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

• Published in: Transportation research. Part D, Transport and environment Vol. 82; p. 102318
• Main Authors: Wang, Likun, Peng, Chen, Shi, Wenming, Zhu, Mo
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2020
• Subjects: Container distribution facilities; Green port; local Moran’s I; Port carbon emissions; Spatial Durbin model; local Moran’s I; Container distribution facilities; Port carbon emissions; Spatial Durbin model; Green port
• ISSN: 1361-9209; 1879-2340
• DOI: 10.1016/j.trd.2020.102318

•An easily implemented method for calculating CO2 emissions from port container distribution (PCD) is proposed.•Key driving factors of PCD carbon emissions are analyzed.•Spatial patterns of PCD carbon emissions are examined. 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.