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Observational Evidence of Unknown NO<sub>x</sub> Source and Its Perturbation of Oxidative Capacity in Bermuda's Marine Boundary Layer

AbstractNitrogen oxides (NOx) are key intermediates in the atmospheric cycling of reactive nitrogen, the spatiotemporal distribution of which modulates ozone (O3) production. Field campaigns were conducted at the Tudor Hill Marine Atmospheric Observatory, Bermuda, in the spring and summer of 2019 to explore atmospheric cycling of NOx and its modulation of photochemical O3 production in the marine boundary layer. In aged, clean marine air, an atypical NO2 diel profile with a solar noon peak of 69 ± 5 pptv was recorded, challenging the classic U‐shaped diel profile with a solar noon valley characterized by fast photolysis and oxidation consumption in the daytime. This result indicated an unknown daytime NOx source excluded from the current near‐explicit chemical model, which underestimated the solar noon NOx level by 20–56 pptv and source rate by 9.7–33.5 pptv hr−1, considering the upper and lower limits of total OH reactivity and halogen photochemistry in the marine boundary layer. The observed HONO level accounted for ∼56% of the unknown NOx source, implying an unknown NOx regeneration pathway with HONO as an intermediate. The photochemical nature of the unknown NOx source maximized perturbation of photochemical OH and O3 production. The O3 abundance and production rate were underestimated by 2–4 ppbv and 28%–80%, respectively, and the OH abundance and source rate were 7%–55% and 21%–57% lower than the estimated levels with the constraint of NOx, respectively. The unknown NOx source requires urgent revision of the current understanding of reactive nitrogen cycling and the oxidative capacity of the clean marine atmosphere.

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Further understanding NaClO cleaning of bacteria-fouled ultrafiltration membrane: Variation of membrane structure and formation of halogenated by-products

NaClO has been extensively used for controlling membrane fouling in water and wastewater treatment processes, with bacteria being a common foulant in long-term ultrafiltration. However, the potential impact of NaClO cleaning on membrane structure and the formation of halogenated by-products remains unclear. This study comprehensively investigated the variation of membrane characteristics and formation of halogenated by-products during the chemical cleaning of Escherichia coli (E. coli) cell-fouled membrane using NaClO solution. The feed water containing E. coli cells resulted in severe membrane fouling by forming a dense cake layer, while NaClO cleaning achieved complete restoration of membrane flux under optimal conditions. The cleaning performance was compromised under high temperature and acidic conditions due to the lysis of E. coli cells and the limited oxidative capability of HClO. Excellent chemical resistance of polyethersulfone membrane against NaClO was confirmed under appropriate operational conditions. The biofouling and membrane materials played critical roles as precursors in the formation of halogenated chemicals during NaClO cleaning, and the generation pattern of by-products is highly dependent on the composition of membrane foulants. Increasing E. coli concentration, NaClO dosage, temperature and blending time led to the monotonical accumulation of almost all eleven representative by-products. As solution pH rose continuously, several by-products including trichloroacetic acid and chloral hydrate exhibited an initial increasing then decreasing trend, which could be attributed to the relative quantities between their formation and decomposition rates.

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Humification levels of dissolved organic matter in the eastern plain lakes of China based on long-term satellite observations

Under the influence of intensive human activities and global climate change, the sources and compositions of dissolved organic matter (DOM) in the eastern plain lake (EPL) region in China have fluctuated sharply. It has been successfully proven that the humification index (HIX), which can be derived from three-dimensional excitation-emission matrix fluorescence spectroscopy, can be an effective proxy for the sources and compositions of DOM. Therefore, combined with remote sensing technology, the sources and compositions of DOM can be tracked on a large scale by associating the HIX with optically active components. Here, we proposed a novel HIX remote sensing retrieval (IRHIX) model suitable for Landsat series sensors based on the comprehensive analysis of the covariation mechanism between HIX and optically active components in different water types. The validation results showed that the model runs well on the independent validation dataset and the satellite-ground synchronous sampling dataset, with an uncertainty ranging from 30.85 % to 36.92 % (average ± standard deviation = 33.6 % ± 3.07 %). The image-derived HIX revealed substantial spatiotemporal variations in the sources and compositions of DOM in 474 lakes in the EPL during 1986–2021. Subsequently, we obtained three long-term change modes of the HIX trend, namely, significant decline, gentle change, and significant rise, accounting for 74.68 %, 17.09 %, and 8.23 % of the lake number, respectively. The driving factor analysis showed that human activities had the most extensive influence on the DOM humification level. In addition, we also found that the HIX increased slightly with increasing lake area (R2 = 0.07, P < 0.05) or significantly with decreasing trophic state (R2 = 0.83, P < 0.05). Our results provide a new exploration for the effective acquisition of long-term dynamic information about the sources and compositions of DOM in inland lakes and provide important support for lake water quality management and restoration.

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Insight into the mechanism of nitrogen sufficiency conversion strategy for microalgae-based ammonium-rich wastewater treatment

The strategy of nitrogen sufficiency conversion can improve ammonium nitrogen (NH4+-N) removal with microalgal cells from ammonium-rich wastewater. We selected and identified one promising isolated algal strain, NCU-7, Chlorella sorokiniana, which showed a high algal yield and tolerance to ammonium in wastewater, as well as strong adaptability to N deprivation. The transition from N deprivation through mixotrophy (DN, M) to N sufficiency through autotrophy (SN, P) achieved the highest algal yields (optical density = 1.18 and 1.59) and NH4+-N removal rates (2.5 and 4.2 mg L−1 d−1) from synthetic wastewaters at two NH4+-N concentrations (160 and 320 mg L−1, respectively). Algal cells in DN, M culture obtained the lowest protein content (20.6%) but the highest lipid content (34.0%) among all cultures at the end of the stage 2. After transferring to stage 3, the lowest protein content gradually recovered to almost the same level as SN, P culture on the final day. Transmission electron microscopy and proteomics analysis demonstrated that algal cells had reduced intracellular protein content but accumulated lipids under N deprivation by regulating the reduction in synthesis of protein, carbohydrate, and chloroplast, while enhancing lipid synthesis. After transferring to N sufficiency, algal cells accelerated their growth by recovering protein synthesis, leading to excessive uptake of NH4+-N from wastewater. This study provides specific insights into a nitrogen sufficiency conversion strategy to enhance algal growth and NH4+-N removal/uptake during microalgae-based ammonium-rich wastewater treatment.

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Estimating the temporal and spatial distribution and threats of bisphenol A in temperate lakes using machine learning models

Bisphenol A (BPA) is easily enriched in many human-disturbed watersheds, particularly lakes with poor water mobility, which is posing a threat to aquatic biota. While previous studies have focused on the concentration of BPA in water and its toxicity to aquatic organisms, a small amount of measured data is not enough to reveal the temporal and spatial distribution and threats of BPA, and estimate the ecological risk in watersheds. Therefore, we collected 164 measured BPA data points from Taihu Lake to develop machine learning models using random forest (RF), support vector machine (SVM) and least square regression (LSR) and created month-by-month watershed prediction maps in temperate lakes to estimate the spatiotemporal distribution and threats of BPA. Due to RF's superior robustness to noisy data, the RF model exhibits the best performance among the three algorithms. The RF model showed acceptable predictive performance on the modeling dataset (coefficients of determination and root-mean-square error for the training set were 0.927 and 17.499, respectively, and 0.607, 39.645 for the validation set, respectively). The maps indicated that areas susceptible to anthropogenic activities were more severely polluted by BPA, and rainy climate may favor the migration of BPA to aquatic ecosystems. The model was also applied to predict 42 data points of BPA collected from Dianchi Lake, and the results showed that most predicted data were within a factor of 10 of the measured data, but the prediction accuracy of the model has declined. The ecological risks in the two lakes were evaluated and attention should be paid to the regions with higher risks. Our study provided a novel idea for comprehensive monitoring of an unconventional trace pollutant with endocrine disrupting effects in aquatic ecosystems and analyzing their spatiotemporal distribution, which will contribute to the scientific assessment of the ecological risk of BPA.

Open Access
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Gas–particle partitioning and dry deposition of atmospheric parent, alkylated, nitrated and hydroxyl polycyclic aromatic hydrocarbons over the Bohai sea and northern Yellow sea in autumn

To elucidate the gas–particle partitioning characteristics and dry deposition contributions of polycyclic aromatic hydrocarbons (PAHs) in the marine environment, 23 integrated air samples were collected during a research cruise in the northern Yellow Sea (NYS) and Bohai Sea (BS) in mid-autumn 2020. The atmospheric concentrations of 23 parent PAHs (PPAHs), 18 alkylated PAHs (APAHs), five nitrated PAHs (NPAHs), and seven hydroxyl PAHs (OPAHs) in gaseous and particulate phases were measured simultaneously. The total concentrations of 53 PAHs varied from 8.77 to 348 ng/m3. The 2-ring and 3-ring PPAHs and APAHs had lower particle-bound fractions than those of the NPAHs and OPAHs. For the gas–particle partitioning of the PAHs, the gas–particle partitioning coefficients (Kp) estimated using an octanol–air partition coefficient (KOA)–based model and KOA/soot–air partition coefficient (KSA) dual model (KOA–KSA dual model) were lower than the Kp measured in the field. Underestimation of the Kp commonly occurred with these models, but the KOA–KSA dual model was more suitable than the KOA–based model for gas–particle partitioning of the 53 atmospheric PAHs in the BS and NYS. The estimated atmospheric dry deposition fluxes of the 53 PAHs ranged from 631 to 14,345 ng/m2/day. The BS receives a PAHs load of up to 117 tons/year. The study provides background information on the occurrence and environmental fate of PAHs and could be vitally important for environmental safety management for the Northwest Pacific Ocean.

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Occurrence, influencing factors and sources of atmospheric microplastics in peri-urban farmland ecosystems of Beijing, China

Atmosphere is an important component of the microplastics (MPs) cycle. However, studies on atmospheric MPs in peri-urban farmland ecosystems are limited. Herein, the occurrence, influencing factors and geographic sources of atmospheric MPs in peri-urban farmland ecosystems have been analyzed. The average deposition flux of atmospheric MPs was found to be 167.09 ± 92.03 item·m−2·d−1. Around 68 % MPs had particle size <1000 μm, while the main colors of MPs were black (40.71 %) and blue (20.64 %). Approximately 91 % MPs were fibers, while polyethylene terephthalate (49 %) and rayon (36.93 %) were observed as the major microplastic types. The main factors influencing the atmospheric deposition of MPs were gross domestic product (GDP), population density, air pressure, and wind direction. Deposition fluxes exhibited positive correlations with GDP, population density and air pressure, and negative correlations with wind direction. Combined with the backward trajectory model, MPs were mainly found to be originated from the southeast in September and from the northwest in October–February. The study of atmospheric MPs in farmland ecosystems in peri-urban areas is important for the protection of ecological environment, prevention of human diseases and control of MPs pollution.

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