Clean-soil Air Water最新文献

The dye manufacturing industry generates substantial volumes of wastewater that contains color, metals, and various toxic chemicals depending on the specific dyes produced. Effective treatment of this complex wastewater is of great importance to ensure compliance with discharge regulations and protect aquatic ecosystems. In this study, the treatability of wastewater samples taken from the dye manufacturing industry at two different times was investigated using adsorption and Fenton oxidation processes. Treatment performance and cost-effectiveness were assessed by using different pH values and activated carbon dosages in the adsorption process, and different Fe²⁺ and H₂O₂ dosages in the Fenton process. The optimum removal of chemical oxygen demand (COD) and color in the adsorption process was achieved at pH 5, and at 20 g L⁻¹ activated carbon, COD and color removal were achieved at above 64.2% and 95%, respectively. In Fenton oxidation studies, a COD removal rate of 56.6% was achieved for wastewater 1 at 3000 mg L⁻¹ Fe²⁺ and 6000 mg L⁻¹ H₂O₂. Similarly, a 60.3% COD removal rate was achieved at 4000 mg L⁻¹ Fe²⁺ and 6000 mg L⁻¹ H₂O₂ in wastewater 2. In the Fenton process, the color removal rate for both wastewaters approached approximately 98%–99%. The cost of wastewater treatment for dye manufacturing wastewater was calculated to be $10.58–15.53 m⁻³ in the adsorption process and $20.57–22.89 m⁻³ in the Fenton oxidation process. Overall, the findings indicate that both adsorption and Fenton processes are effective treatment alternatives for dye manufacturing wastewater, providing significant reductions in COD and color.

As plants gradually age and die, uranium-rich plant residues are at risk of migration and diffusion of accumulated uranium to the surrounding environment under the action of monsoon and rainfall. In this study, we collected roots and stems of Macleaya cordata from restored uranium-rich soils to simulate the decomposition of M. cordata residues under rainfall drenching. We analyzed the characteristics of uranium release, microbial community composition, and functional group changes during the decomposition of residues. The results showed that after 36 days of decomposition, the stems of the plant residues decomposed faster than the roots, whereas the uranium release rate from the stems (65.09%) was greater than that from the roots (59.09%). On the basis of microbial community analysis and infrared spectroscopy, our results show that Galactomyces, Proteobacteria, and Firmicutes (Ascomycota phylum) play critical roles in the degradation of cellulose, hemicellulose, and lignin in M. cordata residues. These results suggest that after the uranium-rich plant residues migrate and disperse with the monsoon, the uranium in the plant is released into the water body under the action of rain, and migrates and disperses with the water body, causing pollution to the surrounding environment.

Hazardous gases such as oxides of nitrogen (NOx) come from fossil fuel combustion and, therefore, require special attention because there is a regular usage of fuel on a day-to-day basis. In the current work, a new methodology is proposed for diesel exhaust treatment involving electrical discharge plasma causing possible catalysis in a combination of two industrial wastes (composite waste) for removal of NOx. A dual-metal film and helical wire reactor were used to generate surface discharge plasma at room temperature and pressure. Five composite wastes (CW), namely, waste tiles + foundry sand, copper slag + red mud, iron tailings + waste tiles, red mud + waste tiles, and foundry sand + red mud, were used to examine their catalytic properties. A 5-kW diesel engine exhaust was sampled for laboratory experiments. The NOx removal efficiency, which was 16% under plasma-alone treatment at a specific energy of 140 J/L, got enhanced to 80%–93% in plasma-catalysis mode when CWs containing metal oxides were introduced into the plasma reactor. Further, it was verified that plasma catalysis with individual wastes yielded less NOx removal efficiency compared to that with CWs (40%–71% against 80%–93%), indicating the synergy of two wastes that are blended in the CWs.

Polyester fabrics are widely used in various fields, from textiles to packaging applications, due to their easy production and low cost. However, the C─C chains and C─O bonds of these polymers make it difficult for them to spontaneously decompose in nature, and it takes decades for polyester fabric to decompose in nature. This, combined with the increasing production rates, causes serious risks to human, living, and environmental health, and concerns about waste pollution are steadily increasing. In this study, the use of greater wax moth (Gallleria mellonella) larvae was proposed as a natural method to accelerate polyester decomposition. For this purpose, polyester fabric was exposed to the larvae. The surface morphology was then examined using scanning electron microscopy (SEM), and chemical changes were analyzed via Fourier-transform infrared spectroscopy (FTIR). SEM images indicated a rapid onset of surface degradation, and FTIR spectra suggested that the larvae caused the fabric to oxidize. These findings suggest that the polyester chains may have been compromised by this oxidation process, whereas the disintegration of the fabric was likely accelerated by the mechanical actions of the larvae. Although further research is required to gain a full understanding of the precise process of larval-induced decomposition, these preliminary results highlight a promising method for breaking down synthetic polymer-based fabrics, potentially contributing to ecological balance and sustainability.

Nano-sized semiconductors, particularly zinc oxide nanoparticles (ZnO-NPs), have gained significant attention due to their unique properties and applications in fields such as solar energy, electronics, biology, and medicine. This study focused on the environmentally friendly synthesis of ZnO-NPs using lavender (Lavandula angustifolia) extract (l-ZnO-NPs) and the effects of two different applications, foliar spraying and integration into hydrogel, on the growth and development of wheat plants. Characterization using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FT-IR), and x-ray diffraction (XRD) confirmed their excellent purity and crystallinity. According to SEM data, the average particle size distribution of Raw- and l-ZnO-NPs was 92.23 and 82.61 nm, respectively; they were determined as 26.78 and 21.9 nm, according to XRD data. ZnO-NPs suspension increased the seed germination percentage (GP) by 20%, root and shoot lengths by 30%, and chlorophyll content by 15% compared to the control. Raw- and l-ZnO-NPs suspensions exhibited 100% GP at 4000 mg/L concentration. Moreover, the hydrogel treatment enhanced the plant height at 3000 mg/L concentration of Raw- and l-ZnO-NPs content. Foliar and hydrogel treatments promoted the Zn²⁺ uptake, and the maximum values were 4.47 mg/g at 2000 mg/L l-ZnO-NPs concentration and 3.47 mg/g at 1000 mg/L hydrogels contained l-ZnO-NPs concentrations, respectively. This study underscores green-synthesized ZnO-NPs’ potential for sustainable agriculture, providing an eco-friendly method to boost crop productivity. The findings contribute to addressing food security and environmental sustainability amidst the ongoing climate crisis. The water retention properties of hydrogels further address critical challenges like water scarcity in irrigation, exacerbated by climate change.

In the present era of industrial automation, low-cost sensing techniques for accurate liquid level measurement within storage tanks are essential. Storage tanks may contain various sensitive liquids, and changes in their physical properties, as sensed by the sensor, can affect measurement accuracy. An IoT-enabled experimental setup has been established to collect real-time data using low-cost differential pressure, temperature, and turbidity sensors. This work focuses on the detailed characterization of a low-cost differential pressure sensing technique, considering the effects of temperature variation, density, and turbidity. Both in situ and ex situ setups are studied using a differential pressure sensor with an air pocket. The effects of changes in temperature and density are analyzed using a proposed mathematical model and validated through experimental setup. The collected data are preprocessed using filters to remove possible noise and are further used for the estimation of various statistical parameters. For stable water levels, the average root mean square error (RMSE) is less than 0.4 mm (0.16%), and the average standard deviation is less than 0.1 mm. Considering the interrelationship among different parameters, linear and other regression models are developed for comprehensive characterization of the proposed model to ensure accurate measurements. The proposed empirical relationship and regression model show strong correlation between predicted and measured values, with RMSE in the range of 1–2 mm during the filling or draining of the storage tank.

This study aimed to determine the levels, mobility, and concentration fluctuations of cadmium, lead, and zinc in soils southern Poland's Beskid Mały mountains. The examined massif is located approximately 60–100 km to the south and southeast of potential industrial contamination sources, including the Upper Silesian Coal Basin (USCB), the Katowice Iron Steelworks, as well as the Bukowno zinc–lead ore mine and smelter. Soil pollution in the study area was assessed utilizing the geoaccumulation index and the potential ecological risk index. At the same time, the Bureau Communitaire de Reference (BCR) sequential extraction technique was employed to assess the mobility of the elements. The results indicate a discernible influence of industrial sources on mountainous environmental contamination, with a robust correlation among lead, zinc, and cadmium concentrations, affirming a common origin. Furthermore, a statistically significant disparity in metal concentrations was observed between the leeward and windward sides of the mountains, notwithstanding the relatively low absolute height. This phenomenon has not been previously documented in low-altitude regions (below 1000 m above sea level). Therefore, despite their modest height, the studied highlands serve as an impediment to the dissemination of airborne pollutants. The research presented here also paves the way for further analyses and attempts to systematize information on the minimum height of a mountain barrier as a function of its distance from potential sources of pollution.

Air pollutants (e.g., SO₂ and NO_x) were released as a result of the rapid socioeconomic growth and industrial development, leading to the formation of acid rain globally. Acid rain can be detrimental to soil systems because of their significant ecological functions, such as maintaining microbial activities and retaining nutrients for plants. This study investigated the impact of acid rain on soil physicochemical properties using simulated acid rain in laboratory-scale soil leaching experiments. Multiple sets of simulated acid rain with various pH levels were employed in the leaching processes. The properties of soil, including pH, electrical conductivity (EC), pH buffering capacity, and soil ions, were investigated after leaching with simulated acid rain. Results showed that the pH of simulated acid rain significantly influenced soil pH and the pH of soil leachate. There was a positive correlation between the pH levels of simulated acid rain and those of the soil. The surface soil (0–10 cm in depth) maintained a higher pH buffering capacity than the slightly deeper soil (10–40 cm in depth). Fourier transform infrared (FTIR) spectroscopic analysis indicated the consumption of inorganic carbonate functional groups, which could explain the loss of soil base cations.

A textile industry effluents contaminated soil-derived strain of Reactive Red 120 (RR120) dye-degrading bacteria was shown to be extremely effective and metabolically adaptable. Pseudomonas aeruginosa JU_CHE_01 (OR388872) was the isolated strain, as determined by phylogenetic analysis. P. aeruginosa JU_CHE_01 shown the ability to break down 600 mg/L concentration of RR120 dye along with many harmful textile azo dyes. The strain also showed resistance to ampicillin and cefradine but remained susceptible to other tested antibiotics. Five process factors were evaluated for optimal condition using the Taguchi approach. Three physicochemical parameters (pH, temperature, and inoculum dose) and two media components (glucose and yeast extract) were optimized because of their significant impact on RR120 biodegradation. The L-18 orthogonal arrays (OAs) architecture was utilized in the design of multiple experimental studies. Analysis of the experimental data was done using the signal-to-noise (S/N) ratio with the “larger is better” features to determine the key variables and ideal circumstances for optimizing RR120 dye biodegradation. When the predicted data was validated using the confirmatory experiments, it was found that under the ideal conditions of glucose and yeast extract of concentration 1 g/L each, pH 8, temperature 37°C, and inoculum dose 10% (v/v) in 48 h, 97.63% of the RR120 dye degradation could be achieved, leading to a 66.75% enhancement in the RR120 degradation. Analysis of variance (ANOVA) indicated that the nitrogen source (yeast extract) and carbon source (glucose) significantly influenced RR120 biodegradation, accounting for 27.933% and 19.526%, respectively, followed by pH at 4.664%, temperature at 13.476%, and inoculum dose at 28.951%.