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      Simulation of Carbon Emission Reduction in Power Construction Projects Using System Dynamics: A Chinese Empirical Study

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      Buildings
      MDPI AG

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          Abstract

          Power construction projects (PCPs) consume a large amount of energy and contribute significantly to carbon emissions. There is relatively little research on carbon emission reduction in PCPs, especially in predicting carbon emission reduction from a dynamic perspective. After identifying the influencing factors that promote the carbon emission reduction effect of PCPs, this study adopted a dynamic analysis method to elucidate the relationship between the variables. A quantitative carbon emission reduction system for PCPs with 51 variables was established using the system dynamics model, and the system simulation was performed using Vensim PLE software. Finally, a sensitivity analysis was conducted on four key factors: R&D investment, the prefabricated construction level, the scale of using energy-saving material, and the energy efficiency of transmission equipment. The results show that: (1) The reduction in carbon emissions from PCPs continues to increase. (2) R&D investment is the most significant factor for improving the carbon emission reduction in PCPs. (3) The value of the above four influencing factors should be increased within a reasonable range so that the four factors can work better to promote the carbon emission reduction effect of PCPs. This paper creatively proposes a dynamic prediction model for carbon emission reduction in the PCP, and the research results provide the scientific basis for government supervision and enterprise decision-making.

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          Driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods

          Anthropogenic carbon emission gives rise to a situation where global warming is becoming serious. China is paying for reducing carbon emissions. The concept of carbon curse suggests that countries rich in fossil fuels tend to be closely linked to high carbon emissions, but this is not absolute, which reminds policymakers that the policies implemented are positivelycorrelateswith carbon emission reduction. This study is also aimed at this, hoping to provide some proposals about reducing CO2 emissions to policy-makers by decomposing and analyzing the important factors. To achieve this target, this paper employs the extended the Kaya identity, combines the LMDI method to analyze the impact factors of carbon emissions in China from 1996 to 2016 and discusses the effects and causes of each factor according to the actual situation. It is found that the economic activity is the greatest driving force to promote carbon emissions, while on the contrary, energy intensity is the biggest suppressor. Optimizing industrial structure, improving the structure of energy and export-import trade and intensifying the development of clean energy can effectively restrain the growth of carbon emissions. In addition, the relative innovation point in this study is to analyze carbon emissions with the combination of electricity trading and discusses that increasing imported electricity is also a strategy to reduce carbon emissions.
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            System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China

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              Evaluating Green Technology Strategies for the Sustainable Development of Solar Power Projects: Evidence from Pakistan

              Energy is the main element for a modern lifestyle that must be considered in economically reliable and sustainable development dialogues. The financial performance of solar power projects has become the main issue, especially in developing countries such as Pakistan, where it has gained the special attention of government and regulatory authorities. The present study evaluates green technology strategies for the sustainable development of solar power projects in Pakistan. We examine the moderating role of cost and riskiness of the methods between the nexus of capital budgeting techniques and the financial performance of solar power projects. The analysis is performed on data collected from 44 respondents (chief financial officers and chief executive officers) by accompanying an inclusive questionnaire survey. Partial least squares structural equation modeling (PLS-SEM) is used to assess the formulated suppositions. The results reveal that green technology strategies positively impact the sustainable development of solar power projects. The profitability index is a good source of higher financial performance of the solar power projects. The results further demonstrate that the cost and riskiness of the methods significantly moderate the nexus of capital budgeting techniques and the financial performance of solar power projects. These findings provide a valuable manual for policymakers, government institutions, and regulators to select the appropriate green technology strategy to increase cleaner production and sustainable development of solar power projects.
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                Author and article information

                Journal
                BUILCO
                Buildings
                Buildings
                MDPI AG
                2075-5309
                December 2023
                December 15 2023
                : 13
                : 12
                : 3117
                Article
                10.3390/buildings13123117
                890d0e7e-78e2-4bd7-bfb3-2ef352eb826a
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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