Clean-soil Air Water最新文献

Water pollution from industrial-colored effluents, generated by large volumes of liquid effluents containing synthetic dyes, generally harmful and non-biodegradable, affects environmental biota and human health. Considering the potential use as bio-adsorbents of agro-industrial residues, in the present work insights into the kinetics, equilibrium, and mechanism of the methylene blue (MB) dye adsorption by six bio-adsorbents produced from the post-harvest residues from the banana tree, a widely cultivated crop in Brazil, were investigated. The six prepared bio-adsorbents were tested to verify the adsorption capacity as gross residues, after carbonization, and after alkaline-chemical activation. Bench-scale experiments conducted at different conditions showed that experimental data were better described by the Langmuir isotherm, by the intraparticle diffusion model (with external diffusion being the dominant step), followed by the pseudo-second-order model, indicating the predominance of monolayer chemisorption. In addition, maximum adsorption capacities ranged between 10.55 and 25.51 mg/g, with a higher dye removal rate at alkaline pH. The adsorption of the MB dye onto the six produced bio-adsorbents occurred through both polar and nonpolar interactions. The overall study indicated that both the pseudo-stem and the leaves from post-harvest banana crops could be a cost-effective natural bioresource for producing efficient and sustainable bio-adsorbents for treating colored liquid effluents.

The prediction of pollutants removal efficiency from the generated effluent of a treatment plant is valuable and can reduce the time, sampling and energy required during performance assessment. The present study aims to predict the effect of different input parameters on the treatment efficiency of the developed microbial-based anaerobic process for textile effluent using machine leaning algorithms. The decolourisation and chemical oxygen demand (COD) reduction of the treated effluent were predicted on the basis of the three different input parameters pH, COD and colour value of the textile wastewater. The effectiveness of different machine learning algorithms, support vector machines (SVM), random forest (RF), gradient boost regressor (GBR), AdaBoost, extreme gradient boosting (XGB) regressor and voting regressor, were evaluated based on the correlation coefficient (R²) value. The results revealed that the RF achieved the highest accuracy for decolourisation (training data R²: ∼0.85 and test data R²: ∼0.84) as well as COD reduction (training data R²: ∼0.87 and test data R²: ∼0.94) compared to the other algorithms. These results were validated experimentally, confirming that RF can be used as a tool to predict the performance efficiency of a microbial-based treatment system.

Discharging effluents with high chemical oxygen demand (COD) and nitrogen content into the environment threatens human and aquatic life. An increase in nitrogen load results in depletion of dissolved oxygen (DO), eutrophication, ecological stress, and biodiversity loss. Intake of water containing excess nitrate can cause different diseases. Conventional physicochemical nitrogen removal techniques are expensive and also generate secondary pollutants. In contrast, biological methods offer effective and economical outcomes with global acceptance. Biofilm-based techniques have the advantages of low space requirement, resistance toward toxic shocks, and absence of sludge backflow. The carriers used in biofilm reactors allow the growth of heterogeneous microbial consortia, which can simultaneously remove COD, nitrogenous compounds, and phosphates. This review aims to summarize the outcomes of the individual lab-scale research in this area, critically analyze the scientific findings, and understand the research gap. Conventional nitrification–denitrification and anammox have often been replaced by more efficient approaches such as simultaneous nitrification–denitrification, partial nitrification–denitrification, partial nitritation and anammox, and simultaneous partial nitrification, anammox, and denitrification. Multistage moving bed biofilm reactors have been specially designed with step feeding for complete nitrogen removal. Through anammox in a sequencing batch reactor, a high rate of denitrification could be obtained, whereas simultaneous nitrification–denitrification using a membrane bioreactor resulted in almost complete removal of nitrogen. We expect that this review will provide the direction for designing experiments on enhanced removal of nitrogen and COD from different wastewater sources using microbial biofilms.

In a changing climate, conservation tillage and agronomic biofortification are essential for enhancing crop yield, nutritional security, carbon stocks, and soil quality. Consequently, a field study was conducted in central India to assess the short-term (4 years) effects of crop establishment techniques (CETs) and agronomic biofortification methods (ABMs) on soil health indicators, grain yield, and quality in the soybean–wheat cropping system. The experiment followed a split-plot design with two CETs in the main plots (permanent broad bed furrow, PBBF, and conventional tillage, CT) and eight ABMs, each with three replications. The results indicated that PBBF and ABMs (seed inoculation with the microbial strains MDSR 14 + MDSR 34, and soil and foliar application of Zn+Fe) improved soil carbon stock (by 49.6% and 52.4%), available nitrogen, phosphorus, potassium, available Zn (by 30.0%), and Fe (by 21.9%) after the fourth year of the study. Similarly, PBBF and microbial inoculation increased soil enzyme activities (dehydrogenase, acid phosphatase, and β-glucosidase), substrate-induced respiration, and microbial biomass carbon content. As a result, a higher soybean equivalent yield (5.59% higher in PBBF and 14.2% higher with foliar spray of Zn+Fe) and seed quality attributes (crude protein yield, grain Zn, and Fe) were observed in PBBF and the foliar spray of Zn and Fe treatments compared to CT and control, respectively. Overall, adopting the short-term PBBF system, microbial inoculation, and soil and foliar application of Zn and Fe improved rhizosphere biochemical properties, yield, and seed quality in the soybean–wheat system.

Synthetic microfibers are emerging environmental microplastic pollutants released from different industrial and domestic sources. The present investigation describes the isolation of potential bacterial strains from microplastic-contaminated sites of Bhubaneswar city of Odisha, India. Four morphologically distinct bacterial strains were isolated using 2% polyethylene glycol (PEG) supplemented nutrient agar (NA) medium and were screened for their polymer tolerance ability by growing them on 2%–8% PEG. A single microorganism capable of growing on 8% PEG was selected for biodegradation experiment. Through 16S rRNA sequencing, the selected bacterial strain was identified as Exiguobacterium sp. with gene bank accession number ON318396. The microbial strain's microfiber biodegradation ability was assessed in a laboratory setting over a period of 28 ± 2 days, utilizing optimized conditions with an initial pH of 7, 2 mL inoculum volume, an incubation temperature of 30°C ± 2°C, and 150 rpm, using 2 g of polyester microfiber. In optimum conditions, the weight loss of the treated sample with the selected microbial strain was 19.2%. The polyester degradation was confirmed through scanning electron microscopic images viewing the degradation of the polyester microfiber surfaces. Variation in functional groups confirmed through Fourier transform infrared spectrophotometry. Detection of carbonyl (C═O) group stretching band at 1711 cm⁻¹ through ATR-FTIR analysis in the treated sample confirmed the polymer biodegradation. The potential isolate can efficiently degrade polyester and, in the future, can be employed as a promising solution for the sustainable treatment of synthetic microfiber pollution.

The degree and severity of zinc (Zn) deficiency in soil reduced the agricultural yield and quality, thus encouraging malnutrition in humans worldwide. The study was hypothesized to increase the bioavailability and release of Zn in soil and Zn biofortification in wheat grains under integrated nutrient management (INM). The long-term (54 years) experiment laid out in a split-plot design comprising single (W) and dual (PW) applications of farmyard manure (FYM) (0, 5, 10, and 15 Mg ha⁻¹) and nitrogen (0, 60, and 120 kg ha⁻¹) was studied to understand the distribution of different Zn fractions in soil and their relationship to wheat grain yield and Zn uptake. A laboratory incubation study was performed on surface soils to evaluate the release kinetics of native Zn at field capacity. The different fractions of Zn in soil increased with increasing frequency and levels of FYM application. Residual Zn constituted the maximum proportion (89.03%) of total soil Zn. A high positive correlation (p < 0.01) of diethylenetriaminepentaacetic acid (DTPA)-extractable Zn and total grain Zn content were observed with different Zn fractions. The release kinetics of native soil Zn increased up to 10 days and became almost constant, indicating the establishment of chemical equilibria between the soil solid and solution phase. Thus, long-term INM ensured higher wheat production (6.08 Mg ha⁻¹) and Zn biofortification (38.95 mg kg⁻¹) to combat Zn malnutrition and achieve the United Nations’ sustainable development goals on “zero hunger” and “good health and well-being.”