Evaluation of potential human health risks arising from nitrate and fluoride in the groundwater of Aurangabad, Bihar using GIS and chemometric analysis.

This study employed the groundwater pollution index to assess the appropriateness of groundwater for human consumption. Additionally, the hazard index was utilized to evaluate the potential non-carcinogenic risks associated with fluoride and nitrate exposure among children, women, and men in the study region. A total of 103 samples were collected from the Aurangabad district of Bihar. The analyzed samples were assessed using several physicochemical parameters. Major cations in the groundwater are Ca2+ > Mg2+ and major anions are HCO3- > Cl- > SO42- > NO3- > F- > PO43-. Around 17% of the collected groundwater samples surpassed the allowable BIS concentration limits for Nitrate, while approximately 11% surpassed the allowed limits for fluoride concentration. Principal component analysis was utilized for its efficacy and efficiency in the analytical procedure. Four principal components were recovered that explained 69.06% of the total variance. The Hazard Quotient (HQ) of nitrate varies between 0.03-1.74, 0.02-1.47, and 0.03-1.99 for females, males, and children, respectively. The HQ of fluoride varies between 0.04-1.59, 0.04-1.34, and 0.05-1.82 for females, males, and children, respectively. The central part of the district was at high risk according to the spatial distribution maps of the total hazard index (THI). Noncarcinogenic risks due to THI are 47%, 37%, and 28% for children, females, and males, respectively. According to the human health risk assessment, children are more prone to getting affected by polluted water than adults. The groundwater pollution index (GPI) value ranges from 0.46 to 2.27 in the study area. Seventy-five percent of the samples fell under minor pollution and only one fell under high pollution. The spatial distribution of GPI in the research area shows that the central region is highly affected, which means that this water is unsuitable for drinking purposes.

Comprehensive evaluation of nitrogen contamination in water ecosystems of the Miyun reservoir watershed, northern China: distribution, source apportionment and risk assessment.

Miyun Reservoir plays a vital role as a source of drinking water for Beijing, however it grapples with nitrogen contamination issues that have been poorly understood in terms of their distribution, source, and associated health risks. This study addresses this knowledge gap by employing data on nitrate nitrogen (NO3--N), chloride (Cl-), dual isotopic compositions of NO3- (δ15N-NO3- and δ18O-NO3-) data in water ecosystems, systematically exploring the distribution, source and health risk of nitrogen contaminants in Miyun reservoir watersheds. The results showed that over the past 30 years, surface water runoff has exhibited a notable decrease and periodic fluctuations due to the combined influence of climate and anthropogenic activities, while the total nitrogen (TN) concentration in aquatic ecosystems presented an annual fluctuating upward trend. The TN concentration in the wet season was predominantly elevated because a large amount of nitrogen contaminants migrated into water ecosystems through heavy rainfall or river erosion. The concentration of NO3--N, the main contaminant of the water ecosystems, showed distinct variations across different watersheds, followed as rivers over the Miyun reservoir. Moreover, NO3--N levels gradually increased from upstream to downstream in different basins. NO3--N in surface water was mainly derived from the mixture of agricultural ammonia fertilizer and sewage and manure, with a minority of samples potentially undergoing denitrification. Comparatively, the main sources of NO3--N in groundwater were soil N and sewage and manure, while the denitrification process was inactive. The carcinogenic risks caused by NO3--N in groundwater were deemed either nonexistent or minimal, while the focus should predominantly be on potential non-carcinogenic risks, particularly for infants and children. Therefore, it is crucial to perform proactive measures aimed at safeguarding water ecosystems, guided by an understanding of the distribution, sources, and associated risks of nitrogen contamination.

Hydrochemical characterization and health risk assessment of different types of water bodies in Fenghuang Mountain Area, Northeast China.

Groundwater, as an essential resource, holds significant importance for human production and livelihoods. With the deterioration of the water environment, the issue of groundwater quality has become an urgent international concern. This study focused on the Fenghuang Mountain Area (FMA) and collected a total of 41 sets of samples including pore groundwater (PGW), fissure groundwater (FGW), karst groundwater (KGW), and river water (RW). Hydrochemical analysis methods were employed to identify the hydrochemical characteristics and controlling factors. The entropy-weighted water quality index (EWQI) and health risk assessment model were utilized to assess the groundwater quality and nitrate health risk, respectively. The results indicated that the dominant anion and cation in both groundwater and surface water in the FMA were HCO3- and Ca2+, respectively, with the main hydrochemical type being HCO3-Ca. Groundwater and surface water in the FMA were primarily controlled by rock weathering process, with ion concentrations influenced mainly by the dissolution of halite, sylvite, carbonates (calcite and dolomite), silicates, and gypsum, as well as by reverse anion exchange process. PGW was significantly affected by agricultural activities, with NO3- concentration closely related to human activities. The water quality of FGW was relatively good, with Class I and Class II water accounting for the highest proportion, reaching 84.62%. The high-value area of EWQI in PGW was influenced by human activities. The impact of nitrate health risk on children was significantly greater than on adults, with FGW having the lowest health risk and PGW having the highest health risk. The research results can provide important guarantees for the rational development and utilization of water resources in the FMA and the sustainable development of the economy in Northeast China.

Complete exhaustion of dissolved nutrients in a large lowland river.

Riverine phytoplankton takes up phosphate, dissolved silicate, and nitrate. We investigated which nutrients are depleted during a Lagrangian sampling in the free-flowing part of the River Elbe in 2023. As part of this study, we tested the hypotheses that nutrient depletion might be caused by (1) above-average phytoplankton biomass or by (2) decreased nutrient load of the river during previous years. Phytoplankton biomass increased up to 350 km in rivers and stopped increasing exactly when soluble reactive phosphorus had been completely consumed, and molar carbon to phosphorus ratios of seston indicated the beginning phosphorus limitation. The concentrations of dissolved silicate and nitrate dropped below the detection limit as well. In contrast to the results from eight previous longitudinal samplings taken in 2018-2022, nitrate exhaustion was detected for the first time in 2023 within the transect. This was caused neither by an above-average phytoplankton biomass nor by a declined overall nutrient load of the river in 2018-2023. Instead, denitrification appears to be the most plausible explanation for the downstream decrease of nitrate and the loss of total nitrogen which was supported by enrichment of nitrate stable isotopes and a decreasing ratio of nitrate 15N/18O.

A machine learning framework for spatio-temporal vulnerability mapping of groundwaters to nitrate in a data scarce region in Lenjanat Plain, Iran.

The temporal aspect of groundwater vulnerability to contaminants such as nitrate is often overlooked, assuming vulnerability has a static nature. This study bridges this gap by employing machine learning with Detecting Breakpoints and Estimating Segments in Trend (DBEST) algorithm to reveal the underlying relationship between nitrate, water table, vegetation cover, and precipitation time series, that are related to agricultural activities and groundwater demand in a semi-arid region. The contamination probability of Lenjanat Plain has been mapped by comparing random forest (RF), support vector machine (SVM), and K-nearest-neighbors (KNN) models, fed with 32 input variables (dem-derived factors, physiography, distance and density maps, time series data). Also, imbalanced learning and feature selection techniques were investigated as supplementary methods, adding up to four scenarios. Results showed that the RF model, integrated with forward sequential feature selection (SFS) and SMOTE-Tomek resampling method, outperformed the other models (F1-score: 0.94, MCC: 0.83). The SFS techniques outperformed other feature selection methods in enhancing the accuracy of the models with the cost of computational expenses, and the cost-sensitive function proved more efficient in tackling imbalanced data issues than the other investigated methods. The DBEST method identified significant breakpoints within each time series dataset, revealing a clear association between agricultural practices along the Zayandehrood River and substantial nitrate contamination within the Lenjanat region. Additionally, the groundwater vulnerability maps created using the candid RF model and an ensemble of the best RF, SVM, and KNN models predicted mid to high levels of vulnerability in the central parts and the downhills in the southwest.

High-frequency monitoring during rainstorm events reveals nitrogen sources and transport in a rural catchment.

Rural areas lacking essential sewage treatment facilities and collection systems often experience eutrophication due to elevated nutrient loads. Understanding nitrogen (N) sources and transport mechanisms in rural catchments is crucial for improving water quality and mitigating downstream export loads, particularly during storm events. To further elucidate the sources, pathways, and transport mechanisms of N from a rural catchment with intensive agricultural activities during storm events, we conducted an analysis of 21 events through continuous sampling over two rainy seasons in a small rural catchment from the lower reaches of the Yangtze River. The results revealed that ammonia-N (NH4+-N) and nitrate-N (NO3--N) exhibited distinct behaviors during rainstorm events, with NO3--N accounting for the primary nitrogen loss, its load being approximately forty times greater than that of NH4+-N. Through examinations of the concentration-discharge (c-Q) relationships, the findings revealed that, particularly in prolonged rainstorms, NH4+-N exhibited source limited pattern (b = -0.13, P < 0.01), while NO3--N displayed transport limited pattern (b = -0.21, P < 0.01). The figure-eight hysteresis pattern was prevalent for both NH4+-N and NO3--N (38.1% and 52.0%, respectively), arising from intricate interactions among diverse sources and pathways. For NO3--N, the hysteresis pattern shifted from clockwise under short-duration rainstorms to counter-clockwise under long-duration rainstorms, whereas hysteresis remained consistently clockwise for NH4+-N. The hysteresis analysis further suggests that the duration of rainstorms modifies hydrological connectivity, thereby influencing the transport processes of N. These insights provide valuable information for the development of targeted management strategies to reduce storm nutrient export in rural catchments.

Mowing aggravates the adverse effects of nitrogen addition on soil acid neutralizing capacity in a meadow steppe.

Soil acidification induced by reactive nitrogen (N) inputs is a major environmental issue in grasslands, as it lowers the acid neutralizing capacity (ANC). The specific impacts of different N compound forms on ANC remain unclear. Grassland management practices like mowing and grazing can remove a considerable amount of soil N and other nutrients, potentially mitigating soil acidification by removing N from the ecosystem or aggravating it by removing base cations. However, empirical evidence regarding the joint effects of adding different forms of N compounds and mowing on ANC changes in different-sized soil aggregates is still lacking. This study aimed to address this knowledge gap by examining the effects of three N compounds (urea, ammonium nitrate, and ammonium sulfate) combined with mowing (mown vs. unmown) on soil ANC in different soil aggregate sizes (>2000 µm, 250-2000 µm, and <250 µm) through a 6-year field experiment in Inner Mongolia grasslands. We found that the average decline in soil ANC caused by ammonium sulfate (AS) addition (-78.9%) was much greater than that by urea (-25.0%) and ammonium nitrate (AN) (-52.1%) as compared to control. This decline was attributed to increased proton (H+) release from nitrification and the leaching of exchangeable Ca2+ and Mg2+. Mowing aggravated the adverse effects of urea and AN on ANC, primarily due to the reduction in soil organic matter (SOM) contents and the removal of exchangeable Ca2+, K+, and Na + via plant biomass harvest. This pattern was consistent across all aggregate fractions. The lack of variation in soil ANC among different soil aggregate fractions is likely due to the contrasting trend in the distribution of exchangeable Ca2+ and Mg2+. Specifically, the concentration of exchangeable Ca2+ increased with increasing aggregate size, while the opposite was true for that of exchangeable Mg2+. These findings underscore the importance of considering the forms of N compounds when assessing the declines of ANC induced by N inputs, which also calls for an urgent need to reduce N emissions to ensure the sustainable development of the meadow ecosystems.

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Nitrate pollution in groundwater has become a global concern. One of the most important issues in controlling the nitrate pollution of groundwater is to identify the pollution source quickly and accurately. In this review, we firstly summarized the isotopic background values of potential sources of nitrate pollution in groundwater in 17 provinces (cities, autonomous regions) and 29 study areas in China, which could provide the fundamental database for subsequent research. Secondly, we reviewed the research progress of nitrate isotopes combined with multiple tracers for tracing nitrate in groundwater, and discussed their applicable conditions, advantages, and disadvantages. We found that halides and microorganisms combined with nitrate isotopes could accurately trace the pollution sources of domestic sewage, excrement and agricultural activities. The combination of Δ17O and nitrate isotopes could effectively distinguish the source of atmospheric deposition of nitrate in groundwater. The combination of groundwater age and nitrate isotopes could further determine the time scale of nitrate pollution. In addition, we summarized the application cases and compared the characteristics of mass balance mixing model, IsoSource model, Bayesian isotope mixing model, and EMMTE model for quantitative identification of nitrate pollution in groundwater. For the complexity and concealment of groundwater pollution sources, the coupling of nitrate isotopes with other chemical and biological tracing methods, as well as the application of nitrate isotope quantitative models, are effective tools for reliably identifying groundwater nitrate sources and transformation processes.

Characteristics of sub-micron aerosols in the Yellow Sea and its environmental implications.

The Yellow Sea, characterized by an influx of both natural marine and anthropogenic pollutants, coupled with favorable photochemical conditions, serve as key sites for potential interactions between atmospheric gases and aerosols. A recent air monitoring campaign in the Yellow Sea revealed aerosol contributions from four sources, with the highest mass concentrations and dominance of NO3- (38.1 ± 0.37 %) during winds from China. Indications of potential secondary aerosol formation were observed through the presence of hydrolysis and oxidation products of nitrate and volatile organic compounds. Correlations between time series distributions of biomass burning organic aerosols and particle number counts (Dp 100-500 nm, R2 = 0.94) further suggest potential size growth through adsorption and scavenging processes. The results from this study provide observational evidence of a shift in atmospheric compositions from sulfate to nitrate, leading to an increased atmospheric nitrogen deposition in the Yellow Sea.

Comparative evaluation between Taguchi method and response surface method for optimization of electrocoagulation process in the context of treatment of dairy industry wastewater.

The presence of a large amount of organic and inorganic pollutants in dairy effluent is a substantial environmental issue. This study investigated electrocoagulation (EC) as a potential treatment method for dairy wastewater under different operating conditions, such as applied voltage (5-25 V), electrolysis time (30-90 min), and inter-electrode distance (1-2 cm) by using aluminum electrodes. This study focuses on achieving the maximum removal of BOD, COD, and nitrate in dairy effluents with the aforementioned operating conditions. The process was optimized using the response surface methodology (RSM) and Taguchi method. RSM method optimized the electrocoagulation operating conditions such as the voltage at 23.75 V, time of 90 min, and inter-electrode distance at 1.07 cm. This optimization achieved the maximum removal percentage of BOD, COD, and nitrate at 79.06%, 84.35%, and 79.64%, respectively, in dairy effluent. Taguchi method optimized the electrocoagulation parameters such as the voltage at 25 V, time duration of 90 min, and inter-electrode distance of 1.00 cm, showcasing improved removal percentages of BOD, COD, and nitrate as 90.54%, 89.28%, and 82.74% respectively. The current study attempts to understand the optimization efficiencies between Taguchi method and response surface method for diary wastewater treatment.

[Spatial Patterns of Soil Bacterial Communities and N-cycling Functional Groups Along an Altitude Gradient in Datong River Basin].

The altitude distribution patterns of soil microorganisms and their driving mechanisms are crucial for understanding the consequences of climate change on terrestrial ecosystems. There is an obvious altitude difference in Datong River Basin in the Qilian Mountains. Two spatial scale transections were set up along the mountain slope (with altitude spanning 1 000 m) and the mainstream direction (with altitude spanning 300-500 m), respectively. The distribution characteristics of the soil bacterial community structure and diversity along the altitude gradients were examined using high-throughput sequencing technology. Based on the FAPROTAX database, the altitude distribution patterns of nitrogen cycling functional groups were analyzed to investigate the major environmental factors influencing the altitude distribution patterns of soil bacterial communities. The findings revealed that:① Soil physicochemical characteristics varied significantly with altitude. The content of total nitrogen (TN) and nitrate nitrogen (NO3-) were positively correlated with the altitude (P < 0.01), whereas the soil bulk density and pH were negatively connected (P < 0.001). ② The abundance of OTU increased significantly along the altitude (P < 0.01), and the richness and diversity indices increased along the altitude, although the trend was not statistically significant (P > 0.05). ③ The predominant bacterial communities were Acidobacteria, Proteobacteria, and Bacteroidetes, and as altitude climbed, their relative abundances varied between increasing, decreasing, and slightly decreasing, respectively. ④ The nitrogen cycling processes involved 13 functional groups, primarily nitrification, aerobic ammonia oxidation, aerobic nitrite oxidation, etc. As the altitude increased, the response law changed, with an increase in the abundance of nitrobacteria (P < 0.01), a slight increase in the abundance of aerobic ammonia-oxidizing bacteria and nitrite-oxidizing bacteria, and a hump-back tendency in bacteria abundance for nitrogen respiration. ⑤ Redundancy analysis revealed that the key determinants influencing soil bacterial populations at the phylum level were altitude, pH, and the content of NH4+. Mantel analysis showed that the dominant groups of soil bacterial nitrogen cycling were all statistically and significantly driven by altitude (P < 0.01). ⑥ The α-diversity of the bacterial community with increasing altitude were both increased along the mountain slope and the mainstream direction, but the soil properties, the abundance of N-cycling functional groups, and the main environmental factors differed. Therefore, it is of great significance to explore the altitude distribution pattern of soil microorganisms at different spatial scales.

Investigation of pollutants accumulation in the submerged zone for pyrite-based bioretention facilities under continuous rainfall events.

Submerged zone in bioretention facilities for stormwater treatment has been approved to be an effective structure amendment to improve denitrification capability. However, the role and influence of water quality changes in the submerged zone under natural continuous random rainfall patterns are still not clear, especially when the rainfall is less than the pore water in the submerged zone. In this study, continuous rainfall events with different rainfall volume (light rain-light rain-heavy rain) were designed in a lab-scale woodchip mulched pyrite bioretention facility to test the effects of rainfall pattern. The results exhibited that light rain events significantly affected the pollutant removal performance of bioretention for the next rainfall. Different effects were observed during the long-term operation. In the 5th month, light rain reduced the ammonia removal efficiency of subsequent rainstorm events by 8.70%, while in the 12th month, when nitrate leakage occurred, light rain led to a 40.24% reduction in the next heavy rain event's nitrate removal efficiency. Additionally, light rain would also affect the concentration of by-products in the next rainfall. Following a light rain, the concentration of sulfate in the subsequent light rainfall can increase by 24.4 mg/L, and by 11.92 mg/L in a heavy rain. The water quality in the submerged zone and media characteristics analysis suggested that nitrogen conversion capacity of the substrate and microbes, such as Nitrospira (2.86%) and Thiobacillus (35.71%), as well as the in-situ accumulation of pollutants under light rain played important roles. This study clarifies the relationship between successive rainfall events and provides a more comprehensive understanding of bioretention facilities. This is beneficial for field study of bioretention facilities in the face of complex rainfall events.

Evaluation of 12-Week Standardized Beetroot Extract Supplementation in Older Participants: A Preliminary Study of Human Health Safety.

In recent years, there has been a notable surge in the popularity of beetroot-based dietary supplements, driven by their rich nitrate composition. Several types of beetroot-based dietary supplements can be found in markets worldwide; however, ensuring the safety of dietary supplements is a crucial consideration, as there is limited evidence on their safety, especially for older populations. Therefore, the purpose of the current study was to evaluate the safety and tolerability of a nitrate-rich beetroot extract in older participants taking supplements over 12 weeks. The participants were randomly assigned to receive 20 g daily of beetroot extract or a matching placebo. The safety and tolerability of the supplementation were evaluated as the occurrence of adverse events and anthropometric, biochemical, and hemodynamic parameters were measured. No serious adverse events were reported in any group. Anthropometric, biochemical, and hemodynamic parameter changes between the baseline and the end of the study were not statistically significant in either group. However, interestingly, the group receiving beetroot extract supplementation exhibited a notable increase in plasma nitrate levels (p = 0.076, f = 0.50) and showed a decrease in insulin levels (p = 0.026, f = 0.59). In conclusion, we found that 20 g of beetroot extract supplementation for 12 weeks was safe and well tolerated in older participants.

Quantifying the Potential for Nitrate-Dependent Iron Oxidation on Early Mars: Implications for the Interpretation of Gale Crater Organics.

Geological evidence and atmospheric and climate models suggest habitable conditions occurred on early Mars, including in a lake in Gale crater. Instruments aboard the Curiosity rover measured organic compounds of unknown provenance in sedimentary mudstones at Gale crater. Additionally, Curiosity measured nitrates in Gale crater sediments, which suggests that nitrate-dependent Fe2+ oxidation (NDFO) may have been a viable metabolism for putative martian life. Here, we perform the first quantitative assessment of an NDFO community that could have existed in an ancient Gale crater lake and quantify the long-term preservation of biological necromass in lakebed mudstones. We find that an NDFO community would have the capacity to produce cell concentrations of up to 106 cells mL-1, which is comparable to microbes in Earth's oceans. However, only a concentration of <104 cells mL-1, due to organisms that inefficiently consume less than 10% of precipitating nitrate, would be consistent with the abundance of organics found at Gale. We also find that meteoritic sources of organics would likely be insufficient as a sole source for the Gale crater organics, which would require a separate source, such as abiotic hydrothermal or atmospheric production or possibly biological production from a slowly turning over chemotrophic community.

Using stacked pot connection of wetland microbial fuel cells to charge the battery: Potential and effecting factor.

In the practical application of wetland microbial fuel cells (WMFCs), suitable designs and stacked connection systems have consistently been employed to increase and harvest power generation. Our study compares different WMFCs designs and demonstrates that the cylinder pot design outperforms the small hanging pot design in terms of electrical energy production. Moreover, power generation from the cylinder pot can be further optimized through separator modification and stacked connections. The stacked WMFCs design exhibited no voltage reversal, with an average power output ranging from 0.03 ± 0.01 mW (single pot) to 0.11 ± 0.05 mW (stacked connection of 5 pots) over a 60-day operational period. Additionally, our study identifies distinct patterns in both anodic and cathodic physiochemical factors including electrical conductivity (EC), pH, and nitrate (NO3-), highlighting the significant influence of plant involvement on altering concentrations and levels in different electrode zones. The WMFCs bioelectricity production system, employing 15 pots stacked connections achieves an impressive maximum power density of 9.02 mW/m2. The system's practical application is evidenced by its ability to successfully power a DC-DC circuit and charge a 1.2 V AAA battery over a period of 30 h, achieving an average charging rate of 0.0.2 V per hour.

Development of the sustainable green nanosensor using corn silk extract for nitrate detection in leafy vegetables.

Nitrate is prevalent in environment and present in foods of plant origin as part of nitrogen cycle. It is now one of the most pervasive and persistent contaminants in animal food chain. Present work is focussed on development of a novel green nanosensor using corn silk extract for nitrate detection in leafy vegetables (Spinacia oleracea, Amaranthus viridis and Amaranthus cruentus). The green reduced graphene oxide (rGO) and a nanocomposite (G-Fe3O4@rGO) was synthesized for the first-time using corn silk extract and used for fabrication of the nanosensor. Various characterization techniques were used to expose the optical, crystallographic and surface morphology details of the nanosubstrates. Electrochemical studies of the fabricated nanosensor were conducted using the electrochemical impedance spectroscopy (EIS) technique. The performance of NiR/G-Fe3O4@rGO/ITO green nanosensor was the best, in terms of the electrochemical performance parameters among different fabricated nanosensors in the study. The developed green nanosensor demonstrated high sensitivity of 122.1 Ohm/log(mg/L)/cm2 and lower limit of detection 0.076 mg/L for detection of nitrate in leafy vegetables. The green nanosensor exhibited higher recovery rates (>86%) and high precision in nitrate detection in leafy vegetables (RSD <5.2%). Validation studies were conducted with HPLC technique also. The results of green nanosensor were found in good agreement with HPLC studies (p < 0.05) highlighting the market acceptability with usefulness and effectiveness of the nanosensor for food quality and safety evaluation.

Effect of agriculture on surface water quantity and quality in Gilgel Gibe watershed, southwestern Ethiopia.

Monitoring water quality and quantity is crucial to be sure that water resources are sustainably used. However, there is no monitoring system of water quantity and quality in southwestern Ethiopia, despite expansion of agricultural activities demanding water resources. The objective of this study was to investigate the effect of agriculture on water quantity and quality with special emphasis on irrigation in southwestern Ethiopia. Data of water quantity was collected from four rivers and four irrigation canals during dry season of 2023. Physico-chemical water quality data was collected from 35 sites. Water quantity was calculated by estimating the water discharge of the rivers and irrigation canals. Weighted arithmetic water quality index was calculated to assess the status of the studied rivers. Principal component analysis was used to identify the relation of the sites with water quality parameters. This study revealed that the average amount of abstracted water for irrigation from the four studied rivers was 22,399 m3/day during the studied period, and the average percentage of abstracted water was 17%. Sites downstream of the irrigation site were characterized by poor water quality compared with the upstream sites. Sites surrounded by agricultural land use were correlated with chemical oxygen demand, electric conductivity, nitrate, orthophosphate, water temperature, and pH, whereas all sites surrounded by forest were positively correlated with dissolved oxygen. This study indicates that agricultural activities have a negative impact on surface water quality and quantity if not managed properly. Hence, we recommend sustainable use of water resources for the planned irrigation expansion.

Quali-quantitative water behaviour in an intensive swine production catchment in the Atlantic Forest biome, Southern Brazil.

Agriculture is an essential economic activity in Brazil. However, it is also the main source of water quality degradation. Monitoring catchments with agricultural land use is a way to generate information on a scale to identify causes and sources of water quality degradation. This work used monitoring data derived from hydrology and the quality of surface and underground water in an intensive agricultural catchment in the Atlantic Forest biome. The Fortaleza River catchment is located in the western part of Santa Catarina state in southern Brazil and has 62 km2 of drainage area. Hydrological and water quality monitoring was conducted for 7 years at two fluviometric stations, three lysimeters, one meteorological station, and one piezometer. Data on precipitation, temperature, water flow, surface runoff, drainage, and water quality were used. Statistical analyses were also developed. Precipitation between 2013 and 2019 presented a homogeneous distribution in monthly and annual data, with January and July the months with the highest and lowest values, respectively. Statistical difference in the average and Q95 flows was found in upstream and downstream fluviometric sections. In terms of quality, statistical differences were identified for ammonium, nitrate, and potassium concentrations, which had higher concentrations in lysimeter runoff, indicating direct influence of agricultural activity on water quality. Principal component analysis (PCA) indicated that (i) surface water presented a positive relationship in Component 1 for the magnesium-calcium, sulphate-chloride, and acetate-bromide groups and a negative relationship for phosphate-nitrate; (ii) in lysimeters, the positive relationship occurred for Component 2 for the phosphate-chloride and sulphate-nitrate groups and was negative for ammonium-lithium and calcium-potassium-magnesium; and (iii) in piezometer, positive relationships were found for chloride-sodium and phosphate-nitrite pairs, while negative relationships were found for calcium-magnesium.

Associations of incident female breast cancer with long-term exposure to PM2.5 and its constituents: Findings from a prospective cohort study in Beijing, China.

This study aimed to investigate the association between long-term exposure to fine particulate matter (PM2.5) and its constituents (black carbon (BC), ammonium (NH4+), nitrate (NO3-), organic matter (OM), inorganic sulfate (SO42-)) and incident female breast cancer in Beijing, China. Data from a prospective cohort comprising 85,504 women enrolled in the National Urban Cancer Screening Program in Beijing (2013-2019) and the Tracking Air Pollution in China dataset are used. Monthly exposures were aggregated to calculate 5-year average concentrations to indicate long-term exposure. Cox models and mixture exposure models (weighted quantile sum, quantile-based g-computation, and explanatory machine learning model) were employed to analyze the associations. Findings indicated increased levels of PM2.5 and its constituents were associated with higher breast cancer risk, with hazard ratios per 1-µg/m3 increase of 1.02 (95% confidence interval (CI): 1.01, 1.03), 1.39 (95% CI: 1.16, 1.65), 1.28 (95% CI: 1.12, 1.46), 1.15 (95% CI: 1.05, 1.24), 1.05 (95% CI: 1.02, 1.08), and 1.15 (95% CI: 1.07, 1.23) for PM2.5, BC, NH4+, NO3-, OM, and SO42-, respectively. Exposure-response curves demonstrated a monotonic risk increase without an evident threshold. Mixture exposure models highlighted BC and SO42- as key factors, underscoring the importance of reducing emissions of these pollutants.

Spectral and molecular insights into the characteristics of dissolved organic matter in nitrate-contaminated groundwater.

The characteristics of dissolved organic matter (DOM) serve as indicators of nitrate pollution in groundwater. However, the specific DOM components associated with nitrate in groundwater systems remain unclear. In this study, dual isotopes of nitrate, three-dimensional Excitation emission matrices (EEMs) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) were utilized to uncover the sources of nitrate and their associations with DOM characteristics. The predominant nitrate in the targeted aquifer was derived from soil organic nitrogen (mean 46.0%) and manure &sewage (mean 34.3%). The DOM in nitrate-contaminated groundwater (nitrate-nitrogen >20 mg/L) exhibited evident exogenous characteristics, with a bioavailable content 2.58 times greater than that of uncontaminated groundwater. Regarding the molecular characteristics, DOM molecules characterized by CHO + 3N, featuring lower molecular weights and H/C ratios, indicated potential for mineralization, while CHONS formulas indicated the exogenous features, providing the potential for accurate traceability. These findings provided insights at the molecular level into the characterization of DOM in nitrate-contaminated groundwater and offer scientific guidance for decision-making regarding the remediation of groundwater nitrate pollution.