Field Samples Research Articles

Utilizing Random Forest algorithm for identifying mafic and ultramafic rocks in the Gameleira Suite, Archean-Paleoproterozoic basement of the Brasília Belt, Brazil

Geological mapping techniques have continuously advanced, particularly with the increasing use of remote data acquisition methods, such as aerogeophysical data analysis and the use of machine learning techniques, both has become essential for mapping and understanding geological environments. Mafic-ultramafic bodies, which may be linked to metallic ore deposits, can be mapped using these innovative techniques. In Brazil, the Tocantins Province is reknown for its primary Cu–Co–Ni–Cr ore deposits, which are found in mafic-ultramafic rocks. The Tocantins Province contains several mafic-ultramafic bodies that have received less attention than the well-known deposits in the Brasília Belt. The Gameleira Suite is a geological unit located in the basement of the North Brasília Belt. Our study aims to use machine learning to identify new potential mafic-ultramafic occurrences in the Gameleira Suite. To achieve this, aerogeophysical surveys data, including magnetometry and radiometry, were used in conjunction with remote sensing. The data collected from aerogeophysics surveys were compiled into a database. The Random Forest algorithm was used to analyze this database, with 1.96% (from a total of 84.535 samples) used for training and generating the predictive map. Three approaches were used to verify and evaluate the data: analyzing magnetic lineaments to assess the influence of structural tectonic factors on body positioning, collecting field samples, and utilizing Magnetic Vector Inversion (MVI) to analyze the magnetic properties of the projected bodies at depth. This was done because the Gameleira Suite bodies display magnetic remanence. Our findings suggest that the utilization of these methods, in conjunction with the verification techniques employed, aids in the mapping and identification of mafic-ultramafic rocks. Machine learning can improve cartography by identifying new occurrences or indicating areas that need more detailed mapping. The use of additional geological knowledge and information not included in the model is crucial because the predictive map does not inherently represent geological truth. It is necessary to interpret the results from a geological perspective.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables.

Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.

New Insights on Tools for Detecting β-Tubulin Polymorphisms in Trichuris trichiura Using rhAmpTM SNP Genotyping.

Soil-transmitted helminth (STH) infections, commonly treated with benzimidazoles, are linked to resistance through single nucleotide polymorphisms (SNPs) at position 167, 198, or 200 in the β-tubulin isotype 1 gene. The aim of this study was to establish a novel genotyping assay characterized by its rapidity and specificity. This assay was designed to detect the presence of SNPs within the partial β-tubulin gene of Trichuris trichiura. This was achieved through the biallelic discrimination at codons 167, 198, and 200 by employing the competitive binding of two allele-specific forward primers. The specificity and reliability of this assay were subsequently confirmed using Trichuris samples isolated from captive primates. Furthermore, a molecular study was conducted to substantiate the utility of the β-tubulin gene as a molecular marker. The assays showed high sensitivity and specificity when applied to field samples. Nevertheless, none of the SNPs within the β-tubulin gene were detected in any of the adult worms or eggs from the analyzed populations. All specimens consistently displayed an SS genotype. The examination of the β-tubulin gene further validated the established close relationships between the T. trichiura clade and Trichuris suis clade. This reaffirms its utility as a marker for phylogenetic analysis.

Liquid-nitrogen-free CTAB DNA extraction method from silica-dried specimens for next-generation sequencing and assembly

Next-generation sequencing requires intact and high-quality DNA. However, typical liquid-nitrogen DNA extraction methods are expensive and not practical for field sample collections. Hence, we present a cost-effective method for DNA extraction from silica-dried leaf samples, eliminating the need for liquid nitrogen. Two protocols were evaluated to determine the effectiveness of grinding dried plant samples without liquid nitrogen in comparison to the standard protocol for tissue homogenization and cell lysis. Protocol 1 involved grinding fresh leaf samples with liquid nitrogen, while Protocol 2 entailed incubating dried plant samples at-20 °C for 1 h before grinding in the absence of liquid nitrogen. Both protocols produced comparable DNA yields with an average A260/A280 ratio of 1.78±0.02, suitable for short- and long-read sequencing. Using Protocol 2, we successfully assembled ten plastomes. It also demonstrated versatility as comparable DNA quality was obtained from dried mollusks and actinomycetes, resulting in thesuccessful assembly of two complete mitochondrial genomes. The protocol is advantageous for research workflows involving the collection of samples in the field as a long-term source of genetic material.•Drying: Fresh samples were silica-dried at silica-to-sample ratio of 2:1.•Pre-lysis: Dried samples were frozen at −20 °C for 1 hour before grinding.•Frozen samples were subjected to tissue homogenization followed by the standard CTAB DNA extraction.

Oxidative Stress Response of Honey Bee Colonies (Apis mellifera L.) during Long-Term Exposure at a Frequency of 900 MHz under Field Conditions.

In this study, oxidative stress and lipid peroxidation in honey bee larvae, pupae and the midguts of adult bees were investigated during a one-year exposure to radiofrequency electromagnetic fields (RF-EMFs) at a frequency of 900 MHz under field conditions. The experiment was carried out on honey bee colonies at three locations with electric field levels of 30 mV m-1, 70 mV m-1 and 1000 mV m-1. Antioxidant enzymes, glutathione-S-transferase (GST), catalase (CAT) and superoxide dismutase (SOD) and thiobarbituric acid reactive substances (TBARS) as indicators of lipid peroxidation were measured spectrophotometrically. The GST activity within the same developmental stage showed no significant differences regardless of electric field level or sampling time. The highest GST activity was found in the pupae, followed by activity in the larvae and midguts. Both CAT activity and TBARS concentration were the highest in the midguts, regardless of field level and sampling time. The larvae showed a significantly higher TBARS concentration at the location with an electric field level of 1000 mV m-1 compared to the locations with lower levels. Our results show that RF-EMFs at a frequency of 900 MHz can cause oxidative stress in honey bees, with the larval stage being more sensitive than the pupal stage, but there was no linear relationship between electric field level and effect in any of the developmental stages.

Human Health Risk Assessment of Radionuclide Contamination in Drinking Water

This study investigates the human health risks of uranium, radium, radon, and other drinking water radionuclides and their mitigation strategies. It was implemented through literature review, field sampling, and analytical methods. Samples were taken from various sources, including groundwater, surface water, municipal supplies, and private wells. ICPI-MS and liquid scintillation counters were used for radiation measurements. Statistical analysis and risk assessment models were used to measure health risks and treatment effectiveness. Groundwater sources were the main sources of radionuclides, with private wells being the main sources. The elimination efficiencies of reverse osmosis were exceptional, reaching up to 99%. The elderly population (60+ years) were the most likely to have cancer, with the highest risks for bladder cancer, lung cancer, kidney cancer, and leukemia. The frequency of radionuclide contamination in drinking water sources varied, with the U.S. Environmental Protection Agency, Nigerian EPA, and Canada having the strictest schedules. The results emphasize the urgent need for monitoring programs, effective treatment technologies, and targeted risk management strategies to cope with radionuclide contamination. Government advice includes improving the regulatory system, developing advanced treatment methods, long-term epidemiological studies, public awareness, interdisciplinary collaboration, scientific exploration of alternative water sources, and prioritizing interventions for vulnerable populations.

Field isolation and capture of fluoroquinolones in waters with porous monolith-based multiple channels in-tip microextraction technique prior to HPLC quantification

Field isolation and capture is significant in the accuracy and reliable monitoring of fluoroquinolones (FQs) contents in environmental waters. For this purpose, a new porous monolith-based adsorbent (PMPA) was in-situ fabricated in pipette tip using 1-octyl-3-vinylimidazolium tetrafluoroborate and 1H,1H,2H,2H-heptadecafluorodecyl acrylate as mixed functional monomers. The PMPA prepared under the optimized parameters was characterized by various techniques. In addition, the prepared PMPA was employed as the adsorbent of home-developed multiple channels in-tip microextraction technique (MCIM) for the field sample preparation of FQs. Results revealed that the obtained PMPA exhibited satisfactory capture capability towards studied FQs, and the enrichment factors ranged from 128 to 203. Under the most beneficial extraction conditions, the developed PMPA/MCIM was employed to on-site extract trace FQs in a variety of aqueous samples and followed by quantification with HPLC equipped with fluorescence detector. The achieved limits of detection, precision and spiked recoveries were in the ranges of 0.22–0.78 ng/L, 1.4–9.9 % and 80.0–118 %, respectively. Furthermore, confirmation experiments with reported approach were utilized to evaluate method accuracy. In comparison with documented approaches, the current study exhibits some features such as high sensitivity, convenience, low cost and environmental friendliness. At the same time, the established method overcomes the dilemmas encountered in traditional lab-based sample preparation procedure.

Characterization of Respirable Coal Mine Dust Recovered from Fibrous Polyvinyl Chloride Filters by Scanning Electron Microscopy

The characterization of respirable dust on the basis of constituent fractions and particle sizes is increasingly of concern for evaluating exposure hazards. For high-resolution particle analysis, scanning electron microscopy with energy dispersive X-ray (SEM-EDX) can be an effective tool. However, it requires particles to be deposited on a smooth, uniform substrate such as a polycarbonate (PC) filter for optimal results. While direct sampling onto PC is possible, this is not the standard approach in many situations. For example, in coal mines, respirable dust samples have typically been collected onto polyvinyl chloride (PVC) filters because they are intended for gravimetric and/or infrared spectroscopy analysis. Such fibrous substrates are not ideal for SEM-EDX (or other microscopy), but an effective method to recover and redeposit the dust particles could render such samples suitable for the additional analysis. Here, we present a simple method and compare SEM-EDX results for paired samples analyzed directly on PC and following recovery from PVC and redeposition on PC. Both laboratory-generated dust samples (n = 10 pairs) and field samples of respirable coal mine dust (n = 44 pairs) are included in this study. Although some changes in particle size distributions were observed between samples analyzed directly and those that were recovered and redeposited prior to analysis, the results indicate the dust recovery method generally yields a representative sample in terms of mineral constituents. That said, results also highlighted the effects of high particle loading density on individual particle analysis. Considering all sample pairs, those with similar loading density between the directly analyzed and recovered sample tended to exhibit similar mineralogy distributions. This was generally the case for the lab-generated sample pairs, and the Freeman-Halton exact test of independence indicated that the samples in just three (of 10) pairs were in disagreement in terms of their mineralogy distributions. On the other hand, for the field samples, the directly analyzed sample often had higher loading density than the recovered sample; and the Freeman-Halton test showed that 25 (of 44) pairs were in disagreement. However, the effect of possible particle agglomeration on the directly analyzed samples cannot be ruled out—and exploration of this factor was beyond the scope of the current study.

Effect of thermodiffusion on compositional grading in hydrocarbon reservoirs: Insights from field cases and simulations

Heterogeneity of fluid composition in vertical and lateral directions is observed in many reservoirs, known as compositional grading. It is necessary to evaluate the diffusion forces for modeling this phenomenon. In addition to the chemical and gravity forces, the temperature gradient causes mass diffusion. In the present investigation, the accuracy and reliability of the Haase theory and the Shukla-Firoozabadi method in thermodiffusion modeling are studied comprehensively using field samples from light to heavy-oil reservoirs. On the one hand, the Shukla-Firoozabadi model results in compositional grading reduction by thermodiffusion; on the other hand, the Haase theory reveals enhancement and attenuation effects of thermodiffusion depending on reference enthalpy quantification. A new approach, which employs the reference enthalpies of pseudocomponents as tuning parameters, is proposed to improve the results of the Haase theory. The proposed procedure is also validated using field cases. In addition, the experimental field information compared with isothermal and nonisothermal models are studied to answer the question of "how" and to "what extent" thermodiffusion contributes to compositional grading. Results demonstrated the limited attenuation effect of thermodiffusion in light oils, while this phenomenon leads to severe enhancement of compositional grading in the medium and heavy-oil reservoirs. In heavy oils, the thermodiffusion effect is more pronounced on heavy pseudocomponents rather than light paraffinic species. Finally, the practice of compositional gradient model optimization, which is of particular interest to reduce the uncertainty in fluid initialization and to address reservoir compartmentalization, is presented.

Advancing illicit connection diagnosis of urban stormwater pipes: Comprehensive analysis with EEM fluorescence spectroscopy

Urban drainage systems are significant contributors to the issue of black-odorous water bodies. The current application of stormwater pipe inspection technologies faces substantial limitations, especially in industrial areas with diverse wastewater. This study introduced an innovative approach using excitation-emission matrix (EEM) fluorescence spectroscopy for rapid and accurate diagnosis, providing a new perspective for diagnosing illicit connections. In single wastewater-type areas like residential zones, the method achieved a remarkable 91.5 % accuracy solely through spectra observation and fluorescence peak intensity comparison, outperforming conventional NH3-N-based techniques, which reached an accuracy of only 68.1 %. For regions with complex wastewater scenarios, after EEM subtraction, the residual spectra can be roughly categorized into four distinctive categories based on characteristics. This provides a preliminary assessment and helps in initially identifying the types and sources of inflowing wastewater. Furthermore, the least squares (LS) method refines diagnosis results, offering calculated coefficients reflecting the probability and severity of suspected wastewater intrusion. Simulation experiments and field sample analyses validated the feasibility and accuracy of the EEM-based method, highlighting its advantages for diagnosing illicit connections in both single and mixed wastewater scenarios. The results can significantly narrow down the investigation scope and enhance the confirmation of wastewater sources, exhibiting promising application prospects.

Deep soil desiccation hinders nitrate leaching to groundwater in the global largest apple cultivation area

Massive use of N fertilizer in apple orchards aids China’s Loess Plateau (CLP) to become the largest region of apple production in the world, but it also leads to substantial nitrate accumulation in the vadose zone, posing a potential environmental risk. However, a holistic understanding of the spatial patterns and controls of soil nitrate in the vadose zone of apple orchards remains understudied, which is unfavorable for the formulation of a science-based N application strategy. To this end, we collected a total of 2852 paired data across apple orchards on the CLP from 52 published literature and 1000 paired data from our field sampling. We found that residual nitrate accumulation primarily occurred in the top 4–8.8 m soil layer, and it varied according to mean annual precipitation (MAP) and stand age; the accumulation peaked in sites with MAP of 500–600 mm and declined with a decrease in MAP; and among various stand ages, the highest nitrate content was observed in the 25-yr-old orchard. It was found that MAP and N fertilizer application amounts dominated nitrate accumulation in the soil. Furthermore, the desiccation index of the soil layer below the maximum cumulative depth was identified as the main factor influencing soil nitrate maximum accumulation depth . This means that deep soil desiccation hinders nitrate leaching towards deeper layers and reduces the risk of groundwater contamination. The findings here may provide insights into sustainable nitrogen and water management in apple orchards on the CLP and potentially in other similar regions.

Satellite Advanced Spaceborne Thermal Emission and Reflection Radiometer Mineral Maps of Australia Unmixed of Their Green and Dry Vegetation Components: Implications for Mapping (Paleo) Sediment Erosion–Transport–Deposition Processes

The 2012 satellite ASTER geoscience maps of Australia were designed to provide public, web-accessible, and spatially comprehensive surface mineralogy for improved mapping and solutions to geoscience challenges. However, a number of the 2012 products were clearly compromised by variable green and/or dry vegetation cover. Here, we show a strategy to first estimate and then unmix the contributions of both these vegetation components to leave, as residual, the target surface mineralogy. The success of this unmixing process is validated by (i) visual suppression/removal of the regional climate and/or local fire-scar vegetation patterns; and (ii) pixel values more closely matching field sample data. In this process, we also found that the 2012 spectral indices used to gauge the AlOH content, AlOH composition, and water content can be improved. The updated (new indices and vegetation unmixed) maps reveal new geoscience information, including: (i) regional “wet” and “dry” zones that appear to express “deep” geological characters often expressed through thick regolith cover, with one zone over the Yilgarn Craton spatially anti-correlated with Archaean gold deposits; (ii) a ~1000 km wide circular feature over the Lake Eyre region defined by a rim of abundant “muscovite” that appears to coincide with opal deposits; (iii) a N–S zonation across the western half of the continent defined by abundant muscovite in the south and kaolinite in the north, which appears to reflect opposing E ↔ W aeolian sediment transport directions across the high-pressure belt; (iv) various paleo-drainage networks, including those over aeolian sand covered the “lowlands” of the Canning Basin, which are characterized by low AlOH content, as well as those over eroding “uplands”, such as the Yilgarn Craton, which have complicated compositional patterns; and (v) a chronological history of Miocene barrier shorelines, back-beach lagoons, and alluvial fans across the Eucla Basin, which, to date, had proved elusive to map using other techniques, with potential implications for heavy mineral sand exploration. Here, we explore the latter three issues.

Rapid morphosedimentary development of a shallow subtropical embayment in response to extreme episodic flooding

Variability in supply of terrestrial sediments to the coastal zone impacts sediment transport processes and ecological dependencies. This study investigated surface sediment distribution and transportation within a 2020 km2 shallow embayment following a period of flood induced sediment supply. Extensive field sampling of 221 common sites between 2015 and the 2019 follow-up survey presented, identified significant reduction in fine sediment fractions, evident through a 367 km2 decrease in surface mud coverage. Wind-wave sediment transport processes controlled the spatial distribution of fine sediments, exporting 23 million tonnes of mud from the shallow sedimentation zones. In a broader context, sensitive benthic habitats such as seagrass meadows exhibited signs habitat recolonisation coinciding with areas of reduced mud content. Despite these promising short-term outlooks, the developed fine sediment budget suggests ongoing terrestrial sedimentation will exhaust key sediment sinks within Moreton Bay, effectively reducing the system's ability to buffer future sedimentation events.

Crown ether decorated silicon photonics for safeguarding against lead poisoning

Lead (Pb2+) toxification is a concerning, unaddressed global public health crisis that leads to 1 million deaths annually. Yet, public policies to address this issue have fallen short. This work harnesses the unique abilities of crown ethers, which selectively bind to specific ions. This study demonstrates the synergistic integration of highly-scalable silicon photonics, with crown ether amine conjugation via Fischer esterification in an environmentally-friendly fashion. This realizes an integrated photonic platform that enables the in-operando, highly-selective and quantitative detection of various ions. The development dispels the existing notion that Fischer esterification is restricted to organic compounds, facilitating the subsequent amine conjugation for various crown ethers. The presented platform is specifically engineered for selective Pb2+ detection, demonstrating a large dynamic detection range, and applicability to field samples. The compatibility of this platform with cost-effective manufacturing indicates the potential for pervasive implementation of the integrated photonic sensor technology to safeguard against societal Pb2+ poisoning.

First ontogenesis and bioecological study of Sciobia bouvieri (Orthoptera, Gryllidae), a North African endemic species

This study aimed to investigate the bioecology and life cycle of the Algerian endemic Sciobia bouvieri, which remained unknown until recently. A combined approach of field sampling through direct searching and captive rearing of S. bouvieri nymphs under natural conditions was employed to determine the population ontogeny. The life cycle was found to comprise three stages: egg, nymph, and adult. The embryonic development period ranged from 22 to 30 days. Females laid an average of 9.4 ± 1.3 eggs per clutch. The nymphal stage consisted of six instars, lasting an average of 306.5 days. Adult longevity varied, with males living 32.3 ± 16.2 days and females living 23.9 ± 22.4 days. The duration of the ontogenesis cycle of Sciobia bouvieri in nature showed that it has a univoltine life cycle with summer and winter diapauses occurring during the fourth and fifth larval stages, respectively. These diapauses are likely controlled by photoperiod and temperature. This is the first study of the bioecology and life cycle of this North African endemic species.

Simultaneous determination of five plant hormones in cotton leaves using QuEChERS combined with HPLC‒MS/MS

BackgroundPlant hormones profoundly influence cotton growth, development, and responses to various stresses. Therefore, there is a pressing need for an efficient assay to quantify these hormones in cotton. In this groundbreaking study, we have established QuEChERS-HPLC‒MS/MS method, for the simultaneous detection of multiple plant hormones in cotton leaves, allowing the analysis and quantification of five key plant hormones.ResultsSample extraction and purification employed 0.1% acetic acid in methanol and C18 for optimal recovery of plant hormones. The method applied to cotton demonstrated excellent linearity across a concentration range of 0.05–1 mg·L−1, with linear regression coefficients exceeding 0.99. The limits of quantification (LOQs) were 20 μg·kg−1 for GA3 and 5 μg·kg−1 for the other four plant hormones. Recovery rates for the five plant hormones matrix spiked at levels of 5, 10, 100, and 1000 μg·kg−1 were in the range of 79.07% to 98.97%, with intraday relative standard deviations (RSDs) ranging from 2.11% to 8.47%. The method was successfully employed to analyze and quantify the five analytes in cotton leaves treated with plant growth regulators.ConclusionThe study demonstrates that the method is well-suited for the determination of five plant hormones in cotton. It exhibits excellent selectivity and sensitivity in detecting field samples, thus serving as a robust tool for in-depth research into cotton physiology.

The Development of a Sensitive Droplet Digital Polymerase Chain Reaction Test for Quantitative Detection of Goose Astrovirus

(1) Goose astrovirus (GAstV) is a novel emerging pathogen that causes significant economic losses in waterfowl farming. A convenient, sensitive, and specific detection method for GAstV in field samples is important in order to effectively control GAstV. Droplet digital polymerase chain reaction (ddPCR) is a novel, sensitive, good-precision, and absolute quantitation PCR technology which does not require calibration curves. (2) In this study, we developed a ddPCR system for the sensitive and accurate quantification of GAstV using the conserved region of the ORF2 gene. (3) The detection limit of ddPCR was 10 copies/µL, ~28 times greater sensitivity than quantitative real-time PCR (qPCR). The specificity of the test was determined by the failure of amplification of other avian viruses. Both ddPCR and qPCR tests showed good repeatability and linearity, and the established ddPCR method had high sensitivity and good specificity to GAstV. Clinical sample test results showed that the positive rate of ddPCR (88.89%) was higher than that of qPCR (58.33%). (4) As a result, our results suggest that the newly developed ddPCR method might offer improved analytical sensitivity and specificity in its GAstV measurements. The ddPCR could be widely applied in clinical tests for GAstV infections.

Global diversity of airborne pathogenic bacteria and fungi from wastewater treatment plants

Wastewater treatment plants (WWTPs) have been recognized as one of the major potential sources of the spread of airborne pathogenic microorganisms under the global pandemic of COVID-19. The differences in research regions, wastewater treatment processes, environmental conditions, and other aspects in the existing case studies have caused some confusion in the understanding of bioaerosol pollution characteristics. In this study, we integrated and analyzed data from field sampling and performed a systematic literature search to determine the abundance of airborne microorganisms in 13 countries and 37 cities across four continents (Asia, Europe, North America, and Africa). We analyzed the concentrations of bioaerosols, the core composition, global diversity, determinants, and potential risks of airborne pathogen communities in WWTPs. Our findings showed that the culturable bioaerosol concentrations of global WWTPs are 102–105 CFU/m3. Three core bacterial pathogens, namely Bacillus, Acinetobacter, and Pseudomonas, as well as two core fungal pathogens, Cladosporium and Aspergillus, were identified in the air across global WWTPs. WWTPs have unique core pathogenic communities and distinct continental divergence. The sources of airborne microorganisms (wastewater) and environmental variables (relative humidity and air contaminants) have impacts on the distribution of airborne pathogens. Potential health risks are associated with the core airborne pathogens in WWTPs. Our study showed the specificity, multifactorial influences, and potential pathogenicity of airborne pathogenic communities in WWTPs. Our findings can improve the understanding of the global diversity and biogeography of airborne pathogens in WWTPs, guiding risk assessment and control strategies for such pathogens. Furthermore, they provide a theoretical basis for safeguarding the health of WWTP workers and ensuring regional ecological security.

Seasonal Variation of Groundwater Quality in Bonny Island, Rivers State Nigeria

This study investigated the seasonal variations in physicochemical parameters, heavy metals, and petroleum hydrocarbons in groundwater samples collected in nine locations in Bonny Island, Rivers State Nigeria. The water samples for the dry season were collected in December and January while for the wet season, water samples were collected in July and October. A quantitative approach was employed, involving the collection of quantitative data through field sampling and laboratory analysis. Physicochemical parameters, including pH, electrical conductivity, dissolved oxygen, and nutrient levels, were measured using standard analytical techniques. Heavy metal concentrations (Fe, Cd, etc.) were determined using atomic absorption spectrophotometry, while petroleum hydrocarbons (total hydrocarbons and polycyclic aromatic hydrocarbons) were analyzed through solvent extraction and gas chromatography techniques. The study revealed significant seasonal variations in several parameters, with notable significant decreases in phosphate during the wet season and significant increases in chromium and cadmium levels during the dry season (p-value < 0.05). Petroleum hydrocarbon concentrations also exhibited seasonal fluctuations, potentially influenced by precipitation patterns, oil and gas activities, and accidental spills or leaks which were observed during the dry season.

Effects of the freeze–thaw process on sources and pathways of subsurface flow in an alpine hillslope on the northeastern Qinghai-Tibet Plateau

The impact of the freeze–thaw process on the active layer is reflected in the changed subsurface flow (SSF) process in cold alpine regions. Identifying sources and pathways of SSF in the freeze–thaw process is critical but difficult, and the related dominant factors and mechanisms are still unknown. In this paper, the effective identification and analysis of SSF are promoted based on field sampling data from the thawing (June) to freezing (September) period of 2022 in the Qinghai Lake basin on the northeastern Qinghai-Tibetan Plateau. By the proposed method with a high sampling frequency and refined sampling spatial scale, the sources and pathways of SSF are clearly identified. The results are as follows: (1) The soil temperature is considered the most fundamental factor affecting the SSF pathways, it influences water infiltration to the deep layer and the effect is extended to the saprolite and weathered bedrock layers. (2) Thawing promotes water to infiltrating into deep layer. 30 cm soil water contributes the most to SSF (2 %–86 %) in the thawing period, while the contribution difference of the water from the 30 cm, 60 cm, and 90 cm layers is small (ranging from 32 %–33 %, 24 %–26 %, and 32 %–35 %, respectively) in the thawed period. (3) Meanwhile, the soil water from different slope positions contribute differently to SSF, and the SSF from deep soil layer is transit in prolong paths and depths. It is caused by the out-of-sync water transit process in the hillslope. With continuing climate warming, we propose that the differences in the water sources of SSF across soil layers may decrease, while the differences in the transit processes of SSF across soil layers may increase.