Innovative lake pollution profiling: unveiling pollutant sources through advanced multivariate clustering techniques.

In many developed and developing nations, lakes are the primary source of drinking water. In the current scenario, due to rapid mobilization in anthropogenic activities, lakes are becoming increasingly contaminated. Such practices not only destroy lake ecosystems but also jeopardize human health through water-borne diseases. This study employs advanced hierarchical clustering through multivariate analysis to establish a novel method for concurrently identifying significantly polluted lakes and critical pollutants. A systematic approach has been devised to generate rotating component matrices, dendrograms, monoplots, and biplots by combining R-mode and Q-mode analyses. This enables the identification of contaminant sources and their grouping. A case study analyzing five lakes in Bengaluru, India, has been conducted to demonstrate the effectiveness of the proposed methodology. Additionally, one pristine lake from Jammu & Kashmir, India, has been included to validate the findings from the aforementioned five lakes. The study explored correlations among various physical, chemical, and biological characteristics such as temperature, pH, dissolved oxygen, conductivity, nitrates, biological oxygen demand (BOD), fecal coliform (FC), and total coliform (TC). Critical contaminants forming clusters included conductivity, nitrates, BOD, TC, and FC. Factor analysis identified four primary components that collectively accounted for 85% of the overall variance. Following identification of pollution hotspots, the study recommends source-based pollution control and integrated watershed management, which could significantly reduce lake pollution levels. Continuous monitoring of lake water quality is essential for identifying actual contaminant sources. These findings provide practical recommendations for maximizing restoration efforts, enforcing regulations on pollutant sources, and improving water quality conditions to ensure sustainable development of lakes.

Delineation of agricultural fields in arid regions from Worldview-2 datasets based on image textural properties.

Barren lands are being transformed into agricultural fields with the growing demand for agriculture-based products. Hence, monitoring these regions for better planning and management is crucial. Surveying with high-resolution RS (remote sensing) satellites like Worldview-2 provides a faster and cheaper solution than conventional surveys. In the study, the arid region comprising cropland and barrenlands are efficiently and autonomously delineated using its spectral and textural properties using state-of-the-art random forest (RF) ensemble classifiers. The textural information window size is optimized and at a GLCM (gray-level co-occurrence matrix) window size of 13, a stable trend in classification accuracy was observed. A further rise in window sizes did not improve the classification accuracy; beyond GLCM 19, a decline in accuracy was observed. Comparing GLCM-13 RF with the no-GLCM RF classifier, the GLCM-based classifiers performed better; thus, the textural information assisted in removing isolated crop-classified outputs that are falsely predicted pixel groups. Still, it also obscured information about barren lands present within croplands. Delineation accuracy was 93.8 % for the no-GLCM RF classifier, whereas, for the GLCM-13 RF classifier, an accuracy of 97.3 % was observed. Thus, overall, a 3.5 % improvement in accuracy was observed while using the GLCM RF classifier with window size 13. The textural information with proper calibration over high-spatial resolution datasets improves crop delineation in the present study. Henceforth, a more accurate cropland identification will provide a better estimate of the actual cropland area in such an arid region, which will assist in formulating a better resource management policy.

Subsurface 3D analysis, modeling, and presentation of pollutant nitrate in semi-arid region.

The work incorporates the field data collection, assessment, and use of interpolation and extrapolation methods in modeling the existence of pollutant in groundwater, namely nitrate, and future prediction. To view the variation of concentration of pollutants in any form, 3D representation is required. However, not many techniques are available to achieve the objective accurately. Many modeling studies are done but very little is known about the variation of a group of chemical parameters at vertical scale in any of the climatic zone or habitable region. This kind of study is needed to help stakeholders for better planning. Earlier studies do not show the variation of chemical parameters (contaminants) at vertical scale in the climatic zone, and modellings are very objective specific. Present work presents 3D models using Inverse Distance Weighting technique in Matlab. The concentration pattern of nitrate is studied in 3D and presented in lucid manner at regional scale. The 3D block presentation demonstrates its affiliation and dispersion. The relationship from these models between parameter fixation and profundity shows the presence of distinct layers up to desired depth. The relationship plots are developed to extract the information how the groundwater quality is being transmitted beneath the surface. The projection is verified with the real field data, which will help in future resource management actions and minimize the pollution risks to mankind and the environment. The modeling helps in selecting the danger zones for ground water recharge and discharge for natural cause of elevated concentration of nitrate in groundwater. This study opens up the methodology for finding the variation of other contaminants against depth and that of total water quality.

Megapixel digital PCR.

We present a microfluidic 'megapixel' digital PCR device that uses surface tension-based sample partitioning and dehydration control to enable high-fidelity single DNA molecule amplification in 1,000,000 reactors of picoliter volume with densities up to 440,000 reactors cm(-2). This device achieves a dynamic range of 10(7), single-nucleotide-variant detection below one copy per 100,000 wild-type sequences and the discrimination of a 1% difference in chromosome copy number.

Bio-chelate assisted leaching for enhanced heavy metal remediation in municipal solid waste compost.

Municipal solid waste compost, the circular economy's closed-loop product often contains excessive amounts of toxic heavy metals, leading to market rejection and disposal as waste material. To address this issue, the study develops a novel approach based on: (i) utilizing plant-based biodegradable chelating agent, L-glutamic acid, N,N-diacetic acid (GLDA) to remediate heavy metals from contaminated MSW compost, (ii) comparative assessment of GLDA removal efficiency at optimal conditions with conventional nonbiodegradable chelator EDTA, and (iii) enhanced pre- and post-leaching to evaluate the mobility, toxicity, and bioavailability of heavy metals. The impact of treatment variables, such as GLDA concentration, pH, and retention time, on the removal of heavy metals was investigated. The process was optimized using response surface methodology to achieve the highest removal effectiveness. The findings indicated that under optimal conditions (GLDA concentration of 150 mM, pH of 2.9, retention time for 120 min), the maximum removal efficiencies were as follows: Cd-90.32%, Cu-81.96%, Pb-91.62%, and Zn-80.34%. This process followed a pseudo-second-order kinetic equation. Following GLDA-assisted leaching, the geochemical fractions were studied and the distribution highlighted Cd, Cu, and Pb's potential remobilization in exchangeable fractions, while Zn displayed integration with the compost matrix. GLDA-assisted leaching and subsequent fractions illustrated transformation and stability. Therefore, this process could be a sustainable alternative for industrial applications (agricultural fertilizers and bioenergy) and social benefits (waste reduction, urban landscaping, and carbon sequestration) as it has controlled environmental footprints. Hence, the proposed remediation strategy, chemically assisted leaching, could be a practical option for extracting heavy metals from MSW compost, thereby boosting circular economy.

Heavy metal remediation using chelator-enhanced washing of municipal solid waste compost based on spectroscopic characterization.

Due to high metal toxicity, mixed municipal solid waste (MSW) compost is difficult to use. This study detected the presence of heavy metals (Cd, Cu, Pb, Ni, and Zn) in MSW compost through mineralogical analysis using X-ray diffraction (XRD) and performed topographical imaging and elemental mapping using a scanning electron microscope and energy dispersive X-ray analysis (SEM-EDX). Ethylenediaminetetraacetic acid (EDTA), a typical chelator, is tested to remove heavy metals from Indian MSW compost (New Delhi and Mumbai). It deals with two novel aspects, viz., (i) investigating the influence of EDTA-washing conditions, molarity, dosage, MSW compost-sample size, speed, and contact time, on their metal removal efficiencies, and (ii) maximizing the percentage removal of heavy metals by determining the optimal process control process parameters. These parameters were optimized in a batch reactor utilizing Taguchi orthogonal (L25) array. The optimization showed that the removal efficiencies were 96.71%, 47.37%, and 49.94% for Cd, Pb, and Zn in Delhi samples, whereas 45.55%, 79.52%, 59.63%, 82.31%, and 88.40% for Cd, Cu, Pb, Ni, and Zn in Mumbai samples. Results indicate that the removal efficiency of heavy metals was greatly influenced by EDTA-molarity. Fourier-transform infrared spectroscopy (FTIR) confirmed the presence of hydroxyl group, which aids heavy metal chelation. The results reveal the possibility of EDTA to reduce the hazardous properties of MSW compost.

Radiation Shielding Concrete with alternate constituents: An approach to address multiple hazards.

Radiation Shielding Concrete (RSC) is a superior alternative to many conventional and modern shields against gamma and neutron radiation hazards. The present work is the first comprehensive review on utilization of alternate materials, emphasizing hazardous industrial byproducts, as constituents of RSC. Such usage enhances the performance, sustainability, and affordability of RSC. Added advantages are the immobilization of wastes and the conservation of natural resources for RSC. The review analyses incorporation of ferrous and non-ferrous slags, mines wastes, plastics, red mud, cathode ray tube's glass, metallic wastes, fly ash, silica fume, and miscellaneous residues. Besides, utilization of fibers, nanoparticles, and calcined clay is investigated. The influence on shielding efficiency is adjudged by scrutinizing changes in parameters such as half-value layer and linear attenuation coefficients. Similarly, variations in mechanical and durability properties are investigated and compared. The underlying responsible factors related to the physical, chemical and morphological characteristics of materials and their consequences on RSC's behavior are correlated. In association with alternatives, the advantages, disadvantages, and possible treatment methods are discussed. The country-wise, material-specific, and progressive research trends are revealed to facilitate future work in this upcoming field. Finally, conclusions are drawn with exposition of current bottlenecks and scope of future research.

Microfluidic measurement of antibody-antigen binding kinetics from low-abundance samples and single cells.

We present a simple microfluidic fluorescence bead assay for accurately measuring antibody-antigen binding kinetics with a standard inverted fluorescent microscope. We measured association and dissociation rate constants from antibody-antigen interactions spanning nearly 4 orders of magnitude in equilibrium binding affinity (30 pM-100 nM). Two versions of this assay are presented, which allow for dissociation rate measurements either directly, by use of fluorescently labeled antigen, or indirectly, by use of unlabeled antigen. We also demonstrate simultaneous, multiplexed binding measurements of multiple antibody-antigen interactions using a combination of spectral separation and spatial localization. Complete antibody-antigen binding kinetics were measured for as little as 8 × 104 antibody molecules (~132 zeptomoles) immobilized on a single bead and less than 2 × 106 antibodies (~3 attomoles) loaded into the microfluidic device, a reduction in detection limit and sample consumption of 4 orders of magnitude when compared to surface plasmon resonance (SPR) spectroscopy and alternative measurement techniques. We show that the microfluidic bead assay, when combined with small volume compartmentalization, enables direct measurement of antigen binding kinetics of antibodies secreted from single hybridoma cells. We anticipate that this assay will be useful as a routine analytical tool for studying molecular interactions as well as for screening primary antibody-secreting plasma cells isolated from immunized animals.

Microfluidic single cell analysis: from promise to practice.

Methods for single-cell analysis are critical to revealing cell-to-cell variability in biological systems, especially in cases where relevant minority cell populations can be obscured by population-averaged measurements. However, to date single cell studies have been limited by the cost and throughput required to examine large numbers of cells and the difficulties associated with analyzing small amounts of starting material. Microfluidic approaches are well suited to resolving these issues by providing increased senstitivity, economy of scale, and automation. After many years of development microfluidic systems are now finding traction in a variety of single-cell analytics including gene expression measurements, protein analysis, signaling response, and growth dynamics. With newly developed tools now being applied in fields ranging from human haplotyping and drug discovery to stem cell and cancer research, the long-heralded promise of microfluidic single cell analysis is now finally being realized.

A study on sludge minimization during the treatment of pickling effluent.

In pickling industries, a lot of sludge is generated during the treatment of pickling effluent and there is severe problem of its disposal. Disposal of this sludge as per the Hazardous Waste (Management & Handling) Rules, 1989 is not easy. Its transportation and construction of lined disposal sites pose very severe problems. In the normal practice, the sludge is being disposed of at the sides of roads and railway tracks to fill low lying areas. This may cause serious health hazards. Considering these problems, a study has been undertaken to minimize the sludge generation during the treatment of pickling effluent by neutralizing it with lime, sodium hydroxide and combination of both. An attempt has been made to do an economic evaluation of the above process.