Low-carbon Development Level Research Articles

Factors Influencing Carbon Emission and Low-Carbon Development Levels in Shandong Province: Method Analysis Based on Improved Random Forest Partial Least Squares Structural Equation Model and Entropy Weight Method

Comprehensively clarifying the influencing factors of carbon emissions is crucial to realizing carbon emission reduction targets in China. To address this issue, this paper develops a four-level carbon emission influencing factor system from six perspectives: population, economy, energy, water resources, main pollutants, and afforestation. To analyze how these factors affect carbon emissions, we propose an improved partial least squares structural equation model (PLS-SEM) based on a random forest (RF), named RF-PLS-SEM. In addition, the entropy weight method (EWM) is employed to evaluate the low-carbon development level according to the results of the RF-PLS-SEM. This paper takes Shandong Province as an example for empirical analysis. The results demonstrate that the improved model significantly improves accuracy from 0.8141 to 0.9220. Moreover, water resources and afforestation have relatively small impacts on carbon emissions. Primary and tertiary industries are negative influencing factors that inhibit the growth of carbon emissions, whereas total energy consumption, the volume of wastewater discharged and of common industrial solid waste are positive and direct influencing factors, and population density is indirect. In particular, this paper explores the important role of fisheries in reducing carbon emissions and discusses the relationship between population aging and carbon emissions. In terms of the level of low-carbon development, the assessment system of carbon emission is constructed from four dimensions, namely, population, economy, energy, and main pollutants, showing weak, basic, and sustainable stages of low-carbon development during the 1997–2012, 2013–2020, and 2021–2022 periods, respectively.

Driving Paths and Evolution Trends of Urban Low-Carbon Transformation: Configuration Analysis Based on Three Batches of Low-Carbon Pilot Cities

In response to global climate challenges, urban low-carbon transformation has become a critical strategy for sustainable development. This study constructs a theoretical model for urban low-carbon transformation using the multi-level perspective framework. We focused on three batches of low-carbon pilot cities in China and employed fuzzy set qualitative comparative analysis to investigate the transformation pathways and impact mechanisms during the periods 2010–2012, 2012–2017, and 2017–2019. The results indicate that none of the six antecedent conditions is necessary for urban low-carbon transformation. Initially, the transformation is primarily driven by a pathway led by low-carbon industries. In the mid-stage, two pathways emerge: one dominated by the combination of low-carbon industries and research and development (R&D) human capital and another led by low-carbon consumption awareness and economic development levels. In the later stage, the influencing factors involve a combination across micro, meso, and macro levels, reflecting an increasingly diversified and intricate configuration. The regional industrial structure consistently plays a dominant role, while awareness of low-carbon consumption has grown over time. This study not only enhances our understanding of the underlying mechanisms but also provides practical policy recommendations for local governments to tailor their strategies for effective low-carbon transformation.

Construction and Application of Regional Carbon Performance Evaluation Index System: The Case of Chinese Provinces

As global warming becomes increasingly severe, reducing carbon emissions and promoting low-carbon development has become an international consensus. Against this backdrop, evaluating regional carbon performance helps better understand the carbon emission status, emission reduction capabilities, and low-carbon development levels, providing a scientific basis for formulating targeted carbon emission reduction policies. This study constructed a “5E” regional carbon performance evaluation index system from five dimensions: economy, effectiveness, efficiency, environmentality, and equity. Then, this study evaluated and analyzed the carbon performance of 30 provinces in China from 2008 to 2021 using the entropy weight TOPSIS method. The research results indicated that (1) during the sample period, China’s carbon performance ranged from 0.416 to 0.504, exhibiting a steady upward trend; the highest score among the first-level indicators was Effectiveness, while the lowest was Economy; (2) in terms of carbon performance among China’s three major regions, it showed a decreasing pattern from east to west, with the growth potential of the central and western regions being greater than that of the eastern region; (3) in 2033, the carbon performance of China in the eastern region, the central region, and the western region will reach 0.602, 0.612, 0.613, and 0.582, respectively. A carbon performance evaluation carries significant practical and strategic implications. Our study can provide a reference for policymakers to assess carbon emission performance and improve carbon management efficiency and decision-making levels.

Efficiency of green and low-carbon coordinated development for mega urban agglomerations: an empirical study

As a critical engine for national economic growth, mega urban agglomerations have significant scale effects and economic and environmental spillover effects. This paper aims to study the green and low-carbon coordinated development of mega urban agglomerations to evaluate the country’s level of ecological civilization and its green and low-carbon development. The traditional research on green and low-carbon urban development tends to homogenize the redistribution theme, leading to significant errors in spatial allocation. This results in a lower accuracy of spatial distribution calculations for green development. Additionally, the research is constrained by data precision and methodology, making it challenging to measure the spatial differences in green and low-carbon development within urban clusters at the block level. This limitation hinders the ability to conduct detailed studies on the efficiency variations of green and low-carbon development in urban clusters. To achieve this aim, the study adopts the DPSR framework of the economic, resource, social, and ecological environment complex system and focuses on the Guangdong-Hong Kong-Macao Greater Bay Area in China. The study uses the entropy method, Gini coefficient method, and non-expected output super-efficiency SBM model to analyze the spatial effects and development efficiency of green and low-carbon development in this region from 2006 to 2020. The study results indicate that: (1) the overall level of green and low-carbon development in the Greater Bay Area is on the rise, with Shenzhen, Guangzhou, Foshan, and Zhuhai showing more stable development than other cities. Foreign direct investment and fixed asset investment in science and technology have significantly promoted green and low-carbon development. (2) The spatial differences in the region’s level of green and low-carbon development have narrowed trends, mainly due to differences between regions. However, well-developed cities such as Guangzhou and Shenzhen have taken the initiative to lead the development of other cities, fully leveraging their advantages in science and technology, geographical location, and other resources to promote the improvement of the external orientation of other cities. (3) The overall development efficiency of green and low-carbon in the Greater Bay Area is on the rise, with Guangzhou region showing overall stability, and Shenzhen region and Zhuhai region experiencing multiple ups and downs in their development. The three sub-regions show significant differences, but the balance and coordination of development have significantly improved. Finally, this study provides theoretical support for the future green and low-carbon development of urban clusters. It is advantageous for integrating the mainstream policy analysis framework of environmental economics with the complex adaptive systems of urban clusters. The research expands the boundaries of existing theoretical studies and offers new methodological approaches for interdisciplinary research. The study achieves a balance between the opportunity effects of green and low-carbon development and environmental policy constraints in super large urban clusters, effectively enhancing resource utilization efficiency in these clusters.

Impacts of urban scale on low-carbon development: evidence from 265 cities in China

Introduction: With rapid urbanization and increasing greenhouse effect, low-carbon development is the integral factor of achieving sustainable development.Methods: A comprehensive analysis framework is built to quantify the impact of urban scale on low-carbon development and we conduct empirical research on 265 cities during 2009–2019.Results and Discussion: We find that: first, urban scale can significantly promote low-carbon development and this finding still holds after the robustness test. Specifically, for every 1% increase in urban scale, the low-carbon development level of the urban increases by 0.128%; second, urban scale promotes low-carbon development mainly through three paths: efficiency improvement, industrial structure upgrading, and innovation; third, there is heterogeneity in this effect among cities with different city levels, city structures, and traffic conditions. Therefore, we propose specific, targeted policy implications, including reducing restrictions on the expansion of large cities and promoting high-tech development.

Simulation of Development Strategies and Evaluation of Low-Carbon Development Level in Jiangsu Province under Carbon Peaking and Carbon Neutrality Goals

Studies on regional low-carbon development are essential for reducing air pollution, protecting human life and health, and environmental sustainability. In this article, after sorting the connotations of low-carbon development, the low-carbon development evaluation indicators system was constructed, and the entropy weighting method and improved analytic hierarchy process were applied to evaluate the low-carbon development level between 2007 and 2021 about Jiangsu Province, China. Also, the system dynamics model was constructed to simulate the low-carbon development process. The research findings show the following: (1) Low-carbon development in Jiangsu Province obtained some achievement; (2) “Coordination force” played the most crucial role in low-carbon development, while “growth force” and “transformation force” performed better; (3) The simulation results showed that the economic development type would be the most beneficial in the long run; the energy conservation type would be steadily developing and improving every year; and the green transformation type had a clear drive for low-carbon development at an early stage and the impact was rapid. The novelty of this paper includes the following: (1) The dimension division of the index system is novel; (2) The measurement method is novel. The weights of indicators are determined by a combination of the entropy weighting method and improved analytic hierarchy process; (3) The low-carbon development pathways of Jiangsu Province are studied by the system dynamics model. Different strategy conditions are innovatively designed, and simulations of the scenarios are carried out.

Evaluation for the effect of low-carbon city pilot policy: evidence from industry in China.

The investigation of the implementation effect of the low-carbon city pilot (LCCP) policy in promoting industrial low-carbon development is important for economic growth and carbon reduction in China. This paper takes the industry sector as an independent investigation object, and aims to examine the effectiveness of the policy in improving industrial low-carbon development. The industrial total factor carbon emission efficiency index (ITFCEE) is constructed to measure the level of industrial low-carbon development by the global frontier directional distance function. From the perspective of the multiple participants of the policy, we analyze the mechanisms of the policy, and construct the time-varying difference-in-difference model to test how LCCP policy impacts the ITFCEE. We conclude that (1) LCCP policy improves significantly the ITFCEE. (2) Heterogeneity analysis results show that the positive influence of LCCP policy is significant in cities with high industrial carbon emission intensity, high industrial structure upgrading, and high government expenditure. (3) The result of the mechanism analysis is that LCCP policy can benefit the ITFCEE by promoting enterprise green technology innovation, public environment concern, government technology support, and administrative regulation.

Possibilities for mitigating the Matthew effect in low-carbon development: Insights from convergence analysis

Under global pressure of climate change, adopting an economic model of low-carbon development has become an inevitable choice for economies worldwide. Playing an important role in economics and carbon emission reduction, cities are crucial in development strategies planning at both national and regional levels. Based on the data of 198 prefecture-level cities in China from 2003 to 2019, this paper quantifies the low-carbon development index for each city, and analyzes the low-carbon development trend within cities using the club convergence method, and finally identifies the relevant factors influencing the low-carbon developmentby taking into account the divergent trends. The study found that: (1) The national low-carbon development index does not exhibit spontaneous convergence. (2) Cities ultimately fall into four converging clubs. Club 1 tends to converge toward a high level of low-carbon development, while Clubs 2, 3, and 4 tend to converge toward lower levels or may fail to achieve low carbon development, resulting in a widening gap with Club 1. This implies the existence of the Matthew effect. (3) Factors such as the financial interrelations ratio, foreign direct investment, urbanization, employment figures, and transportation enhancements can promote low-carbon development and alleviate the Matthew effect.

Evaluation of Green and Low-Carbon Development Level of Chinese Provinces Based on Sustainable Development Goals

Green and low-carbon development are important initiatives to promote the realization of the Sustainable Development Goals (SDGs). In this study, a systematic evaluation method for regional green and low-carbon development levels was established by referring to the evaluation methods of other literature. The evaluation method includes assessing the overall green and low-carbon development levels of the evaluation objects, as well as analyzing the coupling coordination of the two subsystems of green development and low-carbon development. The results show that China’s green low-carbon development level shows a rising trend year by year from 2012 to 2021, but there is still much space for progress. As for 2021, 2 provinces are in the Fair stage, 25 provinces are in the Accepted stage, and 4 provinces are in the Good stage. Provinces with higher levels of green and low-carbon development are characterized by spatial clustering, and the level of green and low-carbon development in the southeast coastal provinces is significantly higher than that in the northwest inland provinces. This study measures the coupling coordination degree of the two subsystems of green development and low-carbon development in each province. The average coupling coordination degree of China’s green and low-carbon development shows a rising trend year by year from 2012 to 2021. By 2021, the coupling coordination degree of China’s 29 provinces belongs to the High level type, and only two provinces belong to the Low level type. This study provides a provincial map of China’s green and low-carbon development levels and a distribution map of the coupling coordination degree of the green and low-carbon development subsystems, which provides support for an in-depth understanding of the spatial–temporal distribution of and development trends in China’s green and low-carbon development level. This study provides support for a deeper understanding of the spatial and temporal distribution and development trend of China’s green and low-carbon development level. The study also provides data to support China’s efforts to promote synergies in reducing pollution and carbon emissions.

The multi-stage evaluation framework for low-carbon development level of rail transit under probabilistic linguistic environment

The scientific evaluation of the low-carbon development level of rail transits is an important prerequisite for their scientific low-carbon transformation, and how to scientifically evaluate it is a problem that needs to be studied. This article first constructs an evaluation index system that includes 4 evaluation attributes and 11 evaluation criteria based on the reality of low-carbon development in rail transit. Then, aiming at the uncertainty of evaluation information and the fluctuation of evaluation results in the evaluation of low-carbon development of rail transits, a multi-stage evaluation model is constructed based on probabilistic linguistic term set, TOPSIS model principle and multi-stage decision theory. The above evaluation index system and evaluation model together constitute a multi-stage evaluation framework for low carbon development level of rail transits. The results of the case study show that the evaluation index system can provide scientific guidance for the low-carbon development level evaluation of rail transits, and the multi-stage evaluation model can improve the robustness and reduce the fluctuation of the evaluation results, so as to improve the scientificity of the evaluation results.

A quantitative simulation and verification of the sustainable and low-carbon development efficiency curves for Beijing–Tianjin–Hebei urban agglomeration

The Beijing–Tianjin–Hebei urban agglomeration (BTHUA) has experienced ecological and environmental issues due to its rapid development and expansion, including air and water pollution. Examining inter-regional plans for sustainable and low-carbon sustainable development is crucial and practical for achieving ecological balance among regions and fostering the BTHUA’s commitment to collaborative innovation. This study applies the three-stage data envelopment analysis (DEA) model to 13 cities in the BTHUA between 2007 and 2020 to compute the sustainable and low-carbon development efficiency (SLE) and index, and then constructs a fundamental model of urban agglomeration growth. In this study, MATLAB software was used to predict the general evolution trend and development curve for the BTHUA’s low-carbon and green economy development. The results of the study indicate (1) the efficiency of sustainable and low-carbon development in the BTHUA has a wave-like ascending tendency, generating an overall development pattern that is centred on core cities and eventually descends toward the periphery. (2) In recent years, coordination between sustainable and low-carbon development indices and development levels within BTHUA has largely improved; however, a changing nonlinear relationship exists between the sustainable and low-carbon efficiency index and development levels. (3) The BTHUA’s sustainable and low-carbon development curve displays a tendency that is consistent with the function model’s anticipated evolution trend.

A hybrid approach for low-carbon transportation system analysis: integrating CRITIC-DEMATEL and deep learning features.

As supply chains, logistics, and transportation activities continue to play a significant role in China's economic and social developments, concerns around energy consumption and carbon emissions are becoming increasingly prevalent. In light of sustainable development goals and the trend toward sustainable or green transportation, there is a need to minimize the environmental impact of these activities. To address this need, the government of China has made efforts to promote low-carbon transportation systems. This study aims to assess the development of low-carbon transportation systems in a case study in China using a hybrid approach based on the Criteria Importance Through Intercriteria Correlation (CRITIC), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and deep learning features. The proposed method provides an accurate quantitative assessment of low-carbon transportation development levels, identifies the key influencing factors, and sorts out the inner connection among the factors. The CRITIC weight matrix is used to obtain the weight ratio, reducing the subjective color of the DEMATEL method. The weighting results are then corrected using an artificial neural network to make the weighting more accurate and objective. To validate our hybrid method, a numerical example in China is applied, and sensitivity analysis is conducted to show the impact of our main parameters and analyze the efficiency of our hybrid method. Overall, the proposed approach offers a novel method for assessing low-carbon transportation development and identifying key factors in China. The results of this study can be used to inform policy and decision-making to promote sustainable transportation systems in China and beyond.

Summary of Research on Low-carbon Development of the Construction Industry under the "Dual Carbon" Goal

As an important pillar industry of the national economy, the construction industry is facing a transformation from resource dependent to green and low-carbon development. This article elaborates on the current research status at home and abroad from three aspects: the connotation of low-carbon development in the construction industry, the factors affecting carbon emissions in the construction industry, and the evaluation of low-carbon development level in the construction industry.

Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries

The severity of the global climate issue is rising, primarily as a result of excessive carbon dioxide emissions. Climate change is a global problem. How to reduce carbon dioxide emissions while promoting social and economic development is a problem that all countries need to face. This study examines global carbon emission efficiency in order to make recommendations for comprehensively improving global low-carbon development level. We extend the research scale of carbon emission efficiency from countries, regions, economic belts and sectors to the world, which can show the differences of countries and has theoretical guiding significance for global low-carbon development. This study calculates the carbon emission efficiency for 136 countries from 2000 to 2019 using the Super-EBM model. The discussion that follows examines the temporal and spatial characteristics of carbon emissions efficiency in 136 countries from the perspective of countries, developed and developing countries, and regions. Finally, the Tobit model is used to comprehensively analyze the factors that affect carbon emission efficiency. The results show that: (1) There are great differences in carbon emission efficiency among countries and regions. Only a few countries reach the production frontier, mainly in Europe, which are Switzerland, Luxembourg, Iraq, Norway, Denmark and the United Kingdom. The carbon emission efficiency of most countries is not ideal, being mainly concentrated in Asia and Africa, and has not achieved significant improvement over time. Asia has the lowest carbon emission efficiency. Mongolia, Ukraine, Iran, Angola, Belarus and Uzbekistan are the key governance areas for global energy conservation and carbon emissions reduction. (2) Developed countries have the much higher average carbon emission efficiency than developing countries. Combined with the industrial development stages of developed and developing countries, this is in line with the environmental Kuznets curve (EKC) hypothesis. The average carbon emission efficiency gap between developing and developed countries shows a trend of “first narrowing and then widening”, which demonstrates that developing countries' reliance on energy input to boost their economies will improve carbon emission efficiency, but only temporarily. (3) Urbanization level, foreign trade and proportion of renewable energy effectively improve the carbon emission efficiency, while industrial structure and proportion of electricity users have an inhibitory effect on the carbon emission efficiency. Global low-carbon development should be hastened by strengthening international cooperation, optimizing industrial structure, promoting urbanization and foreign trade, and adjusting the energy structure.

Promote Carbon Peaking and Carbon Neutrality with The Concept of Global Warming and Carbon Emission Reduction

To achieve peak carbon neutrality, the authors propose an approach based on the concept of global warming carbon reduction. Based on the concepts of "existing carbon economy" and "low-carbon city", the author summarizes the research on low-carbon evaluation indicators at home and abroad and selects the Hierarchical Process (AHP) as an example. This has been proven by many studies. From 2013 to 2020, calculate and evaluate the low-carbon development level of Province A, and analyze the low-carbon development level of 11 provincial-level cities. Display: From 2013 to 2020, the low-carbon development index of cities in province A showed an upward trend. In 2020, the province's urbanization carbon development index reached 0.899, an increase of 41.2% over 2019 and five times that of 2020. Among them, the ecological environment index and low-carbon development index increased by 49 and 15 times respectively in the past six years, while the economic development index and social development index only increased by 5 times and 2 times respectively, it proves that while maintaining the steady growth of the social economy, province A is actively promoting the process of urban low-carbon development and has achieved table-top results. Blockchain technology can empower the digital transformation of traditional industries, optimize business processes, reduce operating costs, improve collaborative efficiency, provide a regulatory environment for carbon peaking and carbon neutrality, build a credible and efficient carbon trading platform and market, and help carbon It is of great significance to achieve the goals of neutralization and carbon peaking and the green and high-quality development of my country's economy and society.

Study on the impact of green finance on low carbon development of manufacturing industry from the perspective of multidimensional space: evidence from China.

In order to test the impact of green finance on the low-carbon development level of China's manufacturing industry, this paper takes green finance as an explanatory variable, and chooses the level of fixed asset investment in the manufacturing industry, the intensity of environmental regulations, the proportion of environmental pollution control investment, and the proportion of R&D investment as four control variables. Empirical tests are carried out on the four dependent variables, including manufacturing industry's low-carbon development level, added value growth rate, industrial structure upgrading level, and environmental protection status. The test results show that green finance is positively correlated with the low-carbon development of the manufacturing industry and the growth rate of added value, and inversely correlated with industrial structure upgrading and environmental protection; green finance supports dependent variables in the following order: low-carbon development > environmental protection > economic growth > industrial structure. It can be seen that the main role of green finance is to promote low-carbon development and environmental protection, but it is not the best tool to promote the growth rate of manufacturing industry and upgrade the level of industrial structure. In addition, due to the spillover effect of green finance in the process of promoting the development of the manufacturing industry, it is necessary to increase green financial investment in a long-term and sustained manner to gradually promote the low-carbon and sustainable development of China's manufacturing industry.

Dynamic evaluation of low-carbon development in China's power industry and the impact of carbon market policies

At the 75th session of the United Nations General Assembly, China clearly put forward the goals of "carbon peak" in 2030 and "carbon neutrality" in 2060. Achievement of carbon targets. Therefore, the goal of this paper is to analyze the low-carbon development level of China's power industry and study the impact of carbon market policies on the low-carbon development level of the power industry. Based on this, this paper first constructs the low-carbon development evaluation index system of the power industry around the connotation of low-carbon development in the power industry and uses the global principal component analysis model to measure the low-carbon development level of China's power industry. Then, the dynamic change trend and spatial distribution characteristics of the low-carbon development level of China's power industry are analyzed using kernel density estimation and the K-means clustering method. Finally, propensity score matching and difference-in-difference methods are used to analyze the impact of carbon market policies on the low-carbon development level of China's power industry. The results show that, first, the low-carbon development level of China's power industry generally shows an upward trend and a polarized development trend. Second, the low-carbon development level of China's power industry has regional effects and gradient effects. The low-carbon development level of the power industry from high to low is the eastern region, central region and western region. Third, carbon market policies can help improve the low-carbon development level of China's power industry. The research results provide some reference and guidance for the evaluation of the low-carbon development level of China's power industry and the improvement of carbon market policies.

Research on Cement Demand Forecast and Low Carbon Development Strategy in Shandong Province

The dual carbon targets and environmental quality constraints have released a clear transition signal for the green and low-carbon development of the cement industry. This study builds a CDI model based on the terminal sector forecasting method, predicts the cement demand in Shandong Province from 2020 to 2035, constructs a CO2 emission scenario in combination with green and low-carbon technical measures, uses the life-cycle assessment method to systematically simulate the CO2 emission trend of the cement industry in Shandong Province from 2020 to 2035, and discusses the low-carbon development path of the cement industry. The research shows that the overall demand for cement in Shandong Province shows a downward trend. Under the HD scenario, the cement demand has reached a historical peak of 166 Mt in 2021, and the per capita cement consumption is 1.63 t. In terms of CO2 emission structure, industrial production process CO2 accounts for 50.89–54.32%, fuel combustion CO2 accounts for 25.12–27.76%, transportation CO2 accounts for 10.65–11.36%, and electricity CO2 accounts for 9.20–10.71%. Through deepening supply-side structural reforms and implementing green and low-carbon technologies, the CO2 emissions and carbon intensity of the cement industry in Shandong Province will be significantly reduced. Under the EL scenario, CO2 emissions will be reduced from 92.96 Mt in 2020 to 56.31 Mt in 2035, the carbon intensity will be reduced from 581.32 kg/tc in 2020 to 552.32 kg/tc in 2035. In the short term, the decarbonization path of the cement industry in Shandong Province is mainly based on improving energy efficiency and comprehensive utilization of resources and energy technologies. In the long term, alternative raw materials and fuels are of great significance to improving the green and low-carbon development level of the cement industry.

The impact of digital transformation on low-carbon development of manufacturing

Objective: To measure the low-carbon development level and digital transformation degree of China’s manufacturing industry, and to examine the impact of digital transformation on low-carbon development.Methods: This paper uses Super Slack Based Measure (SBM) model and multi-regional input-output model to measure the low-carbon development level and digital transformation degree of 17 manufacturing industries in 30 provinces of China from 2012 to 2018, and uses high-dimensional fixed effect model and mediation model to study the impact of digital transformation on low-carbon development.Results: 1) During the study period, China’s manufacturing industry showed an upward trend in terms of low-carbon development level and digital transformation, but there were significant regional and industrial disparities. 2) Digital transformation can significantly promote the low-carbon development of manufacturing industry, which is still valid in the robustness test. 3) For sub-indicators, digital industrialization has the most obvious effect on the low-carbon development of manufacturing industry, and the improvement of digital development environment also has a positive impact on low-carbon development. 4) The heterogeneity analysis indicate that digital transformation has a greater impact on promoting low-carbon development of manufacturing in underdeveloped regions, and the positive effect is obvious in medium-low-energy-consuming industries, but not in high-energy-consuming industries. 5) The mechanism test shows that technological innovation is a channel for digital transformation to promote low-carbon development.Value: This paper provides empirical evidence for the environmental impact of digital transformation, and offers a scientific basis for relevant departments to formulate low-carbon development policies from the perspective of digital transformation.

A Study of the Spatial Mechanism of Financial Agglomeration Affecting Green Low-Carbon Development: Evidence from China

China has stepped into the assertive stage of transforming the economic development mode and economic growth momentum, while green and low-carbon development is undoubtedly the way to promote high-quality economic development in the new period. As the core of modern economic growth, the spatial scale concentration of finance plays a crucial role in the development of economic transformation. In this paper, the SBM-GML production index method was used to measure the green low-carbon development level of 30 provinces in China from 2003 to 2019. It also empirically examines the impact and effect of financial agglomeration on green low-carbon development from a two-dimensional perspective of time and space using a systematic generalized matrix and a spatial dynamic panel model. At the same time, the spatial spillover effects of financial agglomeration were measured using a partial differential approach combined with the mediating effect model to reveal the path of financial agglomeration on green low-carbon development. It was found that, firstly, financial agglomeration achieves green low-carbon, and high-quality development through economic growth, industrial structure upgrading, and technological innovation improvement. It also achieves the enhancement of green, low-carbon development through the dual improvement of green technological progress and green technological efficiency. Second, financial agglomeration can enhance the green low-carbon development of neighboring regions; the positive effect of financial agglomeration has a significant positive spatial spillover. Third, the relationship between financial agglomeration and green low-carbon development shows a significant inverted U-shaped relationship, i.e., short-term promotion and long-term inhibition; at present, financial agglomeration, as a whole, has not crossed the critical value but still has a promotional effect on green low-carbon development. Finally, this article points out that in order to effectively promote green, low-carbon development, China needs to continuously promote the formation and optimization of financial agglomeration and make concerted efforts in economic growth, industrial structure upgrading, and technological progress.