Low-carbon governance at the county level has been an important issue for sustainable development due to the large contributions to carbon emission. However, the experiences of carbon emission governance at the county level are lacking. This paper discusses 5 carbon emission governance zones for 1753 counties. The zoning is formed according to a differentiated zoning method based on a multi-indicator evaluation to judge if the governance had better focus and had formulated a differentiated carbon emission governance system. According to zoning results, there is 1 high-carbon governance zone, 2 medium-carbon governance zones, and 2 low-carbon zones. The extensive high-carbon governance zone and medium-carbon zones are key governance areas, in which the counties are mainly located in the northern plain areas and southeast coastal areas and have contributed 51.88% of total carbon emissions. This paper proposes differentiated governance standards for each indicator of the 5 zones. The differentiated zoning method mentioned in this paper can be applied to other governance issues of small-scale regions.

Serious farmland scarcities make smallholders a default mode for China’s agriculture, which makes efficient and equitable rural development a great challenge. Tensions lead to alternation between autonomous family farming and coordinated collective agriculture. Rapid urbanization since the 1980s has strongly stimulated flower-growing and agribusiness in Yunnan, China. The organization for commercial flower-farming is, however, an issue. Officially promoted for collective farming, voluntary cooperatives are wrecked by the free-riding problem. Grower associations nevertheless spontaneously emerge, with the flexible entry and exit of members without binding joint-assets and joint-ownership, which is facilitated by technological changes to the transaction. Empirical investigation in Tonghai, Yunnan, unveiled the institution of agribusiness–smallholder partnership for inclusive rural development. Smallholders have actively participated in flower agriculture, which has contributed significantly to the development of rural economies. The high casualty of micro-smallholders suggests that farm size is an important and crucial factor for sustainable farming. Effective rural development has to be supported by endogenous non-agricultural jobs so that farm size can be increased.

As China shifts from rapid to high-quality development, urban growth has exhibited allometric patterns. This study evaluated land use efficiency from the perspective of architectural space, focusing on 41 cities in the Yangtze River Delta urban agglomeration from 2010 to 2020. A land development intensity index was constructed at both the provincial and municipal levels using the entropy weight method, integrating floor area ratio, building density, and functional mix. The spatiotemporal characteristics of land development intensity and population density were analyzed, and a coordination coupling model was applied to identify mismatches between land and population. The results reveal: (1) Temporally, the imbalance of “more people, less land” in the Yangtze River Delta diminished. Spatially, leading regions exhibit a diffusion effect. Shanghai showed a decline in both population density and development intensity; Zhejiang maintained balanced development; Jiangsu experienced accelerated growth; and Anhui showed signs of catching up. (2) Although the two indicators showed a high coupling degree and strong correlation, the coordination degree remained low, indicating poor quality of correlation. The land-population relationship demonstrated a fluctuating pattern of “strengthening–weakening” over time. Shanghai exhibited the highest coordination, while more than half of the cities in Jiangsu, Zhejiang, and Anhui still needed optimization. (3) Unlike previous findings that linked such patterns to shrinking cities, in this transformation stage, the number of cities where land development intensity exceeded population density continued to grow in advanced regions. This study first applied 3D building data at the macro scale to support differentiated spatial policies.