Exploring the development laws of new quality productivity and leveraging its role in empowering marine economy high-quality development (MEHQ) is of great significance for promoting the construction of a maritime power in China, achieving the goals of Chinese-style modernization and solidifying the country’s advantages in marine economic development. This paper systematically reviews the mechanisms and effects of new quality productivity (NQP) in empowering MEHQ. Using panel data from 17 cities along the Bohai Sea from 2010 to 2022, we comprehensively measure the combined levels of NQP and MEHQ. Employing various statistical analysis methods, including benchmark regression models, multiple mediation effect models, and spatial Durbin models, we empirically test the mechanisms and spatial spillover effects of NQP in empowering MEHQ. The results indicate that NQP has a significant positive driving effect on MEHQ, and this conclusion remains valid after a series of robustness tests. The empowering effect of NQP on MEHQ mainly occurs through three pathways: marine technological innovation, optimization of marine industrial structure, and improvement of marine resource allocation efficiency. There is a positive correlation between NQP and MEHQ, with significant agglomeration phenomena, reflecting the non-uniform characteristics of spatial distribution. NQP not only empowers MEHQ but also exhibits significant spatial spillover effects, promoting MEHQ in adjacent regions and releasing growth dividends.

As a national strategic development area, the Yellow River Basin (YRB) has seen progress in research on the synergy efficiency of pollution reduction and carbon reduction (SEPCR). However, there are still notable gaps. The theoretical framework for this area is lacking, leading to diverse and inconsistent conclusions. Additionally, difficulties in data collection and processing, along with incomplete and inconsistent data, negatively affect the accuracy of research findings. Current studies tend to focus on single aspects and lack a comprehensive and systematic analysis of the SEPCR across the entire basin. There is insufficient understanding of key network nodes, connections, and overall structural characteristics. A scientific assessment of its spatial correlation structure has far-reaching implications for the national battle against pollution and the realization of “dual carbon” goals. This study is based on panel data from 75 cities in the YRB from 2006 to 2022. It employs an ultra-efficiency SBM model to measure the SEPCR. Additionally, it utilizes a modified gravity model and social network analysis to explore the spatial network correlation structure in depth. Furthermore, the QAP model is used to clarify the mechanisms of various influencing factors. The research findings indicate that there is an imbalance in the spatial and temporal distribution of the SEPCR in the YRB. Although there is a fluctuating upward trend over time, significant internal spatial disparities exist. While the gaps between regions are gradually narrowing, there are still evident research disparities. Moreover, the spatial connectivity of the SEPCR in the YRB is gradually strengthening, with overall network connectivity also improving, yet there remains a considerable distance from an ideal state. The network density shows a decreasing trend from the downstream to the midstream and then to the upstream regions, with significant differences in spatial network centrality among these areas, particularly pronounced between the midstream and upstream regions. Differences in economic development levels, technological development levels, and industrial structure development levels promote the formation of spatial correlations in SEPCR, while disparities in energy utilization have a suppressive effect.

Enhancing the marine carrying capacity (MCC) is of important value in hastening the transformation of the marine economy and realising the marine economy high-quality development (MEHD). We explore the synergistic mechanism between the MCC and MEHD and its comprehensive indicator system, measure the synergistic relationship between China’s MCC and MEHD from 2006 to 2020 using the improved TOPSIS model and the composite system synergism model, and explore the influencing factors and their interactions using geographic probes. The research findings are (1) that China’s MCC and MEHD show a growing trend during the study period, in which marine green development is at a higher level and the cultivation of marine knowledge improves most significantly, but the general value of the MEHD is relatively low. (2) In terms of the synergistic relationship, the degree of ordering of the two shows a sustained rising trend, and the degree of ordering of the marine economy development as a whole is higher than the MCC; the degree of synergy is increasing, but the general value of synergistic development is low. (3) The main factors driving the MCC and MEHD are the marine consumption capacity, the marine opening, and the marine industrial structure; the explanatory power of most factor interactions tends to decrease, and the explanatory power of the interactions among the development of land-based economy, the marine industry structure, and the marine economy increase, and the impacts of the different factor interactions on the synergistic development are all greater than the factors. The influence of different factors on synergistic development is greater than the influence of each factor alone.

The integration of sea and land ecological economies is crucial for the development of a high-quality sea–land economy. This study explores and proposes the concept of a sea–land-integrated ecological economy. By constructing the evaluation index system for developing a sea–land-integrated ecological economy, the development level, evolution process, and development trend prediction of a sea–land-integrated ecological economy were evaluated and analysed in cities around the Bohai Sea from 2009 to 2019 using methods such as a model for assessing the development level, a spatio-temporal autocorrelation model, and an exploratory spatio-temporal data analysis model. The results of the study show that (1) the development level of the ecological economy of the cities of Bohai Rim’s sea–land integration generally had an upward trend; however, the magnitude significantly varied between cities; (2) the spatio-temporal autocorrelation pattern formed three major agglomerations with Dalian in the north, Yantai and Qingdao in the south, and Tianjin and Tangshan in the centre as the core cities and contained low agglomerations and scattered L–H spatio-temporal heterogeneous units; and (3) the integration prediction curve for 2020–2029 indicates that the level value for integration of most cities will improve over time.