Search Results (24)

The Abelar pilot basin in Coruña (northwestern Spain) has been monitored for hydrological and hydrochemical data to assess the effects of eucalyptus plantation and manure applications on water resources, water quality, and nitrate contamination. Here, we report the machine learning analysis of hydrological and hydrochemical data from the Abelar basin. K-means cluster analysis (CA) is used to relate nitrate concentrations at the outlet of the basin with daily interflows and groundwater flows calculated with a hydrological balance. CA identifies three linearly separable clusters. Times series Gaussian process regression (TS-GPR) is employed to predict surface water nitrate concentration by incorporating hydrological variables as additional input parameters using a time series shifting. TS-GPR allows modelling nitrate concentrations based on shifted interflows and groundwater flows and chemical concentrations with R² = 0.82 and 0.80 for training and testing, respectively. Groundwater flow from five days prior to the current date, $Q_{g5}$, is the most important input parameter of the TS-GPR model. Interaction effects between the variables are found. TS-GPR validation with recent data provides results consistent with those of testing (R² = 0.85). Model inspection by permutation feature importance and partial dependence plots shows interactions between $Q_{g5}$ and Cl, and between Ca and Mg. Full article

Background: In the last few decades, the field of coordination chemistry has grown very fast, especially in the fields of pharmaceutical, biological and catalytic studies. In ancient times, metals were thought to be beneficial to health issues but nowadays the link between organic–metal substances and different industrial and medicinal properties is well established. Methods: A Schiff base ligand (2-fluoro-N’-[(E)-2-hydroxyphenyl) methylene] benzohydrazide) was reacted with a series of transition metals to produce complexes with a general formula [ML₂(NO₃)]NO₃.nH₂O, where [M = Zn, Cu, Co, Ni, Mn], and [n = 0, 1], corresponding to complexes 1–5. The nature of the bond was determined in the solid state and solution using spectral studies (¹H-NMR, ¹³C-NMR, UV-Vis and FT-IR), TGA, EPR, elemental analysis and molar conductivity measurement. Results: All M(II) complexes are 1:1 electrolytes, as illustrated by their molar conductivities. The results demonstrate that all synthesized complexes present a coordination number of six by the bonding of the bidentate ligand via its azomethine nitrogen atoms and carbonyl oxygen atoms, as well as with one nitrate group as a bidentate ligand via two oxygen atoms. The DPPH radical scavenging technique was used to investigate the antioxidant activities of the ligand [L] and the metal complexes. It is clear that the activity increased in M (II) complexes compared to the Schiff base ligand. Complex 5 showed the highest activity, with an excellent activity of 90.4%, while complex 4 showed the lowest. The antibacterial activities of the Schiff base and its complexes have been examined against various pathogenic bacteria to measure their inhibition potential. Complex 2 showed remarkable activity against Gram (+) bacteria and fungi with an MIC value of 8 μg/mL, which is greater than that of the positive controls, oxytetracycline and fluconazole. The catalytic activities of all complexes were examined in the oxidation of aniline, and the results illustrated that all complexes had a 100% selectivity in producing only azobenzene, and complex 4 had the highest activity (91%). Conclusion: The obtained results from this study show that the antioxidant and antibacterial properties of both the Schiff base ligand and its derived complexes are promising, with some demonstrating remarkable activities. Moreover, the catalytic activities and selectivities of the prepared complexes in aniline oxidation are interesting. Full article

Chalcones are organic structures that occur naturally in flavonoids and isoflavonoids from diverse vegetables and fruits. Their properties have promising applications in medicinal chemistry as antiparasitic agents against malaria, leishmaniasis, and Chagas disease. Parasitic diseases, a global health challenge, affect thousands of people around the world. The lack of access to affordable treatments causes many deaths, especially in developing countries. Chagas disease, a neglected infection whose etiological agent is the protozoan Trypanosoma cruzi (T. cruzi), is currently incurable without timely treatment and depends on two primary nitrated chemotherapeutic agents: Nifurtimox (Nfx) and Benznidazole (Bzn). However, these drugs exhibit low selectivity and serious adverse effects, accentuating the critical need to develop new, safer chemotherapeutic options. In this context, herein we report the synthesis of halogen chalcone derivatives by an affordable and sustainable method. In vitro studies against T. cruzi demonstrated that the fluorine-containing structures have the best bioactive profile with inhibitions comparable to Nfx and Bzn. Additionally, ADME analysis was performed to determine the crucial physicochemical and pharmacokinetic descriptors of the series of compounds, which were shown to be suitable for enteral absorption and have a low risk of crossing the blood–brain barrier and damaging brain tissue. Full article

The Marano and Grado Lagoon (Adriatic Sea, Italy) is an important transitional environment that furnishes numerous ecosystem services and is under protection as Site of Community Importance. It suffers from an excess of nutrients, especially nitrate (NO₃⁻), and has been designated as a nitrate vulnerable zone. In this work, sixteen water bodies were seasonally monitored for physicochemical parameters and nutrients, to elucidate the trophic state of the lagoon and to check the occurrence of significant temporal trends in a time series from 2011 to 2021. Steep gradients of spatial and seasonal distribution were observed for all parameters with elevated concentration of N-NO₃⁻ (up to 360 µM) in the western sector. The whole lagoon was in phosphorous limitation (P-PO₄³⁻ mean ± s.d. = 0.15 ± 0.22 µM) with a mean Redfield ratio of 1130. The concentration of nutrients was significantly correlated with the degree of both freshwater inputs and precipitation. The calculation of trophic indices shows that the lagoon is in an oligotrophic to hypertrophic condition (i.e., TRIX 1.9–6.8). The analysis of the temporal series showed that despite some significant trends, the time span considered is too short to detect significant changes in the trophic state of this dynamic environment. Full article

Purpose of the study: the creation of a dextran coating on cerium oxide crystals using different ratios of cerium and dextran to synthesize nanocomposites, and the selection of the best nanocomposite to develop a nanodrug that accelerates quality wound healing with a new type of antimicrobial effect. Materials and methods: Nanocomposites were synthesized using cerium nitrate and dextran polysaccharide (6000 Da) at four different initial ratios of Ce(NO₃)₃x6H₂O to dextran (by weight)—1:0.5 (Ce0.5D); 1:1 (Ce1D); 1:2 (Ce2D); and 1:3 (Ce3D). A series of physicochemical experiments were performed to characterize the created nanocomposites: UV-spectroscopy; X-ray phase analysis; transmission electron microscopy; dynamic light scattering and IR-spectroscopy. The biomedical effects of nanocomposites were studied on human fibroblast cell culture with an evaluation of their effect on the metabolic and proliferative activity of cells using an MTT test and direct cell counting. Antimicrobial activity was studied by mass spectrometry using gas chromatography–mass spectrometry against E. coli after 24 h and 48 h of co-incubation. Results: According to the physicochemical studies, nanocrystals less than 5 nm in size with diffraction peaks characteristic of cerium dioxide were identified in all synthesized nanocomposites. With increasing polysaccharide concentration, the particle size of cerium dioxide decreased, and the smallest nanoparticles (<2 nm) were in Ce2D and Ce3D composites. The results of cell experiments showed a high level of safety of dextran nanoceria, while the absence of cytotoxicity (100% cell survival rate) was established for Ce2D and C3D sols. At a nanoceria concentration of 10⁻² M, the proliferative activity of fibroblasts was statistically significantly enhanced only when co-cultured with Ce2D, but decreased with Ce3D. The metabolic activity of fibroblasts after 72 h of co-cultivation with nano composites increased with increasing dextran concentration, and the highest level was registered in Ce3D; from the dextran group, differences were registered in Ce2D and Ce3D sols. As a result of the microbiological study, the best antimicrobial activity (bacteriostatic effect) was found for Ce0.5D and Ce2D, which significantly inhibited the multiplication of E. coli after 24 h by an average of 22–27%, and after 48 h, all nanocomposites suppressed the multiplication of E. coli by 58–77%, which was the most pronounced for Ce0.5D, Ce1D, and Ce2D. Conclusions: The necessary physical characteristics of nanoceria–dextran nanocomposites that provide the best wound healing biological effects were determined. Ce2D at a concentration of 10⁻³ M, which stimulates cell proliferation and metabolism up to 2.5 times and allows a reduction in the rate of microorganism multiplication by three to four times, was selected for subsequent nanodrug creation. Full article

Nitrogen fertilizer increases agricultural yields but increases economic costs and causes a series of environmental problems. Arbuscular mycorrhizal fungi (AMF) have the potential to be used as biological fertilizer. However, the influence of nitrogen form on plant growth responsiveness to AMF inoculation is poorly understood. In this study, we investigated the effects of Funneliformis mosseae on growth, root morphology and photosynthetic characteristics of Camellia oleifera under different nitrogen forms during three harvest periods and clarified the most suitable nitrogen form for C. oleifera–AMF symbiosis. The results showed that urea, ammonium and nitrate nitrogen promoted plant growth and photosynthetic capacity, among which urea treatment had the highest value in all three harvests. No significant difference in plant growth parameters was observed between ammonium and nitrate nitrogen treatments in the first two harvests, while the plant height was significantly lower under ammonium nitrogen treatment than nitrate nitrogen treatment in the third harvest. Inoculation with F. mosseae in the presence of indigenous AMF could promote AMF colonization and plant growth at all three harvest times. Inoculation with F. mosseae significantly increased gas exchange parameters, the maximum photochemical efficiency (Fv/Fm) and the actual photochemical efficiency (ΦPSII). Inoculation with AMF increased the photochemical quenching coefficient (qP) better under urea treatment and improved the non-photochemical quenching coefficient (qN) better under ammonium nitrogen treatment. Principal component analysis showed that urea is the most beneficial nitrogen fertilizer for C. oleifera–AMF symbiosis. The results of this study provide a theoretical basis for the combination use of AMF and nitrogen fertilizer in agroforestry. Full article

This paper aims to systematize a series of statistical methods of analysis and control and proposes some forecast models for surface water pollution both in and near a large city. The monitoring data of heavy metals, nitrites, and phosphates collected for three years are processed using different statistical tools. It is demonstrated that they are under statistical control, and appropriate mathematical models are formulated to allow for forecasting and understanding of the causes of the appearance and perpetuation of certain phenomena. A comparative analysis is made, and the generalization of some methods is considered as an analysis and control tool. Full article

Groundwater is regarded as the primary source of agricultural and drinking water in semi-arid and arid regions. However, toxic substances released from sources such as landfills, industries, insecticides, and fertilizers from the previous year exhibited extreme levels of groundwater contamination. As a result, it is crucial to assess the quality of the groundwater for agricultural and drinking activities, both its current use and its potential to become a reliable water supply for individuals. The quality of the groundwater is critical in Egypt’s Sohag region because it serves as a major alternative source of agricultural activities and residential supplies, in addition to providing drinking water, and residents there frequently have issues with the water’s suitability for human consumption. This research assesses groundwater quality and future forecasting using Deep Learning Time Series Techniques (DLTS) and long short-term memory (LSTM) in Sohag, Egypt. Ten groundwater quality parameters (pH, Sulfate, Nitrates, Magnesium, Chlorides, Iron, Total Coliform, TDS, Total Hardness, and Turbidity) at the seven pumping wells were used in the analysis to create the water quality index (WQI). The model was tested and trained using actual data over nine years from seven wells in Sohag, Egypt. The high quantities of iron and magnesium in the groundwater samples produced a high WQI. The proposed forecasting model provided good performances in terms of average mean-square error (MSE) and average root-mean-square error (RMSE) with values of 1.6091 × 10⁻⁷ and 4.0114 × 10⁻⁴, respectively. The WQI model’s findings demonstrated that it could assist managers and policymakers in better managing groundwater resources in arid areas. Full article

Over the last decades, groundwater resources at global level have suffered a significant deterioration due to nitrate pollution, mainly related to the input of agricultural fertilizers, manure, sewage, and untreated urban and industrial effluents. The most impacted waters are those forming surface and shallow reservoirs, which usually play a key role in supplying waters to civil, agricultural, and industrial activities. The terminal portion of the Metauro River plain, located in central Italy along the Adriatic Sea coastline, hosts a strategic phreatic aquifer that, along with the surface water of the Metauro River, supplies water to the local population (i.e., about 60,000 people). This shallow coastal aquifer experiences a long-lasting story of nitrate contamination since the 1970s when the increase in the use of agricultural fertilizers contributed to very high levels of pollution (NO₃⁻ > 100 mg/L). This fact prompted the local authorities to carry out remediation actions that involve a pumping system to inject the NO₃⁻-poor waters from the Metauro River course directly into the shallow aquifer. The present work was aimed at defining the contamination of nitrates in this important water resource. The main geochemical characteristics and the temporal evolution of NO₃⁻ concentrations (between 2009 and 2020), in the shallow coastal aquifer of the Metauro River plain, were analyzed by means of classical geochemical analyses and multivariate methods accounting for the compositional nature of the data, to assess the efficiency of the in-situ remediation over time. Full article

Excess irrigation may result in deep percolation and nitrate transport to groundwater. Furthermore, under Mediterranean climate conditions, heavy winter rains often result in high deep percolation, requiring the separate identification of the two sources of deep percolated water. An integrated methodology was developed to estimate the spatio-temporal dynamics of deep percolation, with the actual crop evapotranspiration (ET_{c act}) being derived from satellite images data and processed on the Google Earth Engine (GEE) platform. GEE allowed to extract time series of vegetation indices derived from Sentinel-2 enabling to define the actual crop coefficient (K_{c act}) curves based on the observed lengths of crop growth stages. The crop growth stage lengths were then used to feed the soil water balance model ISAREG, and the standard K_c values were derived from the literature; thus, allowing the estimation of irrigation water requirements and deep drainage for independent Homogeneous Units of Analysis (HUA) at the Irrigation Scheme. The HUA are defined according to crop, soil type, and irrigation system. The ISAREG model was previously validated for diverse crops at plot level showing a good accuracy using soil water measurements and farmers’ irrigation calendars. Results show that during the crop season, irrigation caused 11 ± 3% of the total deep percolation. When the hotspots associated with the irrigation events corresponded to soils with low suitability for irrigation, the cultivated crop had no influence. However, maize and spring vegetables stood out when the hotspots corresponded to soils with high suitability for irrigation. On average, during the off-season period, deep percolation averaged 54 ± 6% of the annual precipitation. The spatial aggregation into the Irrigation Scheme scale provided a method for earth-observation-based accounting of the irrigation water requirements, with interest for the water user’s association manager, and at the same time for the detection of water losses by deep percolation and of hotspots within the irrigation scheme. Full article

Groundwater is an important source of fresh water in the world. However, the excessive extraction and increasing pollution represent a major challenge for water sustainability in Mexico. Nowadays, since water quality changes in aquifers are not noticeable, aquifer monitoring and assessment are imperious. In this study, the water quality of the Cuernavaca aquifer was evaluated using a database of 23 parameters in 4 sampling points from 2012 to 2019. The spatial behavior of water quality variables was described by using interpolation. The temporal evaluation of groundwater quality was carried out through time series. Water quality indices (WQI) were obtained in this aquifer and the WQI values suggest that the groundwater could be considered as good quality for potable use and of medium-high quality for irrigation. The chemical characteristics of the groundwater were also evaluated using Gibb, Piper, and Schoeller diagrams. Finally, with a total of 34 samples of each parameter in each sampling site, a multivariate statistical analysis was performed using a Pearson correlation and hierarchical cluster analysis. This analysis showed a correlation between hydrochemical features and groundwater quality parameters, where nitrates presented the highest number of significant correlations with other parameters. These results may be useful for the authorities to adopt planning methods to improve the sustainable development of the aquifer. Full article

Accurate, on-site determinations of macronutrients (phosphate (PO₄³⁻), nitrate (NO₃⁻), and silicic acid (H₄SiO₄)) in seawater in real time are essential to obtain information on their distribution, flux, and role in marine biogeochemical cycles. The development of robust sensors for long-term on-site analysis of macronutrients in seawater is a great challenge. Here, we present improvements of a commercial automated sensor for nutrients (including PO₄³⁻, H₄SiO₄, and NO₂⁻ plus NO₃⁻), suitable for a variety of aquatic environments. The sensor uses the phosphomolybdate blue method for PO₄³⁻, the silicomolybdate blue method for H₄SiO₄ and the Griess reagent method for NO₂⁻, modified with vanadium chloride as reducing agent for the determination of NO₃⁻. Here, we report the optimization of analytical conditions, including reaction time for PO₄³⁻ analysis, complexation time for H₄SiO₄ analysis, and analyte to reagent ratio for NO₃⁻ analysis. The instrument showed wide linear ranges, from 0.2 to 100 μM PO₄³⁻, between 0.2 and 100 μM H₄SiO₄, from 0.5 to 100 μM NO₃⁻, and between 0.4 and 100 μM NO₂⁻, with detection limits of 0.18 μM, 0.15 μM, 0.45 μM, and 0.35 μM for PO₄³⁻, H₄SiO₄, NO₃⁻, and NO₂⁻, respectively. The analyzer showed good precision with a relative standard deviation of 8.9% for PO₄³⁻, 4.8% for H₄SiO₄, and 7.4% for NO₂⁻ plus NO₃⁻ during routine analysis of certified reference materials (KANSO, Japan). The analyzer performed well in the field during a 46-day deployment on a pontoon in the Kiel Fjord (located in the southwestern Baltic Sea), with a water supply from a depth of 1 m. The system successfully collected 443, 440, and 409 on-site data points for PO₄³⁻, Σ(NO₃⁻ + NO₂⁻), and H₄SiO₄, respectively. Time series data agreed well with data obtained from the analysis of discretely collected samples using standard reference laboratory procedures and showed clear correlations with key hydrographic parameters throughout the deployment period. Full article

With its high water potential, the Ziz basin is one of the most important basins in Morocco. This paper aims to develop a methodology for spatiotemporal monitoring of the water quality of the Hassan Addakhil dam using remote sensing techniques combined with a modeling approach. Firstly, several models were established for the different water quality parameters (nitrate, dissolved oxygen and chlorophyll a) by combining field and satellite data. In a second step, the calibration and validation of the selected models were performed based on the following statistical parameters: compliance index R², the root mean square error and p-value. Finally, the satellite data were used to carry out spatiotemporal monitoring of the water quality. The field results show excellent quality for most of the samples. In terms of the modeling approach, the selected models for the three parameters (nitrate, dissolved oxygen and chlorophyll a) have shown a good correlation between the measured and estimated values with compliance index values of 0.62, 0.56 and 0.58 and root mean square error values of 0.16 mg/L, 0.65 mg/L and 0.07 µg/L for nitrate, dissolved oxygen and chlorophyll a, respectively. After the calibration, the validation and the selection of the models, the spatiotemporal variation of water quality was determined thanks to the multitemporal satellite data. The results show that this approach is an effective and valid methodology for the modeling and spatiotemporal mapping of water quality in the reservoir of the Hassan Addakhil dam. It can also provide valuable support for decision-makers in water quality monitoring as it can be applied to other regions with similar conditions. Full article

The synthesis of the copper-poor and aluminum-rich layered double hydroxides (LDHs) of the CuAl₄ type was optimized in detail in this work, by applying an intense mechanochemical treatment to activate the gibbsite starting reagent. The phase-pure forms of these LDHs were prepared for the first time; using copper nitrate and perchlorate salts during the syntheses turned out to be the key to avoiding the formation of copper hydroxide sideproducts. Based on the use of the optimized syntheses parameters, the preparation of layered triple and multiple hydroxides was also attempted using Ni(II), Co(II), Zn(II) and even Mg(II) ions. These studies let us identify the relative positions of the incorporating cations in the well-known selectivity series as Ni²⁺ >> Cu²⁺ >> Zn²⁺ > Co²⁺ >> Mg²⁺. The solids formed were characterized by using powder X-ray diffractometry, UV–Vis diffuse reflectance spectroscopy, Fourier-transform infrared spectroscopy, thermogravimetric analysis and scanning electron microscopy. The catalytic potential of the samples was investigated in carbon monoxide oxidation reactions at atmospheric pressure, supported by an in situ diffuse reflectance infrared spectroscopy probe. All solids proved to be active and the combination of the nickel and cobalt incorporation (which resulted in a NiCoAl₈ layered triple hydroxide) brought outstanding benefits regarding low-temperature oxidation and increased carbon monoxide conversion values. Full article

The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM_2.5) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April–May), 19 (July–August), 27 (September–October), 28 (December–January) of PM_2.5 were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM_2.5 were analyzed via ion chromatography and inductively coupled plasma–mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM_2.5 concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017–2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM_2.5 concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM_2.5 to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO₃⁻) and sulfate (SO₄²⁻) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM_2.5 in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM_2.5 has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM_2.5 rises by 10 μg·m⁻³, hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741–11.264) and 0.068% (95% CI, 0.067–0.069). GAM model analysis predicted the maximum effect of PM_2.5 exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM_2.5 on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM_2.5 has the greatest effect on HGB. The maximum cumulative effect of PM_2.5 on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM_2.5 increases significantly and has a significant correlation with some blood routine indicators. Full article