Agricultural carbon emission is an important cause of climate change, and the carbon transfer caused by agricultural trade is a key area related to carbon emissions of all countries. Based on the Eora database, this paper aims to constructs a multi-region input-output database of 185 countries or regions, analyzes a spatial correlation network of embodied net carbon transfer in global agricultural trade by using UCINET, selects multi-dimensional network measurement indicators, and comprehensively studies the global evolution characteristics and functional features of network plate role of embodied carbon transfer in the global agricultural trade. The result shows that the embodied net carbon transfer network of global agricultural trade is densely connected, the spatial correlation spillover effect is significant, and the edge of the network core structure is clear. On the one hand, the top four countries or regions in terms of embodied carbon outflow in agricultural trade are the USA, Australia, Vietnam, and China. On the other hand, the top four countries or regions of embodied carbon inflow are Malaysia, Central Africa, Singapore, and Serbia. From the perspective of outdegree, indegree, proximity centrality, and intermediary centrality, Cambodia, the Netherlands, Vietnam, Ghana, and South Africa, with the high frequency of the shortest path of the globally embodied net carbon transfer network, have a strong influence and linking facility in spatial correlation and have a strong control ability to the spatial correlation of other countries or regions. The embodied carbon emission network of global agricultural trade can be divided into four sectors: main spillover, two-way spillover, broker, and main benefit. The main spillover segment, constituted by the USA, India, Germany, and China, has significant embodied carbon spillover effects on the internal segment and other segments. It is the main embodied carbon spillover sector of embodied net carbon transfer of global agricultural trade. Countries should reasonably allocate the responsibility of carbon reduction according to the trading embodied carbon transfer and made efforts to optimize the export structure of agricultural products.
The circular economy practices contribute to sustainable development by maximising efficiency, utilising renewable resources, extending product lifespans, and implementing waste reduction strategies. This study investigates the individual impacts of four sources of the circular economy on the ecological footprint in Germany, a country that is among the pioneers in establishing a comprehensive roadmap for the circular economy. The four sources examined are renewable energy consumption (REC), recycling, reuse, and repair of materials. Using time series data from 1990 to 2021, the study employed the dynamic autoregressive distributed lag (ARDL) simulation technique and also applied kernel-based linear regression (KRLS) to test the robustness of the results. The findings revealed that reuse practices significantly reduce the ecological footprint in both the short and long run. REC and repair also substantially decrease the ecological footprint, as shown by the simulation analysis. Conversely, while recycling is generally considered crucial for minimising environmental impact, in this study, it was found to contribute to environmental degradation. This paradox may be attributed to the nascent state of the recycling industry and data limitations. The results from KRLS confirm the findings of the dynamic ARDL. It is recommended that policymakers develop measures that are appropriate, efficient, and targeted to enhance the role of each source of the circular economy in reducing the ecological footprint in Germany. The major limitation of the study is its reliance on the indirect measures of circular economy attributed to the non-availability of data on direct measures.
This study represents a pioneering effort to integrate geographic information systems (GIS) and ensemble machine learning methods to predict noise levels on a university campus. Three ensemble models including random forest (RF), gradient boosting (GB), and extreme gradient boosting (XGB) were developed to predict traffic noise based on data collected over a 4-week period at the Universiti Teknologi Malaysia (UTM) campus. Noise measurements were obtained during peak morning hours (7:30 to 9:30 a.m.) on weekdays within the UTM campus in Johor. Additional predictor variables, including data from the digital elevation model (DEM) and land use, were incorporated to capture the complex nonlinear relationships influencing noise levels. The models were optimized through hyperparameter tuning, resulting in high precision, as evidenced by performance metrics such as the coefficient of determination (R2), mean absolute error (MAE), and mean squared error (MSE). The XGB model emerged as the most accurate, with R2 = 0.96, MAE = 0.9, and MSE = 0.3. Noise maps generated using the inverse distance weighting (IDW) interpolation technique highlighted the spatial distribution of noise levels, classified into five classes considering WHO standards. The findings identified distance from roads, the number of light vehicles, and proximity to green areas as the most significant predictors. However, challenges remain in accurately predicting noise levels associated with other predictors. The outcomes of the study indicate the superior performance of the XGB model compared to the GB and RF models. The study recommends several measures to manage and control noise pollution on the UTM campus, including raising awareness, regulating and enforcing vehicle speed limits, reevaluating land use, installing sound insulation systems, and planting trees and vegetation buffer zones around and within educational buildings.
In this study, the fruit of Terminalia chebula, commonly known as chebulic myrobalan, is used as the precursor for carbon for its application in supercapacitors. The Terminalia chebula biomass-derived sponge-like porous carbon (TC-SPC) is synthesized using a facile and economical method of pyrolysis. TC-SPC thus obtained is subjected to XRD, FESEM, TEM, HRTEM, XPS, Raman spectroscopy, ATR-FTIR, and nitrogen adsorption-desorption analyses for their structural and chemical composition. The examination revealed that TC-SPC has a crystalline nature and a mesoporous and microporous structure accompanied by a disordered carbon framework that is doped with heteroatoms such as nitrogen and sulfur. Electrochemical studies are performed on TC-SPC using cyclic voltammetry, galvanostatic charge-discharge, and electrochemical impedance spectroscopy. TC-SPC contributed a maximum specific capacitance of 145 F g-1 obtained at 1 A g-1. The cyclic stability of TC-SPC is significant with 10,000 cycles, maintaining the capacitance retention value of 96%. The results demonstrated that by turning the fruit of Terminalia chebula into an opulent product, a supercapacitor, TC-SPC generated from biomass has proven to be a potential candidate for energy storage application.
Excessive use of tetracycline (TC) is alarming owing to its increased detection in water systems. In this study, a photocatalyst was developed to degrade TC using a Ce-N-co-doped AC/TiO2 photocatalyst, denoted as Ce/N-AC/TiO2, prepared using the sol-gel method assisted by microwave radiation, speeding up the synthesis process. Ce/N-AC/TiO2 achieved maximum TC degradation of 93.1% under UV light with optimum sorption system conditions of an initial concentration of 10 mg L-1, pH 7, and 30 ℃, under 120 min. Scavenger experiments revealed that holes and superoxide radicals were the active species influencing the photodegradation process. The TC degradation was appropriately fitted with Langmuir isotherms and a pseudo-second-order (PSO) kinetic model. The change in enthalpy (ΔH) (2.43 kJ mol-1), entropy (ΔS) (0.024 kJ mol-1), and Gibbs free energy (ΔG) (- 4.941 to - 5.802 kJ mol-1) suggested that the adsorption process was spontaneous, favourable, and endothermic. Electrostatic interaction, hydrogen bonding, pore-filling, cationic-π, n-π, and π-π interaction were among the interactions involved between TC and Ce/N-AC/TiO2. Furthermore, Ce/N-AC/TiO2 stability was confirmed through 80% removal efficiency even after the fifth reuse cycle. Notably, this work provides new insight into the production of efficient, reusable, and enhanced photocatalysts using a rapid and cost-effective microwave-assisted synthesis process for pollutant remediation.