Sustainable agriculture is often required for the “pollution reduction, carbon reduction, green expansion, and economic growth” against global warming in recent years. This study aims to systematically investigate the spatiotemporal differentiation and driving mechanisms of synergistic effects between agricultural pollution and carbon emission reduction. Taking the Yangtze River Delta as an example, agricultural non-point source pollution and carbon emissions were calculated for each city from 2008 to 2022. A global super-efficiency slack measure model was also combined with the coupling coordination model. A spatiotemporal weighted regression model was introduced to explore the influences of five dimensions (e.g., cultivated land use, socio-economic factors, production, policy, and natural endowment) on the synergistic effects. The results show that: 1) Agricultural non-point source pollution declined from 2008 to 2022, with reduction rates of 20% in Zhejiang and Jiangsu provinces. Anhui province averaged only a 0.34% annual decline. Agricultural carbon emissions shared significant spatiotemporal heterogeneity, with the gradual decrease in Zhejiang and Jiangsu provinces, significant carbon reduction in Shanghai, and a rapid decline in Anhui after peaking in 2014. 2) The mean synergistic effects improved steadily from 0.366 in 2008 to 0.627 in 2022. While most cities remained coordinated, and the number of low-value synergistic effects decreased progressively, indicating a converging trend toward medium-high values. Meanwhile, the polarization was intensified among cities, with a high-east and low-west gradient. High-value areas were concentrated in northern Zhejiang and southern Jiangsu, whereas low-value areas were scattered in central-western Anhui and southern Zhejiang, such as Huainan, Chuzhou, and Quzhou. 3) Crop cultivation structure, cultivation land scale, urbanization, and financial support for agriculture were the key drivers of the synergistic effects, with remarkable spatiotemporal heterogeneity between them. The crop cultivation structure overall played a positive role, especially in southern Zhejiang and northeastern Jiangsu; Its regression coefficients were negative in the central study area, where the negative zone gradually shifted toward northwestern Anhui. The positive impact of cultivation land scale strengthened continuously in western Anhui and northeastern Jiangsu, while the expansion scale was unfavorable for the synergistic effects in southwestern Zhejiang province. Since urbanization exerted an inhibitory effect, a positive driving force of eco-friendly agriculture was observed in southern Zhejiang. Regression coefficients of financial support displayed a west-high and east-low differentiation pattern. In conclusion, the findings can provide a strong reference for the synergistic effects of pollution and carbon emission reduction from an efficiency perspective in sustainable agriculture.

Low-carbon transition is often required in the context of the carbon emission peak and carbon neutrality goals at present. It is very necessary to measure the land use efficiency of the urban expansion areas. Zoning regulations can also be used to clarify the differential effects of the multidimensional factors on the land use efficiency in different zones of cities. Previous studies have focused mainly on the urban land use efficiency. However, three limitations still remain to be solved: the spatial heterogeneity of the land use efficiency within cities, the differential impacts of the multidimensional factors on the land use efficiency, and the regional strategies for the different types of urban patches at the micro scale. In this research, a patch-scale model was constructed to measure the land use efficiency in the urban expansion areas, from an “economy-environment” perspective. Zhejiang Province was taken as an example. Its spatial patterns were also analyzed using standard deviation ellipses. Four types were then classified using a two-dimensional matrix coupled with the “economy-environment”. A systematic investigation was made to explore its influencing factors using Geodetector. The results showed that: 1) The average economic efficiency of the land use was 0.74 in Zhejiang Province. High-value areas were concentrated in the intersection of four cities in northern Zhejiang and central Ningbo. While the low-value areas were formed, the multiple small and medium-sized clusters were in southern Zhejiang. The average carbon emission efficiency was 0.77. The spatial pattern was characterized by the concentration in the high-value areas and the dispersion in the low-value ones. 2) The urban expansion in Zhejiang Province was classified into four types according to the matching relationship between the economy and carbon emission efficiency. The low-carbon development zones accounted for 59.12% of the total area. There was a block pattern of the “large agglomeration and small dispersion”. The emission reduction and efficiency enhancement zones accounted for the lowest proportion (8.30%) of the land area. Most zones were concentrated in the belt area composed of Jiaxing, Hangzhou, Ningbo, and Zhoushan. The low-carbon demonstration zones were interwoven with the emission reduction and efficiency enhancement zones. The green transformation zones were dominated mainly by early urban expansion patches during the study period. There was a distribution pattern in a centralized manner. Two large clusters were centered on the urban areas of Hangzhou and Ningbo, with less distribution in the mountainous counties in southern Zhejiang. 3) The functional configuration elements shared a significant impact on the economic efficiency of the land use in the low-carbon development, emission reduction, and efficiency enhancement, as well as low-carbon demonstration zones. In the green transformation zone, the transportation construction and public service elements also exerted a greater influence than the rest. In terms of the carbon emission efficiency of land use, the spatial structure elements shared significant influences in the low-carbon development zones. The functional configuration was the core driving factor for the carbon emission efficiency of the land use in the emission reduction and efficiency enhancement zones, as well as the green transformation zones. Furthermore, there were relatively strong impacts of the transportation construction factor in the low-carbon demonstration zones. In conclusion, the urban measures can be tailored to the different types of urban expansion areas, in order to improve their economic efficiency for less carbon emission, thereby promoting the low-carbon transformation in cities.