A mesoporous activated carbon was produced from the Azolla Pinnate (AP) seaweed by two-step chemical activation technique using sulphuric acid as activating agent. The adsorption of Acid Brown (AB) from aqueous solutions is examined using the produced carbon (AP). The produced activated carbon renders a homogeneous porous structure, predominantly mesoporous with 686.5 m2/g of BET surface area. The infra-red spectrum revealed AB affinity by multiple functional groups. The point of zero charge and the pH studies evidenced that the surface charge responsible for electronic affinity favours adsorption at higher pH. The SEM and FTIR analysis of AP before and after adsorption of acid brown shows multiple interactions, which is further substantiated by equilibrium, kinetic and thermodynamic models. Equilibrium adsorption data matched best with Langmuir isotherm model, thus primarily follows chemical interaction. However, physical affinity and heterogeneity of surface and species interaction also do exist nearly equally. Pseudo-second order kinetics provided the best explanation of the adsorption kinetics. The temperature variation studies revealed that acid brown adsorption is endothermic with high surface affinity.
以硫酸为活化剂，通过两步化学活化技术从羽衣杜鹃（AP）海藻中制备出一种介孔活性炭。使用制得的碳（AP）对水溶液中的酸性棕色（AB）进行了吸附测试。制得的活性炭具有均匀的多孔结构，主要为中孔，BET 表面积为 686.5 m2/g。红外光谱显示了 AB 与多种官能团的亲和性。零电荷点和 pH 值研究表明，电子亲和性的表面电荷有利于在较高的 pH 值下吸附。酸性棕色吸附前后 AP 的扫描电镜和傅立叶变换红外光谱分析显示了多种相互作用，平衡、动力学和热力学模型进一步证实了这一点。平衡吸附数据与 Langmuir 等温线模型最为吻合，因此主要遵循化学作用。不过，物理亲和性和表面异质性与物种相互作用也几乎同样存在。伪二阶动力学为吸附动力学提供了最佳解释。温度变化研究表明，酸性棕色的吸附是内热的，表面亲和力很高。
{"title":"Evaluation of aqueous phase adsorption of Acid Brown on mesoporous activated carbon prepared from Azolla Pinnate seaweed","authors":"","doi":"10.30955/gnj.005560","DOIUrl":"https://doi.org/10.30955/gnj.005560","url":null,"abstract":"A mesoporous activated carbon was produced from the Azolla Pinnate (AP) seaweed by two-step chemical activation technique using sulphuric acid as activating agent. The adsorption of Acid Brown (AB) from aqueous solutions is examined using the produced carbon (AP). The produced activated carbon renders a homogeneous porous structure, predominantly mesoporous with 686.5 m2/g of BET surface area. The infra-red spectrum revealed AB affinity by multiple functional groups. The point of zero charge and the pH studies evidenced that the surface charge responsible for electronic affinity favours adsorption at higher pH. The SEM and FTIR analysis of AP before and after adsorption of acid brown shows multiple interactions, which is further substantiated by equilibrium, kinetic and thermodynamic models. Equilibrium adsorption data matched best with Langmuir isotherm model, thus primarily follows chemical interaction. However, physical affinity and heterogeneity of surface and species interaction also do exist nearly equally. Pseudo-second order kinetics provided the best explanation of the adsorption kinetics. The temperature variation studies revealed that acid brown adsorption is endothermic with high surface affinity. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":" March","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139617897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Industrial by-products such as cementitious materials or aggregates have the potential to mitigate the adverse environmental effects associated with traditional cement manufacture. Geopolymer Concrete (GPC) is more eco-friendly than conventional concrete because it does not require cement. GPC with Recycled concrete aggregates (RCA), Ground granulated blast furnace slag (GGBS), and Fly Ash (FA) reduce raw material use and create sustainable infrastructure. GPC compounds increase workability, slump value above standard concrete, and reduce the amount of water usage. The study examines GPC mechanical properties, durability, and environmental properties with different RCA content. The M30 concrete mix design is established by trial and error utilizing a 0.45 water/binder ratio. GPC with 0%, 10%, 20%, 30%, 40%, and 50% recycled coarse aggregate replaced natural aggregate(NA) by mass. GPC with 50% GGBS provides an early strength of 96% of normal compressive strength on day seven. The compressive, split tension, and flexural strengths exhibit significant improvement with up to a 40% substitution of NA with RA. These results highlight GPC's potential as a sustainable alternative in the construction sector.
{"title":"Transforming waste into sustainable building materials: Properties and environmental impacts of Geopolymer concrete with recycled concrete aggregates","authors":"","doi":"10.30955/gnj.005518","DOIUrl":"https://doi.org/10.30955/gnj.005518","url":null,"abstract":"Industrial by-products such as cementitious materials or aggregates have the potential to mitigate the adverse environmental effects associated with traditional cement manufacture. Geopolymer Concrete (GPC) is more eco-friendly than conventional concrete because it does not require cement. GPC with Recycled concrete aggregates (RCA), Ground granulated blast furnace slag (GGBS), and Fly Ash (FA) reduce raw material use and create sustainable infrastructure. GPC compounds increase workability, slump value above standard concrete, and reduce the amount of water usage. The study examines GPC mechanical properties, durability, and environmental properties with different RCA content. The M30 concrete mix design is established by trial and error utilizing a 0.45 water/binder ratio. GPC with 0%, 10%, 20%, 30%, 40%, and 50% recycled coarse aggregate replaced natural aggregate(NA) by mass. GPC with 50% GGBS provides an early strength of 96% of normal compressive strength on day seven. The compressive, split tension, and flexural strengths exhibit significant improvement with up to a 40% substitution of NA with RA. These results highlight GPC's potential as a sustainable alternative in the construction sector. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139616672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biodiesel can be derived from the oils of fruit seeds for powering diesel engines, and this study focuses on extracting biodiesel from Manilkara Zapota seeds, which are readily available and not intended for human consumption. The primary aim is to underscore the use of non-edible oils as a cost-effective raw material for biodiesel production. The research indicates a successful production yield of 92.45% using a 0.76% catalyst, an excess of 6 methanol equivalents in comparison to the oil, a temperature of 62°C, and a reaction time of 90 minutes. The biodiesel obtained from Manilkara Zapota seed oil predominantly comprises methyl esters of oleic, stearic, and palmitic acids, presenting a viable alternative to fossil diesel for unmodified diesel engines. Optimal performance variables for maximum conversion efficiency were determined as a 40°C reaction temperature, 6:1 alcohol-to-oil ratio, 120 minutes of experimental duration, and a 0.5wt.% NaOH catalyst. Among these variables, the alcohol-to-oil ratio was identified as the most influential, contributing 84.34% to the overall performance. The thermal profile of Manilkara Zapota Seeds biomass exhibited multistage decomposition behavior. The synthesized Manilkara Zapota Methyl Ester (MZME) derived from seed oil, using the optimized performance variables, complies with the ASME D 6751 and EN14214 Biodiesel Standards.
{"title":"Utilizing Manilkara zapota seed oil for biodiesel production and conducting an investigation into its properties and characteristics","authors":"","doi":"10.30955/gnj.005387","DOIUrl":"https://doi.org/10.30955/gnj.005387","url":null,"abstract":"Biodiesel can be derived from the oils of fruit seeds for powering diesel engines, and this study focuses on extracting biodiesel from Manilkara Zapota seeds, which are readily available and not intended for human consumption. The primary aim is to underscore the use of non-edible oils as a cost-effective raw material for biodiesel production. The research indicates a successful production yield of 92.45% using a 0.76% catalyst, an excess of 6 methanol equivalents in comparison to the oil, a temperature of 62°C, and a reaction time of 90 minutes. The biodiesel obtained from Manilkara Zapota seed oil predominantly comprises methyl esters of oleic, stearic, and palmitic acids, presenting a viable alternative to fossil diesel for unmodified diesel engines. Optimal performance variables for maximum conversion efficiency were determined as a 40°C reaction temperature, 6:1 alcohol-to-oil ratio, 120 minutes of experimental duration, and a 0.5wt.% NaOH catalyst. Among these variables, the alcohol-to-oil ratio was identified as the most influential, contributing 84.34% to the overall performance. The thermal profile of Manilkara Zapota Seeds biomass exhibited multistage decomposition behavior. The synthesized Manilkara Zapota Methyl Ester (MZME) derived from seed oil, using the optimized performance variables, complies with the ASME D 6751 and EN14214 Biodiesel Standards. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"53 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139526927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The concentration of ozone in the earth atmosphere has been steadily falling by 4% in the total amount since late 1970. With the widespread usage of modern industry chlorofluorocarbons, the rate at which ozone content decreases is escalating, resulting in an ozone hole. The depletion permits harmful UV into the earth surface which brings harmful hazards to earth living organisms. Increased UV radiation exposure can lead to skin cancer, cataracts, and ecological disruptions. The machine learning models face difficulties in accurately accounting for unpredictable events, such as sudden changes in emission patterns or unforeseen interactions, which limits their capacity to provide precise and reliable forecasts for future ozone depletion scenarios. To overcome this issue, a novel hybridization of Convolution Neural Network (CNN) and Support Vector Machine (SVM) is proposed to detect the variation in the ozone depletion around earth surfaces. The input images are collected from the thermosphere meteorological satellite and transformed into clean data in preprocessing. Then, the images are annotated and fed to the learning model for training. Followed by SVM classifier taken the CNN feature as an input and show the exact level of the ozone. The experimental findings show that the proposed CNN-SVM framework accomplishes satisfactory prediction accuracy of 99.44%. The overall accuracy range improves by 0.21%, 6.74%, and 4.44% with the CNN, SVM-IF, and Faster RCNN test outcomes, and by 2.59%, 3.52%, and 4.13% with the proposed CNN model, respectively. The proposed SVM model increases the total f1-Score by 2.3%, 3.19%, and 0.7%, respectively. The proposed CNN-SVM model obtains high accuracy rate than other existing models.
{"title":"Prediction of Ozone Depletion Levels using Intelligent CNN-SVM Classification System","authors":"","doi":"10.30955/gnj.005461","DOIUrl":"https://doi.org/10.30955/gnj.005461","url":null,"abstract":"The concentration of ozone in the earth atmosphere has been steadily falling by 4% in the total amount since late 1970. With the widespread usage of modern industry chlorofluorocarbons, the rate at which ozone content decreases is escalating, resulting in an ozone hole. The depletion permits harmful UV into the earth surface which brings harmful hazards to earth living organisms. Increased UV radiation exposure can lead to skin cancer, cataracts, and ecological disruptions. The machine learning models face difficulties in accurately accounting for unpredictable events, such as sudden changes in emission patterns or unforeseen interactions, which limits their capacity to provide precise and reliable forecasts for future ozone depletion scenarios. To overcome this issue, a novel hybridization of Convolution Neural Network (CNN) and Support Vector Machine (SVM) is proposed to detect the variation in the ozone depletion around earth surfaces. The input images are collected from the thermosphere meteorological satellite and transformed into clean data in preprocessing. Then, the images are annotated and fed to the learning model for training. Followed by SVM classifier taken the CNN feature as an input and show the exact level of the ozone. The experimental findings show that the proposed CNN-SVM framework accomplishes satisfactory prediction accuracy of 99.44%. The overall accuracy range improves by 0.21%, 6.74%, and 4.44% with the CNN, SVM-IF, and Faster RCNN test outcomes, and by 2.59%, 3.52%, and 4.13% with the proposed CNN model, respectively. The proposed SVM model increases the total f1-Score by 2.3%, 3.19%, and 0.7%, respectively. The proposed CNN-SVM model obtains high accuracy rate than other existing models. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"13 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study's two primary goals are to synthesize bioethanol from biowaste and examine its thermal characteristics. Bioethanol must first undergo a comprehensive assessment of its thermal characteristics in order to be approved for usage in spark-ignition engines. A multi-step procedure comprising extraction, pretreatment, enzymatic hydrolysis, and fermentation was used to manufacture the bioethanol. The raw material was put through a preliminary screening using thermogravimetric analysis to find the mass loss rate as a function of temperature before to starting this process. Remarkably, the Manila tamarind leaves exhibited the highest mass loss, up to 34%. Enzymatic cellulose conversion to fermentable sugars was a critical step in the production of cellulosic ethanol. Following hydrolysis, Saccharomyces cerevisiae was employed in the fermentation process, leading to the bioethanol synthesis phase. The Manila Tamarind leaves yielded the most, around 29% by weight, which is amazing. In order to assess the thermal properties of the extracted ethanol, a variety of parameters were carefully examined, including the viscosity, density, cetane number, and calorific value. In each of these areas, mixtures of tire oil, gasoline, and bioethanol consistently outperformed the others. Furthermore, Fourier Transform Infrared Spectrometry spectra were utilized to validate the concentrations of potential groups, including alcohol, aromatic, alkyne, amide, and carbonyl groups. Clear objectives guide the fermentation process, aiming for consistent quality, safety, and functionality in the end product.
{"title":"Characteristics and evolution of bioethanol from Manila Tamarind (Pithecellobium dulce) leaf through fermentation","authors":"","doi":"10.30955/gnj.005634","DOIUrl":"https://doi.org/10.30955/gnj.005634","url":null,"abstract":"This study's two primary goals are to synthesize bioethanol from biowaste and examine its thermal characteristics. Bioethanol must first undergo a comprehensive assessment of its thermal characteristics in order to be approved for usage in spark-ignition engines. A multi-step procedure comprising extraction, pretreatment, enzymatic hydrolysis, and fermentation was used to manufacture the bioethanol. The raw material was put through a preliminary screening using thermogravimetric analysis to find the mass loss rate as a function of temperature before to starting this process. Remarkably, the Manila tamarind leaves exhibited the highest mass loss, up to 34%. Enzymatic cellulose conversion to fermentable sugars was a critical step in the production of cellulosic ethanol. Following hydrolysis, Saccharomyces cerevisiae was employed in the fermentation process, leading to the bioethanol synthesis phase. The Manila Tamarind leaves yielded the most, around 29% by weight, which is amazing. In order to assess the thermal properties of the extracted ethanol, a variety of parameters were carefully examined, including the viscosity, density, cetane number, and calorific value. In each of these areas, mixtures of tire oil, gasoline, and bioethanol consistently outperformed the others. Furthermore, Fourier Transform Infrared Spectrometry spectra were utilized to validate the concentrations of potential groups, including alcohol, aromatic, alkyne, amide, and carbonyl groups. Clear objectives guide the fermentation process, aiming for consistent quality, safety, and functionality in the end product. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"29 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The biological synthesis of nanomaterials is drawing immense interest because of their non-hazardous nature and enormous antimicrobial application. In the present study, we explored Polygonatum geminiflorum Decne for phytochemical profiling and biosynthesis of silver nanoparticles to control soft rot/blackleg and bacterial wilt pathogens of potato through in vitro experiment. Phytochemical screening indicated the presence of important secondary chemicals including tannins, glycosides, flavonoids and terpenoids, while, gas chromatography-mass spectrophotometry (GC-MS) study of leaf extract showed the presence of 30 phytochemicals, the most prominent among which included ç-Sitosterol and n-Hexadecanoic acid. The GC–MS qualitative analysis also supported the presence of bioactive compounds responsible for metal reduction processes and synthesized nanoparticles stabilization. In vitro study showed that concentration of 100µg/mL of AgNPs and AgNPs-PE efficiently control both Erwinia carotovora and Ralstonia solanacearum. The outcomes have provided an improved protocol to use prepared AgNPs against the tested pathogens without health hazards.
{"title":"GC-MS characterization of Polygonatum geminiflorum depicted by antibacterial efficacy of the biosynthesized silver nanoparticles using its leaf extract","authors":"","doi":"10.30955/gnj.005495","DOIUrl":"https://doi.org/10.30955/gnj.005495","url":null,"abstract":"The biological synthesis of nanomaterials is drawing immense interest because of their non-hazardous nature and enormous antimicrobial application. In the present study, we explored Polygonatum geminiflorum Decne for phytochemical profiling and biosynthesis of silver nanoparticles to control soft rot/blackleg and bacterial wilt pathogens of potato through in vitro experiment. Phytochemical screening indicated the presence of important secondary chemicals including tannins, glycosides, flavonoids and terpenoids, while, gas chromatography-mass spectrophotometry (GC-MS) study of leaf extract showed the presence of 30 phytochemicals, the most prominent among which included ç-Sitosterol and n-Hexadecanoic acid. The GC–MS qualitative analysis also supported the presence of bioactive compounds responsible for metal reduction processes and synthesized nanoparticles stabilization. In vitro study showed that concentration of 100µg/mL of AgNPs and AgNPs-PE efficiently control both Erwinia carotovora and Ralstonia solanacearum. The outcomes have provided an improved protocol to use prepared AgNPs against the tested pathogens without health hazards. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"12 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, based on the factors of treatment process, treatment scale, as well as water quality, the level and distribution of electricity consumption, drug consumption, and indirect carbon emission of five typical wastewater treatment plants (WWTPs) were examined. The distribution of electricity consumption within the WWTPs were analyzed in terms of wastewater treatment units. The results uncovered that the biological treatment unit was the treatment unit with a high percentage of electricity consumption in the WWTPs. Carbon emissions of main units in the WWTPs presented that the aeration blower, sewage lifting pump, submersible pusher, phosphorus remover and return sludge pump of the biological treatment unit were the top 5 emission units of carbon emissions in the WWTPs, and the key influencing factors of the carbon emissions of the main carbon emission units had been analyzed. Combined with the current situation of sewage treatment energy consumption in Chongqing, the analysis put forward a library of energy saving and consumption reduction measures for Chongqing WWTPs, which applied them to the sewage treatment plant A energy saving and consumption reduction renovation project.
{"title":"Investigation of Key Technologies for Energy Saving and Consumption Reduction in Chongqing Municipal Wastewater Treatment Plants Based on Carbon Emission Reduction Contribution","authors":"","doi":"10.30955/gnj.005642","DOIUrl":"https://doi.org/10.30955/gnj.005642","url":null,"abstract":"In this paper, based on the factors of treatment process, treatment scale, as well as water quality, the level and distribution of electricity consumption, drug consumption, and indirect carbon emission of five typical wastewater treatment plants (WWTPs) were examined. The distribution of electricity consumption within the WWTPs were analyzed in terms of wastewater treatment units. The results uncovered that the biological treatment unit was the treatment unit with a high percentage of electricity consumption in the WWTPs. Carbon emissions of main units in the WWTPs presented that the aeration blower, sewage lifting pump, submersible pusher, phosphorus remover and return sludge pump of the biological treatment unit were the top 5 emission units of carbon emissions in the WWTPs, and the key influencing factors of the carbon emissions of the main carbon emission units had been analyzed. Combined with the current situation of sewage treatment energy consumption in Chongqing, the analysis put forward a library of energy saving and consumption reduction measures for Chongqing WWTPs, which applied them to the sewage treatment plant A energy saving and consumption reduction renovation project. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"16 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Environmental protection and the need for accurate pollutant forecasting have become increasingly important as worries about environmental issues and the harmful effects of pollution have grown. Predictive accuracy of air pollutants is generally unsatisfactory due to the fact that conventional methodologies prioritise time series analysis over the important spatial transmission dynamics among neighbouring locations. To address this inherent limitation, our proposed solution introduces an innovative Time Series Prediction Network, augmented by the auto-optimization capabilities of a Spatio-Temporal Graph-based Neural Network. This groundbreaking network comprises distinct spatial and temporal modules. The spatial module harnesses a Graph Sampling and Aggregation Network to extract essential spatial information from the data. Simultaneously, the temporal module integrates a Bayesian approach with a Complex Valued Graph Gated Recurrent Unit (BCV-GRU), seamlessly incorporating a graph network into the Gated Recurrent Unit (GRU) to capture temporal intricacies. Moreover, to manage the challenge of model inaccuracy stemming from inappropriate hyperparameters, Bayesian optimization was employed. The efficacy of our proposed method was validated using real PM2.5 data from the USGS website, showcasing a significant enhancement in prediction accuracy. This study puts forth a robust and effective approach for forecasting PM2.5 concentrations, bridging gaps in existing methodologies and contributing substantially to the evolution of environmental prediction models.
{"title":"An Automated Graph-Based Neural Network Model for Predicting Urban Environmental Air Quality Using Spatio-Temporal Data Optimization","authors":"","doi":"10.30955/gnj.005598","DOIUrl":"https://doi.org/10.30955/gnj.005598","url":null,"abstract":"Environmental protection and the need for accurate pollutant forecasting have become increasingly important as worries about environmental issues and the harmful effects of pollution have grown. Predictive accuracy of air pollutants is generally unsatisfactory due to the fact that conventional methodologies prioritise time series analysis over the important spatial transmission dynamics among neighbouring locations. To address this inherent limitation, our proposed solution introduces an innovative Time Series Prediction Network, augmented by the auto-optimization capabilities of a Spatio-Temporal Graph-based Neural Network. This groundbreaking network comprises distinct spatial and temporal modules. The spatial module harnesses a Graph Sampling and Aggregation Network to extract essential spatial information from the data. Simultaneously, the temporal module integrates a Bayesian approach with a Complex Valued Graph Gated Recurrent Unit (BCV-GRU), seamlessly incorporating a graph network into the Gated Recurrent Unit (GRU) to capture temporal intricacies. Moreover, to manage the challenge of model inaccuracy stemming from inappropriate hyperparameters, Bayesian optimization was employed. The efficacy of our proposed method was validated using real PM2.5 data from the USGS website, showcasing a significant enhancement in prediction accuracy. This study puts forth a robust and effective approach for forecasting PM2.5 concentrations, bridging gaps in existing methodologies and contributing substantially to the evolution of environmental prediction models. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"29 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Composites gain utility when filler materials are incorporated. The qualities of the material are changed when filler components are added. In recent years, the use of bio-based components in polymers and polymer composites has significantly increased. Agricultural wastes are employed in this case as filler component to create bioplastic composites since they are inexpensive, plentiful, and easily accessible. By varying the weight ratios of Eggshell (ES) powder and Walnut shell (WS) powder added to the plasticized PLA, bioplastic composite samples are created. Epoxidized soybean oil (5wt%) is used to create the plastic. The obtained bioplastic particles are then subjected to additional processing by being shaped into dog-bone-shaped samples and tested mechanically and thermally. Mechanical testing, including Tensile, Charpy Impact, and Flexural tests, revealed that the PLA possessed inferior properties to those of virgin PLA. The qualities of plasticized PLA-ES composite, however, performed better than those of plasticized PLA-WS composite.
{"title":"Exploring the effects of eco-friendly and biodegradable biocomposite incorporating eggshell and walnut powder as fillers","authors":"","doi":"10.30955/gnj.005471","DOIUrl":"https://doi.org/10.30955/gnj.005471","url":null,"abstract":"Composites gain utility when filler materials are incorporated. The qualities of the material are changed when filler components are added. In recent years, the use of bio-based components in polymers and polymer composites has significantly increased. Agricultural wastes are employed in this case as filler component to create bioplastic composites since they are inexpensive, plentiful, and easily accessible. By varying the weight ratios of Eggshell (ES) powder and Walnut shell (WS) powder added to the plasticized PLA, bioplastic composite samples are created. Epoxidized soybean oil (5wt%) is used to create the plastic. The obtained bioplastic particles are then subjected to additional processing by being shaped into dog-bone-shaped samples and tested mechanically and thermally. Mechanical testing, including Tensile, Charpy Impact, and Flexural tests, revealed that the PLA possessed inferior properties to those of virgin PLA. The qualities of plasticized PLA-ES composite, however, performed better than those of plasticized PLA-WS composite. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"31 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The proliferation of environmental pollution, particularly from hazardous industrial dyes, poses a significant threat to ecosystems and aquatic life. This study uses extract from Nerium oleander leaves as a natural capping and reducing agent to produce copper oxide nanoparticles (CuO NPs), an ecologically acceptable way to tackle this problem. The CuO nanoparticles have improved physicochemical characteristics, as shown by their average crystalline size of 15.56 nm and decreased particle size of 31.84 nm. Additional studies such as SEM, EDX, TEM, and zeta potential were accomplished and revealed the spherical structure; an elevated negative zeta potential of -25.6 mV was observed on the surface property. The photodegradation efficacy of these bio-synthesized CuO NPs was assessed against various industrial dyes, including Rhodamine 6G, Malachite Green, Eosin Yellow, and Reactive Black. The results demonstrated exceptional degradation efficiencies, with rates of up to 97.48%, 99.54%, 89.73%, and 89.33% respectively. The decolorization of organic dyes presented a visual cue that the degradation process was progressing. Notably, using Nerium oleander leaves as reducing agents contributed to the nanoparticles' stability, making them suitable for repeated cycles of photocatalysis. This research underscores the potential of green synthesis methods and highlights the vital role of plant-based reducing agents in advancing environmentally friendly nanomaterials for wastewater treatment and environmental remediation. The findings offer a promising pathway toward sustainable and eco-friendly solutions to mitigate the environmental impact of hazardous industrial dyes, fostering responsible industrial practices and preserving aquatic ecosystems.
{"title":"Eco-Friendly Cost-Effective Formation of Copper Oxide Nanostructures and its Prodigious Potential for Environmental Remediation Applications","authors":"","doi":"10.30955/gnj.005557","DOIUrl":"https://doi.org/10.30955/gnj.005557","url":null,"abstract":"The proliferation of environmental pollution, particularly from hazardous industrial dyes, poses a significant threat to ecosystems and aquatic life. This study uses extract from Nerium oleander leaves as a natural capping and reducing agent to produce copper oxide nanoparticles (CuO NPs), an ecologically acceptable way to tackle this problem. The CuO nanoparticles have improved physicochemical characteristics, as shown by their average crystalline size of 15.56 nm and decreased particle size of 31.84 nm. Additional studies such as SEM, EDX, TEM, and zeta potential were accomplished and revealed the spherical structure; an elevated negative zeta potential of -25.6 mV was observed on the surface property. The photodegradation efficacy of these bio-synthesized CuO NPs was assessed against various industrial dyes, including Rhodamine 6G, Malachite Green, Eosin Yellow, and Reactive Black. The results demonstrated exceptional degradation efficiencies, with rates of up to 97.48%, 99.54%, 89.73%, and 89.33% respectively. The decolorization of organic dyes presented a visual cue that the degradation process was progressing. Notably, using Nerium oleander leaves as reducing agents contributed to the nanoparticles' stability, making them suitable for repeated cycles of photocatalysis. This research underscores the potential of green synthesis methods and highlights the vital role of plant-based reducing agents in advancing environmentally friendly nanomaterials for wastewater treatment and environmental remediation. The findings offer a promising pathway toward sustainable and eco-friendly solutions to mitigate the environmental impact of hazardous industrial dyes, fostering responsible industrial practices and preserving aquatic ecosystems. \u0000","PeriodicalId":502310,"journal":{"name":"Global NEST: the international Journal","volume":"22 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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