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Article

The Sustainability Study and Exploration in the Building Commercial Complex System Based on Life Cycle Assessment (LCA)–Emergy–Carbon Emission Analysis

1
School of Architecture, Southeast University, Nanjing 210096, China
2
School of Civil Engineering and Architecture, Jiangsu University of Science and Technology, Zhenjiang 212100, China
3
School of Civil Engineering, Architecture, and Environment, Hubei University of Technology, Wuhan 430068, China
*
Author to whom correspondence should be addressed.
Processes 2023, 11(7), 1989; https://doi.org/10.3390/pr11071989
Submission received: 2 June 2023 / Revised: 24 June 2023 / Accepted: 28 June 2023 / Published: 30 June 2023

Abstract

:
This paper focuses on the sustainable exploration of building systems, which combines ecological concepts and low-carbon designs for a comprehensive sustainability assessment investigation. The study employed the Life Cycle Assessment (LCA)-Emergy and Life Cycle Assessment (LCA)-Carbon emission methods to discuss a range of topics, including the main contributing factors, sustainability index verification, sensitivity analysis, and potential improvement measures. From an ecological sustainability perspective, the results indicate that the building operation stage plays a critical role, accounting for approximately 45% of the entire emergy in the building commercial complex. The sustainable index (ESI) is 0.354, which is below the standard of 1. Moreover, the building operation stage also significantly contributes to carbon emissions, particularly in the 50th anniversary of operation. Based on these findings, the study recommends two potential strategies to improve the ecological state and low-carbon design which involve the use of renewable energy and carbon sink improvement, respectively.

1. Introduction

With abnormal climate change becoming increasingly prevalent, the development of building systems that prioritize ecology, low energy consumption, and low carbon emissions has become a research hotspot in many countries [1,2,3,4]. In China, building carbon emissions and energy consumption account for nearly half of the country’s total consumption, according to data from 2022 [5]. Despite this, the construction industry continues to grow rapidly, with China’s added value reaching 8.33831 billion yuan in 2022—a 5.5 percent increase from the previous year—and Jiangsu’s total output value exceeding 4 trillion yuan for the first time at 4066.05 billion yuan [6]. However, this growth is also exacerbating negative impacts on the climate and environment. To address these issues and meet China’s goal of being carbon neutral by 2060, it is crucial that the building industry focuses on low-carbon retrofitting and design to mitigate the pressures of climate change [7,8].
Currently, there is a range of literature available on the topic of sustainable building systems from an ecological perspective, utilizing various methods, including ecological footprint analysis [9], ecological assessment [10], ecological security analysis [11], Eco-GIS framework [12], and ecological emergy [13]. One notable framework, which integrates both the emergy method and life cycle assessment, is the LCA-Emergy framework designed and utilized in the building system, providing a novel methodology [14]. However, life cycle assessment (LCA) involves various stages, including building material production, building construction, operation, and demolition, and requires the integration of both basic data and unit emergy values [15]. Due to the wide range of sustainable inputs involved in the building system, such as materials, machinery, and human services, different researchers have explored this concept in diverse ways [16,17,18,19,20,21].
Sustainable emergy evaluation of building material systems is a popular research direction that includes material production processes as well as labor and transportation inputs. As building materials are one of the main components of the building system, research in this direction is valuable [22,23,24,25,26,27]. The combination of Building Information Modeling (BIM) technology and building systems has brought more accurate research results to sustainable architecture, and the fully visualized results provide designers and engineers with a more intuitive sense, improving the ecological level of the entire building system [28,29]. Due to the coupling of numerous devices in building systems, including refrigeration equipment, power generation equipment, heating equipment, intelligent equipment, etc., the complexity of building system operation is caused. At the same time, the sustainability of individual equipment systems also affects the ecological level of the entire building, which is also an area of interest for many researchers [30,31,32]. As one of the necessary components of building systems, building envelope structures directly affect the sustainable level of the entire building system. Various walls, glass, doors, and windows that come into contact with the environment are all reasons for fluctuations in sustainable results for the entire building system [33]. Scholars have also studied energy types in building systems. Different energy inputs maintain the operation of building systems while also bringing different results. Which type of building energy is more suitable for building systems is also an important research topic [34,35]. Furthermore, different ecological assessment models have a direct impact on sustainable assessment results for building systems. Different processes for updating building systems are also reasons for these changes; therefore, scholars from various countries have explored this research field as well [36,37]. In addition to this, research on similarities and differences in sustainability among high-density buildings [38], renewable balance design for building systems [39], sustainable residential construction assessment [40], and accuracy analysis models for architectural energy value analysis [41] have also gained favor among researchers.
Indeed, low-carbon design throughout the entire life cycle of a building system is an essential means for achieving sustainable architecture [42,43]. Sustainable architecture aims to promote environmentally responsible and resource-efficient design and construction practices that minimize negative impacts on the environment and promote social well-being. Low carbon design is critical to achieving sustainable architecture as it addresses the significant environmental impact of buildings throughout their entire life cycle. By reducing greenhouse gas emissions, minimizing energy consumption, and promoting renewable energy sources, low-carbon design helps reduce the environmental footprint of buildings and promotes long-term sustainability [44,45,46]. Moreover, sustainable architecture also considers other aspects beyond low-carbon design, such as water efficiency, waste reduction, use of environmentally friendly materials, and enhancement of indoor environmental quality. Therefore, low-carbon design is not only a necessary means for achieving sustainable architecture but also an integral part of it [47,48].
Low carbon design throughout the entire life cycle of a building system refers to the reduction of greenhouse gas emissions from the production, construction, operation, and demolition phases of the building. It involves optimizing the choice of building materials, reducing energy consumption during operation, increasing the efficiency of renewable energy utilization, and promoting sustainable waste management [49,50,51,52].
In the production phase, low carbon design can be achieved by selecting environmentally friendly raw materials, reducing transportation distances, and improving production processes to reduce energy consumption and greenhouse gas emissions [8]. During the construction phase, efficient construction methods, high-performance insulation materials, and renewable energy sources should be considered to minimize carbon emissions. For the operational phase, low carbon design can be achieved by adopting energy-efficient technologies, using renewable energy sources, promoting energy-saving behaviors, and implementing green building certification systems. In addition, carbon sinks, such as green roofs and vertical gardens, should be incorporated into the building’s design to absorb carbon dioxide and reduce carbon emissions [53]. During the demolition phase, low carbon design can be achieved through the reuse and recycling of building materials, reducing waste generation, and promoting circular economy principles. Through the implementation of low-carbon design throughout the entire life cycle of a building system, it is possible to significantly reduce greenhouse gas emissions, improve energy efficiency, and promote sustainable development in the construction industry [54].
However, currently, there is a greater focus on research related to low-carbon buildings and ecological buildings, and there are few studies that specifically explore the sustainability of building systems based on the concepts of ecological value and low-carbon methods. This has resulted in a lag in research in this area. Since ecological buildings and low-carbon buildings are defined from different perspectives as architectural types, it is essential to conduct a sustainable analysis of building systems using both ecological value and low-carbon methods.
The purpose of this study is to use the building system as a carrier to complete the positioning and analysis of the target building case through ecological emergy and carbon emissions assessment throughout the life cycle. By analyzing from an ecological perspective and a carbon emission view, the sustainability level of the building system was comprehensively judged, and the main influencing stages under the two categories were identified to verify the accuracy of the analysis results.
Through the promotion of this research, the deviation in the sustainable analysis of the building system under a single method has been filled, which is conducive to the accuracy of research results and provides a new way of thinking for architects, engineers, and government managers.

2. Material and Methods

2.1. Research Framework

Figure 1 presents the basic research framework for this paper, which consists of four subsections that guide the research direction. The research questions are displayed on the left, focusing on the ecological and carbon emission effects of the building commercial complex system. The system is analyzed using the LCA method, which is divided into five stages: material production, material transport, construction, building operation, and building demolition. To assess the ecological and carbon emission stages, a range of indicators are adopted using the LCA–Emergy–Carbon emission methodology.

2.2. Emergy Diagram of the Building System

The emergy diagram depicts the structure of the building system, consisting of four parts: renewable energy (on the left), non-renewable input (on the top), the building system (in the middle), and output (on the right). The flow of the process is from left to right and top to bottom, with inputs entering the building system and various outputs being produced. The main input and output types can be easily identified and displayed through the emergy structure diagram. Based on the emergy diagram (shown in Figure 2), the LCA-Emergy calculation model and sustainable indexes are presented in the following section.

2.3. LCA-Emergy Analysis Model

In order to realize the LCA-Emergy calculation model, seven types of input need to be calculated for emergy evaluation (in Figure 3). The specific calculation models have been displayed in Table 1.

2.4. Emergy Indexes

Based on the emergy diagram and LCA-Emergy implementation path, a series of sustainable indicators can be utilized for the ecological evaluation, as follows:
(1) Renewable rate (Ri) expresses the proportion of renewable energy in the overall system structure.
(2) Non-renewable rate (Ni) represents the ratio of non-renewable resources and energy sources.
(3) Emergy yield ratio (EYR) reveals the dependence of the whole building system on the outside world.
(4) Environmental loading ratio (ELR) demonstrates the ecological pressure of building commercial complex systems.
(5) Emergy sustainability indicator (ESI) can be obtained based on EYR and ELR, which illustrates the sustainability state for the building commercial complex system.

2.5. LCA-Carbon Emission Calculation Model

Based on the national standard [56], the LCA-Carbon emission implementation path and calculation models have been shown in Figure 4 and Table 2.

3. Case Study and Data Collection

3.1. Case Introduction

A large architectural design category commercial complex has been selected for this project, consisting of six floors of commercial buildings and fifteen floors of hotel buildings (in Figure 5). The complex is located in Nanjing City, China, and covers a total building area of 40,000 square meters. The building is constructed using a reinforced concrete pattern, with partial use of assembly mode to reduce negative environmental impact. The design of the complex is based on ecological principles, with a high-rise building located in the northwest corner to provide a better view. The landscape design in front of the building includes a green space design on the west side, a sunken green square in the middle, and an embedded garden on the east side, enhancing the ecological attributes of the complex. The style of the complex is divided into two categories, with the high-rise hotel buildings mainly using gray to represent the business attribute, while the commercial podium building uses warm colors in its facade design to attract shoppers.
As this architectural case is a new construction project, it was initially defined as a Nearly Zero Energy Building (NZEB), involving the implementation of several passive design measures throughout the entire building project. Some of these measures include:
(1)
Optimizing orientation and layout: Maximizing the use of daylighting and natural ventilation by strategically positioning and designing buildings to reduce energy consumption.
(2)
High-performance insulation materials: Utilizing high-quality insulation materials such as insulation materials and double-glazed windows to minimize heat transfer and energy loss.
(3)
Natural lighting and lighting control: Designing windows and skylights effectively to increase natural lighting and implementing intelligent lighting systems to reduce energy consumption.
(4)
Thermal bridge control: Designing to avoid or minimize thermal bridges, which prevent heat from transferring through the building structure and improve thermal performance.
(5)
Natural ventilation: Designing appropriate ventilation systems to utilize natural airflow for air circulation and improvement of indoor air quality, reducing reliance on mechanical ventilation.
(6)
Passive solar energy utilization: Maximizing the use of solar energy to meet the building’s energy needs through the selection of suitable materials and design features such as solar collectors and photovoltaic panels.
(7)
Green roofs and vertical greening: Adding vegetation layers such as green roofs and vertical green walls to provide insulation and thermal benefits, enhancing indoor comfort.
(8)
Optimization of heating, cooling, and ventilation systems: Designing efficient systems like geothermal energy and air-source heat pumps to reduce energy consumption and carbon emissions.
The combination of these measures can collectively reduce energy use and environmental impact in buildings, contributing to energy efficiency and sustainable development goals.
The reason for choosing this architectural case is primarily because commercial complexes are a complex type of building that involves various types of spaces, including residential, commercial, and surrounding landscape design. It holds significant representative value for sustainable research on ecological and low-carbon methods. Additionally, this particular case has a relatively complete database that is allowed to be accessed and utilized, ensuring the typicity and accuracy of the entire study.

3.2. Data Collection

In this study, we collected basic building data, including information on the main building materials, transportation of building materials, labor involved in construction, emergy conversion rates for building inputs, and carbon emission factors related to construction. The detailed data can be found in the calculation list. We obtained all the data from the Nanjing Urban Construction Department with proper authorization.

4. Results and Discussion

The analysis point of view is elaborated from two aspects, which are LCA-Emergy and LCA-Carbon, respectively. LCA-Emergy analysis contains dominated contributors’ selection, sustainable index explanations, and sensitivity analysis. LCA-Carbon emission analysis involves full life cycle carbon emission status and carbon sink improvement, etc.

4.1. LCA-Emergy Analysis

In this section, according to the national standard [57], the emergy of building commercial complexes is calculated according to the term of 50 years of comprehensive land use.

4.1.1. Primary Emergy Contributors Analysis

In Figure 6 and Figure 7, the life cycle emergy trend is shown. The building operation stage plays a critical effect, accounting for roughly 45% of the entire emergy for the commercial building complex, followed by the building construction stage (approximately 32%), building material production stage (approximately 17%), building transport stage (approximately 5%) and building demolition stage (approximately 2%), etc.
The building operation stage is the most important factor in determining the emergy calculation for a commercial building complex. It consists of six subsystems: Labor and Service, Water Supply and Sewage Treatment Facilities, Heating and Cooling Systems, Electricity Installations, Telecommunications Systems, and Elevator Systems. The contribution of each subsystem to the total emergy was compared, with Labor and Service accounting for 31.3%, followed by Water Supply and Sewage Treatment Facilities (roughly 23.5%), Heating and Cooling Systems (roughly 20.31%), Electricity Installations (roughly 14.6%), Telecommunications Systems (roughly 6.49%), and Elevator Systems (roughly 3.81%) in Figure 8.
Labor and Service include all emergy inputs for various subsystems, which explains why it has the highest emergy amount. Water supply and heating/cooling subsystems are critical inputs, contributing to more than 40% of the entire emergy in the building system due to their frequent use. The remaining three subsystems have relatively minor contributions to emergy in the building commercial complex system.
In conclusion, understanding the emergy contribution of each subsystem in the building operation stage is crucial for sustainable building design and operation. This information can guide us in optimizing resource usage and reducing energy waste, leading to a healthier and more sustainable environment.

4.1.2. Sustainable Indicator Analysis

In this paper, five sustainability indicators have been selected for analysis, which are as follows:
(1) Renewable rate (Ri) expresses the proportion of renewable energy in the overall system structure.
(2) Non-renewable rate (Ni) represents the ratio of non-renewable resources and energy sources.
(3) Emergy yield ratio (EYR) reveals the dependence of the whole building system on the outside world.
(4) Environmental loading ratio (ELR) demonstrates the ecological pressure of building commercial complex systems.
(5) Emergy sustainability indicator (ESI) can be obtained based on EYR and ELR, which illustrates the sustainability state for the building commercial complex system.
Based on five emergy indexes, their influence was demonstrated. Through the calculation for the commercial building complex, its renewable rate is only 6.18%. Correspondingly, the non-renewable rate is more than 90 percent, which puts a serious burden on the sustainability of the building system. According to the Renewable rate (Ri) and Non-renewable rate (Ni), Emergy yield ratio (EYR), Environmental loading ratio (ELR), and Emergy sustainability indicator (ESI) were counted, which are 26.3, 74.2, 0.354, respectively. Taking the ESI as an example, its eligibility criteria are 1. Now the result is 0.354 (less than 1), which illustrates that the sustainability of the building system is not qualified and needs to enhance the degree of sustainability.

4.1.3. Sensitivity Analysis

To ensure the accuracy of research results, it is crucial to conduct a sensitivity analysis. In this study, an uncertainty analysis was carried out on five emergy indicators. The changes in these indicators were attributed to two factors—variations in underlying data and differences in emergy transformity. To test this, four hypotheses were formulated and assessed.
Hypothesis 1.
Float the underlying data by 5% to see how the sustainability indicators change.
Hypothesis 2.
Change 10% of the underlying data and see the results.
Hypothesis 3.
Ensure basic data is unchanged, emergy transformity changes by 5%.
Hypothesis 4.
Similarly, holding the basic data constant, emergy transformity changes by 10%.
To better illustrate the results of the four hypotheses, their trend changes are shown in Figure 9, as follows.
Based on the data presented, it is evident that Hypothesis 1 is more stable than Hypothesis 2. Similarly, when considering emergy transformity, it can be concluded that Hypothesis 3 is superior to Hypothesis 4 in terms of sensitivity stability.

4.2. LCA-Carbon Emission Analysis

In addition to LCA-Emergy analysis, it is important to consider the full-cycle carbon perspective. Section 4.2 explores three subsections, namely the carbon emissions associated with building material production and transport stages, building construction stage, building operation stage, and building demolition stage. The life cycle carbon emission status and sensitivity analysis of the LCA-Carbon view is also presented.

4.2.1. The Carbon Emission of the Building Material Production and Transport Stages

This section consists of two aspects, which are the building material production stage material transport stage. The primary material list has been displayed in Table 3, including main material items (18 types) and the amount of diesel fuel used to transport materials.
Table 3, Figure 10 and Figure 11 present the carbon emission amounts, indicating that steel, wood, and iron are the top three inputs for carbon emissions, accounting for 19%, 18%, and 18% of the total carbon emission amount, respectively. This is because these industries are highly polluting, resulting in significantly more carbon emissions than other inputs (as shown in Figure 10). Additionally, glass (12%), gravel (8%), polyester (5%), lime (5%), cement (4%), water (4%), brick (2%), sand (2%), and aluminum (1%) are the input items with higher carbon emissions.
To confirm and analyze their sensitivity, six hypotheses have been proposed: a 5%, 8%, and 10% reduction and increase in carbon emissions, respectively. The violin diagram (in Figure 12) is used to analyze data structure changes, data density, data contour, etc.
Figure 12 depicts the changes in data structure before and after implementing the six proposed hypotheses using the violin plot. Each change resulted in a different data structure form. Generally, reducing the data narrows the overall data structure (5%, 8%, and 10%), whereas increasing it widens the shape of the data structure (as indicated by the 97.5% to 100% location). When compared with the original data model, about 25% of the data showed little change at the 25% location. Changes become noticeable at the 50% position of the data structure, first down and then up. At the same time, the density of the data structure increases from left to right in Figure 12. Between the 75% to 97.5% positions, the change is more and more prominent.
When considering only the reduction of data structures (B, C, D), the structural morphology is similar. A similar pattern of change can also be seen when increasing the data variation (E, F, G). However, compared to the original data patterns (A), all of them show significant changes in Table 3, indicating the high sensitivity of data and the need to verify its accuracy repeatedly.

4.2.2. The Carbon Emission of Building Construction Stage

For the construction stage, carbon emissions involve multiple subsystems, including Subsystem transport, water supply, and sewage treatment facilities, heating and cooling systems, electricity installations, telecommunications system, elevator systems, etc.
Table 4, Figure 13 and Figure 14 compare the carbon emissions of the six subsystems. It is evident that water supply and sewage treatment facilities are the primary contributors (36,124 tCO2), accounting for 46% of the entire carbon emission of the six subsystems. The other five subsystems have significantly lower carbon emissions, with electricity installations being the second-largest contributor (approximately 24%), followed by subsystem transport (11% roughly), telecommunications systems (8% roughly), heating and cooling systems (6% roughly), and elevator systems (6% roughly).
Comparing the six subsystems, the large amount of water usage and sewage treatment required results in significantly more carbon emissions than any other project (the other five subsystems). Additionally, the use of power systems is also a common input, responsible for about 24% of the carbon emissions in Figure 14. The other four carbon emissions play minor roles.
Figure 15 displays the carbon emission distribution of the six subsystems, and it confirms the primary input elements. For instance, in the case of subsystem transport (in Figure 15(1)), machinery diesel has the most significant carbon emissions, followed by Diesel fuel and Transport diesel. Similar analysis can be obtained from other sub-graphs (in Figure 15(2–6)).

4.2.3. The Carbon Emission in the Building Operation Stage

According to the standards for the use of public buildings in China [55], the fiftieth anniversary building life cycle is considered and calculated. It was found that the carbon emission from electricity usage accounts for approximately 76.2% of the total carbon emission in the building operation phase, significantly more than the carbon emission from heat (approximately 22.8%). Moreover, water has the least amount of carbon emissions throughout the entire life cycle of the building. However, it is important to note that the water used here is for the sewage treatment plant. Therefore, considering the significant differences in the efficiency of different sewage treatment plants, it is necessary to carry out separate calculations for specific projects (in Table 5 and Figure 16).

4.2.4. The Carbon Emission in the Building Demolition Stage

Table 6 and Figure 17 present the carbon emissions of the demolition phase, revealing that glass emits 1638 tons of carbon dioxide, accounting for about 28% of the total carbon emission (in Figure 18). Iron follows closely behind with 1498.6 tCO2, followed by concrete, aluminum (1023.8 tCO2), PVC (152.8 tCO2), bricks (158.6 tCO2), and diesel fuel (29.73 tCO2), respectively.
In this stage, four types of materials will be recycled for reuse to enhance the utilization efficiency of materials. Glass (iron, aluminum) can be remelted and recast into new products for building systems. Concrete will be broken down and used as raw materials to regenerate building products, reducing carbon emissions, and improving the sustainability of the building system.

4.2.5. Life Cycle Carbon Emission Status

Table 7 displays the carbon emissions of the five stages in the building system, revealing that the carbon emission amount in the building operation stage accounts for the majority, approximately 97.4% of the entire carbon dioxide proportion (as shown in Figure 19 and Figure 20). This highlights that the operational phase of the building system emits a significant amount of carbon dioxide within the 50-year cycle range, requiring special attention to reduce system carbon emissions and improve the sustainability of the entire building system.

4.3. Entropy Analysis of Building System

Entropy, as an expression of the state in the system, can demonstrate how chaotic the building system is and indicate sustainable changes in the building system. For example, in a closed building system, the result is increasingly chaotic and inefficient. Therefore, to improve the efficiency of a building system, it is necessary to exchange material flow, energy flow, and information flow.
In this study, several inputs were considered to assess their effectiveness in creating a sustainable system. Although the building system may function normally based on a series of inputs, it doesn’t guarantee the orderliness of the building system. For instance, according to the Emergy Sustainability Indicator (ESI), the building is in an unsustainable state (confusion state), which is less than the standard value. In line with the analysis in this section, improvement strategies for building systems need to be provided to enhance their sustainability.

5. Improvement Measures and Strategies

According to the analysis in Section 4.3, two optimized measures were provided, involving renewable energy use and carbon sink improvement, respectively.

5.1. Renewable Energy Use

From the perspective of life cycle assessment (LCA)-Emergy analysis, the input of renewable energy helps improve the sustainability of the building system [58,59]. Therefore, in this study, solar energy was selected and applied to the building case to explore the quantitative analysis of renewable energy on the sustainability of the building system. To better demonstrate the effects of renewable energy, four strategies were considered and calculated by substituting total emergy in the building system with 3% (Scheme 1), 5% (Scheme 2), 8% (Scheme 3), and 10% (Scheme 4) renewable energy inputs, respectively.
Figure 21 displays the sustainable change effect of solar energy. In Scheme 1, when only a 3% increase in renewable energy is applied, compared to the original state, Emergy yield ratio (EYR) increases, the Environmental loading ratio (ELR) decreases, and Emergy sustainability indicator (ESI) improves. With the increase in the proportion of solar energy utilization in the building system (as shown in Figure 22), the increased Emergy yield ratio (EYR) contrasts with the decreased Environmental loading ratio (ELR), resulting in improved ecological sustainability for the building system. These results illustrate that the increased utilization of solar energy has a significant positive effect on the sustainability of the building system.

5.2. Carbon Sink Improvement

Carbon sequestration refers to the process of removing and storing carbon dioxide (CO2) from the atmosphere through natural or artificial means. Here are some common methods of carbon absorption: (1) Plant Absorption: Plants absorb carbon dioxide from the atmosphere through photosynthesis and store it in their tissues. This includes forests, grasslands, and other vegetation types. (2) Forest Management: Increasing carbon storage in forests can be achieved through activities such as protecting existing forests, reforestation, or afforestation. (3) Soil Carbon Storage: Improving soil quality and preserving organic matter can increase carbon storage in the soil. This involves adopting appropriate agricultural practices, vegetation cover, and organic waste composting. (4) Ocean Carbon Sink: Marine phytoplankton absorbs carbon dioxide through photosynthesis and stores it in marine organisms. Additionally, the ocean absorbs carbon dioxide through dissolution and sedimentation processes. (5) Carbon Capture and Storage (CCS) Technology: This is an artificial method that involves capturing carbon dioxide from combustion processes and storing it underground or in other locations. This can be achieved using techniques like absorption, membrane separation, and chemical reactions. These carbon sequestration methods aim to reduce the concentration of carbon dioxide in the atmosphere and have a positive impact on global climate change. However, it is important to integrate these principles and implement effective management measures to maximize carbon storage effectiveness.
The application of carbon sinks in building systems has an important positive significance for carbon reduction. In Section 5.2, two types of carbon sinks are considered and evaluated, including the carbon absorption of soil and concrete materials and landscape plant, respectively.
The two carbon absorption models are calculated as follows:
(1) Life zone method computational model (soil absorption)
Relationship between density and depth of soil organic carbon:
B D = b 0 + b 1 D + b 2 lg C f
where B D is soil weight; b1, b2, b3 is the constant of soil weight and carbon density under different vegetation types; D is the depth from the surface to the center of the soil layer; Cf is the Organic carbon mass fraction.
The average carbon density of layers per unit area:
C = C f + B D ( 1 δ 2 m m ) V
(2) Molecular-level carbonization theory estimation model (concrete materials absorption)
d = 2 D C O 2 [ C O 2 ] 0 [ C a ( O H ) 2 ] 0 + 3 [ C S H ] 0 + 3 [ C 3 S ] 0 + 2 [ C 2 S ] 0 · t
Among them, [ C a ( O H ) 2 ] 0 C S H ] 0 C 3 S ] 0 [ C 2 S ] 0 there are respectively the initial concentration of each carbide-able substance; D C O 2 is the Effective diffusion coefficient of carbon dioxide in concrete; [ C O 2 ] 0 is the concentration of carbon dioxide on the concrete surface.
The two kinds of carbon absorption effects are verified as follows:
According to the building operation cycle of 50 years, the carbon dioxide absorption of the building area and concrete material are displayed in Figure 23.
Figure 23 illustrates the effect trends of carbon sink measures. Fifty years of CO2 sequestration of soil and building materials significantly reduces the carbon emissions of the entire building system. Building materials have better carbon dioxide absorption than soil. A 12.4% reduction in CO2 absorbed through building materials is compared to the total building carbon emission, whereas the corresponding effect of soil absorption is only 5.76%. Both contribute more than 18.3% to building carbon emissions, making it necessary to consider carbon sink design in the building system.
However, since there are different calculation models for soil carbon dioxide storage and concrete carbon dioxide storage, there may be differences in the calculation results that need to be further verified.
Some researchers have conducted in-depth studies on carbon sequestration, particularly analyzing the carbon absorption effects of building materials and soil [60,61,62]. The results indicate that both types of substances have the ability to absorb carbon dioxide. However, the carbon absorption capacity varies depending on the type of material, soil composition, and scale, and it needs to be individually validated.

6. Conclusions

This study focuses on the ecologically low carbon sustainability of a commercial building complex. Using the LCA–Emergy–Carbon emission methodology, questions were explored and discussed from the perspective of ecology and carbon emissions. The research framework, evaluated indicators, calculation equations, LCA-Emergy analysis, LCA-Carbon emission discussion, and improvement measures were all considered.
The main research results are as follows:
(1)
The results highlight that the building operation stage plays a critical role, accounting for roughly 45% of the entire emergy in the building complex. Additionally, the carbon emission amount in the building operation stage accounts for the majority, approximately 97.4% of the entire carbon dioxide proportion. These two analyses indicate that the ecology and carbon emission of the building operation phase needs to be focused on.
(2)
According to the Renewable rate (Ri) and Non-renewable rate (Ni), Emergy yield ratio (EYR), Environmental loading ratio (ELR), and Emergy sustainability indicator (ESI) were counted, which are 26.3, 74.2, 0.354, respectively. Taking the ESI as an example, its eligibility criteria are 1. Now the result is 0.354 (less than 1), illustrating that the sustainability of the building system is not qualified and needs to enhance sustainability degree.
(3)
The carbon emission amount in the building operation stage accounts for the majority, approximately 97.4% of the entire carbon dioxide proportion. This highlights that the operational phase of the building system emits a significant amount of carbon dioxide within the 50-year cycle range, requiring special attention to reduce system carbon emissions and improve the sustainability of the entire building system.
(4)
Two optimized measures were provided, involving renewable energy use and carbon sink improvement, respectively. Simultaneously, both types of effects have also been validated.
In future research, this paper plans to conduct an in-depth discussion on the operation mode, element analysis, and sensitive design of the building system.

Author Contributions

Conceptualization, J.Z., J.C.; investigation, J.C., Y.Z., H.W. and H.Z.; formal analysis, J.Z., Y.Z.; methodology, J.Z., J.C., H.W.; resources, J.C., J.Z., H.Z.; writing—review and editing, J.Z., J.C., Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

The work described in this paper was supported by the National Natural Science Foundation of China (No. 52208009): Research on Tissue Recognition and Interactive Optimization of Place Unit in High-density Urban Form Based on “Meta Modeling”; National Natural Science Foundation of China (No. 52278010): Research on the Mixed-Use Mode and Internal Mechanism of Intensive-Oriented Old City Residential Blocks: Typomorphological Lineage Analysis. Major research projects on philosophy and social sciences of Jiangsu universities in 2023 (No. 2023SJZD131).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

This study did not report any data.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Goubran, S.; Walker, T.; Cucuzzella, C.; Schwartz, T. Green building standards and the United Nations’ Sustainable Development Goals. J. Environ. Manag. 2023, 326, 116552. [Google Scholar] [CrossRef] [PubMed]
  2. Guidetti, E.; Ferrara, M. Embodied energy in existing buildings as a tool for sustainable intervention on urban heritage. Sustain. Cities Soc. 2023, 88, 104284. [Google Scholar] [CrossRef]
  3. Tang, Z.W.; Ng, T.S.; Skitmore, M. Influence of procurement systems to the success of sustainable buildings. J. Clean. Prod. 2019, 218, 1007–1030. [Google Scholar] [CrossRef]
  4. Shukla, A.K.; Sudhakar, K.; Baredar, P.; Mamat, R. BIPV based sustainable building in South Asian countries. Sol. Energy 2018, 170, 1162–1170. [Google Scholar] [CrossRef]
  5. Tsinghua University Building Energy Saving Research Center. 2019 Annual Report on China Building Energy Efficiency; China Architecture and Building Press: Beijing, China, 2019. (In Chinese) [Google Scholar]
  6. China Construction Industry Association. Construction Industry Development Statistical Analysis Report; China Construction Industry Association: Beijing, China, 2022. [Google Scholar]
  7. Chen, R.; Tsay, Y.-S.; Zhang, T. A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective. Energy 2023, 262, 125373. [Google Scholar] [CrossRef]
  8. Du, Q.; Wang, Y.; Pang, Q.; Hao, T.; Zhou, Y. The dynamic analysis on low-carbon building adoption under emission trading scheme. Energy 2023, 263, 125946. [Google Scholar] [CrossRef]
  9. Zhang, J.; Ma, L. Urban ecological security dynamic analysis based on an innovative emergy ecological footprint method. Environ. Dev. Sustain. 2021, 23, 16163–16191. [Google Scholar] [CrossRef]
  10. Fischer, H.; Frühwald, F.; Korjenic, A. Ecological comparison of hygrothermally safe floor constructions based on renewable raw materials for multi-storey buildings. J. Build. Eng. 2022, 57, 104899. [Google Scholar] [CrossRef]
  11. Fan, X.; Rong, Y.; Tian, C.; Ou, S.; Li, J.; Shi, H.; Qin, Y.; He, J.; Huang, C. Construction of an Ecological Security Pattern in an Urban-Lake Symbiosis Area: A Case Study of Hefei Metropolitan Area. Remote Sens. 2022, 14, 2498. [Google Scholar] [CrossRef]
  12. D’Ambrosio, V.; Di Martino, F.; Rigillo, M. GIS-Based Model for Constructing Ecological Efficiency Maps of Urban Green Areas: The Case Study of Western Naples, Italy. Sustainability 2022, 14, 6830. [Google Scholar] [CrossRef]
  13. Chen, X.; Wang, H.; Zhang, J.; Zhang, H.; Asutosh, A.T.; Wu, G.; Wei, G.; Shi, Y.; Yang, M. Sustainability Study of a Residential Building near Subway Based on LCA-Emergy Method. Buildings 2022, 12, 679. [Google Scholar] [CrossRef]
  14. Brian, F.A.; Guo, H.W. Stakeholders’ perspectives on BIM and LCA for green buildings. J. Build. Eng. 2022, 48, 103931. [Google Scholar]
  15. Anand, C.K.; Amor, B. Recent developments, future challenges and new research directions in LCA of buildings: A critical review. Renew. Sustain. Energy Rev. 2017, 67, 408–416. [Google Scholar] [CrossRef]
  16. Villa, V.; Bruno, G.; Aliev, K.; Piantanida, P.; Corneli, A.; Antonelli, D. Machine Learning Framework for the Sustainable Maintenance of Building Facilities. Sustainability 2022, 14, 681. [Google Scholar] [CrossRef]
  17. Wang, W. Automatic System Design of Assembly Building Components for Sustainable Building Projects Based on BIM Technology. Math. Probl. Eng. 2022, 11, 4902862. [Google Scholar] [CrossRef]
  18. Bahadiroğlu, A.; Koç, A.Y.; Parlak, E.; Larsson, N.; Kujawski, W.; Unver, U. Sustainable building evaluation: A case study, Energy Sources Part A Recovery Util . Environ. Eff. 2022, 44, 3149–3163. [Google Scholar]
  19. Assefa, S.; Lee, H.-Y.; Shiue, F.-J. A building sustainability assessment system (BSAS) for least developed countries: A case of Ethiopia. Sustain. Cities Soc. 2022, 87, 104238. [Google Scholar] [CrossRef]
  20. Wang, Y.; Chen, D.; Tian, P. Research on the Impact Path of the Sustainable Development of Green Buildings: Evidence from China. Sustainability 2022, 14, 13628. [Google Scholar] [CrossRef]
  21. Scherz, M.; Hoxha, E.; Kreiner, H.; Passer, A.; Vafadarnikjoo, A. A hierarchical reference-based know-why model for design support of sustainable building envelopes. Autom. Constr. 2022, 139, 104276. [Google Scholar] [CrossRef]
  22. Zhang, J.; Zhang, H.; Asutosh, A.T.; Sun, N.; Fu, X.; Wang, H.; Li, X. Ecological sustainability assessment of building glass industry in China based on the point of view of raw material emergy and chemical composition. Environ. Sci. Pollut. Res. 2023, 30, 40670–40697. [Google Scholar] [CrossRef]
  23. Zhang, J.; Srinivasan, R.S.; Peng, C. A Systematic Approach to Calculate Unit Emergy Values of Cement Manufacturing in China Using Consumption Quota of Dry and Wet Raw Materials. Buildings 2020, 10, 128. [Google Scholar] [CrossRef]
  24. Zhang, J.; Srinivasan, R.S.; Peng, C. Ecological Assessment of Clay Brick Manufacturing in China Using Emergy Analysis. Buildings 2020, 10, 190. [Google Scholar] [CrossRef]
  25. Thomas, T.; Praveen, A. Emergy parameters for ensuring sustainable use of building materials. J. Clean. Prod. 2020, 276, 122382. [Google Scholar] [CrossRef]
  26. Amponsah, N.; Lacarrière, B.; Jamali-Zghal, N.; Le Corre, O. Impact of building material recycle or reuse on selected emergy ratios. Resour. Conserv. Recycl. 2012, 67, 9–17. [Google Scholar] [CrossRef] [Green Version]
  27. Pulselli, R.M.; Simoncini, E.; Ridolfi, R.; Bastianoni, S. Specifific emergy of cement and concrete: An energy-based appraisal of building materials and their transport. Ecol. Indic. 2008, 8, 647–656. [Google Scholar] [CrossRef]
  28. Yi, H.; Braham, W.W.; Tilley, D.R.; Srinivasan, R. A metabolic network approach to building performance: Information building modeling and simulation of biological indicators. J. Clean. Prod. 2017, 165, 1133–1162. [Google Scholar] [CrossRef]
  29. Paneru, S.; Foroutan Jahromi, F.; Hatami, M.; Roudebush, W.; Jeelani, I. Integration of Emergy. Analysis with Building Information Modeling. Sustainability 2021, 13, 7990. [Google Scholar] [CrossRef]
  30. Wang, J.; Wang, J.; Yang, X.; Xie, K.; Wang, D. A novel emergy-based optimization model of a building cooling, heating and power system. Energy Convers. Manag. 2022, 268, 115987. [Google Scholar] [CrossRef]
  31. Kumar, T.; Srinivasan, R.; Mani, M. An Emergy-based Approach to Evaluate the Effectiveness of Integrating IoT-based Sensing Systems into Smart Buildings. Sustain. Energy Technol. Assess. 2022, 52, 102225. [Google Scholar] [CrossRef]
  32. Wang, J.; Xu, S.; Ma, G.; Gou, Q.; Zhao, P.; Jia, X. Emergy analysis and optimization for a solar-driven heating and cooling system integrated with air source heat pump in the ultra-low energy building. J. Build. Eng. 2023, 63, 105467. [Google Scholar] [CrossRef]
  33. Pulselli, R.; Mazzali, U.; Peron, F.; Bastianoni, S. Emergy based evaluation of environmental performances of Living Wall and Grass Wall systems. Energy Build. 2014, 73, 200–211. [Google Scholar] [CrossRef]
  34. Luo, Z.; Zhao, J.; Yao, R.; Shu, Z. Emergy-based sustainability assessment of different energy options for green buildings. Energy Convers. Manag. 2015, 100, 97–102. [Google Scholar] [CrossRef]
  35. Huang, P.-J.; Huang, S.-L.; Marcotullio, P.J. Relationships between CO2 emissions and embodied energy in building construction: A historical analysis of Taipei. Build. Environ. 2019, 155, 360–375. [Google Scholar] [CrossRef]
  36. Li, D.; Zhu, J.; Hui, E.C.; Leung, B.Y.; Li, Q. An emergy analysis-based methodology for eco-effificiency evaluation of building manufacturing. Ecol. Indic. 2011, 11, 1419–1425. [Google Scholar] [CrossRef]
  37. Andrić, I.; Pina, A.; Ferrão, P.; Lacarrière, B.; Le Corre, O. The impact of renovation measures on building environmental performance: An emergy approach. J. Clean. Prod. 2017, 162, 776–790. [Google Scholar] [CrossRef]
  38. Lee, J.M.; Braham, W.W. Building emergy analysis of Manhattan: Density parameters for high-density and high-rise developments. Ecol. Model. 2017, 363, 157–171. [Google Scholar] [CrossRef]
  39. Srinivasan, R.S.; Braham, W.W.; Campbell, D.E.; Curcija, C.D. Re(De)fifining Net Zero Energy: Renewable Emergy Balance in environmental building design. Build. Environ. 2012, 47, 300–315. [Google Scholar] [CrossRef]
  40. Rothrock, H. Sustainable housing: Emergy evaluation of an off-grid residence. Energy Build. 2014, 85, 287–292. [Google Scholar] [CrossRef]
  41. Yi, H.; Braham, W.W. Uncertainty characterization of building emergy analysis (BEmA). Build. Environ. 2015, 92, 538–558. [Google Scholar] [CrossRef]
  42. Zhu, C.; Li, X.; Zhu, W.; Gong, W. Embodied carbon emissions and mitigation potential in China’s building sector: An outlook to 2060. Energy Policy 2022, 170, 113222. [Google Scholar] [CrossRef]
  43. Hiyama, K.; Srisamranrungruang, T. Low-carbon assessment of building facades using dynamic CO2 intensity of electricity generation in Japan. Energy Build. 2023, 278, 112637. [Google Scholar] [CrossRef]
  44. Liu, J.; Bao, L.; Ye, B.; Wang, J. Low-carbon progressive design for sustainable development of buildings. Indoor Built Environ. 2023, 0, 1–19. [Google Scholar] [CrossRef]
  45. Ansah, M.K.; Chen, X.; Yang, H. A holistic environmental and economic design optimization of low carbon buildings considering climate change and confounding factors. Sci. Total Environ. 2022, 821, 153442. [Google Scholar] [CrossRef] [PubMed]
  46. Li, Y.; Li, S.; Xia, S.; Li, B.; Zhang, X.; Wang, B.; Ye, T.; Zheng, W. A Review on the Policy, Technology and Evaluation Method of Low-Carbon Buildings and Communities. Energies 2023, 16, 1773. [Google Scholar] [CrossRef]
  47. Nie, S.; Zhou, J.; Yang, F.; Lan, M.; Li, J.; Zhang, Z.; Chen, Z.; Xu, M.; Li, H.; Sanjayan, J.G. Sanjayan. Analysis of theoretical carbon dioxide emissions from cement production: Methodology and application. J. Clean. Prod. 2022, 334, 130270. [Google Scholar] [CrossRef]
  48. Xing, X.; Ye, A. Consumption Upgrading and Industrial Structural Change: A General Equilibrium Analysis and Empirical Test with Low-Carbon Green Transition Constraints. Sustainability 2022, 14, 13645. [Google Scholar] [CrossRef]
  49. Xu, C.; Gong, Y.; Yan, G. Research on Cement Demand Forecast and Low Carbon Development Strategy in Shandong Province. Atmosphere 2023, 14, 267. [Google Scholar] [CrossRef]
  50. Wang, X.; Du, Q.; Lu, C.; Li, J. Exploration in carbon emission reduction effect of low-carbon practices in prefabricated building supply chain. J. Clean. Prod. 2022, 368, 133153. [Google Scholar] [CrossRef]
  51. Fan, M.; Gu, Z.; Li, W.; Zhou, D.; Yu, C.W. Integration of a large green corridor with an underground complex—A low carbon building solution for urban climate revival. Indoor Built Environ. 2022, 1, 872–877. [Google Scholar] [CrossRef]
  52. Zhang, Q.; Wu, X.; Chen, Y. Is economic crisis an opportunity for realizing the low-carbon transition? A simulation study on the interaction between economic cycle and energy regulation policy. Energy Policy 2022, 168, 113114. [Google Scholar] [CrossRef]
  53. Zhang, N.; Luo, Z.; Liu, Y.; Feng, W.; Zhou, N.; Yang, L. Towards low-carbon cities through building-stock-level carbon emission analysis: A calculating and mapping method. Sustain. Cities Soc. 2022, 78, 103633. [Google Scholar] [CrossRef]
  54. Liu, Y.; Xue, S.; Guo, X.; Zhang, B.; Sun, X.; Zhang, Q.; Wang, Y.; Dong, Y. Towards the goal of zero-carbon building retrofitting with variant application degrees of low-carbon technologies: Mitigation potential and cost-benefit analysis for a kindergarten in Beijing. J. Clean. Prod. 2023, 393, 136316. [Google Scholar] [CrossRef]
  55. Xie, F.; Zhang, J.; Wu, G.; Zhang, C.; Wang, H. The Environmental Sustainability Study of an Airport Building System Based on an Integrated LCA-Embodied Energy (Emergy)-ANN Analysis. Sustainability 2023, 15, 7626. [Google Scholar] [CrossRef]
  56. GB/T 51366-2019; Standard for Building Carbon Emission Calculation. Ministry of Housing and Urban-Rural Development of the People’s Republic of China: Beijing, China, 2019. Available online: http://www.ntgh.com.cn/News_Info.aspx?id=2367 (accessed on 5 June 2023).
  57. GB 55031-2022; General Code for Civil Buildings. Ministry of Housing and Urban-Rural Development of China: Beijing, China, 2022.
  58. Yin, Y.; Chen, H.; Zhao, X.; Yu, W.; Su, H.; Chen, Y.; Lin, P. Solar-absorbing energy storage materials demonstrating superior solar-thermal conversion and solar-persistent luminescence conversion towards building thermal management and passive illumination. Energy Convers. Manag. 2022, 266, 115804. [Google Scholar] [CrossRef]
  59. Mahaya, C.; Zemmouri, N.; Benharra, H.; Elnokaly, A. Solar Access Assessment in Semi-Arid Urban Context: An Application Study for Ten Urban Forms of Existing Apartment Buildings Districts in Batna City, Algeria. Sustain. Cities Soc. 2022, 83, 103909. [Google Scholar] [CrossRef]
  60. Xu, Q.; Dong, Y.-X.; Yang, R. Influence of the geographic proximity of city features on the spatial variation of urban carbon sinks: A case study on the Pearl River Delta. Environ. Pollut. 2018, 243, 354–363. [Google Scholar] [CrossRef]
  61. He, Y.; Ren, Y. Can carbon sink insurance and financial subsidies improve the carbon sequestration capacity of forestry? J. Clean. Prod. 2023, 397, 136618. [Google Scholar] [CrossRef]
  62. Pittau, F.; Lumia, G.; Heeren, N.; Iannaccone, G.; Habert, G. Retrofit as a carbon sink: The carbon storage potentials of the EU housing stock. J. Clean. Prod. 2019, 214, 365–376. [Google Scholar] [CrossRef]
Figure 1. Research framework based on the LCA–Emergy–Carbon emission methodology.
Figure 1. Research framework based on the LCA–Emergy–Carbon emission methodology.
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Figure 2. Emergy diagram of the building commercial complex system.
Figure 2. Emergy diagram of the building commercial complex system.
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Figure 3. LCA-Emergy implementation path.
Figure 3. LCA-Emergy implementation path.
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Figure 4. LCA-Carbon emission analysis implementation path.
Figure 4. LCA-Carbon emission analysis implementation path.
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Figure 5. Building plan of the commercial complex.
Figure 5. Building plan of the commercial complex.
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Figure 6. Emergy trend graph.
Figure 6. Emergy trend graph.
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Figure 7. Emergy distribution proportion.
Figure 7. Emergy distribution proportion.
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Figure 8. Emergy contribution proportion of six subsystems.
Figure 8. Emergy contribution proportion of six subsystems.
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Figure 9. Sensitivity analysis trend changes of sustainable indicators.
Figure 9. Sensitivity analysis trend changes of sustainable indicators.
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Figure 10. Carbon emission comparison before improvement.
Figure 10. Carbon emission comparison before improvement.
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Figure 11. Quantitative carbon emission comparison.
Figure 11. Quantitative carbon emission comparison.
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Figure 12. Violin structure analysis diagram.
Figure 12. Violin structure analysis diagram.
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Figure 13. Carbon emission comparison of six subsystems.
Figure 13. Carbon emission comparison of six subsystems.
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Figure 14. Carbon emission proportion of six subsystems.
Figure 14. Carbon emission proportion of six subsystems.
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Figure 15. Detailed carbon emission distribution in six subsystems.
Figure 15. Detailed carbon emission distribution in six subsystems.
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Figure 16. The carbon emission in the building operation stage.
Figure 16. The carbon emission in the building operation stage.
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Figure 17. The carbon emission in the building demolition stage.
Figure 17. The carbon emission in the building demolition stage.
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Figure 18. The proportion of various inputs.
Figure 18. The proportion of various inputs.
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Figure 19. Full life cycle carbon emission analysis of building system.
Figure 19. Full life cycle carbon emission analysis of building system.
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Figure 20. The proportion of each stage.
Figure 20. The proportion of each stage.
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Figure 21. The relationship between solar energy substitution and sustainability.
Figure 21. The relationship between solar energy substitution and sustainability.
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Figure 22. Variation variance trend.
Figure 22. Variation variance trend.
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Figure 23. The change in carbon emissions by conducting carbon sinks measure.
Figure 23. The change in carbon emissions by conducting carbon sinks measure.
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Table 1. The calculation models for LCA-emergy assessment.
Table 1. The calculation models for LCA-emergy assessment.
TypesEquationExplains
Solar E S = A × J × ( 1 β ) × T C × T U E V s Where E S represents the solar emergy in the construction process; A is the site surface; J is the solar radiation amount (3.5 × 109 J/m2); β is the surface albedo (0.7); T C is the construction time; T U E V s is the unit emergy value.
Material E material = i = 1 n Q i × T U 1 Where E mass is the emergy value of mass; Q i is mass amount; T U 1 represents the unit emergy value.
Electricity E e = L × T U e Where E e is the emergy of electricity in the building system. L is the electricity quantity. T U e is the unit emergy value of electricity.
Water E w a t e r = V × ρ × G × U E V w Where E w a t e r is the water emergy; V is the water volume; ρ is the water density; G is the Gibbs energy of water (4.92 J/g); U E V w is the water transformity.
Diesel fuel E diesel = μ × χ × U E V d Where E diesel is the emergy of the diesel fuel; μ is the amount of diesel oil used in the buildings system; χ is the calorific value of diesel fuel; U E V d is the unit emergy value of diesel fuel.
Gasoline E g a s o l i n e = ϕ × φ × U E V g Where E g a s o l i n e is the gasoline emergy; ϕ is the gasoline quantity; φ is the calorific value of gasoline; U E V g is the unit emergy value of gasoline.
Human labor E H = L T × N P × T d × U E V H Where E H is the emergy of human labor; L T is the working time (8 h); N P is the number of employed workers; T d is the working day; U E V H is the unit emergy value of human labor.
Note: The above formulas can be referenced from the literature [55].
Table 2. The calculation models for LCA-carbon emission assessment.
Table 2. The calculation models for LCA-carbon emission assessment.
TypesEquationExplains
Total carbon emission E W = E σ + E t + E c + E o + E d Where E W is the total carbon emission in the building system; E σ is the carbon emission in the building material production stage; E t is the carbon emission in the construction material transport stage; E c is the carbon emission in the construction phase; E o is the carbon emission in the operational use and maintenance phase; E d is the carbon emission in the abandoned and dismantled stage.
Building material production stage E σ = i = 1 n Q i × F i + μ i × [ F i × ( 1 φ i ) + F i × φ i ] Where E σ is the carbon emission calculation of the building material production stage; n is the number of building materials; Q i is the consumption of building material i; F i is the carbon emission factor in the initial state; φ i is the carbon emission factor in the recycling state; μ i is the rate of attrition; F i is the recovery utilization rate.
Material transport stage E t = i , j m , n Q i 100 × V i , j × D i × F j Where E t is the carbon emission calculation of the construction transport stage; n is the number of building materials; Q i is the consumption of building material i; V i , j is the amount of energy used to transport materials (t/100 t·km); D i is the transportation distance of materials or equipment (km); F j is the carbon emission factor.
Construction stage E c = i , j m , n Q × L i , j × F j Where E c is the carbon emission calculation of the building construction stage; n is the quantity of equipment; m is the number of energy types; Q is the Total number of machines; L i , j is the energy consumed by machinery; F j is the carbon emission factor.
Operational use stage E o = j m P i , j × N i × H i × F j × t + r = 0 n Q r × β r × F r × t Where E o is the carbon emission calculation of operational use stage; m is the total types of energy; n is the material renewal quantity; t is the life of the building (year); P i , j is the energy expended per hour; N i is the total number of equipment; H i is the average operating hours of the device; F j is the carbon emission factor of equipment; Q r is the maintenance update consumption; β r is the annual renewal rate; F r is the carbon emission factor of alternate material.
Building demolition stage E d = E d e + E d w Where E d is the carbon emission at the stage of building demolition; E d e is the carbon emission of mechanical equipment; E d w is the carbon emission of waste transportation.
Note: The above formulas can be referenced from the literature [56].
Table 3. The carbon emission in the material production and transport stages.
Table 3. The carbon emission in the material production and transport stages.
ItemDataUnitCarbon Emission FactorsCarbon EmissionUnit
Steel6.31 × 103t2.67 tCO2/t16,847.7tCO2
Cement5.23 × 104t0.07 tCO2/t3661tCO2
Gravel4.57 × 102t16 kgCO2/kg7312tCO2
Brick8.92 × 103t0.24 kgCO2/kg2140.8tCO2
Lime9.52 × 103t0.44 tCO2/t4188.8tCO2
Sand7.59 × 105t2.51 kgCO2/t1905.09tCO2
Water4.22 × 106m30.82 kgCO2/m33460.4tCO2
Iron7.74 × 103t2.05 tCO2/t15,867tCO2
Wood5.31 × 105t0.31 kgCO2/kg16,461tCO2
Glass7.63 × 103t1.4 kgCO2/kg10,682tCO2
Polyester6.42 × 101t72.65 tCO2/t4664.13tCO2
Adhesive5.19 × 101t1.1 kgCO2/kg57.09tCO2
Bituminous6.83 × 101t0.04 kgCO2/kg2.732tCO2
Aluminum7.89 × 101t15.8 tCO2/t1246.62tCO2
Ceramic tile5.28 × 101t0.74 tCO2/t39.072tCO2
Polystyrene4.82 × 101t3.78 kgCO2/kg182.196tCO2
Fly ash5.69 × 102t0.18 tCO2/t102.42tCO2
PVC1.37 × 101t4.79 kgCO2/kg65.623tCO2
Diesel fuel7.84 × 101t3.797 tCO2/t297.6848tCO2
Table 4. The carbon emission in the building construction stage.
Table 4. The carbon emission in the building construction stage.
ItemDataUnitCarbon Emission FactorsCarbon EmissionUnit
Subsystem Transport
Diesel fuel7.50 × 102t3.797 tCO2/t2847.75tCO2
Machinery diesel1.05 × 103t3.797 tCO2/t3986.85tCO2
Transport diesel4.31 × 102t3.797 tCO2/t1636.51tCO2
Water supply and sewage treatment facilities
Steel7.60 × 106Kg2.67 tCO2/t20,283.99tCO2
PVC1.38 × 104Kg4.79 kgCO2/kg66.24tCO2
Polystyrene6.43 × 103Kg3.78 kgCO2/kg21.67tCO2
Brass4.93 × 103Kg3.73 tCO2/t18.40tCO2
Polypropylene9.43 × 103Kg5.98 tCO2/t56.40tCO2
Glass fiber7.55 × 103Kg1.4 kgCO2/kg10.57tCO2
Iron5.64 × 104Kg2.05 tCO2/t115.69tCO2
Ceramic7.62 × 105Kg0.74 tCO2/t563.88tCO2
Glass9.11 × 106Kg1.4 kgCO2/kg12,754tCO2
Cement3.99 × 106Kg0.07 tCO2/t279.3tCO2
Water6.38 × 104m30.82 kgCO2/m352.316tCO2
Gravel6.69 × 104Kg16 kgCO2/kg1070.4tCO2
Diesel fuel7.61 × 102t3.797 tCO2/t831.54tCO2
Heating and cooling systems
Steel7.12 × 105Kg2.67 tCO2/t1901.04tCO2
Polypropylene6.76 × 103Kg5.98 tCO2/t40.41882tCO2
Aluminum7.31 × 103Kg15.8 tCO2/t115.498tCO2
Glass wool1.04 × 104Kg1.4 kgCO2/kg14.5894tCO2
Brass9.81 × 103Kg3.73 tCO2/t36.59876tCO2
Copper9.12 × 103Kg3.73 tCO2/t34.02879tCO2
Diesel fuel6.51 × 102t3.797 tCO2/t2471.847tCO2
Electricity installations
Copper1.77 × 104Kg3.73 tCO2/t49.982tCO2
Aluminum sheet6.37 × 104Kg15.8 tCO2/t761.56tCO2
Galvanized steel7.56 × 104Kg15.8 tCO2/t903.76tCO2
Steel1.19 × 106Kg15.8 tCO2/t14,283.2tCO2
Rubber9.24 × 104Kg2.4 tCO2/t167.76tCO2
Polyester1.03 × 104Kg72.65 tCO2/t568.458tCO2
Iron7.19 × 104Kg2.05 tCO2/t111.52tCO2
Ceramics8.96 × 104Kg0.74 tCO2/t50.172tCO2
Plastic1.31 × 105Kg7.83 kgCO2/kg778.302tCO2
Glass5.05 × 104Kg1.4 kgCO2/kg53.48tCO2
Diesel fuel2.23 × 102t3.797 tCO2/t847.97tCO2
Telecommunications system
Copper7.44 × 104Kg3.73 tCO2/t277.50tCO2
PVC8.81 × 104Kg4.79 kgCO2/kg422.20tCO2
Aluminum sheet1.05 × 105Kg15.8 tCO2/t1666.15tCO2
Plastic3.08 × 104Kg7.83 kgCO2/kg241.09tCO2
Brass5.99 × 104Kg3.73 tCO2/t223.29tCO2
Aluminum8.91 × 104Kg15.8 tCO2/t1407.25tCO2
Glass1.17 × 105Kg1.4 kgCO2/kg164.28tCO2
Steel8.97 × 104Kg15.8 tCO2/t1417.69tCO2
Diesel fuel2.51 × 100t3.797 tCO2/t721.43tCO2
Elevator system
Steel2.79 × 105Kg15.8 tCO2/t4405.47tCO2
Rubber7.03 × 103Kg2.4 tCO2/t16.87tCO2
Iron1.18 × 104Kg2.05 tCO2/t24.19tCO2
Glass1.20 × 104Kg1.4 kgCO2/kg16.76tCO2
Diesel fuel2.52 × 101t3.797 tCO2/t95.84tCO2
Table 5. The carbon emission in the building operation stage.
Table 5. The carbon emission in the building operation stage.
ItemDataUnitCarbon Emission FactorsCarbon EmissionUnit
Electricity7.41 × 109kWh0.7025 kgCO2/kWh5.21 × 106tCO2
Heat7.79 × 108J0.002 tCO2/J1.56 × 106tCO2
Water8.25 × 106m30.82 kgCO2/m36.77 × 103tCO2
Table 6. The carbon emission of the building demolition stage.
Table 6. The carbon emission of the building demolition stage.
ItemDataUnitCarbon Emission FactorsCarbon EmissionUnit
Glass1.17 × 106Kg1.4 kgCO2/kg1638tCO2
Iron7.31 × 105Kg2.05 tCO2/t1498.6tCO2
PVC3.19 × 104Kg4.79 kgCO2/kg152.8tCO2
Aluminum6.48 × 104Kg15.8 tCO2/t1023.8tCO2
Bricks6.61 × 105Kg0.24 kgCO2/kg158.6tCO2
Concrete9.95 × 106Kg0.13 kgCO2/kg1293.5tCO2
Diesel fuel7.83 × 103Kg3.797 tCO2/t29.73tCO2
Table 7. The carbon emission calculation of the LCA-Carbon method.
Table 7. The carbon emission calculation of the LCA-Carbon method.
StagesAbbreviationCarbon EmissionUnit
Building material production stageB18.92 × 104tCO2
Building material transport stageB28.47 × 103tCO2
Building construction stageB37.89 × 104tCO2
Building operation stageB46.77 × 106tCO2
Building demolition stageB55.79 × 103tCO2
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Cao, J.; Zhu, Y.; Zhang, J.; Wang, H.; Zhu, H. The Sustainability Study and Exploration in the Building Commercial Complex System Based on Life Cycle Assessment (LCA)–Emergy–Carbon Emission Analysis. Processes 2023, 11, 1989. https://doi.org/10.3390/pr11071989

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Cao J, Zhu Y, Zhang J, Wang H, Zhu H. The Sustainability Study and Exploration in the Building Commercial Complex System Based on Life Cycle Assessment (LCA)–Emergy–Carbon Emission Analysis. Processes. 2023; 11(7):1989. https://doi.org/10.3390/pr11071989

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Cao, Jun, Yangfei Zhu, Junxue Zhang, Hechi Wang, and Haohao Zhu. 2023. "The Sustainability Study and Exploration in the Building Commercial Complex System Based on Life Cycle Assessment (LCA)–Emergy–Carbon Emission Analysis" Processes 11, no. 7: 1989. https://doi.org/10.3390/pr11071989

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