Removal of 6-methylquinoline from shale gas wastewater using electrochemical carbon nanotubes filter.

6-Methylquinoline (6-MQ) is identified as a high-concentration organic compound pervasive in shale gas wastewater (SGW) and poses a significant risk of environmental pollution. In response, this study aimed to address these challenges by introducing an innovative electrochemical membrane constructed with multi-walled carbon nanotubes (CNTs) for the removal of 6-MQ. The investigation systematically explored the impact of voltage, initial pollutant concentration, and salinity on the performance of the electrochemical CNTs filter. It was found a positive correlation between removal efficiency and increasing voltage and salinity levels. Conversely, as the initial concentration of pollutants increased, the efficiency showed a diminishing trend. The electrochemical CNTs filter exhibited remarkable efficacy in both adsorption removal and electrochemical oxidation of 6-MQ. Notably, the CNTs membrane exhibited robust adsorption capabilities, evidenced by the sustained adsorption of 6-MQ for over 33 h. Furthermore, applying an electrochemical oxidation voltage of 3 V consistently maintained a removal rate exceeding 34.0% due to both direct and indirect oxidation, underscoring the sustained efficacy of the electrochemical membranes. Besides, real wastewater experiments, while displaying a reduction in removal efficiency compared to synthetic wastewater experiments, emphasized the substantial potential of the electrochemical CNTs filter for practical applications. This study underscores the significant promise of electrochemical membranes in addressing low molecular weight contaminants in SGW, contributing valuable insights for advancing SGW treatment strategies.

The effects of carbon trading on resident income: a theoretical and empirical study on the pilot carbon market in China.

Establishing an efficient carbon emissions trading market is a priority to achieve the goal of carbon peaking and carbon neutrality. In the context of income inequality and emissions inequality, this study examined the efficiency of carbon trading in China from the perspective of resident income. First, this paper used the Cobb-Douglas (C-D) production function to incorporate carbon intensity into the production network model and obtained the expression of household income by solving the Walras equilibrium. Secondly, this study put forward a theory that Carbon trading affects the income level of individuals. Finally, in order to test the theory, the study used the differences-in-differences (DID) method, provincial panel data from 2005 to 2019, and the quasi-natural experiment of China's carbon emissions trading pilot. The results indicated that this policy could reduce the per capita disposable income level. Further heterogeneity research showed that although the emission reduction effect was significant, the pilot policy failed to save emission reduction costs and improve residents' welfare. The low efficiency of the carbon market was mainly attributed to the insufficient liquidity of the pilot carbon market. Therefore, it not only failed to achieve efficiency but also increased unnecessary costs, which had a negative impact on income. In addition, the consumption patterns of residents and the industrial-oriented economic structure exacerbated the decline in income.

A Rare Case of Sinonasal Pleomorphic Adenoma.

Pleomorphic adenoma (PA) is the most prevalent benign tumor of the salivary glands, characterized by both epithelial and mesenchymal differentiation. It primarily originates within the parotid and submandibular glands, with only rare occurrences in the minor salivary glands. PA in the sinonasal area is extremely rare. Herein, we present a case of a 61-year-old female with a large soft tissue mass in the paranasal sinus and nasal cavity, as evidenced by computed tomography imaging. The patient suffered from repeated nasal congestion for more than 6 months. Eventually, the mass was completely resected using an endoscopic endonasal prelacrimal approach under general anesthesia. Postoperative pathological examination revealed the presence of PA in the nasal sinus.

Decomposition and decoupling research of Chinese power sector carbon emissions through the consumption accounting principle.

The Logarithmic Mean Divisia Index (LMDI) model is applied to study Chinese national and regional power sector carbon emission changes through consumption side from 2003 to 2017, and regional power sector carbon emissions are estimated through the production and consumption accounting principle. The two-factor ANOVA and one-factor ANOVA are used to compare the differences of regional power sector carbon emissions through the two principles. In addition, the Tapio decoupling analysis model is used to investigate the decoupling state between carbon emissions of power sector and the corresponding driving forces through the consumption side. There are several results: (1) Through the two different principles, regional power sector carbon emissions are statistically significant, yet national power sector carbon emissions are not statistically significant; (2) the main factors contributing to the power sector carbon emission growth are economic scale effect and income level effect, and the main restraining factors are electricity consumption carbon intensity effect and production sector electricity intensity effect; (3) the highest contribution effect to the decoupling indexes between various influencing factors and power sector carbon emissions was scale effect, and technical effect had the second largest contribution value; (4) in 2003-2017, economic scale effect was the first significant factor causing the difference of regional power sector carbon emissions, followed by production sector electricity intensity effect and electricity consumption carbon intensity through the regional decomposition analysis. Finally, this paper gives some targeted suggestions for the low-carbon development of the power sector through national and regional perspectives.

Decoupling analysis between carbon dioxide emissions and the corresponding driving forces by Chinese power industry.

This study applied the Logarithmic Mean Divisia Index (LMDI) model to analyze changes in carbon dioxide emissions by Chinese power industry from 2003 to 2017. Besides, the Tapio decoupling analysis model is applied to explore the decoupling states between power industry carbon dioxide emissions and the corresponding influence factors. Several conclusions were obtained: (1) the power industry carbon dioxide emissions only displayed a slight downward trend during 2011-2012, 2013-2014, and 2014-2015; (2) the factors promoting the growth in power industry carbon dioxide emissions are energy consumption structure effect and total power generation effect. Power generation structural effect and fossil energy conversion efficiency effect inhibit the power industry carbon dioxide emissions from increasing, but they were far from offsetting the positive contribution value brought by total power generation effect; (3) changes in carbon dioxide emissions by the power industry were not sensitive to the change of fossil energy conversion efficiency and power production structure but were sensitive to the change of total power generation; (4) the contributions of technical effect were higher than those of structural effect on the decoupling index between impact factors and power industry carbon dioxide emissions.

Regional decomposition analysis of electric carbon productivity from the perspective of production and consumption in China.

This study is concerned with the impact factors of electric carbon productivity change in China. Some influencing factors are identified by examining the time series decomposition of electric carbon productivity based on data from 2003 to 2015, where the usual Logarithmic Mean Divisia Index (LMDI) method is used but with the regional dimension taken into consideration. Moreover, this study analyzes the driving factors of electric carbon productivity change from the perspective of production and consumption in China's power industry, where the influences of power transfers among provinces, imports and exports, and transmission losses are considered. Based on the decomposition analysis of existing data in 30 provinces (including province-level municipalities), from the perspective of production, regional actual electric carbon productivity, and per capita GDP are the main influencing forces for the growth of electric carbon productivity, and the reciprocal of per capita electric carbon emissions, energy intensity, and energy emission intensity play dominate roles in the decline of electric carbon productivity. From the perspective of consumption, the main impact factors to improve electric carbon productivity are power transfers among provinces, imports and exports, the reciprocal of emission intensity of power consumption and regional electric carbon productivity, and the impact of energy consumption on thermal power generation, the proportion of thermal power to total electricity generation, and the effect of transmission losses. Finally, several conclusions are drawn that might be meaningful for the Chinese government to improve China's electric carbon productivity.