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Abstract The technology heterogeneity in the construction industry causes difficulties for an unbiased evaluation of safety performance. The non-parametric and two-hierarchy frontier data envelopment analysis (DEA) model was constructed according to the inputs and outputs of China’s provincial construction industry in 2017. Safety performance and its potential as well as undesirable output potential were analyzed from the aspect of technology gap and management efficiency. The results showed that the average safety performance in China's provincial construction industry was calculated to be 0.715, which was caused by technology gap and management efficiency. Northwest China has good performance in technology gap ratio and Central China performs well in management efficiency. Meanwhile, the strategies to improve safety performance in China's provincial construction industry were developed. In addition, potential of the safety technology gap and safety management efficiency took up 70.18% and 29.82% in terms of the undesirable output control. East, Central, South and Southwest China are the main areas needing to strengthen accident prevention practice. The findings can be used to help scholars understand the condition of safety performance in China's provincial construction industry, and provide guidelines to evaluate the performance in construction safety considering production technology heterogeneity.

This work was aimed to comprehensively evaluate the potential for sustainable development of China's shale gas industry. It will contribute to the sustainable development of China's energy and economic. Factors of resource, technology, economy and environment were selected to develop the DPSIR framework evaluation indicators in system for shale gas based on the previous research. Next, The PPFCI (projection pursuit fuzzy clustering model) technique was developed by combining the projection pursuit model with a fuzzy clustering iterative model. So that it can deal with the multi-source, high-dimensional, fuzzy data of the proposed evaluation indicators. And then, the RAGA (accelerated genetic algorithm based on real coding) algorithm was developed to run the PPFCI technique. The results show that core technical capability, investment in projects of prevention of geological disasters, and ecological environment damage indicators were the key factors affecting the sustainability of China's shale gas industry. The potential for sustainable development of China's shale gas industry was relatively low. And it was unbalanced in different provinces. The potential for sustainable development of the southwest region was better than the northwest region. Among them, the development of Sichuan was more stable than Chongqing, with a 99% probability of maintaining a stable and sustainable development state, while Chongqing province has a 15%-20% probability to fluctuate towards the poles.

Abstract China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.

Abstract To empirically verify whether financial risk affects global carbon emissions, this study investigates the financial risk-emission nexus by employing a global balanced panel dataset of 62 countries over the period 2003–2018. Furthermore, we explore the mediation effect of technological innovation on the financial risk-emission nexus. Fully considering potential regional heterogeneity and asymmetry, this study further analyzes the heterogeneous and asymmetric relationships among the variables, such as the difference between regional comprehensive economic partnership countries and other countries. The empirical results indicate that: (1) a mediation effect between financial risk and global carbon emissions exists; in other words, increased financial risk not only reduces global carbon emissions directly, but can also have an indirect impact in mitigating carbon emissions by promoting technological innovation; (2) the impacts of financial risk and technological innovation on global carbon emissions show significant regional heterogeneity; and (3) financial risk and technological innovation show asymmetry across different quantiles. To be specific, technological innovation and financial risk have a significant inhibitory effect on global carbon emissions only in the 10th quantile, while promoting carbon emissions in other quantiles.

Scientifically evaluating the level of low-carbon development in terms of theoretical and practical significance is extremely important to coal enterprise groups for implementing national energy-related systems. This assessment can assist in building institutional mechanisms that are conducive for the economic development of coal business cycle and energy conservation as well as promoting the healthy development of coal enterprises to realize coal scientific development and resource utilization. First, by adopting systematic analysis method, this study builds low-carbon development evaluation index system for coal enterprise groups. Second, to determine the weight serving as guideline and criteria of the index, analytic hierarchy process (AHP) is applied using integrated linear weighted sum method to evaluate the level of low-carbon development of coal enterprise groups. Evaluation is also performed by coal enterprise groups, and the process comprises field analysis and evaluation. Finally, industrial policies are proposed regarding the development of low-carbon coal conglomerate strategies and measures. This study aims mainly to guide the low-carbon development of coal enterprise groups, solve the problem of coal mining and the destruction of ecological environment, support the conservation of raw materials and various resources, and achieve the sustainable development of the coal industry.

The upsurge in higher education is considered a key determinant for enhancing green growth. Moreover, ICT development is also the main catalyst of green growth. This research explores the role of higher education and ICT on green growth for China from 1995 to 2020. The study employs auto-regressive distributive lag (ARDL) approach for short-run and long-run estimates of green growth. The effect of higher education and ICT on green growth is significantly positive in the long run and short run. The outcomes of the empirical models reveal that financial inclusion is positively associated with green growth in both long run and short run. Moreover, renewable energy consumption is found to have a positive impact on green growth. The findings thus point to the need for policies that promote human capital and ICT infrastructure as a way of accelerating green growth.

In the light of The Paris Agreement (COP 21), global leaders reached a consensus to curtail the increase in global temperature up to 2.0 °C ideally 1.5 °C pre-industrial level. Likewise, it has become a pathway to accomplish long-term goals of achieving carbon neutrality. In this regard, this paper aims to explore the role of green process innovation and environmental orientation toward environmental performance for achieving the long-term goal of carbon neutrality. In addition, this paper also discovers a mediating role of green competitive advantage in said context. Using data from a survey among managers of equipment manufacturing sector, the study employed structural equation modeling technique and found that green process innovation, environmental orientation and green competitive advantage significantly influence environmental performance. Subsequently, mediation analysis indicated that green competitive advantage partially mediates the relation from green process innovation and environmental orientation to environmental performance. In light of the carbon neutrality targets, the study highlight that improving environmental performance through green process innovation and environmental orientation can be a way-forward for manufacturing sector to play its role to achieve carbon neutrality. The study concludes with theoretical and practical implications.

Abstract The rapid urbanization in the Belt and Road Initiative (BRI) area has aggravated the cross-regional pollution of PM2.5 and aroused concern about the conflicts between urban development and air quality. This study aims to examine the spatial-temporal PM2.5 variations in the BRI region, in which area many countries are undergoing rapid urbanization and the main field of future urbanization, to delineate the driving mechanism of PM2.5 accumulation or dissipation. Previous studies have analyzed the PM2.5 distribution at the national level, providing limited information regarding regional heterogeneity in urbanization and PM2.5 concentrations within each country. Additionally, the regional differences in the driving mechanisms of urbanization factors on PM2.5 concentrations have not been thoroughly investigated within the BRI areas. In this study, remote sensing raster data was combined with geographic grid units to examine variations in urbanization and PM2.5 within the BRI region, identifying “typical regions” where urbanization could enhance PM2.5 accumulation. The main results are as follows: i) The spatial autocorrelation of urbanization and PM2.5 concentrations has gradually strengthened, showing consistent high-value distributions in the North China Plain, Ganges Plain and indicating a synergistic growth among emerging developing regions such as China, India, and the Persian Gulf Coast. ii) The correlation between urbanization and PM2.5 concentrations exhibited a distinct trend of differentiation within the BRI regions. The influence of urbanization on PM2.5 changed from agglomeration to dispersion, forming a “typical region” category composed of ten countries, including China, India, and Morocco. iii) The three main urbanization-related factors for PM2.5 accumulation in the “typical regions” for 2005–2016 were energy pollution emission, economic activities, and human activities. By 2023, the effects of energy pollution and economic activities are expected to converge in some “typical region” countries. Targeted urban strategies and governance actions based on the different driving-types of “typical regions” in BRI have been proposed to coordinate relationship between urban construction and atmospheric environmental protection.

Under Smart Grid circumstance, the problem that the large grid system is difficult to schedule can be solved by the micro-grid. Meanwhile, the shortage of traditional energy makes the demand-supply gap enlarge and renewable energy will become the primary energy supply in the future. Therefore, the study on how to expand renewable energy in the co-generation system in micro-grid is of great significant and valuable. In this paper, the minimum total cost of the expansion plan and the improvement of micro-grid reliability are taken as the optimal goal. The expansion planning model of the wind-thermal co-generation system is established, which uses the Harmony Search (HS) and the Genetic Algorithm (GA) to simulate a micro-grid with five nodes in a decade respectively. The comparison results of the simulation results show that the expansion planning model of the co-generation system with the HS method is more feasible and effective than that with GA. Through the research on the expansion planning of wind-thermal co-generation system, it can provide the decision support and reference for the long-term expansion planning of co-generation system in micro-grid under the Smart Grid.