Clean-soil Air Water最新文献

Rainfall–runoff modeling requires a selection of a suitable hydrologic model for the determination of an accurate quantity. A better understanding of rainfall–runoff processes is important for stream flow generation within a river basin. This study investigate the long-term spatial–temporal trend of rainfall and streamflow using the hydrologic engineering center-hydrologic modeling system (HEC-HMS) model to understand the rainfall–runoff dynamics in the Banas River basin. Rainfall variability was analyzed for two periods: 1971–1995 and 1996–2020. Continuous wavelet transform was used to analyze the periodicity and the inter-seasonal relationship in rainfall. HEC-GeoHMS was used to generate the various inputs for the hydrologic modeling inputs for the HEC-HMS model. Initial constant loss and ModClark transform method were used to set up the HEC-HMS model for the study area. Calibration and validation of the model were performed using 3 years of observed data 2010–2012 and 2013–2015, respectively. Statistical model efficiency was checked using the coefficient of determination (R²), Nash–Sutcliffe efficiency, and root mean squared error to evaluate the performance of the HEC-HMS model. The finding indicated that the R² values are 0.80 for calibration and 0.82 for validation periods, respectively, which are in good arrangement with the measured values. This study analyzes the relationship between rainfall and runoff, which will aid in proper and efficient water resource management.

In conventional wastewater treatment plants, micropollutants mix with the aquatic environment because they cannot be removed entirely due to their nonbiodegradable structure. Advanced oxidation processes can be considered an alternative solution to this problem. In this study, five different pharmaceutical and personal care products, carbamazepine, diclofenac, ibuprofen, paracetamol, and triclosan, which are commonly found in aquatic environments, were selected as target pollutants. The removal of these target pollutants was investigated using advanced oxidation methods such as the Fenton and UV processes (UV, UV/H₂O₂, and UV/TiO₂). The feasibility of processes in terms of cost was investigated. In the study, both initial and final pharmaceutical concentrations were measured using liquid chromatography mass spectrometry/mass spectrometry to accurately calculate removal efficiency. It has been determined that processes other than the UV process have removal efficiency >99.9%. The UV process showed removal efficiency of 40% for carbamazepine, 90% for diclofenac, 85% for ibuprofen, 86% for paracetamol and 85% for triclosan. Among the processes with high removal efficiency, the Fenton process has been integrated into wastewater treatment plants and has been shown to be the most suitable system in terms of both performance and cost in solving the micropollutant problem.

For this research, a 28-day bioremediation experiment was conducted, simulating an oil spill on the Brazilian coast using mesocosm units and two different bioremediation strategies, adding rate-limiting nutrients in the form of NPK fertilizer during the first four days (Bior1) and weekly (Bior2). The gas chromatography–mass spectrometry analysis results showed that oil natural degradation (Control) removed 33.8 wt.% of the alkanes on Day 7, while bioremediation processes plus evaporation in Bior1 and Bior2 contributed to minimizing alkanes in 83.4 and 80.8 wt.%, respectively. Bior1 strategy also accelerated the biodegradation of recalcitrant polycyclic aromatic hydrocarbons (PAH) such as phenanthrene, methyl phenanthrenes, and methyl dibenzothiophenes up to the second week when compared to Bior2. Low-cost NPK fertilizer addition demonstrated efficiency in the bioremediation strategy, especially in the first days of the simulated oil spill (Bior1), leading to savings in time and financial investment in recovering an oil contaminated area. Results also showed the efficiency of the oil-degrading bacteria Pseudomonas mesophilica, identified for the first time in Brazilian seawater. In addition, results confirmed the influence of tropical temperatures over oil natural natural degradation and bioremediation as an oil spill cleanup solution for recovering contaminated areas in tropical countries, especially in sensitive marine environments.

Exploring the community characteristics of petroleum degrading bacteria and revealing the types of petroleum metabolites produced by degrading bacteria play an important role in solving the problem of oil pollution. In this study, the bacterial suspension was extracted from the sludge of the sewage treatment plant, and the efficient dominant bacteria were enriched and cultured by microbial screening. The optimal environmental conditions and kinetic behavior of microbial degradation of petroleum hydrocarbons in groundwater were discussed, and the metabolites of microbial degradation of petroleum hydrocarbons were analyzed. The results showed that the optimum degradation conditions of the strain were as follows: bacterial suspension inoculum: 2%, pH: 7, temperature: 30°C, initial concentration of contaminated water sample: 500 mg/L. Under these conditions, the microbial petroleum hydrocarbon degradation efficiency was 84.7% and followed the first-order kinetics; qualitative and quantitative statistical analysis of the metabolites of the microbial degradation of petroleum hydrocarbons by gas chromatography-time-of-flight mass spectrometry was performed. A total of 10 significantly upregulated products and 12 significantly downregulated products were screened, which were significantly different from the metabolites of the control group. Further microbial community analysis showed that Pseudomonas was dominant in the bacterial suspension, more than 99.5%, which was significantly different from the sludge sample, providing data support for the degradation of petroleum hydrocarbons by Pseudomonas. This study has provided a scientific basis for in situ remediation of petroleum pollution in groundwater.

Sensors used to detect explosive, flammable, toxic, and harmful gases are in focus of research. The gas sensor can be affected by many factors in the process of use, and among the many adverse elements affecting the function of the gas sensor, humidity is the most common. With the rapid development of gas sensors, the influence of humidity on gas sensors has been paid more and more attention. To reduce the impact of humidity, many methods have been proposed. In this review, the specific impact of humidity on the function of metal-oxide semiconductors and solid electrolyte gas sensors is summarized. Practical techniques are proposed to reduce the effect of humidity on device performance, which is of great help in improving the detection efficiency and quality of gas sensors in high-humidity environment. The information may be valuable for expanding the application field of gas sensors.

The applicability of potassium nickel hexacyanoferrate–polyacrylonitrile (KNiFC–PAN) for the sorption of Co²⁺, Sr²⁺, and Cs⁺ from radioactive laundry wastewater generated in nuclear power plants was investigated. Competitive sorption of Co²⁺, Sr²⁺, and Cs⁺ onto KNiFC–PAN was studied for single, binary, and ternary solutions. The Langmuir, Freundlich, Kargi–Ozmıhci, Koble–Corrigan, and Langmuir–Freundlich models predicted the single-sorption data (R² ≥ 0.942, sum of squared error ≤ 0.105). The sorption isotherms were nonlinearly favorable (Freundlich coefficient, N_F = 0.288–0.842). According to the Langmuir, Freundlich, Kargi–Ozmıhci, Koble–Corrigan, and Langmuir–Freundlich models, at pH 5 (C₀ = 20 mM), KNiFC−PAN exhibited the highest maximum sorption capacity (q_mL) for Cs⁺ among the investigated cations, wherein the primary mechanism was physical sorption. The competition between the metal ions in the binary and ternary systems reduced the respective sorption capacities. Binary and ternary sorption models, such as the ideal adsorbed solution theory (IAST) model coupled with Freundlich (IAST–Freundlich), IAST–Langmuir, and IAST–Langmuir–Freundlich models, were fitted to the experimental data; among these, the IAST–Freundlich model was the most accurate for the binary and ternary systems. The presence of sodium 4-n-octylbenzenesulfonate and dodecylbenzene–sulfonic acid sodium salt as anionic surfactants strongly affected the sorption capacity on KNiFC–PAN owing to increased distribution coefficients (K_d) of Cs⁺, Sr²⁺, and Co²⁺. Thus, KNiFC–PAN is promising for removing Cs⁺, Sr²⁺, and Co²⁺ from radioactive laundry wastewater.