Effects of iron concentration level in extracting solutions from contaminated soils on the determination of zinc by flame atomic absorption spectrometry with two background correctors

Identification of zinc pollution in rice plants based on two characteristic variables

Traditional chemical methods used to measure the zinc content in rice plants are time-consuming, laborious, requires reagents, and have a limited monitoring range, while the Raman spectroscopy method has the advantage of being fast, non-destructive, and requires no reagents. Unfortunately, the identification accuracy of the Raman partial least squares (PLS) model based on principal components is only 53.33%. To boost this, a One-Way ANOVA method was used to extract the characteristic variables in the Raman spectra. Based on these Raman variables, a model for identifying zinc stressed samples was established. The identification accuracy was improved to 70% but still fell short of the measurement requirements. To further enhance these results, the Raman spectrum was decomposed into components based on the Hilbert Vibration Decomposition (HVD) method. Using characteristic variables of the Raman spectrum and its HVD components to establish a PLS model, the identification accuracy of the test set is raised to 90.25%. These results are a significant improvement from those obtained using a model solely based on the Raman spectral characteristic variables, revealing that HVD components provide highly effective identification information. A Raman modeling method based on the characteristic variables of the HVD component is an innovative way for improving the accuracy of Raman detection, especially for the measurement of trace substances.

Effect of consortium bioaugmentation and biostimulation on remediation efficiency and bacterial diversity of diesel-contaminated aged soil

This study aimed to evaluate the effects of consortium bioaugmentation (CB) and various biostimulation options on the remediation efficiency and bacterial diversity of diesel-contaminated aged soil. The bacterial consortium was prepared using strains D-46, D-99, D134-1, MSM-2-10-13, and Oil-4, isolated from oil-contaminated soil. The effects of CB and biostimulation were evaluated in various soil microcosms: CT (water), T1 (CB only), T2 (CB + NH₄NO₃ and KH₂PO_4, nutrients), T3 (CB + activated charcoal, AC), T4 (CB + nutrients + AC), T5 (AC + water), T6 (CB + nutrients + zero-valent iron nanoparticles, nZVI), T7 (CB + nutrients + AC + nZVI), T8 (CB + activated peroxidase, oxidant), T9 (AC + nZVI), and T10 (CB + nZVI + AC + oxidant). Preliminary evaluation of the bacterial consortium revealed 81.9% diesel degradation in liquid media. After 60 days of treatment, T6 demonstrated the highest total petroleum hydrocarbon (TPH) degradation (99.0%), followed by T1 (97.4%), T2 (97.9%), T4 (96.0%), T7 (96.0%), T8 (94.8%), T3 (93.6%), and T10 (86.2%). The lowest TPH degradation was found in T5 (24.2%), T9 (17.2%), and CT (11.7%). Application of CB and biostimulation to the soil microcosms decreased bacterial diversity, leading to selective enrichment of bacterial communities. T2, T6, and T10 contained Firmicutes (50.06%), Proteobacteria (64.69%), and Actinobacteria (54.36%) as the predominant phyla, respectively. The initial soil exhibited the lowest metabolic activity, which improved after treatment. The study results indicated that biostimulation alone is inadequate for remediation of contaminated soil that lacks indigenous oil degraders, suggesting the need for a holistic approach that includes both CB and biostimulation. Graphical Abstract.

Development of a bacterial consortium comprising oil-degraders and diazotrophic bacteria for elimination of exogenous nitrogen requirement in bioremediation of diesel-contaminated soil

The purpose of this study was to develop an effective bacterial consortium and determine their ability to overcome nitrogen limitation for the enhanced remediation of diesel-contaminated soils. Towards this, various bacterial consortia were constructed using oil-degrading and nitrogen-fixing microbes. The diesel removal efficiency of various developed consortia was evaluated by delivering the bacterial consortia to the diesel-contaminated soils. The consortium Acinetobacter sp. K-6 + Rhodococcus sp. Y2-2 + NH₄NO₃ resulted in the highest removal (85.3%) of diesel from the contaminated soil. The consortium containing two different oil-degrading microbes (K-6 + Y2-2) and one nitrogen-fixing microbe Azotobacter vinelandii KCTC 2426 removed 83.1% of the diesel from the soil after 40 days of treatment. The total nitrogen content analysis revealed higher amounts of nitrogen in soil treated with the nitrogen-fixing microbe when compared with that of the soil supplemented with exogenous inorganic nitrogen. The findings in this present study reveal that the consortium containing the nitrogen-fixing microbe degraded similar amounts of diesel to that degraded by the consortium supplemented with exogenous inorganic nitrogen. This suggests that the developed consortium K-6 + Y2-2 + KCTC 2426 compensated for the nitrogen limitation and eliminated the need for exogenous nitrogen in bioremediation of diesel-contaminated soils.