To lessen the financial burden of disaster mitigation and prevention for debris flows, along with the losses from such events, it is vital to accurately determine their susceptibility. Machine learning models are extensively utilized for the evaluation of susceptibility to debris flow disasters. While employing non-disaster data, these models sometimes exhibit randomness in selection, potentially leading to redundant information and affecting the accuracy and usefulness of the susceptibility evaluation results. Focusing on debris flow disasters in Yongji County, Jilin Province, China, this paper aims to resolve this issue by enhancing the sampling approach for non-disaster data in machine learning susceptibility assessments and proposing a susceptibility prediction model integrating information value (IV) with artificial neural network (ANN) and logistic regression (LR) models. This model underpins a high-accuracy map that showcases the distribution of debris flow disaster susceptibility. Model performance is assessed through the area under the receiver operating characteristic curve (AUC), the information gain ratio (IGR), and typical disaster point verification procedures. this website The rainfall's impact and the terrain's role in debris flow disasters were definitively demonstrated by the results, with the IV-ANN model achieving the highest accuracy in this study (AUC = 0.968). Traditional machine learning models were outperformed by the coupling model, which generated an increase of approximately 25% in economic benefit and a decrease of roughly 8% in the average disaster prevention and control investment cost. This paper, drawing from the model's susceptibility mapping, puts forward actionable strategies for disaster mitigation and control in the context of sustainable regional development. These strategies include creating monitoring systems and information platforms for improved disaster management.
Precisely determining the effect of digital economic growth on lessening carbon emissions, particularly within the overarching structure of global climate governance, is of significant importance. This measure is indispensable for the rapid development of a low-carbon economy at the national level, the swift achievement of carbon neutrality and peaking, and the creation of a shared future for all of humankind. Investigating the influence of digital economy development on carbon emissions and the underlying mechanisms, a mediating effect model is constructed using cross-country panel data from 100 countries, spanning the years 1990 to 2019. government social media The findings of the study suggest that the growth of national carbon emissions can be considerably suppressed through the development of a digital economy, with the emission reductions being positively associated with each country's economic standing. Growth in the digital economy's influence on regional carbon emissions is mediated by factors like energy sector structure and operational efficiency, and energy intensity stands out as a crucial intermediary element. Discrepancies exist in the inhibitory effect of digital economic development on carbon emissions across nations with diverse income levels, and improvements in energy structures and efficiency can lead to both energy savings and reduced emissions in middle- and high-income countries. The observations detailed above inform policy strategies for integrating the development of the digital economy with climate management, propelling national economies toward a low-carbon future and supporting China's carbon peaking targets.
The synthesis of a cellulose nanocrystal (CNC)/silica hybrid aerogel (CSA) involved a one-step sol-gel method, combining cellulose nanocrystals (CNC) with sodium silicate, and subsequently drying under atmospheric conditions. When the weight ratio of CNC to silica was 11, CSA-1 displayed a highly porous network structure, a considerable specific area of 479 square meters per gram, and a remarkable adsorption capacity for CO2 of 0.25 millimoles per gram. By impregnating CSA-1 with polyethyleneimine (PEI), its CO2 adsorption performance was boosted. surgical oncology Temperatures (70-120°C) and PEI concentrations (40-60 wt%) were scrutinized in a systematic study of CO2 adsorption on CSA-PEI. The remarkable CO2 adsorption capacity of 235 mmol g-1 was achieved by the CSA-PEI50 adsorbent at 70 degrees Celsius with a PEI concentration of 50 wt%. The adsorption kinetic models were scrutinized to understand the adsorption mechanism employed by CSA-PEI50. The adsorption of CO2 by CSA-PEI, as affected by temperature and PEI concentration, exhibited a strong correlation with the Avrami kinetic model, indicative of a multifaceted adsorption process. Within the Avrami model, fractional reaction orders were observed to span a range of 0.352 to 0.613, and the root mean square error was remarkably small. Besides, the rate-limiting kinetic study indicated that film diffusion acted as a bottleneck for the adsorption rate, and intraparticle diffusion resistance controlled the subsequent stages of the adsorption process. The CSA-PEI50's stability remained robust following ten adsorption-desorption cycles. Experimental data from this study suggest that CSA-PEI may be a suitable adsorbent for capturing CO2 from exhaust fumes.
A critical component of mitigating the environmental and health impacts of Indonesia's burgeoning automotive industry lies in the effective management of end-of-life vehicles (ELVs). However, the efficient and thorough management of ELV has been underappreciated. A qualitative study was implemented to determine the roadblocks for effective ELV management in Indonesia's automotive sector, thereby bridging the existing gap. Scrutinizing key stakeholders through in-depth interviews, coupled with a detailed SWOT analysis, allowed us to pinpoint internal and external determinants of effective electronic waste (e-waste) management. Our research points to crucial impediments, characterized by inadequate government policies and enforcement, deficient infrastructure and technological capabilities, limited public knowledge and education, and insufficient financial incentives. We also unearthed internal factors, including inadequate infrastructure, deficient strategic planning, and problems with waste management and cost collection systems. The research results dictate a complete and integrated strategy for electronic waste (e-waste) management, entailing an increased emphasis on cooperation between government, industry, and stakeholders. Proper ELV management strategies necessitate the enforcement of regulations by the government, coupled with the provision of financial incentives. End-of-life vehicle (ELV) treatment necessitates investment in technology and infrastructure by industry players to ensure its effectiveness. Indonesia's fast-moving automotive sector can benefit from sustainable ELV management policies and decisions, which can be created by policymakers by overcoming these barriers and putting our recommendations into practice. Indonesia's ELV management and sustainability strategies benefit from the insightful contributions of our study.
Despite efforts toward global fossil fuel reduction and the promotion of alternative energy sources, several countries persist in their reliance on carbon-intensive fuels to meet their energy needs. The results of prior studies concerning the relationship between financial development and CO2 emissions have proven to be inconsistent. In the wake of these factors, the study examines the impact of financial development, human capital, economic growth, and energy efficiency on carbon dioxide emissions. The panel study from 1995 to 2021 involved 13 South and East Asian (SEA) nations, and the empirical analysis employed the CS-ARDL model. Energy use, in conjunction with energy efficiency, human capital, and economic growth, reveals divergent outcomes in the empirical analysis. Economic growth has a positive bearing on CO2 emissions, in contrast to the negative impact of financial progress on CO2 emissions. Data suggests that advancements in human capital and energy efficiency contribute to a positive impact on CO2 emissions, but this correlation is not statistically significant. The correlation between CO2 emissions and policies promoting financial advancement, human capital, and energy efficiency, as per the analysis of causes and consequences, is unilateral; the inverse relationship is not anticipated. To achieve the sustainable development goals and address the policy implications revealed by these findings, financial resources and human capital development must be prioritized.
This research involved modifying and re-employing the used water filter carbon cartridge for water defluoridation. A suite of techniques including particle size analysis (PSA), Fourier transformed infrared spectroscopy (FTIR), zeta potential, pHzpc, energy-dispersive X-ray spectroscopy (EDS), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and X-ray crystallography (XRD) was employed to characterize the modified carbon. Experiments were designed to assess the adsorption capability of modified carbon, considering diverse conditions including pH (4-10), dose (1-5 g/L), contact time (0-180 minutes), temperature (25-55 °C), fluoride concentration (5-20 mg/L), and the presence of competing ions. An evaluation of fluoride adsorption onto surface-modified carbon (SM*C) included thorough studies of adsorption isotherms, kinetic parameters, thermodynamic aspects, and breakthrough behavior. Carbon's adsorption of fluoride was characterized by a Langmuir model fit (R² = 0.983) and a pseudo-second-order kinetic model (R² = 0.956). Fluoride elimination suffered a reduction due to the presence of HCO3- within the solution. Four times, the carbon was regenerated and reused, with a removal percentage increasing from 92 to 317%. The adsorption phenomenon demonstrated a release of heat. At an initial concentration of 20 mg/L, the maximum fluoride uptake capacity of SM*C reached 297 mg/g. For the successful removal of fluoride from water, the modified carbon cartridge of the filter was employed.