Brominated flame retardants (BFRs) are an important group of additives in plastics that increase resistance to ignition and slow down the rate of burning. Because of concerns about their environmental and human health impacts, however, some of the most widely employed BFRs, including hexabromocyclododecane (HBCD) and commercial mixtures of penta-, octa- and deca- (poly)bromodiphenyl ethers (PBDEs), have been restricted or phased out. In this review, the oceanic sources and pathways of PBDEs, the most widely used BFRs, are evaluated and quantified, with particular focus on emissions due to migration from plastics into the atmosphere versus emissions associated with the input of retarded or contaminated plastics themselves. Calculations based on available measurements of PBDEs in the environment suggest that 3.5 and 135 tonnes of PBDEs are annually deposited in the ocean when scavenged by aerosols and through air-water gas exchange, respectively, with rivers contributing a further ∼40 tonnes. Calculations based on PBDE migration from plastic products in use or awaiting or undergoing disposal yield similar net inputs to the ocean but indicate a relatively rapid decline over the next two decades in association with the reduction in the production and recycling of these chemicals. Estimates associated with the input of PBDEs to the ocean when “bound” to marine plastics and microplastics range from about 360 to 950 tonnes per year based on the annual production of plastics and PBDEs over the past decade, and from about 20 to 50 tonnes per annum based on the abundance and distribution of PBDEs in marine plastic litter. Because of the persistence and pervasiveness of plastics in the ocean and diffusion coefficients for PBDEs on the order of 10⁻²⁰ to 10⁻²⁷ m² s⁻¹, microplastics are likely to act as a long-term source of these chemicals though gradual migration. Locally, however, and more important from an ecotoxicological perspective, PBDE migration may be significantly enhanced when physically and chemically weathered microplastics are exposed to the oily digestive fluids conditions of fish and seabirds.

This study aimed to evaluate the impact factors and effectiveness of management policies on the presence of polybrominated diphenyl ethers (PBDEs) in sediment samples in Taiwan from the last 10 years. Twenty-four PBDE congeners were detected in 838 sediment samples collected from 4 stages (2006–2019) in 30 principal rivers, based on the national project for background monitoring of the environmental distribution of chemical substances. The ΣPBDE concentrations in the 4 stages ranged from 30.00 to 147.10 ng/g dw, 6.03–15.30 ng/g dw, 4.99–7.00 ng/g dw, and 1.20–2.10 ng/g dw in the northern, southern, central, and eastern areas, respectively. The concentrations of PBDEs (e.g., penta-BDE and octa-BDE) in sediment samples notably decreased (−6 to −73%) as the Taiwan Environmental Protection Administration implemented policies banning PBDEs (except deca-BDE). The PBDEs levels of the sediment samples collected in the dry season were higher than those collected in the wet season. The levels of ΣPBDEs in sediment samples were affected by season, the amount of general waste present, and nearby PBDE-related factories and e-waste recycling facilities. Reducing the release of PBDEs, especially deca-BDE, through sound waste management and recycling practices is still needed to improve environmental sustainability in Taiwan.

Synthetic microfibers have been identified as the most prevalent type of microplastic in samples from aquatic, atmospheric, and terrestrial environments across the globe. Apparel washing has shown to be a major source of microfiber pollution. We used California as a case study to estimate the magnitude and fate of microfiber emissions, and to evaluate potential mitigation approaches. First, we quantified synthetic microfiber emissions and fate from apparel washing in California by developing a material flow model which connects California-specific data on synthetic fiber consumption, apparel washing, microfiber generation, and wastewater and biosolid management practices. Next, we used the model to assess the effectiveness of different interventions to reduce microfiber emissions to natural environments. We estimate that in 2019 as much as 2.2 kilotons (kt) of synthetic microfibers were generated by apparel washing in California, a 26% increase since 2008. The majority entered terrestrial environments (1.6 kt), followed by landfills (0.4 kt), waterbodies (0.1 kt), and incineration (0.1 kt). California's wastewater treatment network was estimated to divert 95% of microfibers from waterbodies, mainly to terrestrial environments and primarily via land application of biosolids. Our analysis also reveals that application of biosolids on agricultural lands facilitates a directional flow of microfibers from higher-income urban counties to lower-income rural communities. Without interventions, annual synthetic microfiber emissions to California's natural environments are expected to increase by 17% to 2.1 kt by 2026. Further increasing the microfiber retention efficiency at the wastewater treatment plant would increase emissions to terrestrial environments, which suggests that microfibers should be removed before entering the wastewater system. In our model, full adoption of in-line filters in washing machines decreased annual synthetic microfiber emissions to natural environments by 79% to 0.5 kt and offered the largest reduction of all modeled scenarios.

Facing billions of tons of pollutants entering the ocean each year, aquatic toxicity is becoming a crucial endpoint for evaluating chemical adverse effects on ecosystems. Notably, huge amount of toxic chemicals at environmental relevant doses can cause potential adverse effects. However, chronic aquatic toxicity effects of chemicals are much scarcer, especially at population level. Rotifers are highly sensitive to toxicants even at chronic low-doses and their communities are usually considered as effective indicators for assessing the status of aquatic ecosystems. Therefore, the no observed effect concentration (NOEC) for population abundance of rotifers were selected as endpoints to develop machine learning models for the prediction of chemical aquatic chronic toxicity. In this study, forty-eight binary models were built by eight types of chemical descriptors combined with six machine learning algorithms. The best binary model was 1D & 2D molecular descriptors – random trees model (RT) with high balanced accuracy (BA) (0.83 for training and 0.83 for validation set), and Matthews correlation coefficient (MCC) (0.72 for training set and 0.67 for validation set). Moreover, the optimal model identified the primary factors (SpMAD_Dzp, AMW, MATS2v) and filtered out three high alerting substructures [c1cc(Cl)cc1, CNCO, CCOP(=S)(OCC)O] influencing the chronic aquatic toxicity. These results showed that the compounds with low molecular volume, high polarity and molecular weight could contribute to adverse effects on rotifers, facilitating the deeper understanding of chronic toxicity mechanisms. In addition, forecast models had better performances than the common models embedded into ECOSAR software. This study provided insights into structural features responsible for the toxicity of different groups of chemicals and thereby allowed for the rational design of green and safer alternatives.

Decision Support System (DSS) is a novel approach for smart, sustainable controlling of environmental phenomena and purification processes. Toluene is one of the most widely used petroleum products, which adversely impacts on human health. In this study, Fusarium Solani fungi are utilized as the engine of the toluene bioremediation procedure for the monitoring part of DSS. Experiments are optimized by Central Composite Design (CCD) - Response Surface Methodology (RSM), and the behavior of the mentioned fungi is estimated by M5 Pruned model tree (M5P), Gaussian Processes (GP), and Sequential Minimal Optimization (SMOreg) algorithms as the prediction section of DSS. Finally, the control stage of DSS is provided by integrated Petri Net modeling and Failure Modes and Effects Analysis (FMEA). The findings showed that Aeration Intensity (AI) and Fungi load/Biological Waste (F/BW) are the most influential mechanical and biological factors, with P-value of 0.0001 and 0.0003, respectively. Likewise, the optimal values of main mechanical parameters include AI, and the space between pipes (S) are equal to 13.76 m³/h and 15.99 cm, respectively. Also, the optimum conditions of biological features containing F/BW and pH are 0.001 mg/g and 7.56. In accordance with the kinetic study, bioremediation of toluene by Fusarium Solani is done based on a first-order reaction with a 0.034 s-1 kinetic coefficient. Finally, the machine learning practices showed that the GP (R2 = 0.98) and M5P (R2 = 0.94) have the most precision for predicting Removal Percentage (RP) for mechanical and biological factors, respectively. At the end of the present research, it is found that by controlling seven possible risk factors in bioremediation operation through the FMEA- Petri Net technique, efficiency of the process can be adjusted to optimum value.

The inorganic components of particulate matter (PM), especially transition metals, have been shown to contribute to PM toxicity. In this study, the spatial distribution of PM elements and their potential sources in the Greater Los Angeles area were studied. The mass concentration and detailed elemental composition of fine (PM₂.₅) and coarse (PM₂.₅₋₁₀) particles were assessed at 46 locations, including urban traffic, urban community, urban background, and desert locations. Crustal enrichment factors (EFs), roadside enrichments (REs), and bivariate correlation analysis revealed that Ba, Cr, Cu, Mo, Pd, Sb, Zn, and Zr were associated with traffic emissions in both PM₂.₅ and PM₂.₅₋₁₀, while Fe, Li, Mn, and Ti were affected by traffic emissions mostly in PM₂.₅. The concentrations of Ba, Cu, Mo, Sb, Zr (brake wear tracers), Pd (tailpipe tracer), and Zn (associated with tire wear) were higher at urban traffic sites than urban background locations by factors of 2.6–4.6. Both PM₂.₅ and PM₂.₅₋₁₀ elements showed large spatial variations, indicating the presence of diverse emission sources across sampling locations. Principal component analysis extracted four source factors that explained 88% of the variance in the PM₂.₅ elemental concentrations, and three sources that explained 86% of the variance in the PM₂.₅₋₁₀ elemental concentrations. Based on multiple linear regression analysis, the contribution of traffic emissions (27%) to PM₂.₅ was found to be higher than mineral dust (23%), marine aerosol (18%), and industrial emissions (8%). On the other hand, mineral dust was the dominant source of PM₂.₅₋₁₀ with 45% contribution, followed by marine aerosol (22%), and traffic emissions (19%). This study provides novel insight into the spatial variation of traffic-related elements in a large metropolitan area.

Although the utilization of biosolids in agricultural lands is widely considered as an effective way to improve resource reuse, the presence of antibiotic resistance genes (ARGs) severely restricts biosolids returning to fields. A 12-year long-term experiment with different biosolids application rates (from 0 to 36 t ha⁻¹ yr⁻¹) was conducted to study the effect of biosolids application on shaping ARGs in soil. Biosolids application significantly increased ARGs abundance in the soil, except for MBS treatment (9 t ha⁻¹ yr⁻¹ biosolids application). The abundance of ARGs in soil did not increase linearly with the dose of biosolids applied, but they were significantly (P < 0.05) positively correlated. A total of 173 subtypes were detected, among them mobile genetic elements (MGEs), aminoglycoside, and multidrug resistance genes were the most dominant types. Except for MBS treatment, most of the ARGs detected were enriched in amended soils after long-term continuous biosolids application. Specifically, tetPA, sul1, mefA, and IS6100 were highly enriched in all amended soils. In addition, biosolids application increased soil nutrients and heavy metals, and changed the soil microbial community, all of which affected ARGs formation. But MGEs may be a greater factor for shaping ARGs profiles than soil properties. Overall, controlling the rate of biosolid application is the key to reducing the accumulation and horizontal transfer of ARGs in soils.

Health effects of particulate matter (PM) from aircraft engines have not been adequately studied since controlled laboratory studies reflecting realistic conditions regarding aerosols, target tissue, particle exposure and deposited particle dose are logistically challenging. Due to the important contributions of aircraft engine emissions to air pollution, we employed a unique experimental setup to deposit exhaust particles directly from an aircraft engine onto reconstituted human bronchial epithelia (HBE) at air-liquid interface under conditions similar to in vivo airways to mimic realistic human exposure. The toxicity of non-volatile PM (nvPM) from a CFM56-7B26 aircraft engine was evaluated under realistic engine conditions by sampling and exposing HBE derived from donors of normal and compromised health status to exhaust for 1 h followed by biomarker analysis 24 h post exposure. Particle deposition varied depending on the engine thrust levels with 85% thrust producing the highest nvPM mass and number emissions with estimated surface deposition of 3.17 × 10⁹ particles cm⁻² or 337.1 ng cm⁻². Transient increase in cytotoxicity was observed after exposure to nvPM in epithelia derived from a normal donor as well as a decrease in the secretion of interleukin 6 and monocyte chemotactic protein 1. Non-replicated multiple exposures of epithelia derived from a normal donor to nvPM primarily led to a pro-inflammatory response, while both cytotoxicity and oxidative stress induction remained unaffected. This raises concerns for the long-term implications of aircraft nvPM for human pulmonary health, especially in occupational settings.

Magnetic carbon were synthesized from sugarcane bagasse using hydrothermal carbonization followed by thermal activation was converted to solid state as beads (hydrogels SACFe) using sodium alginate and applied as adsorbent in removal sulfamethoxazole in batch and column mode. From adsorption parameter analysis it was confirmed that 0.6 g L⁻¹ SACFe was effective in removing 50 mg L⁻¹ of SMX at pH 6.2. Sorption of SMX on SACFe beads followed Elovich kinetics and Freundlich isotherm. It was further confirmed that sorption occurred on heterogeneous surface of SACFe beads with chemisorption as rate limiting step. Maximum adsorption capacity was obtained as 58.439 mg g⁻¹ pH studies revealed that charged assisted hydrogen bonding, EDA interactions are some of the mechanism that favoured removal of SMX. From column studies it was found that bead height of 2 cm and flow rate of 1.5 mL min⁻¹ found to be best in removing pollutant. Thomas model fitted better the experimental data stating that improved interaction between adsorbent and adsorbate act as major driving force tool in obtaining maximum sorption capacity. Breakthrough curve was completely affected by varied flow rate and bed height. Column adsorption was effective in reducing COD and BOD levels of sewage which are affected by toxic pollutants and miscellaneous compounds. Feasibility analysis showed that SACFe beads could be employed for real-time applications as it is cost, energy effective and easy recovery.

Bacteria and their secreted extracellular polymeric substances (EPS) are widely distributed in ecosystems and have high capacity for heavy metal immobilization. The knowledge about the molecular-level interactions with heavy metal ions is essential for predicting the behavior of heavy metals in natural and engineering systems. This comprehensive study using potentiometric titration, Fourier-transform infrared (FTIR) spectroscopy, isothermal titration calorimetry (ITC) and X-ray absorption fine structure (XAFS) was able to reveal the functional diversity and adsorption mechanisms for Pb onto bacteira and the EPS in greater detail than ever before. We identified mono-carboxylic, multi-carboxylic, phosphodiester, phosphonic and sulfhydryl sites and found the partitioning of Pb to these functional groups varied between gram-negative and gram-positive bacterial strains, the soluble and cell-bound EPS and Pb concentrations. The sulfhydryl and phosphodiester groups preferentially complexed with Pb in P. putida cells, while multifunctional carboxylic groups promoted Pb adsorption in B. subtilis cells and the protein fractions in EPS. Though the functional site diversity, the adsorption of Pb to organic ligands occurred spontaneously through a universal entropy increase and inner-sphere complexation mechanism. The functional group scale knowledge have implications for the modeling of heavy metal behavior in the environment and application of these biological resources.