Next Article in Journal
Study on Chloride Permeability and Chloride Ion Transport of Fiber-Reinforced Cementitious Composite Repair System
Next Article in Special Issue
Sick Building Syndrome: Prevalence and Risk Factors Among Medical Staff in Chinese Hospitals
Previous Article in Journal
Work–Study Conflict Stressors and Impacts: A Cross-Disciplinary Analysis of Built Environment Undergraduates
Previous Article in Special Issue
Comparative Analysis of Residents’ Willingness to Pay for Diverse Low-Carbon Measures in Hangzhou, China: Implications for Urban Sustainability and Policy
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Impact Characteristics of Common Low-Carbon Design Methods on Reducing Carbon Emissions in Industrial Plant Buildings in Architectural Design

1
Northwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Xi’an 710075, China
2
School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(6), 974; https://doi.org/10.3390/buildings15060974
Submission received: 4 February 2025 / Revised: 9 March 2025 / Accepted: 12 March 2025 / Published: 19 March 2025

Abstract

Amidst global warming and energy crises, low-carbon building design is essential. China, the largest carbon emitter, commits to peaking emissions by 2030 and achieving carbon neutrality by 2060. This study focuses on low-carbon strategies for industrial buildings in cold regions, aiming to develop optimization designs centered on carbon emissions. Using ENERGYPLUS and the “standard coal method”, it quantifies operational carbon emissions and analyzes the impact of design methods on energy consumption across architectural layout, materials, and photovoltaic technology. This study, set in Xi’an and Yulin, assesses low-carbon techniques in cold and severely cold climate zones. It demonstrates that, for the architectural layout, the orientation of the building has a relatively small impact on carbon emissions, while an increase in the window-to-wall ratio significantly increases the carbon emissions of the building. For the building materials, the form of window glass, the reflectivity of roofs and walls, and the thickness of roof and wall insulation significantly affect carbon emissions. For the photovoltaic technology, the angle of photovoltaic roofs has no significant impact on carbon emissions. By further comparing the effectiveness of various low-carbon design technologies in reducing building carbon emissions, it was found that choosing more appropriate wall insulation boards can provide more significant carbon reduction effects at the same cost.

1. Introduction

1.1. Background

Global climate change and the depletion of fossil fuels are significant environmental issues threatening human survival and development. The Kyoto Protocol lists six main greenhouse gases emitted by humans: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6) [1]. CO2 has the most significant impact on climate warming, accounting for about 77%; thus, greenhouse gas accounting is often simplified to carbon dioxide emissions [2].
After the eighteenth century, the widespread use of coal, oil, and electricity successively drove the first and second industrial revolutions, making energy an important force in global economic development. Today, the extensive use of fossil fuels has triggered a global ecological crisis represented by climate change. Atmospheric monitoring around the world clearly shows that global temperatures have risen sharply since the Industrial Revolution, with the fastest increase from the end of the last century to the beginning of this century. Global carbon emissions have also grown dramatically during the same period, with data indicating that about half of the anthropogenic CO2 since 1850 has been produced in the last 40 years. Comparing global climate change trends with carbon emission trends reveals a high degree of consistency. As human economies and societies continue to develop, the dependence on fossil energy consumption is high, and global carbon emissions continue to increase, maintaining the trend of global warming. According to the current trend of carbon emissions, global warming is expected to rise by 1.5 °C between 2030 and 2052, leading to a redistribution of global precipitation, the melting of glaciers, the rising sea levels, and a series of irreversible global disasters, posing a significant threat to ecological balance and human survival [3].
China’s current and long-term energy structure is still mainly based on fossil fuels such as coal, which, influenced by extensive production methods and industrial characteristics, results in a large amount of CO2 emissions [4]. Since 2005, China’s annual CO2 emissions have exceeded those of the United States, becoming the country with the highest carbon emissions in the world. In 2017, China’s CO2 emissions reached 9232.6 million tons, accounting for 27.6% of the global total that year [5]. Although China’s rapid economic growth and industrialization have made significant contributions to the global economy, this development model also comes with a huge environmental cost and high carbon emission pressure. Currently, China’s energy structure is still dominated by coal, accounting for more than 60% of total energy consumption, which not only restricts the country’s sustainable development but also makes China face a more severe emission reduction task [6].
To address climate change and energy crises, the international community has taken a series of measures since the 1990s to promote the reduction of greenhouse gas emissions by countries. The adoption of the United Nations Framework Convention on Climate Change in 1992 and the signing of the Kyoto Protocol in 1997 marked the beginning of global climate governance. The Paris Agreement reached in 2015 further clarified the global goals for addressing climate change in the 21st century, which is to control the global average temperature increase within 2 °C above the pre-industrial level and strive to keep the temperature rise within 1.5 °C [7]. In response to these international agreements, Chinese government has pledged to achieve carbon emission peaking before 2030 and to strive for carbon neutrality before 2060. The proposal of these goals demonstrates China’s firm determination to address global climate change and promote low-carbon development.
In this context, the development and application of low-carbon technology have become an important means for countries to address climate change. Especially in the construction industry, promoting low-carbon design, improving energy efficiency, using renewable energy, and reducing carbon emissions throughout the life cycle of buildings have become key strategies to achieve global temperature control targets and promote sustainable development. Deepening the understanding of climate change issues and energy crises can better guide the research and application of low-carbon building technology, contributing to the global environmental challenge.
With the increasing severity of global climate change and the high attention of the international community to carbon emission issues, countries around the world have formulated and implemented policies and regulations to address climate change, promoting low-carbon development and reducing greenhouse gas emissions [8]. The construction industry, as one of the main areas of energy consumption and carbon emissions, has become a key focus of policy and regulation.
As the world’s largest emitter of greenhouse gases, China has been actively participating in international climate change governance and has formulated low-carbon development strategies. In 2020, China announced at the 75th United Nations General Assembly that it would strive to achieve carbon emission peaking before 2030 and carbon neutrality before 2060 [9]. To achieve this goal, the Chinese government has introduced a series of policies and regulations, including carbon emission trading, energy efficiency improvement, and renewable energy development, aiming to promote the green and low-carbon transformation of the economy and society. In recent years, China has issued several policy documents and action plans related to low-carbon development. For example, the National Climate Change Plan (2021–2035) proposes medium and long-term emission reduction targets and key tasks, explicitly requiring the promotion of low-carbon development in all industries, including the construction industry [10]. The Action Plan for Carbon Peaking Before 2030 further refines the path to achieving the goal of carbon peaking, emphasizing that the construction industry needs to comprehensively improve building energy-saving standards and vigorously promote green and low-carbon buildings [11].
In the field of construction, carbon emissions mainly come from the production of building materials, the construction process, and the energy consumption during the operation phase of buildings. Among these, carbon emissions during the operation phase account for more than 40%; thus, reducing carbon emissions during the operation phase is the core goal of achieving low-carbon buildings, with the carbon emissions caused by cooling and heating being the most important part [12]. Currently, many scholars in architecture have discussed low-carbon design methods for residential buildings, but there is relatively less research on low-carbon design for industrial plant buildings. Although the area of industrial plants in cities is not as large as that of residential buildings, as the main place for production and life, this type of building must also be considered in low-carbon development.
Industrial plant buildings are different from office and residential buildings in that the user activity area reaches all building spaces. Due to management and production needs, there is a clear division of “office area” and “production area” in plant buildings. The office area is the main activity area for personnel, and although the space area is not large in the building, the personnel density is relatively large; the production area, although large in area, has a very small personnel density. Therefore, there are obvious heating/cooling areas and cold/heat storage areas in the building.
At present, there is a clear theoretical and practical gap in the research on the low-carbon design of industrial plant buildings in the severely cold and cold regions of northern China, especially the lack of low-carbon design theories and clear design elements specifically for these climatic conditions. The main goal of this study is to build a clear and systematic building low-carbon optimization design method with carbon emission indicators at the core, ensuring the low-carbon development of industrial building design decisions, and ultimately providing a set of efficient and reliable low-carbon building design solutions for severe cold and cold regions.

1.2. Literature Review

1.2.1. Evaluation Methods for Building Carbon Emissions

Building carbon emission evaluation methods are crucial for effective reduction strategies. Miguel et al. used the input–output method to analyze Spain’s construction sector carbon emissions [13], while Mavromatidis et al. applied the Kaya identity to assess Switzerland’s construction industry energy consumption and carbon emissions [14]. Zhang et al. statistically analyzed 13 years of construction industry data in the Gansu Province to identify carbon emission patterns [15], and Chau et al. compared three quantitative assessment methods: Life-Cycle Assessment (LCA), Life-Cycle Energy Assessment (LCEA), and Life-Cycle Carbon Emission Assessment (LCCO2A) [16]. These methods provide a scientific basis for future low-carbon development in the construction sector. The main current methods for quantifying building carbon emissions include the direct measurement method [17], the emission factor method [18], the material balance method [19], and the hybrid method [20].
In general, the emission factor method can detail the assessment of carbon emissions at each stage of economic activities, with accurate results and easy data updating, but due to the non-uniformity of system boundaries, there are errors [21]. The material balance method, based on the “input–output” principle, quantifies carbon emissions at the macro level through economic value and input–output tables, ensuring complete system boundaries, but it has lower accuracy for the carbon emissions of specific processes [22]. The hybrid method combines the advantages of the emission factor method and the material balance method, and it has been widely used in carbon emission quantification in recent years, divided into stratified hybrid methods, input–output analysis-based hybrid methods, and integrated hybrid methods according to the focus of the two methods [23]. The hybrid method aims to solve the error problems of the two methods, but some studies have shown that it may lead to errors in double counting in actual use, and its specific applicability still needs further research.

1.2.2. Research Boundaries for Building Carbon Emissions

A review of quantitative analysis of building carbon emissions shows that defining the boundaries of building carbon emissions is the primary issue for quantification. Different researchers have various ways of dividing the life cycle of building carbon emissions, such as Bayer dividing the entire life cycle of buildings into four stages: material production, construction, operation and maintenance, and building demolition [24]; Cole included raw material production (covering transportation, on-site construction equipment consumption, and building support measures), initial construction, building decoration and maintenance, and demolition and disposal stages [25]. Leif Gustavsson mainly studied the production of building materials, on-site construction, operation, demolition, and disposal processes [26]. Ramesh summarized that, in the energy consumption of the entire life cycle of buildings from 73 building cases in 13 countries, the use phase is the main energy consumption phase, accounting for 80% to 90% of the entire life cycle, with the construction phase accounting for 10% to 20%, and other stages consuming less energy, with carbon emission proportions consistent with energy consumption proportions [27]. Yu Ping and Chen Xiaoqun et al. concluded through review studies that the proportion of carbon emissions during the operation and use phase of buildings is the largest, accounting for 49% to 96.9% [28]. Lin, through the analysis of the calculation model, energy consumption, and carbon emission data of 97 typical cases, summarized that there are significant differences in the establishment of building life-cycle models in different studies, and the division of stages and data sources lack unity. Their research, through the organization of international carbon emission-related quantitative analysis, provides a certain reference for establishing a building life-cycle energy consumption and carbon emission evaluation system suitable for China’s specific situation [29].
Studies on the entire life-cycle carbon emissions of buildings show that the operation phase of buildings is the main source of carbon emissions; thus, carbon reduction measures should focus on improving energy efficiency and optimizing usage behavior during the operational phase.

1.2.3. Relevant Carbon Emission Quantitative Analysis Software and Low-Carbon Design Tools

Michael combined BIM software with carbon emission estimation models to visualize building carbon emission data, thereby directly discovering carbon emission problems to reduce the total amount of carbon emissions [30]. Peng used Ecotect energy consumption simulation software and Revit software for the carbon emission accounting of cases, concluding that about 85.4% of carbon emissions come from the operation phase of buildings [31].
In the current research on building carbon emission analysis and low-carbon design, auxiliary tools mainly include three categories: building performance and environmental simulation software focused on energy consumption simulation (such as Ecotect, EnergyPlus, etc.), BIM software with carbon emission data analysis (such as Revit, ArchiCAD, etc.), and software suitable for product life-cycle carbon emission analysis (such as GaBi, SimaPro, eBalance, etc.). Among these, EnergyPlus, developed by Lawrence Berkeley National Laboratory (LBNL), National Renewable Energy Laboratory (NREL), Oak Ridge National Laboratory (ORNL), and Pacific Northwest National Laboratory (PNNL), has outstanding advantages as a building energy consumption simulation and heat load calculation software. It can fully simulate and analyze cooling, heating, ventilation, lighting, carbon emissions, and economic costs of buildings within the time required by users. EnergyPlus is not only widely used worldwide but is also favored by researchers for its strong data processing capabilities and flexible simulation settings.

1.2.4. Low-Carbon Design Strategies and Technical Measures for Buildings in Cold/Severely Cold Regions

Cold and severely cold regions are two of the five climate zones in China. The climate characteristics of cold areas in China are that the average temperature of the coldest month is between -10 °C and 0 °C, and the number of days with an average temperature ≤ 5 °C is 90 to 145 days; in severely cold areas, the average temperature of the coldest month is ≤−10 °C, or the number of days with an average temperature ≤ 5 °C is no less than 145 days. Building design in these areas needs to focus particularly on cold resistance, insulation, and anti-freezing properties to cope with the harsh local climate conditions, making these regions also the areas with the largest carbon emissions during the building operation phase [32,33].
Low-carbon design strategies for buildings in cold/severely cold regions can be summarized from aspects such as improving site space utilization efficiency, reducing building ventilation-related energy consumption, optimizing building daylighting and shading strategies, and enhancing the carbon sequestration effect of spatial greenery [34,35].
Improving site space utilization efficiency is crucial for achieving low-carbon design. This can be performed by optimizing site layout and building spatial form design [36], taking into account factors such as natural ventilation [37,38], daylighting [39,40], and insulation performance [41]. For instance, arranging buildings along the prevailing wind direction in summer and reserving open outdoor spaces on the south side can enhance ventilation effects. Moreover, optimizing the building’s form coefficient can significantly reduce air conditioning and heating energy consumption.
Reducing building ventilation-related energy consumption is essential. In cold and severe cold regions, buildings often need to lower indoor temperatures through ventilation during hot seasons. However, mechanical ventilation can increase energy consumption and operational carbon emissions [42,43]. Therefore, natural ventilation should be fully utilized first [44,45], and the efficiency of mechanical ventilation should be optimized to achieve energy saving and carbon emission reduction in ventilation measures [46].
Optimizing building shading strategies aims to reduce the entry of solar radiation heat in summer while maximizing its use in winter [47]. This can be achieved through spatial form optimization and shading component design. For example, using protrusions, recesses, and facade corners in building shapes can reduce direct sunlight entry. Additionally, combining external shading boards, grilles, and louvers and selecting fixed or adjustable shading components according to building orientation and light angles can effectively reduce solar radiation heat gain in summer without affecting lighting needs [48].
Enhancing the carbon sequestration role of spatial greenery can contribute to low-carbon effects during the operational phase of buildings. Each hectare of natural grassland can sequester 1.3 tons of carbon annually. Increasing the amount of greenery and improving carbon fixation efficiency can be achieved through various measures [49,50].
Utilizing renewable energy sources such as solar energy, wind energy, and heat pump technology can significantly reduce carbon emissions [51]. Solar energy can be harnessed through photovoltaic and thermal conversion, with applications in photovoltaic systems and hot water systems [52,53]. Wind energy is mainly used for wind power generation, and integrating it with building design can improve energy utilization [54]. Heat pump technology uses low-temperature heat sources for heating and cooling, effectively reducing CO2 emissions compared to direct fossil fuel use [55].

1.2.5. Research on Low-Carbon Design of Industrial Buildings

Industrial buildings encompass a wide variety of types. Even when considering only factory-type buildings, there are numerous scenarios tailored to different production functions. These buildings exhibit significant differences in terms of spatial characteristics, duration of use, number of occupants, and so on. As a result, many previous studies have focused on a specific type of industrial building, such as garment factories [56], cigarette factories [57], and paper mills [58], among others. Additionally, some scholars have conducted research on general industrial factories [59]. Although industrial buildings vary in type, green building technology strategies and measures can be mutually informative and referential. Monika [60] and Wan [61] investigated the application of green building materials and related technologies, Golroudbar [62] focused on energy usage methods, and Shi [63] explored issues related to environmental policies.

1.2.6. Summary of Current Research Status

Carbon emission analysis for specific building projects is currently conducted mostly from a life-cycle assessment perspective. Different researchers define the scope of building life-cycle carbon emissions variously, but the definition essentially includes the production phase of building materials, the construction phase, the operation phase, and the demolition phase of buildings. Existing studies often quantify the carbon emissions of buildings that have already been constructed and are in use, which allows for the collection of actual data at each stage to obtain accurate carbon emissions. However, for the low-carbon optimization of existing buildings, the focus is often on adding and updating technical equipment to “compensate” for the effects of carbon emission reductions. To truly control the carbon emissions throughout the entire life cycle of a building, it is necessary to consider the carbon emissions at each stage from the design phase of the building. Currently, traditional building design still emphasizes the pursuit of aesthetics and functionality. In the face of the era’s demand for sustainable development, new-age building design needs to pay attention to low-carbon emission reduction. The practical operation of building carbon emission quantification research is often carried out through BIM software, energy consumption simulation software, and related carbon emission databases and calculation software. Therefore, in order to assist designers in more accurately estimating the carbon emission levels after the completion of a building during the determination of architectural schemes, it is crucial to employ quantifiable analytical tools suitable for use in the design phase and to propose a set of material selection and design methods that align with the characteristics of actual engineering projects.

2. Method

2.1. Method for Calculating Building Carbon Emissions

This manuscript uses the “standard coal method” for the quantification of carbon emissions during the operational phase of buildings, which is one of the most commonly used quantification methods for building carbon emissions in China.
The “Standard Coal Method” is a building carbon emission calculation approach based on energy consumption. Its core lies in converting various types of energy consumption into standard coal equivalents and then calculating the carbon emissions using corresponding emission factors. Specifically, the first step involves collecting data on energy consumption during the operational phase of a building, including electricity, gas, and heating, and converting these into standard coal equivalents. Subsequently, an appropriate carbon emission factor is selected based on the type of energy and regional characteristics to convert the standard coal consumption into carbon emissions. The carbon emission factor is annually provided by the State Grid Corporation of China. This calculation method complies with China’s national standards for carbon emission quantification, as stipulated in the “Standard for Calculation of Building Carbon Emissions” (GB/T 51366-2019) [64].
The carbon emission factors used in this study are derived from the report data published by the National Bureau of Statistics of China in April 2024. For the regions where the two cities of this manuscript, the carbon emission factor is 0.6336 kgCO2/kWh.
The specific calculation process is shown in Figure 1. It includes five stages: (1) establishing a building energy consumption model, (2) calculating the energy consumption for building heating and cooling, (3) calculating the electricity consumption for building heating and cooling for whole year, (4) converting electricity consumption into standard coal usage, and (5) using the carbon emission coefficients provided by the State Grid of China to convert standard coal usage into building annual carbon emissions. Since the usage of lighting and mechanical equipment during the operational phase does not change regardless of the indoor thermal environment of the building (the electricity consumption of this part is directly determined by the type of building), the carbon emissions from building cooling and heating (calculated using the “standard coal method”) can serve as a representative indicator of carbon emissions during the operational phase of the building.

2.2. Model Initialization

2.2.1. Calculation Model

This paper used ENERGYPLUS software (version 2210) to simulate and calculate the energy characteristics of industrial buildings.
EnergyPlus is an advanced building energy simulation software developed by the U.S. Department of Energy. It is characterized by its comprehensive simulation capabilities, covering heating, cooling, ventilation, lighting, and equipment energy consumption. This software supports flexible time-step simulations, ranging from hourly to sub-hourly intervals, making it suitable for dynamic systems. It employs a heat balance approach to calculate thermal loads, accounting for both radiative and convective effects. Its modular design allows for a wide range of building and HVAC system configurations and user-defined control strategies.
The simulation case selects a standard factory building in a real environment (with production and management areas in separate spaces) as the research subject. The Longteng Industrial Park No. 1 factory building located in Yulin City, Shaanxi Province, is used as a representative standard factory building. The building area is 46,829 square meters, and the building height is 10 m. The three-dimensional model of the building is shown in Figure 2.

2.2.2. General Model Settings

The building studied in this paper was designed in accordance with the “Unified Standard for Energy-efficient Design of Industrial Buildings” (GB 51245-2017) [65] issued by the Chinese government. The basic roof construction of the building, from top to bottom, consists of the following layers: “40 mm fine aggregate concrete + 100 mm extruded polystyrene board + 20 mm cement mortar + 80 mm aerated concrete/foamed concrete (ρ = 700 kg/m3) + 120 mm reinforced concrete + 20 mm lime mortar.” The exterior wall construction, from outside to inside, is as follows: “20 mm cement mortar + 75 mm rock wool board + 20 mm cement mortar + 300 mm sand aerated products (Grade B06) + 20 mm lime mortar.” The relevant thermal parameters of the materials involved in these two parts are shown in Table 1.
We also have set parameters for the building’s air conditioning equipment, hot water, and other aspects. For the air conditioning units, the combined cooling and heating performance coefficients were determined to be 3.5 and 2.6, respectively. The set temperatures for cooling and heating are 26 °C and 16 °C, respectively. The fresh air volume during operation is 20 m3/h per person. The personnel density in the workshop is set at 50 m2 per person. The lighting and equipment power densities in the workshop are 9 W/m2 and 15 W/m2, respectively. Domestic hot water is provided at a fixed rate of 10 L per person per day throughout the year, with the workshop personnel count assumed to be 100 people. In addition, Table 2 lists the hourly occupancy rates of personnel within the building.
The above thermal parameters of building materials are derived from building energy-saving design codes and empirical values of common building thermal parameters. The values related to the personnel schedule are provided by the design party of the project under study in this research.

2.2.3. Hierarchical Approach to Low-Carbon Design

This manuscript analyzes the impact of common active and passive low-carbon design methods on the cooling and heating energy consumption of industrial buildings from three different levels, including: architectural layout level, building material level, and technical measures level.
(1)
Architectural Layout Level
The architectural layout level is the most fundamental composition of a building, including building orientation and window-to-wall ratio. The surrounding environmental factors determine the initial form of the building during its creation. From a purely architectural form perspective, low-carbon design research is conducted by considering climate conditions and local environments. The purpose of this level is to explore the impact of building planning and layout selection on operational carbon emissions during the initial design phase.
(2)
Building Material Level
The building material level includes the thickness of external walls, windows, external wall and roof insulation, and reflectivity. The envelope structure plays a role in insulation and thermal protection in the overall building construction, and its form and material selection have a direct impact on the energy consumption and carbon emissions during the building’s operational phase. This level is based on the architectural layout level and conducts research on the form and physical properties of the building’s external walls, windows, and roofs, which are the main factors that affect building energy consumption and carbon emissions. The form of the envelope structure, building materials, and the selection of physical coefficients vary significantly in different regions and for different building types.
(3)
Technical Measures Level
The technical measures level is based on the building scheme itself and involves additional energy-saving measures for the building. Different regions apply different building energy-saving strategies, which are additional options in low-carbon building design. These are selected based on specific climatic conditions, either individually or in combination. Building components play a role in improving the comfort of the building environment and are an important factor in energy saving and emission reduction during the building’s operational phase. The technical measures level is an indispensable factor in low-carbon buildings. In this level, the installation of solar photovoltaic roofs is considered.
The specific variable settings for the aforementioned three levels are shown in Table 3. The table provides variables that represent the common design methods and mainstream material selections for industrial buildings in China’s cold and severely cold regions, which can represent the mainstream scenarios of industrial building construction.

2.3. Meteorological Data

From the perspective of climate zone division, Xi’an is selected as the representative of the cold climate zone, and Yulin is chosen as the representative of the severely cold climate zone. The climate data for both regions are based on the typical meteorological year data of the respective cities. These data come from the China Building Thermal Environment Analysis Meteorological Data set (CSWD), which is a collaboration between the Meteorological Information Center of the China Meteorological Administration and the Department of Building Technology Science at Tsinghua University. These datasets are generated based on long-term, continuous meteorological observation data and can represent the climatic characteristics of different regions in China. They provide unified outdoor meteorological data for building energy efficiency analysis, selecting years that are closest to the multi-year average meteorological conditions through statistical methods. Therefore, they can better reflect the typical climatic conditions of a region and are representative for energy consumption simulation and building performance assessment. This dataset is widely recognized in the industry for building energy consumption calculations.

2.4. Accuracy of the Calculation Results

To ensure that the calculation model adopted in this paper can accurately reflect the energy consumption and carbon emissions of the building, this paper compared the hourly energy consumption of the building modeled by our method with that modeled by the design party using the building carbon emission calculation model recognized by the Chinese government. The building carbon emission calculation method recognized by China is primarily based on the “Standard for Calculation of Building Carbon Emissions” (GB/T 51366-2019). This standard provides detailed methods for calculating carbon emissions across the entire life cycle of a building, including the operational phase, construction and demolition phase, as well as the phase of the production and transportation of building materials.
It should be noted that the reason we adopted this method to verify the feasibility of the research is that the building under investigation in this manuscript has not yet been completed, and we are unable to obtain actual measured building energy consumption data. Therefore, we employed an energy consumption calculation method based on national standards.
Since this research investigates the characteristics of building cooling and heating energy consumption, we only compared the electricity demand during the operational phase of the building. The calculation results are shown in Figure 3.
The calculation results show that the difference between the two energy demand calculations is very small, with a correlation coefficient as high as 0.96. Considering the P-value, it can be concluded that the simulation results calculated by EnergyPlus software (version 2210) can accurately reflect the actual energy demand of the building. It should be noted that the “actual data” used for validation here was essentially also obtained through theoretical calculations, involving factors such as the thermal properties of building materials, energy efficiency of HVAC, lighting, and ventilation systems, etc. If more precise building energy demand data can be obtained in the future, it would be beneficial to further optimize the calculation model of EnergyPlus software. However, taking into account the software’s recognition in the building thermal industry and the comparison of calculation results in this study, we can consider the simulation results of building energy characteristics using EnergyPlus(v2210) in this paper to be reliable and the modeling method to be feasible.

3. Results

In order to compare the impact of various factors on building carbon emissions, based on the basic design scheme of the building, the basic carbon emission characteristics of the building were calculated according to the Chinese “Standard for Building Carbon Emission Calculation” (GB/T 51366-2019).

3.1. Architectural Layout Level

(1)
Building Orientation
The orientation of a building has a significant impact on the amount of thermal radiation and the lighting and illumination within the building. Building orientation falls within the scope of preliminary planning. Based on the characteristics of climate analysis and the specific features of the site, the optimal orientation for the building is determined and the corresponding thermal radiation surface is increased. For buildings with the same plan and window-to-wall ratio, a comparison of orientations is made. According to the set angles, the energy consumption simulation and carbon emission calculations for the two climate zones are shown in Figure 4.
As shown in the figure, the carbon emissions for buildings with the main facade facing south are generally lower (Xi’an is 7.1 kgCO2/m2·a, Yulin is 10.4 kgCO2/m2·a), but the overall differences are not significant. Overall, the impact of building orientation on carbon emissions is relatively small, indicating that other factors play a more important role in carbon emissions.
(2)
Window-to-Wall Ratio
The carbon emission results from the simulation comparing window-to-wall ratios at set values are shown in Figure 5. As illustrated, the window-to-wall ratio has a significant impact on building energy consumption and carbon emissions. Overall, carbon emissions gradually increase with the increase of the window-to-wall ratio, a trend that is very clear in both Xi’an and Yulin. Under the same window-to-wall ratio conditions, Yulin has higher carbon emissions than Xi’an, which is due to the greater amount of energy required annually in Yulin to maintain a suitable building environment (for indoor heating).
Figure 6 shows a positive correlation between the window-to-wall ratio and carbon emissions. As the window-to-wall ratio increases, carbon emissions rise, with a quadratic fit closely matching the data. This indicates that the window-to-wall ratio significantly impacts carbon emissions. Critical points derived from the model (−2.57 for Xi’an and −1.33 for Yulin) are not practically applicable, suggesting no turning points within the data range.
The relationship between the window-to-wall ratio and carbon emissions is influenced not only by the exterior window area but also by factors such as regional climate, building materials, and glass insulation performance. Considering these variables may reveal deeper insights. Window-to-wall ratio design should focus on overall energy efficiency, not just carbon emissions. For instance, optimizing window orientation and size can enhance natural ventilation and sunlight effects, improving comfort and energy efficiency while maintaining low carbon emissions.
Based on current data, carbon emissions increase with the window-to-wall ratio, with no clear critical point identified. Therefore, in the design phase, it is essential to comprehensively consider energy efficiency, window technology, and regional characteristics, avoiding over-reliance on increasing the window-to-wall ratio for natural lighting. This approach balances the building’s energy needs with carbon emissions.

3.2. Building Material Level

(1)
Window Glass Forms
The manuscript compared the carbon emission characteristics of industrial buildings under five common types of window glass used in actual engineering, and the results are shown in Figure 7. It is evident that low-emissivity (Low-E) glass and multi-layer glass have a significant effect on effectively reducing carbon emissions. Low-E glass is coated with one or more layers of special metal or oxide films on its surface. These films can reflect indoor heat, reducing the loss of indoor heat in winter, and can also effectively block infrared rays from solar radiation and some visible light from entering the room in summer, thereby reducing the building’s cooling and heating energy consumption. This improvement in insulating performance directly reduces the energy consumption during the operation of the building, thus lowering carbon emissions. Multi-layer glass, by increasing the number of glass layers and the air layer in between, forms a more complex heat transfer structure, which can more effectively block the transfer of heat and enhance the insulation and thermal retention performance of the windows.
It should be noted that the window area of factory buildings using the window–wall system is usually small, but with the update of production work forms, more curtain wall system factory buildings will be constructed; hence, the impact of different glass combinations may be more significant than office buildings or industrial plants, especially when combined with different climatic conditions and the orientation of the buildings.
Comparison Analysis of Ar Glass (Argon Glass) and Non-Ar Glass: Ar glass (argon-filled glass): By using argon as an insulating layer can effectively reduce thermal conductivity, especially in cold climates, Ar glass can significantly reduce heat loss in winter. For example, the 6+12Ar+6 combination shows relatively low levels of carbon emissions in Xi’an and Yulin, indicating that argon-filled layers have a significant effect on improving insulation. Non-Ar glass: The insulating effect of ordinary air-filled glass is slightly worse than argon, but it can still provide sufficient performance in warm climates and is suitable for buildings with low energy consumption requirements. For example, the 6+12A+6 performs slightly lower than argon glass in different regions, but it can still effectively reduce carbon emissions in some cases, especially in areas with high cooling demands in summer. However, it should be pointed out that the carbon reduction effect of argon-added glass is not better than Low-E glass and glass windows with more vacuum layers.
Comparison Analysis of Double Glazing and Triple Glazing: Triple glazing (such as 5+9A+5+9A+5 and 6+12A+6+12A+6) provides better insulation due to an additional layer of glass and insulating layer. Triple-glazed window structures are usually used in buildings in cold or extreme climate conditions, especially in situations with high energy-saving requirements. Triple glazing shows the most significant carbon reduction effect in dormitory buildings, with a substantial decrease in carbon emissions, indicating the superiority of triple glazing combinations in improving building energy efficiency.
Comparison of Coated Glass and Uncoated Glass: Low-E glass, by reducing infrared radiation, can significantly improve the insulation of buildings and reduce heat loss in winter. For example, the 6Low E+12A+6 shows a clear advantage in carbon emissions in Xi’an and Yulin, especially in the cold winter, where coated glass can effectively reduce energy loss. Uncoated glass: Ordinary glass does not have this insulating coating, and in some warmer climates, the use of ordinary glass is sufficient to meet energy-saving needs, but it does not perform as well as coated glass in cold regions.
In summary, triple-glazed structures and Low-E-coated glass can significantly reduce carbon emissions, especially in areas with high winter heating demands. In cases with high summer cooling demands, Low-E-coated glass and argon-filled glass are better choices, and in warm regions, ordinary double glazing can also provide sufficient insulation effects.
(2)
Roof Reflectance
By setting different parameters, such as the solar radiation reflectance coefficient of the roof, it is possible to compare the impact of different roof material options on the building’s carbon emissions. These parameters can determine how the building’s roof interacts with solar radiation and the surrounding environment in terms of heat exchange, thereby affecting the building’s energy consumption. The results are shown in Figure 8.
It can be observed that, as the roof reflectance increases (from dark-colored surface concrete to light-colored floor tiles), the overall carbon emissions of the building decrease. This indicates that using materials with high reflectance can help reduce the absorption of solar radiation in the summer, thereby lowering the demand for cooling and consequently reducing energy consumption and carbon emissions. It should be noted that a large area of factory-type buildings is the production area, where there is no need for heating or cooling, and the main demand for indoor thermal comfort is in the office area, which has a smaller roof area. Therefore, although using light-colored materials may lead to rapid heat dissipation from the roof in winter, resulting in increased heating demands and energy consumption, the overall impact on the building’s carbon emissions is small. Overall, for industrial buildings, it is necessary to choose roofing materials based on the actual production characteristics and building shape and to balance the thermal environment between the winter and summer seasons.
(3)
Wall Reflectance
By setting different parameters, such as the wall’s solar radiation absorption coefficient and visible light reflectance coefficient, we can compare the carbon emission impact of different wall materials. The solar radiation absorption coefficient determines the proportion of solar radiation energy absorbed by the wall, while the visible light reflectance coefficient reflects the wall’s ability to reflect natural light. By adjusting these parameters to different values, we can simulate the energy performance of buildings under various scenarios, with the results shown in Figure 9.
As shown in the figure, with the increase of wall reflectance, the carbon emissions of buildings show a decreasing trend under the climatic conditions of Xi’an. The dark-colored profiled steel plate has the lowest reflectance and higher carbon emissions, while the white-colored profiled steel plate has a higher reflectance, with a corresponding significant reduction in carbon emissions. This characteristic is opposite in the Yulin area. This is because buildings usually have a large area of walls, and the wall reflectance has a significant impact on the building’s heat absorption. High reflectance wall materials can reduce the solar radiation absorbed by the building, especially in the summer, which helps to lower indoor temperatures, thereby reducing the need for air conditioning systems, energy consumption, and carbon emissions. However, in extremely cold areas like Yulin in winter, high reflectance walls, while reducing cooling demands in summer, are not conducive to absorbing solar radiation in winter, leading to increased heat loss from buildings and lower indoor temperatures.
In summary, the increase in wall reflectance has a significant effect on reducing carbon emissions in the summer. Using light-colored or white wall coatings can effectively reduce the carbon emissions of buildings in areas where winter heating demands are not very high, such as Xi’an. However, in areas with high heating demands, it is more appropriate to choose darker facade materials.
(4)
Thickness of Roof Insulation
By setting different thicknesses of roof insulation, the transfer of heat between the inside and outside of the building can be changed, allowing for a comparison of the carbon emission characteristics of different cases, with the results shown in Figure 10. Overall, as the thickness of the roof insulation increases, the carbon emissions of the building show a significant downward trend. Therefore, changing the thickness of the roof insulation can serve as an effective strategy, playing a key role in reducing carbon emissions during the operation of the building.
To calculate the inflection point for carbon reduction through critical point calculation, the rate of change (derivative) of the curve can be used to determine it. The most significant carbon reduction critical point shows a notable trend of carbon emission reduction when the thickness of the insulation board is between 62 mm and 80 mm. Within this range, the increase in the thickness of the roof insulation board has the greatest impact on carbon emissions. Beyond this thickness, the rate of change gradually decreases, and the effect of further increasing the thickness becomes less noticeable. The improvement in carbon emissions from continuing to increase the insulation layer will gradually weaken, and a cost-benefit analysis should be conducted in conjunction with the building type and climatic conditions.
(5)
Wall Insulation Thickness
By setting different wall insulation thicknesses, the impacts of various external insulation practices on building carbon emissions were compared, and the results are shown in Figure 11. Overall, as the thickness of the insulation layer increases, the carbon emissions tend to decrease. The greater the thickness, the better the insulation effect of the wall, and the less the thermal loss of the building, thereby reducing the energy consumption for heating or cooling, which leads to a reduction in carbon emissions. However, the reduction in carbon emissions gradually slows down with the increase in insulation layer thickness, and the rate of change shows significant differences across different thickness ranges, exhibiting a critical inflection point.
The inflection point range for the impact of industrial plant wall insulation thickness on building carbon emissions is between 62 mm and 80 mm, and the rate of change in carbon emissions in the Yulin area is greater than in Xi’an, indicating that buildings in the Yulin area are more sensitive to changes in insulation thickness, and carbon emissions decrease more significantly with increased thickness. The reason for this may be that the demand for heating in the Yulin area is relatively high in winter, and improved insulation can significantly reduce energy consumption. The rate of change in carbon emissions in Xi’an is relatively smaller, especially in the Yingma dormitory buildings, where the change in carbon emissions with increased insulation thickness is not as great as in Yulin. This may be related to the climatic conditions and thermal performance requirements of buildings in Xi’an.

3.3. Technical Measures Level: BIPV Roof

Photovoltaic (PV) roofs have a shading effect, and the impact of the area of photovoltaic panels on building energy consumption has been extensively studied by scholars. In addition to the proportion of the photovoltaic panel area, the angle of the photovoltaic panels also has different effects on building energy consumption, especially considering that different angles of inclination affect the power generation of the roof’s photovoltaic panels, which makes the impact of photovoltaic roofs on building carbon emissions more complex. It should be noted that this study does not consider energy storage of photovoltaic power generation, but instead it calculates it as “the amount of carbon emissions that the building can reduce”.
As shown in Figure 12, an increase in the angle of photovoltaic roofs can help reduce the carbon emissions of buildings to a certain extent (the optimal photovoltaic installation angle in the Xi’an area is around 22°), but this effect is not significant. This is because, as the angle of the roof’s photovoltaic panels increases, the power generation of the photovoltaics increases for the same area, thus providing a greater “green carbon” amount. However, it also reduces the shading effect on the roof, leading to an increase in energy consumption in the summer. It should be noted that less roof shading reduces the energy consumption of the building in winter, which also reduces the overall annual carbon emissions of the building to some extent.

4. Discussion

4.1. Integrated Multi-Factor Simulation and Optimal Scheme Design

By dividing the building’s low-carbon system levels and setting single-factor parameters, a low-carbon building design system is established. Through simulation calculations of single factors in common factory building design, the simulation results with the lowest single-factor carbon emissions are selected, and the optimal carbon-reducing design parameters are chosen to explore the maximum extent of carbon reduction in common design practices.
As shown in Table 4, for industrial buildings in Xi’an (cold region), the building orientation can be set to the west, with a window-to-wall ratio of 0.1 (this is an ideal parameter obtained through numerical simulation, but it needs to be adjusted according to actual engineering conditions); using five-pane triple-glazed glass (6 mm glass with 12 mm air layer), the roof can be set to light-colored floor tiles, and an insulation layer thickness of 180 mm can be chosen; the walls can be white profiled steel plates with an insulation layer thickness of 120 mm, and BAPV photovoltaic roofs can be set at an angle of 33 degrees. Compared to the original standard scheme, it can reduce carbon emissions by about 24%.
As shown in Table 5, for industrial buildings in Yulin (severely cold region), it is appropriate to choose dark-colored profiled steel plates with low reflectivity for wall materials, and the rest of the design methods are the same as in the Xi’an area. With this design method, the factory can reduce carbon emissions by about 21% compared to the original standard scheme.
Overall, regardless of whether the building is located in a cold or severely cold region, employing more scientific architectural design methods can significantly reduce the carbon emissions of buildings. It should be noted that the low-carbon technologies mentioned above are materials or methods that are commonly used in everyday design and construction, and they are both universal and economical. Although the design and construction costs of low-carbon buildings may be higher than those of traditional buildings, the increase in cost can be kept at a relatively low level through scientific optimization in design [66].

4.2. Sensitivity of the Impact of Various Factors

On the basis of understanding the extent to which a combination of various low-carbon design methods can reduce building carbon emissions, it is also necessary to understand the efficiency of various low-carbon design technologies in reducing building carbon emissions. This can also be considered as a horizontal comparison of the sensitivity of various design elements to building carbon emissions. Research on sensitivity can horizontally compare various low-carbon design techniques (since building orientation and window-to-wall ratio are not controlled by cost, they are not discussed in this part), and it can help engineers choose the appropriate design techniques to optimize on the basis of the same total investment. This conclusion is even more important in the retrofitting of existing buildings.
Therefore, according to comparative simulations, comparing the carbon reduction range and cost difference ratio of various design elements can effectively evaluate the sensitivity of impact. The ranking of carbon reduction degrees of various elements is shown in the Table 6. We find that choosing more suitable wall insulation boards for buildings can provide more significant carbon reduction effects at the same cost. The use of BAPV roofs has the worst carbon reduction effect at the same cost (in the Xi’an area, it is 1/108.6 of the carbon reduction degree of wall insulation, and in Yulin, it is 1/92.3). The main reason for this is the high cost of BAPV roofs (the cost of photovoltaics is 15.4 times that of wall insulation boards). In addition to roof and facade insulation boards, choosing the right glass materials can also provide better carbon reduction effects at the same cost. Next is the facade and roof materials. Due to the area limit of the roof, its improvement effect is very unobtrusive. Although the unit price carbon reduction capability of roof materials is higher than that of photovoltaic roofs, photovoltaic roofs can provide more clean energy for buildings. Therefore, the total energy demand of the building is also an important factor that needs to be considered in future research.

4.3. Limitation

When conducting research on industrial buildings, it is important to consider the characteristics of human activities within them. For example, there are differences in activity intensity and personnel density between office areas and workshop areas. Moreover, these differences also exist among different types of industrial buildings. However, this manuscript employs a more universal modeling approach. The basis for these parameters is primarily the general regulations established by the Chinese government for building energy efficiency standards. This means that the research findings cannot accurately calculate the actual carbon emissions of a specific industrial building or a particular category of industrial buildings. Instead, they can only reflect the relative differences in building carbon emissions resulting from the adoption of different architectural design methods.

4.4. Future Research Prospects

This manuscript primarily focuses on the carbon emissions during the operational phase of buildings. However, it is important to note that 60% of the total carbon emissions in a building’s entire life cycle still originate from the construction and demolition phases.
Previous research has demonstrated that construction in cold climates often necessitates specific preventive measures, such as enhanced insulation or heating systems, which can significantly impact the energy consumption and CO2 emissions of a building [67].
Environmental Product Declarations (EPD) are increasingly crucial in the construction industry for comparing the emissions of materials and components. This trend aligns with the broader research focus on assessing and reducing the life-cycle carbon emissions (LCCE) of buildings. Recent studies have shown that the LCCE of buildings can be significantly influenced by factors such as material choices, building lifespan, and operational energy efficiency. For instance, the use of low-carbon materials like timber or rapidly renewable plant-based materials has been found to reduce embodied carbon emissions (ECE) by up to 96.5% compared to traditional materials. Additionally, optimizing the building’s operational phase through energy-efficient technologies can further minimize operational carbon emissions (OCE). These findings highlight the importance of adopting a comprehensive life-cycle perspective on building design and material selection to achieve sustainable outcomes [68].
These studies highlight that adopting a full life-cycle perspective is essential for identifying and implementing the most sustainable solutions, as it allows for a comprehensive assessment of environmental impacts across all stages of a building’s life, from construction to demolition.
It can be observed that numerous scholars have paid attention to the carbon emissions from other stages of a building’s entire life cycle. In future research, these emissions could be quantified and analyzed using statistical models. This approach is particularly relevant given the development trends of building information modeling (BIM) technology and the project general contracting (engineering, procurement, construction) model. These areas are expected to become focal points of future research.

5. Conclusions

Global climate change and the extensive use of fossil fuels pose a threat to the sustainable development of human society. After the Industrial Revolution, the global temperature rose sharply, and carbon emissions continued to increase. China, as the current largest carbon emitter globally, has committed to achieving carbon emission peaking by 2030 and carbon neutrality by 2060. The construction industry, as a major field of energy consumption and carbon emissions, plays a crucial role in achieving global temperature control targets. With diverse building forms and significant differences in the spatial characteristics of various types of buildings, industrial plants, as the most important type of building for production activities, account for a large proportion of the global building stock. Therefore, creating a low-carbon design for representative industrial plants has become a key issue that architects must face and solve.
This manuscript, based on the ENERGYPLUS (version 2210) platform, used the “standard coal method” to quantify the carbon emissions during the operational phase of industrial plants. This study analyzed the impact of common low-carbon design methods on the energy consumption of industrial buildings from three levels: architectural layout, building materials, and photovoltaic technology, and we selected Xi’an and Yulin areas as the background for the study, analyzing the applicability of common low-carbon design techniques in cold and severely cold climate zones.
This study demonstrated that, at the architectural layout level, the orientation of the building has a relatively small impact on carbon emissions, while an increase in the window-to-wall ratio significantly increases the carbon emissions of the building. At the building material level, the form of window glass, the reflectivity of roofs and walls, and the thickness of roof and wall insulation boards have a significant impact on carbon emissions. At the technical measures level, the angle of photovoltaic roofs has no significant impact on carbon emissions. Through simulation calculations of single-factor parameters, the optimal carbon-reducing design parameters were selected, exploring the maximum extent of carbon reduction in common design practices. By further comparing the efficiency of various low-carbon design technologies in reducing building carbon emissions, it was found that choosing more suitable wall insulation boards can provide more significant carbon reduction effects at the same cost.
The influence of diverse low-carbon retrofitting methods on the annual carbon emissions of buildings serves as a valuable reference for refining the design approaches of low-carbon buildings. Initially, the selection of appropriate insulation materials is crucial, with particular emphasis on the thickness of roof insulation. Subsequently, determining the optimal window-to-wall ratio is essential, as this parameter significantly affects the annual carbon emissions of buildings. Following this, the choice of building glass type becomes imperative, given its strong correlation with the window-to-wall ratio. As the proportion of glass on the façade increases, the impact of the glass material on annual carbon emissions becomes increasingly significant. Additionally, consideration should be given to the reflectivity of building exterior materials, especially the roof material. Furthermore, the installation of photovoltaic materials is highly recommended, as it not only reduces the annual carbon emissions of buildings but also supplies them with clean energy.
This paper presents a systematic approach to the low-carbon optimization design of buildings, which can significantly reduce their carbon emissions by integrating architectural layout, building materials, and photovoltaic technology measures. These methods are universal and cost-effective, and the adoption of passive low-carbon design strategies will not lead to a noticeable increase in building costs. This study underscores the necessity of evaluating the carbon emissions across all stages of a building during the design phase and highlights the importance of considering the building’s total energy demand in future research. This conclusion aids architects in selecting the most suitable or effective carbon-reducing design methods for designing and retrofitting industrial plants. It also provides the government with a more scientific and quantitative basis for formulating low-carbon development plans for industrial buildings.

Author Contributions

Conceptualization, L.S. and X.L.; methodology, D.X. and Y.Y.; software, Y.Y.; investigation, D.X., X.L., L.H., Y.L. and T.H.; resources, D.X., X.L., L.H., Y.L. and T.H.; data curation, D.X., X.L., L.H., Y.L. and T.H.; writing—original draft preparation, L.S., D.X. and Y.Y.; writing—review and editing, Y.Y.; visualization, D.X. and Y.Y.; supervision, L.S.; project administration, L.S.; funding acquisition, Y.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China’s Young Scientists Fund No. 52208032.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

Authors Long Shi, Xin Li, Lei Huang, Yafeng Li and Tingru Huang were employed by the company Northwest Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. United Nations Framework Convention on Climate Change. Kyoto Protocol Reference Manual. Available online: https://unfccc.int/process-and-meetings/the-kyoto-protocol/what-is-the-kyoto-protocol/kyoto-protocol-targets-for-the-first-commitment-period (accessed on 3 November 2024).
  2. Chaturvedi, K.; Singhwane, A.; Dhangar, M.; Mili, M.; Gorhae, N.; Naik, A.; Prashant, N.; Srivastava, A.K.; Verma, S. Bamboo for producing charcoal and biochar for versatile applications. Biomass Convers. Biorefin. 2023, 13, 15159–15185. [Google Scholar] [CrossRef] [PubMed]
  3. Wei, X.; Zhang, M.; Wang, G.Y.; Liu, G.L.; Chi, Z.M.; Chi, Z. The ornithine-urea cycle involves fumaric acid biosynthesis in Aureobasidium pullulans var. aubasidani, a green and eco-friendly process for fumaric acid production. Synth. Syst. Biotechnol. 2022, 8, 33–45. [Google Scholar] [CrossRef] [PubMed]
  4. Fu, L.; Wang, Q. Spatial and Temporal Distribution and the Driving Factors of Carbon Emissions from Urban Production Energy Consumption. Int. J. Environ. Res. Public Health 2022, 19, 12441. [Google Scholar] [CrossRef] [PubMed]
  5. Lal, R.M.; Tibrewal, K.; Venkataraman, C.; Tong, K.; Fang, A.; Ma, Q.; Wang, S.; Kaiser, J.; Ramaswami, A.; Russell, A.G. Impact of Circular, Waste-Heat Reuse Pathways on PM2.5-Air Quality, CO2 Emissions, and Human Health in India: Comparison with Material Exchange Potential. Environ. Sci. Technol. 2022, 56, 9773–9783. [Google Scholar] [CrossRef]
  6. Jiang, H.; Fan, G.; Zhang, D.; Zhang, S.; Fan, Y. Evaluation of eco-environmental quality for the coal-mining region using multi-source data. Sci. Rep. 2022, 12, 6623. [Google Scholar] [CrossRef]
  7. Kong, Y.; Feng, C.; Guo, L. Peaking Global and G20 Countries’ CO2 Emissions under the Shared Socio-Economic Pathways. Int. J. Environ. Res. Public Health 2022, 19, 11076. [Google Scholar] [CrossRef]
  8. He, Y.; Liu, G. Coupling coordination analysis of low-carbon development, technology innovation, and new urbanization: Data from 30 provinces and cities in China. Front. Public Health 2022, 10, 1047691. [Google Scholar] [CrossRef]
  9. Li, H.; Lin, T. Do Land Use Structure Changes Impact Regional Carbon Emissions? A Spatial Econometric Study in Sichuan Basin, China. Int. J. Environ. Res. Public Health 2022, 19, 13329. [Google Scholar] [CrossRef]
  10. National Development and Reform Commission of China. National Strategy for Climate Change Adaptation 2035. Available online: https://www.gov.cn/zhengce/zhengceku/2022-06/14/content_5695555.htm (accessed on 3 November 2024).
  11. National Development and Reform Commission of China. Action Plan for Carbon Dioxide Peaking Before 2030. Available online: https://www.gov.cn/zhengce/content/2021-10/26/content_5644984.htm (accessed on 3 November 2024).
  12. Qin, H.; Yu, Z.; Li, T.; Liu, X.; Li, L. Heating Control Strategy Based on Dynamic Programming for Building Energy Saving and Emission Reduction. Int. J. Environ. Res. Public Health 2022, 19, 14137. [Google Scholar] [CrossRef]
  13. Miguel, G.S.; Bañales, B.M.; Ruiz, D.; Álvarez, S.; Pérez, J.; Arredondo, M.T. Carbon footprint and employment generation produced by ICT networks for Internet deployment: A multi-regional input-output analysis, Science of The Total Environment. Sci. Total Environ. 2024, 914, 169776. [Google Scholar] [CrossRef]
  14. Mavromatidis, G.; Orehounig, K.; Richner, P.; Carmeliet, J. A strategy for reducing CO2 emissions from buildings with the Kaya identity—A Swiss energy system analysis and a case study. Energy Policy 2016, 88, 343–354. [Google Scholar] [CrossRef]
  15. Li, M.; Zhang, X. Calculation of Industrial Carbon Emissions and Analysis of Influencing Factors in Gansu Province. Environ. Sci. Manag. 2016, 41, 6. [Google Scholar]
  16. Chau, C.K.; Leung, T.M.; Ng, W.Y. A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings. Appl. Energy 2015, 143, 395–413. [Google Scholar] [CrossRef]
  17. Yu, Y.; You, K.; Cai, W.; Feng, W.; Li, R.; Liu, Q.; Chen, L.; Liu, Y. City-level building operation and end-use carbon emissions dataset from China for 2015–2020. Sci. Data 2024, 11, 138. [Google Scholar] [CrossRef]
  18. Guo, D.; Chen, H.; Long, R.; Ni, Y. An integrated measurement of household carbon emissions from a trading-oriented perspective: A case study of urban families in Xuzhou, China. J. Clean. Prod. 2018, 188, 613–624. [Google Scholar] [CrossRef]
  19. Liu, J.; Yang, Q.; Ou, S.; Liu, J. Factor decomposition and the decoupling effect of carbon emissions in China’s manufacturing high-emission subsectors. Energy 2022, 248, 123568. [Google Scholar] [CrossRef]
  20. Nie, S.; Zhou, J.; Yang, F.; Lan, M.; Li, J.; Zhang, Z.; Chen, Z.; Xu, M.; Li, H.; Sanjayan, J.G. Analysis of theoretical carbon dioxide emissions from cement production: Methodology and application. J. Clean. Prod. 2022, 334, 130270. [Google Scholar] [CrossRef]
  21. Yao, S.; Liu, Z.; Lu, Z.; Guo, S.; Xie, Z.; Li, Z.; Huang, Y.; Li, L.; Lu, W.; Chen, X. Research progress of soft measurement technology optimizing carbon emission measurement of coal-fired power plants. Clean Coal Technol. 2024, 30, 18–31. [Google Scholar]
  22. Ren, H.; Ou, X.; Zhu, H. Spatial characteristics and coupling coordination between carbon emission efficiency and industrial structure in three metropolitan areas of Jiangsu Province, China. Sci. Prog. 2023, 106, 368504231176146. [Google Scholar] [CrossRef]
  23. Chen, J.; Zhu, Y.; Yang, C.; Wang, H.; Wang, K. Evaluation and prediction of carbon emission from logistics at city scale for low-carbon development strategy. PLoS ONE 2024, 19, e0298206. [Google Scholar] [CrossRef]
  24. Bayer, C.; Gamble, M.; Gentry, R.; Joshi, S. Guide to building life cycle assessment in practice. Am. Inst. Archit. 2010, 1–193. [Google Scholar]
  25. Cole, R.J. Energy and greenhouse gas emissions associated with the construction of alternative structural systems. Build. Environ. 1999, 34, 335–348. [Google Scholar] [CrossRef]
  26. Gustavsson, L.; Joelsson, A.; Sathre, R. Life cycle primary energy use and carbon emission of an eight-story wood framed apartment building. Energy Build. 2010, 42, 230–242. [Google Scholar] [CrossRef]
  27. Ramesh, T.; Prakash, R.; Shukla, K.K. Life cycle energy analysis of buildings: An overview. Energy Build. 2010, 42, 1592–1600. [Google Scholar] [CrossRef]
  28. Yu, P.; Chen, X.; Ma, L. A Review of Carbon Emissions in the Life Cycle of Residential Buildings. Build. Sci. 2011, 27, 35. (In Chinese) [Google Scholar]
  29. Lin, B.; Liu, N.; Peng, B.; Zhu, Y. Comparative Study on International Building Life Cycle Energy Consumption and CO2 Emissions. Build. Sci. 2013, 8, 22–27. (In Chinese) [Google Scholar]
  30. Mousa, M.; Luo, X.; McCabe, B. Utilizing BIM and Carbon Estimating Methods for Meaningful Data Representation. Procedia Eng. 2016, 145, 1242–1249. [Google Scholar] [CrossRef]
  31. Peng, C. Calculation of a building’s life cycle carbon emissions based on Ecotect and building information modeling. J. Clean. Prod. 2016, 112, 453–465. [Google Scholar] [CrossRef]
  32. Yang, Q.; Huo, R.; Tong, H. Research on Design Trend of Solar Photocoltaic High-Rise Residential Buildings Based on Future Climate from the Perspective of Carbon Neutrality. Ind. Constr. 2022, 52, 8–16. (In Chinese) [Google Scholar]
  33. Cao, H.; Liu, X.; Feng, G.; Wang, C.; Huang, K.; Hou, X.; Chen, J. Research on the evaluation of the renovation effect of existing energy-inefficient residential buildings in a severe cold region of China. Energy Build. 2024, 312, 114184. [Google Scholar] [CrossRef]
  34. Chen, L.; Msigwa, G.; Yang, M.; Osman, A.I.; Fawzy, S.; Rooney, D.W.; Yap, P.-S. Strategies to achieve a carbon neutral society: A review. Environ. Chem. Lett. 2022, 20, 2277–2310. [Google Scholar] [CrossRef] [PubMed]
  35. Wang, L.; Chen, T.; Yu, Y.; Wang, L.; Zang, H.; Cang, Y.; Zhang, Y.; Ma, X. Impacts of Vegetation Ratio, Street Orientation, and Aspect Ratio on Thermal Comfort and Building Carbon Emissions in Cold Zones: A Case Study of Tianjin. Land 2024, 13, 1275. [Google Scholar] [CrossRef]
  36. Gao, Z.; Liu, H.; Xu, X.; Xiahou, X.; Cui, P.; Mao, P. Research Progress on Carbon Emissions of Public Buildings: A Visual Analysis and Review. Buildings 2023, 13, 677. [Google Scholar] [CrossRef]
  37. Wang, Y.; Mauree, D.; Sun, Q.; Lin, H.; Scartezzini, J.L.; Wennersten, R. A review of approaches to low-carbon transition of high-rise residential buildings in China. Renew. Sustain. Energy Rev. 2020, 131, 109990. [Google Scholar] [CrossRef]
  38. Liu, Y.S.; Yigitcanlar, T.; Guaralda, M.; Degirmenci, K.; Liu, A.; Kane, M. Leveraging the Opportunities of Wind for Cities through Urban Planning and Design: A PRISMA Review. Sustainability 2022, 14, 11665. [Google Scholar] [CrossRef]
  39. Wuyun, Q.; Li, B.; Bian, M.; Wang, C.; Huang, Z.; Wang, B.; Cai, W.; Wang, M.; Zhang, X.; He, T.; et al. Demonstration and data analysis of a Zero Emission Building (ZEB) in Beijing, China. Solar Energy 2024, 272, 112488. [Google Scholar] [CrossRef]
  40. Chen, Y.; Wang, Z.; Peng, Z. A Study on Carbon Emission Reduction in the Entire Process of Retrofitting High-Rise Office Buildings Based on the Extraction of Typical Models. Sustainability 2024, 16, 8506. [Google Scholar] [CrossRef]
  41. Wang, J.; Liu, W.; Du, X.; Zhang, W. Low-carbon-oriented commercial district urban form optimization and impact assessment analysis. Build. Environ. 2024, 254, 111377. [Google Scholar] [CrossRef]
  42. Chen, Y.; Luo, L. Energy consumption behaviors and the potential of natural ventilation emission reduction in residential building. J. Asian Archit. Build. Eng. 2024, 23, 2029–2040. [Google Scholar] [CrossRef]
  43. Hałacz, J.; Skotnicka-Siepsiak, A.; Neugebauer, M. Assessment of Reducing Pollutant Emissions in Selected Heating and Ventilation Systems in Single-Family Houses. Energies 2020, 13, 1224. [Google Scholar] [CrossRef]
  44. Elaouzy, Y.; El Fadar, A. Energy, economic and environmental benefits of integrating passive design strategies into buildings: A review. Renew. Sustain. Energy Rev. 2022, 167, 112828. [Google Scholar] [CrossRef]
  45. Zhong, H.-Y.; Sun, Y.; Shang, J.; Qian, F.-P.; Zhao, F.-Y.; Kikumoto, H.; Jimenez-Bescos, C.; Liu, X. Single-sided natural ventilation in buildings: A critical literature review. Build. Environ. 2022, 212, 108797. [Google Scholar] [CrossRef]
  46. Lestinen, S.; Kilpeläinen, S.; Kosonen, R.; Valkonen, M.; Jokisalo, J.; Pasanen, P. Effects of Night Ventilation on Indoor Air Quality in Educational Buildings—A Field Study. Appl. Sci. 2021, 11, 4056. [Google Scholar] [CrossRef]
  47. Echenagucia, T.M.; Moroseos, T.; Meek, C. On the tradeoffs between embodied and operational carbon in building envelope design: The impact of local climates and energy grids. Energy Build. 2023, 278, 112589. [Google Scholar] [CrossRef]
  48. Shah, I.; Soh, B.; Lim, C.; Lau, S.-K.; Ghahramani, A. Thermal transfer and temperature reductions from shading systems on opaque facades: Quantifying the impacts of influential factors. Energy Build. 2023, 278, 112604. [Google Scholar] [CrossRef]
  49. Fan, J.; Wang, H.; Zhou, D. Policy approaches to optimize the layout of ecological construction and enhance carbon sequestration capacity. J. Chin. Acad. Sci. 2022, 37, 459–468. [Google Scholar] [CrossRef]
  50. Besir, A.B.; Cuce, E. Green roofs and facades: A comprehensive review. Renew. Sustain. Energy Rev. 2018, 82, 915–939. [Google Scholar] [CrossRef]
  51. China News Service. State Council Meeting: By 2020, Non-Fossil Energy Will Account for 15% of Primary Energy. Available online: https://www.chinanews.com.cn/cj/cj-hbht/news/2009/11-26/1986477.shtml (accessed on 3 November 2024).
  52. Finnegan, S.; Jones, C.; Sharples, S. The embodied CO2e of sustainable energy technologies used in buildings: A review article. Energy Build. 2018, 181, 50–61. [Google Scholar] [CrossRef]
  53. Liu, Z.; Zhang, L.; Gong, G.; Li, H.; Tang, G. Review of solar thermoelectric cooling technologies for use in zero energy buildings. Energy Build. 2015, 102, 207–216. [Google Scholar] [CrossRef]
  54. Ozkan, O.; Coban, M.N.; Destek, M.A. Navigating the winds of change: Assessing the impact of wind energy innovations and fossil energy efficiency on carbon emissions in China. Renew. Energy 2024, 228, 120623. [Google Scholar] [CrossRef]
  55. Dong, S.; Zhao, H.; Zheng, Y.; Ni, L. Carbon reduction analysis of electric heat pumps in carbon neutrality in China. Sustain. Cities Soc. 2023, 97, 104758. [Google Scholar] [CrossRef]
  56. Kaizer, T.H. Green Garment Factories in Bangladesh: Motivation and Challenges. 2020. Available online: https://api.semanticscholar.org/CorpusID:245536680 (accessed on 3 November 2024).
  57. Zhu, T.; Li, R.; Li, C. The Analysis of Natural Lighting Simulation and Study on Energy Saving in Cigarette Factory. Procedia Eng. 2017, 205, 896–901. [Google Scholar] [CrossRef]
  58. Rana, B.; Patel, A. Application of Green Building Concepts to Enhancement of Environment & Health of workers of Paper Mill. Int. J. Sci. Res. Dev. 2017, 3, 467–470. Available online: https://ijsrd.com/articles/IJSRDV5I30380.pdf (accessed on 3 November 2024).
  59. Lee, B.; Trcka, M.; Hensen, J.L.M. Embodied energy of building materials and green building rating systems—A case study for industrial halls. Sustain. Cities Soc. 2011, 1, 67–71. [Google Scholar] [CrossRef]
  60. Patil, M.; Boraste, S.; Minde, P. A comprehensive review on emerging trends in smart green building technologies and sustainable materials. Mater. Today Proc. 2022, 65, 1813–1822. [Google Scholar] [CrossRef]
  61. Wang, H.; Chiang, P.-C.; Cai, Y.; Li, C.; Wang, X.; Chen, T.-L.; Wei, S.; Huang, Q. Application of Wall and Insulation Materials on Green Building: A Review. Sustainability 2018, 10, 3331. [Google Scholar] [CrossRef]
  62. Golroudbary, S.R.; Makarava, I.; Kraslawski, A.; Repo, E. Global environmental cost of using rare earth elements in green energy technologies. Sci. Total Environ. 2022, 832, 155022. [Google Scholar] [CrossRef]
  63. Shi, J.; Yu, Y. To Advance Industrial Green Technology via Environmental Governance—Evidence from China’s Industrial Sector. Processes 2021, 9, 1797. [Google Scholar] [CrossRef]
  64. GB/T 51366-2019; Standard for Calculation of Building Carbon Emissions. Ministry of Housing and Urban-Rural Development of the People’s Republic of China: Beijing, China, 2019.
  65. GB 51245-2017; Unified Standard for Energy-efficient Design of Industrial Buildings. Ministry of Housing and Urban-Rural Development of the People’s Republic of China: Beijing, China, 2017.
  66. UK Green Building Council, Building the Case for Net Zero: A Feasibility Study into the Design, Delivery and Cost of New Net Zero Carbon Buildings. Available online: https://ukgbc.org/resources/building-the-case-for-net-zero/ (accessed on 3 November 2024).
  67. Nilimaa, J.; Zhaka, V. Material and Environmental Aspects of Concrete Flooring in Cold Climate. Constr. Mater. 2023, 3, 180–201. [Google Scholar] [CrossRef]
  68. Huang, Z.; Zhou, H.; Miao, Z.; Tang, H.; Lin, B.; Zhuang, W. Life-Cycle Carbon Emissions (LCCE) of Buildings: Implications, Calculations, and Reductions. Engineering 2024, 35, 115–139. [Google Scholar] [CrossRef]
Figure 1. Methods for calculating building carbon emissions.
Figure 1. Methods for calculating building carbon emissions.
Buildings 15 00974 g001
Figure 2. Three-dimensional model of Longteng Industrial Park No. 1 factory building.
Figure 2. Three-dimensional model of Longteng Industrial Park No. 1 factory building.
Buildings 15 00974 g002
Figure 3. Comparison of calculation models.
Figure 3. Comparison of calculation models.
Buildings 15 00974 g003
Figure 4. The impact of building orientation on carbon emissions in Xi’an (left) and Yulin (right).
Figure 4. The impact of building orientation on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g004
Figure 5. The impact of building window-to-wall ratio on carbon emissions in Xi’an (left) and Yulin (right).
Figure 5. The impact of building window-to-wall ratio on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g005
Figure 6. Quadratic fitting chart of the impact of the window-to-wall ratio on carbon emissions.
Figure 6. Quadratic fitting chart of the impact of the window-to-wall ratio on carbon emissions.
Buildings 15 00974 g006
Figure 7. The impact of window glass forms on carbon emissions in Xi’an (left) and Yulin (right).
Figure 7. The impact of window glass forms on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g007
Figure 8. The impact of roof reflectance on carbon emissions in Xi’an (left) and Yulin (right).
Figure 8. The impact of roof reflectance on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g008
Figure 9. The impact of wall reflectance on carbon emissions in Xi’an (left) and Yulin (right).
Figure 9. The impact of wall reflectance on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g009
Figure 10. The impact of thickness of roof insulation on carbon emissions in Xi’an (left) and Yulin (right).
Figure 10. The impact of thickness of roof insulation on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g010
Figure 11. The impact of thickness of wall insulation on carbon emissions in Xi’an (left) and Yulin (right).
Figure 11. The impact of thickness of wall insulation on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g011
Figure 12. The impact of photovoltaic installation angle on carbon emissions in Xi’an (left) and Yulin (right).
Figure 12. The impact of photovoltaic installation angle on carbon emissions in Xi’an (left) and Yulin (right).
Buildings 15 00974 g012
Table 1. Thermal properties of building materials.
Table 1. Thermal properties of building materials.
Material Name Thermal Conductivity (λ)Heat Storage Coefficient (S)Thermal Resistance (R)Thermal Inertiaindex
W/(m·K)W/(m2·K)(m2·K)/WD = R * S
Aggregate concreteRoof1.51015.3600.0260.407
Squeeze polystyrene board0.0320.3652.6041.141
Cement mortar0.93011.3700.0220.245
Aerated concrete, foamed concrete0.1803.1000.4441.378
Steel reinforced concrete1.74017.2000.0691.186
Lime mortar0.81010.0700.0250.249
Cement mortarWall0.93011.3700.0220.245
Rock wool board0.0400.7501.5631.406
Cement mortar0.93011.3700.0220.245
Sand filling products0.2003.1901.5004.785
Lime mortar0.81010.0700.0250.249
Table 2. Hourly occupancy rates of personnel within the building.
Table 2. Hourly occupancy rates of personnel within the building.
123456789101112131415161718192021222324
PeopleWorkday000001010501001001003010010010010050201000000
Holiday00000101020454545104545454545101000000
LightingWorkday101010101010103662565443535558674018101010101010
Holiday101010101010101010101010101010101010101010101010
EquipmentWorkday0000010105010010010010010010010010050201000000
Holiday00000101020454545454545454545101000000
Table 3. Low-carbon design hierarchical system.
Table 3. Low-carbon design hierarchical system.
Hierarchy LevelSimulation FactorsForm
Architectural LayoutOrientationEast (E)
South-East (SE)
South (S)
South-West (SW)
West (W)
Window-to-Wall Ratio0.5
0.4
0.3
0.2
0.1
Building MaterialWindow Glass6 mm glass + 12 mm air cavity + 6 mm glass
(6+12A+6)
6 mm Low-e glass + 12 mm air cavity + 6 mm glass
(6Low E+12A+6)
6 mm glass + 12 mm argon cavity + 6 mm glass
(6+12Ar+6)
5 mm Low-e glass + 9 mm air cavity + 5 mm glass + 9 mm air cavity + 5 mm glass
(5+9A+5+9A+5)
6 mm Low-e glass + 12 mm air cavity + 6 mm glass + 912 mm air cavity + 6 mm glass
(6+12A+6+12A+6)
Roof ReflectanceConcrete (reflectivity = 0.23)
Dark-Colored Profiled Steel Plate (reflectivity = 0.35)
Color-Coated Profiled Steel Plate (reflectivity = 0.50)
Light-Colored Profiled Steel Plate (reflectivity = 0.60)
Light-Colored Floor Tiles (reflectivity = 0.70)
Wall ReflectanceDark Gray Profiled Steel Plate (reflectivity = 0.35)
Light Gray Profiled Steel Plate (reflectivity = 0.50)
White Profiled Steel Plate (reflectivity = 0.70)
Thickness of XPS Roof Insulation (mm)90
120
150
180
210
Thickness of XPS Wall Insulation (mm)60
80
100
120
Technical MeasuresBuilding-Attached Photovoltaic (BAPV) RoofWithout PV
11°
22°
33°
Table 4. Low-carbon retrofit of factories in the Xi’an area (the red part indicates the parts that are different from the original design scheme).
Table 4. Low-carbon retrofit of factories in the Xi’an area (the red part indicates the parts that are different from the original design scheme).
Hierarchy LevelSimulation FactorsFormCarbon Emission of Current DesignCarbon Emission of Low-Carbon Design
Architectural LayoutOrientationWest2.6 tCO22.0 tCO2
Window-to-Wall Ratio0.1
Building MaterialWindow Glass6+12A+6+12A+6
Roof ReflectanceLight-Colored Floor Tiles
Wall ReflectanceWhite Profiled Steel Plate
Thickness of XPS Roof Insulation (mm)180
Thickness of XPS Wall Insulation (mm)120
Technical MeasuresPV Roof33°
Table 5. Low-carbon retrofit of factories in the Yulin area.
Table 5. Low-carbon retrofit of factories in the Yulin area.
Hierarchy LevelSimulation FactorsFormCarbon Emission of Current DesignCarbon Emission of Low-Carbon Design
Architectural LayoutOrientationSouth3.8 tCO23.0 tCO2
Window-to-Wall Ratio0.1
Building MaterialWindow Glass6+12A+6+12A+6
Roof ReflectanceDark-Colored Floor Tiles
Wall ReflectanceWhite Profiled Steel Plate
Thickness of XPS Roof Insulation (mm)180
Thickness of XPS Wall Insulation (mm)120
Technical MeasuresPV Roof33°
Table 6. Sensitivity analysis of the impact of low-carbon design factors.
Table 6. Sensitivity analysis of the impact of low-carbon design factors.
FactorsRegionMost Economic SolutionCarbon Emission Reduction per 10,000 Yuan
(KgCO2/10,000 Yuan)
Window GlassXi’an6LowE+12A+6−333.9
Yulin6LowE+12A+6−555.8
Roof MaterialXi’anLight-Colored Floor Tiles−45.5
YulinLight-Colored Floor Tiles−27.3
Wall MaterialXi’anWhite Profiled Steel Plate−253.4
YulinDark-colored Profiled Steel PlateCommon Design
Roof Insulation Xi’an90 mm XPS−873.8
Yulin90 mm XPS−1114.0
Wall Insulation Xi’an80 mm XPS−1889.8
Yulin80 mm XPS−2676.3
PV Roof AngleXi’an−17.4
Yulin11°−29.0
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

Shi, L.; Xu, D.; Li, X.; Huang, L.; Li, Y.; Huang, T.; Yang, Y. The Impact Characteristics of Common Low-Carbon Design Methods on Reducing Carbon Emissions in Industrial Plant Buildings in Architectural Design. Buildings 2025, 15, 974. https://doi.org/10.3390/buildings15060974

AMA Style

Shi L, Xu D, Li X, Huang L, Li Y, Huang T, Yang Y. The Impact Characteristics of Common Low-Carbon Design Methods on Reducing Carbon Emissions in Industrial Plant Buildings in Architectural Design. Buildings. 2025; 15(6):974. https://doi.org/10.3390/buildings15060974

Chicago/Turabian Style

Shi, Long, Duo Xu, Xin Li, Lei Huang, Yafeng Li, Tingru Huang, and Yujun Yang. 2025. "The Impact Characteristics of Common Low-Carbon Design Methods on Reducing Carbon Emissions in Industrial Plant Buildings in Architectural Design" Buildings 15, no. 6: 974. https://doi.org/10.3390/buildings15060974

APA Style

Shi, L., Xu, D., Li, X., Huang, L., Li, Y., Huang, T., & Yang, Y. (2025). The Impact Characteristics of Common Low-Carbon Design Methods on Reducing Carbon Emissions in Industrial Plant Buildings in Architectural Design. Buildings, 15(6), 974. https://doi.org/10.3390/buildings15060974

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