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.

Both amphibian metamorphosis assay (AMA) and larval amphibian growth and development assay (LAGDA) can detect thyroid-mediated modality and adversity on the basis of morphological changes during the thyroid hormone-dependent metamorphosis. They are used for identification of thyroid hormone system disrupting chemicals (TDCs) for non-target organisms or the environment. The EU Guidance recommends that the AMA and the LAGDA should be used to address sufficient investigation of the thyroid-mediated modality and adversity, respectively. In the EU discussions over identification of TDCs, the necessity of using LAGDA as a follow-up of positive results of the AMA has been questioned because of the overlap between the endpoints and the exposure of both tests. This study analyzed similarities, differences, and sensitivity of these two assays in detection of TDCs. For agonists and most of antagonists of the hypothalamic-pituitary-thyroid (HPT) axis, both AMA and LAGDA can detect the thyroid-mediated modality and adversity. The LAGDA, as a follow-up of the positive results of the AMA, may not be needed because the results of AMA are considered enough for identification of TDCs. For chemicals like inhibitors of iodotyrosine deiodinase, the LAGDA is considered necessary for identification of TDCs because the thyroid-mediated adversity cannot be detected until Nieuwkoop and Faber (NF) stage 62. Incorporation of mechanistic endpoints into existing test guidelines and the use of Xenopus Eleutheroembryo Thyroid Assay (XETA), extended amphibian metamorphosis assay (EAMA) and adverse outcome pathways (AOPs) for testing and identification of TDCs are further discussed.

Microcystis blooms pose a major threat to the quality of drinking water. Cyanobactericidal bacteria have attracted much attention in the research community as a vehicle for controlling Microcystis blooms because of their ecological safety. Nonetheless, most studies on cyanobactericidal bacteria have been conducted on a laboratory scale but have not been scaled-up as field experiments. Thus, our understanding of the microbial response to cyanobactericidal bacteria in natural ecosystems remains elusive. Herein, we applied Paucibacter aquatile DH15 to control Microcystis blooms in a 1000 L mesocosm experiment and demonstrated its potential with the following results: (1) DH15 reduced Microcystis cell density by 90.7% within two days; (2) microcystins released by Microcystis death decreased to the control level in four days; (3) during the cyanobactericidal processes, the physicochemical parameters of water quality remained safe for other aquatic organisms; and (4) the cyanobactericidal processes promoted the growth of eukaryotic microalgae, replacing cyanobacteria. The cyanobactericidal processes accelerated turnover rates, decreased stability, and altered the functional profile of the microbial community. Network analysis demonstrated that this process resulted in more complex interactions between microbes. Overall, our findings suggest that strain DH15 could be considered a promising candidate for controlling Microcystis blooms in an eco-friendly manner.

Silicon is absorbed as uncharged mono-silicic acid by plant roots through passive absorption of Lsi1, an influx transporter belonging to the aquaporin protein family. Lsi2 then actively effluxes silicon from root cells towards the xylem from where it is exported by Lsi6 for silicon distribution and accumulation to other parts. Recently, it was proposed that silicon nanoparticles (SiNPs) might share a similar route for their uptake and transport. SiNPs then initiate a cascade of morphophysiological adjustments that improve the plant physiology through regulating the expression of many photosynthetic genes and proteins along with photosystem I (PSI) and PSII assemblies. Subsequent improvement in photosynthetic performance and stomatal behaviour correspond to higher growth, development, and productivity. On many occasions, SiNPs have demonstrated a protective role during stressful environments by improving plant-water status, source-sink potential, reactive oxygen species (ROS) metabolism, and enzymatic profile. The present review comprehensively discusses the crop improvement potential of SiNPs stretching their role during optimal and abiotic stress conditions including salinity, drought, temperature, heavy metals, and ultraviolet (UV) radiation. Moreover, in the later section of this review, we offered the understanding that most of these upgrades can be explained by SiNPs intricate correspondence with phytohormones, antioxidants, and signalling molecules. SiNPs can modulate the endogenous phytohormones level such as abscisic acid (ABA), auxins (IAAs), cytokinins (CKs), ethylene (ET), gibberellins (GAs), and jasmonic acid (JA). Altered phytohormones level affects plant growth, development, and productivity at various organ and tissue levels. Similarly, SiNPs regulate the activities of catalase (CAT), ascorbate peroxidase (APX), superoxide dismutase (SOD), and ascorbate-glutathione (AsA-GSH) cycle leading to an upgraded defence system. At the cellular and subcellular levels, SiNPs crosstalk with various signalling molecules such as Ca²⁺, K⁺, Na⁺, nitric oxide (NO), ROS, soluble sugars, and transcription factors (TFs) was also explained.

Green tide outbreaks caused by overgrowth of Ulva prolifera in the Yellow Sea of China can cause serious ecological stress with concomitant economic hardships, especially to marine fisheries. In this study, short-term effects (14 days) were evaluated using fresh algae U. prolifera (FU), and a 7-day assessment of the effects of decomposing U. prolifera (DU) algal effluent was conducted to determine the effects on the environmental and intestinal microbiota, intestinal transcriptome and mortality of the commercial marine benthic fish, Japanese flounder (Paralichthys olivaceus). The results revealed that algal degradation altered the microbial community structure of fish farm water and fish intestines and increased the relative abundance of the pathogens Flavobacteriaceae in water and Vibrio in fish intestines. Fish intestinal tissue structure appeared to be damaged, as indicated in pathological sections, and transcriptome analysis showed intestinal inflammation after exposure, which may have caused an increase in fish mortality. The degradation of U. prolifera led to a bloom of potential pathogenic bacteria and the inflammation of fish intestines, which resulted in disease in the flounder population that reduced fish harvests and might pose a potential health threat.

The growth and development patterns of crop plants are being seriously threatened by arsenic (As) contamination in the soil, and it also acts as a major hurdle in crop productivity. This study focuses on arsenate As(V) mediated toxicity in rice plants. Further, among the different type of NPs, iron oxide nanoparticles (FeO NPs) display a dose-dependent effect but their potential role in mitigating As(V) stress is still elusive. FeO NPs (500 μM) play a role in imparting cross-tolerance against As(V) induced toxicity in rice. Growth attributes, photosynthetic performance, nutrient contents and biochemical parameters were significantly altered by As(V). But FeO NPs rescued the negative consequences of As(V) by restricting its entry with the possible involvement of NO in rice roots. Moreover, results related with gene expression of NO(OsNoA1 and OsNIA1) and proline metabolism were greatly inhibited by As(V) toxicity. But, FeO NPs reversed the toxic effect of As(V) by improving proline metabolism and stimulating NO mediated up-regulation of antioxidant enzymes particularly glutathione-S-transferase which may be possible reasons for the reduction of As(V) toxicity in rice roots. Overall, it can be stated that FeO NPs may act as an As(V) barrier to restrict the As(V) uptake by roots and have the ability to confer cross tolerance by modulating various morphological, biochemical and molecular characteristics with possible intrinsic involvement of NO.

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.

Soil chemistry of toxic metalloids and metals differs, making their simultaneous removal difficult. Soil contaminated with As, Pb, Zn and Cd was washed with oxalic acid, Na-dithionite and EDTA solution. Toxic elements were removed from the washing solution by alkalinisation with CaO to a pH 12.5: As was co-precipitated with Fe from Fe-EDTA chelate formed after the soil washing. The toxic metals precipitated after substitution of their EDTA chelates with Ca. The novel method was scaled up on the ReSoil® platform. On average, 60, 76, 29, and 53% of As, Pb, Zn, and Cd were removed, no wastewater was generated and EDTA was recycled. Addition of zero-valent iron reduced the toxic elements’ leachability. Remediation was most effective for As: phytoaccessibility (CaCl₂ extraction), mobility (NH₄NO₃), and accessibility from human gastric and gastrointestinal phases were reduced 22, 104, 6, and 51 times, respectively. Remediation increased pH but had no effect on soil functioning assessed by fluorescein diacetate hydrolysis, dehydrogenase, β-glucosidase, urease, acid and alkaline phosphatase activities. Brassica napus produced 1.9 times more biomass on remediated soil, accumulated no As and 5.0, 2.6, and 9.0 times less Pb, Zn and Cd, respectively. We demonstrated the novel remediation technology as cost-efficient (material cost = 41.86 € t⁻¹) and sustainable.