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This paper used the multi-region input-output model to calculate the embodied carbon and its industrial structure of China's inter-city industrial trade based on the perspective of value-added trade, depict the structural characteristics of the embodied carbon transfer network, and the mechanism of the embodied carbon transfer network is revealed through the exponential random graph model (ERGM). The study found that: The inter-city industrial trade embodied carbon transfer network is dense but without scale, with small world structure and miscompatibility. Resource-intensive and capital-intensive industries contribute more than 90% of the embodied carbon transfer. Cities with high embodied carbon net outflow are mainly resource-based and industrial cities in the Yellow River Basin and the Bohai Rim region, while cities with high embodied carbon net inflow are mainly the national and regional central cities east of Hu Huanyong Line. Large-scale embodied carbon transfer mainly occurs among the cities within the provinces, and the inter-city embodied carbon transfer network has a certain provincial boundary effect. The embodied carbon transfer of provincial cities presents the "core-edge" structure around the provincial central cities. The embodied carbon transfer of inter-provincial cities shows the radial structure from the resource-based cities and industrial cities in the Yellow River basin and the Bohai Rim region to Beijing, Shanghai, Hangzhou, Ningbo, Suzhou, Chongqing, Guangzhou, Guangzhou and Shenzhen and other central cities. In the mechanism of inter-city embodied carbon transfer network, mutualism and preference dependence effect are important endogenous mechanisms. Cities with developed economy, dense population, high per capita consumption level and advanced industry are more inclined to flow into the embodied carbon. Cities with higher comparative advantages and low energy efficiency in resource-based industries are more inclined to outflow embodied carbon. Policy proximity and geographic proximity have a positive impact on the inter-city embodied carbon transfer network, and technical proximity has a negative impact.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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