Although urbanization greatly benefits economy-society development in China, it poses enormous challenges to cultivated land utilization. In the context of urbanization acceleration and carbon neutrality, it’s of significance to achieve high-quality economy-society development and sustainable agricultural development. Thus, the coupling coordination relationship between new-type urbanization and cultivated land low-carbon utilization (CLLCU) needs to be examined. However, this topic has not been adequately addressed in previous studies. To fill the gap, this paper adopted a comprehensive evaluation model and a super-efficiency SBM (Slacked Based Measure) model to evaluate the level of new-type urbanization and the cultivated land low-carbon utilization efficiency (CLLCUE) of cities in the Yangtze River Delta in China from 2000 to 2018. Furthermore, the coupling coordination degree model (CCDM) and the relative development degree model (RDDM) were employed to measure the coupling coordination degree and the relative state of the new-type urbanization and CLLCU The results show that the coupling coordination degree between the new-type urbanization level and CLLCUE experienced a process of “rapid increase-steady develop” and presented a spatial pattern of “polarization-regional equilibrium”. In addition, the relative state of the new-type urbanization and CLLCU presented the “reversal” phenomenon. In other words, the relative state changed from the new-type urbanization lagging behind CLLCU to the new-type urbanization ahead of CLLCU. None of the cities were in the state of simultaneous development. Finally, this paper puts forward policy recommendations to explore differentiated CLLCU modes and improve the quality and efficiency of new-type urbanization.

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Urban green space can help to reduce PM2.5 concentration by absorption and deposition processes. However, few studies have focused on the historical influence of green space on PM2.5 at a fine grid scale. Taking the central city of Wuhan as an example, this study has analyzed the spatiotemporal trend and the relationship between green space and PM2.5 in the last two decades. The results have shown that: (1) PM2.5 concentration reached a maximum value (139 μg/m3) in 2010 and decreased thereafter. Moran’s I index values of PM2.5 were in a downward trend, which indicates a sparser distribution; (2) from 2000 to 2019, the total area of green space decreased by 25.83%. The reduction in larger patches, increment in land cover diversity, and less connectivity led to fragmented spatial patterns of green space; and (3) the regression results showed that large patches of green space significantly correlated with PM2.5 concentration. The land use/cover diversity negatively correlated with the PM2.5 concentration in the ordinary linear regression. In conclusion, preserving large native natural habitats can be a supplemental measure to enlarge the air purification function of the green space. For cities in the process of PM2.5 reduction, enhancing the landscape patterns of green space provides a win-win solution to handle air pollution and raise human well-being.