Fan Liu

The low-carbon transformation of manufacturing enterprises is considered to be imperative to achieve carbon neutrality. Therefore, we propose a data-driven strategy to achieve a low-carbon transformation of manufacturing enterprises from an eco-efficiency perspective. Following the collection of input (energy, materials, equipment, R&D, and services) and output (waste and products) data from production systems of manufacturing enterprises, an ecological efficiency model of manufacturing enterprise production system was constructed from the perspective of carbon emissions, thus allowing the quantitative evaluation of the ecological efficiency of the production system. Furthermore, a “measurable, evaluable, and optimized” low-carbon transformation and upgrading method for manufacturing enterprise production system was established. Finally, through the production practice data of an enterprise from 2017 to 2021, the feasibility and effectiveness of this method were verified. The results show that this method can effectively improve the ecological efficiency of enterprises by 3.6% and reduce waste emissions by 12%. Our study provides new tools for improving the ecological efficiency of manufacturing systems, along with theoretical and methodological support to manufacturing enterprises for low-carbon transformation.

A rapid development in regional economy is often accompanied by an increase in energy consumption and the intensification of environmental pollution, which brings great pressure to the social economy and the natural environment. In order to solve the integrated problem of economic, social, and natural factors, we propose an evaluation method for the sustainable development of the regional economy, based on emergy. By analyzing the statistical data of Henan’s economic development from 2010 to 2018, an evaluation index system of regional eco-economic sustainable development was constructed based on four aspects: natural subsystem, economic subsystem, social subsystem, and sustainable development index. The index system was then used to measure and comprehensively evaluate the sustainable development of the ecological economy and the environmental friendliness of Henan Province. The assessment results showed that the emergy self-sufficiency rate decreased, indicating decreased self-sufficiency. Moreover, the environmental load rate was high, indicating high environmental pressure. The emergy currency rate declined with a rise in the emergy investment rate, indicating economic growth. Additionally, the population carrying capacity was consistently > 1, indicating that the population was overloaded. Collectively, the emergy-based evaluation method of regional economic sustainable development in this study provides a comprehensive and scientific evaluation framework, which can help decision makers and researchers better understand and evaluate the problems brought about by the rapid development of regional economy, and provide targeted decision making suggestions. It includes four sub-systems: natural, economic, social, and sustainable, which have important theoretical and practical significances, while also serving as a useful reference for the evaluation of the sustainable economic development of similar regions.

Industrial ecological efficiency is regarded as an urgent challenge that affects the development of ecological civilization and environmental governance. Here, we propose a data-driven approach to measure and promote regional industrial ecological efficiency. We collected data related to regional industrial development and used the Data Envelopment Analysis-Banker Charnes and Cooper (DEA-BCC) model to measure regional industrial ecological efficiency from a static perspective. The Malmquist index model was then used to measure regional industrial ecological efficiency from a dynamic perspective. In addition, we used a Tobit regression model to identify the factors affecting regional industrial ecological efficiency. Through a case study of regional industrial ecological efficiency, we demonstrate the specific application of the proposed data-driven approach. This study provides a new and effective tool for improving industrial ecological efficiency at a regional scale. This method can help enterprises and local governments improve industrial ecological efficiency, coordinate the relationship between industrial economic growth and the ecological environment, and boost regional efforts to achieve carbon peaking and carbon neutralization goals.

Green development is an important connotation of high-quality development and is one of the goals of scientific and technological innovation. This study constructs a data-driven measurement model of the green development efficiency of regional sci-tech finance, measures the green development efficiency of sci-tech finance by using the super-slack-based measure model, and deeply analyses and evaluates the changes in green development efficiency of regional sci-tech finance by calculating Malmquist index. This study calculates the green development efficiency of sci-tech finance in the Yangtze River Delta. Results show that the green development efficiency of sci-tech finance in the Yangtze River Delta is on the rise as a whole and maintains an efficient state, but differences are observed between provinces and cities. This study provides theoretical and methodological support for the evaluation of the green development efficiency of regional sci-tech finance and serves as reference for policy makers and researchers of sci-tech finance.

Improving industrial ecological efficiency is important in promoting the industry’s sustainable development. However, the economy, resources, the environment, and other factors should be considered. This paper proposes a data-driven evaluation and promotion method for improving industrial ecological efficiency. Based on industrial input and output data, the super-efficiency slack-based model containing an unexpected output was used to measure industrial ecological efficiency. The kernel density estimation method was employed to analyze the time-series characteristics of industrial ecological efficiency. Using data from 30 provinces and cities in China, this study demonstrated the implementation of a data-driven method. The results show that China’s overall industrial ecological efficiency is increasing, and industrial ecological efficiency in the western region is rapidly improving. Differences exist between provinces and cities; the characteristics of polarization are significant, and there are short boards in the eastern, central, and western regions. Based on this, suggestions are made to improve the industrial ecological efficiency of the central region, narrow the gaps between the regions, and promote each region to develop its strengths and mitigate its weaknesses. This provides a basis for formulating policies related to ecological environment protection and industrial pollution control.

The Yangtze River Delta (YRD) has abundant regional advantages. Its rapid economic development plays an essential strategic role in China's overall growth; however, this place significantly pressurized on resources and the environment. Accordingly, this study developed an evaluation index and system of sustainable development for a green economic system based on the emergy theory. Moreover, comparative analyses were made according to the present ecological–socioeconomic systems of the YRD. The results indicated a large gap between the production efficiencies of the three provinces and a single city in the YRD. The highest emergy yield ratio was in Anhui Province, but the corresponding emergy yield per capita and emergy output density was the lowest; the environmental load ratios were all > 10, which is considered a high load; the sustainable development indices were all < 1, which represents a state of unsustainable development. According to the present research results, suggestions for the sustainable development of the YRD were put forth here. This research provides theoretical and methodological support for the sustainable development of an ecological economy in the YRD. It can serve as a decision-making reference for China to achieve the goal of carbon peak and carbon neutralization.

This study aims to promote the high-quality development of regional agriculture. This study proposes a data-driven method for regional agricultural analysis and evaluation. Based on the data collection and processing related to regional agricultural development, the location entropy index was used to analyze the industrial agglomeration level, and the shift-share model was constructed to evaluate the industrial structure and competitiveness. Based on the above analysis and evaluation, high-quality development policy suggestions for regional agriculture were provided. Taking the agricultural development of the Yangtze River Delta from 2010 to 2019 as an example, this study shows the implementation process of the method. From the perspective of high-quality agricultural development in the Anhui Province, this paper proposes policy suggestions on industrial structure adjustment and promoting competitiveness. This study provides theoretical and methodological support for the development of high-quality regional agriculture.

Human survival depends on the sustainable development of agriculture. This study constructs a data-driven evaluation and optimization method of agricultural sustainable development capacity, aiming to better cope with challenges such as environmental pollution and excessive consumption of resources and energy, as well as improve agricultural economic level. Further, an evaluation index system was constructed based on comprehensive consideration of energy and resources utilization, environmental pollution, and agricultural economy. After simplifying and integrating the data, a data envelopment analysis model was constructed to quantitatively evaluate the capability for agricultural sustainable development and its changing trend. Moreover, its influencing factors were analyzed from the perspective of input, which provides accurate countermeasures for improving agricultural sustainable development ability, resource utilization efficiency, and process optimization. This study shows the realization process of the aforementioned method for the agricultural development of six cities in northern Anhui from 2010 to 2019. Our results suggest that the sustainable development ability of northern Anhui is weak, but overall, has a good development trend. Based on our results, some countermeasures were proposed to control production scale reasonably, reduce environmental load, and improve resource efficiency, which provides a reference for policymakers to guide and standardize the development of regional agriculture.