The impact of carbon finance on energy consumption structure: evidence from China.

As a financial innovation model to promote sustainable economic development, carbon finance promotes green and inclusive economic development by reshaping the financial system. As a big energy consumer, China has been committed to the green transformation of energy structure, and carbon finance has been regarded as an important tool to support carbon emission reduction. This paper divides carbon finance from three levels, financial macro, environmental governance, and technological development, and selects 17 indexes to measure the development level of carbon finance in China. Time series regression model and the entropy weight method (EWM) are used to analyze the impact of carbon finance on China's energy consumption structure. The empirical results show that carbon finance plays a positive role in promoting China's energy consumption structure, and developing carbon finance is conducive to the use of clean energy and the optimization of energy consumption structure in China; carbon finance can further optimize China's energy consumption structure by investing capital, resources, and technology in industries related to promoting clean energy consumption. Therefore, China should continue to develop carbon finance and promote the establishment of a unified national carbon trading market; at the same time, China should use the CCER trading mechanism to promote the development of renewable energy and enhance the endogenous driving force of energy transformation by promoting technological progress.

The relationship between individual-level socioeconomic status and preference for medical service in primary health institutions: a cross-sectional study in Jiangsu, China.

Background: While China's primary health care (PHC) system covers all citizens, the use of medical services supplied by primary health institutions (PHIs) is not at ideal levels. This study explored the impact of socioeconomic status (SES) on residents' first choice of medical services provided by PHIs. Methods: This community-based, cross-sectional study was conducted in Jiangsu Province, China, from October 2021 to March 2022. A custom-designed questionnaire was used to evaluate 4,257 adults, of whom 1,417 chose to visit a doctor when they were sick. Logistic regression was used to test the relationships among SES, other variables and the choice of medical services, and interaction effects were explored. Results: A total of 1,417 subjects were included in this study (48.7% female; mean age 44.41 ± 17.1 years). The results showed that older age (p < 0.01), rural residence (p < 0.01), a preference for part-time medical experts in PHIs (p < 0.01), and lack of coverage by basic medical insurance (p < 0.05) were associated with the first choice to use PHIs. In the multiple logistic regression model, SES was not associated with the first choice of medical services supplied by PHIs (p > 0.05), but it interacted with three variables from the Commission on Social Determinants of Health Framework (material circumstances, behaviors and biological factors, and psychosocial factors). Conclusion: Vulnerable individuals who are the target visitors to PHIs are older, live in rural areas, and suffer from chronic diseases. SES, as a single factor, did not impact whether medical services at PHIs were preferred, but it mediated relationships with other factors.

Influence of emotion on purchase intention of electric vehicles: a comparative study of consumers with different income levels.

Promoting electric vehicles (EVs) adoption has become one of the important paths for countries around the world to address climate change and accelerate the transformation of energy system for achieving sustainable development. As one of the important psychological factors, the research on the explanatory power of emotions to EVs purchase intention is still insufficient. This paper collected 400 valid questionnaires all around China. By incorporating emotions and moral norms into the Theory of Planned Behavior (TPB) model, this study used structural equation model to estimate the impact of positive anticipated emotion (PAE), negative anticipated emotion (NAE), and moral norms together with TPB elements on EVs purchase intention. In order to explore the heterogeneity effect of the above factors on EVs purchase intention among consumers of different income groups, we divided the total sample into high-income subsample and low-income subsample according to the household monthly disposable income. We concluded as follows: for the total sample, PAE has the greatest impact on EVs purchase intention, followed by attitude, NAE, and perceived behavioral control (PBC). In particular, the purchase intention of high-income consumers mainly depends on NAE, while the purchase intention of low-income consumers mainly depends on PAE. Additionally, PBC has more significant impact on EVs purchase intention of high-income group. Finally, targeted policy implications are proposed to promote EVs purchase.

Exploring the spatial pattern of renewable energy technology innovation: evidence from China.

Considering the obvious regional differences in China, research on the drivers for renewable energy technology innovation (RETI) needs to fully consider the spatial factors. Based on the expanded function of knowledge production, which includes the human capital, institutional quality, and industrial scale, and using panel data from 29 provinces during 2006-2017, this study examines the factors promoting RETI by employing spatial regression methods. The results show that RETI presents moderate spatial agglomeration and spatial heterogeneity. Human capital, enterprise R&D intensity, and research institution R&D intensity have a significant driving effect on the local RETI, and the university R&D intensity, institutional quality, and industrial scale have no significant contribution. Human capital is the most important factor driving the local RETI, and enterprise R&D intensity has the strongest spatial spillover effect on the RETI of the surrounding provinces. In addition, the R&D intensity of enterprises and research institutions can enhance the local RETI and also significantly promote RETI in surrounding provinces through the spatial spillover effect. In contrast, human capital has played a significant driving role in the local RETI, whereas its spatial spillover effect on the surrounding provinces is not obvious. Therefore, the direct and spatial spillover effects of enterprise R&D intensity and research institution R&D intensity should be fully considered in policy making. In addition, effective policies should be formulated to break the block division of human capital investment and to promote the optimized allocation of talented people in order to better promote RETI in China.

Correction to "Life-Cycle Assessment of Gingko-Wood Three-Dimensional Membrane for Wastewater Treatment".

[This corrects the article DOI: 10.1021/acsomega.9b03722.].

Life-Cycle Assessment of Gingko-Wood Three-Dimensional Membrane for Wastewater Treatment.

Forest is one of nature's most generous gifts to human beings, providing materials and shelters for all living beings with over 30% global land coverage. Apart from being sustainable, biodegradable, and renewable, wood is also extremely fascinating from the application aspect, with numerous advantages including hierarchical and macroporous structure, excellent mechanical performance, and versatile chemistry. The macroporous structure of wood is comprised of numerous long, partially aligned channels along the growth direction. This structure is suitable for a range of emerging applications, especially as a separation/membrane material. In this research, the potentiality of Gingko biloba (Gb) wood in the remediation of wastewater, contaminated with methylene blue (MB), a dye found in the industrial waters, was investigated. We report a macroporous, three-dimensional (3D) Gb-wood membrane decorated with palladium nanoparticles (Pd NPs) for efficient wastewater treatment. The efficiency of the Pd NPs/Gb-wood membrane to remove MB from a flowing aqueous solution was demonstrated. The wastewater treatment rate of the 3D Pd NPs/Gb-wood membrane can reach 0.5 L/min, with a high MB removal efficiency (>99.9%). The 3D Gb-wood macroporous membrane with partially aligned channels exhibits promising results for water treatment and is applicable for an even wider range of separation applications. In addition, the benefit of this 3D-wood membrane system for wastewater treatment was evaluated against the potential impacts on the environment and human health by employing the life-cycle assessment (LCA) approach. The LCA was carried out using the Gabi-education version with the gate-to-grave approach, including industrial wastewater, 3D-wood membrane, and electricity consumption using CML (Centrum VoorMilieukunde Leiden). From the LCA, it can be observed that wastewater filtration using this membrane exhibited a better environmental footprint due to the improved performance of the membrane in treating a higher volume of the permeate. Therefore, this filtration system had outweighed the additional environmental impact of the wastewater treatment process. The energy demand was identified as the main environmental hotspot in the LCA analysis. The analysis revealed that the energy source for electricity generation had a significant influence on the overall sustainability of this system. Additionally, the wood itself, a naturally abundant and eco-friendly material, presented zero environmental hazard to the environment during the filtration process. The experimental and environmental impact results indicate that Gb-wood can be employed as a natural and eco-friendly adsorbent material for the removal of waste from aqueous solutions.