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Carbon dioxide emissions from port container distribution: Spatial characteristics and driving factors

机译:港口集装箱分配的二氧化碳排放:空间特征和驱动因素

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Port carbon dioxide (CO2) emissions in China have become an ever-increasing public concern due to their significant impacts on human health and the environment. However, existing studies focus mainly on CO2 emissions from vessels calling at the ports and cargo handling within the ports, paying little attention to the inland distribution networks. To fill this gap, this paper proposes an easily implemented method for calculating CO2 emissions from port container distribution (PCD) and investigates their spatial characteristics and driving factors. By analyzing 30 container ports in China, the main findings are as follows. First, road transportation is the major contributor of CO2 emissions from PCD due to the lack of rail and inland water transportation. Second, PCD carbon emissions exhibit significant local spatial clustering. That is, ports with similar geographical locations tend to present a similar pattern of PCD carbon emissions. Third, as suggested by the spatial Durbin model, PCD carbon emissions are negatively determined by local gross domestic product, number of port berths, but are positively determined by local tertiary industry value and highway freight volume, and waterway freight volume in both local and neighboring ports. These results provide empirical insights into cross-port collaboration in reducing PCD carbon emissions.
机译:由于对人类健康和环境的重大影响,中国的港口二氧化碳(二氧化碳)排放已成为不断增加的公众关注。然而,现有研究主要关注船舶在港口内港口和货物处理的二氧化碳排放,几乎没有注意内陆分销网络。为了填补这一差距,本文提出了一种易于实现了从端口容器分布(PCD)的CO2排放的方法,并调查其空间特征和驱动因子。通过在中国分析30个集装箱港口,主要研究结果如下。首先,道路运输是由于缺铁和内陆水运输缺乏PCD的二氧化碳排放的主要贡献者。其次,PCD碳排放表现出显着的局部空间聚类。也就是说,具有相似地理位置的端口往往呈现类似的PCD碳排放模式。第三,如空间德国模型所提出的,PCD碳排放由当地国内生产总值,港口泊位数量负面决定,但港口泊位数量肯定地确定,本地和邻近的水路货运量和水路货运量港口。这些结果在减少PCD碳排放时对交叉口合作提供了经验洞察。

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