Average Nitrate Concentration Research Articles

Enhanced Pollutant Removal and Antifouling in an Aerobic Ceramic Membrane Bioreactor with Bentonite for Pharmaceutical Wastewater Treatment.

This study examined the impact of adding bentonite clay (concentration of 1.5 to 10 g/L) to a pilot-scale aerobic ceramic membrane bioreactor (AeCMBR) for treating pharmaceutical wastewater (PhWW). The hydraulic retention time (HRT) was maintained at 24 h; the dissolved oxygen was between 2 mg/L (on) and 4 mg/L (off) throughout operation. Organic and nitrogen pollution removal rates and heavy metal (Cu, Ni, Pb, Zn) reduction rates were assessed. The chemical oxygen demand (COD) removal efficiency exceeded 82%. Adsorption improved ammonia (NH4+) removal to 78%; the addition of 5 g of bentonite resulted in a 38% improvement compared with the process without bentonite. The average nitrate concentration decreased from 169.69 mg/L to 43.72 mg/L. The average removal efficiencies for Cu, Ni, Pb and Zn were 86%, 68.52%, 46.90% and 56.76%, respectively. Bentonite at 5 g/L significantly reduced membrane fouling. The cost-benefit analysis enabled us to predict that the process will meet the multiple objectives of durability, treatment performance and economic viability. The combination of an AeCMBR and bentonite adsorption has proven to be a valuable solution for treating highly polluted wastewater.

Geographic Information Systems for Water Quality Modeling in the Zhytomyr District Communities

Abstract To ensure safe and quality drinking water for residents of rural settlements who use their own wells, boreholes, and natural sources for domestic water supply, a comprehensive approach to evaluating the quality of underground drinking water using geographic information system (GIS) technologies is necessary. The purpose of the study was to assess the quality of drinking water sources of noncentralized water supply in rural settlements of the united territorial communities (UTCs) of Zhytomyr district and to create geoinformation models based on the research results. The following research methods were used during the research: analytical, field, laboratory, statistical, calculation, and cartographic. The research was conducted in 129 settlements of 12 UTCs of Zhytomyr district, where drinking water samples were collected from noncentralized water supply sources for further analysis in the Measurement Laboratory of Polissia National University, and the creation of geoinformation models using the ArcGIS Pro software package. It has been proven that the average pH level in none of the studied settlements exceeded the norm. The average nitrate concentration in the drinking water from noncentralized water sources exceeded the norm by 1.4–3.5 times, specifically in the water of the Pulyny, Cherniakhiv, Vilshanka, Volytsia, and Oliivka communities, exceeding the maximum acceptable concentration (MAC) limit by more than two times. Only in rural settlements in the Liubar community was the average iron content found to be above the norm by more than 1.9 times. Overall, it was established that the calculated value of the overall water quality class in the Zhytomyr district was 2.03, which is determined as “good,” clean water of acceptable quality. The best water quality was found in the Vilshanka, Cherniakhiv, and Stanyshivka communities, with a quality class range of 1.85–1.93, while the worst water quality was recorded in the Oliivka, Teterivka, and Liubar communities, with a quality class range of 2.13–2.31. It was determined that the highest contribution to the overall water quality was made by nitrate and iron content. The obtained research results and models based on them can be used by local governments of the studied communities to inform the population about the quality of drinking water and to develop a plan for improving the state of drinking water supply with the aim of increasing the level of environmental safety of drinking water.

Pollution, spatial distribution, and health risks assessment of nutrient concentration in surface water resources of Maroon-Jarahi Basin in southwestern Iran.

Nowadays, the introduction of nutrients caused by human activities is considered an environmental issue and a significant problem in river basins and coastal ecosystems. In this study, the concentration of nutrients ( and ) in the surface water sources of the Maroon-Jarahi watershed in the southwest of Iran was determined, and the pollution status and health risk assessment were done. The average concentration of nitrate and phosphate in Ludab, Maroon, Zard, Allah, Jarahi rivers, and Shadegan wetland were obtained at 2.25-0.59, 4.59-1.84, 4.07-2.02, 5.40-2.81, 11.51-4.67, 21.63 and 6.20 (mg/l), respectively. A comparison of the results with the World Health Organization (WHO) limit showed that nitrate was lower than in all stations, but phosphate was higher than the limit in some stations of the Maroon, Allah, Jarahi rivers, and Shadegan wetland. Calculation of linear regression analysis showed significant positive relationships between nitrate and phosphate in all surface water sources (except Ludab) and based on the N/P ratio, nitrogen was estimated as the limiting factor in phytoplankton growth (N/P < 16). The evaluation of the status of the Nutrient pollution index (NPI) was observed as: Shadegan > Jarahi > Allah > Maroon > Zard > Ludab that the Jarahi River and Shadegan wetland were in the medium pollution class (1 < NPI ≤ 3) and other waterbodies were in the non-polluted to low pollution state (NPI < 1). Calculation of the chronic daily intake (CDI) showed that water body nutrients cause more non-carcinogenic health risks through the oral route than dermal exposure, and according to HI, children's health is more at risk than adults. Findings showed that surface water resources especially downstream of the Maroon-Jarahi watershed are at eutrophication risk, and to control the nearby human activities and as a result increase the nutrients in these water resources, measures should be taken.

Spatial Distribution of Nutrient in The Waters of Haruku Strait, Central Maluku Regency, Maluku Province

Strait waters are influenced by tides, water masses and surrounding land. This study aims to analyze the spatial distribution of nutrients in the waters of the Haruku Strait, Central Maluku Regency, Maluku Province. The research method used is the survey method by taking water samples. Water samples were taken from 17 observation stations spread across the Haruku Strait at depths of 1 meter, 25 meters and 50 meters using the Niskin Bottle Water Sampler. Nitrate concentration analysis using the OPTIZEN Alfa equipment (Spectrophotometer UV-Vis) and the Brucine Sulfate method (SNI: 06-2480-1991) and phosphate concentration analysis using the Ammonium Molybdate method (APHA 10th ed. 5400-PD, 1998). The time of observation took place on July 23, 2022. The results showed that the average concentration of nitrate at a depth of 1 m was 1.146 ± 0.647 mg/L, a depth of 25 m was 1.148 ± 0.709 mg/L and a depth of 50 m was 1.136 ± 0.701 mg/L while the average concentration of phosphate at a depth of 1m was 0.051 ± 0.028 mg/L, a depth of 25 m was 0.053 ± 0.029 mg/L and at a depth of 50 m was 0.049 ± 0.020 mg/L. The waters of the Banda Sea, the Seram Strait and contributions from the rivers on the coast of Ambon Island play a role in the distribution of nutrients in the waters of the Haruku Strait.

Long-term exposure to ambient PM2.5 and its components on menarche timing among Chinese adolescents: evidence from a representative nationwide cohort

BackgroundAmbient air pollutants have been suggested to affect pubertal development. Nevertheless, current studies indicate inconsistent effects of these pollutants, causing precocious or delayed puberty onset. This study aimed to explore the associations between long-term exposure to particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) along with its components and menarche timing among Chinese girls.MethodSelf-reported age at menarche was collected among 855 girls from China Health and Nutrition Survey 2004 to 2015. The pre-menarche annual average concentrations of PM2.5 and its components were calculated on the basis of a long-term (2000–2014) high-resolution PM2.5 components dataset. Generalized linear models (GLM) and logistic regression models were used to analyze the associations of exposure to a single pollutant (PM2.5, sulfate, nitrate, ammonium, black carbon and organic matter) with age at menarche and early menarche (< 12 years), respectively. Weighted quantile sum methods were applied to examine the impacts of joint exposure on menarche timing.ResultsIn the adjusted GLM, per 1 µg/m3 increase of annual average concentrations of nitrate and ammonium decreased age at menarche by 0.098 years and 0.127 years, respectively (all P < 0.05). Every 1 µg/m3 increase of annual average concentrations of PM2.5 (OR: 1.04, 95% CI: 1.00-1.08), sulfate (OR: 1.23, 95% CI: 1.01–1.50), nitrate (OR: 1.23, 95% CI: 1.06–1.43) and ammonium (OR: 1.32, 95% CI: 1.06–1.66) were significantly positively associated with early menarche. Higher level of joint exposure to PM2.5 and its components was associated with 11% higher odds of early menarche (P = 0.04). Additionally, the estimated weight of sulfate was the largest among the mixed pollutants.ConclusionsLong-term exposure to PM2.5 and its components could increase the risk of early menarche among Chinese girls. Moreover, sulfate might be the most critical components responsible for this relationship. Our study provides foundation for targeted prevention of PM2.5 components.

Influence of prescribed fire intensity and grass mulch on soil erosion and runoff under rainfed maize in Nigeria

The experiment was conducted at the Teaching and Research Farm, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria to investigate the influence of prescribed fire intensity on soil erosion and runoff, a situation that occur regularly in the study area. The experimental site is within the rainforest ecosystem of the Southwest Nigeria, and usually experiences a significant amount of rainfall every year. This encourages rainfed farming around the study area with most farmers using prescribed fire for land preparation before planting. It is presumed that bush burning causes erosion and degradation of other soil properties. The study therefore investigated the influence of prescribed fire of two intensities and mulching on runoff and soil loss, runoff coefficient, phosphate and nitrate contents of the runoff water. The treatments consisted of fire intensities of 200 °C (with effect correspondingly felt at a maximum of 2 cm soil depth) and 500 °C (with effect correspondingly felt at a maximum of 5 cm soil depth), grass mulch, and control (bare soil without vegetation or plant residue). Each treatment was imposed on a plot of 1 m2 arranged in a randomized complete block design with triplicates, for three cropping seasons, and prescribed burning at the start of each cropping season. The first season was from May to August 2019, second season was from September to December 2019 while the third season was from September to December 2020. Runoff volume, soil loss, phosphate and nitrate contents in runoff were measured using bounded erosion plots of polyvinyl chloride (PVC) materials with a harvesting container (25 L) installed at about 1 m deep. The 200 °C prescribed fire plots had higher soil loss than that of 500 °C. The runoff in the 200 °C prescribed fire plot were 13.36 mm, 10.80 mm and 12.78 mm during the first, second and third seasons respectively, while those of the 500 °C prescribed fire were 12.88 mm, 7.63 mm and 11.96 mm in the same order. Soil loss from the 200 °C prescribed fire plot was an average of 2.46, 3.40, 1.77 Mg ha−1 in the first, second and third seasons respectively, while the 500 °C prescribed fire plot lost an average of 1.70, 1.23 and 2.17 Mg ha−1 in the same order. The Average concentration of nitrates in the runoff under 200 °C prescribed fire were an average of 0.14, 0.21, and 0.38 mg L−1 while for 500 °C, they were 0.18, 0.19, 0.81 mg L−1 in the first, second and third seasons respectively. Nitrate and phosphate contents of the runoff were not significantly influenced by prescribed fire. The fire intensities did not have a significant impact on the total runoff and soil loss under maize in the prescribed fire plots. The slash and pack plots without burning experienced the highest runoff and soil loss. However, grass mulch plot reduced total runoff and soil loss. Therefore, grass mulching of soil is encouraged to mitigate soil erosion in maize fields.

Mariculture may intensify eutrophication but lower N/P ratios: a case study based on nutrients and dual nitrate isotope measurements in Sansha Bay, southeastern China

The mariculture industry has grown rapidly worldwide over the past few decades. The industry helps meet growing food demands and may provide an effective means of carbon sequestration; however, it may harm the marine ecological environment, and the extent of its impact depends on the type of mariculture. Here we focus on the impact of mariculture on the nutrient status and eutrophication in Sansha Bay, which is a typical aquaculture harbor in southeastern China that employs a combination of shellfish and seaweed farming. Nutrient concentrations and dual nitrate isotopes were measured in Sansha Bay during the winter of 2021. The average concentrations of nitrate and phosphate were 31.3 ± 10.5 and 2.26 ± 0.84 µM, respectively, indicating that the water was in a eutrophic state. However, the N/P ratios were relatively low (14.3 ± 2.2). Nitrate isotope measurements were 8.8‰–11.9‰ for δ15N-NO3− and 2.2‰–6.0‰ for δ18O-NO3−. Source analysis based on the nitrate isotope measurements indicates that nitrate in Sansha Bay is derived mainly from the excretion of organisms and sewage discharge from mariculture. The isotopic fractionation model of nitrate assimilation by organisms indicates that surface waters in Sansha Bay experience strong biological uptake of nitrate, which is likely related to seaweed farming in winter. The low N/P ratios may be attributed to excessive nitrogen uptake (relative to phosphorus) during shellfish and seaweed farming, as well as nitrogen removal through sediment denitrification, which is fueled by the sinking of particulate organic matter from mariculture. Overall, our study shows that mariculture activities dominated by shellfish and seaweed cultivation in Sansha Bay may exacerbate eutrophication but reduce N/P ratios in the water column in aquaculture areas.

Ingested nitrate and nitrite and end-stage renal disease in licensed pesticide applicators and spouses in the Agricultural Health Study

BackgroundNitrate and nitrite ingestion has been linked to kidney cancer, possibly via the endogenous formation of carcinogenic N-nitroso compounds. These exposures might also contribute to end-stage renal disease (ESRD).ObjectivesWe investigated associations of drinking water nitrate and dietary nitrate and nitrite intakes (total and by food type) with incident ESRD in the Agricultural Health Study. We also explored modifying effects of vitamin C and heme iron intake, which may affect endogenous nitrosation.MethodsWe performed complete case analyses among private pesticide applicators and their spouses. We obtained water nitrate estimates for participants whose primary drinking water source at enrollment (1993−1997) was public water supplies (PWS) or private wells (N = 59,632). Average nitrate concentrations were computed from historical data for PWS users and predicted from random forest models for private well users. Analysis of dietary nitrate and nitrite was restricted to the 30,177 participants who completed the NCI Dietary History Questionnaire during follow-up (1999−2003). Incident ESRD through 2018 was ascertained through linkage with the U.S. Renal Data System. We estimated adjusted hazard ratios (HRs) and 95%CI for associations of tertiles (T) of exposure with ESRD overall and explored effects in strata of vitamin C and heme iron intake.ResultsWe identified 469 incident ESRD cases (206 for dietary analysis). Water nitrate and total dietary nitrate/nitrite were not associated with ESRD, but increased ESRD was associated with nitrate and nitrite from processed meats. We found apparent associations between nitrite and ESRD only among participants with vitamin C <median (T3 vs. T1 HR: 2.26, 95%CI: 1.05, 4.86) and with heme iron ≥median (T3 vs. T1 HR: 1.73, 95%CI: 0.89, 3.39).SignificanceESRD incidence was associated with dietary nitrate/nitrite from processed meat among all study participants and with total dietary nitrite among participants with lower vitamin C or higher heme iron intake.Impact statementThere are few well-established environmental risk factors for end-stage renal disease (ESRD), a worldwide public health challenge. Ingestion of nitrate and nitrite, which may lead to endogenous formation of carcinogenic N-nitroso compounds, has been linked to some cancers and chronic diseases. We investigated these exposures in relation to ESRD in an agricultural cohort. ESRD incidence was associated with dietary nitrate/nitrite from processed meat and with total dietary nitrite among subgroups with lower vitamin C or higher heme iron intake. This study provides preliminary evidence that points to dietary nitrite and possibly dietary nitrate intake as a potential contributor to ESRD.

Health risk assessment of drinking groundwater in rural areas of Ru village and surrounding areas in Wutai County, China.

Nitrate pollution in groundwater is a global environmental problem that poses risks to human health. We investigate the health risks of nitrate in rural drinking groundwater in Rucun Township and surrounding areas of Wutai County, and provide a basis for healthy drinking water. By using statistical analysis software (SPSS19) and hydrogeochemical analysis software (AqQA), a qualitative and quantitative evaluation of nitrate health risks was conducted among populations of different ages and genders through water sample collection, chemical analysis, and construction of a human health risk model (HHRA). Through research, it was found that the average concentration of nitrate in the study area is 43.99 mg/L. Groundwater is severely polluted by NO3-, and nitrate pollution areas are mainly concentrated in the main human activity areas, especially in the main agricultural production areas. The Quaternary loess layer, as a permeable layer, cannot prevent groundwater from being polluted by NO3-. Through evaluation, it is believed that there is a health risk of nitrate pollution in rural drinking groundwater in Rucun Township and surrounding areas. Health risk level: infants>children>adult females>adult males. The discovery and evaluation results can provide a basis for the prevention and control of nitrate pollution in groundwater.

Lower nitrate leaching from dairy cattle slurry compared to synthetic fertilizer calcium ammonium nitrate applied to grassland

Nitrate leaching from agriculture can be reduced by the choice of fertilizer and a proper timing of its application. For permanent grassland grown under temperate conditions, nitrate leaching was hypothesized to be lower from dairy cattle slurry (CS) compared to synthetic fertilizer calcium ammonium nitrate (CAN), based on differences in chemical composition, consequential effects on nitrogen (N) conversion processes in soil, and resulting differences in synchronization of (nitrate) N availability and plant N uptake. We tested the hypothesis in a two-year field experiment on cut grassland on a leaching-sensitive sandy soil, fertilized each year with 320 kg ha−1 of plant-available N from either 100% top-dressed CAN or a combination of 40% from CAN and 60% from sod-injected CS, and measured effects on grass herbage yield, herbage N uptake, and nitrate concentration in pore water at 1.0 m depth. Our results show a comparable level of herbage N uptake for both treatments, allowing for a proper comparison of nitrate leaching at a similar level of plant-available N. Average nitrate concentration in pore water in the main leaching period (over winter) was after the first (dry) growing season 44% lower for CS + CAN (41 mg l−1) compared to CAN only (73 mg l−1), and after the second (wet) growing season 35% lower for CS + CAN (32 mg l−1) compared to CAN only (49 mg l−1). Nitrogen application increased nitrate concentration at 1.0 m depth not only in winter but also in the growing season. We conclude that for permanent grasslands in temperate regions, nitrate leaching from timely applied CS may be considerably lower than from CAN, which is different from previous assumptions.

Nitrate concentrations and health risks in cow milk from Iran: Insights from deterministic, probabilistic, and AI modeling

Excessive nitrate consumption has been linked to potential health risks in humans. Thus, understanding nitrate levels in staple foods such as cow milk can provide insights into their health implications. This study meticulously examined nitrate concentrations in 70 cow milk samples from traditional and industrialized cattle farming systems in Fars province, Iran. A combination of deterministic modeling, a probabilistic approach, and six artificial intelligence algorithms was employed to determine health risk assessments. The data disclosed average nitrate concentrations of 32.63 mg/L in traditional farming and 34.95 mg/L in industrialized systems, presenting no statistically significant difference (p > 0.05). The Hazard Quotient (HQ) was deployed to gauge potential health threats, underscoring heightened vulnerability in children, who exhibited HQ values ranging from 0.05 to 0.58 (mean = 0.19) in contrast to adults, whose values spanned 0.01 to 0.16 (mean = 0.05). Monte Carlo simulations enriched the risk assessment, demarcating the 5th and 95th percentile nitrate concentrations for children at 0.07 and 0.39, respectively. In children, pivotal interactions that influenced HQ encompassed those between nitrate concentration and consumption rate, as well as nitrate concentration and body weight. The interplay between nitrate concentration and consumption rate was most consequential for the adult cohort. Among the algorithms assessed for HQ prediction, Gaussian Naive Bayes (GNB) was optimal for children and eXtreme Gradient Boosting (XGB) for adults, with nitrate concentration being a key determinant. The results underscore the imperative for rigorous oversight of milk nitrate concentrations, highlighting the enhanced susceptibility of children and emphasizing the need for preventive strategies and enlightened consumption.

Effects of Substituting Activated Carbon with Titanium-Dioxide-Coated Cenospheres in Conventional Aquarium Filters

We investigated the effectiveness of TiO2 cenospheres in reducing the concentrations of three common harmful compounds, ammonium, nitrate, and nitrite, in fish aquariums. These cenospheres can contribute to more sustainable and eco-friendly aquarium filtration systems while also improving the health of fish. We designed a 30-day experiment with three treatment groups based on the filter type: (1) a control group with a conventional aquarium filter, (2) a group with a TiO2 cenosphere filter, and (3) a group with a dark TiO2 cenosphere filter. The water quality was the same baseline in all groups, and each tank was monitored daily for changes in temperature, pH, ammonia, nitrate, and nitrite concentrations. We found that the TiO2 cenosphere filter was effective in reducing the concentrations of all three pollutants. By the end of the experimental period, the average concentration of nitrite in the control group was 10.7 µM, while the average concentration in the TiO2 cenosphere filter group dropped 55% to 4.7 µM from the baseline. The average concentration of nitrate was reduced by 17% and ammonia by 28% in the cenosphere-treated group. Hence, the cenospheres were effective in reducing the concentrations of all three pollutants, with the greatest reduction seen for nitrite. These findings support further investigation for incorporating TiO2 cenospheres into aquarium filtration to help reduce the environmental burden of the aquarium industry.

Accounting for the annual variability when assessing non-point source pollution potential in Mediterranean regulated watersheds

The characterization of non-point source pollution at the watershed scale difficult owing to its distributed nature combined with the lack of suitable measurements for validation. This study proposes the classification of land within a Mediterranean watershed according to its potential source of non-point pollution, considering interannual precipitation variability and dam regulation effects. For this purpose, the potential non-point pollution index (PNPI) developed by the Italian Environmental Protection Agency was modified to include annual local precipitation behavior, named local annual PNPI (APNPI). PNPI and APNPI were computed for the Guadalquivir River (Spain), which has a drainage surface of 57,500 km2 and is highly regulated by >60 reservoirs. The results reflect the vulnerability along the Guadalquivir River in terms of the spatially variable non-point pollutant nature of its contributing watersheds. The annual average nitrate concentration values on the southern side exceeded the average value on the northern side by almost five times and showed a statistically significant power fit with the PNPI, with an R2 of 0.65. Long-term available nitrate data (1981/82–2006/07) on a monthly scale at the outlets of some watersheds allowed us to rank priority pollutant source areas within the watershed. The power fits between the annual average nitrate loads and the APNPI (R2 = 0.51–0.99) were statistically significant, which validated the utility of adding the variability of precipitation at an annual scale as a dynamic factor in the index. The APNPI can constitute a simple dynamic classification index for assessing the relative risk of non-point source pollution across a large area, especially in data-scarce situations.

Health risk assessment of nitrate pollution of drinking groundwater in rural areas of Suihua, China.

In order to investigate the health risks of NO3- in rural drinking groundwater in Suihua, China and provide a basis for healthy drinking water, 40 sets of groundwater samples were collected in the Suihua area, and the average concentration of nitrate in the study area was 71.66 mg/L, statistical analysis software (SPSS19), Hydrogeochemical Analysis Software (AqQA) and groundwater pollution analysis software were used. Through water sample collection, chemical analysis and construction of human health risk model (HHRA), a qualitative and quantitative assessment of NO3- health risk was carried out for people of different ages and sexes, and it was concluded that there was NO3- pollution health risk in rural drinking groundwater in Suihua. Health risk level: infants > children > adult females > adult males. The evaluation provides a scientific basis for the prevention and control of NO3- pollution in groundwater and new ideas for preventing human health risks.

THE RELATIONSHIP BETWEEN NITRATE, PHOSPHATE AND ORGANIC MATERIAL CONCENTRATION TO PHYTOPLANKTON ABUNDANCE IN RUPAT ISLAND WATERS

Over time, Rupat Island has experienced very rapid development, marked by various activities such as plantations, agriculture, farming, and ecotourism activities which are growing rapidly. This study aims to determine the relationship between concentrations of nitrate, phosphate, and organic matter on the abundance of phytoplankton in Rupat Island waters. The results showed that the average nitrate concentration was relatively high, ranging from 0.0993-0.1618 mg/L and the average phosphate concentration was around 0.0951-0.1571 mg/L. Furthermore, the concentration of organic matter in water ranged from 27.555-35.234 mg/L. The lowest abundance of phytoplankton was found in the Station II area with an average abundance value of around 416.67 cells/L, while the highest average abundance was in the Station V area with an average value of 993.05 cells/L. The relationship between the content of nitrate, phosphate, and organic matter with the abundance of phytoplankton in the Rupat Island area was insignificant or weak with a coefficient of determination (R2) of 8%, 10.5% and 3.3%

Waste load allocation by integrated GMS modeling and economic evaluation for nitrate reduction in Varamin aquifer

Abstract Groundwater is a dependable freshwater resource in arid and semi-arid areas where its quality management is essential. However, untreated wastewater is a risk to safe water supply from aquifers. Wastewater treatment plants (WWTPs) can reduce pollutants, but their impact on groundwater quality versus their operating costs requires case studies. This research uses the two modules of the groundwater modeling system (GMS) to simulate the Varamin Plain, south-eastern Tehran, Iran. The MODFLOW and MT3D were used for groundwater quantity and quality modeling, respectively. Through these modules, the effectiveness of two WWTPs (Pakdasht and Varamin) in six waste load allocation (WLA) scenarios was compared based on nitrate reduction in 3-year and 10-year periods. The construction and operating costs of each WLA scenario were also calculated. The best WLA is a scenario with the lowest marginal cost. Therefore, constructing Varamin WWTP with 25% nitrogen removal was the selected option. Here, the average nitrate concentration in the aquifer is reduced from 28.4 mg/L (±4.1) to less than 25 mg/L (±2.4) with an annual marginal cost of 8 M$.L/mg. It implies that constructing more WWTPs or tertiary units for nitrate removal is not recommended as they do not add significant nitrate abatement in groundwater regarding the related costs.

Seasonal variation characteristics of atmospheric peroxyacetyl nitrate (PAN) and its source apportionment in a megacity in southern China

Owing to its biotoxicity and inductive effect on photochemical pollution, atmospheric peroxyacetyl nitrate (PAN), which is a typical product of atmospheric photochemical reactions, has attracted much research attention. However, to the best of our knowledge, few comprehensive studies have been conducted on the seasonal variation and key influencing factors of PAN concentrations in southern China. In this study, PAN, ozone (O3), precursor volatile organic compound (VOC), and other pollutant concentrations were measured online for 1 year (from October 2021 to September 2022) in Shenzhen, a megacity in the Greater Bay Area of China. The average concentrations of PAN and peroxypropionyl nitrate (PPN) were 0.54 and 0.08 parts per billion (ppb), and the maximum hourly concentrations reached 10.32 and 1.01 ppb, respectively. The results of the generalized additive model (GAM) showed that the atmospheric oxidation capacity and precursor concentration were the most important factors affecting the PAN concentration. According to the steady-state model, the average cumulative contribution to the peroxyacetyl (PA) radical formation rate by six major carbonyl compounds was calculated at 4.2 × 106 molecules cm−3 s−1, and acetaldehyde (63.0 %) and acetone (13.9 %) contributed the most. Furthermore, the photochemical-age-based parameterization method was used to analyze the source contributions of carbonyl compounds and PA radicals. The results showed that although the primary anthropogenic (40.2 %), biogenic (27.8 %), and secondary anthropogenic (16.4 %) sources were the most important contributors of PA radicals, the biogenic and secondary anthropogenic source contributions both increased considerably in summer, and the cumulative proportion of both sources reached ~70 % in July. In addition, a comparison of PAN pollution processes in different seasons revealed that in summer and winter, the PAN concentration was predominantly limited by precursors and meteorological parameters, such as light intensity, respectively.

Groundwater table fluctuation: A driving force affecting nitrogen transformation in nitrate-contaminated groundwater

Groundwater table fluctuation alters the biochemical environment and nitrogen transformation, leading to periodic changes in groundwater nitrate concentration. A microcosm experiment of groundwater table fluctuation was designed to explore the underlying mechanism. The dissolved oxygen (DO), bacterial community, functional gene groups and associated nitrogen transformation were investigated based on field scenario. The results showed that groundwater rising reduced the average nitrate concentration, while falling aggravated it. Owing to the variations in groundwater table, the DO concentration underwent periodic changes. Furthermore, the abundance and diversity of soil bacteria were enriched and the structure of the microbial community was altered. Nitrogen transformation biomarkers such as Arthrobacter sp., Bacillus sp., Chloroflexi sp. and Acidobacteriota sp. as well as nitrogen transformation functional genes were identified. A structure equation model was established which demonstrated that groundwater table fluctuation altered DO and the dominant bacterial abundance, which in turn modified the functional gene groups and nitrogen transformation. This study broadens the understanding of how and to what extent groundwater table fluctuation affects nitrogen transformation and is vital for assessing and managing risks associated with groundwater nitrate contamination

Investigating Nitrate with Other Constituents in Groundwater in Two Contrasting Tropical Highland Watersheds

Nitrate is globally the most widespread and widely studied groundwater contaminant. However, few studies have been conducted in sub-Saharan Africa, where the leaching potential is enhanced during the rainy monsoon phase. The few monitoring studies found concentrations over drinking water standards of 10 mg N-NO3− L−1 in the groundwater, the primary water supply in rural communities. Studies on nitrate movement are limited to the volcanic Ethiopian highlands. Therefore, this study aimed to evaluate the transport and fate of nitrate in groundwater and identify processes that control the concentrations. Water table height, nitrate, chloride, ammonium, reduced iron, and three other groundwater constituents were determined monthly in the groundwater in over 30 wells in two contrasting volcanic watersheds over two years in the Ethiopian highlands. The first watershed was Dangishta, with lava intrusion dikes that blocked the subsurface flow in the valley bottom. The water table remained within 3 m of the surface. The second watershed without volcanic barriers was Robit Bata. The water table dropped rapidly within three months of the end of the rain phase and disappeared except near faults. The average nitrate concentration in both watersheds was between 4 and 5 mg N-NO3− L−1. Hydrogeology influenced the transport and fate of nitrogen. In Dangishta, water was blocked by volcanic lava intrusion dikes, and residence time in the aquifer was larger than in Robit Bata. Consequently, nitrate remained high (in several wells, 10 mg N-NO3− L−1) and decreased slowly due to denitrification. In Robit Bata, the water residence time was lower, and peak concentrations were only observed in the month after fertilizer application; otherwise, it was near an average of 4 mg N-NO3− L−1. Nitrate concentrations were predicted using a multiple linear regression model. Hydrology explained the nitrate concentrations in Robit Bata. In Dangishta, biogeochemistry was also significant.

A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds

High-frequency stream nitrate concentration provides critical insights into nutrient dynamics and can help to improve the effectiveness of management decisions to maintain a sustainable ecosystem. However, nitrate monitoring is conventionally conducted through lab analysis using in situ water samples and is typically at coarse temporal resolution. In the last decade, many agencies started collecting high-frequency (5–60 min intervals) nitrate data using optical sensors. The hypothesis of the study is that the data-driven models can learn the trend and temporal variability in nitrate concentration from high-frequency sensor-based nitrate data in the region and generate continuous nitrate data for unavailable data periods and data-limited locations. A Long Short-Term Memory (LSTM) model-based framework was developed to estimate continuous daily stream nitrate for dozens of gauge locations in Iowa, USA. The promising results supported the hypothesis; the LSTM model demonstrated median test-period Nash-Sutcliffe efficiency (NSE) = 0.75 and RMSE = 1.53 mg/L for estimating continuous daily nitrate concentration in 42 sites, which are unprecedented performance levels. Twenty-one sites (50 % of all sites) and thirty-four sites (76 % of all sites) demonstrated NSE > 0.75 and 0.50, respectively. The average nitrate concentration of neighboring sites was identified as a crucial determinant of continuous daily nitrate concentration. Seasonal model performance evaluation showed that the model performed effectively in the summer and fall seasons. About 26 sites showed correlations >0.60 between estimated nitrate concentration and discharge. The concentration-discharge (c-Q) relationship analysis showed that the study watersheds had four dominant nitrate transport patterns from landscapes to streams with increasing discharge, including the flushing pattern being the most dominant one. Stream nitrate estimation impedes due to data inadequacy. The modeling framework can be used to generate temporally continuous nitrate at nitrate data-limited regions with a nearby sensor-based nitrate gauge. Watershed planners and policymakers could utilize the continuous nitrate data to gain more information on the regional nitrate status and design conservation practices accordingly.