Anthropogenic pollution of the Arctic atmosphere is of great interest due to the vulnerability of the Arctic ecosystems, as well as the processes of global transport and accumulation of atmospheric aerosols at high latitudes under conditions of cold climate. The present work throws light upon chemical composition of Arctic snow as a natural deposition matrix for atmospheric semi-volatile pollutants taken from the northernmost Arctic archipelago - Franz Josef Land, which is least affected by local sources of pollution and being a unique unstudied environmental object. The used methodology involved the liquid-liquid extraction of snow samples with dichloromethane and combination of targeted and non-targeted analyses of semi-volatile organic compounds with comprehensive two-dimensional gas chromatography – high-resolution mass spectrometry. While almost none of the known priority pollutants (except three dialkylphthalates) were identified in the studied samples, non-targeted screening revealed a specific class of biomass burning biomarkers – fatty amides with oleamide being the major component among them. Some peculiar organic pollutants (N,N-dimethylcyclohexylamine and N,N-dimethylbenzylamine) were identified in few samples.First results on the semi volatile pollutants in Franz Joseph Land snow were obtained using the most reliable GC × GC-HRMS non-target analysis.

Environmental contamination of the Arctic has widely been used as a worldwide pollution marker. Various classes of organic pollutants such as pesticides, personal care products, PAHs, flame retardants, biomass burning markers, and many others emerging contaminants have been regularly detected in Arctic samples. Although numerous papers have been published reporting data from the Canadian, Danish, and Norwegian Arctic regions, the environmental situation in Russian Arctic remains mostly underreported. Snow analysis is known to be used for monitoring air pollution in the regions with cold climate in both short-term and long-term studies. This paper presents the results of a nontargeted study on the semivolatile organic compounds detected and identified in snow samples collected at the Russian Artic Archipelago Novaya Zemlya in June 2016. Gas chromatography coupled to a high-resolution time-of-flight mass spectrometer enabled the simultaneous detection and quantification of a variety of pollutants including those from the US Environmental Protection Agency (EPA) priority pollutants list, emerging contaminants (plasticizers, flame retardants-only detection), as well as the identification of novel Arctic organic pollutants, (e.g., fatty acid amides and polyoxyalkanes). The possible sources of these novel pollutants are also discussed.GC-HRMS enabled the detection and identification of emerging contaminants and novel organic pollutants in the Arctic, e.g., fatty amides and polyoxyalkanes.

In the present study, the 16S-rRNA sequencing of heavy metal-resistant and susceptible bacterial strains isolated from the industrial and agriculture soil showed resemblance with Pseudomonas taiwanensis. Based on the growth rate, two bacterial strains SJPS_KUD54 and KUD-MBBT4 exhibited 10 ppm tolerance to Arsenic and Cadmium. These two heavy metals caused, a significant increase in stress enzymes like superoxide dismutase, catalase and glutathione S-transferase activities in SJPS_KUD54 when compared to KUD-MBBT4. Following heavy metal treatment, the atomic-force-microscopy observations showed no change in the cell-wall of SJPS_KUD54, whereas the cell-wall of KUD-MBBT4 got ruptured. Moreover, the protein-profile of SJPS_KUD54 treated with heavy metals exhibited varied patterns in comparison with untreated control. In addition, the accumulation of hydroxyl, thiol and amides were found in the SJPS_KUD54 relative to its control. Furthermore, the resistant SJPS_KUD54 strain showed a remarkable bioaccumulation properties to both Arsenic and Cadmium. Thus, it is inferred that the growth rate, stress enzymes and functional-groups play a significant role in the physiological-adaption of SJPS_KUD54 during stress conditions, which is positively involved in the prevention or repair mechanism for reducing the risks caused by heavy metal stress.

Although organic species are transported and efficiently transformed in clouds, more than 60% of this organic matter remains unspeciated. Using GCxGC-HRMS technique we were able to detect and identify over 100 semi-volatile compounds in 3 cloud samples collected at the PUY station (puy de Dôme mountain, France) while they were present at low concentrations in a very small sample volume (<25 mL of cloud water). The vast majority (∼90%) of the detected compounds was oxygenated, while the absence of halogenated organic compounds should be specially mentioned. This could reflect both the oxidation processes in the atmosphere (gas and water phase) but also the need of the compounds to be soluble enough to be transferred and dissolved in the cloud droplets. Furans, esters, ketones, amides and pyridines represent the major classes of compounds demonstrating a large variety of potential pollutants. Beside these compounds, priority pollutants from the US EPA list were identified and quantified. We found phenols (phenol, benzyl alcohol, p-cresole, 4-ethylphenol, 3,4-dimethylphenol, 4-nitrophenol) and dialkylphthalates (dimethylphthalate, diethylphthalate, di-n-butylphthalate, bis-(2-ethylhexyl)-phthalate, butylbenzylphthalate, di-n-octyl phthalate). In general, the concentrations of phthalates (from 0.09 to 52 μg L−1) were much higher than those of phenols (from 0.03 to 0.74 μg L−1). To our knowledge phthalates in clouds are described here for the first time. We investigated the variability of phenols and phthalates concentrations with cloud air mass origins (marine vs continental) and seasons (winter vs summer). Although both factors seem to have an influence, it is difficult to deduce general trends; further work should be conducted on large series of cloud samples collected in different geographic areas and at different seasons.

Complexation and coagulation of plant-derived dissolved organic matter (DOM) by metal cations are important biogeochemical processes of organic matter in aquatic systems. Thus, coagulation and fractionation of DOM derived from aquatic plants by Ca(II), Al(III), and Fe(III) ions were investigated. Metal ion-induced removal of DOM was determined by analyzing dissolved organic carbon in supernatants after addition of these metal cations individually. After additions of metal ions, both dissolved and coagulated organic fractions were characterized by use of fluorescence excitation emission matrix-parallel factor (EEM-PARAFAC) analysis and Fourier transform infrared (FT-IR) spectroscopy. Addition of Ca(II), Fe(III) or Al(III) resulted in net removal of aquatic plant-derived DOM. Efficiencies of removal of DOM by Fe(III) or Al(III) were greater than that by Ca(II). However, capacities to remove plant-derived DOM by the three metals were less than which had been previously reported for humic materials. Molecular and structural features of plant-derived DOM fractions in associations with metal cations were characterized by changes in fluorescent components and infrared absorption peaks. Both aromatic and carboxylic-like organic matters could be removed by Ca(II), Al(III) or Fe(III) ions. Whereas organic matters containing amides were preferentially removed by Ca(II), and phenolic materials were selectively removed by Fe(III) or Al(III). These observations indicated that plant-derived DOM might have a long-lasting effect on water quality and organisms due to its poor coagulation with metal cations in aquatic ecosystems. Plant-derived DOM is of different character than natural organic matter and it is not advisable to attempt removal through addition of metal salts during treatment of sewage.

Plant- and/or microbe-based systems can provide a cost-effective, sustainable means to remove contaminants from soil. Microbe-assisted phytoremediation has potential utility for polycyclic aromatic hydrocarbons such as fluoranthene (Flu) removal from soils; however, the efficiency varies with the plant and microbes used. This study evaluated the Flu removal efficiency in a system with ryegrass (Lolium multiflorum), an IAA-producing Arthrobacter pascens strain (ZZ21), and/or a Flu-degrading Bacillus cereus strain (Z21). Strain ZZ21 significantly enhanced the growth of ryegrass. Ryegrass in combination with both strains (FIP) was the most effective method for Flu removal. By day 60, 74.9% of the Flu was depleted in the FIP treatment, compared with 21.1% in the control (CK), 63.7% with ryegrass alone (P), 69.0% for ryegrass with ZZ21 (IP), and 72.6% for ryegrass with Z21 (FP). FIP treatment promoted ryegrass growth, accelerated Flu accumulation in plants, and increased soil microbial counts. Microbial carbon utilization was significantly higher in soil in the FIP than with the CK treatment. Principal component analysis of the distribution of carbon substrate utilization showed that microbial functional profiles diverged among treatments, and this divergence became more profound at day 60 than day 30. Microbial inoculation significantly enhanced microbial utilization of phenols. Microbes in the FIP soil dominantly utilized amines/amides and phenols at day 30 but shifted to carbohydrates by day 60. Together, the combination of IAA-producing microbes and Flu-degrading microbes could promote plant growth, facilitate Flu degradation, and change soil microbial functional structure.

Active functional groups in biofilms determine the adsorption and desorption of contaminants and nutrients. Epilithic biofilms were characterized in order to understand the association between the chemistry alteration patterns and the surrounding anthropic activities of the Guaporé River watershed. The instrumental analyses included pyrolysis coupled to gas chromatography and mass spectroscopy, spectroscopy in the IR region with attenuated total reflectance, and two-dimensional nuclear magnetic resonance. Spectrometric techniques demonstrated that epilithic biofilms are mainly composed of polysaccharides, nitrogen-containing compounds, lipids, and aromatic and phenolic structures, which have functional groups characteristic of alcohols, esters, ethers, and amides. The polysaccharide levels reflect well the environmental pressures. The chemical composition of epilithic biofilms can be an effective tool for environmental assessment in watercourses, since the different anthropic actions developed in watersheds, mainly agriculture and urban areas, can modify the organic fraction of biofilms.

The increasing contamination of soils, sediments, and water with heavy metals through natural and industrial processes is a worldwide problem. Mining processes produce tons of material contaminated with radionuclides such as U and different heavy metals such as Cd, Ni, and Pb. U(VI) adsorbs strongly on bacteria, exhibiting pH-dependent adsorption behavior that is caused by a range of uranyl surface complexes on bacteria cell walls. The Amycolatopsis sp. K47 was isolated from Manisa Koprubasi Kasar open-cast uranium mine and identified for the first time. Using the batch adsorption method, the biosorption potential of this microbe was investigated by studying the effects of changes in pH (1–10), biomass dose (0.1–5 g/l), initial uranium metal concentration (5–200 mg/l), contact time (5–180 min), and temperature (20–60 °C). Interpretation of FTIR data obtained for both the uranium loaded and unloaded Amycolatopsis sp. K47 biomass showed the presence of carboxylic acid, hydroxyl, and amide functional groups that could interact with uranium ions. Scanning electron microscopy images demonstrated that uranium was intensely adsorbed on the microbial biomass surface. The sorption isotherms were investigated by analysis of the Langmuir, Freundlich, and Dubinin–Radushkevich (D–R) models. The Langmuir isotherm model was found to show the best fit for the experimental data obtained. Furthermore, thermodynamic parameters, such as ΔH°, ΔS°, and ΔG°, were calculated using adsorption equilibrium constant obtained from the Langmuir isotherm. The optimal experimental conditions were determined to be pH = 4, C₀ = 40 ppm, t = 150 min, temp. = 40 °C, and abs. dose = 1 g/l, and the corresponding U(VI) removal efficiency was about 97 ± 2%.

We propose a simple, fast, and inexpensive method for the analyses of 72 organic compounds in municipal landfill leachate, based on dispersive liquid-liquid microextraction and comprehensive two-dimensional gas chromatography coupled with mass spectrometry. Forty-one organic compounds belonging to several classes including hydrocarbons, mono- and polyaromatic hydrocarbons, carbonyl compounds, terpenes, terpenoids, phenols, amines, and phthalates, covering a wide range of physicochemical properties and linked to municipal landfill leachate, were quantitatively determined. Another 31 organic compounds such as indoles, pyrroles, glycols, organophosphate flame retardants, aromatic amines and amides, pharmaceuticals, and bisphenol A have been identified based on their mass spectra. The developed method provides good performances in terms of extraction recovery (63.8–127%), intra-day and inter-day precisions (< 7.7 and < 13.9 respectively), linearity (R² between 0.9669 and 0.9999), detection limit (1.01–69.30 μg L⁻¹), quantification limit (1.87–138.6 μg L⁻¹), and enrichment factor (69.6–138.5). Detailed information on the organic pollutants contained in municipal landfill leachate could be obtained with this method during a 40-min analysis of a 4-mL leachate sample, using only 75 μL of extraction solvent.

The n-octanol/water partition coefficient (logKₒw) is widely used in the environmental, agricultural and pharmaceutical fields for the risk evaluation and application of organic chemicals. In this work, grounded on atomic distribution matrices, a norm index-based QSPR model was built for organic chemicals with 18 kinds of diverse structures. The statistical results (R² = 0.9037, RMSE = 0.4515) showed that the QSPR model for describing the logKₒw of organics was fitted well. Various validation results showed that the model had good robustness, good predictability and wide applicability. These satisfactory results indicated that the model was applicable for the logKₒw description of organic chemicals and that norm descriptors were reliable and general for the description of organic structures. The model was relatively better at describing logKₒw for aromatics, alcohols, nitriles, esters, amides, halogenated compounds, acids and amine compounds. The intensity of spatial branching and the space charge distribution intensity descriptors could have a greater impact on the logKₒw value of a compound.