Analysis and Measurement of Barriers to Green Transformation Behavior of Resource Industries.

To effectively guide and stimulate the green transformation behavior of resource industries and promote the sustainable and high-quality development of the region, it is necessary to deeply analyze and clarify the barrier factors of the green transformation behavior of resource industries. This study measures the green transformation efficiency of the resource industries by selecting the panel data of the mining industry from 29 Chinese provinces, based on the DEA-SBM model, and employing the ideas and methods of system engineering, for the years 2012-2019. Hence, the study employs the Tobit model to verify the factors that hinder the green transformation behavior of the resource industries. The results show that the (1) resource industries' barriers against the green transformation behavior form a significant barrier effect by inhibiting the efficiency of green transformation; (2) there is a difference in the intensity of the effect of the resource industries' barriers to the green transformation behavior; (3) regional heterogeneity exists in the effects of the barriers to the green transformation behavior of the resource industries. The findings of the study can provide a scientific basis for further improving the effectiveness of policies related to the green transformation behavior of resource industries.

Panel data analysis of energy conservation and emission reduction on high-quality development of logistics industry in Yangtze River Delta of China.

With the implementation of Chinese carbon neutrality policy, the Yangtze River Delta calls for great concern. As a benchmark for the development of Chinese logistics industry, it accompanies energy consumption and environmental problems. This study explores how Chinese logistics industry can achieve energy conservation and emission reduction and high-quality development in the context of carbon neutrality. It analyzes the relationship between the logistics industry and economy, energy, as well as environment in Yangtze River Delta. The data is based on China Statistical Yearbook from 2001 to 2019, by means of the entropy method and panel vector autoregressive (PVAR) model. The main findings are summarized as follows: firstly, the economy, industrial structure, energy, and environment have significant impact on the development of logistics industry in Yangtze River Delta. Secondly, the development of logistics industry in Yangtze River Delta is not balanced. The provinces including Jiangsu, Shanghai, Zhejiang, and Anhui have great differences in economy, industrial structure, demographic dividend, energy consumption, and environmental protection, but they show the possibility of complementary advantages. Thirdly, the economic development and energy consumption have bidirectional effects. Environmental protection is relevant to economic development, industrial structure, energy consumption and logistics supply. Finally, some suggestions are provided on how to realize the high-quality development of logistics industry in Yangtze River Delta. In the context of carbon neutrality, it is necessary to consider energy conservation and emission reduction.

Intervention factors associated with environmental stressors resulting from cross-provincial transfers by coal resource-based enterprises.

The environmental stressors associated with the cross-provincial transfer of coal resource-based enterprises (CREs) have become a critical concern for the green, sustainable, and high-quality development of resource-rich areas in central and western regions. This study referred to socioeconomic statistics and carried out an interview survey, literature review, and systematic analysis to clarify the mechanism underlying environmental stressors arising from the cross-provincial transfer of CREs. The intervention factors associated with such environmental stressors were identified, and the study conducted an empirical analysis of relevant data related to the coal-resources industry in three central and western provinces in China for the period 1997-2016. Research findings: (1) The intensity ranking of the influencing factors associated with environmental stressors caused by cross-provincial transfers of CREs has certain rules. The 'level of the enterprise's investment in environmental protection' is the weakest, the 'enterprise's development mode level' is slightly stronger, the 'enterprise scale' is stronger, and 'environmental regulation' is the strongest. (2) Stricter endogenous and exogenous policy regulations for environmental governance in rich coal resource-based regions are associated with weaker negative externalities in respect of resource development and the intensity of stressors. (3) Larger CREs are associated with a better green mining capacity, environmental repair cost advantages, social constraints, self-discipline, and thus, a weaker stress effect. (4) CREs that adopt more superior modes of development that focus on the utilization of the 'three wastes' are associated with a weaker stress effect. (5) The higher the level of investment by CREs in environmental protection technology, facilities, and equipment, the weaker the stress effect. The conclusions of the study can provide a theoretical basis to assist the Chinese government to develop relevant regulations to control inter-provincial transfers by CREs and to thereby diminish environmental stressor effects.

Combination of tetrandrine and 3-n-butylphthalide protects against cerebral ischemia-reperfusion injury via ATF2/TLR4 pathway.

OBJECTIVE: Cerebral infarction (CI) is the mayor reason of death in China. Reperfusion is the only immediate treatment for acute cerebral infarction. However, blood reperfusion recovery may cause ischemia-reperfusion (I/R) injuries. The purpose of this study was to investigate the effects of Tetrandrine (TTD) and 3-n-Butylphthalide (NBP) on cerebral I/R injury. MATERIALS AND METHODS: I/R was used to establish CI model in vivo. TTD was performed to analyze cerebral infarction volume. OGD was applied to establish CI model in vitro. Flow cytometry and TUNEL assays were utilized to determine the cell death. ELISA was conducted to determine the release of cytokines. mRNA and protein expressions were detected using qRT-PCR and western blot. RESULTS: We found that NBP + TTD treatment significantly reduced cerebral infarction volume and inhibited the death of neurons in vivo. Moreover, NBP + TTD treatment suppressed the apoptosis and inflammatory response of neurons in vitro. Additionally, NBP + TTD suppressed the expression of activator transcription factor 2 (ATF2). However, overexpression of ATF2 contributed to the degeneration of neurons. Moreover, ATF2 transcriptionally activated Toll-like receptor 4 (TLR4). NBP + TTD inactivated ATF2/TLR4 signaling. CONCLUSIONS: Taken together, TTD combined with NBP protected against cerebral infarction by inhibiting the inflammatory response and neuronal cell apoptosis via inactivating ATF2/TLR4 signaling pathways. This may provide an alternative for I/R injury.

Decoupling effect and forecasting of economic growth and energy structure under the peak constraint of carbon emissions in China.

The decoupling effect between economic growth and energy structure was quantitatively analyzed from 1999 to 2014 across China. The results showed it existed weak decoupling effects in most regions. Based on the analysis of the influence of energy structure on carbon intensity, using scenario simulation methods and Markov chain modeling, the carbon intensity was predicted for China in 2020. The impact of energy structure adjustment on the carbon intensity to meet China's carbon target by 18 possible scenarios are calculated. Furthermore, the peak value of carbon emissions was also calculated in 2030. The results showed that the carbon intensity predicted for China in 2020 can be achieved regardless of whether the energy structure was adjusted or not when energy saving and carbon reduction policies maintained with economic growth at 6-7%. Moreover, given fixed energy structure growth, for each 1% of economic growth, the carbon intensity will decrease by about 3.5%. Given fixed economic growth, the decrease of energy intensity will be greater if the control of energy consumption is stronger. The effect of energy structure adjustment on the decreasing of carbon intensity will be 4% higher under constraints than without constraints. On average, the contribution of energy structure adjustment to achieving the carbon intensity target was calculated as 4% higher than that with constraints. In addition, given relatively fixed economic growth at 6-7%, the peak value of carbon emission in 2030 was calculated as 13.209 billion tons with constraints and 14.38 billion tons without constraints.

The impact of urbanization on CO2 emissions in China: an empirical study using 1980-2014 provincial data.

Towns and cities are not only the focus of attention for their consumption of energy and resources; they are also scrutinized closely for their emissions of greenhouse gases. China's urbanization level now exceeds 50%, but there is still much disparity compared with the level of urbanization in developed countries. This study selects China's urban population and carbon emissions data for the years 1980-2014 and discusses the timing and cause effect of urbanization and the corresponding carbon emissions using the Granger causality test and an error correction model (ECM) then uses STIRPAT models to extract six indicators to measure the quality of urbanization, namely, the level of urbanization, area of built-up regions, added value of tertiary industries, disposable income per capita, green areas per capita, and energy intensity. These six indicators represent population agglomeration, the expansion of urban areas, industrial agglomeration, quality of life improvements, ecological conservation, and technological improvements, respectively. The study divides 29 provinces in China into three groups based on the quality of urbanization and analyzes the impacts of the six indicators of urbanization quality on carbon emissions. The findings show that the impacts of different factors on carbon emissions vary substantially among the provinces. Finally, the study uses the findings to give suggestions on how to develop low-carbon urbanization.

Three new taxanes with the 10-alkoxy group from the heartwood of Taxus cuspidata.

Three novel taxanes with the 10-alkoxy group were isolated from heartwood of Taxus cuspidata. The structures were identified as 2alpha,14beta-diacetoxy-10beta-ethoxytaxa-11,4(20)-dien-5alpha-ol (1), 2alpha,14beta-diacetoxy-10beta-methoxytaxa-11,4(20)-dien-5alpha-ol (2), and 2alpha-acetoxy-10beta-ethoxytaxa-11,4(20)-diene-5alpha,14beta-diol (3) on the basis of spectroscopic analysis. These are the first taxanes with an alkoxy moiety on the skeleton.

New 14-hydroxy-taxane and 2alpha,20-epoxy-11(15-->1)abeotaxane from the needles of Taxus canadensis.

Two new taxanes were isolated from the needles of Taxus canadensis. Their structures were established as 10beta,13alpha-diacetoxytaxa-4(20),11-diene-5alpha,9alpha,14beta-triol (1) and 4alpha,13alpha-diacetoxy-2alpha,20-epoxy-11(15-->1)abeotaxa-11,15-diene-5alpha,7beta,9alpha,10beta-tetraol (2) on the basis of a spectroscopic analysis.

Structural determination of a new 2(3 --> 20)abeotaxane with an unusual 13beta-substitution pattern and a new 6/8/6-ring taxane from Taxus cuspidata.

A new 2(3 --> 20)abeotaxane with an unusual 13beta-substitution pattern and a new 6/8/6-ring taxane were isolated from the methanol extract of the needles of Taxus cuspidata. The structures were established as 2alpha,7beta-diacetoxy-5alpha,10beta,13beta-trihydroxy-2(3 --> 20)abeotaxa-4(20), 11-dien-9-one (1) and 2alpha,5alpha,7beta,9alpha,13alpha-pentahydroxy-10beta-acetoxytaxa-4(20),11-diene (2) on the basis of 1D and 2D NMR spectral data and high-resolution FAB-MS analyses.

A new metabolite with a new substitution pattern from the seeds of the Chinese Yew, Taxus mairei.

A new taxoid metabolite with a new substitution pattern was isolated from the methanol extract of the seeds of Taxus mairei, and its structure was established as 5alpha,15-dihydroxy-7beta,9alpha-diacetoxy-11(15-->1)abeo-taxa-4(20),11-dien-13-one (1) on the basis of spectral analysis including (1)H- and (13)C-NMR, HMQC, HMBC, NOESY, and confirmed by HR-FAB mass spectrometry.