Excess nitrate has been reported to be associated with many adverse effects in humans and experimental animals. However, there is a paucity of information of the effects of nitrate on intestinal microbial community. In this study, the effects of nitrate on development, intestinal microbial community, and metabolites of Bufo gargarizans tadpoles were investigated. B. gargarizans were exposed to control, 5, 20 and 100 mg/L nitrate-nitrogen (NO₃–N) from eggs to Gosner stage 38. Our data showed that the body size of tadpoles significantly decreased in the 20 and 100 mg/L NO₃–N treatment group when compared to control tadpoles. Exposure to 20 and 100 mg/L NO₃–N also caused indistinct cell boundaries and nuclear pyknosis of mucosal epithelial cells in intestine of tadpoles. In addition, exposure to NO₃–N significantly altered the intestinal microbiota diversity and structure. The facultative anaerobic Proteobacteria occupy the niche of the obligately anaerobic Bacteroidetes and Fusobacteria under the pressure of NO₃–N exposure. According to the results of functional prediction, NO₃–N exposure affected the fatty acid metabolism pathway and amino acid metabolism pathway. The whole-body fatty acid components were found to be changed after exposure to 100 mg/L NO₃–N. Therefore, we concluded that exposure to 20 and 100 mg/L NO₃–N could induce deficient nutrient absorption in intestine, resulting in malnutrition of B. gargarizans tadpoles. High levels of NO₃–N could also change the intestinal microbial communities, causing dysregulation of fatty acid metabolism and amino acid metabolism in B. gargarizans tadpoles.

Urine, which is an important waste biomass resource, is the main source of nitrogen in sewage and contains large quantities of emerging contaminants (ECs). In this study, we propose a new method to efficiently remove urine, simultaneously eliminate ECs, and control the generation of toxic chlorate during urine treatment using a photoelectrocatalytic-chlorine (PEC-Cl) system. A type-II heterojunction of WO₃/BiVO₄ was used as a photoanode to generate chlorine radicals (Cl•) by decreasing the oxidation potential of WO₃ valence band for the highly selective conversion of urine to N₂ and the simultaneous degradation of ECs in an efficient manner. The method presented surprising results. It was observed that the amount of toxic chlorate was significantly inhibited by circumventing the over-oxidation of Cl⁻ by holes or hydroxyl radicals (•OH). Moreover, the removal of urea nitrogen reached 97% within 90 min, while the degradation rate of trimethoprim in urine was above 98.6% within 60 min, which was eight times more than that in the PEC system (12.1%). Compared to the bare WO₃ photoanode, the toxic chlorate and nitrate generated by the WO₃/BiVO₄ heterojunction photoanode decreased by 61% and 44%, respectively. Thus, this study provides a safe, efficient, and environmentally-friendly approach for the disposal of urine.

To investigate chemical characteristics, abatement mechanisms and regional transport of atmospheric pollutants during the COVID-19 outbreak control period in the Yangtze River Delta (YRD) region, China, the measurements of air pollutants including fine particulate matter (PM₂.₅) and volatile organic compounds (VOCs) on non-control period (NCP, 24 December 2019–23 January 2020) and control period (CP, 24 January–23 February 2020) were analyzed at the urban Pudong Supersite (PD) and the regional Dianshan Lake Supersite (DSL). Due to the stricter outbreak control, the levels of PM₂.₅ and VOCs, and the occurrence frequencies of haze-fog episodes decreased substantially from NCP to CP, with average reduction rates of 31.6%, 38.9% and 35.1% at PD, and 34.5%, 50.7% and 37.9% at DSL, respectively. The major source for PM₂.₅ was secondary sulfate & nitrate in both periods, and the emission control of primary sources such as coal burning and vehicle exhaust decreased the levels of precursors gas sulfur dioxide and nitrogen oxide, which highly contributed to the abatement of PM₂.₅ from NCP to CP. The higher levels of ozone at both PD and DSL on CP might be due to the weak nitrogen monoxide titration, low relative humidity and high visibility compared with NCP. Vehicle exhaust and fugitive emission from petrochemical industry were the major contributors of ambient VOCs and their decreasing activities mainly accounted for VOCs abatement. Moreover, the high frequency of haze-fog events was closely impacted by medium-scale regional transport within Anhui and Jiangsu provinces. Therefore, the decreasing regional transported air pollutants coincided with the emission control of local sources to cause the abatement of haze-fog events in YRD region on CP. This study could improve the understanding of the change of atmospheric pollutants during the outbreak control period, and provide scientific base for haze-fog pollution control in YRD region, China.

This study presents a comprehensive analysis of organic carbon (OC), elemental carbon (EC), and particularly the light absorption characteristics of EC and water-soluble brown carbon (WS–BrC) in total suspended particles in the Kathmandu Valley from April 2013 to January 2018. The mean OC, EC, and water-soluble organic carbon (WSOC) concentrations were 34.8 ± 27.1, 9.9 ± 5.8, and 17.4 ± 12.5 μg m⁻³, respectively. A clear seasonal variation was observed for all carbonaceous components with higher concentrations occurring during colder months and lower concentrations in the monsoon season. The relatively low OC/EC ratio (3.6 ± 2.0) indicates fossil fuel combustion as the primary source of carbonaceous components. The optical attenuation (ATN) at 632 nm was significantly connected with EC loading (ECS) below 15 μg cm⁻² but ceased as ECS increased, reflecting the increased influence of the shadowing effect. The derived average mass absorption cross-section of EC (MACEC) (7.0 ± 4.2 m² g⁻¹) is comparable to that of freshly emitted EC particles, further attesting that EC was mainly produced from local sources with minimal atmospheric aging processes. Relatively intensive coating with organic aerosols and/or salts (e.g., sulfate, nitrate) was probably the reason for the slightly higher MACEC during the monsoon season, whereas increased biomass burning was a major factor leading to lower MACEC in other seasons. The average MACWS₋BᵣC at 365 nm was 1.4 ± 0.3 m² g⁻¹ with minimal seasonal variations. In contrast to MACEC, biomass burning was the main reason for a higher MACWS₋BᵣC in the non-monsoon season. The relative light absorption contribution of WS-BrC to EC was 9.9% over the 300–700 nm wavelength range, with a slightly higher ratio (13.6%) in the pre-monsoon season. Therefore, both EC and WS-BrC should be considered in the study of optical properties and radiative forcing of carbonaceous aerosols in this region.

Recently, sulfate radical-based advanced oxidation processes (SR-AOPs) have been studied extensively for the removal of pollutants, however, few researches focused on the activation of bisulfite by nanoscale zerovalent iron (nZVI), especially, surface reaction mechanism and sulfate radical-mediated degradation pathway have not been elucidated in detail. In this study, influencing factors, the kinetics, transformation pathway and mechanism of triphenyl phosphate (TPHP) degradation in the nZVI/bisulfite system were systematically discussed. Compared with Fe²⁺, nZVI was found to be a more efficient and long-lasting activator of bisulfite via gradual generation of iron ions. The optimal degradation efficiency of TPHP (98.2%) and pseudo-first-order kinetics rate constant (kₒbₛ = 0.2784 min⁻¹) were obtained by using 0.5 mM nZVI and 2.0 mM bisulfite at the initial pH 3.0. Both Cl⁻ and NO₃⁻ inhibited the degradation of TPHP and the inhibitory effect of Cl⁻ was stronger than that of NO₃⁻ due to the higher reaction rate of Cl⁻ with •SO₄⁻. Furthermore, SEM, XRD and XPS characterization revealed that a thin passivation layer (Fe₂O₃, Fe₃O₄, FeOOH) deposited on the surface of fresh nZVI and a few iron corrosion products generated and assembled on the surface of reacted nZVI. Radical quenching tests identified that •SO₄⁻ was the dominant reactive oxidative species (ROS) for TPHP removal. Based on HRMS analysis, six degradation products were determined and a sulfate radical-mediated degradation pathway was proposed. In a word, this study revealed that the nZVI/bisulfite system had a great potential for the TPHP elimination in waterbody.

Evaluation of the effectiveness of best management practices for reducing nitrate leaching in agricultural systems requires detailed water and nitrogen (N) budgets. A 3-year field experiment using 15 auto-weighing lysimeters was set up to quantify nitrate leaching, crop evapotranspiration (ET), and N and water use efficiencies within an intensive wheat-maize rotation system in the Northern China Plain. The lysimeter consists mainly of the following: (1) high-resolution weighing cells; (2) ceramic solution samplers for soil solutions collection; and (3) circular stainless steel leaching trays for collecting seepage water. Two N fertilizer types were applied at two rates (150 and 225 kg N hm⁻² for each crop) with no-N applied as the control. The N fertilizer types were monotypic un-coated urea and a blend product with controlled-release urea (CRU) and un-coated urea. The results indicate that when compared with un-coated urea at the same application rate, the blend product greatly improved water and N use efficiencies with significant increase in yields and crop ET as well as reduction of nitrate accumulation and leaching in the soil profile (p < 0.05). This was mostly because the blend product consistently supplied N to meet crop demands over the entire growth season. The study implied that effective best management practices to control nitrate leaching should be based on technically sound fertilization and irrigation schemes in terms of timing, rate, and fertilizer type to suit site specific conditions.

Hexavalent chromium and nitrate co-contaminated groundwater remediation are attracting extensive attention worldwide. However, the transformation pathways of chromium and nitrate and the interplay mechanism between them remain unclear. In this work, zeolite-supported nanoscale zero-valent iron/palladium (Z-Fe/Pd) was synthesized and used for the first time to simultaneously remediate Cr(VI) and nitrate. Transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy analyses confirmed that nanoscale zero-valent iron/palladium was successfully loaded onto zeolite and it exhibited good dispersibility and oxidation resistance. Results of batch experiments showed that the Cr(VI) and nitrate removal efficiencies decreased from 95.5% to 91.5% to 45% and 73%, respectively, with the initial solution pH increasing from 3.0 to 8.0. The removal rates and efficiencies of Cr(VI) and nitrate under anoxic conditions were higher than those under open atmosphere because the dissolved oxygen diminished the electron selectivity toward the target pollutants. Moreover, the presence of Cr(VI) inhibited nitrate reduction by forming Fe(III)-Cr(III) hydroxide to impede electron transfer. Cr(VI) removal was promoted by nitrate, within limits, by balancing the consumption and generation rate of Fe₃O₄, which enhanced electron migration from the Fe(0) core to the external surface. The removal capacities of Cr(VI) and nitrate reached 121 and 95.5 mg g⁻¹, respectively, which were superior to the removal capacities of similar materials. Results of product identification, XRD, and XPS analyses of spent Z-Fe/Pd indicated that the reduction of Cr(VI) was accompanied by adsorption and co-precipitation, whereas the reduction of nitrate was catalyzed by the synergism of Fe(0) and Pd(0). An alternative to the simultaneous remediation of Cr(VI) and nitrate from groundwater under anoxic conditions is provided.

The present study attempts to explore and compare the seasonal variability in chemical composition and contributions of different sources of fine and coarse fractions of aerosols (PM₂.₅ and PM₁₀) in Delhi, India from January 2013 to December 2016. The annual average concentrations of PM₂.₅ and PM₁₀ were 131 ± 79 μg m⁻³ (range: 17–417 μg m⁻³) and 238 ± 106 μg m⁻³ (range: 34–537 μg m⁻³), respectively. PM₂.₅ and PM₁₀ samples were chemically characterized to assess their chemical components [i.e. organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSICs) and heavy and trace elements] and then used for estimation of enrichment factors (EFs) and applied positive matrix factorization (PMF5) model to evaluate their prominent sources on seasonal basis in Delhi. PMF identified eight major sources i.e. Secondary nitrate (SN), secondary sulphate (SS), vehicular emissions (VE), biomass burning (BB), soil dust (SD), fossil fuel combustion (FFC), sodium and magnesium salts (SMS) and industrial emissions (IE). Total carbon contributes ∼28% to the total PM₂.₅ concentration and 24% to the total PM₁₀ concentration and followed the similar seasonality pattern. SN and SS followed opposite seasonal pattern, where SN was higher during colder seasons while SS was greater during warm seasons. The seasonal differences in VE contributions were not very striking as it prevails evidently most of year. Emissions from BB is one of the major sources in Delhi with larger contribution during winter and post monsoon seasons due to stable meteorological conditions and aggrandized biomass burning (agriculture residue burning in and around the regions; mainly Punjab and Haryana) and domestic heating during the season. Conditional Bivariate Probability Function (CBPF) plots revealed that the maximum concentrations of PM₂.₅ and PM₁₀ were carried by north westerly winds (north-western Indo Gangetic Plains of India).

Despite the large number of studies reporting the phytotoxicity of graphene-based materials, the effects of these materials on nutrient uptake in plants remain unclear. The present study showed that nitrate concentrations were significantly decreased in the roots of wheat plants treated with graphene oxide (GO) at 200–800 mg L⁻¹. Non-invasive microelectrode measurement demonstrated that GO could significantly inhibit the net NO₃⁻ influx in the meristematic, elongation, and mature zones of wheat roots. Further analysis indicated that GO could be trapped in the root vacuoles, and that the maximal root length and the number of lateral roots were significantly reduced. Additionally, root tip whitening, creases, oxidative stress, and weakened respiration were observed. These observations indicate that GO is highly unfavorable for vigorous root growth and inhibits increase in root uptake area. At the molecular level, GO exposure caused DNA damage and inhibited the expression of most nitrate transporters (NRTs) in wheat roots, with the most significantly downregulated genes being NRT1.3, NRT1.5, NRT2.1, NRT2.3, and NRT2.4. We concluded that GO exposure decreased the root uptake area and root activity, and decreased the expression of NRTs, which may have consequently suppressed the NO₃⁻ uptake rate, leading to adverse nitrate accumulation in stressed plants.

The increasing availability of water quality datasets has led to a greater focus on hydrologic and water quality analysis, thus requiring more efficient and accurate modelling methods. Data mining techniques have been increasingly used for water quality analysis and prediction of the concentration and load of nitrogen pollutants instead of more traditional simulation methods. In this study, we tested the multilayer perceptron (MLP), k-nearest neighbor (k-NN), random forest, and reduced error pruning tree (REPTree) methods, along with the traditional linear regression, to predict nitrate levels based on long-term data from six watersheds with different land-use practices in the midwestern United States. Both the concentration and load results indicated that REPTree had the best performance, with an R² of 0.61–0.85 and a relative absolute error of <75.8%. The different watershed types, however, influenced the performance of the data mining methods, where all four methods showed a higher accuracy for urban dominant watershed and lower accuracy for agricultural and forest watersheds. Out of these four methods, classification tree methods (REPTree and RF) performed better than cluster methods (MLP and k-NN) for agricultural and forested watersheds. Our results indicated that both the data structure based on the dominant land use and type of algorithmic method should be carefully considered for selecting a data mining method to predict nitrate concentration and load for a watershed.