Pollutants in real aquatic systems commonly occur as chemical mixtures. Yet, the corresponding risk assessment is still mostly based on information on single-pollutant toxicity, accepting the assumption that pollutant mixtures exhibit additive toxicity effect which is often not the case. Therefore, it is still better to use the experimental approach. Unfortunately, experimental determination of toxicity for each mixture is practically unfeasible. In this study, quantitative structure-activity relationship (QSAR) models for the prediction of toxicity of binary mixtures towards bioluminescent bacteria Vibrio fischeri were developed at three toxicity levels (EC₁₀, EC₃₀ and EC₅₀). For model development, experimentally determined toxicity values of 14 pollutants (pharmaceuticals and pesticides) were correlated with their structural features, applying multiple linear regression together with genetic algorithm. Statistical analysis, internal validation and external validation of the models were carried out. The toxicity is accurately predicted by all three models. EC₃₀ and EC₅₀ values are mostly influenced by geometrical distances between nitrogen and sulfur atoms. Furthermore, the simultaneous presence of oxygen and chlorine atoms in mixture can induce the increase in toxicity. At lower effect levels (EC₁₀), nitrogen atom bonded to different groups has the highest impact on mixture toxicity. Thus, the analysis of the descriptors involved in the developed models can give insight into toxic mechanisms of the binary systems.

Subsurface wastewater infiltration systems (SWISs) have been widely used to treat rural domestic sewage. However, the low nitrogen removal and severe clogging problem always restrict the sustainability of SWISs for wastewater treatment. This study investigated the effects of aeration and biochar on the accumulation of nutrients and dissolved organic matter (DOM) in the substrate of loess soil-based SWISs for understanding the accumulation characteristics of DOM and the enhanced decontamination mechanism. The results showed that biochar addition could not improve the accumulation of nitrogen and phosphorus in the substrate, but could enhance denitrification (22%) via providing sufficient carbon for microorganisms. Moreover, the accumulation of organic matter in the substrate was also greatly affected. The DOM concentration of System D in the 40–60 cm layer reached 85.76 mg L⁻¹, which indicated that biochar could release abundant DOM. Substrate DOM mainly contained humic acid-like and tryptophan-like substances. Moreover, the refractory macromolecular DOM components with high aromaticity and humification were found in the substrate below 60 cm of systems with biochar addition. This may be related to the DOM released by biochar and the extracellular polymeric substance (EPS) produced by microorganisms. It may affect the sustainability of the substrate to a certain extent, but fortunately that intermittent aeration could reduce this adverse effect. This research could provide new insights for preventing clogging and useful guidance for improving wastewater treatment performance in SWISs.

The anaerobic digestion of wastewater rich in volatile fatty acids (VFAs) provides a sustainable approach for methane production whilst reducing environmental pollution. However, the anaerobic digestion of VFAs may not be stable during long-term operation under a short hydraulic retention time. In this study, conductive carbon cloth was supplemented to investigate the impacts on the anaerobic digestion of VFAs in wastewater sourced from dark fermentation. The results demonstrated that the failure of anaerobic digestion could be avoided when carbon cloth was supplemented. In the stable stage, the methane production rate with carbon cloth supplementation was improved by 200–260%, and the chemical oxygen demand (COD) removal efficiency was significantly enhanced compared with that in the control without carbon cloth. The relative abundance of potential exoelectrogens on the carbon cloth was increased by up to 8-fold compared with that in the suspension. Electrotrophic methanogens on the carbon cloth were enriched by 4.2–17.2% compared with those in the suspension. The genera Ercella and Petrimonas along with the methanogenic archaea Methanosaeta and Methanosarcina on the carbon cloth may facilitate direct interspecies electron transfer, thereby enhancing methane production.

Ecological floating beds (EFBs) have become a superior method for treating secondary effluent from wastewater treatment plant. However, insufficient electron donor limited its denitrification efficiency. Iron scraps from lathe cutting waste consist of more than 95% iron could be used as electron donors to enhance denitrification. In this study, EFBs with and without iron scraps supplementation (EFB-Fe and EFB, respectively) were conducted to explore the impacts of iron scraps addition on nitrogen removal, nitrous oxide (N₂O) emissions and microbial communities. Results showed the total nitrogen (TN) removal in EFB-Fe improved to 79% while that in EFB was 56%. N₂O emission was 0–6.20 mg m⁻² d⁻¹ (EFB-Fe) and 1.74–15.2 mg m⁻² d⁻¹ (EFB). Iron scraps could not only improve nitrogen removal efficiency, but also reduce N₂O emissions. In addition, high-throughput sequencing analysis revealed that adding iron scraps could improve the sum of denitrification related genera, among which Novosphingobium accounted for the highest proportion (6.75% of PFe1, 4.24% of PFe2, 3.18% of PFe3). Iron-oxidizing bacteria and iron-respiring bacteria associated with and nitrate reducing bacteria mainly concentrated on the surface of iron scraps. Principal co-ordinates analysis (PCoA) indicated that iron scraps were the key factor affecting microbial community composition. The mechanism of iron scraps enhanced nitrogen removal was realized by enhanced biological denitrification process. Iron release dynamic from iron scraps was detected in bench-scale experiment and the electron transfer mechanism was that Fe⁰ transferred electrons directly to NO₃⁻-N, and biological iron nitrogen cycle occurred in EFB-Fe without secondary pollution.

This study investigates changes in air quality conditions during the restricted COVID-19 lockdown period in 2020 across 21 metropolitan areas in the Middle East and how these relate to surface urban heat island (SUHI) characteristics. Based on satellite observations of atmospheric gases from Sentinel-5, results indicate significant reductions in the levels of atmospheric pollutants, particularly nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). Air quality improved significantly during the middle phases of the lockdown (April and May), especially in small metropolitan cities like Amman, Beirut, and Jeddah, while it was less significant in “mega” cities like Cairo, Tehran, and Istanbul. For example, the concentrations of NO₂ in Amman, Beirut, and Jeddah decreased by −56.6%, −43.4%, and −32.3%, respectively, during April 2020, compared to April 2019. Rather, there was a small decrease in NO₂ levels in megacities like Tehran (−0.9%) and Cairo (−3.1%). Notably, during the lockdown period, there was a decrease in the mean intensity of nighttime SUHI, while the mean intensity of daytime SUHI experienced either an increase or a slight decrease across these locations. Together with the Gulf metropolitans (e.g. Kuwait, Dubai, and Muscat), the megacities (e.g. Tehran, Ankara, and Istanbul) exhibited anomalous increases in the intensity of daytime SUHI, which may exceed 2 °C. Statistical relationships were established to explore the association between changes in the mean intensity and the hotspot area in each metropolitan location during the lockdown. The findings indicate that the mean intensity of SUHI and the spatial extension of hotspot areas within each metropolitan had a statistically significant negative relationship, with Pearson's r values generally exceeding - 0.55, especially for daytime SUHI. This negative dependency was evident for both daytime and nighttime SUHI during all months of the lockdown. Our findings demonstrate that the decrease in primary pollutant levels during the lockdown contributed to the decrease in the intensity of nighttime SUHIs in the Middle East, especially in April and May. Changes in the characteristics of SUHIs during the lockdown period should be interpreted in the context of long-term climate change, rather than just the consequence of restrictive measures. This is simply because short-term air quality improvements were insufficient to generate meaningful changes in the region's urban climate.

The present study provides an environmental risk assessment of the pharmaceutical mixtures detected in Brazilian surface waters, based on Toxic Units and Risk Quotients. Furthermore, the applicability of a previously proposed prioritization methodology was evaluated. The pharmaceuticals were classified according to their properties (occurrence, persistence, bioaccumulation, and toxicity) and the contribution of the prioritized compounds to the mixture risk was determined. The mixture risk quotients, based on acute and chronic toxicity data, often exceed 1, demonstrating a potential risk for the environment. While algae were most affected by acute effects, fish were the most sensitive organism to sublethal effects. The lipid regulator atorvastatin was the main driver for the mixture risk. Despite their lower occurrence, the antibiotics norfloxacin and enrofloxacin were critical compounds for the algae group. The prioritized pharmaceuticals contributed to more than 75% of the mixture risk in most of cases, indicating the applicability of prioritization approaches for risk management.

Air pollution is an important risk factor for autoimmune diseases, but its association with the recurrence of rheumatoid arthritis (RA) remains unclear so far. This study aimed to investigate the short-term association between traffic-related air pollutants and hospital readmissions for RA in Hefei, China. Data on daily hospital readmissions for RA and traffic-related air pollutants, including particulate matter (PM₂.₅ and PM₁₀), nitrogen dioxide (NO₂), and carbon monoxide (CO), from 2014 to 2018 were retrieved. A time-series approach using generalized linear regression model was employed. The analysis was further stratified by sex, age and season. A total of 1153 readmissions for RA were reported during the study period. A significant association between high-concentration PM₂.₅ (90th percentile) and RA readmissions was observed on lag1 (relative risk (RR) = 1.09, 95% confidence interval (CI): 1.01–1.19) and lasted until lag3 (RR = 1.06, 95%CI: 1.01–1.12). From lag2 to lag5, high-concentration NO₂ (90th percentile) was associated with increased risk of RA readmissions, with the highest RR observed at lag 4 (1.11, 95%CI: 1.05–1.17). Stratified analyses indicated that females and the elderly appeared to be more vulnerable to high-concentration PM₂.₅ and NO₂ exposure. High-concentration PM₂.₅ and NO₂ in cold seasons were consistently significantly associated with increased risk of RA readmissions. Exposure to high-concentration PM₂.₅ and NO₂ was associated with increased risk of RA readmissions. Protective measures against the exposure to high-concentration PM₂.₅ and NO₂ should be taken to reduce the recurrence risk in RA patients, especially in females, the elderly and during cold seasons.

In this study, the occurrence of aflatoxins (AFs), fumonisins (FBs), ochratoxin A (OTA), deoxynivalenol (DON), zearalenone (ZEN) and some of their metabolites were assessed in breast milk and urine of lactating women (N = 74) from Pirassununga, São Paulo, Brazil. Exposure estimations through urinary mycotoxin biomarkers was also performed. Samples were collected in four sampling times (May and August 2018, February and July 2019) and analyzed by liquid chromatography coupled to tandem mass spectrometry. Aflatoxin M₁ (AFM₁) was not detected in breast milk. However, two samples (3%) presented FB₁ at 2200 and 3400 ng/L, while 4 samples (5%) had OTA at the median level of 360 ng/L. In urine, AFM₁ and aflatoxin P₁ (AFP₁) were found in 51 and 11% of samples, respectively (median levels: 0.16 and 0.07 ng/mg creatinine, respectively). Urinary DON (median level: 38.59 ng/mg creatinine), OTA (median level: 2.38 ng/mg creatinine) and ZEN (median level: 0.02 ng/mg of creatinine) were quantified in 18, 8 and 10% of the samples, respectively. Mean probable daily intake (PDI) values based on urinary biomarkers were 1.58, 1.09, 5.07, and 0.05 μg/kg body weight/day for AFM₁, DON, OTA, and ZEN, respectively. Although a low mycotoxin occurrence was detected in breast milk, the PDI for the genotoxic AFs was much higher than those reported previously in Brazil, while PDI values obtained for OTA and DON were higher than recommended tolerable daily intakes. These outcomes warrant concern on the exposure of lactating women to these mycotoxins in the studied area.

Prorocentrum lima is a dinoflagellate that forms hazardous blooms and produces okadaic acid (OA), leading to adverse environmental consequences associated with the declines of zooplankton populations. However, little is known about the toxic effects and molecular mechanisms of P. lima or OA on zooplankton. Here, their toxic effects were investigated using the brine shrimp Artemia salina. Acute exposure of A. salina to P. lima resulted in lethality at concentrations 100-fold lower than densities observed during blooms. The first comprehensive results from global transcriptomic and metabolomic analyses in A. salina showed up-regulated mRNA expression of antioxidant enzymes and reduced non-enzyme antioxidants, indicating general detoxification responses to oxidative stress after exposure to P. lima. The significantly up-regulated mRNA expression of proteasome, spliceosome, and ribosome, as well as the increased fatty acid oxidation and oxidative phosphorylation suggested the proteolysis of damaged proteins and induction of energy expenditure. Exposure to OA increased catabolism of chitin, which may further disrupt the molting and reproduction activities of A. salina. Our data shed new insights on the molecular responses and toxicity mechanisms of A. salina to P. lima or OA. The simple zooplankton model integrated with omic methods provides a sensitive assessment approach for studying hazardous algae.