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The urbanization process has an impact on greenhouse gas emissions, but little research has linked specific processes of urbanization to CO2 emissions. Particularly, for China, the urban–rural dual system and unique fertility policy play an important role in its urbanization process. A large population base and a sharp urban–rural divide need to be taken into account in CO2 emission forecast. Based on three urbanization processes corresponding to Shared Socioeconomic Pathways (SSPs) scenarios, this article combined the Population-Development-Environment (PDE) model and the Global Change Assessment Model (GCAM) to forecast energy consumption and CO2 emissions in China in this century. The results show as follows. 1. China’s CO2 emissions and energy consumption will experience an inverted U-shaped trend. In the rapid, moderate and slow urbanization scenarios, CO2 emissions peak in 2045, 2035 and 2030 at 11.55 billion tons, 10.88 billion tons and 10.65 billion tons, respectively. 2. The peak time of energy consumption is generally later than that of CO2 emissions. In the rapid, moderate and slow urbanization scenarios, the primary energy consumption peaks at 212.03 EJ in 2055, 190.65 EJ in 2055 and 171.80 EJ in 2045, respectively; the final energy consumption peaks at 192.34 EJ in 2055, 174.47 EJ in 2055 and 157.25 EJ in 2045, respectively. 3. More rapid urbanization corresponds to a later peak in CO2 emissions and energy consumption, but the decline is faster after the peak. In the future, China should vigorously implement intensive and sustainable policies to avoid excessive emissions in the urbanization process.

Urban and rural relations are important for the sustainable development of a nation or region. Urban and rural integration (URI), as a conceptual framework and strategic tool for managing urban–rural relations, is supposed to play a role in linking urban and rural socio-economic systems to promote the two-way flow of resources, facilitate spatial restructuring and functional transformation, enhance resource allocation efficiency, and shorten the gap between urban and rural areas. This article takes agriculture technological innovation in China as an example, and discuss whether and how URI can promote agricultural technological innovation (ATI). Based on a dataset of 288 prefecture-level cities spanning the years from 1999 to 2018, this article analyzes the mechanism and effect of URI on the development of ATI by using the negative binomial regression model and other models based on measuring the level of URI in the municipal area. The main conclusions are as follows. (1) URI positively promotes the development of ATI and exhibits significant heterogeneity across various dimensions, regions, and agricultural production areas. (2) The mechanism analysis shows that governance systems and mature markets positively moderate the impact of URI on promoting ATI, which also exhibits heterogeneous characteristics across various regions. (3) The impact of URI on the development of ATI exhibits a double threshold effect, and its marginal impact on the development of ATI increases with the deepening of URI. Moreover, the threshold effect of URI demonstrates significant heterogeneity. In central and urban areas, after surpassing the threshold value, the influence of URI on agricultural technological innovation becomes greater. Therefore, it is crucial to continuously deepen the development of URI, smooth the channels of factor flow, enhance resource sharing, break down the urban and rural barriers, and create a new engine for ATI development.

As potential ‘hidden champion’ companies originating from Germany, specialized and innovative ‘little giant’ enterprises (LGEs) have become role models for small and medium-sized enterprises (SMEs) in China and have been considered important actors in the strategy of ‘strengthening and supplementing national supply chains’. Based on the exogenous growth theory of the firm, this article takes the perspective of the ‘dual circulation’ new development pattern of China and analyses the spatial patterns and their determinants of LGEs using the data of national-level LGEs from 2019 to 2021 and the geographical weighted regression method. The following results were obtained: (1) the national-level LGEs show the spatial distribution pattern of ‘east–central–west’ decline and are highly concentrated in the high administrative levels of the cities, especially in the Beijing–Tianjin–Hebei, Yangtze River Delta, Cross–Strait urban agglomeration. (2) The domestic and international circulations jointly affect the spatial distribution of LGEs. Local institutional thickness has the largest and widest impact, followed by local industrial synergy. The impact of global linkage is relatively stable. (3) The impacts of the main determinants have spatial heterogeneity. The positive impact of local government support shows a decreasing differentiation law from east to west, and local industrial synergy is mainly significant in the east area of Northeast China, Bohai Rim, Shandong Peninsula, and Huang-Huai-hai Plain. The spatial heterogeneity of the effect of international circulation comes from the difference in marginal effects among regions and the influence of the Belt and Road Initiative. The positive impact of FDI is mainly concentrated in the northeast and southwest regions. This article highlights the importance of the domestic value chain in the strategy of Innovative China, and proves that varying global-local nexus of cities creates ‘soils’ with varying fertility in which LGEs thrives as well.