Using BIM and LCA to Calculate the Life Cycle Carbon Emissions of Inpatient Building: A Case Study in China

Abstract

Hospital buildings provide healthcare services at the costs of significant amounts of energy consumption and carbon emissions, further exacerbating the environmental load. Because of the limited research on the life cycle carbon emissions of Chinese hospitals, this study conducted a detailed carbon-accounting and comparative study. Firstly, BIM and LCA were used to quantify the carbon emissions of the inpatient building in each stage of the life cycle. Secondly, the differences in carbon emissions by stage were compared on the basis of 20 cases of public buildings. The results show that the whole-life carbon emissions of the inpatient building was 10,459.94 kgCO₂/m². The proportion of operational carbon emissions was 94.68%, with HVAC (52.57%), equipment (27.85%), and lighting (10.11%) being the main sources. Embodied carbon emissions accounted for 4.54%, and HRB400 steel and C30 concrete were the main sources of carbon emissions. Hospitals are second only to emporiums in terms of operational carbon intensity, being 1.71 and 1.41 times that of schools and office buildings, with inpatient buildings being 3 and 1.7 times that of medical complexes and outpatient buildings, respectively. The future sustainable development of hospital buildings should promote efficient building performance and good environmental quality, both in terms of energy efficiency and carbon reduction.

1. Introduction

The current situation is one in which the twin crises of the environment and public health are converging [1]. Global warming is having a significant impact on ecosystems and human health as global temperatures have risen by 0.8 °C over the last century, a result of accelerated industry and population growth [2]. The building sector accounts for 30% of global end-use energy consumption and 28% of carbon emissions [3]. As the core of the public healthcare system, hospitals have complex functions, a high density of power-consuming equipment, and they operate year-round, requiring the consumption of large amounts of operational energy and generating considerable carbon emissions [4,5,6]. Healthcare-related carbon emissions are equal to around 200 million tons globally, accounting for 4.4% of total global carbon emissions [7]. Hospitals in Europe account for 7% of nonresidential buildings and 10% of the total energy consumption in the sector [8]. In the United States, hospitals have one of the highest energy intensities of any commercial building [9], with twice the energy intensity per square foot of an office building [10]. In China, hospital buildings have three to four times the energy consumption and two to three times the carbon emissions of the average public building [11]. Buildings that provide healthcare services that require massive energy consumption and carbon emissions will further exacerbate environmental loads in the future [6,12].

At the United Nations Climate Change Conference COP26, in Glasgow, in November 2021, 36 countries committed to developing low-carbon health systems, with a further 14 countries committing to a target of near-zero carbon health services by 2050 [13]. China has pledged to stop increasing its carbon emissions by around 2030, as the largest carbon emitter [14]. To achieve this goal, it is important to further assess the impact of carbon emitted by existing hospitals and promote the development of low-carbon healthcare buildings while ensuring their safe operation [15]. Since the 1990s, Peuportier [16] has developed specialized frameworks for the life cycle assessment (LCA) of buildings, which are widely used to determine the environmental impacts of related products [17,18]. Many researchers have combined an LCA with building information modeling (BIM) to assess the life cycle carbon emissions of buildings; explore the current status of carbon emissions according to different regions, types, structures, construction processes, green technologies, etc.; and propose corresponding carbon reduction strategies [19].

Nematchoua [20] used Designbuilder and Pleiades LCA software to assess the life cycle carbon emissions of the Shanghai Centre Building in China and the World Trade Center in the United States. The carbon intensity of the Shanghai Centre Building (20.9 kgCO₂/m²) was lower than that of the World Trade Center (21.5 kgCO₂/m²), assuming that fossil fuels such as coal were no longer included in the buildings’ energy mixes. The embodied carbon of the World Trade Center was 50% of that of the Shanghai Centre, as all building materials contained 25% recycled content. Wang [21] analyzed the life cycle carbon emissions of the Yiku Building 3 in Nanhai, China, and the Pixel Building in Australia, which are the two highest-rated green buildings in the region, to show the relationship between green buildings and low greenhouse gas emissions, measure the reduction in carbon due to the use of various low-carbon technologies in buildings, and highlight the importance of applying LCA theory in assessing environmental impacts. Li [22] built an assessment model using Simapro software and compared the life cycle carbon emissions of homes, schools, hospitals, and offices in China, and the results showed that hospitals had the highest carbon emission intensity and schools the lowest. Zhang [23] discussed differences in the life cycle carbon emissions of typical residential and office buildings in China according to their different structures. It was shown that a reinforced concrete block masonry structure is a more environmentally friendly choice, reducing carbon emissions by 38~112 kgCO₂/m² compared to brick–concrete and concrete structures. Yang [24] found that the use of wood in the construction of buildings can achieve life cycle carbon reductions ranging from 14.7% to 51.8%, with an average carbon reduction of 32.7%. Zhou and Li [25,26] used BIM technology to assess the difference in the life cycle carbon footprints between prefabricated and conventional cast-in-place buildings, demonstrating the significant low-carbon benefits of prefabrication. Gustavsson [27] studied the life cycle energy consumption and carbon emissions of a wooden apartment building and found that combining it with a biomass energy system resulted in a carbon-negative building life cycle. Wu [28] used the building environmental load evaluation system (BELES) to compare the differences in the life cycle carbon emissions between green and nongreen buildings in China. By analyzing 26 residential and commercial buildings in cold regions and hot-summer and cold-winter regions, it was found that the green residential and commercial buildings achieved carbon reductions of 10% and 32%, respectively.

While China has conducted a large number of carbon emission studies on residential and office buildings in the past, there has been limited research on the life cycle carbon emissions of hospitals, which are specialized buildings that host the urban healthcare system. China’s healthcare industry is huge, with more than 80% of hospitals operating at capacity or even over capacity, and more than half of hospitals having planned or in-progress construction [29]. As hospitals expand their operations and improve the quality of their services, growths in energy consumption and carbon emissions are inevitable trends [11,30]. To clarify the differences in carbon emissions between hospitals and other types of public buildings at different stages of the whole life cycle, this study used BIM and LCA to quantify the whole-life carbon emissions of an inpatient building of a Chinese hospital for infectious diseases and to compare the whole life carbon emissions of 20 cases of different public buildings in China, including office buildings, schools, emporiums, factories, and hospitals. The methodology adopted will help to estimate hospital carbon emissions where partial data are lacking, provide data to support decision making for the optimization of low-carbon design, and also provide case references for the assessment of hospital carbon emissions.

The full text Is structured as follows: Section 2 describes the inpatient building, the modeling process, the carbon emissions calculations, and the methodology used in the stock case study. Section 3 shows the carbon emissions of the inpatient building at each stage of its life cycle. It also shows the carbon emissions of the stock cases. Section 4 discusses the differences between the inpatient building and the stock cases, the impact of the operating mode on carbon emissions, the choice of indicators to assess carbon emissions, and the limitations of this study. Finally, Section 5 presents the conclusions.

2. Materials and Methods

2.1. Life Cycle Assessment

Life cycle assessment (LCA) is a methodology for evaluating the resource and environmental impacts of a product during the stages of raw material extraction, processing, manufacturing, packaging, transport, consumption, recycling, and final disposal (i.e., the entire “cradle-to-grave” life cycle of the product) [31]. Since its introduction in 1990, it has been recognized as an important tool for assessing the environmental impact of products [32]. The application of LCA theory to construction can not only quantitatively assess the degree of the environmental impact of buildings but also guide the selection of schemes, materials, construction methods, and operational strategies at the design stage [33].

In this study, the life cycle carbon emissions boundary of the hospital was divided into the following three parts: embodied stage (stage 1), operational stage (stage 2), and demolition stage (stage 3) [34]. The embodied stage consists in the production of building materials, transport, and construction; the operational stage consists in operational energy consumption and carbon emissions due to maintenance and renewal; and the demolition stage consists in the energy consumption of the demolition machinery and waste transport.

2.2. Case Description

2.2.1. Case Introduction

This case is the inpatient building of an infectious disease hospital in China (Figure 1), which is equipped with the “normal-emergency conversion” function and can quickly respond to public health emergencies by switching its mode of operation. In “normal times”, the building will be used as a hospital for the prevention and treatment of respiratory infectious diseases, such as tuberculosis and hepatitis, and contact infectious diseases. In “emergency times”, it can be quickly converted into a treatment facility for outbreaks of virulent infectious diseases. To avoid cross-infection as much as possible, the layout is designed according to the local standard of “three zones and two passages” [35], which includes a clean zone (Zone 1), semi-contaminated zone (Zone 2), contaminated zone (Zone 3), and corridors for human and logistic flows. Detailed information on this case is shown in

Table 1. Parameters of the inpatient building.

Parameters	Detailed Information
Building location	Nanjing, Jiangsu
Climate zone	Hot-summer, cold-winter zone
Construction period	Designed in 2021 and completed in 2023
Area	15,679.57 m2
Height	5 floors above ground, 1 floor below ground, total height 23.95 m
Structure	Frame structure
Form factor	0.15
Number of beds	150 negative pressure wards with a total of 300 beds
Zone 1	3103.8 m2, including consultation room, lounge, dining room, duty room, and shower room
Zone 2	3029.2 m2, including nurses’ station, treatment room, store room, office, and healthcare corridor
Zone 3	9246.6 m2, including wards, buffer rooms, soiled storage rooms, soiled washrooms, and patient corridor

.

2.2.2. Simulation

Building energy modeling (BEM) is a powerful tool for assessing the energy performances of buildings [36]. This study employed the energy simulation software Designbuilder (V6.1.3.008) with the design documents for the model construction and energy simulation, as shown in Figure 2. Detailed building parameters, envelope characteristics, heating and cooling data, and thermal disturbance data of the building required for the simulation [37] are given in

Table 2. Parameter settings required for simulation.

Parameters	Values
External walls U-value, Uwall	0.58 W/(m2·K)
Roof U-value, Uroof	0.4 W/(m2·K)
Window U-value, Uwindow	2.2 W/(m2·K)
Solar heat gain coefficient, SHGC	SHGCeast = 0.37, SHGCwast = 0.37, SHGCsouth = 0.37, SHGCnorth = 0.37
Window-to-wall ratio, WWR	WWReast = 0.24, WWRwast = 0.22, WWRsouth = 0.12, WWRnorth = 0.04
Occupancy density	0.04 people/m2
Domestic hot water	0.21 L/(m2·day)
Summer setting temperature, Tsummer	26 °C
Winter setting temperature, Twinter	20 °C
Ventilation rate	Zone 1 = 3 ac/h, Zone 2 = 6 ac/h, Zone 3 = 12 ac/h
Default display lighting density	6 W/m2
Power density	15 W/m2

. The occupancy, heating, ventilation and air conditioning (HVAC), equipment, and lighting operating strategies for the model were set concerning the General code for energy efficiency and renewable energy application in buildings GB55015-2021 [38], Design standard for energy efficiency of public buildings GB 50189-2015 [39], and Technical Guidelines for the Construction of Negative Pressure Wards in Emergency Treatment Facilities for COVID-19 (Trial) [40]. Furthermore, this model partition sets the number of air changes per hour (ac/h).

2.3. Detailed Calculation Methodology

This study mainly adopted a combination of the inventory analysis method and the emission factor method to assess carbon emissions. As a carbon emission calculation method recommended by the IPCC, the basic principle of the emission factor method is “carbon emission = activity data × emission factor” [34], which has been widely adopted because it can comprehensively measure the greenhouse gas emissions of buildings, and the inventory analysis method was developed on the basis of this method. However, the inventory analysis method takes the process analysis as a starting point, calculates the carbon emissions of each process of the building in detail, and finally accumulates the carbon emissions of the whole life cycle, which facilitates the analysis of specific stages.

2.3.1. Total Carbon Emissions

The carbon emissions generated over the whole life cycle of a building are made up of embodied carbon emissions, operational carbon emissions and demolition carbon emissions, as shown in Equation (1).

$$C_{lca}=C_1+C_2+C_3$$

(1)

where $C_{lca}$ are the life cycle carbon emissions (kgCO₂); $C_1$ are the embodied carbon emissions (kgCO₂); $C_2$ are the operational carbon emissions (kgCO₂); and $C_3$ are the demolition carbon emissions (kgCO₂).

2.3.2. Stage 1

The embodied carbon emissions consist of the following three components: production of building materials, transport, and construction. This study used the inventory analysis method of calculation, as detailed in Equation (2).

$$C_1=C_P+C_T+C_C$$

(2)

where $C_P$ is the carbon emissions from the production of building materials (kgCO₂); $C_T$ is the carbon emissions from the transportation of building materials (kgCO₂); and $C_C$ is the carbon emissions during construction (kgCO₂).

Carbon emissions from the production of building materials are the carbon emissions generated during the production and processing of a building’s main structural materials, envelope materials and other components, etc., as shown in Equation (3).

$$C_P=\sum _{i=1}^n(M_i\times {EF}_i)$$

(3)

where $M_i$ is the consumption of the $i$-th building material used in the project (unit), and ${EF}_i$ is the carbon emission factor for the production of the $i$-th building material (kgCO₂/unit).

Related studies have shown that according to the Pareto principle or 80/20 rule, only the highest categories of building materials can be calculated to estimate the carbon emissions of all building materials [19,41]. This study collected consumption data on six major building materials, including concrete, cement, steel, brick, wood, and other materials, based on the building list, and the carbon emission factors of the building materials are mainly from the relevant standard [42], as shown in

Table 3. Consumption of key building materials and carbon emission factors.

No.	Material Type		Unit	Amount	${\mathit{E}\mathit{F}}_{\mathit{i}}$
1	Concrete	C15	m3	481.33	177.8
2		C20	m3	647.37	237.32
3		C25	m3	619.74	266.18
4		C30	m3	6642.35	295
5		C35	m3	23.88	362.6
6		C50	m3	854.46	511
7	Cement	32.5	kg	124,597.12	0.621
8		42.5	kg	70,595.28	0.795
9		Cement mortar	m3	714.18	315
10	Steel	Section steel	kg	5593.69	2.365
11		HRB 300	kg	29,638.14	2.34
12		HRB 400	kg	1,103,654.28	2.34
13		HRB 500	kg	67,488.3	2.34
14		Cold-rolled ribbed bar	kg	5243.82	3.368
15		Pipe support	kg	28,593.13	2.43
16		Steel pipe scaffolding	kg	35,442.28	2.43
17	Brick	Brick (190 × 90 × 40)	m3	51.76	336
18		Standard brick (240 × 115 × 53)	One hundred	377.17	49.15
19		KM1 brick (190 × 190 × 90)		3934.75	109.17
20		Concrete solid brick (190 × 90 × 43)		149.42	24.71
21		Concrete block (600 × 250 × 200)	m3	928.7	212
22	Wood		m3	1079.51	178
23	Others	Sand	t	332.12	2.51
24		Gravel	t	297.75	2.18
25		Sealing bolt	kg	6048.19	1.54
26		Welding rod	kg	4773.85	3.027

.

Carbon emissions from the transport of building materials are generated during the transport of building materials to the construction site, as shown in Equation (4).

$$C_T=\sum _{i=1}^n(M_i\times T_i\times {EF}_t)$$

(4)

where $T_i$ is the distance of the i-th building material from the production site to the construction site (km); ${EF}_t$ is the carbon emission factor for different modes of transport.

Transport vehicles typically include trucks, trains, and ships [18]. This case follows the principle of proximity, with the main materials, such as concrete, steel, sand, gravel, and cement, coming from Nanjing, and the rest of the building materials being procured in Jiangsu. Building material factories in Nanjing are usually located in the suburbs of Jiangning, Pukou, and Liuhe [43]. In this study, the procurement distance was 40 km in Nanjing and 400 km in Jiangsu; heavy-duty diesel trucks were chosen as the only means of transport, and the transport carbon emission factor was taken as 0.162 kgCO₂/(t·km) [42].

Construction carbon emissions are mainly generated by the consumption of energy such as diesel, petrol, and electricity during the use of construction machinery, as shown in Equation (5).

$$C_C=\sum _{k=1}^n(M_{m,k}\times B_{m,k}\times {EF}_{e,j})$$

(5)

where $M_{m,k}$ is the class consumption of the k-th mechanical equipment (unit); $B_{m,k}$ is the energy consumption quota of the $k$-th mechanical equipment; and ${EF}_{e,j}$ is the carbon emission factor of the $j$-th energy (kgCO₂/unit).

As shown in

Table 4. Consumption list of major construction machinery and equipment.

No.	Machinery and Equipment	Energy Consumption per Shift			Number of Shifts
		Gasoline (kg)	Diesel (kg)	Electricity (kWh)
1	Pipe cutting machine (150 mm)	/	/	12.90	96.79
2	Conical thread turning machine (45 mm)	/	/	9.24	566.45
3	Truck crane (5 t)	/	26.43	/	56.10
4	Truck crane (16 t)	/	35.85	/	4.50
5	Truck crane (20 t)	/	38.41	/	28.00
6	Truck crane (40 t)	/	48.52	/	16.00
7	Self-lifting tower crane (400 t)	/	/	164.31	179.54
8	Truck (4 t)	25.48	/	/	226.80
9	Truck (8 t)	/	35.49	/	16.00
10	Truck (15 t)	/	56.74	/	15.00
11	Platform trailer (20 t)	/	45.39	/	12.00
12	Tipping car (1 t)	/	6.03	/	26.41
13	Low-speed winch (30 kN)	/	/	28.76	380.43
14	Mortar mixer (200 L)	/	/	8.61	23.41
13	Concrete vibrator (flat type)	/	/	6.72	561.01
14	Concrete vibrator (insertion type)	/	/	5.38	403.11
15	Vortex concrete mixer (500 L)	/	/	107.71	5.78
16	Steel bar cutting machine (40 mm)	/	/	32.10	123.38
17	Steel bar bender (40 mm)	/	/	12.80	365.06
18	Woodworking circular sawing machine (500 mm)	/	/	24.00	579.81
19	Electric multistage centrifugal water pump (100 mm)	/	/	180.40	66.76
20	Submersible pump (100 mm)	/	/	25.00	10.32
21	AC arc welding machine (30 kVA)	/	/	96.53	279.68
22	AC arc welding machine (40 kVA)	/	/	132.23	6.22
23	Butt welding machine	/	/	122.00	50.07
24	Argon welder	/	/	70.70	71.32
25	Electric hammer	/	/	4.20	839.68

, this study collected data on the consumption of 20 major types of machinery and equipment during the construction process. The energy consumption per unit shift of each piece of machinery and equipment refers to the relevant standards in China, and the main energy consumed is petrol, diesel, and electricity, and the carbon emission coefficients of energy are given in

Table 5. Carbon emission factors of major energy sources.

Type	CO2 Emission Factor	Data Sources
Gasoline	2.93 kgCO2/kg	[42,44]
Diesel oil	3.1 kgCO2/kg
Natural gas	2.16 kgCO2/m3
Tap water	0.168 kgCO2/t	[42]
Electricity (Jiangsu Province)	0.7 kgCO2/kWh	[45]

.

2.3.3. Stage 2

Operational carbon emissions consist in both operational energy consumption and maintenance, as shown in Equation (6).

$$C_2=C_E+C_M$$

(6)

where $C_E$ are the carbon emissions caused by operational energy consumption (kgCO₂); $C_M$ are the carbon emissions of maintenance (kgCO₂).

The main types of energy consumed in the operation of the hospital are electricity, gas, and domestic water. In this study, Designbuilder software was used to assess the building’s energy consumption for heating, cooling, lighting, and equipment; Equation (7) was used to calculate the carbon emissions due to electricity and gas consumption; and the carbon emissions due to domestic water consumption were estimated with reference to Equation (8) [46]. The energy carbon emission factors required for the above calculations are shown in Table 5.

$$C_E=\left[\left(\frac{Q_C}{{COP}_c}+\frac{Q_H\phi }{{\eta }_1{q}_1{q}_2}\right)+S\left(E_l+E_e\right)\right]{EF}_{e}A+C_W$$

(7)

$$C_W=D\times S\times A\times {EF}_w$$

(8)

where $Q_C$ is the cumulative annual cooling consumption (kWh); ${COP}_c$ is the coefficient of performance for cooling systems in public buildings, taken as 3.5; $Q_H$ is the cumulative annual heat consumption (kWh); ${\eta }_1$ is the combined efficiency of the heating system, where the heat source is a gas-fired boiler, taken as 0.85; $q_1$ is the standard calorific value of natural gas, taken as 9.87 kWh/m³; $q_2$ is the combined coal consumption for power generation, taken as 0.33 kgce/kWh; $\phi$ is the conversion factor between natural gas and standard coal, taken as 1.21 kgce/m³; $S$ is the area of the building (m²); $E_l$ is the annual lighting energy consumption (kWh/m²); $E_e$ is the annual equipment energy consumption (kWh/m²); ${EF}_{e,j}$ is the electricity carbon emission factor (kgCO₂/kWh); $A$ is the design life of the building, taken as 50 years; $C_W$ are the carbon emissions caused by domestic water (kgCO₂); $D$ is the daily consumption, taken as 2 t/m²; and ${EF}_w$ is the carbon emission factor of water (kgCO₂/t).

Maintenance carbon emissions are those from the renewal and maintenance of equipment and components, which can be quickly estimated by multiplying the embodied carbon emissions by a maintenance factor [46], referring to Equations (9) and (10).

$$C_M=M\times C_1$$

(9)

$$M=1\%\times n_1+20\mathrm{\%}\times n_2+25\mathrm{\%}\times n_3$$

(10)

where $M$ is the maintenance coefficient, taken as 0.65 [46]; $n_1$, $n_2$, and $n_3$ are the number of minor, intermediate, and major repairs, respectively.

2.3.4. Stage 3

Demolition carbon emissions include carbon emissions from demolition and waste disposal. As this is a new building and data on demolition are not available, a quick assessment was made using the empirical formula proposed in a related study [46], as shown in Equation (11).

$$C_3=S(2.88X+19.37)$$

(11)

where $X$ is the number of floors above ground.

2.4. Stock Cases

This study collected data on carbon emissions from public buildings in China by researching related studies. The research included the basic design factors of buildings (such as geographical location, climatic environment, building scale, and structure) and carbon emissions data (such as total carbon emissions, carbon emissions and percentages at each stage, and types of accounting data at each stage). Considering that different scholars have drawn different carbon emissions boundaries for the accounting process, this will lead to difficulties in conducting comparative studies [47]. Therefore, in this study, the life cycle boundary of each stock case was uniformly divided into the embodied stage, operational stage, and demolition stage according to the content described in Section 2.1.

2.5. Evaluation Indices for Carbon Emissions

This study chose to use carbon emissions per unit area, $C_A$, to make a side-by-side comparison of the carbon emissions at each stage of the life cycle of different buildings, as shown in Equation (12).

$$C_A=\frac{C_l}{S}$$

(12)

where $C_A$ are the carbon emissions per unit area (kgCO₂/m²), and $C_l$ are the carbon emissions in stage $l$ (kgCO₂).

3. Results

3.1. Embodied Carbon Emissions

3.1.1. Building Materials Production

As shown in Figure 3, the total carbon emissions from the production of building materials in the inpatient building were 7050.28 tCO₂, and the carbon emissions per unit area were 449.65 kgCO₂/m². Only carbon emissions from the production of steel and concrete accounted for 82.38% of carbon emissions, and the carbon emissions and consumption for steel and concrete were analyzed in detail, as follows:

• The carbon emissions from the production of all steel materials were 2996.31 tCO₂, accounting for 42.52%. Among them, the carbon emissions of HRB400 steel were 2582.55 tCO₂, as shown in Figure 4a.
• The carbon emissions from the production of all concrete amounted to 2808.95 tCO₂, accounting for 39.86%. The carbon emissions of C30 concrete and C50 concrete were 2396.12 tCO₂, which were the two largest concrete materials (85.32% of all concrete) in terms of carbon emissions, as shown in Figure 4b.
• The two most carbon-intensive building materials were HRB400 steel and C30 concrete, accounting for 64.42% of the carbon emissions from the production of building materials.
• As shown in

  Table 6. Consumption of main building materials.

  Material	Consumption per Unit Area
  Concrete	0.497 m3/m2
  Steel	68.39 kg/m2
  Cement	87.04 kg/m2
  Wood	0.011 m3/m2
  Brick	95.24 kg/m2
  Sand	33.77 kg/m2

  , the consumptions of concrete and steel, in this study, were 0.497 m³/m² and 68.39 kgCO₂/m², respectively, which is in line with the statistical values for concrete (0.3~0.5 m³/m²) and steel (40~70 kg/m²) consumption for Chinese buildings [46].

Figure 3. Carbon emissions from production of major building materials.

Figure 3. Carbon emissions from production of major building materials.

3.1.2. Transport

As shown in Figure 5, the total carbon emissions from the transport of building materials were 269.45 tCO₂, with a carbon emission per unit area of 17.18 kgCO₂/m². Among these, C30 concrete and concrete blocks (600 × 250 × 200) were the two types of building materials that emitted the most carbon during transport, generating 94.69 tCO₂ and 81.24 tCO₂ of the carbon emissions from transport, respectively, with a combined percentage of 65.29%.

3.1.3. Construction

As shown in Figure 6, the total carbon emissions from the construction phase were 126.4 tCO₂ and 8.06 kgCO₂/m² per unit area. The three pieces of mechanical equipment with the largest share were the self-lifting tower crane, the AC arc welding machine (30 kVA), and the truck (4 t), accounting for 16.4%, 15%, and 13.4%, respectively. In addition, electricity, gasoline, and diesel were the main sources of carbon emissions during the construction phase, and the project consumed a cumulative total of 131,033 kWh of electricity, 5778.97 kg of gasoline, and 5618.73 kg of diesel during construction. Electricity generated 92.05 tCO₂ of the carbon emissions, accounting for 73% of the total. Gasoline and diesel produced 16.93 tCO₂ and 17.42 tCO₂, respectively.

3.2. Operational Carbon Emissions

The simulation results are shown in Figure 7. The energy intensity of the hospital is 270.52 kWh/m², of which 66.96 kWh/m² is for cooling, 90.12 kWh/m² is for heating, 30.22 kWh/m² is for lighting, and 83.22 kWh/m² is for other equipment. The total carbon emissions due to energy consumption are 148,715.32 tCO₂, and the carbon emissions per unit area are 9485 kgCO₂/m². Among them, the carbon emission intensity of heating is 3154.2 kgCO₂/m², accounting for 33.25%; the carbon emission intensity of cooling is 2343.6 kgCO₂/m², accounting for 24.71%; the carbon emission intensity of lighting is 1057.7 kgCO₂/m², accounting for 11.15%; and the carbon emission intensity of other equipment is 2912.7 kgCO₂/m², accounting for 30.71%. The carbon emission intensity of other equipment is 2912.7 kgCO₂/m², accounting for 30.71%; the carbon emission intensity of domestic water is 16.8 kgCO₂/m², accounting for 0.18%.

In addition, carbon emissions of approximately 4839.98 tCO₂ were generated by the maintenance and renewal of the inpatient building.

3.3. Demolition Carbon Emissions

On the basis of Equation (11), the carbon emissions from the demolition of the inpatient building were 629.9 tCO₂ and 40.17 kgCO₂/m² per unit area.

3.4. Life Cycle Carbon Emissions

As shown in

Table 7. Carbon emissions throughout the life cycle of the inpatient building.

	Carbon Emission (tCO2)	Carbon Emission Intensity (kgCO2/m2)	Percentage (%)
Embodied stage	7446.13	474.91	4.54%
Production of building materials	7050.28	449.66	4.30%
Transport of building materials	269.45	17.19	0.16%
Construction	126.4	8.06	0.08%
Operational stage	155,925.31	9944.85	95.08%
Cooling	36,745.31	2343.60	22.41%
Heating	49,454.71	3154.20	30.16%
Lighting	16,583.68	1057.70	10.11%
Equipment	45,668.22	2912.70	27.85%
Domestic water	2633.41	167.96	1.61%
Maintenance	4839.98	308.69	2.95%
Demolition stage	629.9	40.17	0.38%
Total life cycle carbon emissions	164,001.34	10,459.94	100.00%

, the inpatient building generates a total of 164,001.34 tCO₂ carbon emissions over 50 years, with a carbon emissions per unit area of 10,459.94 kgCO₂/m². The embodied stage accounts for 4.54% of the carbon emissions, the demolition stage for only 0.38%, and the operational stage for 95.08%, which is significantly higher than the other stages, with a carbon emissions per unit area of 9944.85 kgCO₂/m². Heating, equipment, and cooling were the largest contributors to carbon emissions, accounting for 30.16%, 27.85%, and 22.41%, respectively.

3.5. Comparison of Stock Cases

This study compiled 20 cases of public buildings in China, as shown in

Table 8. Composition of the stock cases.

No	Location	Zone	Type	Structure	Area (m2)	Floors	Calculation Method			Sources
							Stage 1	Stage 2	Stage 3
C1	Guangdong	IV	Office	Reinforced concrete	192,181	36	SimaPro	SimaPro	SimaPro	[22]
C2	Xiamen	IV	Office	Frame	24,533.19	9	Main materials (10 types)	DeST-c	Estimation	[48]
C3	Enshi	III	Office	Frame-shear wall	44,615.56	9	Main materials (3 types)	IBE	Estimation	[49]
C4	Tianjin	II	Office	Steel	12,878.5	5	Detailed list	Measurement	Estimation	[50]
C5	Enshi	III	Office	Frame-shear wall	20,036.81	9	Main materials (3 types)	IBE	Estimation	[51]
C6	Shenzhen	IV	Office	Frame	25,023.9	5	Detailed list	Measurement	Estimation	[21]
C7	Shanghai	III	Office	Reinforced concrete	24,261	7	Main materials (11 types)	E-Quest	Estimation	[52]
C8	Harbin	I	Office	Concrete	15,514	28	Main materials (14 types)	Energyplus	List	[53]
C9	Xi’an	II	Office	Frame	11,351	6	Detailed list	Designbuilder	List	[54]
C10	Tianjin	II	Office	Frame	57,000	9	Detailed list	Measurement	List	[55]
C11	Zhejiang	III	School	Reinforced concrete	4981	5	SimaPro	SimaPro	SimaPro	[22]
C12	Guangzhou	IV	School	Frame	27,066.7	10	Main materials (6 types)	Statistic	Estimation	[56]
C13	Hangzhou	III	School	Frame	20,933	5	Detailed list	Statistic	Estimation	[57]
C14	Changsha	III	School	Shear wall	2347.43	3	Revit	GBS	List	[58]
C15	Nanjing	III	School	Concrete	16,873	15	Revit	Prediction model	Estimation	[53]
C16	Chaoyang	I	Emporium	Frame	97,000	5	Detailed list	Measurement	Estimation	[59]
C17	Foshan	IV	Emporium	Frame	130,000	4	Detailed list	Measurement	Estimation	[60]
C18	Beijing	II	Factory	Steel	50,461.14	2	Main materials (10 types)	Statistic	Estimation	[61]
C19	Guangdong	IV	Hospital	Reinforced concrete	1601	7	SimaPro	SimaPro	SimaPro	[22]
C20	Chuzhou	III	Hospital	Frame	6367	4	Revit	GBS	Estimation	[62]

. In terms of the building types, 10 cases of office buildings (C1–C10), 5 cases of schools (C11–C15), 2 cases of emporiums (C16–C17), 1 case of factories (C18), and 2 cases of hospitals (C19–C20) were included. In terms of location distribution, two cases in a severe cold zone (I), three cases in a cold zone (II), eight cases in a hot-summer and cold-winter zone (III), and six cases in a hot-summer and warm-winter zone (IV) were included. In terms of the calculation methods, six cases in stage 1 applied Revit and SimaPro to consider the detailed consumption related to building materials; seven cases applied the complete list actually obtained; and seven cases only assessed the consumption of major building materials. The carbon emissions assessment in stage 2 mainly adopted four methods, namely, software simulation (11 cases), monitoring and measurement (5 cases), statistical averaging (3 cases), and predictive modeling (1 case) method. Among them, software simulation is widely used as a reliable method to assess energy consumption, and common software includes DeST-c, IBE, E-Quest, Energyplus, Designbuilder, and Green Building Studio (GBS). Because of the difficulty in obtaining data and the small proportion of carbon emissions in stage 3, estimation methods tend to be used for rapid assessment.

As shown in Figure 8, the average carbon emissions of the stock cases were counted by building type. In terms of the total life cycle carbon emissions, from lowest to highest, the order is factory (2913.69 kgCO₂/m²), school (3103.67 kgCO₂/m²), office (3669.39 kgCO₂/m²), hospital (4842.76 kgCO₂/m²), and emporium (5133.75 kgCO₂/m²). The operational stage is the key to making a difference, and the order, from lowest to highest, is school (2345.74 kgCO₂/m²), factory (2665.26 kgCO₂/m²), office (2844.19 kgCO₂/m²), hospital (4004.2 kgCO₂/m²), and emporium (4603.54 kgCO₂/m²). The operational carbon intensity of hospitals is second only to emporiums and 1.71 times that of schools and 1.41 times that of office buildings.

4. Discussion

4.1. Comparison of Inpatient Building and Stock Cases

As shown in

Table 9. Average carbon emissions of different building types and comparison.

Carbon Emission Intensity (kg CO2/m2)	Embodied Stage	Operational Stage	Demolition Stage	Total
Office	795.14	2844.19	30.21	3669.39
School	679.84	2345.74	77.56	3103.67
Emporium	482.20	4603.54	48.01	5133.75
Hospital	604.19	4004.20	229.87	4842.76
This study	474.91	9944.85	40.17	10,459.94

, the embodied and demolition stages of each building type contribute a relatively minor proportion of the carbon emissions, with the operational stage representing the largest contributor. This is directly related to the 50-year operational cycle. Office buildings and schools account for a relatively small proportion of the operational carbon emissions compared to emporiums and hospitals (78% and 76%, respectively), and embodied carbon is 22% in both cases. Emporiums and hospitals generate a large amount of operational carbon emissions, 90% and 83%, respectively, due to the significant increase in building energy consumption over long periods of operation, while the share of embodied carbon emissions is only 10%. Demolition of all types of buildings accounted for less than 2% of carbon emissions. Life cycle carbon emissions in this study were 2.03~3.33 times higher than for other buildings, with operational carbon emissions 3.5 times higher than office buildings and 2.48 times higher than hospitals. The primary reason for the discrepancy is that the indoor temperatures of inpatient buildings must be maintained within a specified range (20~26 °C) throughout the year. This is necessary to provide optimal comfort and ensure safety. The numbers of air changes in Zone 1, Zone 2, and Zone 3 were 3 ac/h, 6 ac/h, and 12 ac/h, respectively. This results in a considerable quantity of heating and cooling carbon emissions from ventilation and air changes compared to a conventional hospital building.

In addition, C19, C20, and this study researched the whole life cycle carbon emission intensity of the medical complex building, outpatient building, and inpatient building, respectively. The inpatient building had the highest carbon emissions due to long-term operation, and the medical complex had the lowest carbon emissions. The results demonstrate that despite their common classification as hospital buildings, the diverse utilization of these facilities gives rise to notable discrepancies in carbon emissions. Future research on hospital buildings should employ a clear analysis of the specific mode of operation.

4.2. Impact of Operating Modes on Carbon Emissions

As shown in Figure 9, this section discusses the carbon emissions of inpatient buildings under different modes of operation. Scenario 1 is a standard operational mode of a hospital, in which the air changes in each of the three zones are set according to the relevant standards [63]. In this study, the “normal times” operational mode was adopted. Scenario 2 is the “emergency times” operational mode, and the number of air changes in each of the three zones is set according to the requirements issued by the Chinese government during the COVID-19 pandemic [40], as shown in

Table 10. Energy consumption and carbon emissions under different operational modes.

No	Operational Scheme	Energy Consumption [kWh/(m2·Year)]	Operational Carbon Intensity (kg CO2/m2)
Scenario 1	Zone 1 = 2 ac/h, Zone 2 = 2 ac/h, Zone 3 = 2 ac/h	149.98	5725.89
This study	Zone 1 = 3 ac/h, Zone 2 = 6 ac/h, Zone 3 = 12 ac/h	270.52	9944.85
Scenario 2	Zone 1 = 12 ac/h, Zone 2 = 12 ac/h, Zone 3 = 12 ac/h	312.04	15,587.81

. The results show that the operational carbon intensity and share in Scenario 1 are basically the same as those of the outpatient building in C20, which are 5725.89 kgCO₂/m² and 5748.39 kgCO₂/m², respectively, further verifying the reliability of the calculations. The operational energy consumption in this study is 1.8 times higher than in Scenario 1, and the carbon emissions are 1.74 times higher. The operational energy consumption in Scenario 2 is 2.08 times higher than in Scenario 1, and the carbon emissions are 2.72 times higher.

4.3. Limitation

This study has some limitations that can be further discussed in future studies. Firstly, although relevant studies have shown that the energy consumption of medical devices can account for up to 25% of the energy consumed during operation [64], this study did not consider the energy consumption and carbon emissions of medical devices. It is difficult to make a detailed assessment because of the limitations of the simulation software and the lack of monitoring data, as well as the wide variation in hospital types and operating methods. Secondly, most hospitals are accompanied by a large amount of renewal and maintenance of building components and equipment during their long-term operation. A detailed assessment was not carried out in this study because of data limitations. Finally, the impact of carbon trading in hospitals was not discussed in this study. Implementing sustainability in hospitals involves multiple stages and stakeholders, including decision making, implementation, and management [65].

With the promotion and popularization of energy consumption and carbon emissions data collection technologies in the future, more energy consumption and carbon emissions data for hospital buildings can be further obtained. Using this as a basis for exploring the carbon emission characteristics of buildings in different climate zones and countries will be of great significance in understanding the current situation, challenges, and trends in energy conservation and carbon reduction in hospital buildings in China.

5. Conclusions

This study assessed, in detail, the whole life cycle carbon emissions of an inpatient building in China using BIM and LCA and conducted a comparative study based on a collection of 20 cases from other public buildings in China. The following conclusions were obtained:

• The carbon intensity of the inpatient building was 10,459.94 kgCO₂/m², of which 94.68% was operational carbon emissions, 4.54% was embodied carbon emissions, and only 0.38% was demolition carbon emissions. HVAC, equipment, and lighting were the largest contributors to carbon emissions, accounting for 52.57%, 27.85%, and 10.11%, respectively. HRB400 steel and C30 concrete were the two building materials with the largest carbon emissions.
• By comparing the life cycle carbon emissions of office buildings, schools, emporiums, factories, and hospitals, the most significant differences were found in the operational stage. Regarding operational carbon intensity, hospitals were second only to emporiums, with 1.71 and 1.41 times the carbon intensity of schools and office buildings, respectively. The inpatient building was 3 and 1.7 times that of the medical complex and the outpatient building, respectively, and although all three were part of the hospital, the different operating modes resulted in significant differences in carbon emissions.
• This study discussed the differences in energy consumption and carbon emissions of the inpatient building under the following three scenarios: standard operation (Scenario 1), “normal times” operation (this study), and “emergency times” operation (Scenario 2). The energy consumption and carbon emissions in Scenario 2 were 2.08 and 2.72 times greater than those in Scenario 1, and those in this study were 1.8 and 1.74 times greater than those in Scenario 1.

This study provides a calculation method and data reference for related scholars to assess the carbon emissions of hospital buildings in China. Hospitals generate a large amount of carbon emissions from HVAC, equipment, and lighting due to the use of 24/7 services to ensure patient comfort and health. Hospital operators should make more efforts in these three aspects by carrying out low-carbon renovations (improving thermal insulation, replacing smart lighting, etc.), adopting energy management contracts, and utilizing renewable energy sources. Future research will analyze the operational characteristics of hospitals in different regions of China, and study the green and low-carbon pathways applicable to different scenarios in hospitals.