Effects of industrial agglomeration and environmental regulation on urban ecological efficiency: evidence from 269 cities in China

Coupling coordination of new urbanization in Chinese urban agglomeration-characteristics and driving factors

The coordinated development of new urbanization (NU) in urban agglomerations (UAs) is key for promoting sustainable urban development and the way to achieve Chinese-style modernization. Based on the mechanisms of coupling and coordination of NU, the internal subsystem coupling coordination of NU was deconstructed into five dimensions-economic, population, land, social, and ecological. Using 200 cities in 19 Chinese UAs areas, the spatio-temporal evolution characteristics of the coupling coordination degree of NU (CCDNU) were analyzed, and the driving factors were analyzed from both spatial spillover effect and stratification heterogeneity. The results are as follows: (1) CCDNU has increased from moderate disorder to barely coordinated, exhibiting a spatial distribution of a higher CCDNU in the east and lower CCDNU in the west with a positive global spatial autocorrelation feature; (2) economic drive, population concentration, spatial carrying capacity, and environmental quality play facilitating roles in the CCDNU of the study region, while the spatial carrying capacity, quality of life, and environmental quality inhibit the CCDNU of neighboring regions. From the decomposition of long- and short-term effects, both direct and indirect effects of driving factors were found to accumulate significantly over time. In addition, the model results were robust after replacing the geographic distance weight matrix and excluding the extreme values; (3) the spatial carrying capacity, population concentration, and economic drive are the dominant factors affecting the CCDNU in China. The dominant driving factors of are different in different regions. Meanwhile, the interaction detection shows that the interaction of each driver exhibits a two-factor enhancement or non-linear enhancement. Based on these results, corresponding policies are recommended.

Can new urbanization and ecological environment achieve synergistic development? Empirical evidence from 63 counties in Zhejiang, China

As China's urbanization accelerates, ecological environmental issues have become increasingly prominent, and how to achieve the synergistic development of urbanization and ecological environment is worth exploring. The paper uses the Super-SBM model and the improved entropy method to calculate the ecological efficiency and the new urbanization in 63 counties in Zhejiang Province from 2000 to 2019. Furthermore, the coupling coordination degree between new urbanization and ecological efficiency is discussed with the coupling degree model, Markov chain, and spatial correlation methods, and its influencing factors are explored by the geographic detector. The results show that: (1) The development trends of new urbanization and ecological efficiency in Zhejiang Province counties both present a "U" shape. Their inflection points appeared in 2005 and 2006, respectively. The gap between counties is gradually narrowing. (2) The coupling coordination degree between new urbanization and ecological efficiency in Zhejiang Province counties also develops in a "U" shape with the minimum value appearing in 2006. Its temporal evolution is dominated by advancement towards a higher level and maintenance of the original type, with most countries advancing from General Disorder to Preliminary Coordination. There is a good positive correlation in the spatial distribution, showing significant High-High and Low-Low agglomeration. (3) In detecting the driving factors, the explanatory power of economic development, natural conditions and social conditions diminishes sequentially. The interaction groups mostly are nonlinear enhancements, and the rest are all two-factor enhancements. Social factors are the main interaction objects. (4) The empirical analysis verified the efficacy of the "Two Mountains" theory and the importance of government investment in the regional coordinated development.

Does air pollution exposure affect semen quality? Evidence from a systematic review and meta-analysis of 93,996 Chinese men

Background

Air pollution may impair male fertility, but it remains controversial whether air pollution affects semen quality until now.

Objectives

We undertake a meta-analysis to explore potential impacts of six pollutants exposure during the entire window (0-90 days prior to ejaculation) and critical windows (0-9, 10-14, and 70-90 days prior to ejaculation) on semen quality.

Methods

Seven databases were retrieved for original studies on the effects of six pollutants exposure for 90 days prior to ejaculation on semen quality. The search process does not limit the language and search date. We only included original studies that reported regression coefficients (β) with 95% confidence intervals (CIs). The β and 95% CIs were pooled using the DerSimonian-Laird random effect models.

Results

PM2.5 exposure was related with decreased total sperm number (10-14 lag days) and total motility (10-14, 70-90, and 0-90 lag days). PM10 exposure was related with reduced total sperm number (70-90 and 0-90 lag days) and total motility (0-90 lag days). NO2 exposure was related with reduced total sperm number (70-90 and 0-90 lag days). SO2 exposure was related with declined total motility (0-9, 10-14, 0-90 lag days) and total sperm number (0-90 lag days).

Conclusion

Air pollution affects semen quality making it necessary to limit exposure to air pollution for Chinese men. When implementing protective measures, it is necessary to consider the key period of sperm development.

Environmental regulation, industrial agglomeration, and marine green development efficiency: an empirical analysis from China's coastal provinces

Environmental regulation (ER) and industrial agglomeration (IA) are important factors that affect green development efficiency (GDE). However, there is a lack of studies on their relation in the context of the marine economy. This paper integrates ER, IA, and marine GDE (MGDE) into a unified analytical framework and uses balanced panel data from China's 11 coastal provinces during 2008-2019 to quantify the linear, nonlinear, and spatial spillover effects between the three using the spatial Durbin model (SDM) and threshold effect model. The results show that ER has a negative impact on local and surrounding MGDE through the direct and spatial spillover effects. IA has a positive impact on local and surrounding MGDE through direct and spatial spillover effects. The synergistic impact of ER and IA can significantly boost local and surrounding MGDE. When ER surpasses a certain threshold, it amplifies the positive impact of IA on MGDE. These findings offer theoretical and practical references for the Chinese government to formulate marine environmental governance and industrial development policies.

Development zone policy and urban carbon emissions: empirical evidence from the construction of national high-tech industrial development zones in China

As a key strategy to promote system reform, improve the investment environment, and encourage industrial agglomeration, the national high-tech industrial development zone (NHTDZ) policy in China can not only reduce energy consumption through the scale effect but also improve energy efficiency by modernizing industrial structure and fostering technological innovation, thereby alleviating environmental pollution. Existing studies, however, focus solely on the effects of NHTDZ policy on social and economic development, ignoring their impact on the ecological environment, especially carbon (CO₂) emissions that contribute to global warming. Thus, this article analyzes a panel data of 285 prefecture-level cities and above in China from 2003 to 2019 to assess the influence of NHTDZ policy on CO₂ emissions, treating the NHTDZ construction since 1988 as a quasi-natural experiment. The results indicate that the NHTDZ policy would mitigate urban carbon emissions, particularly in middle, southeastern, medium-sized, resource-based (RB), non-key environmental protection (non-KEP), and non-two control zone (non-TCZ) cities. In addition, the mediation mechanism test demonstrates that the environmental benefits of the NHTDZ policy in China are attributable to the scale effect, the structural upgrading effect, and the technology innovation effect. The NHTDZ policy would lower per capita CO₂ emissions by reducing energy consumption, upgrading industrial structure, and promoting green technology innovation.

A dynamic view of environmental regulation influence mechanism on manufacturing agglomeration-a case study of the Yangtze River Delta city cluster

Rapid development and agglomeration of manufacturing industries in China inevitably lead to serious environmental pollution problems. The government restrains development of manufacturing industries through environmental regulation policies, but this may affect manufacturing industries agglomeration. Therefore, studying the impact of environmental regulation (ER) on manufacturing agglomeration (MA) is a critical prerequisite for the sustainability of China's manufacturing industry. Based on the panel data of 41 cities in Yangtze River Delta (YRD) region of China from 2003 to 2017, this paper explores the threshold effect of ER on MA using a panel threshold model and analyzes the heterogeneity impact of ER on MA in different regions and analyzes the dynamic mechanism and contribution of each influencing factor on MA using a panel vector autoregressive model. The results show that (1) there is a double threshold effect of ER on MA, showing an inverted "U"-shaped effect of rising and then falling; there are threshold effects of ER on MA based on foreign direct investment (FDI) and economic development level (EDL). The effect of ER on MA has the threshold effect under different FDI and EDL level, in which the effect based on FDI shows an inverted "U" shape relationship of rising and then falling; the effect based on EDL shows a growing trend. (2) There are 29 cities in YRD region in the "weak regulation" or "strong regulation" stage, both of which are not conducive to MA. (3) ER has a facilitating effect on MA, but with the extension of forecast period, this facilitating effect turns into an inhibiting effect. MA is mainly influenced by itself and transportation conditions (TC). Our study can provide some insights for improving the ecological environment and promoting the development of manufacturing clusters in YRD region.

Can industrial agglomeration improve energy efficiency? Empirical evidence based on China's energy-intensive industries

With economic growth, China's energy consumption and industrial agglomeration have increased significantly. This paper uses China's provincial-level energy-intensive industries from 2004 to 2017 as the research object and employs a multi-dimensional panel fixed effect model to investigate the impact of industrial agglomeration on energy efficiency and its mechanism. Results show the following: (1) In general, industrial agglomeration and energy efficiency have a significant "inverted U-shaped" relationship, with an inflection point of 3.309. As the degree of agglomeration increases, energy efficiency first increases and then decreases, but the degree of agglomeration does not cross the inflection point. (2) The impact of industrial agglomeration on energy efficiency has regional heterogeneity. In the eastern and central regions, there is no significant non-linear relationship between industrial agglomeration and energy efficiency but a monotonous positive correlation. In the western region, industrial agglomeration has a significant "inverted U-shaped" impact on energy efficiency, with an inflection point of 3.495, but the agglomeration degree is still on the left of the inflection point, suggesting that a moderate increase in agglomeration is conducive to the improvement of energy efficiency. (3) Industrial agglomeration improves energy efficiency by increasing human capital and promoting fixed asset investment. Therefore, this paper argues that the agglomeration of energy-intensive industries in various regions should be increased to improve energy efficiency. However, it is necessary to raise the industrial threshold in the western region to prevent industrial agglomeration from crossing the inflection point.

Ecological efficiency evaluation and driving factor analysis of the coupling coordination of the logistics industry and manufacturing industry

The coupling coordination of the logistics industry and manufacturing industry is conducive to the sustainable development of logistics and manufacturing and the stability of sustainable supply chain. The logistics and manufacturing industries are not only the basic industries that support social development, but also the industries with high carbon emissions. This paper constructs the measurement system of coupling coordinating ecological efficiency of two industries based on carbon emission constraints and finds out the driving factors affecting ecological efficiency, which is of great significance to the low-carbon coordinated development of the two industries in the future. Firstly, this paper classifies the carbon emissions from the logistics industry and manufacturing industry as undesirable outputs and evaluates the ecological efficiency of the logistics industry (LEE) and manufacturing industry (MEE) in the three urban agglomerations from 2006 to 2019 by using the unexpected slacks-based measure (SBM) model. Secondly, the coupling coordination method is used to analyze the coupling coordination scheduling of industrial ecological efficiency (MLCC). Finally, the spatial econometric model is used to analyze the driving factors of the MLCC. The results show that during the study period, the coupling coordination of the three urban agglomerations continued to grow, the Pearl River Delta coupling coordination is the highest, the Yangtze River Delta coupling coordination grew the fastest, and the Beijing-Tianjin-Hebei coupling coordination grew slightly slower. The development during the 13th Five-Year Plan period is obviously faster than that during the 11th and 12th Five-Year Plan. The empirical analysis results of spatial econometrics show that the driving factors have an impact on the coupling coordination degree of the three urban agglomerations, but the significance of each factor is different. The driving factors have significant spatial heterogeneity. The three urban agglomerations should formulate low-carbon industry development policies in line with local development according to the actual situation of each region and local conditions.

Assessing the Spatiotemporal Development of Ecological Civilization for China’s Sustainable Development

The ecological civilization strategy in China has accelerated its national sustainability. However, few systematic evaluations of Chinese Ecological Civilization Construction (ECC) have provided detailed and timely information regarding estimations of the sustainable development levels. Here, we combined indicators and policies of the United Nations (UN) sustainable development goals (SDGs) with Chinese ecological civilization and built an integrated assessment system with mixed indicators for evaluating the sustainable development levels in five dimensions (i.e., economy, society, ecology, culture, and institutions). Based on the acquired sustainability index from the system, we revealed the spatiotemporal transitions at the national and provincial levels from 2005 to 2019 in China. Specifically, both the national and provincial ECC temporally increased in this period, while spatially, the development performance of ECC was differentiated across provinces and regions. In particular, sustainable trajectories in east China and coastal regions presented better than the west and inland. Moreover, we identified the different dimensional contributions between the top and bottom provinces in ECC development. The results showed that the institutional, social, and cultural dimensions created more effects than the economic and ecological dimensions. By analyzing the provincial development patterns, we recommend the comprehensive development of ECC across the five dimensions and suggest that addressing weak dimensions is a priority. The proposed system will elevate the sustainable development strategies and pave the way for the broadening of the framework’s application to other regions and countries in the future.

Research on Industrial Ecological Efficiency Evaluation and Improvement Countermeasures Based on Data-Driven Evaluations from 30 Provinces and Cities in China

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.

Assessing economic sustainability and ecological efficiency with genuine progress indicator: a case study of the Yangtze River Delta from 2000 to 2018

To achieve urban sustainability, it is critical to enhance the environment, economy, and society simultaneously. This study adopted the revised genuine progress indicator (GPI) and ecological footprint (EF) to evaluate the ecological efficiency and economic sustainability of the Yangtze River Delta from 2000 to 2018. Spatial analysis was utilized to identify spatial autocorrelation. A total of 27 cities were then partitioned through k-means cluster analysis. The results showed that GPI and ecological efficiency improved rapidly, but economic sustainability showed a downward trend. GPI and GDP had a high degree of spatial correlation, especially in Suzhou-Wuxi-Changzhou Metropolitan Area. However, no spatial correlation existed between GPI and EF. The city with high GEE can reach 3000 $/gha, indicating the city consumed 1 global hectare to create $3000 of genuine economic growth. Shanghai, Hangzhou, and Taizhou were cities with the highest level of economic sustainability and ecological efficiency. The spatiotemporal characteristics of economic sustainability and ecological efficiency revealed in this study will provide theoretical guidance for alleviating ecological pressure and promoting economic sustainable development.

Ecological efficiency of hog scale production under environmental regulation in China: based on an optimal super efficiency SBM-Malmquist-Tobit model

China's hog production is facing the dual pressures of the market and environment. A systematic analysis of the ecological efficiency (eco-efficiency) of hog cultivation is of great significance for the development of sustainability and distribution optimization in the industry. This paper investigates the eco-efficiency of hog production and the determinants of eco-efficiency in China using panel data (2004-2018). An optimal super efficiency slacks-based measure (SBM)-Malmquist-Tobit model is adopted for hog production analysis, and the empirical results show a great variation in eco-efficiency across provinces, ranging from 0.557 to 1.19 with a mean value of 0.937 in 2018. The predominant production area of hogs is found being transferred from north to south, with small- and medium-scale predominant production areas shifted from East China to Southwest China, and large-scale predominant production areas shifted from North China to South Central China. Another finding is that eco-efficiency increased by the improvement of technical efficiency. In addition, the Tobit regression results show that rural economic development, the government's investment in environmental control, the market advantage index, and transportation conditions had positive effects on the eco-efficiency; meanwhile, the forbidden policy for livestock cultivation in certain areas, the structure of the hog breeding industry, the density of slaughtered fattened hogs, and the prices of hogs had negative effects on the eco-efficiency.

Is the "pollution haven hypothesis" valid for China's carbon trading system? A re-examination based on inter-provincial carbon emission transfer

In recent years, China had released various environmental regulations in order to respond climate change and corresponding environmental issues. However, due to imbalanced economic development and industrial structure, different Chinese regions had different enforcement levels on environmental regulations, which led to the regional transfer of pollution-intensive industries. To study the regional disparities on carbon emission transfer, this paper used the propensity score matching-difference in differences method (hereinafter abbreviated as "PSM-DID") to evaluate the mechanism between carbon trading pilot policies and the transfer of pollution-intensive industries. Panel data on 30 Chinese provinces were used to test the validity of the "pollution haven hypothesis," covering the period of 2010-2018. The empirical results showed that under the constraints of established environmental regulation, the pilot policy promoted the transfer of pollution-intensive industries to a certain extent and verified the "pollution haven hypothesis"; the proportion of the secondary sector and energy industry in the pilot areas had been reduced after the pilot policy; on the contrary, the technical level and the economic development level of the pilot provinces and cities had been further improved.