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Geothermal energy is one of the most potential renewable energy resources. How to efficiently extract and utilize geothermal energy has been a worldwide hot topic. Co-axial closed-loop geothermal system is a novel method using a continuously closed wellbore without water exchange with. It is more suitable for reservoirs with medium or low temperature and permeability because many problems could be avoided such as lack of in situ groundwater or low infectivity of the reservoir. Many companies and research institutes have applied closed-loop geothermal system in building heating engineering and some fine results have been gained. However, in practical engineering construction, the area of a closed-loop geothermal system heating system is a very important parameter. It directly determines the cost accounting and initial design of the project. Accurate and reliable estimation of heating capacity becomes very important. In this study, a wellbore–reservoir coupling model is established, which is calibrated using measured data from a short-term field trial operation. We have carried out mixed convective–conductive fluid-flow modeling using a wellbore flow model for TOUGH2 called T2Well to investigate the heat extraction performance of closed-loop geothermal system. The system evolution and the effect of flow rate and injection temperature on heat production performance are discussed. The result shows that the intermittent production cycles are more beneficial for heat extraction and system maintenance, and the temperature recovery between two heating seasons is enough to maintain system heating. And we can calculate that a geothermal well can ensure heating of buildings of 10,000–20,000 m2 and the heating area of intermittent operation is 4000 m2 more than continuous operation. Besides, the sensitivity analysis of parameters is also carried out.

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The sustainability of the ecological environment has been greatly threatened. Based on carbon emissions and combined with the panel data of 30 provinces in China from 2003 to 2020, this paper studied the various mechanisms of industrial structure optimization and population agglomeration on carbon emissions. The fixed effect model, panel threshold model and spatial spillover model are used to study the direct and indirect effects of industrial structure optimization and population agglomeration on carbon emissions, and the robustness of the results is tested in various ways. In terms of direct effects, the industrial structure optimization has a significant negative effect on carbon emissions, and the significance level is 1%. Population agglomeration has a significant positive effect on carbon emissions, with a significance level of 1%. In terms of indirect effects, 1) by adding the cross term of industrial structure optimization and population agglomeration, it is proved that population agglomeration can promote the carbon emission reduction effect of industrial structure optimization. 2) Population agglomeration was used as the threshold variable to verify the interval effect of industrial structure optimization on carbon emission reduction. The results show that the industrial structure optimization has a double threshold effect of population agglomeration on carbon emissions, and the threshold values are 2.1137 and 5.9263, respectively. And the larger the population agglomeration interval, the weaker the inhibition effect of industrial structure optimization on carbon emissions. 3) The industrial structure optimization, population agglomeration and carbon emissions have significant spatial spillover effects. The industrial structure optimization in neighboring areas has a significant inhibitory effect on carbon emissions, and the population agglomeration in neighboring areas has a significant promoting effect on carbon emissions.

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