International Journal of Environmental Science and Technology最新文献

Industrial developments and settlements along the Siak River have affected the quality of the river water. Based on laboratory tests, the COD and BOD content of Siak River water still exceeds the standard set under Government Regulation No. 22 of 2021. This research was conducted to analyze the role of variations in the composition and size of materials of clay, fly ash, and sawdust, in synthesizing ceramic membranes for COD and BOD removal of Siak River water. These residual materials from pulp and paper industry were used for ceramic membranes synthesis and further applied in drinking water treatment. In this study, ceramic membranes with a diameter of 11 cm, a thickness of 0.5 cm, and a combustion temperature of 900 °C were obtained and the composition of clay, fly ash, and sawdust of the ceramic membranes was varied in terms of ratio, respectively, at 32.5%:60%:7.5%, 45%:45%:10%, and 70%:25%:5%. Meanwhile, the variations in the size of the materials were as follows: 60, 80, and 100 mesh. The obtained results have shown that the COD and BOD content of Siak River water was reduced during the filtration process using the ceramic membranes, with the greatest percentage reductions in COD and BOD content (48.9% and 64.6%, respectively). The highest removals percentage were recorded upon using the ceramic membrane M8 (with a composition of 60% fly ash, 32.5% clay, 7.5% sawdust and particle size of 100 mesh). This result indicated that the ceramic membranes can be effectively used for the targeted application.

Machine learning is presently receiving great attention. However, machine learning applications to gasoline engine research are limited. This paper investigated the implementation of various machine learning models in predicting the emissions (CO₂, CO, and PM_2.5) and noise levels of gasoline-powered household generators for the first time. Data of operating and installed capacity, efficiency (input) and emissions, and noise level (output) obtained from 166 generators were used in extreme gradient boosting, artificial neural network (ANN), decision tree (DT), random forest (RF), and polynomial regression (PNR) algorithms to develop predictive models. Results revealed high prediction performance (R² = 0.9377–1.0000) of these algorithms marked with very low errors. The implementation of PNR followed by the RF exhibited the best models for predicting CO₂, CO, PM_2.5, and the noise level of generators. R² of 1.000 and 0.9979–0.9994, mean squared error of < 10⁻⁶ and 2 × 10⁻⁵–8.6 × 10⁻⁵, mean absolute percentage error of 9.15 × 10⁻¹⁶–1.3 × 10⁻¹⁵ and 7.1 × 10⁻³–8.1 × 10⁻², and root mean squared error of 3.3 × 10⁻¹⁶–5.4 × 10⁻¹⁶ and 4.4 × 10⁻³–9.3 × 10⁻² were recorded for all the output parameters using PNR and RF respectively. DT models had the least prediction capacity for CO, CO₂, and noise levels (R² = 0.9493–0.9592) while ANN produced the least performance for PM_2.5 (R² = 0.9377). This study further strengthens machine learning applications in engine research for the prediction of various output parameters.

The investigation of bio-liquid fuels as a sustainable fuel has garnered significant attention. However, because of high production cost, other co-products need to be investigated. The pretreatment process of second-generation (2G) bioethanol produces black liquor that contains lignin. In this paper, we report a direct bubbling and a two-step acidification process for lignin isolation from black liquor of the pilot scale bioethanol production and its utilization as lead adsorber. This research investigated how Pb (II) ions adsorbed onto new modified lignin recovered from black liquor called dimethylamine-soda lignin. Alkaline pretreatment at 150 °C and 5 kg/cm³ by using a 450 L reactor was used to extract the lignin from oil palm (Elaeis guineensis) empty fruit bunches (OPEFB). The acidic precipitation was achieved by adding 3% HCl until the pH reached 2, and the air bubbling was done at a rate of 2 L/min. By applying dimethylamine-acetone-formaldehyde to soda lignin in the Mannich reaction, lignin derivative was produced. The Fourier-transform infrared spectroscopy, scanning electron microscopy, and Brunauer, Emmett, and Teller methods were used to characterize all types of lignin. The analyses confirmed the formation of dimethylamine-lignin, as indicated by a 19-fold increase in the total nitrogen content in the modified lignin. Pb (II) adsorption was verified by pseudo-first-order and second-order reactions. Dimethylamine-soda lignin had the adsorption capability for lignin extracted from acid and the air bubbling technique, 6.0 and 6.8 mg/g, respectively. The outcomes demonstrate that the eco-friendly aminated lignin can effectively lower Pb (II) in the solution, making it a suitable adsorbent for removing lead from aqueous media.

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This study delves into exploring the potential of agricultural waste materials for effectively reducing lead(II) contamination in water sources. Unlike many biosorbents which undergo costly modifications leading to secondary pollution risks, this research focuses on the unmodified Citrus paradisi (grapefruit) peel (CPP) as a promising biosorbent for Pb⁺² ion removal. A comprehensive analysis utilizing various techniques such as FTIR, XRD, boehm titration, point zero charge, BET, TGA, DTA, elemental analysis, AFM, and SEM–EDX was conducted on CPP shedding light on its structural and chemical properties. The biosorption process was scrutinized across multiple parameters including initial metal concentration, contact time, pH, particle size, and solution temperature. Through systematic experimentation covering a range of concentrations and temperatures, kinetic models (Pseudo first order, Pseudo second order, and Elovich) and isotherm equations (Langmuir, Freundlich, and Temkin) were applied to unveil the adsorption behavior. Remarkably, the Langmuir model revealed q_max = 43.48 mg/g at 310 K and pH 5.6, underscoring the efficiency of CPP in lead removal. Further analysis employing kinetic modeling, notably the pseudo-second order model (R² = 0.999), provided insights into the rate of adsorption, affirming its effectiveness. Thermodynamic assessments unveiled an endothermic and spontaneous biosorption process onto CPP, suggesting its feasibility for lead removal in a nature-friendly manner. Moreover, the biosorption mechanism was elucidated through FTIR analysis, elucidating the molecular interactions involved. Overall, the findings of this study underscore the potential of utilizing unmodified agricultural waste, such as grapefruit peel, as a sustainable solution for mitigating lead contamination, offering a cost-effective and eco-friendly approach to water treatment.

The study was focused on analyzing the land use and land cover status, change patterns, and future scenarios in the Mayurakshi basin in Jharkhand and West Bengal state of eastern India. The dataset collected for image classification included Landsat 5 (TM) (1991–2008) and Landsat 8 (OLI) (2020). Various sequential preprocessing steps such as atmospheric correction, image enhancement, mosaicking, masking, and clipping were performed using QGIS 3.16 and ArcGIS 10.8 software. The land use and land cover classes found in the study area were water, vegetation, bare land, agriculture, and built-up, and classification was executed by using the Random Forest machine learning algorithm. The accuracy of the classified land use and land cover was validated and accepted with Kappa agreements of 0.89, 0.85, and 0.88 for the years 1991, 2005, and 2020, respectively. Throughout the study period, agriculture emerged as the dominant land use class, followed by vegetation and bare land. The area under the land use and land cover categories of water, vegetation, and bare land continuously decreased between the years 1991–2005 and 2005–2020, while agriculture and built-up areas recorded an increase of 4.49%, 0.76%, 17.81%, and 2.04%, respectively. To project future land use and land cover status, the popular Cellular Automata Markov Chain Model was employed. The projected results indicate that agriculture will remain the dominant land cover with a share of 70.24%, followed by vegetation at 17.72% and built-up areas at 5.09%. However, a marginal decline is expected in both the agriculture and built-up classes.

Novel polymer composites with unique characteristics as new materials are essentially needed to meet future demands. Terpoly(anthranilic acid, m-aminobenzoic acid, and o-nitroaniline) emeraldine base (EB)/macro-microcomposites were generated from equimolar ratios of the corresponding molecules and different ratios of bentonite via in situ oxidative terpolymerization. Their spectral properties upon joining the m-aminobenzoic acid and the o-nitroaniline moieties in the skeleton of polyanthranilic acid were inspected. The spectral analyses were utilized to emphasize the results of both terpoly(o, m-aminobenzoic acid, and o-nitroaniline) (EB) and poly(o, m-aminobenzoic acid, and o-nitroaniline)/bentonite composites. The TGA analyses of the purified terpolymer with and without bentonite in the N₂ atmosphere were investigated. Furthermore, the terpolymer composite morphology was investigated by the SEM technique with the micro-macrometric particle sizes 0.470–2.780 μm at different magnifications.

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Plastic pollution and microplastic (MP, 1 µm to 5 mm) generation are growing problems affecting the global community and a wide range of natural and disturbed environments. Urban and suburban waterways are directly impacted by plastic pollution due to their proximity to population centers and many different types single use plastic waste sources. In this study, plastic waste accumulation and fragmentation was investigated along the Cooper River in Camden County, NJ. Polymer composition was identified for individual plastic waste particles collected along the Cooper River using Fourier transform infrared (FTIR) spectrometry. Multiple human-built structures (Wallworth Lake, Evans Pond and Hopkins Pond dams) along the Cooper River were found to accumulate different types of plastic waste. The accumulation of plastic waste along these structures resulted in the initial stages of plastic fragmentation and the identification of large MP particles (1 to 5 mm). Quantitative analysis revealed that fragmented polystyrene (PS) particles constituted 82.8% of the total plastic fragments identified, most of which were identified at the Wallworth Lake dam. Many other types of fragmented plastic litter, including polyethylene and polypropylene, were identified at the Wallworth Lake dam, as well. This research demonstrates that engineered structures within urban and suburban aquatic ecosystems serve as significant aggregators of plastic debris, thereby catalyzing its breakdown into microplastics. Considering the escalating ecological and human health ramifications of microplastic proliferation, the fragmentation of plastic waste in an urban and suburban waterway observed in this study can also result in potentially toxic smaller MP particles, and increased exposure to aquatic organisms and humans.

The nickel oxide nanoparticles (NPs) were synthesized using the solvothermal method in the oleic acid to remove congo red via an adsorption process. Furthermore, for the first time, in this study subsequently regeneration of deactivated adsorbent by low-energy ultrasound waves as an inventive technique was investigated. The morphology, porosity, and crystallinity of the as-synthesized NPs were investigated by transmission electron microscopy (TEM), Scanning electron microscope (SEM), Brunauer–Emmett–Teller (BET), and X-ray diffraction (XRD) techniques. Congo red, a water-soluble azo dye, is adsorbed by nickel oxide nanoparticles, reaching about 83.20% adsorption within two hours with a pseudo-first-order rate constant of 0.0099 min⁻¹. In the regeneration process, the nanoparticles regenerated by low-frequency ultrasound waves up to 94.35% within 35 min. The obtained data shows that the amount of regenerated nanoparticles increased with the intensity of ultrasonic irradiation. Most importantly, it can be recycled by ultrasound irradiation, which retains high performance in 3 cycles, proving its promising application for different environmental decontamination.

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