In this study, the phytoremediation potential of Taro (Colocasia esculenta L. Schott) plant was examined, utilizing horizontal subsurface flow constructed wetlands with and without an electric current supply for the purpose of removing pollutants from paper mill effluent. For this, different wetlands were set up with varying concentrations of effluent: CW (Control), CW1 (25%), CW2 (50%), CW3 (75%), CW4 (100%). After 45 days, the highest plant height (85.13 ± 4.24 cm), leaf area index( 250.83 ± 10.14), fresh biomass (565.30 ± 6 .10 g), root biomass (392.85 ± 4.34 g), root-to-shoot ratio (2.41 ± 2.10), relative growth rate (0.044 ± 0.002 ggd), and chlorophyll content (3.29 ± 0.07 mg/g fwt) was observed in CW2 with current supply, along with significant removal of pollutants (pH: 7.13 ± 0.15, EC: 2.33 ± 0.07 dS/m, TDS: 192.52 ± 6.12 mg/L, COD: 490.17 ± 5.01 mg/L, BOD: 206.74 ± 5.92 mg/L, potassium: 73.27 ± 4.11 mg/L, sodium: 46.62 ± 2.27 mg/L, phosphate phosphorus: 34.08 ± 1.43 mg/L, and nitrate nitrogen: 104.85 ± 5.94 mg/L) and highest first-order rate constant (k) values. Furthermore, the microbial community assessment of constructed wetlands using V3-V4 16S rRNA sequence data was prepared on the Illumina MiSeq framework. The major phyla identified were Proteobacteria, Firmicutes, Bacteroidetes, Actinobacteria, Chloroflexi, Acidobacteria, Nitrospirae, Planctomycetes, and others. The findings offer innovative insights for sustainable wastewater treatment strategies through phytoremediation of paper mill effluent using Taro plants in modified constructed wetlands and highlight the role of diverse microbial communities capable of degrading various pollutants in wastewater.
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http://dx.doi.org/10.1007/s10661-024-13523-z | DOI Listing |
Chemistry
December 2024
University of British Columbia, Department of Chemistry, 2036 Main Mill, V6T 1Z1, Vancouver, CANADA.
The creation of multicomponent materials with desired properties and functions is a challenge of modern materials chemistry. Chiral nematic mesoporous organosilicas have iridescent properties that make them attractive for decoration and sensing. In this paper, we demonstrate the chemical functionalization of chiral nematic mesoporous organosilica films with cyclodextrin.
View Article and Find Full Text PDFInt J Biol Macromol
December 2024
College of Horticulture, Hebei Agricultural University, Baoding, Hebei 071001, China; Research Center of Chinese Jujube, Hebei Agricultural University, Baoding, Hebei 071001, China. Electronic address:
Chinese jujube (Ziziphus jujuba Mill.) exhibits a remarkable resilience to both drought and salinity. Additionally, it is characterized by a high sugar content, with sucrose being the predominant component of its soluble sugars.
View Article and Find Full Text PDFPlant Physiol Biochem
December 2024
College of Life Science and Technology, Harbin Normal University, Harbin, China; Heilongjiang Provincial Key Laboratory of Plant Biology in Ordinary Colleges and Universities, Harbin Normal University, Harbin, China; Key Laboratory of Aquatic Biodiversity Research in Hei Longjiang Province, Harbin Normal University, Harbin, China. Electronic address:
Salinity stress is a major threat to agricultural productivity and sustainability, often causing irreversible damage to photosynthesis. Lavender, a valuable aromatic plant, experiences growth impacts under salt stress. However, the regulatory mechanisms of photosynthesis related to its adaptation to salt stress remain unclear.
View Article and Find Full Text PDFMolecules
December 2024
Department of Materials Engineering, University of Pannonia, P.O. Box 1158, H-8210 Veszprém, Hungary.
The availability of industrially used supplementary cementitious materials (SCMs, e.g., fly ash) decreases due to the rise in renewable energy sources and recycling technologies.
View Article and Find Full Text PDFInt J Pharm X
December 2024
Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ 08854, USA.
In pharmaceutical manufacturing, integrating model-based design and optimization can be beneficial for accelerating process development. This study explores the utilization of Machine Learning (ML) techniques as a surrogate model for the optimization of a three-unit wet-granulation based flowsheet model for solid dosage form manufacturing. First, a reduced representation of a wet granulation flowsheet model is developed, incorporating a granulation and milling process, along with a novel dissolution model that accounts for the effect of particle size, porosity, and microstructure on dissolution rate.
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