12th Five-Year Research Articles

An Evidential Reasoning Method of Comprehensive Evaluation of Water Quality Based on Gaussian Distribution

This study provides an evidential reasoning method for water quality evaluation based on Gaussian distribution to handle the problem of comprehensive water quality evaluation for a region across a period (multiple sections and multiple time points). The method turns the collection of observed water quality indicator values into a probability distribution of water quality grades by using the Gaussian distribution to compute the confidence assessment of water quality grades over one period. It eliminates the subjectivity involved in determining confidence levels and the problem of information loss during data fusion that arises with conventional approaches. The probability distribution of each assessment grade is then determined by repeatedly synthesizing evidence of the same water quality grade using the improved evidential reasoning synthesis rule. To avoid the subjectivity included in experience-based weight settings, principal component analysis (PCA) is utilized to calculate the weights of water quality indicators based on contribution rates and load coefficients. In the end, utility theory is presented to modify the discrete probability distribution of precise numerical expressions, offering thorough results for the evaluation of water quality and facilitating the comparison of various water quality grades. Using the Xiangjiang River Basin as a case study, the proposed evaluation method is contrasted with popular techniques for assessing water quality, including the Single-Factor Evaluation Method, the Fuzzy Comprehensive Evaluation Method, and the Evidential Reasoning Comprehensive Evaluation Method. The findings suggest that the evidence reasoning approach for evaluating water quality that is based on Gaussian distribution is more rational, accurate, and scientific. Additionally, empirical studies on the annual water quality trends in various regions, the upstream, midstream, and downstream trends, and the water quality trends during wet and dry periods are conducted using this method to assess and analyze changes in water quality in the Xiangjiang River Basin during the “11th Five-Year Plan” and “12th Five-Year Plan” periods. The analysis findings demonstrate that, even if the rate of progress has slowed, the Xiangjiang River Basin’s overall water quality has been steadily improving since management and protection measures were put in place. This shows that the preventive and control efforts implemented in the “11th Five-Year Plan” and “12th Five-Year Plan” periods were successful; nevertheless, carrying out the current tactics might only have a limited impact. As a result, more advanced and creative approaches are required to encourage the ongoing enhancement of the water quality in the Xiangjiang River Basin.

Carbon emissions and drivers across five urban agglomerations of China: Comparison between the 12th and 13th Five-Year Plan periods

Carbon emissions and drivers across five urban agglomerations of China: Comparison between the 12th and 13th Five-Year Plan periods

Artificial intelligence empowerment in China’s energy landscape: enhancing power grid investment efficiency

Against the backdrop of China’s initiative to construct a new power system focusing on new energy, optimizing power grid investment holds significant importance. This study aims to investigate whether the application of artificial intelligence (AI) contributes to power grid investment efficiency. By considering diverse factors, power grid investment efficiency in China is assessed by using a Slack-based measure model. Then we analyze the relationship between AI and power grid investment efficiency, as well as their nonlinear threshold effect. We find a notable increase in China’s power grid investment efficiency, accompanied by evident regional differences. In addition, the utilization of AI exerts a significantly positive effect on power grid investment efficiency. Particularly, such a promoting effect is more pronounced in the China Southern Power Grid cohort and remains significant during the 12th Five-Year Plan period. Moreover, grid investment exhibits a double-threshold effect, and it diminishes the contributing effect of AI on power grid investment efficiency. AI shows a single threshold effect on power grid investment efficiency as electricity sales increase, and the positive impact manifests only when electricity sales surpass a specific threshold. These insights are important for the strategic deployment of power grid projects through using AI.

What combinations drive the urban green infrastructure development in China’s Yangtze River Economic Belt? − An empirical study based on fs/QCA methodology

In cities, green infrastructure (GI) is a vital natural life support system that is intimately linked to the daily lives of citizens. High levels of Urban Green Infrastructure (UGI) can help mitigate a series of ecological problems faced by cities, which is extremely important for preserving the stability of urban ecosystems and promoting sustainable urban development. However, current research has not fully explored the influencing factors of UGI and the interaction effect between them. Therefore, in order to better explore the results of China’s proposed policy to promote GI development, data from 110 cities in China’s Yangtze River Economic Belt (YREB) region during the 12th Five-Year Plan and 13th Five-Year Plan periods were measured separately, and natural and geographic environmental conditions, quality of urban construction, level of economic development, socio-cultural development, and eco-environmental quality were selected as the influencing factors. The entropy TOPSIS was used to evaluate the development trend of UGI in the two periods of the region, and the relationship between influencing factors and UGI development was investigated through the use of fs/QCA, and the high-level development path of each city to achieve GI was explained. The results show that (1) Cities with high UGI development are mostly concentrated in economically developed areas, while cities in the YREB’s central and western regions have relatively low levels of UGI development. (2) According to the spatial and temporal differences, the factors driving the high level and non-high level of UGI development in prefecture-level cities in the YREB showed several different configurations, confirming that the development level of UGI was affected by a variety of conditions. (3) During the 12th Five-Year Plan to 13th Five-Year Plan periods, the configuration of urban high-level UGI was found to be more consistent, while the development path of non-high-level UGI is more diversified. The study explores the overall development level and trend of green infrastructure in different cities, and the citation of fs/QCA provides a better understanding of the complex mechanisms of the interactions between these variables, with a view to providing some guidance and enlightenment for enhancing the future urban UGI development and urban high-quality development in the Yangtze River Economic Belt.

Research on Optimization Design Strategies for Natural Ventilation in Living Units of Institutional Elderly Care Facilities Based on Computational Fluid Dynamics Simulation

As China transitions into a deeply aging society, the elderly population’s growth has driven a rapid increase in elderly care institutions and facilities during the “13th Five-Year Plan” period, rising by over 235% compared to the “12th Five-Year Plan”. The ongoing normalization of COVID-19 prevention measures has underscored the urgent need to improve natural ventilation in elderly care residential facilities. This study conducted empirical surveys to assess the current state of natural ventilation in typical elderly care facilities and analyzed the architectural elements influencing it. By examining the needs and preferences of the elderly for natural ventilation, two basic living space layout types were identified through typological analysis. Suitable CFD simulation software was then employed to model key elements, and effective methods to enhance ventilation were summarized. This study found that modifying the floor plan to reduce the depth of south-facing rooms to 8.4 m, relocating external openings to the center of the rooms, adjusting the ratio of ventilation openings to room area to greater than 1/12, and adding 0.5 m high windows facing internal traffic roads can significantly improve indoor ventilation while maintaining privacy. Furthermore, placing the main activity and resting areas of the elderly in well-ventilated zones with minimal drafts can enhance both comfort and ventilation effectiveness. The research provides a scientific basis and methodological guidance for the construction and renovation of elderly care residential facilities.

Impact of carbon emission trading system on green technology innovation of energy enterprises in China

China proposed establishing a carbon emission trading market in its 12th Five-Year Plan to reduce carbon dioxide emissions through market mechanisms, promote the development of science and technology and help China become an environment-friendly country. To examine the impact of carbon emission trading on green technology innovation in Chinese energy enterprises, data from 1993 to 2020 were collected from 494 A-share-listed energy enterprises. Enterprises located in the pilot area of carbon emissions trading were assigned to the treatment group, while those in the non-pilot area were assigned to the control group. The propensity-score-matching method was utilized to match the treatment group with the control group, and the resulting samples were used as the actual sample data. The difference-in-differences method was then employed to assess the net impact of carbon emission trading and investigate its effect on green technology innovation in energy enterprises. This empirical study suggested that carbon emission trading has a positive impact on green technology innovation in energy enterprises, particularly state-owned ones. Larger enterprises are more willing to engage in green technological innovation than small enterprises. Furthermore, when faced with a carbon emission trading system, ‘mature’ companies tend to pay more attention to green technology innovation than younger enterprises do. This study puts forward policy measures for establishing a national-level carbon emission market in China in the future.

The Effects of The Multi-Target Policy on Green Productivity: Evidence from China’s Fossil Fuel Power Plants

We propose the non-radial meta-frontier global Luenberger productivity index, which addresses the issues of technology heterogeneity, slack variable, and linear programming infeasibility, and decompose it based on the technology perspective and factor perspective. With the dataset of China’s power plants from 2005 to 2015, we identify the effects of the multi-targets, including energy-saving targets and [Formula: see text] reduction targets, in the 12th Five-Year Plan on green productivity encompassing all channels of effects. A [Formula: see text] increase in the average energy-saving target cumulatively increases green productivity by [Formula: see text], while a [Formula: see text] increase in the average [Formula: see text] reduction target cumulatively decreases that by [Formula: see text]. In all channels, the technology leadership effect and generation efficiency exhibit sensitivity. Differential effects of the multi-targets on state-owned versus non-stateowned plants imply significant differences in observed production technology.

Evaluation of land resources carrying capacity based on entropy weight and cloud similarity

Land is the foundation of human life and development, which is also the most important part of a country. The study of land carrying capacity is one of the important contents of land management, wherein the evaluation of land resource carrying capacity (LRCC) is an important reference for land resource planning. Aiming at the information fuzziness and uncertainty in the evaluation of LRCC, firstly, a comprehensive evaluation model based on entropy weight and normal cloud similarity was proposed, which is based on cloud model theory and combined with normal cloud similarity measurement method and entropy weight method. Secondly, taking the asphalt pavement experiment as an example for empirical analysis, the experimental results are consistent with the actual situation, which proves the feasibility and effectiveness of the proposed model. Finally, taking China’s Chongqing city as the research area, the proposed evaluation model is used to study LRCC. The research results indicate that the comprehensive carrying capacity and average carrying capacity of various systems in China’s Chongqing have been improved in the past decade. Among them, the comprehensive carrying capacity rose from the second level during the "12th Five-Year Plan" period to the third level during the "13th Five-Year Plan" period. In the future, it is necessary to focus on the improvement of soil and water resources system and economic and technological system. This conclusion reflects LRCC of Chongqing in China objectively and has a reference value for Chongqing's land planning.

The opposite innovation impacts of air and water pollution regulations: Evidence from the total emissions control policy in China

This paper uses a unique firm-level data set from China’s two most developed regions, the Yangtze River Delta (YRD) and the Pearl River Delta (PRD), to examine the effects of environmental regulations on innovation. Variations in air and water pollution reduction plans under the Total Emissions Control Policy from the 10th to the 12th Five-Year Plans (2001–2015) are explored to measure the stringency of environmental regulations faced by industrial firms. To alleviate endogeneity concerns, we calculate city-level fair pollution reduction volumes which rely only on each city’s contribution to national pollution emissions in the base years and use them as instrumental variables of reduction plans. The two-stage least square estimations reveal that while air pollution regulation (APR) motivates industrial firms to innovate, water pollution regulation (WPR) hinders firm innovation. We confirm the opposite effects by estimating the impact on entrepreneurs’ perceptions of the importance of innovation in industrial firms’ development. Heterogeneity effect analysis shows that APR also hinders innovation in heavily air-polluting industries and state-owned firms, and WPR produces a decreasing innovation-hindering effect over time, which is larger in the YRD region than in the PRD region. We interpret the opposite impacts with the fact that water pollution discharges are more equally distributed across industries than air pollution emissions, resulting in more pervasive and stringent WPR.

Using fs/QCA to explore the influencing factors of urban green infrastructure development and its combinational drivers: the case of the Yangtze River Delta region of China.

High levels of urban green infrastructure (UGI) development can help mitigate the climate, biodiversity, and habitat crises faced by cities and support the achievement of sustainable urban development. Based on the relevant data of 41 cities in the Yangtze River Delta region obtained from 2011 to 2020, this study measured the development level of natural and geographic conditions, economic development, urban construction, social and cultural development, and eco-environment quality and urban green infrastructure (UGI); evaluated the development trend of UGI in the region during the 12th Five-Year Plan and 13th Five-Year Plan by using entropy TOPSIS; and used fs/QCA to explain the high-level development path of each city toward the achievement of a green infrastructure. The results showed that (1) the development level of UGI in the Yangtze River Delta region decreases from southeast to northwest, and gradually decreases from Shanghai, Hangzhou, and other central cities. (2) There were several different configurations of high levels and non-high levels of UGI development drivers across regions, confirming the existence of multiple causality and asymmetry indices in the drivers of UGI. (3) During the "12th Five-Year Plan" and the "13th Five-Year Plan" period, the conditions needed to achieve a high level of UGI gradually became stricter, expanding from nature-social culture and urban construction-eco-environmental drivers to nature-urban construction, nature-social culture-eco-environmental, urban construction-economy-social culture-eco-environmental drivers. Research findings can provide greater guidance and implications for future sustainable urban development.

Research on the impact of carbon emission trading on GTFP

Faced with the serious environmental pollution caused by greenhouse gas emissions, the Chinese government has put forward the target of controlling greenhouse gas emissions in the 12th Five-Year Plan and adopted a series of measures. Among them, the pilot policy of carbon emission trading is an important market-oriented instrument, which aims to control carbon dioxide emissions through the market mechanism. This paper studies the impact of this policy on GTFP, using the DID model to analyze the data of 30 provinces from 2004 to 2020. The study finds that the pilot carbon emission trading policy has significantly promoted the improvement of GTFP in the pilot areas. Moreover, the impact of policies on GTFP can be realized through two mechanisms: technological innovation and industrial structure upgrading. The impact of this policy is particularly significant in the central and western regions. These conclusions are of great significance for promoting green and low-carbon transformation, reducing carbon emissions and improving relevant carbon trading policies.

Can target-based environmental regulations effectively improve city air quality? Evidence from China’s total emissions control policy

This paper uses city-planned air pollution reductions under China’s Total Emissions Control (TEC) Policy between the 10th and the 12th Five-Year Plan (FYP) periods (2001 − 2015) to estimate the atmospheric effects of target-based environmental regulations. We hypothesize with a multi-task agency model that targeted-based regulation can reduce emissions of targeted air pollution but does not necessarily improve city air quality. Our difference-in-differences framework confirms that the TEC policy reduced the emissions of a targeted air pollutant, Sulfur Dioxide (SO2), but worsened the overall city air quality. We also document that in contrast to the persistent air quality worsening effect, the SO2 emission reduction effect decreased over FYP periods but is greater in late FYP periods and more marketized areas. Moreover, the adverse air quality effect is more pronounced in cities with top leader turnovers and northern cities. These results suggest that target-based environmental regulation shifts emissions from targeted pollutants to non-targeted ones.

Convergence of Chinese urban carbon marginal abatement cost

ABSTRACT Heterogeneity in Chinese urban carbon marginal abatement cost (UCAC) is driven by an imbalance in urban economic development and resource endowments. Analysing the convergence of UCAC provides policy insights to the Chinese government for dual carbon targets and harmonizing carbon reduction efforts across regions cost-effectively. We construct a data envelopment analysis (DEA) model considering the materials balance principle (MBP) to analyse the relationship between desirable outputs and undesirable outputs in actual production processes. Furthermore, we calculate Chinese UCAC and conduct an in-depth analysis of its evolution using convergence models. The results reveal that UCAC in the central and western regions are higher than the national average, whereas, it is relatively low in the eastern region. The convergence analysis indicates that during the 12th Five-Year Plan (FYP) period, UCAC in the eastern and central regions exhibits σ convergence, whereas UCAC in the western region exhibits σ divergence during the whole sample period. We observe conditional β convergence in Chinese UCAC. This study highlights the need for the Chinese government to develop region-specific carbon reduction strategies that consider factors such as geographical location. Additionally, the convergence characteristics of UCAC provide an opportunity to establish a multi-regional carbon trading market.

The decoupling relationship between land use efficiency and carbon emissions in China: An analysis using the Socio-Ecological Systems (SES) framework

The Socio-Ecological Systems (SES) framework provides a comprehensive approach to studying the decoupling of land use efficiency (LUE) and carbon emissions (CEs), thereby supporting the transition towards low-carbon land use from a holistic social-ecological perspective. In this study, we utilized the SES framework to examine the decoupling patterns of LUE and CEs across different land use categories (agricultural, industrial, commercial, and ecological land) in 285 Chinese cities from 2007 to 2019. We found that: (1) The decoupling relationships between LUE and CEs varied across different land categories, influenced by input/output values as well as social, economic, and regulatory factors. (2) During the 12th Five-Year Plan period (2011–2015), significant decoupling between agricultural, industrial, commercial, and ecological LUEs and CEs was observed in 170 (59%), 119 (42%), 117 (41%), and 139 (49%) cities, respectively. (3) From a long-term perspective (2010–2019), all types of LUE and CEs that were initially absent in geographic agglomeration showed improvement and achieved decoupling. (4) The initial set of low-carbon pilot cities that aimed to reduce CEs showed the most success, but this advantage faded with time. Our research delves into the interactions of actors with land resources and their implications for CEs within the SES framework. Through exploring the decoupling of LUE and CEs, we provide valuable insights for actors to make strategic adjustments, enhancing societal resilience and promoting harmonious development between humans and nature in the social-ecological system.

Socio-Economic Development of Tibet in the 10th Five-Year Plan (2001–2005). Part 8

Fourth session of the 9th NPC, held in Beijing from March 5 to 15, 2001, approved the draft of the 10th five-year plan (2001–2005). The plan provided for an annual increase in China's GDP by 7 %. At the same time, the volume of the economy over five years was to increase by 40 % and amount to ¥ 12.5 trillion in 2005. Plan targets were largely met and exceeded. The average annual economic growth rate was 9.5 %, significantly higher than the world average (3.8 %). The volume of GDP in 2005 amounted to ¥ 18.2 billion.The standard of living in Tibet in the years under review was about two times lower than the Chinese average. Therefore, the region was provided with advanced growth rates of 12 % per year. The main event of the five-year plan in Tibet was the construction of the Qinghai-Tibet railway.

Construction and Significance of Comprehensive Geophysical Observatory Array in Dabie Monitoring and Forecasting Experimental Site

This paper reviews the development process of the seismic scientific experimental site at home and abroad and introduces the background, significance and construction of the the Dabie Monitoring and Prediction Experimental Site, which led by Anhui Earthquake Agency. During the 12th Five-Year Plan, the office of this experimental site was built, which is located in Lu’an Seismic Station. During the 13th Five-Year Plan, a comprehensive geophysical observation array is built, including a seismic science array, a flux-gate array, a optical-fiber array, a infra-sound array and a baseline of the gravity field at this experimental site. Through these constructions, it can not only play a important role in the study of earthquake monitoring and prediction, but also contribute to the study of the crustal structure detection, crustal strain analysis, seismic acoustic characteristics and gravity equipment calibration.

Relationship between the evaluation of agricultural scientific and technological innovation capacity and the influencing factors of green agriculture.

China has limited arable land area, and its output value is increased with enhanced agricultural inputs such as machinery, irrigation, fertilizers, and pesticides. However, this mode is accompanied by an increase in agricultural carbon emissions. With the aim to further examine the driving effect of scientific and technological innovation on economic growth and green agriculture, this study uses the Solow growth model coupled with the Cobb-Douglas production function and vector autoregressive models. Then, the agricultural scientific and technological innovation capacity in Guangdong Province during 2006-2020 is evaluated by using the contribution rate of agricultural scientific and technological progress (ASTP) as the assessment index. In addition, the carbon footprints of green agricultural indexes such as machinery, irrigation, fertilizers, and pesticides are measured to analyze the relationship between green agriculture and agricultural scientific and technological innovation capacity. Results demonstrate the gradual increase in the contribution rate of ASTP in Guangdong Province. During the 11th, 12th, and 13th Five-Year Plan periods, the rates were 65.09%, 65.94%, and 70.40%, respectively, indicating that the agricultural scientific and technological innovation ability constantly improved. Among the indexes of green agriculture, the carbon footprints of machinery have a significant impact on agricultural scientific and technological innovation, which is quickly transformed into machinery. Such innovation requires the driving force of science and technology itself, which have relatively significant and rapid effects. On the basis of the results, corresponding policy suggestions are proposed: increasing investments in scientific and technological innovation in the agricultural field, vigorously developing new energy-saving and emission reduction products and processes for fertilizers, and increasing the research and promotion of agricultural machinery. The proposed method provides good prospects for the development of agricultural production towards mechanization, intelligence, efficiency, and greenness.

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

The frequent fluctuation of pork prices has seriously affected the sustainable development of the pork industry. The accurate prediction of pork prices can not only help pork practitioners make scientific decisions but also help them to avoid market risks, which is the only way to promote the healthy development of the pork industry. Therefore, to improve the prediction accuracy of pork prices, this paper first combines the Sparrow Search Algorithm (SSA) and traditional machine learning model, Classification and Regression Trees (CART), to establish an SSA-CART optimization model for predicting pork prices. Secondly, based on the Sichuan pork price data during the 12th Five-Year Plan period, the linear correlation between piglet, corn, fattening pig feed, and pork price was measured using the Pearson correlation coefficient. Thirdly, the MAE fitness value was calculated by combining the validation set and training set, and the hyperparameter “MinLeafSize” was optimized via the SSA. Finally, a comparative analysis of the prediction performance of the White Shark Optimizer (WSO)-CART model, CART model, and Simulated Annealing (SA)-CART model demonstrated that the SSA-CART model has the best prediction of pork price (compared with a single decision tree, R2 increased by 9.236%), which is conducive to providing support for pork price prediction. The accurate prediction of pork prices with an optimized machine learning model is of great practical significance for stabilizing pig production, ensuring the sustainable growth of farmers’ income, and promoting sound economic development.

Single or pluralistic? The game and balance of China's community governance policy tools.

Policy tools embody policy concepts and are essential to achieving policy objectives. The effective allocation of policy tools directly impacts the effectiveness of community governance and determines the modernization process of grassroots governance. We aim to analyze the logic of community governance policy tool selection, and then provide assistance for the modernization of grassroots governance. We selected 100 national and provincial government work reports and 63 policy documents related to community governance during China's "12th Five-Year Plan" to "14th Five-Year Plan" period as analysis samples. And build an analysis framework based on the three dimensions of time, space, and tools. We used Nvivo.20 software for text encoding analysis. Based on the model framework, we analyze the results as follows. From the perspective of the time dimension, among the five types of policy tools, the proportion of command-type policy tools used showed a downward trend, from 88.16% in the 12th Five-Year Plan to 83.50% in the 14th Five-Year Plan. However, motivation-type and persuasion-type tools showed an upward trend, rising from 1.34% and 5.26% in the 12th Five-Year Plan period to 3.40% and 8.74% in the 14th Five-Year Plan respectively. The system-change-type policy tools decreased from 1.32% in the 12th Five-Year Plan to 0.97% in the 14th Five-Year Plan. The proportion of capacity-building-type policy tools has gradually increased from 2.63% in the 12th Five-Year Plan to 4.85% in the 14th Five-Year Plan. From the perspective of spatial dimension, apart from command and persuasion policy tools, the usage frequency of the other three types of policy tools in the three major regions all display a "growth-decline-growth" trend. From the perspective of tool dimension, command-type policy tools are dominant in China's community governance, with a cumulative frequency of 1405 times and a high proportion of 81.75%. Apart from command policy tools, persuasive policy tools and capacity-building policy tools have a relatively high proportion, with usage frequencies of 186 and 78 respectively. We found that current community governance policy tools mainly consist of command tools. However, there is a trend towards combining tools such as command, persuasion, incentive, capacity building, and system change in the future. There is a typical contradiction between instrumental rationality and value rationality, indicating an evolution from instrumental rationality to the integration of instrumental and value rationality. This study addresses the conflict of policy tools through rational guidance of values, the rational guarantee of tools, and cooperation to achieve the goal of high-quality development of community governance.

Carbon intensity constraint, economic growth pressure and China's low-carbon development

Within the context of promotion tournaments among local governments, the management of economic growth goals plays a crucial role in China's economic development. Despite China's rise as the second-largest economy globally, it has also emerged as the largest emitter of carbon emissions. Since the implementation of the 12th Five-Year Plan in 2011, the Chinese central government has made carbon intensity targets mandatory indicators for national economic development. This has prompted local governments to pursue low-carbon growth and adjust their economic growth targets (EGT) to comply with carbon intensity constraints. In this study, a sample of 282 prefecture-level cities in China is used to empirically examine the impact of carbon intensity constraints on total factor carbon emission efficiency (TCE) using the intensity difference-in-differences (DID) framework. The study also emphasizes the role of the transmission channel for economic growth pressure (EGP). The findings of the study reveal several key results. Firstly, the implementation of carbon intensity constraints leads to an average increase of 8.24% in total factor carbon emission efficiency (TCE), which is supported by robustness tests, parallel trend analysis, and placebo tests. Secondly, these constraints result in an average decrease of 0.1828 in local governments' economic growth targets (EGT) and a reduction of 0.1269 in economic growth pressure (EGP). Thirdly, cities with a higher proportion of secondary industry experience a more significant mitigation effect, although the promotion of provincial EGT hinders this effect. Fourthly, synergistic policies can effectively promote low-carbon development, and government expenditure on technology and marketization can facilitate a positive relationship between carbon intensity constraints and TCE. Lastly, the effects of carbon intensity constraints vary across the east, middle, and west regions, suggesting the presence of heterogeneity. The article proposes a shift in the assessment of lower governments by superior governments, from growth assessment to low-carbon growth assessment.