Theranostic nanoparticles ZIF-8@ICG for pH/NIR-responsive drug-release and NIR-guided chemo-phototherapy against non-small-cell lung cancer.

This study leverages nanotechnology by encapsulating indocyanine green (ICG) and paclitaxel (Tax) using zeolitic imidazolate frameworks-8 (ZIF-8) as a scaffold. This study aims to investigate the chemo-photothermal therapeutic potential of ZIF-8@ICG@Tax nanoparticles (NPs) in the treatment of non-small cell lung cancer (NSCLC). An "all-in-one" theranostic ZIF-8@ICG@Tax NPs was conducted by self-assembly based on electrostatic interaction. First, the photothermal effect, stability, pH responsiveness, drug release, and blood compatibility of ZIF-8@ICG@Tax were evaluated through in vitro testing. Furthermore, the hepatic and renal toxicity of ZIF-8@ICG@Tax were assessed through in vivo testing. Additionally, the anticancer effects of these nanoparticles were investigated both in vitro and in vivo. Uniform and stable chemo-photothermal ZIF-8@ICG@Tax NPs had been successfully synthesized and had outstanding drug releasing capacities. Moreover, ZIF-8@ICG@Tax NPs showed remarkable responsiveness dependent both on pH in the tumor microenvironment and NIR irradiation, allowing for targeted drug delivery and controlled drug release. NIR irradiation can enhance the tumor cell response to ZIF-8@ICG@Tax uptake, thereby promoting the anti-tumor growth in vitro and in vivo. ZIF-8@ICG@Tax and NIR irradiation have demonstrated remarkable synergistic anti-tumor growth properties compared to their individual components. This novel theranostic chemo-photothermal NPs hold great potential as a viable treatment option for NSCLC.

Inherent mechanism of digital technology application empowered corporate green innovation: Based on resource allocation perspective.

Confronted with the treacherous digital wave and the aggressive environmental challenges, digital technology and green innovation are becoming critical tools for corporations to secure a sustainable advantage. The significance of identifying the role of digital technology application on corporate green innovation has been widely debated in the extant literature. Nevertheless, few researchers have investigated the inherent mechanism between them from the resource allocation perspective. From this research gap, we construct a theoretical model of the inherent mechanism by which digital technology application affects corporate green innovation, validate it using listed corporations in China from 2011 to 2020, and further investigate the differences in their inherent mechanism triggered by property rights and industry competition. We found that digital technology application is effective in promoting corporate green innovation. Stronger green innovation effect of digital technology application in state-owned corporations and those in highly competitive industries. The inherent mechanism between them manifest in optimizing the allocation of conventional labor, expanding the scale of non-conventional labor, and enhancing investment in R&D and digital infrastructure capital. We further explored that the impact of applying digital technology to optimize conventional labor allocation, expand non-conventional labor scale, and enhance investment in R&D and digital infrastructure capital is stronger for corporations in highly competitive industries than those in lowly competitive industries. The difference is that the role of the digital technology application in boosting capital investment in R&D does not differ across corporations with different property rights. Findings provide theoretical and empirical evidence on effectively developing the digital technology application's green innovative effects.

Dynamic decomposition and regional differences of urban emergy ecological footprint in the Yangtze River Delta.

Maintaining the balance between the economy and the environment and further realizing sustainable economic development has become an important topic. The existing research has not used the emergy ecological footprint model to calculate the ecological footprint of the Yangtze River Delta, nor have they used the factor decomposition method to analyze the influencing factors affecting the ecological footprint change. The differences in the emergy ecological footprint among different provinces and cities have not been studied. This study reported the emergy ecological footprint in the Yangtze River Delta region from 2008 to 2020. The Logarithmic Mean Divisia Index model (LMDI) was constructed to decompose the change of emergy ecological footprint into the land structure, technology, economy, and population factors to screen the main influencing factors. Gini coefficient and Theil index were used to further analyze the main influencing factors which caused the differences in the footprints at regional and intra-regional levels. The results show that: (1) The fluctuation of the per capita emergy ecological footprint in the Yangtze River Delta region has decreased, while the fluctuation of the per capita emergy ecological carrying capacity has increased. However, the per capita emergy ecological deficit is still high, where the sustainable development of the regional economy is not optimistic. (2) Technology and economy are the main factors affecting the emergy ecological footprint of the Yangtze River Delta. (3) Regional differences refer to the differences between different provinces, while intra-regional differences refer to the difference between cities within the province. In the Yangtze River Delta region, the intra-regional differences are the main reasons causing the technical differences, while the regional differences are the main reasons causing the economic differences. The significance of the study is that scientific analysis of the sustainable development status and utilization degree of resources and environment are vital for realizing the sustainable development of the Yangtze River Delta region. By decomposing the factors affecting sustainable development, the regional differences of these factors could be analyzed and serve as a theoretical basis for local governments to formulate policies to minimise the emergy ecological footprint of a targeted region.

The effects of digital technology application and supply chain management on corporate circular economy: A dynamic capability view.

Developing circular economy capability has emerged as an effective response to environmental pressures on firms. The proliferation of digital technology has created uncertainty in developing corporate circular economy capability. Although research has begun to focus on the impact of digital technology application on corporate circular economy capability, empirical evidence remains absent. Simultaneously, few studies have concerned corporate circular economy capability obtained from supply chain management. The answer to the correlation between digital technology application, supply chain management, and circular economy capability is unavailable in current research. Based on a dynamic capability view, we investigate how digital technology application affects corporate circular economy capability through supply chain management regarding supply chain risk management, collaboration, and integration. This underlying mechanism was verified with 486 Chinese-listed industrial firms and the mediating model. The findings demonstrate that digital technology application and supply chain management significantly affect corporate circular economy capability. The mediating channel whereby the digital technology application provides circular economy capability can facilitate the positive impact of supply chain risk management and collaboration while undermining the adverse effects of supply chain integration. These mediating channels differentiate in heterogeneous growth firms and are more pronounced in low-growth groups. It presents an opportunity to use digital technology to reinforce the positive impact of supply chain risk management and collaboration and mitigate the negative effect of supply chain integration on circular economy capability.

Comparing the impacts of carbon tax and carbon emission trading, which regulation is more effective?

While many literatures have examined the influence of environmental regulation policy, which environmental regulation policy is more effective is still controversial. Taking China and two different economic regions as samples, we explore the effect of two popular environmental regulation policies, that is carbon tax and carbon emission trading, by a multi-regional environmental dynamic computable general equilibrium model. The results show that for the economic development, the carbon emission trading outperforms the carbon tax for the carbon emission trading will generate the lower economic cost. But for the emission reductions, the carbon tax outperforms the carbon emission trading for the total emissions from 2020 to 2030 are smallest when introducing carbon tax policy. We further study the effect of environmental regulation on different industries. It is found that the environmental regulation has a more obvious effect on energy industry, heavy industry and transport service industry.

Effect of Chinese pilots carbon emission trading scheme on enterprises' total factor productivity: The moderating role of government participation and carbon trading market efficiency.

Based on the tightening regulation of carbon emissions, China has launched the pilot carbon emission trading scheme (CETS) since 2013. There is growing empirical evidence of the actual effect of CETS to promote enterprises' productivity which is characterized by total factor productivity (TFP). However, most studies ignored the further analysis of influence mechanisms. This paper aims to explore the impact of CETS on the TFP of enterprises and discuss the mediating role of government participation and carbon trading market efficiency. Using data from A-share listed enterprises from CETS-covered enterprises, this paper employed a combination of the propensity score matching (PSM) and difference-in-differences (DID) strategies and found that the CETS has a statistically significant positive impact on the TFP of enterprises, and the positive effect has been maintained for six years since its inception. The moderation analysis indicated that: (1) two dimensions of government participation in terms of the market incentive and government supervision significantly moderate the positive impact of CETS on TFP of enterprises; (2) two dimensions of carbon trading market efficiency in terms of the market scale and liquidity significantly moderates the positive impact of CETS on TFP of enterprises. In light of Chinese pilots CETS policy, the study highlights the important moderating roles of government participation and high carbon trading market efficiency on enterprise's TFP.

Energy market integration and renewable energy development: Evidence from the European Union countries.

Based on the panel data of 20 countries in EU during the period of 2007-2019, this paper study the effect of energy market integration (EMI) on renewable energy development (RED). We develop a general equilibrium model to explain how EMI affect the RED and the role of different mechanisms. The empirical results reports that the European EMI increased both the consumption and power generation of renewable energy, which proves a significant positive effect of EMI on the RED. In line with our expectations of theoretical model, our estimates show that the increase of renewable energy consumption is mainly due to the fossil energy cost increased, technology advancement and regional environmental regulation strengthening. And the fossil energy cost is the main driven force which plays a completely mediating role between EMI and RED. Furthermore, we also observe a negative effect of FDI and industry structure on RED.

Does R&D element flow promote the spatial convergence of regional carbon efficiency?

Carbon efficiency has attracted increased attention due to the carbon neutrality goal of various responsible countries, including China. R&D element has been proved to be an effective method to promote carbon efficiency from a static perspective without considering spatial factors. However, due to regional inequality in China, the level of carbon efficiency and R&D element flow vary in different regions. If ignoring the importance of R&D element flow from a dynamic perspective and neglecting the spatial factors of carbon efficiency convergence, it may be not conducive to the improvement of carbon efficiency and its overall development. Thus, this study proposes a gravity model to figure out the specific condition of R&D element flow (including R&D personnel flow and R&D capital flow) between Chinese provinces and cities from 2009 to 2019, builds up a MinDS model with undesirable outputs to estimate carbon efficiency and analyzes the characteristics of regional carbon efficiency with kernel density estimation, and employs a spatial Durbin model to investigate the effect of R&D element flow on regional carbon efficiency convergence. The results show that, firstly, the R&D personnel flow and R&D capital flow show a gathering trend in the neighboring regions, and the flow distribution is unbalanced. Secondly, the overall regional carbon efficiency has improved at first, then decreased gradually. There are large spatial differences among Chinese regional carbon efficiency, and the carbon efficiency between provinces and cities converges. Thirdly, R&D element flow promotes regional carbon efficiency convergence. The results of this study can be useful for solving the problem of unequal regional carbon efficiency development by managing the distribution and transfer of R&D element among provinces and cities.

Chemokines in post-traumatic stress disorder: A network meta-analysis.

BACKGROUND: Previous studies on the association between chemokines concentrations and post-traumatic stress disorder (PTSD) yielded inconsistent results. Therefore, the purpose of this network meta-analysis was to summarize these results. METHODS: The databases of PubMed, Web of Science, Psyc-ARTICLES, Embase and Cochrane Library were searched for relevant articles published not later than January 15, 2020. Then, eligible studies were selected based on predefined study selection criteria. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated as group differences in chemokines concentrations. Moreover, network meta-analysis was used to rank chemokines effect values according to their respective surface under cumulative ranking curve (SUCRA) probabilities. FINDINGS: A total of 18 eligible studies that investigated the association between 9 different chemokines and PTSD were identified. They involved 1,510 patients and 2,012 controls. Results of the meta-analysis showed that the concentrations of CCL3, CCL4 and CCL5 in the PTSD patients were significantly higher than that in the controls (SMDs of 4.12, 6.11 and 1.53 respectively). However, although not statistically significant, concentrations of CCL2 tended to be lower in PTSD patients than in the controls (SMD = -0.76); whereas concentrations of CXCL12 tended to be higher in PTSD patients than in the controls (SMD = 0.37). SUCRA probabilities showed that, among all the chemokines studied, the effect of CCL5 was the highest in PTSD patients. INTERPRETATION: Concentrations of CCL3, CCL4 and CCL5 may be associated with a trauma and/or PTSD. Also, CXCL12 and CCL2 may be the underlying biomarkers for trauma and/or PTSD. Thus, future studies with large population based samples are needed to further assess these associations. In addition, future research should explore possible mechanisms underlying these associations, with the aim to develop new diagnostics for PTSD. PROSPERO CRD42019147703.

Cross-disciplinary approaches to assist with nucleic acid testing for SARS-CoV-2.

Improving the capacity of detecting positive severe acute respiratory syndrome coronavirus 2 is critical for identifying the infection of coronavirus disease 2019 (COVID-19) precisely and thereby curbing the pandemic. Cross-disciplinary approaches may improve the efficiency of COVID-19 diagnosis by compensating to some extent the limitations encountered by traditional test methods during the COVID-19 pandemic. Combining computed tomography (CT), serum-specific antibody detection, and nanopore sequencing with nucleic acid testing for individual testing may improve the accuracy of identifying COVID-19 patients. At community or even regional/national levels, the combination of pooled screening and spatial epidemiological strategies may enable the detection of early transmission of epidemics in a cost-effective way, which is also less affected by restricted access to diagnostic tests and kit supplies. This would significantly advance our capacity of curbing epidemics as soon as possible, and better prepare us for entering a new era of high-impact and high-frequency epidemics.

Chemokines in hepatocellular carcinoma: a meta-analysis.

Accumulating evidence suggests that chemokines may play an important role in the formation and mediating of the immune microenvironment of hepatocellular carcinoma (HCC). The purpose of this meta-analysis was to explore the differences in blood or tissues chemokines concentrations between HCC patients and controls. Online databases, namely PubMed, Web of Science, Embase and Cochrane Library, were systematically searched for relevant articles published on or before 15 January 2020. Standardized mean differences (SMDs) with corresponding 95% confidence intervals of the chemokines concentrations were calculated as group differences between the HCC patients and the controls. Sixty-five studies met the inclusion criteria for the meta-analysis. Altogether they consisted of 26 different chemokines compared between 5828 HCC patients and 4909 controls; and 12 different chemokines receptors compared between 2053 patients and 2285 controls. The results of meta-analysis indicated that concentrations of CCL20, CXCL8 and CXCR4 in the HCC patients were significantly higher than those in the controls (SMD of 6.18, 1.81 and 1.04, respectively). Therefore, higher concentration levels of CCL20, CXCL8 and CXCR4 may indicate the occurrence of HCC Future research should explore the putative mechanisms underlying this linkage. Meanwhile, attempts can be made to replicate the existing findings in prospective cohort populations and explore the cause-and-effect relationships pertaining to this linkage in order to develop new diagnostic and therapeutic strategies for HCC.

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The pathogenesis of autistic spectrum disorders is complicated and the exact etiology and pathogenesis remain unclear. Major advances in spatial information technology have revealed the potential of spatial information technology as an effective tool in research and treatment for children with autistic spectrum disorders. However, there are too many fragmented research topics. According to recent reports on spatial information technology, there is no precedent for the application of spatial information technology in autistic spectrum disorders in China. Space information technology analysis for autistic spectrum disorders can be divided into the following steps: pre analysis, spatial clustering analysis, spatial model analysis, and interpretation of related results. It is hopeful that the space information technology can provide proposals for the future research on the pathogenesis of autistic spectrum disorders in our country.

Salivary cortisol in post-traumatic stress disorder: a systematic review and meta-analysis.

BACKGROUND: Studies investigating salivary cortisol level as susceptibility marker for post-traumatic stress disorder (PTSD) produced inconsistent results. The aim of this study was to compare salivary cortisol concentration levels in PTSD patients with those in controls by synthesizing published data. METHODS: We did a systematic review, meta-analysis and meta-regression of studies comparing concentrations of salivary cortisol between patients with PTSD and controls. The electronic databases of PubMed, Embase, Web of Science and Psyc-ARTICLES were searched for relevant articles. A random-effects model with restricted maximum-likelihood estimator is used to synthesize the effect size (assessed by standardized mean difference). RESULTS: A total of 784 articles were identified of which 22 were included in the final analysis. A trend of lower salivary cortisol levels was found in PTSD patients when compared with the controls (SMD = - 0.28, 95% CI-0.53;-0.04, p = 0.022). Subgroup analysis showed that the salivary cortisol levels were lower in patients with PTSD than in controls in studies conducted after 2007 or in studies using saliva samples collected in the morning. CONCLUSIONS: The evidence from this meta-analysis supports that salivary samples collected in the morning consistently showed a lower salivary cortisol level in patients with PTSD than in controls, although whether salivary cortisol could be used as a diagnostic tool requires further research.

Effect of marine ecological compensation policy on coastal water pollution: Evidence from China based on a multiple period difference-in-differences approach.

With the development and utilization of marine resources, coastal water pollution has become increasingly prominent. The marine ecological compensation (MEC) is a key measure to balance the utilization of marine resources and the protection of marine environment. This paper attempts to explore the governance effect of MEC policy on coastal water pollution. Based on panel data of coastal cities in China from 2006 to 2020, a multiple period difference-in-differences (DID) model is used to estimate the impact of MEC policy on coastal water pollution. The research results show that the coastal water pollution has decreased significantly in the polit cities after implementing the MEC policy. The governance effect of MEC policy on coastal water pollution will last for three year and cover areas within a geographical distance of 200 km. The transmission mechanisms of MEC policy on coastal water pollution are the reduction of land-based sewage, marine technological progress and optimization of industrial structure. Further, this paper provides operational suggestions for strengthening the governance effect of MEC policy on coastal water pollution.

Identification of commensal gut bacterial strains with lipogenic effects contributing to NAFLD in children.

Gut microbiota is known to have a significant impact on nonalcoholic fatty liver disease (NAFLD), particularly in children with obesity. However, the specific functions of microbiota at the strain level in this population have not been fully elucidated. In this study, we successfully isolated and identified several commensal gut bacterial strains that were dominant in children with obesity and NAFLD. Among these, four novel isolates were found to have significant lipogenic effects in vitro. These strains exhibited a potential link to hepatocyte steatosis by regulating the expression of genes involved in lipid metabolism and inflammation. Moreover, a larger cohort analysis confirmed that these identified bacterial strains were enriched in the NAFLD group. The integrated analysis of these strains effectively distinguished NASH from NAFL. These four strains might serve as potential biomarkers in children with NAFLD. These findings provided new insights into the exploration of therapeutic targets for NAFLD.

Chemokines in diabetic eye disease.

BACKGROUND: Diabetic eye disease is a common micro-vascular complication of diabetes and a leading cause of decreased vision and blindness in people of working age worldwide.Although previous studies have shown that chemokines system may be a player in pathogenesis of diabetic eye disease, it is unclear which chemokines play the most important role.To date, there is no meta-analysis which has investigated the role of chemokines in diabetic eye disease.We hope this study will contribute to a better understanding of both the signaling pathways of the chemokines in the pathophysiological process, and more reliable therapeutic targets for diabetic eye disease. METHODS: Embase, PubMed, Web of Science and Cochrane Library systematically searched for relevant studies from inception to Sep 1, 2023. A random-effect model was used and standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated to summarize the associated measure between chemokines concentrations and diabetic eye disease. Network meta-analysis to rank chemokines-effect values according to ranked probabilities. RESULTS: A total of 33 different chemokines involving 11,465 subjects (6559 cases and 4906 controls) were included in the meta-analysis. Results of the meta-analysis showed that concentrations of CC and CXC chemokines in the diabetic eye disease patients were significantly higher than those in the controls. Moreover, network meta-analysis showed that the effect of CCL8, CCL2, CXCL8 and CXCL10 were ranked highest in terms of probabilities. Concentrations of CCL8, CCL2, CXCL8 and CXCL10 may be associated with diabetic eye disease, especially in diabetic retinopathy and diabetic macular edema. CONCLUSION: Our study suggests that CCL2 and CXCL8 may play key roles in pathogenesis of diabetic eye disease. Future research should explore putative mechanisms underlying these links, with the commitment to develop novel prophylactic and therapeutic for diabetic eye disease.

Integrative metabolomics highlights gut microbiota metabolites as novel NAFLD-related candidate biomarkers in children.

Altered gut microbiota and metabolites are important for non-alcoholic fatty liver disease (NAFLD) in children. We aimed to comprehensively examine the effects of gut metabolites on NAFLD progression. We performed integrative metabolomics (untargeted discovery and targeted validation) analysis of non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), and obesity in children. Fecal samples were collected from 75 subjects in the discovery cohort (25 NAFL, 25 NASH, and 25 obese control children) and 145 subjects in an independent validation cohort (53 NAFL, 39 NASH, and 53 obese control children). Among 2,491 metabolites, untargeted metabolomics revealed a complete NAFLD metabolic map containing 318 increased and 123 decreased metabolites. Then, machine learning selected 65 important metabolites that can distinguish the severity of the NAFLD. Furthermore, precision-targeted metabolomics selected 5 novel gut metabolites from 20 typical metabolites. The functionality of candidate metabolites was validated in hepatocyte cell lines. In the end, this study annotated two novel elevated pathogenic metabolites (dodecanoic acid and creatinine) and a relationship between depleted protective gut microbiota (Butyricicoccus and Alistipes), increased inflammation (IL-1ß), lipid metabolism (TG), and liver function (ALT and AST). This study demonstrates the role of novel gut metabolites (dodecanoic acid and creatinine), as the fatty acid metabolism regulator contributing to NAFLD development through its influence on inflammation and liver function. IMPORTANCE: Altered gut microbiota and metabolites are a major cause of non-alcoholic fatty liver disease (NAFLD) in children. This study demonstrated a complete gut metabolic map of children with NAFLD, containing 318 increased and 123 decreased metabolites by untargeted metabolomic. Multiple validation approaches (machine learning and targeted metabolomic) selected five novel gut metabolites for targeted metabolomics, which can distinguish NAFLD status and severity. The gut microbiota (Butyricicoccus and Alistipes) and metabolites (creatinine and dodecanoic acid) were novel biomarkers associated with impaired liver function and inflammation and validated by experiments of hepatocyte cell lines. The data provide a better understanding of the importance of gut microbiota and metabolite alterations in NAFLD, which implies that the altered gut microbiota and metabolites may represent a potential target to prevent NAFLD development.

Cultivated Enterococcus faecium B6 from children with obesity promotes nonalcoholic fatty liver disease by the bioactive metabolite tyramine.

Gut microbiota plays an essential role in nonalcoholic fatty liver disease (NAFLD). However, the contribution of individual bacterial strains and their metabolites to childhood NAFLD pathogenesis remains poorly understood. Herein, the critical bacteria in children with obesity accompanied by NAFLD were identified by microbiome analysis. Bacteria abundant in the NAFLD group were systematically assessed for their lipogenic effects. The underlying mechanisms and microbial-derived metabolites in NAFLD pathogenesis were investigated using multi-omics and LC-MS/MS analysis. The roles of the crucial metabolite in NAFLD were validated in vitro and in vivo as well as in an additional cohort. The results showed that Enterococcus spp. was enriched in children with obesity and NAFLD. The patient-derived Enterococcus faecium B6 (E. faecium B6) significantly contributed to NAFLD symptoms in mice. E. faecium B6 produced a crucial bioactive metabolite, tyramine, which probably activated PPAR-γ, leading to lipid accumulation, inflammation, and fibrosis in the liver. Moreover, these findings were successfully validated in an additional cohort. This pioneering study elucidated the important functions of cultivated E. faecium B6 and its bioactive metabolite (tyramine) in exacerbating NAFLD. These findings advance the comprehensive understanding of NAFLD pathogenesis and provide new insights for the development of microbe/metabolite-based therapeutic strategies.

Does marine ecological compensation policy have improved marine carbon emission efficiency? Evidence from coastal areas in China.

The marine ecological compensation (MEC) policy is a scheme for protecting and restoring marine ecology. The previous studies have verified that the policy has improved the marine environment, ignoring the comprehensive performance of the economy and environment. Is the MEC policy actually effective for reducing marine carbon emission considering resource input and economy output? To address the question, this paper evaluates the impact of MEC policy on marine carbon emission efficiency by introducing the multi-stage difference-in-difference with propensity score matching. The results show that the MEC policy significantly improves marine carbon emission efficiency, and the positive effects dynamically enhance over time. Low-carbon technology innovation is confirmed to play a mediating role by which the MEC policy improves marine carbon emission efficiency. Therefore, gradually popularizing the MEC policy and accelerating low-carbon technology innovation are crucial measures to improve marine carbon emission efficiency and achieve sustainable marine development.

Exploring the asymmetric effects of urbanization and trade on CO2 emissions: fresh evidence from Pakistan.

Over the past few decades, rapid or unplanned urbanization has been a major problem for developing countries, affecting the environment very badly. Pakistan is also the fifth most vulnerable country in terms of environmental impact from socio-economic activities. Mostly, this type of research has been conducted across countries. So, this study intends to analyze the role of urbanization in energy consumption, economic growth, trade, and technology in carbon emissions by evaluating data from 1985 to 2021 in the context of Pakistan. Autoregressive distributed lag (ARDL) and non-linear autoregressive distributed lag (NARDL) with Granger causality assessment are employed to experimentally examine the variables' short and long-term associations. The ARDL result demonstrates that carbon dioxide (LCO2) emissions are increased by energy consumption (LEC) and technology (LTech), while they are decreased by economic growth (LEG) and trade (LT). In NARDL, rising and falling urbanization (LU) lead to increased carbon emissions, but insignificantly. Ascending LEC leads to increased emissions, whereas descending LEC leads to reduced emissions in the context of short and long-term asymmetry. Yet, the opposite is true in the case of trade: a rise in LT decreases emissions significantly, whereas a fall in LT increases emissions insignificantly. This paper highlights the importance of international trade for a country facing these challenges. This means that LT is at the forefront of emission-reducing technology. A Granger causality analysis results show that LU and LTech are two critical determinants of LCO2 emissions. Diagnostic tests ensure the model's reliability, ensuring that it could potentially be used without adverse intent. The research concludes that in order to minimize carbon dioxide emissions, the government should encourage the adoption of low-carbon technology through international trade (the exchange or import of low-carbon products) and implement policies tailored to urbanization and energy demand.