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In this paper, we propose an integrated method, called quantile mediation analysis, which combines quantile regression and mediation analysis, to examine the impact of renewable energy on carbon dioxide emissions, whether connected to or separate from through economic growth, from 1990 to 2018 in Taiwan. The results of this novel approach indicate that Taiwan's renewable energy did not affect carbon dioxide emissions through the mediation effect of economic growth from the period of 1990 to 2018, and that there is only a direct effect from renewable energy to carbon dioxide emissions at any distribution. Moreover, this result is remarkably different from the result of the traditional ordinary least square approach, which shows that Taiwan's renewable energy affects carbon dioxide emissions through the partial mediation effect of economic growth. In conclusion, we suggest that the Taiwanese government should increase the use of renewable energy in reducing local and global carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

In this paper, we propose an integrated method, called quantile mediation analysis, which combines quantile regression and mediation analysis, to examine the impact of renewable energy on carbon dioxide emissions, whether connected to or separate from through economic growth, from 1990 to 2018 in Taiwan. The results of this novel approach indicate that Taiwan's renewable energy did not affect carbon dioxide emissions through the mediation effect of economic growth from the period of 1990 to 2018, and that there is only a direct effect from renewable energy to carbon dioxide emissions at any distribution. Moreover, this result is remarkably different from the result of the traditional ordinary least square approach, which shows that Taiwan's renewable energy affects carbon dioxide emissions through the partial mediation effect of economic growth. In conclusion, we suggest that the Taiwanese government should increase the use of renewable energy in reducing local and global carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Introduction: Although forecasting electric vehicles' growth in China was frequently reported in the literature, predicting electric vehicles market penetration as well as corresponding energy saving and carbon dioxide mitigation potential in a more suitable method is not well understood. Methods: This study chose the double species model to predict electric vehicles' growth trajectory under mutually competitive conditions between electric vehicles and internal combustion engine vehicles. For comparison, it set two scenarios: with 200 and 300 vehicles per thousand persons at 2050. To give details on energy saving and carbon dioxide mitigation potential induced by electric vehicles' market penetration, it further divided electric vehicles into five subgroups and internal combustion engine vehicles into seven subgroups, therein forming respective measurement formulas. Results: This paper solved the double species model and thus got its analytical formula. Then it employed the analytical formula to conduct an empirical study on electric vehicles market penetration in China from year 2010 to 2050. Under scenario 300, electric vehicles growth trajectory will emerge a quick growth stage during 2021–2035, thereafter keeping near invariant till 2050. Meanwhile, current internal combustion engine vehicles' quick growth will continue up to 2027, then holding constant during 2028–2040, afterwards following a 10-year slowdown period. Scenario 200 has similar features, but a 2-year delay for electric vehicles and a 5-year lead time for internal combustion engine vehicles were found. On average, scenario 300 will save 114.4 Mt oil and 111.5 Mt carbon dioxide emissions, and scenario 200 will save 77.1 Mt oil and 73.4 Mt carbon dioxide emissions each year. Beyond 2032, annual 50.0% of road transport consumed oil and 18.6% of carbon dioxide emissions from this sector will be saved under scenario 300. Discussion: Compared with scenario 200, scenario 300 was more suitable to predict electric vehicle market penetration in China. In the short-term electric vehicle penetration only brings about trivial effects, while in the long-term it will contribute a lot to both energy security and carbon dioxide mitigation. The contribution of this article provided a more suitable methodology for predicting electric vehicle market penetration, simulated two coupled trajectories of electric vehicles and internal combustion engine vehicles, and discussed relative energy-saving and climate effects from 2010 to 2050. [ABSTRACT FROM AUTHOR]

Introduction: Although forecasting electric vehicles' growth in China was frequently reported in the literature, predicting electric vehicles market penetration as well as corresponding energy saving and carbon dioxide mitigation potential in a more suitable method is not well understood. Methods: This study chose the double species model to predict electric vehicles' growth trajectory under mutually competitive conditions between electric vehicles and internal combustion engine vehicles. For comparison, it set two scenarios: with 200 and 300 vehicles per thousand persons at 2050. To give details on energy saving and carbon dioxide mitigation potential induced by electric vehicles' market penetration, it further divided electric vehicles into five subgroups and internal combustion engine vehicles into seven subgroups, therein forming respective measurement formulas. Results: This paper solved the double species model and thus got its analytical formula. Then it employed the analytical formula to conduct an empirical study on electric vehicles market penetration in China from year 2010 to 2050. Under scenario 300, electric vehicles growth trajectory will emerge a quick growth stage during 2021-2035, thereafter keeping near invariant till 2050. Meanwhile, current internal combustion engine vehicles' quick growth will continue up to 2027, then holding constant during 2028-2040, afterwards following a 10-year slowdown period. Scenario 200 has similar features, but a 2-year delay for electric vehicles and a 5-year lead time for internal combustion engine vehicles were found. On average, scenario 300 will save 114.4 Mt oil and 111.5 Mt carbon dioxide emissions, and scenario 200 will save 77.1 Mt oil and 73.4 Mt carbon dioxide emissions each year. Beyond 2032, annual 50.0% of road transport consumed oil and 18.6% of carbon dioxide emissions from this sector will be saved under scenario 300. Discussion: Compared with scenario 200, scenario 300 was more suitable to predict electric vehicle market penetration in China. In the short-term electric vehicle penetration only brings about trivial effects, while in the long-term it will contribute a lot to both energy security and carbon dioxide mitigation. The contribution of this article provided a more suitable methodology for predicting electric vehicle market penetration, simulated two coupled trajectories of electric vehicles and internal combustion engine vehicles, and discussed relative energy-saving and climate effects from 2010 to 2050. [ABSTRACT FROM AUTHOR]

Artificial intelligence techniques provide more possibilities for supply chain transformations in the face of global warming and environmental degradation. This study examines the Cournot game model of two competing supply chains with various carbon emission technologies as well as the possibility of upgrading machine learning technology. The investment risk of a supply chain’s technology upgrade is either symmetric or asymmetric information. In the case of symmetric information, results show that the machine learning technology upgrade risk does not affect the market equilibrium outcomes of the duopoly model. However, in the case of asymmetric information, technology upgrade risk is vital in determining the quantities and prices of competition equilibrium. To achieve the goal of green supply chain transformation, the government should provide more technology and financial support to traditional supply chains to upgrade their machine learning technology on carbon emissions. [ABSTRACT FROM AUTHOR]