IntroductionMarine ecological security assessments are considered as a basis for coordinating marine economic development and ecological protection.MethodsWe propose an assessment method based on the emergy ecological footprint which first measures the emergy of the natural and economic elements of the marine ecosystem. Considering the role of economic, social and waste discharge factors in the marine ecosystem, an ecological security evaluation index is constructed, and a dynamic evaluation is conducted based on long time series data to characterize the change trend of ecological security.ResultsThe Guangxi marine ecosystem was selected as the case study, and the ecological security dynamic evaluation was conducted by collecting data from 2008 to 2020. The results show that Guangxi's marine ecosystem has always been in an ecologically secure state, but since 2010, the emergy ecological footprint intensity has been increasing, indicating ecosystem deterioration. Therefore, some targeted suggestions are put forward.DiscussionThis method provides a new assessment tool for marine ecological security evaluation and offers guidance for the sustainable development and utilization of marine ecosystems.

This study aims to improve regional agricultural production efficiency and promote sustainable agricultural development by presenting a data-driven evaluation method for regional agricultural production efficiency. Based on data collection and processing of regional agricultural input-output factors in Anhui Province, China, from 2014 to 2019, a data envelopment analysis Malmquist model is constructed for data modeling. Static analysis of regional agricultural production efficiency and production redundancy is conducted, and the dynamic change of regional agricultural production efficiency is measured. The results show that technical efficiency is the core driving factor for improving regional agricultural production efficiency. The findings indicate significant policy implications for improving agricultural production efficiency from the perspective of regional agricultural high-quality development. This study provides theoretical and methodological support for the sustainable development of regional agriculture.

Improving the logistics industry’s resource efficiency (LIRE) is one of the most significant measures for ensuring sustainable development. We offer a data-driven technique for analyzing and optimizing the LIRE to improve it and achieve sustainable development. A LIRE index system is built based on relevant data gathering and a complete examination of the economy, society, and environment. The Super-EBM-Undesirable model was used to calculate the LIRE; the Global Malmquist–Luenberger index model was used to calculate the LIRE’s dynamic change characteristics, and ArcGIS and spatial autocorrelation models were used to analyze the LIRE’s spatial evolution pattern. The LIRE in 30 Chinese provinces and cities from 2011 to 2019 is used to illustrate the method implementation process. The results indicate the following: (1) The overall LIRE is low, with an average value of 0.717, and there are regional variances with a decreasing gradient pattern of “East–Northeast–Central–West”. (2) Changes in pure technical efficiency have a bigger impact in general; increasing technical efficiency is the LIRE’s principal motivator. (3) Improving the LIRE should take spatial spillover and inhibitory effects into account. This study provides theoretical and methodological support for the evaluation and optimization of the LIRE and a theoretical foundation for the logistics industry’s sustainable development (LISD).

The resources and environmental carrying capacity (RECC) of a region are considered the key and the foundation for achieving sustainable development and the benchmark of environmental protection and pollution control. However, to improve the regional RECC, we need to comprehensively consider the data information and correlation of the economy, society, resources, and the environment. Therefore, we propose a data-driven method for RECC measurement and evaluation of the regional RECC. Based on data collection and the application of the pressure-state-response (PSR) framework to reflect RECC, an evaluation index system for the regional RECC is constructed. The technique for order of preference by similarity to the ideal solution (TOPSIS) model with the entropy weight method is used to measure and evaluate the regional RECC. The obstacle degree model is adopted to select and identify the key factors affecting the regional RECC and to propose targeted policy suggestions for data application. The results indicate that the RECC level in three provinces and one city of the Yangtze River Delta region fluctuated slightly from 2010 to 2019, with an overall upward trend. Anhui Province has a relatively weak carrying capacity, and the main obstacles to RECC improvement in the region are the proportion of wetland area and the ownership of water resources. This study provides theoretical and methodological support for regional RECC research and management as well as a basis for formulating policies related to environmental protection and pollution control.