Iron particles present in drinking water distribution systems (DWDSs) could cause discoloration, while organic pollutants in DWDSs, such as perfluorooctanoic acid (PFOA), could be enriched by iron particles. However, little is known about the enhanced effects of PFOA and iron particles in DWDSs. To fill in these knowledge gaps, herein, iron-PFOA (FEP) particles were generated using residual chlorine as an oxidant in drinking water conditions and then separated into different sizes (ranging from small to large: FEP-S, FEP-M ，and FEP-L). FEP-S harbored the greatest cytotoxicity among the sizes. Interestingly, our data revealed that the PFOA released from FEP particles transformed into PFOS (perfluorooctane sulfonate) upon digestion in the gastrointestinal environment (GI), and FEP-L bored the strongest transformation, showing a toxicity profile that was distinct from that of FEP-S. Furthermore, mechanistic studies revealed that FEP per se should be accountable for the conversion of PFOA to PFOS dependent on the generation of hydroxyl radicals (·OH) in GI, and that FEP-L revealed the greatest production of ·OH. Collectively, these results showed how iron particles and PFOA could result in enhanced toxicity effects in drinking water: (i) PFOA could increase the toxicity of iron particles by reducing particle size and inducing higher generation of ·OH; (ii) iron particles could induce the transformation of PFOA into more toxic PFOS through digestion.

A recently identified chemical, 2-((4-Methylpentan-2-yl)amino)-5-(phenylamino)cyclohexa-2,5-diene-1,4-dione (6PPD-quinone; 6PPD-Q), is a transformation product of an additive used in the manufacture of tire rubber and causes acute lethality in coho salmon (Oncorhynchus kisutch) in urban watersheds. Despite its potential presence and ecotoxicity in receiving waters worldwide, information on the occurrence and fate of 6PPD-Q is limited. Here, we investigated the concentrations of 6PPD-Q and its parent chemical, 6PPD, in road dust collected from arterial and residential roads in Tokyo, Japan from May to October 2021. 6PPD-Q concentrations were highest from May to June, when atmospheric ozone concentrations are the highest in Japan; a correlation between 6PPD-Q and photochemical oxidants, as an alternative to ozone, corroborated this finding. We also found that 6PPD-Q concentrations at photochemical oxidant concentrations ranging from 35 to 47 ppbv were higher in dust collected from roads with high traffic volumes (i.e., arterial roads; median: 8.6 μg/g-OC) than in dust collected from roads with lower traffic volumes (i.e., residential roads; median: 6.3 μg/g-OC), indicating that 6PPD-Q is generated from traffic-related sources. We also found that 6PPD-Q was leached from dust particles within a few hours, with a log partitioning coefficient between organic carbon and water (KOC) of 3.2–3.5. The present results will help to understand the environmental occurrence, fate, and behavior of 6PPD-Q.

Combined chemical oxidation and bioremediation is a promising method of treating polycyclic aromatic hydrocarbon (PAH) contaminated soil, wherein indigenous soil bacteria play a critical role in the subsequent biodegradation of PAHs after the depletion of the oxidant. In this study, different Fenton conditions were applied by varying either the oxidation mode (conventional Fenton (CF), Fenton-like (LF), modified Fenton (MF), and graded modified Fenton (GMF)) or the H₂O₂ dosage (0%, 3%, 6%, and 10% (v/v)) to treat PAH contaminated soil. The results revealed that when equal dosages of H₂O₂ are applied, PAHs are significantly removed following oxidation treatment, and the removal percentages obeyed the following sequence: CF > GMF > MF > LF. In addition, higher dosages of H₂O₂ improved the PAH removal from soil treated with the same oxidation mode. The ranges of total PAHs removal efficiencies in the soil added 3%, 6%, and 10% of H₂O₂ (v/v) were 18.04%∼59.48%, 31.88%∼71.83%, and 47.56%∼78.16%, respectively. The PAH removal efficiency decreased with increasing ring numbers for the same oxidation treatment. However, the negative influences on soil bacterial abundance, community composition, and function were observed after Fenton treatment. After Fenton oxidation, the bacterial abundance in the soil received 3%, 6%, and 10% of H₂O₂ (v/v) decreased 1.96–2.69, 2.44–3.22, and 3.09–3.42 orders of magnitude compared to the untreated soil. The soil bacterial abundance tended to be impacted by the oxidation mode and H₂O₂ dosage simultaneously. While the main factor influencing the soil bacterial community composition was the H₂O₂ dosages. The results of this study showed that different oxidation mode and H₂O₂ dosage exhibited different effects on PAHs removal and soil bacteria (including abundance, community composition, and function), and there was a trade-off between the removal of PAHs and the adverse impact on soil bacteria.

Though many studies pertaining to soil bioremediation have been performed to study the microbial kinetics in shake flasks, the process efficiency in column tests is seldom. In the present study, soil columns tests were carried out to study the biodegradation of soil contaminated with a high concentration of diesel (≈19.5 g/kg) petroleum hydrocarbons expressed as C₁₀–C₅₀. Experiments were done with crude enzymatic cocktail produced by the hydrocarbonoclastic bacterium, Alcanivorax borkumensis. A. borkumensis was grown on a media with 3% (v/v) motor oil as the sole carbon and energy source. The effects of the enzyme concentration, treatment time and oxidant on the bioremediation efficiency of C₁₀–C₅₀ were investigated. A batch test was also carried out in parallel to investigate the stability of the enzymes and the effect of the biosurfactants on the desorption and the bioconversion of C₁₀–C₅₀. Batch tests indicated that the biosurfactants significantly affected the desorption and alkane hydroxylase and lipase enzymes, maintained their catalytic activity during the 20-day test, with a half-life of 7.44 days and 8.84 days, respectively. The crude enzyme cocktail, with 40 U/mL of lipase and 10 U/mL of alkane hydroxylase, showed the highest conversion of 57.36% after 12 weeks of treatment with a degradation rate of 0.0218 day⁻¹. The results show that the soil column tests can be used to optimize operating conditions for hydrocarbon degradation and to assess the performance of the overall bioremediation process.

During March 2020, most European countries implemented lockdowns to restrict the transmission of SARS-CoV-2, the virus which causes COVID-19 through their populations. These restrictions had positive impacts for air quality due to a dramatic reduction of economic activity and atmospheric emissions. In this work, a machine learning approach was designed and implemented to analyze local air quality improvements during the COVID-19 lockdown in Graz, Austria. The machine learning approach was used as a robust alternative to simple, historical measurement comparisons for various individual pollutants. Concentrations of NO₂ (nitrogen dioxide), PM₁₀ (particulate matter), O₃ (ozone) and Oₓ (total oxidant) were selected from five measurement sites in Graz and were set as target variables for random forest regression models to predict their expected values during the city’s lockdown period. The true vs. expected difference is presented here as an indicator of true pollution during the lockdown. The machine learning models showed a high level of generalization for predicting the concentrations. Therefore, the approach was suitable for analyzing reductions in pollution concentrations. The analysis indicated that the city’s average concentration reductions for the lockdown period were: -36.9 to −41.6%, and −6.6 to −14.2% for NO₂ and PM₁₀, respectively. However, an increase of 11.6–33.8% for O₃ was estimated. The reduction in pollutant concentration, especially NO₂ can be explained by significant drops in traffic-flows during the lockdown period (−51.6 to −43.9%). The results presented give a real-world example of what pollutant concentration reductions can be achieved by reducing traffic-flows and other economic activities.

Sodium percarbonate (SPC, 2Na₂CO₃∙3H₂O₂), is a compound that can be used under multiple environmental applications. In this work, SPC was employed as oxidant in the treatment of soil contaminated with diesel oil. The soil samples were collected during the earthmoving stage of RNEST Oil Refinery (Petrobras), Brazil. Then, the samples were air-dried, mixed and characterized. Subsequently, raw soil was contaminated with diesel and treated by photo-Fenton reaction (H₂O₂/Fe²⁺/UV). SPC played a significant role in the generation of hydroxyl radicals under the catalytic effect of ferrous ions (Fe²⁺), hydrogen peroxide (H₂O₂) and radiation. These radicals provoked the photodegradation of polycyclic aromatic hydrocarbons (PAHs), in the soil remediation. A factorial design 3³ was carried out to assess the variables which most influenced the decrease in total organic carbon (TOC). The study was performed with the following variables: initial concentration of [H₂O₂] and [Fe²⁺], between 190.0 and 950.0 mmol L⁻¹ and 0.0–14.4 mmol L⁻¹, respectively. UV radiation was supplied from sunlight, blacklight lamps, and system without radiation. All experiments were performed with 5.0 g of contaminated soil in 50.0 mL of solution. The initial concentration of Fe²⁺ showed the statistically most significant effect. The oxidation efficiency evaluated in the best condition showed a decrease from 34,765 mg kg⁻¹ to 15,801 mg kg⁻¹ in TOC and from 85.750 mg kg⁻¹ to 20.770 mg kg⁻¹ in PAHs content. Moreover, the sums of low and high molecular weight polycyclic aromatic hydrocarbons (LMW-PAHs and HMW-PAHs) were 19.537 mg kg⁻¹ and 1.233 mg kg⁻¹, respectively. Both values are within the limits recommended by the United Sates Environmental Protection Agency (USEPA) and evidenced the satisfactory removal of PAHs from contaminated soil, being an alternative to classic oxidation protocols.

Ozone (O₃) is a potent oxidant associated with adverse health effects. Low-cost O₃ sensors, such as metal oxide (MO) sensors, can complement regulatory O₃ measurements and enhance the spatiotemporal resolution of measurements. However, the quality of MO sensor data remains a challenge. The University of Utah has a network of low-cost air quality sensors (called AirU) that primarily measures PM₂.₅ concentrations around the Salt Lake City valley (Utah, U.S.). The AirU package also contains a low-cost MO sensor ($8) that measures oxidizing/reducing species. These MO sensors exhibited excellent laboratory response to O₃ although they exhibited some intra-sensor variability. Field performance was evaluated by placing eight AirUs at two Division of Air Quality (DAQ) monitoring stations with O₃ federal equivalence methods for one year to develop long-term multiple linear regression (MLR) and artificial neural network (ANN) calibration models to predict O₃ concentrations. Six sensors served as train/test sets. The remaining two sensors served as a holdout set to evaluate the applicability of the new calibration models in predicting O₃ concentrations for other sensors of the same type. A rigorous variable selection method was also performed by least absolute shrinkage and selection operator (LASSO), MLR and ANN models. The variable selection indicated that the AirU’s MO oxidizing species and temperature measurements and DAQ’s solar radiation measurements were the most important variables. The MLR calibration model exhibited moderate performance (R² = 0.491), and the ANN exhibited good performance (R² = 0.767) for the holdout set. We also evaluated the performance of the MLR and ANN models in predicting O₃ for five months after the calibration period and the results showed moderate correlations (R²s of 0.427 and 0.567, respectively). These low-cost MO sensors combined with a long-term ANN calibration model can complement reference measurements to understand geospatial and temporal differences in O₃ levels.

Di-(2-ethylhexyl) phthalate (DEHP) has been classified as a priority pollutant which increased the healthy risk to human and animals dramatically. Hence, a novel biochemical system combined by DEHP-resistant bacterial flora (B) and a green oxidant of persulfate (PS) activated by Nano-Fe₃O₄ was applied to degrade DEHP in contaminated soil. In this study, the resistant bacterial flora was screened from activated sludge and immobilized by sodium alginate (SAB). Nano-Fe₃O₄ was coated on biochar (BC@Fe₃O₄) to prevent agglomerating in soil. X-ray diffraction (XRD) and scanning electron microscope (SEM) were utilized to characterize BC@Fe₃O₄. Results demonstrated that the treatment of biochemical system (SAB + BC@Fe₃O₄ + PS) presented the maximum degradation rate about 92.56% within 24 days of incubation and improved soil microecology. The 16S rDNA sequences analysis of soil microorganisms showed a significantly different abundance and a similar diversity among different treatments. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional genes difference analysis showed that some metabolic pathways, such as metabolism of cofactors and vitamins, energy metabolism, cell growth and death, replication and repair, were associated with the biodegradation of DEHP. Besides, DEHP was converted to MEHP and PA by biodegradation, while DEHP was converted to DBP and PA by persulfate and BC@Fe₃O₄, and then ultimately degraded to CO₂ and H₂O.

Disinfection byproducts (DBPs) generated by ballast water treatment have become a concern worldwide because of their potential threat to the marine environment. Predicting the relative DBP concentrations after disinfection could enable better control of DBP formation. However, there is no appropriate method of evaluating DBP formation in a full-scale ballast water treatment system (BWTS). In this study, multiple regression models were developed for predicting the dibromochloromethane (DBCM) and bromoform (TBM) concentrations produced by an emergency BWTS using field experimental data from ballast water treatments conducted at Dalian Port, China. Six combinations of independent variables [including several water parameters and/or the total residual oxidant (TRO) concentration] were evaluated to construct mathematical prediction formulas based on a polynomial linear model and logarithmic regression model. Further, statistical analyses were performed to verify and determine the appropriate mathematical models for DBCM and TBM formation, which were ultimately validated using additional field experimental data. The polynomial linear model with four variables (temperature, salinity, chlorophyll, and TRO) and the logarithmic regression model with seven variables (temperature, salinity, dissolved oxygen, pH, turbidity, chlorophyll, and TRO) exhibited good reproducibility and could be used to predict the DBCM and TBM concentrations, respectively. The validation results indicated that the developed models could accurately predict DBP concentrations, with no significant statistical difference from the measured values. The results of this work could provide a theoretical basis and data reference for ballast water treatment control in engineering applications of emergency BWTSs.

This work evaluates the degradation of benzoic acid, a tracer from biomass burning, by different oxidation agents (Fe (III); H₂O₂; sunlight; and combinations of the previous ones) in model solutions and in real atmospheric waters. The extent of reactions was assessed by Ultraviolet–Visible and molecular fluorescence spectroscopies. The oxidation of benzoic acid occurred with the chemical oxidants Fe (III), H₂O₂, Fe (III) and H₂O₂ simultaneously in the presence of sunlight, and with Fe (III) and H₂O₂ simultaneously in the absence of light. The decrease of the pH value from neutral to acid for atmospheric waters generally increased the extent of oxidation. Sunlight was an important oxidation agent, and its combination with chemical oxidants increased the oxidation rate of benzoic acid, possibly due to the photogeneration of hydroxyl radicals. The results also suggested the occurrence of direct and indirect photolysis of benzoic acid in atmospheric waters. Moreover, the oxidation of benzoic acid produced new and more complex chromophoric compounds, which were then degraded. In addition, the nocturnal period is not sufficient for the full degradation of benzoic acid and of the intermediates formed by Fenton-like oxidation. The diurnal period may be enough for their full degradation through photo-Fenton-like oxidation, but this depends on the composition of the atmospheric waters, namely of the chromophoric content. Thus, this study highlights that benzoic acid from biomass burning, and its derivatives, may persist in atmospheric waters for periods of longer than one day, becoming available for other reactions, and may also affect the terrestrial and aquatic ecosystems through the wet depositions.