Using System Dynamics to Analyze Influencing Factors and Emission Reduction Potential of Geothermal Resources Development and Utilization in Tianjin
Abstract
:1. Introduction
1.1. Contextual Background
1.2. Literature Review
1.3. Research Objectives
2. Study Area, Historical Background Related to Geothermal Development, and Status
2.1. Study Area
2.2. History and Current Status of Geothermal Energy in Tianjin
2.3. Influence Mechanism of Geothermal Development in Tianjin
3. Methodology
3.1. SD Model Boundaries
3.2. A Framework Based on the System Dynamics Model
3.2.1. Causal Loop Diagrams (CLD) Analysis
3.2.2. Socioeconomic Subsystem
3.2.3. Geothermal Resource Subsystem
3.2.4. Environment Subsystem
3.2.5. Policy and Technology Subsystem
3.3. Model Tests
3.3.1. History Test
3.3.2. Sensitivity Test
3.4. Scenario Setting and Parameter Assumptions
3.4.1. Scenario Setting
3.4.2. Parameter Assumptions
4. Results
4.1. Sensitivity Analysis Results and Main Influencing Factors
4.2. Comparative Analysis of Multiscenario Results
4.2.1. Multiscenario Prediction Results of GHA
4.2.2. Multiscenario Prediction Results of HRHA and SGEHA
4.2.3. Multiscenario Prediction Results of CER
5. Discussion
5.1. Improve the Policy Mechanism
5.2. Improve Economic Investment
5.3. Promote Technological Progress
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
CER | Carbon emissions reduction; |
CO2 | Carbon dioxide; |
EPDS | Economic Priority Development Scenario; |
FAI | Fixed asset investment; |
GCHP | Ground-coupled heat pumps; |
GDP | Gross domestic product; |
GHA | Geothermal heating area; |
GWHP | Groundwater heat pumps; |
HETCR | Heat exchange technology conversion rate; |
HRHA | Hydrothermal resources heating area; |
MTCR | Mining technology conversion rate; |
PGR | Population growth rate; |
PSS | Policy-Strengthening Scenario; |
SCS | Status Continuation Scenario; |
SD | System dynamics; |
SGEHA | Shallow geothermal energy heating area; |
TPS | Technological Progress Scenario; |
Nm | Minghuazhen group; |
Ng | Guantao group; |
Ed | Paleogene formation Dongying group; |
O | Paleozoic Ordovician group; |
∈ | Cambrian group; |
Jxw | Mesoproterozoic Jixian Wumishan group. |
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Thermal Reservoir | Distribution Area/km2 | Geothermal Resources/1018 J | Equivalent Standard Coal/108 J |
---|---|---|---|
Nm | 9467.44 | 260.377 | 88.843 |
Ng | 8451.97 | 126.932 | 43.308 |
Ed | 4882.85 | 39.16 | 13.362 |
O | 3548.86 | 125.372 | 42.778 |
∈ | 2753.83 | 54.734 | 18.675 |
Jxw | 3440.78 | 259.966 | 99.604 |
Scenarios | Parameters |
---|---|
Economic Priority Development Scenario (EPDS) | According to the “Fourteenth Five-Year Plan for National Economic and Social Development of Tianjin City” and the outline of the 2035 Visionary Goals, the growth rate of the GDP in Tianjin will adjust to 6% from 2021 to 2025, 4% from 2026 to 2035, 3% from 2036 to 2050, and 2% from 2051 to 2060. |
Technological Progress Scenario (TPS) | The increase in heat exchange technology conversion rate (HETCR) and mining technology conversion rate (MTCR) in Tianjin will be 5% from 2021 to 2030. After carbon peaking, the increase in HETCR and MTCR will be 2% from 2031 to 2050. In consideration of the carbon neutrality goal, the increase in HETCR and MTCR will be 1% from 2051 to 2060. |
Policy-Strengthening Scenario (PSS) | Tianjin City Territorial Spatial Master Plan (2021–2035): Tianjin’s resident population will reach 15 million in 2025. The planned population of Tianjin City in 2035 is controlled at about 20 million. Under the above the EPDS and TPS scenarios, the proportion of the urban population in 2035 will be 85%. |
Year | 2025 | 2030 | 2060 | |
---|---|---|---|---|
Baseline (104 m2) | GHA | 5413.13 | 6688.92 | 18,055.1 |
HRHA | 4106.39 | 5185.24 | 15,330.9 | |
SGEHA | 1306.74 | 1503.68 | 2724.14 | |
CER | 292.43 | 361.35 | 975.38 | |
EPDS (104 m2) | GHA | 5554.8 | 7248.52 | 22,739.2 |
HRHA | 4152.85 | 5578.55 | 19,420.6 | |
SGEHA | 1401.94 | 1670.97 | 3318.56 | |
CER | 300.08 | 391.64 | 1228.43 | |
TPS (104 m2) | GHA | 5472.35 | 6859.92 | 18,952.5 |
HRHA | 4153.15 | 5316.85 | 16,087.1 | |
SGEHA | 1319.20 | 1543.07 | 2865.41 | |
CER | 295.63 | 370.59 | 1023.86 | |
PSS (104 m2) | GHA | 5850.49 | 9101.01 | 32,031.4 |
HRHA | 4418.18 | 7318.47 | 28,362 | |
SGEHA | 1432.31 | 1782.54 | 3369.37 | |
CER | 316.06 | 491.66 | 1730.41 |
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Yuan, R.; Wang, G.; Xu, B.; Zhao, S.; Zhu, X.; Zhang, W.; Lin, W.; Shi, H. Using System Dynamics to Analyze Influencing Factors and Emission Reduction Potential of Geothermal Resources Development and Utilization in Tianjin. Sustainability 2025, 17, 4005. https://doi.org/10.3390/su17094005
Yuan R, Wang G, Xu B, Zhao S, Zhu X, Zhang W, Lin W, Shi H. Using System Dynamics to Analyze Influencing Factors and Emission Reduction Potential of Geothermal Resources Development and Utilization in Tianjin. Sustainability. 2025; 17(9):4005. https://doi.org/10.3390/su17094005
Chicago/Turabian StyleYuan, Ruoxi, Guiling Wang, Bowen Xu, Sumin Zhao, Xi Zhu, Wei Zhang, Wenjing Lin, and Honglei Shi. 2025. "Using System Dynamics to Analyze Influencing Factors and Emission Reduction Potential of Geothermal Resources Development and Utilization in Tianjin" Sustainability 17, no. 9: 4005. https://doi.org/10.3390/su17094005
APA StyleYuan, R., Wang, G., Xu, B., Zhao, S., Zhu, X., Zhang, W., Lin, W., & Shi, H. (2025). Using System Dynamics to Analyze Influencing Factors and Emission Reduction Potential of Geothermal Resources Development and Utilization in Tianjin. Sustainability, 17(9), 4005. https://doi.org/10.3390/su17094005