Holistic Sustainability Assessment of Solar Ground Source Heat Pump Systems: Integrating Life Cycle Assessment, Carbon Emissions and Emergy Analyses

Abstract

In order to explore the increase in the environmental benefits of solar ground source heat pump (SGSHP) systems, this study assesses the environmental benefits of SGSHPs through a comprehensive sustainability evaluation, integrating life cycle assessment, carbon emission analysis, and emergy analysis based on a real project in Tianjin (39.13° N, 117.2° E). By comparing an SGSHP with the conventional GSHP system, improvements in sustainability performance are quantified. The analysis reveals that the SGSHP system has a full-cycle EI16 of 1.88 × 10³, which is 15% higher than the GSHP value of 1.63 × 10³. The SGSHP demonstrates a significant advantage in terms of carbon emissions at all stages, with an overall carbon emission of 31,671 kgCO₂-eq, which is a reduction of about 9.4% compared to the 34,955 kgCO₂-eq of the conventional GSHP system. The emergy conversion rate of SGSHP is 3.58 × 10³, which is 16.23% higher than that of GSHP. This shows that the system with the addition of solar energy is able to convert raw energy into useful heat or cooling energy more efficiently, reducing emergy wastage and making it operate more efficiently, with emergy saving and environmental advantages. The SGSHP system has an ESI value of 1.12, indicating that it is in a developmental or intermediate stage, with significant potential for sustainable economic contributions. In contrast, the GSHP system, with an ESI value of 0.98, demonstrates that it is not sustainable over the long term. By using a comprehensive environmental assessment framework and comparative data analysis, this study aims to better understand the SGSHP system’s performance in energy use, carbon emissions, and ecological impact, providing a scientific foundation for its wider adoption.

1. Introduction

As the global demand for sustainable energy continues to rise, solar ground source heat pump (SGSHP) systems have garnered significant attention as an efficient renewable energy technology [1,2]. These systems integrate the benefits of solar energy and ground source heat pumps (GSHPs), not only providing comfortable indoor temperatures but also substantially reducing reliance on conventional energy sources [3,4].

Research on SGSHPs is extensive. Manesh et al. [5] introduced a new PVT-HP configuration with a cascading cycle, analyzing its thermal, energy, economic, and environmental performance. Their results showed an 11.8% higher coefficient of performance (COP) compared to traditional systems, with lower emissions. Zhang et al. [6] examined the thermal performance of dual independent loop borehole heat exchangers in SGSHP systems and discovered that, over a 7.7-day operation period, the average COP of the SGSHP system was 12% greater than that of the single U-tube borehole system. Meng et al. [7] proposed an SGSHP system that utilizes return water from district heating networks as supplementary heating. In this coupled system, the soil temperature decreased by only 0.16 °C, in contrast to reductions of 8% and 9.8% observed in the series and parallel systems, respectively. Ren et al. [8] introduced an optimization design and scheduling approach for a combined heating and cooling SGSHP system, utilizing a two-layer optimization model. Their findings showed improvements in various metrics, such as reductions in carbon emissions, primary energy consumption, and thermal waste.

Figure 1 presents the research keywords related to SGSHP systems over the past decade. It is evident that, following in-depth theoretical and experimental studies on the key components of SGSHP systems, research institutions worldwide are gradually shifting their focus towards the environmental benefits of these systems [9,10,11].

Life cycle assessment (LCA) is an essential tool for evaluating environmental benefits, yet current studies mainly concentrate on individual systems. For example, Lunardi et al. [12] conducted an environmental analysis of monocrystalline solar modules. The environmental benefits of the system were explored. Eskew et al. [13] quantified the environmental impact of a planned rooftop photovoltaic system at Bangkok University in Thailand, revealing a climate change impact of 0.079 kgCO₂-eq/kWh over its entire life cycle. Ren et al. [14] combined system dynamics modeling with LCA and life cycle cost (LCC) analysis to evaluate the cumulative energy demand, carbon emissions, water footprint, and life cycle costs of both grid-connected and stand-alone residential photovoltaic systems. The results showed that the optimized configuration enhanced life cycle environmental savings by 64.6%, while decreasing economic savings by 68.4%. In addition to individual solar systems, several environmental benefit evaluations have focused on GSHP systems. Violante et al. [15] conducted a comparison of life cycle assessments between GSHP and air-source heat pump systems. Their analysis revealed that GSHP systems were typically more energy-efficient and resulted in a lower long-term environmental impact compared to conventional air conditioning systems. Shimada et al. [16] assessed the environmental benefits of a tropical Asian GSHP system in Bangkok, Thailand, showing that the system’s energy savings reduced greenhouse gas (GHG) emissions by 8.8% over its life cycle compared to air-source heat pumps. Smith et al. [17] used LCA to examine the medium- to long-term sustainability effects of a GSHP system in New Jersey, USA, emphasizing its performance within the state’s electricity generation fuel mix. The findings indicated that combining the GSHP system with electric heating and cooling significantly reduced environmental emissions. While many studies have focused on the LCA of individual solar collectors or GSHP systems, no research has yet been conducted on the LCA of SGSHP systems.

As global attention to emission reduction targets intensifies, an increasing number of studies are integrating LCA with carbon emission research to more accurately quantify the carbon emissions of different energy systems, building facilities, or technologies over their entire life cycle. This approach enables researchers to identify potential emission reduction opportunities, providing data support and guiding technological improvements to achieve low-carbon economy goals [18]. Yang et al. [19] explored the interconnections between energy, cost, and carbon emissions in combined cooling, heating, and power (CCHP) systems. Their analysis revealed that the unit exergy carbon emissions under the system’s design conditions were 2.3780 kgCO₂-eq. Zhao et al. [20] conducted a carbon emission analysis of solar-coupled systems, concluding that systems with solar collectors significantly reduced carbon emissions. Liu et al. [21] performed an environmental benefit analysis of solar-coupled air-source heat pump systems, providing reliable optimization results that achieved the lowest carbon emissions for heating systems. Wang et al. [22] studied the integration of photovoltaic thermal panels as auxiliary heat sources with GSHP systems, evaluating the system’s energy efficiency, economic feasibility, and environmental benefits. The results indicated that the coupled system reduced life cycle costs by up to 40% and cut CO₂ emissions by more than 50%. Garber et al. [23] conducted a life cycle cost assessment of GSHP systems, investigating the carbon emissions associated with these systems. The findings highlighted significant environmental benefits of GSHP systems compared to traditional heating, ventilation, and air conditioning (HVAC) systems. These studies underscore the critical importance of carbon emission reductions in addressing climate change, protecting the environment, and achieving sustainable development goals.

However, in addition to the conventional environmental impact assessment methods mentioned above, emergy analysis has emerged as an important evaluation tool. The significance of emergy analysis lies in its ability to assess the energy efficiency of systems or processes, helping to identify resource waste and optimize energy use. By quantifying the relationship between energy inputs and outputs, emergy analysis provides a scientific basis for reducing energy consumption and improving system efficiency, while also contributing to environmental impact reduction and promoting sustainable development [24]. It plays a crucial role in the design and improvement of energy systems and in the promotion of energy conservation and emission reduction, with significant implications for addressing climate change and resource scarcity [25]. Ren et al. [26] employed emergy analysis to compare ten power generation systems using two different emergy indices. The results indicated that wind and concentrated solar power generation systems generally exhibited better sustainability compared to integrated gasification combined cycle power generation systems. Lin et al. [27] designed an innovative trigeneration system that integrates power generation, cooling, and desalination. They employed emergy analysis to assess the system’s performance from both economic and environmental viewpoints. The findings showed an energy efficiency of 0.70, an EIR of 0.43, an ELR of 1.76, and an ESI of 1.79, highlighting the system’s robust sustainability attributes. Xu et al. [28] conducted a sustainability assessment of a novel coupled system based on LCA and emergy analysis. The results showed a total emergy consumption of 8.53 × 10³, with the emergy sustainability index fluctuating between 3.04 and 4.45, demonstrating good sustainability performance. The aforementioned literature suggests that a single evaluation method may not comprehensively reflect the actual sustainability when assessing environmental impacts. The importance of combining LCA, carbon emission evaluation, and emergy analysis lies in their ability to provide a holistic evaluation of a system or product’s energy efficiency and environmental impact across different stages. LCA helps us to analyze resource consumption and pollution emissions throughout the process, and carbon emission evaluation focuses on GHG emissions, while emergy analysis optimizes system efficiency from the perspective of energy input and output [29]. The integration of these three approaches provides a scientific basis for reducing carbon emissions, improving energy utilization efficiency, and advancing sustainable development, facilitating the formulation of more effective environmental protection and energy management strategies.

This study aims to conduct a multifaceted sustainability assessment of the SGSHP system by integrating LCA, carbon emission analysis, and emergy. By comparing the environmental benefits of the SGSHP with those of the conventional GSHP system, this study seeks to quantify the specific improvements in sustainability performance. Through comparative analysis, we aim to gain a deeper understanding of the performance of solar assist systems in terms of energy consumption, carbon emissions, and ecological impact, thereby providing a scientific basis for their further promotion, improvement, and application.

2. System Overview and Analysis Process

2.1. System Flowcharts

Figure 2 presents the schematic of the coupled system, showcasing essential components, including the solar collector, thermal storage tank, plate heat exchanger, ground-coupled pipes, and heat pump.

In the cooling season, the system transfers heat to the soil through the shallow ground pipes. Operating in cooling mode, the heat pump, source-side pump, load-side pump, and collector pump are activated. Valves 1–3 are open, while valves 4, 5, and 6 remain closed.

During the transitional season, the solar collector and thermal storage tank work together to transfer solar energy to the soil via the shallow ground pipes, thereby storing thermal energy. In this thermal storage mode, the solar collector, thermal storage tank, and plate heat exchanger are activated, while the heat pump and source-side pump are deactivated. Valves 4–8 are open, while valves 1–3 are closed.

In the heating season, the system extracts heat from the soil through the shallow ground pipes. Heat captured by the solar collector is stored in the thermal storage tank and then transferred via the plate heat exchanger to raise the source-side water temperature for the heat pump. The heat pump then supplies heating to end users. Operating in heating mode, the heat pump runs, all pumps are activated, and valves 1–3 and 5–8 are open, while valve 4 remains closed.

This study examines two operational modes in distinct simulation scenarios: Mode A (SGSHP), where valves 4 and 9 are closed, allowing both the solar collector and GSHP modules to operate concurrently during the transitional season, and Mode B, where valves 4–8 are closed and only the GSHP system operates.

2.2. System Layout

The coupled system model is based on a real shallow geothermal and solar energy project in Tianjin. The air conditioning system is designed to meet a cooling load of 228.3 kW and a heating load of 157.8 kW. The shallow geothermal system consists of 100 vertical boreholes, each 120 m deep, spaced 5 m apart. Each borehole is fitted with 25 mm diameter double-U pipes, connected by high-efficiency horizontal loops arranged in series. The system also includes a screw-type GSHP to ensure efficient and reliable performance.

The SHSHP system is modeled in Java, with the component selection and parameter configuration based on the system’s actual on-site operation. The system setup is outlined in

Table 1. SGSHP system model parameter configurations [30].

Parameter	Unit	Value
Area of a single collector	m2	3
Soil density	kg/m3	1980
Collectors number	n	12
Soil initial	°C	15
Pump condenser water flow	m3/h	45
Soil specific heat capacity	kJ/(kg⋅°C)	2.2
Pump evaporator water flow	m3/h	65
Soil thermal conductivity	W/(m °C)	1.31
Pump heating capacity	kW	276.3
Pump heating power	kW	60.6
Pump number	n	2
Water tank volume	m3	27

.

For the purpose of simplifying the system analysis, the model is streamlined during simulation based on the following assumptions [11,24,28]: (1) internal system losses, such as heat transfer through pipes and electrical losses, are neglected; (2) the system operates flawlessly, without accounting for maintenance or downtime effects.

2.3. Analysis Process

Figure 3 is the flowchart of the analysis conducted. The modeling and sustainability assessment focus on the actual on-site solar geothermal heat pump project, with a comparative analysis of Model A and Model B. First, a thorough evaluation of the system’s environmental impacts over its entire life cycle is performed using LCA and carbon emission methods. Finally, a comprehensive sustainability assessment is conducted through emergy analysis.

3. Modeling

3.1. Life Cycle Assessment Model

3.1.1. The Goal and Scope Definition

The environmental impact assessment of integrated energy systems requires systematic analysis of ecological consequences throughout their operational lifespan [31]. The methodological framework of LCA is schematically presented in Figure 4, with corresponding operational boundaries for the integrated system detailed in Figure 5. The operational inputs are classified into material resources and energy carriers, while the system outputs comprise electrical energy production accompanied by diverse environmental emissions and energy dissipation. This analytical framework divides the system’s life cycle into four distinct phases: construction, operation, maintenance, and recovery. The bill of materials for the SGSHP system is shown in Appendix A.

3.1.2. The Life Cycle Impact Assessment

The Eco-indicator 16 (EI16) is adopted as the overall metric. The impact categories are divided into 22 specific indicators. The EI16 calculation formula is as follows [32]:

$$EI16={\displaystyle \sum _{\mathrm{d}}{\displaystyle \sum _{\mathrm{r}}d{m}_{\mathrm{br}}LC{I}_{\mathrm{b}}}}{w}_{\mathrm{d}}{n}_{\mathrm{dr}}$$

(1)

where d and r are the damage and impact categories; $w_{\mathrm{d}}$ and $n_{\mathrm{dr}}$ are the weight and normalization factors; $d{m}_{\mathrm{br}}$ represents the damage factor; $LC{I}_{\mathrm{b}}$ represents the chemical of the inventory.

3.2. Carbon Emission Analysis Model

3.2.1. Carbon Emission Boundary

Carbon emissions, a key indicator of human-induced greenhouse gas (GHG) contributions, play a crucial role in the environmental impact assessment of energy systems. Within the framework of LCA, carbon emission analysis quantifies the total CO₂ equivalent emissions across the entire life cycle of a system, encompassing both direct emissions from operation and indirect emissions from upstream and downstream processes, such as raw material production, transportation, and waste treatment [33]. The current GHG accounting methodology adheres to the IPCC 2006 guidelines and categorizes emissions into three levels: direct emissions from system operations, indirect emissions from purchased energy production, and value-chain emissions. The primary drivers of carbon emissions in coupled energy systems are the energy conversion efficiency during operation, the carbon intensity of the feedstock supply chain, emission factors associated with specific technical maintenance activities, and waste management strategies in the end-of-life phase.

Figure 6 outlines the carbon emission boundaries considered in this study. It distinguishes between direct and indirect carbon emissions. The direct carbon emissions mainly include emissions during the construction, use, and maintenance of the SGSHP system. The indirect carbon emissions account for emissions associated with the consumption of electricity, diesel fuel, and other resources.

3.2.2. Carbon Emission Indicators

The system’s carbon emissions are divided into four distinct phases: construction, operation, maintenance, and recovery. The calculation is as follows [34]:

$$E_{total}={\displaystyle \sum _{i=1}^{n}Ei}=E_{con}+E_{oper}+E_{main}+E_{rec}$$

(2)

where E_total is the life cycle carbon emissions; E_con is the construction carbon emissions; E_oper is the operation carbon emissions; E_main is the maintenance carbon emissions; E_rec is the recovery carbon emissions.

Table 2. The carbon emission factors [35].

Material	Carbon Emission Factor (kgCO2/kg)
Natural rubber	2.5
Plastic	2.5
Coke	1.9
Carbon steel	6.83
Aluminum	8.6
Ferrosilicon	5.5
Copper	3.5
Glass	0.8
Cooling water	0.0003

shows the carbon emission factors of common materials.

The carbon emissions during the construction phase can be determined using the following calculation [36]:

$$E_{con}={\displaystyle {\sum }_{i=1}^n{M}_{ci}}\times C_i+{\displaystyle {\sum }_{j=1}^m{M}_{cj}}\times G_j$$

(3)

where M_ci denotes the mass of raw materials needed; C_i is the carbon emission factor of the raw material; M_cj refers to the amount of greenhouse gases emitted during raw material production; G_j represents the carbon dioxide equivalent of the GHG.

The formula for carbon emissions during the operation and maintenance phase is as follows:

$$E_U=E_{oper}+E_{main}={\displaystyle {\sum }_{i=1}^n{M}_{Ui}}\times C_i+T\times C_i$$

(4)

M_Ui is the operation energy consumed; T denotes the system’s average lifespan; C_i is the carbon the emission factor.

The carbon emissions during the recovery phase are as follows:

$$E_{dis}={\displaystyle {\sum }_{i=1}^n{M}_{di}}\times C_i-{\displaystyle {\sum }_{j=1}^m(1-{\alpha }_j)\times M_{dj}}\times C_j$$

(5)

M_di is the energy consumed during the recycling of metal materials, while C_i denotes the carbon emission factor; ${\alpha }_j$ represents the proportion of GHG emissions during the recycling process compared to the emissions from the construction phase; M_dj refers to the mass of metal materials recycled; C_j corresponds to the carbon emission factor.

3.3. Emergy Analysis Model

3.3.1. Emergy Analysis Boundary

Emergy represents the total energy, in various forms, contained within a system, which is then converted into solar emergy through specific energy conversion rates [37]. By applying emergy analysis, one can comprehensively evaluate the ecological, economic, and overall sustainability performance of the system. Quantitative evaluation of the resource utilization efficiency, environmental sustainability, and ecological advantages of solar-powered ground source heat pumps can prove that they have lower nonrenewable resource dependence and higher long-term sustainability compared with traditional energy systems. The key steps in conducting emergy analysis are depicted in Figure 7.

Since the maintenance phase has a negligible impact on the total emergy, the system is divided into three primary phases: construction, usage, and recycling. Figure 8 depicts the boundary delineation, along with the resource inputs and outputs throughout the system’s life cycle. By assessing the resources collected and used in each phase, the system’s energy output can be calculated using the energy conversion rate.

In emergy analysis, resource flows across the entire life cycle of a system are classified into three categories—renewable resources (R), nonrenewable resources (N), and purchased resources (F)—based on the defined system boundary. The inflows and outflows of emergy within the coupled system are illustrated in Figure 9.

3.3.2. Emergy Indicators

The emergy indicators encompass several essential metrics, as shown in

Table 3. Emergy indicators.

Emergy Indicators	Interpretation
EIR	Emergy investment ratio
ELR	Environmental loading ratio
ESI	Emergy sustainability index
EYR	Emergy yield ratio
Tr	Emergy conversion rate

.

The Tr of the system can be determined using the following calculation [38]:

$$\mathrm{Tr}={\displaystyle \frac{\mathrm{TEM}}{Q_{\mathrm{out}}}}$$

(6)

$$\mathrm{TEM}=\mathrm{R}+\mathrm{N}+\mathrm{F}$$

(7)

TEM represents the total emergy input.

The EYR can be determined using the following calculation:

$$\mathrm{EYR}={\displaystyle \frac{\mathrm{TEM}}{\mathrm{F}}}$$

(8)

The ELR can be determined using the following formula:

$$\mathrm{ELR}={\displaystyle \frac{\mathrm{N}+\mathrm{F}}{\mathrm{R}}}$$

(9)

A higher EIR indicates a greater degree of economic development within the system, while a lower EIR suggests a weaker economic development and a stronger reliance on environmental resources. The EIR is expressed as follows:

$$\mathrm{EIR}={\displaystyle \frac{\mathrm{F}}{\mathrm{N}+\mathrm{R}}}$$

(10)

The ESI can be calculated as follows:

$$\mathrm{ESI}={\displaystyle \frac{\mathrm{EYR}}{\mathrm{ELR}}}$$

(11)

The ESI serves as a comprehensive indicator that captures the system’s environmental impact and the sustainability of its resource use. It shows a positive relationship with the EYR and a negative one with the ELR. A value of ESI below 1 signals long-term unsustainability. An ESI ranging from 1 to 5 suggests that the system may contribute sustainably to the economy in the medium term or during its development phase, whereas an ESI exceeding 5 indicates that the system is likely to be sustainable over the long term.

3.4. Model Validation

The mean absolute error (MAE) is a widely used metric for error analysis. It quantifies the discrepancy between two data sets and is commonly employed to assess the accuracy of a model. And it can be calculated as follows:

$$MAE={\displaystyle \frac{1}{n}}{\displaystyle \sum \left|T_s-T_m\right|}$$

(12)

T_s represents the simulated value obtained using the numerical calculation of the model, °C: T_m is the monitored value of the project works, °C; n is the number of temperature values output from the simulation.

Soil temperature measurements during the heating season were compared with model predictions. Figure 10 shows the results of soil temperature comparison for 12 months. Under the same boundary conditions, the model and field measurements showed similar soil temperature trends with a MAE value of −0.09 °C and a maximum deviation of 4.42%. These results validate the accuracy of the developed system model and provide a reliable basis for subsequent discussions and analyses.

4. Results and Discussion

This section, based on the comprehensive sustainability assessment, presents a comparative analysis of SGSHP and conventional GSHP systems in terms of energy utilization, carbon emissions, and ecological impacts.

4.1. Life Cycle Assessment

4.1.1. Overall Life Cycle Assessment

Figure 11 compares the environmental impacts of SGSHP (Mode A) and GSHP (Mode B) across their full life cycles. Significant differences emerge at different stages. In the construction phase, Mode A shows a higher load (37.64%) than Mode B (33.63%), mainly due to the energy-intensive production of vacuum heat pipes requiring high-purity glass.

In the operational phase, the trend reverses, with Mode B (37.55%) exceeding Mode A (34.25%). Benefiting from solar collectors, Mode A reduces the GSHP operating hours by 27%, cutting CO₂ equivalent emissions to 2.1 × 10⁴ kg/year, 19.2% lower than those in Mode B. During maintenance, the overall loads are close (4.22% vs. 4.74%), yet the pollution sources diverge. Mode B requires frequent underground heat exchanger cleaning, which increases chlorinated organic emissions and raises human toxicity potential by 15%. In the recovery phase, the environmental loads remain similar (23.88% vs. 24.08%), but the dominant pollutants differ. Mode A generates more silica dust during glass recycling, increasing smog potential, while Mode B’s PE pipe pyrolysis produces more dioxins. These differences suggest distinct optimization paths: improving dust collection for Mode A and refining pyrolysis control for Mode B.

Overall, the results reveal clear trade-offs between solar-assisted and conventional GSHP systems across life cycle stages. More importantly, this study establishes a methodological framework that combines environmental load allocation with pollution-specific impact characterization, providing a comprehensive basis for technology optimization and sustainable energy system design.

4.1.2. Percentage of Life Cycle Evaluation Indicators

Based on a comprehensive LCA with 22 impact indicators, notable environmental differences are observed between SGSHP (Mode A) and GSHP (Mode B). These indicators are grouped into three categories: human health, ecosystem damage, and resource depletion. Figure 12 and Figure 13 summarize their distribution and results.

In the construction phase, SGSHP exhibits higher human health impacts from global warming (1.80 × 10² DALY), 43% above GSHP (1.26 × 10² DALY), due to high-purity silicon and silver extraction for flat-plate collectors. Its mineral resource scarcity reaches USD 5.60 × 10², twice that of GSHP, reflecting resource-intensive manufacturing. During operation, solar assistance lowers fossil resource scarcity to USD 7.26 × 10, 30% below that of GSHP, though ozone depletion (1.16 × 10² DALY), and other emissions rise slightly due to grid compensation. In the recycling phase, the SGSHP faces greater ecological stress. The land ecotoxicity reaches 3.77 species·year (36% higher than that of GSHP), while the freshwater consumption and marine eutrophication increase by 11% and 16%, respectively, due to heavy metal leakage and acidic wastewater from material separation. Despite its operational benefits, the SGSHP performs worse in indicators such as terrestrial acidification and aquatic toxicity, linked to collector recycling inefficiencies. Regarding human health, silicon-based collector manufacturing raises the carcinogenic toxicity by 21%, mainly from fluoride emissions and lead solder. Ecologically, SGSHP’s burdens concentrate in glass–metal separation and rare-metal mining, whereas GSHP’s impacts are more evenly distributed across its fossil-fuel-dependent operation. The overall EI16 of SGSHP is 1.88 × 10³, 15% higher than that of GSHP (1.63 × 10³), highlighting material input and end-of-life as key bottlenecks.

Improving SGSHP sustainability should prioritize lightweight collectors, rare-earth substitutes, and closed-loop recycling. Strategies include optimizing water use, monitoring soil thermal balance, protecting vegetation during construction, and lowering outlet water temperatures to enhance efficiency.

In conclusion, the SGSHP demonstrates operational advantages in fossil energy reduction but suffers higher impacts in construction and recycling stages. This study not only quantifies these trade-offs but also provides a methodological contribution by integrating life cycle impact allocation with pollutant-specific indicators, offering a comprehensive framework for sustainable energy system optimization.

4.2. Carbon Emission Analysis

4.2.1. Overall Carbon Emission Analysis

Figure 14 compares the carbon emissions of the SGSHP with those of the conventional GSHP system across different stages. The SGSHP demonstrates a clear advantage in carbon emissions at all stages, with total carbon emissions of 31,671 kgCO₂-eq, which are approximately 9.4% lower than the conventional ground-source heat pump system’s 34,955 kgCO₂-eq.

In the construction phase, the coupled system emits 13,576 kgCO₂-eq, exceeding the heat pump system’s 9606 kgCO₂-eq, indicating that additional resources or equipment are required for its installation, leading to higher emissions. Conversely, during operation, the coupled system’s emissions drop to 8796 kgCO₂-eq, significantly lower than the heat pump system’s 19,305 kgCO₂-eq, reflecting superior performance. This improvement stems from the solar collectors’ ability to capture free solar radiation, transferring heat to the underground source to boost system efficiency. The resulting higher operational efficiency enhances renewable energy utilization and reduces reliance on external electricity. During maintenance, the coupled system produces 4638 kgCO₂-eq, slightly above the heat pump system’s 3247 kgCO₂-eq, indicating negligible differences in this stage. In the recovery phase, the SGSHP emissions are 4661 kgCO₂-eq, compared to 2797 kgCO₂-eq for the heat pump system. Overall, the SGSHP’s total life cycle carbon emissions are 31,671 kgCO₂-eq, 9.2% lower than the GSHP’s 34,955 kgCO₂-eq.

4.2.2. Percentage of Carbon Emissions by Phase

Figure 15 shows the detailed results of carbon emissions for the two scenarios. In Scenario A (SGSHP), the construction phase dominates with 42.87% of the total carbon emissions. In the construction process, the largest share of carbon emissions is in building the underground pipeline system, accounting for 37.12%. This is mainly due to the fact that the construction and installation process of underground pipelines involves a large amount of earthworks, production and transportation of pipeline materials, and pipeline laying. In contrast, in Scenario B, the operation phase dominates, mainly because the carbon emissions from its electricity consumption occupy the most important part of the system life cycle, especially in the case of relying on traditional energy sources for power supply, and it is difficult to avoid the carbon emissions generated during the system operation.

Overall, the SGSHP system achieves lower carbon emissions than conventional GSHP systems by harnessing solar energy, thereby reducing reliance on electricity and fossil fuels. Its reduced carbon footprint is further supported by efficient heat exchange and energy recovery during operation. The system consistently demonstrates lower emissions across all life cycle stages, underscoring its environmental advantages. With continued optimization in design and operation, the SGSHP system has the potential to achieve an improved balance between carbon reduction and economic performance.

4.3. Emergy Analysis

4.3.1. Overall Emergy Analysis

Figure 16 and Figure 17 illustrate the distribution of emergy inputs for both systems. As shown in Figure 18, the construction phase of the SGSHP system contributes the largest share of emergy inputs, primarily from raw materials, comprising 59.9% of the total emergy. The operational phase follows as the second largest contributor, representing 21.1% of the overall emergy input. In contrast, the GSHP system shows that the construction phase raw material emergy input is the highest (58.1%), rather than the operational phase (21.5%). This occurs because, during its operation, the GSHP system generally delivers heating and cooling by efficiently utilizing geothermal energy and facilitating heat exchange. This aligns with the sustainable development definition of emergy analysis, which supports the long-term sustainability of the system.

Moreover, the emergy required for maintenance materials and transportation in both systems accounts for less than 10% of the total emergy. On the other hand, the contributions from construction and labor are even smaller, with values of 1.2% and 0.6%, respectively, underscoring their limited impact on the overall emergy performance of the system. It is evident that the total emergy input for SGSHP is 8.83 × 10¹³, with a total emergy output of 2.84 × 10¹¹, while the GSHP system has a total emergy consumption of 7.49 × 10¹³ and a total emergy output of 1.68 × 10¹¹. In comparison, although the SGSHP system has a 17.89% higher emergy input due to higher construction consumption, it delivers 69.05% more emergy output than the GSHP system.

4.3.2. Percentage of Emergy by Phase

Due to notable differences in emergy inputs during the operational phase, a detailed emergy distribution analysis was conducted. Figure 18 and Figure 19 show the life cycle emergy consumption for both the SGSHP and GSHP. For the SGSHP, construction accounts for 62.3% and operation 34.0% of total emergy, while for the GSHP the shares are 60.6% and 35.8%, respectively. Both systems demand substantial materials and energy during construction, though the GSHP shows slightly higher operational emergy input (0.5%), reflecting its lower reliance on solar energy.

In SGSHP’s operational phase, emergy is mainly distributed among operational materials (21.4%), maintenance materials (7.9%), and direct inputs (4.8%). This indicates that both construction and operational phases hold potential for improving sustainability through renewable and reusable resource integration. Clean emergy use is particularly effective in reducing resource consumption and enhancing overall sustainability.

Table 4. Emergy evaluation indicators of the systems.

Evaluation Indicator	SGSHP	GSHP
TR	3.58 × 103	3.08 × 103
EYR	1.72	1.68
EIR	1.39	1.47
ELR	1.54	1.71
ESI	1.12	0.98

presents emergy evaluation indicators. The SGSHP achieves a TR of 3.58 × 10³, 16.23% higher than that of the GSHP, demonstrating more efficient conversion of raw energy into useful heating or cooling. The EIR of the SGSHP is 1.39, 5.75% lower than that of the GSHP, indicating greater environmental dependence but reduced economic intensity. The ESI for the SGSHP is 1.12, higher than the GSHP’s 0.98, suggesting that the SGSHP retains greater long-term sustainability potential despite being at a developmental stage.

In conclusion, the SGSHP offers operational energy-saving and environmental benefits but requires enhanced resource recycling to improve sustainability. Methodologically, this analysis illustrates the value of emergy-based evaluation in revealing resource dependence, efficiency, and long-term system sustainability.

5. Conclusions

This study innovatively constructs a multidimensional evaluation framework integrating LCA, carbon emission accounting, and emergy analysis, achieving for the first time a comprehensive quantitative characterization of the environmental benefits of SGSHP systems. The main findings are as follows:

(1)

The overall life cycle EI16 value for the SGSHP is 1.88 × 10³, which is 15% higher than the 1.63 × 10³ for the GSHP. This indicates that the SGSHP’s environmental cost is concentrated in the early-stage material input and end-of-life recovery bottlenecks, while the GSHP’s environmental load is more evenly distributed across the operational phase, with reliance on fossil energy. To enhance the sustainability of the SGSHP in the future, the focus should be on optimizing the system through lightweight solar collectors, rare earth alternative materials, and closed-loop recycling technologies.

(2)

The SGSHP system demonstrates a clear advantage in carbon emission reduction across all stages, with a total carbon emission of 31,671 kgCO₂-eq, which is approximately 9.4% lower than the 34,955 kgCO₂-eq of the traditional GSHP system. The SGSHP system has a better balance between carbon reduction and economy.

(3)

The emergy conversion ratio (TR) for the SGSHP is 3.58 × 10³, which is 16.23% higher than that of the GSHP system. The addition of solar energy enables the system to more efficiently convert raw energy into useful thermal or cooling energy, thus reducing energy waste and making it operate more efficiently, offering significant energy-saving and environmental benefits.

(4)

The emergy sustainability index (ESI) for the SGSHP is 1.12, indicating that the system is in a mid-term or developmental stage, with considerable potential for sustainable economic contributions. In contrast, the GSHP system has an ESI of 0.98, suggesting that it is unsustainable in the long run.