Anionic Coordination Control in Building Cu-Based Electrocatalytic Materials for CO2 Reduction Reaction.

Renewable energy-driven conversion of CO2 to value-added fuels and chemicals via electrochemical CO2 reduction reaction (CO2RR) technology is regarded as a promising strategy with substantial environmental and economic benefits to achieve carbon neutrality. Because of its sluggish kinetics and complex reaction paths, developing robust catalytic materials with exceptional selectivity to the targeted products is one of the core issues, especially for extensively concerned Cu-based materials. Manipulating Cu species by anionic coordination is identified as an effective way to improve electrocatalytic performance, in terms of modulating active sites and regulating structural reconstruction. This review elaborates on recent discoveries and progress of Cu-based CO2RR catalytic materials enhanced by anionic coordination control, regarding reaction paths, functional mechanisms, and roles of different non-metallic anions in catalysis. Finally, the review concludes with some personal insights and provides challenges and perspectives on the utilization of this strategy to build desirable electrocatalysts.

Autophagy-related gene model as a novel risk factor for schizophrenia.

Autophagy, a cellular process where cells degrade and recycle their own components, has garnered attention for its potential role in psychiatric disorders, including schizophrenia (SCZ). This study aimed to construct and validate a new autophagy-related gene (ARG) risk model for SCZ. First, we analyzed differential expressions in the GSE38484 training set, identifying 4,754 differentially expressed genes (DEGs) between SCZ and control groups. Using the Human Autophagy Database (HADb) database, we cataloged 232 ARGs and pinpointed 80 autophagy-related DEGs (AR-DEGs) after intersecting them with DEGs. Subsequent analyses, including metascape gene annotation, pathway and process enrichment, and protein-protein interaction enrichment, were performed on the 80 AR-DEGs to delve deeper into their biological roles and associated molecular pathways. From this, we identified 34 candidate risk AR-DEGs (RAR-DEGs) and honed this list to final RAR-DEGs via a constructed and optimized logistic regression model. These genes include VAMP7, PTEN, WIPI2, PARP1, DNAJB9, SH3GLB1, ATF4, EIF4G1, EGFR, CDKN1A, CFLAR, FAS, BCL2L1 and BNIP3. Using these findings, we crafted a nomogram to predict SCZ risk for individual samples. In summary, our study offers deeper insights into SCZ's molecular pathogenesis and paves the way for innovative approaches in risk prediction, gene-targeted diagnosis, and community-based SCZ treatments.

Negative Wealth Shock and Cognitive Decline and Dementia in Middle-Aged and Older US Adults.

Importance: As a financial hardship, negative wealth shock has been implicated in some adverse health outcomes. However, associations between negative wealth shock and cognitive decline and dementia have not been examined. Objective: To investigate whether negative wealth shock was associated with cognitive decline and incident dementia among middle-aged and older US adults. Design, Setting, and Participants: The Health and Retirement Study (HRS) is a prospective cohort study conducted biennially among US adults older than 50 years. Data from the HRS from calendar years 1996 to 2020 were analyzed from July 1 to 31, 2023. The final sample included 8082 participants with complete data of interest. Exposures: Wealth status was quantified with questionnaires. Negative wealth shock was defined as a loss of 75% or more in total wealth over a 2-year period. Asset poverty was defined as zero or less total net wealth. Main Outcomes and Measures: Cognitive function was assessed with the modified Telephone Interview for Cognitive Status (TICS-m). Dementia status was determined with TICS-m scores and proxy assessment. Results: Among 8082 participants included (mean [SD] age, 63.7 [5.7] years; 4179 women [51.7%] and 3903 men [48.3%]; 1111 Black [13.7%], 6689 White [82.7%], and 282 other [3.5%]), 1441 developed incident dementia over a median follow-up time of 14 (IQR, 7-20) years. Compared with participants who had positive wealth without shock, those with negative wealth shock had accelerated cognitive decline (ß coefficient, -0.014 [95% CI, -0.027 to -0.001]; P = .03) and increased risks of dementia (hazard ratio [HR], 1.27 [95% CI, 1.11-1.46]; P < .001). Higher dementia risks were also found in participants with asset poverty at baseline (HR, 1.61 [95% CI, 1.30-2.00]; P < .001). Associations were found in White participants (HR, 1.34 [95% CI, 1.14-1.58]; P < .001) and participants younger than 65 years (HR, 1.38 [95% CI, 1.13-1.68]; P = .001) but not in other races and ethnicities or those 65 years or older. Conclusions and Relevance: In this cohort study, negative wealth shock was associated with accelerated cognitive decline and elevated risks of dementia among middle-aged and older US adults, with modifications by age and ethnicity. These findings should be confirmed by further prospective and interventional studies.

Advances of nanoparticle-mediated diagnostic and theranostic strategies for atherosclerosis.

Atherosclerotic plaque remains the primary cause of morbidity and mortality worldwide. Accurate assessment of the degree of atherosclerotic plaque is critical for predicting the risk of atherosclerotic plaque and monitoring the results after intervention. Compared with traditional technology, the imaging technologies of nanoparticles have distinct advantages and great development prospects in the identification and characterization of vulnerable atherosclerotic plaque. Here, we systematically summarize the latest advances of targeted nanoparticle approaches in the diagnosis of atherosclerotic plaque, including multimodal imaging, fluorescence imaging, photoacoustic imaging, exosome diagnosis, and highlighted the theranostic progress as a new therapeutic strategy. Finally, we discuss the major challenges that need to be addressed for future development and clinical transformation.

Regulating the Electronic Structure of Ni Sites in Ni(OH)2 by Ce Doping and Cu(OH)2 Coupling to Boost 5-Hydroxymethylfurfural Oxidation Performance.

Biomass is a sustainable and renewable resource that can be converted into valuable chemicals, reducing the demand for fossil energy. 5-Hydroxymethylfurfural (HMF), as an important biomass platform molecule, can be converted to high-value-added 2,5-furandicarboxylic acid (FDCA) via a green and renewable electrocatalytic oxidation route under mild reaction conditions, but efficient electrocatalysts are still lacking. Herein, we rationally fabricate a novel self-supported electrocatalyst of core-shell-structured copper hydroxide nanowires@cerium-doped nickel hydroxide nanosheets composite nanowires on a copper mesh (CuH_NWs@Ce:NiH_NSs/Cu) for electrocatalytically oxidizing HMF to FDCA. The integrated configuration of composite nanowires with rich interstitial spaces between them facilitates fast mass/electron transfer, improved conductivity, and complete exposure of active sites. The doping of Ce ions in nickel hydroxide nanosheets (NiH_NSs) and the coupling of copper hydroxide nanowires (CuH_NWs) regulate the electronic structure of the Ni active sites and optimize the adsorption strength of the active sites to the reactant, meanwhile promoting the generation of strong oxidation agents of Ni3+ species, thereby resulting in improved electrocatalytic activity. Consequently, the optimal CuH_NWs@Ce:NiH_NSs/Cu electrocatalyst is able to achieve a HMF conversion of 98.5% with a FDCA yield of 97.9% and a Faradaic efficiency of 98.0% at a low constant potential of 1.45 V versus reversible hydrogen electrode. Meanwhile, no activity attenuation can be found after 15 successive cycling tests. Such electrocatalytic performance suppresses most of the reported Cu-based and Ni-based electrocatalysts. This work highlights the importance of structure and doping engineering strategies for the rational fabrication of high-performance electrocatalysts for biomass upgrading.

Cathepsin D Plays a Vital Role in Macrobrachium nipponense of Ovary Maturation: Identification, Characterization, and Function Analysis.

The oriental river prawn Macrobrachium nipponense is an economically important aquacultural species. However, its aquaculture is negatively impacted by the rapid sexual maturation of female M. nipponense. The fast sexual maturation produces a large number of offspring which leads to a reduction in resilience, a low survival rate, and an increased risk of hypoxia, this in turn, seriously affects the economic benefits of prawn farming. Cathepsin D is a lysosomal protease involved in the ovarian maturation of M. nipponense. In the current study, the cDNA of the gene encoding cathepsin D (Mn-CTSD) was cloned from M. nipponense. The total length was 2391 bp and consisted of an open reading frame (ORF) of 1158 bp encoding 385 amino acids. Sequence analysis confirmed the presence of conserved N-glycosylation sites and characteristic sequences of nondigestive cathepsin D. The qPCR analysis indicated that Mn-CTSD was highly expressed in all tissues tested, most significantly in the ovaries, whereas in situ hybridization showed that expression occurred mainly in oocyte nuclei. Analysis of its expression during development showed that Mn-CTSD peaked during the O-IV stage of ovarian maturation. For the RNAi interference experiment, female M. nipponense specimens in the ovary stage I were selected. Injection of Mn-CTSD double-stranded (ds)RNA into female M. nipponense decreased the expression of Mn-CTSD in the ovaries, such that the Gonad Somatic Index (GSI) of the experimental group was significantly lower than that of the control group (1.79% versus 4.57%; p < 0.05). Ovary development reached the O-III stage in 80% of the control group, compared with 0% in the experimental group. These results suggest that Mn-CTSD dsRNA inhibits ovarian maturation in M. nipponense, highlighting its important role in ovarian maturation in this species and suggesting an approach to controlling ovarian maturation during M. nipponense aquaculture.

A Novel Legumain-Like Protease in Macrobrachium nipponense: Identification, Characterization, and Function Analysis in Ovary Maturation.

Legumain, also called aspartic endopeptidase (AEP), is a member of the cysteine protease family and is involved in various physiological processes. In this study, we analyzed the characteristics of a novel legumain-like (named Mn-Lel) in the female oriental river prawn, Macrobrachium nipponense, which is involved in ovary maturation. The Mn-Lel is 1,454 bp in length, including a 1,290-bp open reading frame that encodes 430 amino acids. qPCR analysis indicated that Mn-Lel is specifically highly expressed in the hepatopancreas and ovaries of female prawns. It is rarely expressed in embryogenesis, weakly expressed in early larval development stages, and then significantly increased after metamorphosis, which indicated that Mn-Lel is not a maternal gene and mainly plays a role in adults. During the different ovarian stages, Mn-Lel expression in the hepatopancreas had no obvious rules, while its expression in the ovaries had a significant peak in stage III. In situ hybridization studies revealed that Mn-Lel is localized in the oocyte of the ovary. Changes in the gonadosomatic index confirmed the inhibitory effects of Mn-Lel dsRNA on ovary maturation. These results suggest that Mn-Lel has a key role in promoting ovary maturation.

Air pollution control and enterprise competitiveness - A re-examination based on China's Clean Air Action.

The "Air Pollution Prevention and Control Action Plan" is regarded as China's war against air pollution, which is also noted as China's Clean Air Action (CAA policy). Although abundant studies have focused on the impact of CAA policy on social activities, such as air quality, pollutants emission, and economic output, limited studies explore its impact on enterprise competitiveness from a more micro perspective. Improving total factor productivity (TFP) is essential to achieve economic efficiency and sustainable development. Identifying the impact and influence mechanism of the CAA policy on TFP is important for China to realize the coordinated development of environment and economy and promote high-quality economic development. Based on the difference-in-differences model, this paper evaluates the impact of the CAA policy on enterprise productivity. The empirical analysis shows that there is a significantly negative effect from the CAA policy to the TFP of polluting enterprises, indicating that the CAA policy has decreased enterprise productivity. Our finding is robust, after conducting several robustness tests, such as replacing different dependent indicators, adopting different policy measurement variables, considering other policy interventions and using propensity score matching. Besides, this paper also discusses the possible heterogeneities. This paper adds additional empirical evidence to understand the relationship between air pollution control and enterprise competitiveness. The conclusions of this paper have important practical significance for China to further promote air pollution control and perfect the environmental control system.

Gender Differences in Mental Health Disorder and Substance Abuse of Chinese International College Students During the COVID-19 Pandemic.

Introduction: The outbreak of coronavirus disease has negatively impacted college students' mental health across the world. In addition, substance abuse also is trouble among these students. This study aims to find the gender difference in Chinese international college students' mental health and substance abuse during the COVID-19 pandemic. Method: We conducted an online survey using PHQ-9, GAD-7, and several questions related to substance abuse frequency, self-injury, and suicidal thoughts, 535 male and 475 female Chinese international college students whose ages ranged from 18 to 23 years old (x = 20.19, SD = 1.50) were recruited during the epidemic. We utilized t-test and binary logistic regression in our study to find out the difference and statistical significance between substance abuse issues and mental health problems across gender. Results: Both male and female Chinese international college students had statistical significance with self-injury ideas and behaviors (t = -2.21, p < 0.05). Furthermore, the male college students with anxiety problems had positive statistical significance with medicine (OR = 3.47, 95%CI = 1.45-8.30, p < 0.01) and negative statistical significance with drinks (OR = 0.23, 95%CI = 0.08-0.65, p < 0.01). While for female college students with an anxiety problem, they had positive statistical significance with medicine (OR = 4.88, 95%CI = 1.53-15.57, p < 0.01), drugs (OR = 4.48, 95%CI = 1.41-14.25, p < 0.05) and cigarettes (OR = 6.63, 95%CI = 1.95-22.57, p < 0.01) and negative statistical significance with drinks (OR = 0.18, 95%CI = -0.05 to 0.65, p < 0.01). Conclusion: This is the first cross-sectional study focusing on the Chinese international college students' mental health and substance abuse problems during the COVID-19 pandemic. We found that Chinese international college students' mental health and substance abuse situation has been negatively influenced during this period. In addition, the self-injury ideas and behaviors also showed a high tendency for these students. The findings of our study also highlight the need to find more interventions and preventions to solve the different mental health and substance abuse problems for college students, especially for female Chinese international college students.

Numerical Simulation on Seismic Behavior of Steel Fiber Reinforced Concrete Beam-Column Joints.

Steel fiber reinforced concrete (SFRC) is a novel material of concrete, which has a great potential to be used in practical engineering. Based on the finite element software Opensees, the main objective of this paper presented a numerical simulation method on investigating the seismic behavior of SFRC-beam-column joints (BCJs) through modifying the calculation method of joint shear and longitudinal reinforcement slip deformations. The feasibility and accuracy of the numerical modeling method were verified by comparing the computed results with experimental data in terms of the hysteresis curves, skeleton curves, feature points, energy dissipation, and stiffness degradation. And then, the influences of some key parameters on the seismic behavior of BCJs were investigated and discussed in detail. The parametric studies clearly illustrated that both adding the steel fiber and increasing the stirrup amount of joint core area could significantly improve the seismic behavior of BCJs. The axial compression ratio had limited influence on the seismic behavior of BCJs. Finally, based on the main factors (steel fiber volume ratio, stirrup amount, and axial compression ratio), a formula for predicting ultimate shear capacity is derived.

Seismic Performance of Steel Fiber Reinforced High-Strength Concrete Beam-Column Joints.

In high-strength concrete, the reinforcement concentration will cause some problems in the beam-column joints (BCJs) due to a large amount of transverse reinforcement. Hence, the main object of this paper is to prevent the reinforcement concentration and reduce the amount of transverse reinforcement in the BCJs through the ideal usage of steel fibers and reinforced high-strength concrete. Pseudo-static tests on seven specimens were carried out to investigate and evaluate the seismic performance of beam-column joints in steel fiber reinforced high-strength concrete (SFRHC). Test variables were steel fiber volume ratio, concrete strength, the stirrup ratio in the core area, and an axial compression ratio of the column end. During the test, the hysteresis curves and failure mode were recorded. The seismic indicators, such as energy dissipation, ductility, strength, and stiffness degradation, were determined. The experimental results indicated that the failure modes of SFRHC beam-column joints mainly included the core area failure and the beam end bending failure. With the increase in stirrup ratio, volume ratio of steel fiber, and axial compression ratio in the core area, both the ductility and energy consumption of beam-column joints increased, while the opposite was true for concrete strength.

Predicting Progression of COVID-19 Infection to Prioritize Medical Resource Allocation: A Novel Triage Model Based on Patient Characteristics and Symptoms at Presentation.

Background: The COVID-19 global pandemic has posed unprecedented challenges to health care systems all over the world. The speed of the viral spread results in a tsunami of patients, which begs for a reliable screening tool using readily available data to predict disease progression. Methods: Multicenter retrospective cohort study was performed to develop and validate a triage model. Patient demographic and non-laboratory clinical data were recorded. Using only the data from Zhongnan Hospital, step-wise multivariable logistic regression was performed, and a prognostic nomogram was constructed based on the independent variables identifies. The discrimination and calibration of the model were validated. External independent validation was performed to further address the utility of this model using data from Jinyintan Hospital. Results: A total of 716 confirmed COVID-19 cases from Zhongnan Hospital were included for model construction. Men, increased age, fever, hypertension, cardio-cerebrovascular disease, dyspnea, cough, and myalgia are independent risk factors for disease progression. External independent validation was carried out in a cohort with 201 cases from Jinyintan Hospital. The area under the curve (AUC) was 0.787 (95% confidence interval [CI]: 0.747-0.827) in the training group and 0.704 (95% CI: 0.632-0.777) in the validation group. Conclusions: We developed a novel triage model based on basic and clinical data. Our model could be used as a pragmatic screening aid to allow for cost efficient screening to be carried out such as over the phone, which may reduce disease propagation through limiting unnecessary contact. This may help allocation of limited medical resources.

Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory impairment. Previous studies have largely focused on alterations of static brain activity occurring in patients with AD. Few studies to date have explored the characteristics of dynamic brain activity in cognitive impairment, and their predictive ability in AD patients. METHODS: One hundred and eleven AD patients, 29 MCI patients, and 73 healthy controls (HC) were recruited. The dynamic amplitude of low-frequency fluctuation (dALFF) and the dynamic fraction amplitude of low-frequency fluctuation (dfALFF) were used to assess the temporal variability of local brain activity in patients with AD or mild cognitive impairment (MCI). Pearson's correlation coefficients were calculated between the metrics and subjects' behavioral scores. RESULTS: The results of analysis of variance indicated that the AD, MCI, and HC groups showed significant variability of dALFF in the cerebellar posterior and middle temporal lobes. In AD patients, these brain regions had high dALFF variability. Significant dfALFF variability was found between the three groups in the left calcarine cortex and white matter. The AD group showed lower dfALFF than the MCI group in the left calcarine cortex. CONCLUSIONS: Compared to HC, AD patients were found to have increased dALFF variability in the cerebellar posterior and temporal lobes. This abnormal pattern may diminish the capacity of the cerebellum and temporal lobes to participate in the cerebrocerebellar circuits and default mode network (DMN), which regulate cognition and emotion in AD. The findings above indicate that the analysis of dALFF and dfALFF based on functional magnetic resonance imaging data may give a new insight into the neurophysiological mechanisms of AD.

EEG power spectral analysis reveals tandospirone improves anxiety symptoms in patients with Alzheimer's disease: a prospective cohort study.

BACKGROUND: To study the efficacy of tandospirone citrate in treating Alzheimer's disease (AD) patients with anxiety. METHODS: Thirty mild-to-moderate AD patients with anxiety symptoms were randomly divided into a monotherapy group (donepezil) and a combination therapy group (donepezil and tandospirone). The treatment lasted for 12 weeks. Drug efficacy was regularly assessed using psychological assessment scales and quantitative pharmaco-electroencephalogram (QPEEG) power spectral analysis. RESULTS: After 12 weeks of treatment, the mean Hamilton Anxiety Scale (HAMA) score and mean Neuropsychiatric Inventory (NPI) score of the combination therapy group were 5.13±4.18 and 4.2±5.0, respectively, which was significantly lower compared to baseline and the monotherapy group (all P<0.05). The mean attention score on the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) was 0.07±0.26 for the combination group, which was significantly lower than that of the monotherapy group (P<0.05). QPEEG revealed that the power values of the δ wave in the right prefrontal lobe, left middle temporal lobe and right posterior temporal lobe decreased in the combination therapy group but not in the monotherapy group. Similarly, the power values of the α2 wave in the right parietal, right posterior temporal and left middle temporal lobes, and the ß1 wave power values of left middle temporal and left posterior temporal lobes were also significantly decreased in the combination therapy group, but not in the monotherapy group. CONCLUSIONS: Tandospirone citrate can significantly improve anxiety symptoms and attention in patients with mild to moderate AD. QPEEG examination might provide a objective way for the efficacy of the tandospirone in anxiety symptoms of the patients with Alzheimer's disease.

Disrupted balance of long and short-range functional connectivity density in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients: a resting-state fMRI study.

BACKGROUND: Alzheimer's disease (AD) is an age-progressive neurodegenerative disorder that affects cognitive function. There have been several functional connectivity (FC) strengths; however, FC density needs more development in AD. Therefore, this study wanted to determine the alternations in resting-state functional connectivity density (FCD) induced by Alzheimer's and mild cognitive impairment (MCI). METHODS: One hundred and eleven AD patients, 29 MCI patients, and 73 healthy controls (age- and sex-matched) were recruited and assessed using resting-state functional magnetic resonance imaging (MRI) scanning. The ultra-fast graph theory called FCD mapping was used to calculate the voxel-wise short- and long-range FCD values of the brain. We performed voxel-based between-group comparisons of FCD values to show the cerebral regions with significant FCD alterations. We performed Pearson's correlation analyses between aberrant functional connectivity densities and several clinical variables with adjustment for age and sex. RESULTS: Patients with cognition decline showed significantly abnormal long-range FCD in the cerebellum crus I, right insula, left inferior frontal gyrus, left superior frontal gyrus, left inferior frontal gyrus, and right middle frontal gyrus. The short-range FCD changed in the cerebellum crus I, left inferior frontal gyrus, left superior occipital gyrus, and right middle frontal gyrus. The long- and short-range functional connectivity in the left inferior frontal gyrus was positively correlated with Mini-mental State Examination (MMSE) scores. CONCLUSIONS: FCD in the identified regions reflects mechanism and compensation for loss of cognitive function. These findings could improve the pathology of AD and MCI and supply a neuroimaging marker for AD and MCI.

Molecular Characterization of a Novel Cathepsin L in Macrobrachium nipponense and Its Function in Ovary Maturation.

Cathepsin L genes, which belonged to cysteine proteases, were a series of multifunctional protease and played important roles in a lot of pathological and physiological processes. In this study, we analyzed the characteristics a cathepsin L (named Mn-CL2) in the female oriental river prawn, Macrobrachium nipponense which was involved in ovary maturation. The Mn-CL2 was1,582 bp in length, including a 978 bp open reading frame that encoded 326 amino acids. The Mn-CL2 was classified into the cathepsin L group by phylogenetic analysis. Real-time PCR (qPCR) analysis indicated that Mn-CL2 was highly expressed in the hepatopancreas and ovaries of female prawns. During the different ovarian stages, Mn-CL2 expression in the hepatopancreas and ovaries peaked before ovarian maturation. In situ hybridization studies revealed that Mn-CL2 was localized in the oocyte of the ovary. Injection of Mn-CL2 dsRNA significantly reduced the expression of vitellogenin. Changes in the gonad somatic index also confirmed the inhibitory effects of Mn-CL2 dsRNA on ovary maturation. These results suggest that Mn-CL2 has a key role in promoting ovary maturation.

Preparation of Syringaldehyde from Lignin by Catalytic Oxidation of Perovskite-Type Oxides.

The influence of different reaction conditions on the yield of syringaldehyde was studied by using perovskite oxide as the catalyst. The optimal reaction conditions are as follows: 0.60 g of dealkali lignin, 0.60 g of 5 wt % theta ring-loaded LaFe0.2Cu0.8O3 catalyst, 30 mL of 1.0 mol/L NaOH solution, 160 °C reaction temperature, 0.80 MPa O2 pressure, and 2.5 h reaction time. Under these conditions, the highest syringaldehyde yield was 10.00%. The recycling performance of the catalyst was studied. It was found by XRD analysis that the catalyst maintained high catalytic activity after four times of use.

Policy effect of the Clean Air Action on green development in Chinese cities.

The Clean Air Action is considered an important measure to control air pollution. Despite extensive studies on the benefits or the cost of the Clean Air Action, the overall effect of such an action on green development is largely unknown. This paper tries to fill this gap. Based on panel data of 278 Chinese cities, this paper begins with the construction of a comprehensive indicator, namely green production efficiency, to reflect the green development over the period 2011 to 2016, we then implement the quasi-difference-in-differences framework to identify the policy effect of the Clean Air Action on green development. The following findings are obtained: (1) The Clean Air Action has enhanced the green development of Chinese cities, especially in areas with relatively high reduction target and rich resource endowment; (2) The dynamic analysis reveals that the positive effect of the Clean Air Action on green development presents an intensifying trend with time. This paper provides new insights to understand the Clean Air Action, based on these findings, we propose that future policies should focus on the transformation of overall green development and take full account of regional heterogeneity.

Determinants of renewable energy technological innovation in China under CO2 emissions constraint.

Renewable energy is not only an efficient way to ensure energy independence and security but also supports the transition to a low carbon economy and society. The progress of renewable energy technological innovation is an important factor that influences the development of renewable energy. An in-depth analysis of the driving factors that influence this progress is crucial to China's energy transition. Based on Chinese provincial data over 2000-2015 and panel data models, this paper regards the CO2 emissions as climate change and explores the response of renewable energy technological innovation to intensive CO2 emissions. We also analyze the effect of the driving factors such as energy price and R&D investment on this innovation process. The main conclusions drawn are: (1) There are significant differences in technological innovation levels across China's provinces. (2) We observe that the intensive CO2 emissions have promoted renewable energy technological innovation level, meaning that innovation process responds actively to climate changes. (3) R&D investment from government and enterprise both are conducive for promoting the innovation level. (4) Energy price has an insignificant effect on innovation in renewable energy technologies and we attribute this to the unreasonable energy price mechanism. This paper provides clear evidence for understanding the role of innovation on climate change.

The role of renewable energy technological innovation on climate change: Empirical evidence from China.

To develop renewable energy as well as promote China's transition to a low-carbon economy, the government needs to pay attention to renewable energy technological innovation (RETI). Using China's provincial panel data from 2000 to 2015, and regarding the CO2 emissions as the proxy of climate change, this paper identifies the relationship between RETI and CO2 emissions as well as seeks to confirm the role of RETI on climate change. The linear regression model confirms that the RETI has a significant negative effect on CO2 emissions. In addition, considering the disparities of energy structure, the impacts of RETI on CO2 emissions may be distinct. We, therefore, construct a panel threshold model by taking into account the distinct effect of RETI under different energy structure. We find that the effect of RETI on curbing CO2 emissions decreases with the rising of coal-dominated energy consumption structure but in contrast, this effect increases with the growing proportion of renewable energy generation. This paper provides new insight into the relationship between technological innovation and climate change. Based on these findings, some relevant policy recommendations are proposed.