Bisphenol A (BPA) is an emerging organic pollutant, widely distributed in environment. Plants can uptake and metabolize BPA, but BPA accumulation induces phytotoxicity. In this study, we administered dopamine, a kind of catecholamines with strong antioxidative potential, to unveil its role in cucumber tolerance to BPA stress. The results showed that exposure to BPA (20 mg L⁻¹) for 21 days significantly reduced growth and biomass accumulation in cucumber seedlings as revealed by decreased lengths and dry weights of shoots and roots. While BPA exposure decreased the chlorophyll content, cell viability and root activity, it remarkably increased reactive oxygen species (ROS) accumulation, electrolyte leakage and malondialdehyde (MDA) content, suggesting that BPA induced oxidative stress in cucumber. However, exogenous dopamine application significantly improved the photosynthetic pigment content, root cell viability, growth and biomass accumulation, and decreased the ROS and MDA levels by increasing the activity of antioxidant enzymes under BPA stress. Further analysis revealed that dopamine application significantly increased the glutathione content and the transcripts and activity of glutathione S-transferase under co-administration of dopamine and BPA compared with only BPA treatment. Moreover, dopamine decreased the BPA content in both leaves and roots, suggesting that dopamine promoted BPA metabolism by enhancing the glutathione-dependent detoxification. Our results show that dopamine has a positive role against BPA phytotoxicity and it may reduce the risks-associated with the dietary intake of BPA through consumption of vegetables.

Hydroxyl radical (•OH)- and sulfate radical (▪)-based advanced oxidation technologies (AOTs) have been proven an effective method to remove antibiotics in wastewater treatment plants (WWTPs). This study aims to gain insights into kinetics and mechanisms of neutral sulfamethoxazole (SMX) degradation, a representative antibiotic, by •OH and ▪ using an experimental and theoretical approach. First, the second-order rate constants (k) of SMX with •OH and ▪ were determined to be (7.27 ± 0.43) × 10⁹ and (2.98 ± 0.32) × 10⁹ M⁻¹ s⁻¹ in UV/H₂O₂ and UV/persulfate (UV/PS) systems, respectively. The following theoretical calculations at the M06–2X level of theory revealed that addition of radicals to the benzene ring is the most favorable first-step reaction for both •OH and ▪, but that ▪ exhibits higher energy barriers and selectivity than •OH due to steric hindrance. We further analyzed subsequent reactions and, interestingly, our findings closely corroborated HOMO/LUMO distributions of SMX to the oxidation pathways. Finally, the estimation of energy consumption for UV alone, •OH–, and ▪–mediated oxidation processes was compared. These comparative results, for the first time, provide insights into the similarities and differences of degradation of SMX by •OH/▪ at the molecular level and can help improve antibiotics removal using radical based AOTs in WWTPs.

As an important component of organic carbon (OC), brown carbon (BrC) plays a significant role in radiative forcing in the atmosphere. Water-insoluble OC (WIOC) generally has higher light absorption ability than water-soluble OC (WSOC). The mass absorption cross-section (MAC) of WIOC is normally investigated by dissolving OC in methanol. However, all the current methods have shortcomings due to neglecting the methanol insoluble particulate carbon that is detached from the filter and suspended in methanol extracts, which results in MAC uncertainties of the methanol-soluble BrC and its climate warming estimation. In this study, by investigating typical biomass combustion sourced aerosols from the Tibetan Plateau and ambient aerosols from rural and urban areas in China, we evaluated the light absorption of extractable OC fraction for the existing methods. Moreover, a new method was developed to overcome the methanol insoluble particulate carbon detachment problem to achieve more reliable MAC values. We found that OC can be dissolved in methanol in a short time (e.g., 1 h) and ultrasonic treatment and long-term soaking do not significantly increase the extractable OC fraction. Additionally, we proved that methanol insoluble particulate carbon detachment in methanol does exist in previous methods, causing overestimation of the BrC mass extracted by methanol and thus the underestimation of MAC values. We therefore recommend the newly developed extraction method in this study to be utilized in future related studies to quantitatively obtain the light absorption property of methanol-soluble BrC.

Tris(2-chloroethyl) phosphate (TCEP) is a widely found emerging pollutant due to its heavy usage as a flame retardant. It is chemically stable and is very difficult to removal from water. The goal of this study was to explore whether iron monosulfide (FeS) can be used for reductive transformation of TCEP as FeS can react with a variety of halogenated organic contaminants. We used batch reactor systems to quantify the transformation reactions in the absence and presence of cetyltrimethylammonium bromide (CTAB, a common surfactant in aquatic environments). The results showed that, in the presence of CTAB (100 mg L⁻¹), FeS exhibited much greater reactivity towards TCEP as 93% of initial TCEP had been transformed within 14 d of reaction. In the absence of CTAB, it required 710 d of reaction to achieve 97.3% reduction of initial TCEP. The enhancement of CTAB on TCEP transformation rate could be due to the facts that CTAB could stabilize FeS suspension against aggregation, protect FeS from rapid oxidation, and increase surface adsorption of TCEP on FeS. XPS analysis showed that both Fe(II) and S(-II) species on the FeS surface were involved in the reductive transformation of TCEP. Analysis of transformation products revealed that TCEP was reductively transformed into bis(2-chloroethyl) phosphate (BCEP), Cl⁻ and C₂H₄. These findings showed that FeS may play an important role in the reductive transformation of TCEP when TCEP coexisting with CTAB in aquatic environments.

Studies of the chemical composition of atmospheric aerosols, rain water and snow in various regions of the globe quite often show the presence of pyridine and a number of its low mass derivatives. Nevertheless, the sources of those compounds in the environment have not yet been established and definitely require elucidation, supported by reliable experimental results. In the present work the chemical composition of peat combustion products as one of the important sources of atmospheric aerosol emission is studied by two-dimensional gas chromatography – high-resolution mass spectrometry with a focus on the detection of pyridine derivatives. Twenty-five compounds of this class were reliably identified and quantified in laboratory experiments on peat burning. Among them 3-hydroxypyridine predominates, while the rest analytes are mostly represented by alkyl derivatives: pyridine, 2-methylpyridine, 3-methylpyridine, 2,5-dimethylpyridine, 2,6-dimethylpyridine, 2-ethylpyridine, lutidines (in order of decreasing concentration). The distribution of these combustion products coincides with that obtained earlier in environmental studies carried out in Arctic, Central Russia and France. The experiments on peat thermal decomposition by pyrolysis GC-MS demonstrated that the maximum concentrations as well as the number of detected analytes were found under conditions of oxygen lack and a temperature of about 500 °C, i.e. characteristic conditions of peat wildfires. The observed levels of pyridines’ emission recalculated on the peat dry weight exceeded 200 mg kg⁻¹. Considering hundreds of millions tons of peat burning in megafires over 20,000 tons of pyridines penetrate the Earth atmosphere annually. The obtained results allow concluding that peat burning may be the major and still underestimated source of pyridine and lower alkylpyridines in the Earth atmosphere.

In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality parameters, especially using spectral reflectance of water, must satisfy certain preconditions (e.g., flat water surface and ideal radiation geometry). In this study, we hypothesized that drone-borne hyperspectral imagery of emergent plants could be better applied to retrieval total nitrogen (TN) concentration in water regardless of preconditions possibly due to the spectral responses of emergent plants on nitrogen removal and water purification. To test this hypothesis, a total of 200 groups of bootstrap samples were used to examine the relationship between the extracted TN concentrations from the drone-borne hyperspectral imagery of emergent plants and the experimentally measured TN concentrations in Ebinur Lake Oasis using four machine learning (ML) models (Partial Least Squares (PLS), Random Forest (RF), Extreme Learning Machine (ELM), and Gaussian Process (GP)). Through the introduction of the fractional order derivative (FOD), we build a decision-level fusion (DLF) model to minimize the regression results’ biases of individual ML models. For individual ML model, GP performed the best. Still, the amount of uncertainty in individual ML models renders their performance to be subpar. The introduction of the DLF model greatly minimizes the regression results’ biases. The DLF model allows to reduce potential uncertainties without sacrificing accuracy. In conclusion, the spectral response caused by nitrogen removal and water purification on emergent plants could be used to retrieve TN concentration in water with a DLF model framework. Our study offers a new perspective and a basic scientific support for water quality monitoring in arid regions.

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating “good” to “excellent” water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl⁻, SO₄²⁻, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄–N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

Passive samplers are useful tools for monitoring hydrophobic, persistent, and potentially bioaccumulative contaminants in the environment. In this study, low density polyethylene passive samplers were deployed in urban-influenced and background nearshore freshwaters of northwestern Lake Ontario and analyzed for a broad range of both legacy halogenated organic contaminants (HOCs) and halogenated flame retardants (HFRs). Non-targeted analysis was conducted for screening additional halogenated substances. For most compounds, concentrations were greatest in the industrialized Hamilton Harbour and more generally at sites that have stronger influences of wastewater effluent discharges and stormwater run-off through rivers and creeks. Polychlorinated biphenyls (PCBs) remain the dominant class of HOCs in water, with dissolved-phase concentrations ranging from 10 to 4100 pg/L (ΣPCBs), followed by polybrominated diphenylethers (ΣPBDEs; 14–960 pg/L) and the organochlorine pesticides (OCPs; 22–290 pg/L). Several non-PBDE brominated flame retardants (nBFRs) and chlorinated Dechlorane-related compounds were detected, with hexabromocyclododecanes (ΣHBCDD; sum of 3 diastereoisomers) the most abundant (1.0–21 pg/L). Non-targeted screening of samples by high resolution mass spectrometry using Kendrick mass defect plots for data analysis indicated that several other halogenated compounds were present in waters at relatively high abundances compared to the flame retardants, based on semi-quantitative estimates. These included methyl-triclosan, four halogenated anisoles (2,4,6-tribromoanisole, dimethyl-trichloroanisole, pentachloroanisole, and pentachlorothioanisole), and pentachloro-aniline. Dissolved-phase methyl-triclosan was estimated to contribute up to approximately 40% of the summed target HOC concentrations. Polyethylene passive samplers provided an excellent medium for both non-targeted screening of HOCs not currently included in monitoring programs and tracking brominated and chlorinated chemicals slated for reductions in uses and emissions through international (Stockholm Convention) and binational (Great Lakes) agreements.

Wildfires may play a role in redistributing radionuclides in the environment in combination with hydrological processes such as surface runoff and soil erosion. We investigated plot-scale radionuclide wash-off at forest sites affected by wildfires in the Chernobyl Exclusion Zone (CEZ). We also compared speciation of the washed-off radionuclides with those in previous studies conducted just after the accident in 1986. We observed the surface runoff and the radionuclide wash-off with a soil erosion plot at forest and post-fire sites during May–September 2018. In the post-fire site, 2.81 mm of surface runoff was observed in at least three flow events resulting from 285.8 mm total rainfall. The fluxes of dissolved and particulate ¹³⁷Cs were estimated as 4.9 and 161 Bq m⁻², respectively. The dissolved phase ⁹⁰Sr flux was estimated as 214 Bq m⁻². At the forest site, a single surface runoff (0.67 mm) event was generated by rainfall of 182.2 mm. The fluxes of dissolved and particulate ¹³⁷Cs wash-off values were 6.2 and 8.6 Bq m⁻², respectively. The flux of dissolved ⁹⁰Sr wash-off from the forest was estimated as 45.1 Bq m⁻². The distribution coefficient, which indicates the dissolved-particulate form of radionuclides, in the post-fire site was 30 times higher than that in the forest site, indicating the importance of particulate ¹³⁷Cs wash-off after fire in the CEZ. The entrainment coefficients for dissolved and particulate ¹³⁷Cs concentrations were around 50 times lower than those obtained in the corresponding position within the CEZ immediately after the accident in 1987. The effect of downward migration of ¹³⁷Cs over 30 years led to decreased entrainment coefficients for dissolved and particulate ¹³⁷Cs. The effect of downward migration of radionuclides was considered sufficient to indicate changes in normalized liquid and solid radionuclides wash-off entrainment coefficient and the distribution coefficient in this study.