Contamination of water sources with lead has been a problem because it is a toxic heavy metal. Detection and monitoring are important for both the environment and human health. In this paper, we present an application of cantilever nanobiosensors that can detect contamination traces of lead (Pb) in real river water samples. The urease and alkaline phosphatase enzymes are used in the device as a biological element with high sensitivity in Pb detection. By change in deflection of the cantilever nanobiosensor in contact with the liquid solution (water), the response was the detection of trace amounts of Pb in water. When using ultrapure water (white), the nanobiosensors did not demonstrate voltage response. The detection limit was in femtograms per milliliter (parts per trillion) for phosphatase alkaline and urease nanobiosensors with good recovery results. The matrix effect was minimized with the dilution of river water in the ratio 1:1 with the working solution. The nanobiosensors demonstrated are efficient in the detection of the presence of Pb in real samples. Thus, the developed cantilever nanobiosensors showed suitability for heavy metal detection in water and could be a promising tool in the environmental area. Graphical Abstract

Anthropogenic activities have caused extensive arsenic (As) contamination in soils. The role of biochar in the remediation of As-contaminated soils has been attracting attention lately. In this study, effects of straw biochar, iron oxide, and iron oxide–modified biochar on soil microbial community composition and soil chemical properties were tested in an As-contaminated soil. After 9 months of incubation, soil chemical properties and microbial communities were analyzed. Our results showed that biochar addition significantly increased soil pH value, soil organic carbon (SOC) concentration, and the ratio of soil carbon to nitrogen (soil C:N ratio) but decreased soil dissolved organic C. Adding iron oxide also increased soil pH value, while iron oxide–modified biochar decreased it. Interestingly, compared with the control, all treatments significantly decreased soil total microbial biomass and biomasses of soil bacteria, fungi, Actinomyces, and protozoa. In addition, significantly positive correlations were found between soil pH and soil total microbial biomass as well as bacterial, Actinomyces, and arbuscular mycorrhizal fungal biomass. There were negative relationships between SOC, soil C:N ratio, and all soil microbial biomass indicators in all treatments. These results indicated that biochar and iron oxide–modified biochar affected soil microbial community composition by altering the soil C:N ratio, but iron oxide affected it via adjusting soil pH. Furthermore, the iron oxide–modified biochar effects on soil microbial community and soil chemical properties are not the same as the additive effects of biochar and iron oxide alone, and its effect on soil microbial community is regulated by the soil C:N ratio. These findings will help guide the development of remediation practices for As-contaminated soil using biochar.

Inorganic pollutants are continuously introduced into the atmosphere. Bioindicators present an alternative method of monitoring air quality. This work proposes to evaluate the Mangifera indica L. leaves as a biomonitor for air quality. Quantification of aluminum (Al), barium (Ba), calcium (Ca), chromium (Cr), copper (Cu), iron (Fe), potassium (K), manganese (Mn), magnesium (Mg), sodium (Na), nickel (Ni), sulfur (S), strontium (Sr), titanium (Ti), and zinc (Zn) were determined in leaves of M. indica using optical emission spectrometer inductively coupled plasma (ICP-OES). The correlogram analyses demonstrated a strong positive correlation between Al and Fe. Contamination of the soil by vehicles and agricultural chemicals, in synergy with the influence of the winds, may be considered as a source of contamination. Enrichment factor (EF) index was used to distinguish between natural and anthropogenic sources. Detection of Mn and Cu could be associated with anthropogenic influence, demonstrating M. indica as a feasible tool to biomonitor air quality.

School resilience is characterized as risk management techniques to build a safe environment for students. Recognizing the need of building disaster resilience for the education sector, this study is aimed at assessing flood disaster resilience of elementary schools in four extremely vulnerable districts of Khyber Pakhtunkhwa province of Pakistan. This paper established the assessment tool by incorporating climate resilience indices and 16 tasks of the Hyogo Framework for action designed for the education sector. It discusses four dimensions: physical conditions of elementary schools, human resources, institutional issues, and external relationships, each with three parameters and five variables. The data were obtained for 60 variables from 20 randomly selected elementary schools. Indicators of resilience were identified, and an index-based approach was used to get the composite values of the four dimensions of resilience. Correlations between the dimensions, components, and indicators were also checked in the current study. Results show that schools in Nowshera, followed by Charsadda, Peshawar, and Dera Ismail Khan, are the most resilient to flood disasters. For all 12 parameters under 4 dimensions, the relative resilience of study districts is the same. The findings further indicated that there is a strong correlation between the pairs of human resources and institutional issues as well as institutional issues and external relationships that can also enhance human resources and external relationships. Furthermore, institutional issues are also correlated with external relationships and human resources, which indicate that there is a triangular relationship among human resources, institutional issues, and external relationships. The findings would encourage policymakers and practitioners to develop an effective plan to improve the resilience of schools using the overall resilience situation. In short, education sector disaster resilience can be achieved by integrated planning and implementation approach. In this respect, disaster managers, public and private education sectors, school staff, students, and parents need to establish synergies to devise a comprehensive plan of action to enhance disaster education.

River estuaries, continental shelf, and sediment contamination are closely linked from the point of view of sediment transport and diffusion that is governed by different factors such as sea waves and currents, river flows and floods, and sediment characteristics. Taking these factors into consideration, we have examined marine environmental and marine bottom sediments off the mouth of a stream to highlight the main ways of sediment and contaminant transport and diffusion on the continental shelf. For this purpose, we followed a multidisciplinary approach, studying circulation of water masses, hydrological characteristics of water column, distribution and main characteristics of sediment grain size, sediment mineralogical composition, and metal concentrations of bottom sediments. Our results allowed identifying the presence of preferential ways of sediment deposition and areas of sediment spread for the Entella Stream, as well as the origin of some metals.

Watershed models are cost-effective and powerful tools for evaluating and controlling non-point source pollution (NPSP), while the reliability of watershed models in a management context depends largely on inherent uncertainties in model predictions. The objective of this study is to present the use of multi-model ensemble applied to streamflow, total nitrogen (TN), and total phosphorus (TP) simulation and quantify the uncertainty resulting from model structure. In this study, three watershed models, which have different structures in simulating NPSP, were selected to conduct watershed monthly streamflow, TN load, and TP load ensemble simulation and 90% credible intervals based on Bayesian model averaging (BMA) method. The result using the observed data of the Yixunhe watershed revealed that the coefficient of determination and Nash–Sutcliffe coefficient of the BMA model simulate streamflow, TN load, and TP load were better than that of the single model. The higher the efficiency of a single model is, the greater the weight during the BMA ensemble simulation is. The 90% credible interval of BMA has a high coverage of measured values in this study. This indicates that the BMA method can not only provide simulation with better precision through ensemble simulation but also provide quantitative evaluation of the model structure through interval, which could offer rich information of the NPSP simulation and management.

The spatial and vertical distributions of radon and uranium are evaluated in relation to the hydrogeology, geomorphology, and hydrochemistry of southwest Punjab. Radon activity of the groundwater ranges from 580 to 3633 Bq/m³ (shallow groundwater 580 to 2438 Bq/m³ and deep groundwater 964 to 3633 Bq/m³), and uranium concentration varies from 24.4 to 253 μg/L (shallow groundwater 24.4 to 253 μg/L and deep groundwater 27.6 to 76.3 μg/L). Shallow groundwater shows higher U concentration compared with deeper ones, which can be attributed to the presence of dissolved oxygen (DO) and NO₃⁻ as oxidants and HCO₃⁻ as stabilizing agent in shallow zone. Unlike uranium, the radon activities were found to be similar in both shallow and deep groundwater. Rnₑₓcₑₛₛ over secular equilibrium was used to confirm the possibility of additional sources of radon, such as secondary minerals present in the subsurface. Surface manifestations show significant influence on radon and uranium distributions in the shallow zone but not in deep zone due to limited hydraulic connectivity. Depth profiles and correlations of radon and uranium with trace elements and hydrochemical parameters indicate that groundwater exhibits different redox characteristics in shallow (younger and oxidizing) and deep zones (older and reducing). The present study provides critical information that can be helpful for planning sustainable groundwater development in this region and other similar regions without contaminating the relatively safer deep aquifers.

The level of tungstate in freshwater is disturbing due to its toxicity and its impact to human health. Thus, the current study explores the use of Ag nanoparticle (AgNP)–treated activated carbon (AgNPs/AC) nanocomposite as solid phase extractor (SPE) for removal of trace levels of tungstate ions in water. The AgNPs/AC was synthesized by chemical binding of Ag nanoparticles onto AC. The microstructure image indicated that the AgNPs were uniformly dispersed on AC surface and thus maintaining high surface area. Scanning electron micrographs of AgNPs/AC revealed a three-dimensional structure which is suitable as SPE. The AgNPs/AC nanocomposite was used as a low-cost and effective SPE for tungstate removal from water. Adsorption of tungstate from aqueous media reached maximum at pH ≈ 4 and reached equilibrium in < 20 min. Tungstate sorption followed pseudo-second-order kinetic with an overall rate constant (k) of 0.72 min.⁻¹ The negative values of ΔH and ΔG are interpreted as exothermic and spontaneous reaction of tungstate sorption by the adsorbent, respectively. The positive value of ΔS (R² = 0.999) reflected good absorption and/or adsorption of the oxyanion [WO₄]²⁻ as an ion associate with the bulky cations and the surface area available in the nanocomposite. The sorbent AgNPs/AC was also packed column for preconcentration of trace levels of tungstate in tap water samples. Tungstate species were satisfactorily recovered with NaOH (1.0 mol L⁻¹) and subsequently ICP-OES analyzed.

In this work, an aqueous solution containing industrial dyes consisting of methylene blue (MB), and methyl red (MR) was treated with bio-oxidize grape marc entrapped or not in calcium alginate hydrogels. Experiments were carried out in batch, a room temperature using different concentration of adsorbents and dyes. When dyes were evaluated separately, non-immobilized grape marc hydrogel was unable to remove any MR, whereas when the bioadsorbent was immobilized in calcium alginate beads the removal of MR was around 88%. Contrarily, 98% of MB was removed with both, non-entrapped or entrapped grape marc. Regarding binary mixtures, it was observed that the adsorption of MR was not affected by the presence of MB, whereas the adsorption of MB decreased in high extend on non-entrapped grape marc when MR was present.Adsorption conditions were optimized for binary mixtures using a Box-Behnken factorial design, obtaining theoretical equations that allowed to calculate the removal percentage and capacity of calcium alginate-grape marc hydrogel depending on the concentration of dyes (40–100 mg/L), ratio between bioadsorbent and water stream (0.6–1.2) and adsorption time (10–60 min). The equations obtained revealed that grape marc hydrogel is able to remove 100.0–93.3% of MB and 78.72–57.80% of MR in 10 min in the range of dye and bioadsorbent stablished in the experimental design, being the extraction time the less significant variable. Additionally, the kinetic study showed that pseudo-second-order was the model that better explained the bioadsorption process for both dyes in binary mixtures onto grape marc hydrogel.

This article describes the water quality scenario of freshwater springs of Baramulla district of Kashmir Valley in light of pollution threats and predicted climate change consequences for Himalayan ecosystems. The study was designed to have insights to what extent the community is relying on the spring water and what policy initiatives and planning perspectives at the government level are currently in vogue for sustainable management of these freshwater springs. Our results indicated that the springs are mild hard water type with nitrate concentration, conductivity, and iron values ranging from 19 to 675 μg/L, 185 to 811 μS/cm, and 1 to 308 μg/L respectively. Water quality index (WQI) revealed that the majority of the springs have excellent to good water quality category, while as in few springs like Aboora (26), Harwan (27), Fugipora (29), and Goigam (30), it was falling under poor to very poor category. Principal component analysis (PCA) generated mainly three components (VF1, VF2, and VF3) with higher Eigen values of 2.0 or more (2.23–6) accounting for 56.92%, 28.85%, and 10.64% of the total variance respectively. The survey highlights revealed the dependence of a large proportion of population for drinking water besides other uses, but no signs of involvement from the government level. Keeping in view the importance of these springs, it is necessitated that this situation should catch the attention of government and policy makers for the management of freshwater springs which can play an important role in fulfilling the UN (United Nations) Sustainable Development Goal (SDG) of access to safe drinking water.