Carbon flow through continental-scale ground logistics transportation
Haotian Cui,
Yonglong Lu,
Yunqiao Zhou,
Guizhen He,
Shuai Song,
Shengjie Yang,
Rui Wang,
Siyu Wang,
Guoxiang Han,
Xiaojie Yi,
Di Du,
Nils Chr. Stenseth,
Dag O. Hessen,
Deliang Chen,
Yinyi Cheng
Affiliations
Haotian Cui
State Key Laboratory of Marine Environmental Science and Key Laboratory of the Ministry of Education for Coastal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Fujian 361102, China; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Yonglong Lu
State Key Laboratory of Marine Environmental Science and Key Laboratory of the Ministry of Education for Coastal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Fujian 361102, China; State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Corresponding author
Yunqiao Zhou
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Guizhen He
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Shuai Song
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Shengjie Yang
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Key Laboratory for Geographical Process Analysis, and Simulation of Hubei Province/College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China
Rui Wang
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Siyu Wang
University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Guoxiang Han
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Xiaojie Yi
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Di Du
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
Nils Chr. Stenseth
Centre for Ecological and Evolutionary Synthesis, University of Oslo, 031603 Oslo, Norway; Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
Dag O. Hessen
Section for Aquatic Biology and Toxicology, Centre for Biogeochemistry in the Anthropocene, University of Oslo, 031603 Oslo, Norway
Deliang Chen
Regional Climate Group, Department of Earth Sciences, University of Gothenburg, 40530 Gothenburg, Sweden
Yinyi Cheng
University of Chinese Academy of Sciences, Beijing 100049, China
Summary: The flourishing logistics in both developed and emerging economies leads to huge greenhouse gas (GHG) emissions; however, the emission fluxes are poorly constrained. Here, we constructed a spatial network of logistic GHG emissions based on multisource big data at continental scale. GHG emissions related to logistics transportation reached 112.14 Mt CO2-equivalents (CO2e), with seven major urban agglomerations contributing 63% of the total emissions. Regions with short transport distances and well-developed road infrastructure had relatively high emission efficiency. Underlying value flow of the commodities is accompanied by logistics carbon flow along the supply chain. The main driving factors affecting GHG emissions are driving speed and gross domestic product. It may mitigate GHG emissions by 27.50–1162.75 Mt CO2e in 15 years if a variety of energy combinations or the appropriate driving speed (65–70 km/h) is adopted. The estimations are of great significance to make integrated management policies for the global logistics sector.
