Clean-soil Air Water最新文献

Leachate from municipal waste contains volatile organic compounds and potentially toxic metals. The leaching of which into water sources also jeopardizes access to clean water. Therefore, reducing the concentration of pollutants in leachate is important to reduce health risks and environmental pollution. In this study, the efficacy of granulated organic leonardite added to leachate from municipal waste in reducing the toxic concentrations of the leachate for different time points (30, 60, 90, and 120 min) at a shaking speed of 200 rpm was investigated. Results demonstrated that leonardite significantly removed various contaminants, including organic acids (71.16%), alcohols (74.31%), aldehydes (68.01%), esters (78.28%), ethers (81.03%), ketones (68.52%), hydrocarbons (84.25%), N compounds (78.56%), S compounds (80.67%), organic N (86.01%), total Kjeldahl nitrogen (93.26%), NH₄-N (84.83%), NO₃-N (89.30%), SO₄ (76.62%), PO₄ (73.85%), organic C (50.07%), Hg (96.80%), Pb (95.99%), Cu (82.68%), Al (65.56%), total Cr (98.11%), Cd (99.28%), Li (96.31%), Ni (97.27%), and As (67.79%). The leonardite granules used in this study showed high adsorption and removal performance for organic/inorganic and volatile compounds in landfill leachate. These results indicate that leonardite can be a suitable adsorption material for leachate pretreatment. However, it is necessary to perform a durability test to use the material in the long term as a covering on landfills.

The aim of this research was to assess the efficacy of different microbial strains in the decolorization of anthraquinone dyes. Strain R81 was obtained from a textile company's wastewater discharge for its remarkable ability to decolorize reactive blue 19 (RB19). By employing physiological and biochemical analyses, along with 16S rRNA gene sequencing, strain R81 was determined to be Brevibacillus laterosporus. After optimization, the decolorization rate achieved a peak of 86.24% over a 48-h timeframe, utilizing an initial dye concentration of 100 mg L^–1. The decolorization capacity of strain R81 was observed to be impeded by heightened levels of salt and temperature in culture solutions, yet remained unaltered when R81 cells were directly introduced into dye solutions. Furthermore, cells that were induced through prior cultivation in a medium containing RB19 demonstrated enhanced efficacy in decolorization compared to noninduced cells. Subsequent analysis indicated that the development of biofilms and the synthesis of polysaccharides by strain R81 were augmented in a concentration-dependent fashion by RB19. Nevertheless, the decolorization efficacy of R81 was impeded by the existence of sodium dodecyl sulfate (SDS) and cetyltrimethylammonium bromide (CTAB), both of which possess the capacity to eliminate polysaccharides. The decolorization capabilities were reinstated by the SDS or CTAB eluent containing polysaccharides, suggesting a reliance on the presence of polysaccharides. The employment of stepwise diethylaminoethyl (DEAE)-cellulose chromatography and decolorization experiments elucidated the importance of a specific polysaccharide in the decolorization process. This study proposes a bacteria-derived polysaccharide as a promising remedy for treating dyeing wastewater contaminated with anthraquinones.

The aim of this study was to evaluate the impact of pandemic-related lockdown on Turkey's air quality throughout time and space. For this purpose, statistical techniques were used to assess daily particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen oxides and nitrogen dioxide (NO_x and NO₂), ozone (O₃), and carbon monoxide (CO). The study's findings showed that, while the lockdown improved air quality in terms of air pollutant emissions, the most notable reduction was in NO₂ and NO_x emissions. When comparing the months prior to the pandemic (November 2019 to January 2020) with the months during the pandemic (November 2020 to January 2021), the declines in NO₂ were 20%, 3%, and 0.5%, respectively. NO_x emissions decreased by an average of 19% and 5% in November and December, respectively, and increased by an average of 16% in January during the pandemic. When the data for the 33 days of lockdown were compared to the data for the same 33 days the previous year, significant differences were determined at several Clean Air Centers, which were two for PM₁₀, two for SO₂, seven for NO_x, four for NO₂, two for CO, and three for O₃, respectively. In this study, pollutant concentrations were found in the following ranges from November 2019 to January 2021: PM₁₀: 3–208 µg m^–3, SO₂: 1–56 µg m^–3, NO_x: 6–600 µg m^–3, NO₂: 4–155 µg m^–3, CO: 1–3921 µg m^–3, and O₃: 2–119 µg m^–3. There were days that exceeded the limit values for PM₁₀.

Due to the critical impacts of microplastic (MP) aggregation on their fate, mobility, and bioavailability, this study developed a simple approach to examine their aggregation under varying water chemistry and MPs’ surface aging conditions. An accelerated photodegradation experiment was conducted for 6 weeks. The water chemistry conditions varied by altering pH, using natural organic matter (NOM), and conducting experiments in ultrapure water and synthetic stormwater. The surface chemistry analysis of photodegraded MPs revealed the formation of carbonyl and vinyl functional groups. Zeta potential measurements revealed a more negative surface charge for photodegraded MPs compared to new MPs. The aggregation kinetics of MPs were studied by comparing the number of MP clusters formed over time after intense dispersion in water. The results showed that the presence of NOMs reduces the aggregation tendency of new low-density polyethylene MPs due to enhanced steric hindrance and electrostatic repulsion. However, variations of pH and utilizing synthetic stormwater versus ultrapure water did not alter the aggregation kinetics of new MPs. The aggregation behavior of photodegraded MPs was significantly different from new MPs. A greater tendency for aggregation of photodegraded MPs was found in the stormwater compared to the ultrapure water. This study contributes to a better understanding of the transport and fate of MPs within the aqueous environment and their subsequent environmental risks.

Air pollution poses a persistent challenge for urban management departments and policymakers due to its significant health and economic impacts. Various cities worldwide have implemented diverse strategies and initiatives to enhance air quality monitoring and modeling standards. However, the outcomes of these efforts often manifest over the long term, leading to a preference for short-term statistical methods. The autoregressive integrated moving average (ARIMA) search grid modeling approach has gained widespread use for forecasting air quality. This paper presents a comprehensive time series analysis conducted to predict air quality in urban areas of Budapest, Hungary, with a focus on nitrogen dioxide (NO₂) and particulate matter (PM₁₀), using air quality data spanning from 2018 to 2022 for four monitoring categories: Urban traffic, industrial background, urban background, and suburban background. The study employs the ARIMA search grid method to forecast concentrations of these pollutants at multiple air quality monitoring stations based on Akaike information criteria (AIC) and the Bayesian information criteria (BIC) criteria along with the results of augmented Dickey–Fuller (ADF) test. The results demonstrate varying levels of forecast accuracy across different stations, indicating the model's effectiveness in short-term predicting of air quality. These findings are essential for assessing the reliability of air quality forecasts in Budapest and can inform decisions regarding air quality management and the development of strategies to address air pollution and particulate matter concerns in the region.

Algae have adsorption properties and reducing agents due to their rich content. In this study, palladium nanoparticles (Pd NP), platinum nanoparticles (Pt NP), and iron oxide nanoparticles (Fe₃O₄ NP) were prepared from Codium macroalgae using green synthesis. The structure of the synthesized nanoparticles was elucidated by X-ray diffractometry, Fourier transforms infrared spectroscopy, Brunauer–Emmett–Teller analysis, transmission electron microscopy, ultraviolet-visible spectroscopy and scanning electron microscopy-energy dispersive X-ray spectrometry and their use as nanoadsorbents for the removal of pollutants from aqueous media was investigated in detail. Naproxen (NPX), an anti-inflammatory drug, and the dyes methylene blue (MB) and cresol red (CR) were selected as pollutants for this study. Batch adsorption experiments were conducted using both real wastewater obtained from the Organised Industrial Zone of Isparta Province and synthetic water samples prepared with tap water from Burdur Province and pure water. Under optimum adsorption conditions, Pd NP showed significant efficiency in the real wastewater sample, with an adsorption capacity of 37.19 and 50.03 mg g^–1 for CR and NPX, respectively, within 150 min. In comparison, Pt NP showed an adsorption capacity of 40.01 mg g^–1 for MB within the same timeframe. These findings indicate that while Pd NP showed the highest adsorption capacity for both CR and NPX, Pt NP showed the highest adsorption capacity for MB. The Langmuir model and the pseudo-second-order equation were more suitable to describe the adsorption behavior of CR, MB, and NPX. In addition, studies on the desorption and reusability of the nanoadsorbents were carried out under the same optimum experimental conditions.

The main goal of the present study was to highlight how crucial odor evaluation methods may be for raising the general standard of living in a region. For this, the dispersion of odor concentrations detected by an olfactometric method in an area of Kocaeli, Turkey, where odor problems are frequently experienced, was investigated using the AERMOD atmospheric dispersion modeling system. According to the findings of the olfactometric measurement, the mean odor concentrations in the industrial area was high at 1342 OU m^–3, while in the residential areas the values were lower, at 578 OU m^–3 within the selected study area. As a result of the modeling study, the maximum odor concentration was 2081 OU m^–3 at the 1 h. The model also showed that the coordinate points where the maximum odor concentration was observed changed with time, and that the concentrations recorded at the 1 h may decrease by as much as 88%–91% at the 24 h. In the study, a survey was also conducted to identify possible effects of odor pollution on people. The survey findings showed a statistically significant difference (p < 0.05) between the two areas (industrial and residential) for seven variables of a total 28. We suggest that measuring odor concentrations, modeling their distribution, and conducting surveys are effective methods when managing the urban planning process.