Science Research Management ›› 2020, Vol. 41 ›› Issue (5): 240-249.
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Guo Jin, Kuang Haibo, Yu Fangping
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Abstract: Statistics showed that the port and shipping industry currently accounts for 2.6 percent of global greenhouse gas emissions. The port industry was under great pressure for energy conservation, emission reduction and green growth in the context of the current national implementation of the carbon emission reduction strategy. In fact, the formation of low carbon port depended on the optimization of energy consumption structure and the iterative upgrading of carbon emission reduction technology and the port self-reduction. There were ways for ports to reduce their own carbon emissions. For example, with the help of technological advances, such as the elimination of energy-intensive loading and unloading equipment and the use of shore power facilities. However, in the process of taking measures to promote carbon emission reduction, there were prominent problems such as high investment but poor carbon emission reduction effect. One of the important causes of the formation mechanism of low carbon port was unclear. In the long run, it may lead to a large deviation in the formulation of policies and measures related to the carbon emission reduction of port industry by traffic management departments. And the same time, it may also lead to some ports carbon emission reduction measures were not enough and the effect was poor. The existing literature have been discussed the forming mechanism of low carbon port evolution path mainly from the aspects of port technology, management and development. However, there were also the following shortcomings. Firstly, from the macro perspective, there was a lack of overall analysis of the formation mechanism of China′s low carbon port, but only from the driving factors of the formation mechanism of the micro perspective analysis. Secondly, the existing researches have not conducted in-depth analysis on the formation mechanism of low carbon port from the historical dimension of China′s low carbon port construction and development, nor have they revealed the driving factors that played a crucial role in this process. For this reason, this paper took Rizhao Port as an example to carry out in-depth research on the formation mechanism of low carbon port. Firstly, the low carbon development of Rizhao Port was divided into three stages from 1987 to 2017, and the characteristics and main driving factors of each stage were analyzed. Then, with the help of Gamma distribution function, the evolution model of low carbon formation mechanism without and within influencing factors was established, and the low carbon evolution model under the interaction of scale, technology and energy was analyzed. Finally, with the help of the Gamma model without influencing factors and within influencing factors, the low carbon evolution trend of Rizhao Port in 2018-2030 is simulated and analyzed, the optimal strategic path for the low carbon construction of Rizhao Port was found, and relevant countermeasures were proposed. The main conclusions were as follows: Firstly, the low-carbon development of Rizhao Port from 1987 to 2017 was divided into three stages, and the characteristics and main driving influencing factors of each stage were analyzed. Rizhao Port low carbon development has experienced its own stage of development and its carbon emission self-development phase (Characteristics: carbon emission rose steadily, but the unit throughput carbon emission has fallen sharply. The reason was scale effect), explore the practice phase (Characteristics: carbon emission has risen sharply, but the unit throughput carbon dropped significantly. The reasons were scale effect, energy effect and technology effect orderly) and policy support phase (Characteristics: carbon emissions fast rise, but the unit throughput carbon dropped steadily. The reasons were policy effect, technology effect and management effect orderly). Secondly, the evolution model of low carbon formation mechanism without and within influencing factors was established by means of Gamma function, and the low carbon formation mechanism and the low carbon evolution model of Rizhao Port under the interaction of scale, technology and energy were analyzed numerically. The empirical results show that the fitting effects of the Gamma models without influencing factors and within influencing factors were very good. The fitting degree of the formation mechanism model within influence factors was better than that without influence factors. With the continuous improvement of technology and energy effect, the carbon emission intensity of Rizhao Port also decreased. With the increase of port throughput scale, the carbon emission intensity of the port decreased slightly, but not obviously. The attenuation rate of Rizhao Port′s carbon emission intensity gradually decreased significantly with time migration. Finally, the low carbon evolution trend of Rizhao Port from 2018 to 2030 was analyzed by using the scenario simulation method, and the results showed that the carbon emission per unit cargo throughput was the smallest under the scenario of low growth + high efficiency (0%, 2%), which could decrease by 61.34% in 2030 compared with that in 2017. At the same time, this paper put forward the countermeasures for Rizhao Port′s next low carbon construction, which focused on improving technology and energy effect, management effect and cooperation effect. This paper also had two shortcomings. Firstly, Rizhao Port′s formation mechanism analysis had a short time span and cannot be compared with other typical low-carbon ports in China. Secondly, there was not enough quantitative analysis of the contribution of the main driving factors to the formation mechanism of Rizhao Port. So the quantitative contribution of more factors needed to be further studied.
Key words: low carbon port, evolution mechanism, Rizhao Port, Gamma Function
Guo Jin, Kuang Haibo, Yu Fangping. A research on the port low carbon evolution mechanism based on Gamma Function: A case study of Rizhao Port[J]. Science Research Management, 2020, 41(5): 240-249.
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