised in Table 11.

4.2.5. Calculation Result Analysis for Prefabricated Housing Projects

Calculations based on the carbon footprint assessment model indicate that the total materialisation phase carbon footprint for this case study amounted to 3,687,123.13 kgCO2e, with a unit carbon footprint of 434.28 kgCO2e/m2. The carbon emission results corresponding to each stage are presented in Table 12.
To comprehensively examine the carbon emission characteristics, we compared the materialisation stage carbon footprint data within the overall life cycle of the case building. The carbon footprint distribution across different phases is displayed in Figure 9.
During the physical–chemical stage, the total carbon footprint was 3,687,123.13 kgCO2e, corresponding to 434.59 kgCO2e/m2 per unit building area; the emissions from the building material production process were the highest, reaching 3,346,493.51 kg of CO2e and accounting for 90.76% of the total. Building material transportation contributed 107,701.38 kgCO2e (2.92%). Prefabricated component production at the factory stage emitted 31,596.07 kgCO2e (0.86%), while component transportation at the logistics stage emitted 13,252.43 kgCO2e (0.36%). During the on-site construction phase, construction activities generated 141,097.11 kgCO2e (3.83%), and assembly activities generated 46,982.63 kgCO2e (1.27%). The results show that building material production was the dominant carbon emission source in the physical–chemical stage, while the contributions of other links were relatively limited.
Table 13 illustrates the carbon emission distribution across different sub-processes within the prefabricated subsystem. At the sub-project level of this study, we employed a breakdown by construction package to clearly distinguish construction activities for prefabricated components versus cast-in-place components. Detailed construction contents for each sub-project and sub-process are provided in Appendix A.5 (Table A8). Results indicate that prefabricated component production accounted for the highest proportion of total emissions (78.03%), followed by on-site assembly (9.32%) and factory manufacturing (6.77%). Material production and transportation contributed relatively minor shares, at 3.05% and 2.84%, respectively. The above granular classification enhances transparency and highlights differences between prefabricated and conventional construction models.
Table 14 presents corresponding results for cast-in-place subsystems, wherein material production became the dominant factor (94.48%), followed by building material transportation (2.96%), while on-site construction accounted for only 2.58%. The above distribution underscores the critical role of material production in determining the overall carbon footprint of cast-in-place structures.
As shown in Table 15, the majority of this building’s carbon footprint—97.62%—stems from the cast-in-place concrete frame and floor slabs. Although the prefabricated components (primarily lightweight partition walls and staircases) are numerous, their contribution to the project’s total carbon emissions is only 2.38%, because their material carbon intensity is inherently lower, and they do not constitute the primary structural elements.
It is important to note that, to clearly contrast the carbon emission difference between prefabrication and traditional cast-in-place methods, the carbon emissions for the cast-in-place portion (3,156,886.68 kgCO2e) specifically refer to emissions generated under the assumption that the entire project employs traditional cast-in-place techniques; therefore, the emissions share corresponding to materials used for prefabricated components was excluded from this calculation. The carbon emissions for the prefabricated portion (467,141.97 kgCO2e) independently account for the incremental emissions across the entire process resulting from the use of prefabrication technology, including the production and transportation of materials contained in prefabricated components, factory manufacturing, component logistics, and on-site installation. Therefore, the sum of these two carbon footprints does not equal the total materialisation phase carbon footprint; this discrepancy arises because the emissions from the materials in the prefabricated components were already deducted from the cast-in-place section and are subsequently counted again within the prefabricated section.

4.3. Uncertainty and Sensitivity Analysis

In order to enhance the credibility of this study’s results, we conducted uncertainty and sensitivity analyses on the key input parameters of carbon footprint accounting in the physical–chemical stage. Considering the differences in material production factors, as well as in energy emission factors and engineering quantity parameters among different databases and measured data, we set reasonable fluctuation ranges based on a triangular distribution. For instance, the emission factors of major building materials (such as cement and steel) were set at ±15%, and those of concrete materials were set at ±10%; the power emission factor was set at ±15%, and the diesel factor is set at ±10%; the fluctuation range of key material usage was ±5% to 15% (depending on the accuracy of the list); and the energy consumption of the factory and on-site machinery and the transportation distance were set at ±20%.
On this basis, Monte Carlo simulation was adopted to calculate the propagation of parameter uncertainty. After each random sampling, the sub-processes and the overall carbon footprint were recalculated to obtain the probability distribution of the final result. The simulation results are shown in Figure 10, showing an approximately normal distribution, with the peaks concentrated in the range of 420–450 kgCO2e/m2, corresponding to a median intensity per unit area of 435.2 kgCO2e/m2; the 95% confidence intervals were 401.9–468.4 kgCO2e /m2, indicating that, within a reasonable range of uncertainty, the overall value fluctuates, but the conclusion is robust. In conclusion, the results of this study verified the method’s robustness and the reliability of the results through uncertainty and sensitivity analyses. Although the numerical values of some molecular processes were greatly influenced by the assumed conditions, the core finding remains unchanged under different assumed and data conditions.

5. Discussion

For this research, we conducted an in-depth examination of the carbon emissions generated during the prefabricated housing materialisation stage, with a particular focus on the differences among its sub-processes. The results demonstrate that construction material production represents the principal emission source, contributing more than 90% of the overall footprint, a finding which is consistent with prior studies that highlight the substantial embodied carbon embedded in high-impact materials, such as cement and steel. Unlike many earlier investigations, primarily depending on generic databases (e.g., Ecoinvent, CLCD), and therefore lacking regional specificity, we incorporated project-level data into this study, offering a more context-sensitive evaluation aligned with local building practices, material supply systems, and energy mixes.
From a comparative standpoint, this work advances the literature in two key respects. First, while the authors of existing research often assess the overall carbon footprint of prefabricated buildings, detailed, phased quantification of emission distribution—particularly distinguishing the embodied carbon of prefabricated subsystems versus cast-in-place components—remains rare. While most studies focus on operational carbon or isolated aspects of prefabricated buildings, we used this research to subdivide the materialisation phase into five distinct process categories and provide a detailed emission assessment at each stage; this methodology enables precise identification of high-emission phases, facilitating the development of targeted mitigation strategies. Second, the results of this study provide empirical evidence for the debate comparing the environmental performance of prefabricated versus traditional construction. While industrialised production significantly reduces on-site emissions, the overall benefits may be offset if raw material sourcing and transportation retain high carbon footprints.
The above findings emphasise the crucial need to implement emission reduction measures within the upstream supply chain. Practical measures may include adopting low-carbon alternatives to cement, increasing the utilisation of recycled steel, optimising aggregate mix designs, and employing digital tools for logistics management in order to reduce transportation-related emissions. Furthermore, although on-site activities and component manufacturing contribute relatively less to the total footprint, enhancing energy efficiency and integrating renewable energy into prefabrication plants represent promising avenues for further emission reduction.
Compared to traditional cast-in-place construction methods, the prefabricated sections in this case study emitted 467,141.97 kgCO2e, representing a reduction of approximately 73% compared to the cast-in-place sections (3,156,886.68 kgCO2e), demonstrating the significant potential of prefabrication technology for emission reduction; however, it should be noted that its overall carbon benefits are highly dependent on the carbon intensity of raw materials and transportation distances.
Looking ahead, the evaluation framework established in this study can be deeply integrated with cutting-edge digital technologies, significantly enhancing the precision and efficiency of carbon management:
(1)
By embedding the carbon emission factors identified in this study into BIM component libraries, model-based carbon budgets can be automatically generated during the design phase.
(2)
Leveraging machine learning algorithms, carbon emission prediction models trained on historical project data can dynamically simulate and optimise carbon footprints under different design schemes, construction techniques, and supply chain layouts.

6. Conclusions

In alignment with the low-carbon transition objectives in the construction sector, we established a carbon footprint assessment framework for the prefabricated housing materialisation stage by employing the carbon emission factor method. The framework was applied to a representative prefabricated residential project, where its reliability was tested. In addition, a comparative evaluation was carried out between floors constructed with conventional cast-in situ techniques and those using prefabricated components. The major outcomes can be summarised as follows:
(1)
From a project-wide perspective, carbon emissions during the materialisation phase are highly concentrated in the building material production process, accounting for 90.76% of total emissions and representing the dominant emission source. The remaining phases contribute as follows: on-site construction (3.83%), building material transportation (2.92%), on-site assembly (1.27%), component manufacturing (0.86%) and component transportation (0.36%). The above distribution highlights that the building material production process holds the greatest potential for emission reductions.
(2)
From the perspective of the prefabrication subsystem, the prefabricated components accounted for 12.67% (467,141.97 kgCO2e) of the project’s total carbon emissions. Within this subsystem, emissions exhibit distinct components, with material production accounting for 78.03%, factory manufacturing 6.77%, component transportation 2.84%, on-site installation 9.32%, and material transportation 3.05%; this structure indicates that, while prefabrication reduces on-site construction emissions, its carbon benefits remain highly dependent on the carbon intensity of upstream supply chains. Although carbon emissions from prefabricated component transportation account for a relatively small proportion, their absolute value is positively correlated with transport distance; analysis indicates that the overall carbon benefits of prefabrication are highly dependent on the carbon intensity of upstream supply chains and logistics radii. If supply chain layouts are inefficient, leading to excessively long transport distances, the carbon advantages may be partially offset; therefore, promoting low-carbon building materials, optimising regional supply chain layouts, and enhancing factory energy efficiency are key pathways to achieving deep emission reductions in prefabricated construction.
The cast-in-place subsystem’s carbon emissions accounted for 85.62% (3,156,886.68 kgCO2e) of the project’s total emissions, highly concentrated in material production (94.48%), followed by building material transportation (2.96%) and on-site construction (2.58%); this distribution highlights that carbon emissions from traditional cast-in-place methods are primarily locked in the building material production stage. Reduction efforts should therefore focus on replacing and optimising high-carbon building materials.
(3)
Comprehensive comparisons indicate that, while prefabrication technology reduces on-site construction emissions through industrialised production, the carbon benefits of both construction methods remain highly dependent on the carbon intensity of upstream building material production. Achieving the overall carbon advantage of prefabrication requires multiple measures, including adopting low-carbon building materials, optimising regional supply chain layouts, and enhancing factory energy efficiency. From a theoretical perspective, this research enriches the literature on embodied carbon by clarifying the internal distribution of emissions during the materialisation phase; from a practical standpoint, it provides valuable references for policymakers, developers, and contractors in formulating effective strategies, such as promoting the use of low-carbon building materials, improving recycling systems, and enhancing production and logistics efficiency.
Several study limitations should be acknowledged. First, the exclusion of minor materials and consumables may result in an underestimation of total emissions in certain scenarios. Second, despite regional adjustments, the emission factors derived from national and international databases may not fully capture local technological conditions. Additionally, since the analysis is based on a single project in Jiangxi Province, the findings may have limited representativeness and transferability. To address these gaps, future research should aim to expand both regional and building-type coverage, incorporate dynamic life cycle assessment methods, and leverage advanced digital tools, such as BIM-based carbon monitoring and AI-driven predictive modelling. Such integration would significantly enhance the accuracy and practical utility of carbon footprint accounting. Specifically, future studies should focus on coupling the proposed model with Building Information Modelling (BIM) and AI-enabled analytics to enable real-time carbon emission tracking against predefined targets during construction, automated environmental product declaration (EPD) generation for building components, and dynamic scenario simulations at the design phase to rapidly evaluate the carbon impacts of various material selections and supply chain configurations.

Author Contributions

Concept and design, J.J. and Y.X.; Experimental work, W.L. and Y.X.; Methodology, J.J. and Y.X.; Resources, J.J.; Supervision, J.J.; Validation work, Y.X.; Drafting the manuscript denote Y.X. and Q.H.; Reviewing and editing denote J.J. and W.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data from this study are available upon request to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A. Summary Table of Carbon Emission Factors

To ensure the traceability of the research calculation results, the carbon emission factors adopted in this study are all sourced from authoritative standards, literature and related databases, covering energy, building materials, electricity and transportation links. The various carbon emission factors are as follows.

Appendix A.1. Carbon Emission Factors from Fossil Energy

Table A1. Main carbon emission factors of fossil energy.
Table A1. Main carbon emission factors of fossil energy.
Energy TypeCarbon Oxidation RateLower Calorific ValueCarbon ContentCO2 FactorN2O FactorCH4 FactorEmission Factor (kgCO2e/Unit)
Fuel oil0.980.00004221,1003.174410.633.18
Gasoline0.980.00004418,9002.928730.632.94
Diesel0.980.00004320,2003.099750.633.11
Raw coal0.980.00002126,3701.983631.511.99
Natural gas0.990.00003815,3202.167690.112.17
Crude oil0.980.00004220,0803.020950.633.03
Coal gangue0.980.00000825,8000.776331.510.78
Other coal washing0.980.00001025,4100.954511.510.96
Briquettes0.900.00002033,5602.315511.512.32
Coke0.930.00002129,4202.856171.512.87
Coke oven gas0.990.00001813,5800.887460.110.89
Washed clean coal0.980.00002625,4102.408391.512.42
Converter gas0.990.00007149,60014.30480.1114.31
Blast furnace gas0.990.00000312,2000.166860.110.17

Appendix A.2. Electricity Carbon Emission Factor

According to the grid regional carbon factor released by the Climate Change Strategy Institute (2019), carbon emission levels vary significantly due to different power source structures.
Table A2. Carbon footprint factors of regional power grids in China in 2019.
Table A2. Carbon footprint factors of regional power grids in China in 2019.
Power Grid AreaCovered ProvincesEmission Factor
(kgCO2/kWh)
Northeast Power GridLiaoning, Heilongjiang, Jilin1.0826
North China Power GridBeijing, Tianjin, Hebei, Shandong, Shanxi, Inner Mongolia0.9419
Northwest Power GridShaanxi, Gansu, Ningxia, Xinjiang, Qinghai0.8922
East China Power GridShanghai, Zhejiang, Fujian, Jiangsu, Anhui0.7921
Central Power GridHenan, Hubei, Jiangxi, Hunan, Chongqing, Sichuan0.8587
China Southern Power GridGuangxi, Guangdong, Guizhou, Yunnan, Hainan0.8042

Appendix A.3. Carbon Emission Factors of Building Materials

Appendix A.3.1. Building Raw Materials

Table A3. Carbon emission factors of building raw materials.
Table A3. Carbon emission factors of building raw materials.
Building Materials CategoriesMaterial NameUnitEmission Factor
(kgCO2e/Unit)
Note
Building Raw MaterialsTap watert0.168Calculation Standard (Based on CLCD)
Sandt2.51
Crushed stonet2.18
Clayt2.69
Limet1190
Fly asht8.385Take the mean value from the literature review
Timberm3178Literature [36] Recommendation score

Appendix A.3.2. Non-Metallic Materials

Table A4. Carbon emission factors of non-metallic materials.
Table A4. Carbon emission factors of non-metallic materials.
MaterialsBuilding MaterialsUnitEmission Factor
(kgCO2e/Unit)
Note
CementOrdinary Portland Cement (PO)t1120Literature [36,37], Calculation standard (based on CLCD) selected by average value
Slag Portland Cement (PS)t820
Pozzolanic Portland Cement (PP)t631.5Literature [36], Calculation standard selected by average value
ConcreteC20m3250Literature [36,37], Calculation standard (based on CLCD) selected by average value
C25m3267.7
C30m3287.7
C35m3307.7
C40m3327.7
C50m3367.7
MortarMasonry mortarm3220
Plastering cement mortarm310

Appendix A.3.3. Metal Materials

Table A5. Carbon emission factors of metal materials.
Table A5. Carbon emission factors of metal materials.
Building MaterialsMaterialsUnitEmission Factor (kgCO2e/Unit)Note
SteelHot-rolled carbon steel small sectionst2310Calculation Standard (Based on CLCD)
Hot-rolled carbon steel medium sectionst2365
Hot-rolled carbon steel large sectionst2380
Hot-rolled carbon steel reinforcing barst2340
Hot-rolled carbon steel high-speed wire rodt2375
AluminiumAluminium productst15,450Carbon Emission Calculation Standard for Buildings GB/T 51366-2019
IronIron products (such as iron nails and iron wire)t2000

Appendix A.3.4. Other Building Materials

Table A6. Carbon emission factors of other building materials.
Table A6. Carbon emission factors of other building materials.
Building MaterialsMaterialsUnitEmission Factor (kgCO2e/Unit)Note
Wall MaterialsConcrete bricksm3336Calculation Standard
(based on CLCD)
Autoclaved fly ash bricksm3341
Clay hollow bricksm3250
Solid shale bricksm3292
Sintered coal gangue solid bricksm322.8
Aerated concrete blocksm3270Carbon Emission Calculation Standard for Buildings GB/T 51366-2019
Sintered perforated bricksm3215
GlassToughened glasst1790Carbon Emission Calculation Standard for Buildings GB/T 51366-2019
General-purpose glasst1190
Thermal insulation materialsOrdinary polystyrene (PS)t4620Calculation standard (based on CLCD)
Rock wool boardt1980
Paints and coatingsPaint coatingst3500Carbon Emission Calculation Standard for Buildings GB/T 51366-2019
Waterproofing membranesABS-modified bitumen waterproofing membranem20.72Carbon Emission Calculation Standard for Buildings GB/T 51366-2019

Appendix A.4. Carbon Emission Factors in the Transportation of Building Materials

Table A7. Carbon emission factors for building materials transportation.
Table A7. Carbon emission factors for building materials transportation.
Transportation CategoryEmission Factor (kgCO2e/t·km)Emission Factor
(*1.67)
Light-duty diesel lorry transport (payload 2 t)0.2860.478
Medium-duty petrol lorry transport (payload 8 t)0.1150.192
Light-duty petrol lorry transport (payload 2 t)0.3340.558
Heavy-duty petrol lorry transport (payload 18 t)0.1040.174
Heavy-duty diesel lorry transport (payload 30 t)0.0780.130
Medium Diesel Lorry Transport (Payload 8 t)0.1790.299
Heavy Petrol Lorry Transport (Payload 10 t)0.1040.174
Heavy Diesel Lorry Transport (Payload 18 t)0.1290.215
Heavy Diesel Lorry Transport (Payload 10 t)0.1620.271
Heavy Diesel Lorry Transport (Payload 46 t)0.0570.095
Note: The Emission Factor (*1.67) should be applied in cases of empty return trips to account for the corrected carbon footprint factor.

Appendix A.5. Carbon Footprint Calculation for Traditional Cast-in-Place and Prefabricated Construction Methods

Table A8. Specific construction contents of each sub-item and sub-division.
Table A8. Specific construction contents of each sub-item and sub-division.
Sub-Projects and Sub-ItemsTraditional Cast-in-Place MethodAssembly Method
Masonry workMasonry Material ProductionALC Wall Panel Production
Masonry Material TransportationALC Wall Panel Transportation
On-Site Masonry ConstructionALC Wall Panel Installation
Steel bar engineeringReinforcement Production for Cast-in-Place SectionsPrecast Reinforcement Production
Reinforcement Transportation for Cast-in-Place SectionsPrecast Reinforcement Transportation
Reinforcement Fabrication and Assembly for Cast-in-Place SectionsPrecast Reinforcement Fabrication and Installation
Template engineeringConcrete Production for Cast-in-Place SectionsPrecast Concrete Production
Concrete Transportation for Cast-in-Place SectionsPrecast Concrete Transportation
Concrete Placement for Cast-in-Place SectionsPrecast Component Transportation and Installation
Concrete engineeringMaterial ProductionTypically, precast formwork can be reused in factories, with its environmental impact already factored into the carbon emission factor for component production. The on-site portion is accounted for in cast-in-place construction
Material Transportation
Formwork Construction

References

  1. Uncovering the lifecycle GHG emissions and its reduction opportunities from the urban buildings: A case study of macau. Resour. Conserv. Recycl. 2019, 147, 214–226. [CrossRef]
  2. Wang, G.; Luo, T.; Luo, H.; Liu, R.; Liu, Y.; Liu, Z. A comprehensive review of building lifecycle carbon emissions and reduction approaches. City Built Environ. 2024, 2, 12. [Google Scholar] [CrossRef]
  3. Pirani, A.; Fuglestvedt, J.S.; Byers, E.; O’Neill, B.; Riahi, K.; Lee, J.-Y.; Marotzke, J.; Rose, S.K.; Schaeffer, R.; Tebaldi, C. Scenarios in IPCC assessments: Lessons from AR6 and opportunities for AR7. Npj Clim. Action 2024, 3, 1. [Google Scholar] [CrossRef]
  4. Yu, H.; Wen, B.; Zahidi, I.; Fai, C.M.; Madsen, D.Ø. China’s green building revolution: Path to sustainable urban futures. Results Eng. 2024, 23, 102430. [Google Scholar] [CrossRef]
  5. Sun, S.; Chen, Y.; Wang, A.; Liu, X. An evaluation model of carbon emission reduction effect of prefabricated buildings based on cloud model from the perspective of construction supply chain. Buildings 2022, 12, 1534. [Google Scholar] [CrossRef]
  6. Wang, Q.; Guo, W.; Xu, X.; Deng, R.; Ding, X.; Chen, T. Analysis of carbon emission reduction paths for the production of prefabricated building components based on evolutionary game theory. Buildings 2023, 13, 1557. [Google Scholar] [CrossRef]
  7. Tian, Y.; Spatari, S. Environmental life cycle evaluation of prefabricated residential construction in China. J. Build. Eng. 2022, 57, 104776. [Google Scholar] [CrossRef]
  8. Cheng, Z.; Zhang, T.; Zhou, X.; Li, Z.; Jia, Y.; Ren, K.; Xu, T.; Li, C.; Hong, J. Life cycle environmental and cost assessment of prefabricated components manufacture. J. Clean. Prod. 2023, 415, 137888. [Google Scholar] [CrossRef]
  9. Zhu, H.; Ren, L.; Cai, M. Influencing factors and prevention and control of quality in the components production and transportation process of prefabricated building. Eng. Adv. 2023, 3, 101–104. [Google Scholar] [CrossRef]
  10. Shang, M.; Geng, H. A study on carbon emission calculation of residential buildings based on whole life cycle evaluation. E3S Web Conf. 2021, 261, 04013. [Google Scholar] [CrossRef]
  11. Cascione, V.; Roberts, M.; Allen, S.; Dams, B.; Maskell, D.; Shea, A.; Walker, P.; Emmitt, S. Integration of life cycle assessments (LCA) in circular bio-based wall panel design. J. Clean. Prod. 2022, 344, 130938. [Google Scholar] [CrossRef]
  12. Zhang, Y.; Jiang, X.; Cui, C.; Skitmore, M. BIM-based approach for the integrated assessment of life cycle carbon emission intensity and life cycle costs. Build. Environ. 2022, 226, 109691. [Google Scholar] [CrossRef]
  13. Su, X.; Huang, Y.; Chen, C.; Xu, Z.; Tian, S.; Peng, L. A dynamic life cycle assessment model for long-term carbon emissions prediction of buildings: A passive building as case study. Sustain. Cities Soc. 2023, 96, 104636. [Google Scholar] [CrossRef]
  14. Izaola, B.; Akizu-Gardoki, O.; Oregi, X. Setting baselines of the embodied, operational and whole life carbon emissions of the average spanish residential building. Sustain. Prod. Consum. 2023, 40, 252–264. [Google Scholar] [CrossRef]
  15. Tavares, V.; Freire, F. Life cycle assessment of a prefabricated house for seven locations in different climates. J. Build. Eng. 2022, 53, 104504. [Google Scholar] [CrossRef]
  16. Gao, H.; Wang, D.; Du, X.; Zhao, Z. An LCA-BIM integrated model for carbon-emission calculation of prefabricated buildings. Renew. Sustain. Energy Rev. 2024, 203, 114775. [Google Scholar] [CrossRef]
  17. Ma, W.; Sun, D.; Deng, Y.; Meng, X.; Li, M. Analysis of carbon emissions of prefabricated buildings from the views of energy conservation and emission reduction. NEPT 2021, 20, 39–44. [Google Scholar] [CrossRef]
  18. Luo, W.; Liu, W.; Liu, W.; Xia, L.; Zheng, J.; Liu, Y. Analysis of influencing factors and carbon emission scenario prediction during building operation stage. Energy 2025, 316, 134401. [Google Scholar] [CrossRef]
  19. Zhan, Z.; Xia, P.; Xia, D. Study on carbon emission measurement and influencing factors for prefabricated buildings at the materialization stage based on LCA. Sustainability 2023, 15, 13648. [Google Scholar] [CrossRef]
  20. Li, X.; Jiang, M.; Lin, C.; Chen, R.; Weng, M.; Jim, C.Y. Integrated BIM-IoT platform for carbon emission assessment and tracking in prefabricated building materialization. Resour. Conserv. Recycl. 2025, 215, 108122. [Google Scholar] [CrossRef]
  21. Liu, W.; Huang, Q. Research on carbon footprint accounting in the materialization stage of prefabricated housing based on DEMATEL-ISM-MICMAC. Appl. Sci. 2023, 13, 13148. [Google Scholar] [CrossRef]
  22. Cang, Y.; Luo, Z.; Yang, L.; Han, B. A new method for calculating the embodied carbon emissions from buildings in schematic design: Taking “building element” as basic unit. Build. Environ. 2020, 185, 107306. [Google Scholar] [CrossRef]
  23. Ouellet-Plamondon, C.M.; Ramseier, L.; Balouktsi, M.; Delem, L.; Foliente, G.; Francart, N.; Garcia-Martinez, A.; Hoxha, E.; Lützkendorf, T.; Nygaard Rasmussen, F.; et al. Carbon footprint assessment of a wood multi-residential building considering biogenic carbon. J. Clean. Prod. 2023, 404, 136834. [Google Scholar] [CrossRef]
  24. Tsay, Y.-S.; Yeh, Y.-C.; Jheng, H.-Y. Study of the tools used for early-stage carbon footprint in building design. e-Prime—Adv. Electr. Eng. Electron. Energy 2023, 4, 100128. [Google Scholar] [CrossRef]
  25. Al-Obaidy, M.; Courard, L.; Attia, S. A parametric approach to optimizing building construction systems and carbon footprint: A case study inspired by circularity principles. Sustainability 2022, 14, 3370. [Google Scholar] [CrossRef]
  26. Sun, W.; Huang, C. Predictions of carbon emission intensity based on factor analysis and an improved extreme learning machine from the perspective of carbon emission efficiency. J. Clean. Prod. 2022, 338, 130414. [Google Scholar] [CrossRef]
  27. Lu, M.; Luo, Z.; Cang, Y.; Zhang, N.; Yang, L. Methods for calculating building-embodied carbon emissions for the whole design process. Fundam. Res. 2024, 5, 2187–2198. [Google Scholar] [CrossRef]
  28. Wang, Z.; Li, Y.; Cai, H.; Wang, B. Comparative analysis of regional carbon emissions accounting methods in China: Production-based versus consumption-based principles. J. Clean. Prod. 2018, 194, 12–22. [Google Scholar] [CrossRef]
  29. Gao, H.; Wang, X.; Wu, K.; Zheng, Y.; Wang, Q.; Shi, W.; He, M. A review of building carbon emission accounting and prediction models. Buildings 2023, 13, 1617. [Google Scholar] [CrossRef]
  30. Liu, Z.; Sun, T.; Yu, Y.; Ke, P.; Deng, Z.; Lu, C.; Huo, D.; Ding, X. Near-real-time carbon emission accounting technology toward carbon neutrality. Engineering 2022, 14, 44–51. [Google Scholar] [CrossRef]
  31. Zhou, J.X.; Shen, G.Q.; Yoon, S.H.; Jin, X. Customization of on-site assembly services by integrating the internet of things and BIM technologies in modular integrated construction. Autom. Constr. 2021, 126, 103663. [Google Scholar] [CrossRef]
  32. Hiete, M.; Berner, U.; Richter, O. Calculation of global carbon dioxide emissions: Review of emission factors and a new approach taking fuel quality into consideration. Glob. Biogeochem. Cycles 2001, 15, 169–181. [Google Scholar] [CrossRef]
  33. Quan, C.; Cheng, X.; Yu, S.; Ye, X. Analysis on the influencing factors of carbon emission in China’s logistics industry based on LMDI method. Sci. Total Environ. 2020, 734, 138473. [Google Scholar] [CrossRef] [PubMed]
  34. Yu, H.; Yang, Y.; Li, B.; Liu, B.; Guo, Y.; Wang, Y.; Guo, Z.; Meng, R. Research on the community electric carbon emission prediction considering the dynamic emission coefficient of power system. Sci. Rep. 2023, 13, 5568. [Google Scholar] [CrossRef] [PubMed]
  35. Zhang, L.; Yan, Y.; Xu, W.; Sun, J.; Zhang, Y. Carbon emission calculation and influencing factor analysis based on industrial big data in the “double carbon” era. Comput. Intell. Neurosci. 2022, 2022, 2815940. [Google Scholar] [CrossRef]
  36. Zhang, X. Research on the Quantitative Analysis of Building Carbon Emissions and Assessment Methods for Low-Carbon Buildings and Structures. Ph.D. Thesis, Harbin Institute of Technology, Harbin, China, 2018. [Google Scholar]
  37. Hu, R. Carbon Emission Measurement of Prefabricated Buildings in Physicochemical Stage. Master’s Thesis, Guangzhou University, Guangzhou, China, 2024. [Google Scholar]
Figure 1. Division of the materialisation stage of prefabricated housing.
Figure 1. Division of the materialisation stage of prefabricated housing.
Buildings 15 03588 g001
Figure 2. Carbon emissions from key construction materials applied in cast-in-place structures (kgCO2e).
Figure 2. Carbon emissions from key construction materials applied in cast-in-place structures (kgCO2e).
Buildings 15 03588 g002
Figure 3. Share of carbon emissions attributed to primary construction materials in cast-in-place components (%).
Figure 3. Share of carbon emissions attributed to primary construction materials in cast-in-place components (%).
Buildings 15 03588 g003
Figure 4. The quantified carbon footprint of prefabricated elements within the production stage of construction materials.
Figure 4. The quantified carbon footprint of prefabricated elements within the production stage of construction materials.
Buildings 15 03588 g004
Figure 5. The relative contribution of carbon emissions during the material production stage of prefabricated buildings.
Figure 5. The relative contribution of carbon emissions during the material production stage of prefabricated buildings.
Buildings 15 03588 g005
Figure 8. Carbon footprint during the transportation stage of prefabricated components (kgCO2e).
Figure 8. Carbon footprint during the transportation stage of prefabricated components (kgCO2e).
Buildings 15 03588 g008
Figure 9. The proportion of carbon footprint in each stage of the physical and chemical phase of prefabricated buildings.
Figure 9. The proportion of carbon footprint in each stage of the physical and chemical phase of prefabricated buildings.
Buildings 15 03588 g009
Figure 10. The probability distribution of carbon intensity per unit area in the physical and chemical stage.
Figure 10. The probability distribution of carbon intensity per unit area in the physical and chemical stage.
Buildings 15 03588 g010
Table 1. Use of prefabricated components in prefabricated buildings.
Table 1. Use of prefabricated components in prefabricated buildings.
Prefabricated Component TypeComponent LocationNumber of Components
(pcs)
Component Volume (m3)
Prefabricated StairsAbove 2nd Floor5632.771
Prefabricated Composite SlabsAbove 2nd Floor759248.321
ALC Prefabricated Wall Panels (100 mm thick)Internal Partition Walls46,146876.142
ALC Prefabricated Wall Panels (200 mm thick)Internal Partition Walls115.6839
Table 2. Inventory of embodied carbon emissions by material type during the materialization stage.
Table 2. Inventory of embodied carbon emissions by material type during the materialization stage.
CategoryMaterial TypeMeasurement UnitQuantity UsedEmission Factor
(kgCO2e/t) or (kgCO2e/m3)
Carbon Emissions (kgCO2e)
Raw MaterialsWatert3111.700.168522.77
Gravelt601.952.181312.24
Sandt213.702.51536.39
Timberm362.0217811,039.20
CementCement (32.5)t105.2182086,272.20
MortarMasonry Mortarm3359.6322079,118.60
Plastering Mortarm3387.29277107,279.33
ConcreteC20m3265.7125066,426.25
C25m3483.10267.7129,326.14
C30m31801.00287.7518,147.70
C35m3256.55307.778,940.44
C40m3534.87327.7175,276.24
C50m3161.30367.759,311.48
SteelHot-rolled small sectiont35.90231082,919.76
Hot-rolled medium sectiont20.92236549,463.98
Hot-rolled high-wiret34.84237582,745.00
Hot-rolled rebart215.852340505,089.00
Other MetalsAluminum Compositet16.7415,450258,633.00
Iron Productst12.86200025,714.00
Bricks and BlocksShale Solid Bricksm3449.97292131,391.24
Sintered Perforated Bricksm3462.3021599,394.50
Concrete Bricksm3456.10336153,249.60
Clay Hollow Bricksm3396.2625099,065.00
Sintered Gangue Solid Bricksm3816.9922.818,627.37
Bricks and BlocksAutoclaved Aerated Concrete Blocksm3104.1827028,128.60
GlassTempered Glasst14.33179025,643.54
General Glasst25.82119030,725.80
WaterproofPolymer-Modified Asphalt Self-Adhesive Membranem22827.390.722035.72
Thermal InsulationRock Wool Boardt10.50198020,790.00
Coatings and PaintsPaints and Coatingst21.44350075,040.00
Total carbon footprint value: 3,002,165.08 kgCO2e
Table 3. Carbon footprint in the production stage of prefabricated building materials.
Table 3. Carbon footprint in the production stage of prefabricated building materials.
CategoryMaterialUnitConsumptionEmission Factor
(kgCO2e/t) or (kgCO2e/m3)
Carbon Emissions (kgCO2e)
Prefabricated staircasePrecast concrete C30m332.77287.79427.93
Reinforcing steelt4.91234011,489.40
Precast composite slabPrecast concrete C30m3248.32287.771,441.66
Reinforcing steelt37.25234087,165.00
ALC Precast Wall Panel, 100 mm ThickAutoclaved aerated concretem3876.14166.02164,662.60
ALC Precast Wall Panel, 200 mm Thick115.68
Steel formworkSteel formworkt0.06142310141.83
Total carbon footprint value: 344,328.42 kgCO2e
Table 6. Estimated greenhouse gas emissions from the production and on-site transport of prefabricated components.
Table 6. Estimated greenhouse gas emissions from the production and on-site transport of prefabricated components.
ProcessPrefabricated Component CategoryProduction MethodTotal Machine-Shift Consumption
(Shifts)
Total Machine-Shift Consumption (kWh/Shift)Emission Factor
(kgCO2e/kWh)
Carbon Emissions (kgCO2e)
Production of Precast ComponentsPrefabricated staircasesSemi-automated production line1.5062880.8587372.44
Prefabricated composite slabsSemi-automated production line15.186080.85877925.32
ALC prefabricated wall panelsAutomated production line29.916400.858716,438.13
Intra-site transportPrefabricated staircasesFlatbed trailer set1.50745.393.11212.73
Composite slab balconiesFlatbed trailer set11.4245.393.111612.08
ALC prefabricated wall panels8-tonne lorry45.6235.493.115035.37
Total carbon footprint value: 31,596.07 kgCO2e
Table 7. Carbon footprint of vertical transportation of prefabricated components.
Table 7. Carbon footprint of vertical transportation of prefabricated components.
ProcessPrefabricated Component CategoryTransport MachineryUnit Shift Consumption
(kWh/Shift)
Total Shift Consumption
(Shifts)
Emission Factor
(kgCO2e/kWh)
Carbon Emissions
(kgCO2e)
Vertical TransportALC Precast Wall PanelsTruck-mounted crane 12 t30.5555.523.115274.99
Precast Composite SlabsTruck-mounted crane 30 t42.1417.383.112277.74
Precast StaircasesTruck-mounted crane 30 t42.142.283.11298.81
Table 8. Emissions associated with horizontal transport of prefabricated components.
Table 8. Emissions associated with horizontal transport of prefabricated components.
ProcessComponent TypeTransport MethodDistance
(km)
Weight
(t)
Emission Factor (kgCO2e/t·km)Carbon Emissions
(kgCO2e)
Horizontal transportPrefabricated ALC wall panelsDiesel lorry (heavy-duty 10 t)18495.910.2712419.05
Prefabricated composite slabsDiesel lorry (heavy-duty 30 t)32633.220.132634.20
Prefabricated staircasesDiesel lorry (heavy-duty 30 t)3283.570.13347.65
Table 9. Carbon footprint during the cast-in-place construction stage Carbon footprint during the cast-in-place construction stage.
Table 9. Carbon footprint during the cast-in-place construction stage Carbon footprint during the cast-in-place construction stage.
Serial NumberType of Construction EquipmentTotal Operating Shifts
(shifts)
Energy Consumption per Shift (kWh/Shift)Emission Factor (kgCO2e/kWh)Carbon Emissions (kgCO2e)
1Rebar straightening machine 40 mm36.7756.53.116461.04
2Diesel3103.18713.116584.06
3Electric compactor 250 N·m0.56216.60.85878.01
4Electric13,176.26210.858710,455.76
5Truck-mounted crane 8 t5.24328.43.11463.08
6Truck-mounted crane 16 t4.36935.853.11487.12
7Truck-mounted crane 20 t8.89738.413.111062.79
8Truck-mounted crane 40 t4.348.523.11648.86
9Self-erecting tower crane 400 kN·m177.254164.310.858725,009.30
10Self-erecting tower crane 2500 kN·m0.43266.040.858798.23
11Gantry crane 10 t0.05388.290.85874.02
12Motorised tipper truck 1 t0.3716.033.116.96
13Mortar mixer 200 L11.3518.610.858783.92
14Dry-mix mortar drum mixer11.79628.510.8587288.78
15Concrete screed machine 5.5 kW4.64123.140.8587844.29
16Rebar straightening machine 40 mm0.1541.60.85871250.34
17Rebar cutting machine 40 mm30.6332.10.858792.49
18Rebar bending machine 40 mm113.75712.80.85870.21
19Circular saw for timber 500 mm4.488240.85870.33
20Sheet metal levelling machine 16 mm × 2000 mm0.002120.60.85874688.90
21Edge planer 12,000 mm0.00575.90.85870.87
22Semi-automatic cutting machine 100 mm55.719980.85871.05
23Shape steel shears 500 mm0.01953.20.858726.81
24Shape Steel Straightener 60 mm × 800 mm0.01964.20.85875224.74
25AC Arc Welder 21 kVA0.51860.270.858785.73
26AC Arc Welder 32 kVA63.03296.530.8587906.29
27AC Arc Welder 42 kVA0.755132.230.85871781.34
28Butt Welder 75 kVA8.6511220.858716.34
29Electroslag Welder 1000 A14.1121470.8587651.39
30Electric Air Compressor 3 m3/min0.177107.50.85876632.63
31Electric Multi-Stage Centrifugal Clean Water Pump 100 mm4.205180.40.8587989.39
32Lorry 6 t64.19333.243.1114.39
338-tonne lorry8.96435.493.11922.72
3412-tonne lorry0.146.273.110.97
3515-tonne lorry5.22956.743.11210.90
3620-tonne lorry0.00562.563.111.52
3720-tonne flatbed trailer unit1.49445.393.115401.06
3810-tonne rail flatcar0.04836.80.85870.18
39Single-cage construction hoist 1 tonne 75 m148.62542.320.85870.20
40Woodworking three-sided planer 400 mm0.00452.40.858729.20
41Radial drill press 50 mm0.0249.870.85876461.04
42Welding rod drying oven 45 × 35 × 45 (cm3)5.0766.70.85876584.06
Total carbon footprint value: 81,436.21 kgCO2e
Table 10. Carbon emission during the assembly of prefabricated components.
Table 10. Carbon emission during the assembly of prefabricated components.
Serial No.Construction MachineryQuantity (Units)Lifting Duration (h)Lifting Machinery Power
(kw)
Emission Factor
(kgCO2e/kWh)
Carbon Emissions
(kgCO2e)
1Prefabricated staircases560.2350.8587336.61
2Prefabricated composite slabs7590.2350.85874562.27
3ALC precast wall panels, 100 mm thick96400.15350.85874345.88
4ALC precast wall panels, 200 mm thick36,5060.15350.858732,915.09
Table 11. Carbon emission of ALC lightweight wall panels during the assembly phase.
Table 11. Carbon emission of ALC lightweight wall panels during the assembly phase.
Serial No.Prefabricated ComponentConstruction MachineryTotal Shift Consumption
(Shifts)
Unit Shift Consumption
(kWh/shift)
Emission Factor
(kgCO2e/kWh)
Carbon Emissions
(kgCO2e)
1Prefabricated staircasesStraight thread connections are not included
2Prefabricated composite slabs
3ALC prefabricated wall panelsSheet metal cutting machine17.653.810.8587813.24
Hammer drill418.880.858764.85
Reaming drill612.590.858764.87
AC arc welder 40 kv·A132.233.930.8587446.24
Table 12. Overview of carbon footprints across sub-processes in the materialisation phase of prefabricated residential buildings.
Table 12. Overview of carbon footprints across sub-processes in the materialisation phase of prefabricated residential buildings.
Materialisation StageSubprocessEmission Factor
(kgCO2e)
Emission Factor per Unit
(kgCO2e/m2)
Proportion
Building material supply stageMaterial production 3,346,493.51 394.44 90.76%
Material transportation 107,701.38 12.69 2.92%
Factory stageComponent manufacturing 31,596.07 3.72 0.86%
Logistics stageComponent transport 13,252.43 1.56 0.36%
On-site stageSite construction 141,097.11 16.63 3.83%
Assembly activities 46,982.63 5.54 1.27%
Total3,687,123.13434.59 100%
Table 13. The proportion of carbon emissions in each stage of the physical and chemical phase of the prefabricated part.
Table 13. The proportion of carbon emissions in each stage of the physical and chemical phase of the prefabricated part.
PhaseEmission Factor
(kgCO2e)
Proportion
Material Production364,477.7078.03%
Material Transportation14,266.723.05%
Factory Production31,596.076.77%
Component Transportation13,252.432.84%
On-site Installation43,549.059.32%
Total for Prefabricated Components467,141.97100%
Table 14. Carbon footprint distribution across physical and chemical stages of cast-in-place components.
Table 14. Carbon footprint distribution across physical and chemical stages of cast-in-place components.
PhaseEmission Factor
(kgCO2e)
Proportion
Material Production2,982,015.8194.48%
Material Transportation93,434.662.96%
On-site Construction81,436.212.58%
Total Cast-in-Place Portion3,156,886.68100%
Table 15. Carbon emissions composition by physical form denote comparison between precast and cast-in-place components.
Table 15. Carbon emissions composition by physical form denote comparison between precast and cast-in-place components.
ProjectEmission Factor
(kgCO2e)
Proportion
Total Carbon Emissions During the Entire Building Construction Phase3,687,123.13100%
Of which Denote Emissions Related to Prefabricated Components467,141.9712.67%
Of which Denote Emissions Related to Cast-in-Place Components3,156,886.6885.62%
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jin, J.; Xu, Y.; Huang, Q.; Liu, W. Research on Carbon Footprint Calculation for the Materialisation Phase of Prefabricated Housing. Buildings 2025, 15, 3588. https://doi.org/10.3390/buildings15193588

AMA Style

Jin J, Xu Y, Huang Q, Liu W. Research on Carbon Footprint Calculation for the Materialisation Phase of Prefabricated Housing. Buildings. 2025; 15(19):3588. https://doi.org/10.3390/buildings15193588

Chicago/Turabian Style

Jin, Junyan, Yuying Xu, Qingcheng Huang, and Wei Liu. 2025. "Research on Carbon Footprint Calculation for the Materialisation Phase of Prefabricated Housing" Buildings 15, no. 19: 3588. https://doi.org/10.3390/buildings15193588

APA Style

Jin, J., Xu, Y., Huang, Q., & Liu, W. (2025). Research on Carbon Footprint Calculation for the Materialisation Phase of Prefabricated Housing. Buildings, 15(19), 3588. https://doi.org/10.3390/buildings15193588

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop