Quantifying methane (CH₄) emissions from paddy fields is essential for evaluating the environmental risks of the paddy rice production system, and improving the accuracy of CH₄ modeling is a key issue that needs to be addressed. Based on a database containing 835 field measurements, both single national and region-specific models were established to estimate CH₄ emissions from paddy fields considering different environmental factors and management patterns using 70% of the measurements. The remaining 30% of the measurements were then used for model evaluation. The performance of the region-specific model was better than that of the single national model. The region-specific model could simulate CH₄ emissions in an unbiased manner with R² values of 0.15–0.70 and efficiency values of 11–60%. The paddy rice type, water regime, organic amendment, latitude, and soil characteristics (pH and bulk density) were identified as the main drivers in the models. By inputting the high-resolution spatial data of these drivers into the established model, the CH₄ emissions from China’s paddy fields were estimated to be 4.75 Tg in 2015, with a 95% confidence interval of 4.19–5.61 Tg. The results indicated that establishing and driving a region-specific model with high-resolution data can improve the estimation accuracy of CH₄ emissions from paddy fields.

Antibiotics in the environment usually co-exist with their transformation products with retained toxicity, raising concerns about environmental risks of their combined exposure. Herein, we reported a novel predictive approach for evaluating the individual and combined toxicity for photodegradation products of fluoroquinolone antibiotics (FQs). Quantitative structure-activity relationship (QSAR) models with promising predictive performance were constructed and validated using experimental data obtained with 13 FQs and 78 mixtures towards E. coli. A structural descriptor reflecting the interaction among FQ molecules and the target protein was employed in the QSAR models, which was obtained through molecular docking and thus provided a rational mechanistic explanation for these models. The predicted results indicated that the degradation products displayed varying degrees of changes compared to the parent FQs, while the combined toxicity of FQs and their degradation products was mostly additive. Furthermore, following UV irradiation the degradation products displayed elevated capacity of inducing resistance mutations in E. coli, though their overall toxicity was reduced. This result highlights the implications of antibiotic degradation products on resistance development in bacteria and stresses the importance of considering such impacts during environmental risk assessments of antibiotics.

A substantial increase in the usage of organophosphate esters (OPEs) as flame retardants and plasticizers in rubbers, textiles, upholstered furniture, lacquers, plastics, building materials and electronic equipment has resulted in their increasing concentrations in the environment over time. However, little is known about the concentrations and fate of OPEs and their metabolites (mOPEs) in biota, including chicken eggs. The aim of this study was to understand the spatial variation in the concentrations in chicken eggs and the partitioning between yolk and albumin. In total, 153 chicken eggs were purchased across Australia and analysed for 9 OPEs and 11 mOPE. Most of the compounds were found to be deposited in egg yolk, where diphenyl phosphate (DPHP, 3.8 ng/g wet weight, median) and tris(2-chloroisopropyl) phosphate (TCIPP, 1.8 ng/g wet weight, median) were predominant mOPE and OPE, respectively. Moreover, no spatial differences in concentrations of OPEs and mOPEs in eggs purchased from different locations were found in this study. Although comparable levels of ∑OPEs were detected in egg yolk and albumin, much higher concentrations of ∑mOPEs were found in yolk than albumin. Meanwhile, a negative correlation (R² = 0.964, p = 0.018) was found between the molecular mass of analytes and partitioning coefficient of Cyₒₗₖ/Cyₒₗₖ₊ₐₗbᵤₘᵢₙ (defined as chemical concentration in egg yolk divided by the sum of chemical concentrations in both yolk and albumin). These results indicate that n-octanol/water partition coefficients (log KOW) may not be a crucial factor in the distribution of OPEs and mOPEs between egg yolk and albumin, which is important in understanding distribution of emerging organic contaminants in biota.

Environmental health is increasingly compromised by persistent toxic substances, which may have serious implications in food safety and, thus, in human health. Polybrominated diphenyl ethers (PBDEs) are anthropogenic contaminants with endocrine disruption abilities and are commonly found in seafood, the main route of human exposure. Growing evidence points out that the human gut microbiota interacts with xenobiotics, which may lead to impairment of host homeostasis if functions of microbiota become compromised. The aim of this study was to ascertain if the physiological balance of human gut microbiome is affected by the presence and degree of exposure to PBDEs. Fermentation was performed in a batch closed-system using an inoculum made from fresh human stool. The volatolomic profile was analysed by solid-phase microextraction coupled to gas chromatography-mass spectrometry. Mesophilic, Gram-negative bacteria and coliforms were quantified by classic plating methods. Changes in the gut microbiome were evaluated after DNA extraction followed by deep sequencing of the 16S rDNA region. The exposure to PBDEs resulted in an imbalance in sulfur, short-chain fatty acids and aromatic organic compounds, changing the microbial volatolome in a dose- and time-dependent manner. Slight deviations in the microbial structure of human gut occurred in the presence of PBDEs, especially for high doses of exposure. For the first time, the impact of PBDEs on the microbial homeostasis of human gut microbiota was taken into consideration, revealing noteworthy modifications with serious health implications even at oral exposure doses considered as safe by worldwide regulatory entities.

In predicting palm oil mill effluent (POME) degradation efficiency, previous developed quadratic model quantitatively evaluated the effects of O2 flowrate, TiO2 loadings and initial concentration of POME in labscale photocatalytic system, which however suffered from low generalization due to the overfitting behaviour. Evidently, high RMSE (131.61) and low R₂ (−630.49) obtained indicates its insufficiency in describing POME degradation at unseen factor ranges, hence verified the fact of poor generalization. To overcome this issue, several models were developed via machine learning-assisted techniques, namely Gaussian Process Regression (GPR), Linear Regression (LR), Decision Tree (DT), Supported Vector Machine (SVM) and Regression Tree Ensemble (RTE), subsequently being assessed systematically. To achieve high generalization, all models were subjected to ‘train-all-test-all’ strategy, 5-fold and 10-fold cross validation. Specifically, GPR model was furnished with high accuracy in ‘train-all-test-all’ strategy, judging from its low RMSE (1.0394) and high R₂ (0.9962), which however menaced by the risk of overfitting. In contrast, despite relatively poorer RMSE and R₂ (1.7964 and 0.9886) obtained in 5-fold cross validation, GPR model was rendered with highest generalization, while sufficiently preserving its accuracy in development process. Besides, SVM and RTE models were also demonstrated promising R₂ (0.9372 and 0.9208), which however shadowed by their high RMSEs (4.2174 and 4.7366). Furthermore, the extraordinary generalization of GPR model was coincidentally verified in 10-fold cross validation. The lowest RMSE (2.1624) and highest R₂ (0.9835) obtained with feature number of 36 asserted its sufficiency in both generalization and accuracy prospect. Other models were all rendered with slight lower R₂ (> 0.9), plausibly due to the higher RMSE (> 4.0). According to GPR model, optimized POME degradation (52.52%) can be obtained at 70 mL/min of O₂, 70.0 g/L of TiO₂ and 250 ppm of POME concentration, with only ∼3% error as compared to the actual data.

The use of polymers such as plastic has become an important part of daily life, and in aqueous environments, these polymers are considered as pollutants. When macropolymers are reduced to the nanoscale, their small particle size and large specific surface area facilitate their uptake by plants, which has a significant impact on aquatic plants. Therefore, it is essential to study the pollution of nanoscale polymers in the aquatic environment. In this work, we prepared nanoscale polymer dots (Pdots) and explored their toxicity, uptake and transport mechanisms in penny grass. From toxicological studies, in the absence of other nutrients, the cell structure, physiological parameters (total soluble protein and chlorophyll) and biochemical parameters (malondialdehyde) do not show significant changes over at least five days. Through in vivo fluorescence and photoacoustic (PA) imaging, the transport location can be visually detected accurately, and the transport rate can be analyzed without destroying the plants. Moreover, through ex vivo fluorescence imaging, we found that different types of Pdots have various uptake and transport mechanisms in stems and blades. It may be due to the differences in ligands, particle sizes, and oil-water partition coefficients of Pdots. By understanding how Pdots interact with plants, a corresponding method can be developed to prevent them from entering plants, thus avoiding the toxicity from accumulation. Therefore, the results of this study also provide the basis for subsequent prevention work.

Endocrine-disrupting chemicals (EDCs) are compounds that interfere with the expression, synthesis, and activity of hormones in organisms. They are released into the environment from flame retardants and products containing plasticizers. Persistent pesticides, such as dichlorodiphenyltrichloroethane (DDT) and hexachlorobenzene, also disrupt the endocrine system through interaction with hormone receptors. Endogenous hormones, such as 17β-estradiol (E2), are released in the urine and feces of farm animals and seep into terrestrial and aquatic ecosystems through sewage. Pigs are widely used as animal models to determine the effects of EDCs because they are physiologically, biochemically, and histologically similar to humans. EDCs primarily disrupt the reproductive and nervous systems of pigs. Moreover, embryonic development during the prenatal and early postnatal periods is particularly sensitive to EDCs. Mycotoxins, such as zearalenone, are food contaminants that alter hormonal activities in pigs. Mycotoxins also alter the innate immune system in pigs, making them vulnerable to diseases. It has been reported that farm animals are exposed to various types of EDCs, which accumulate in tissues, such as those of gonads, livers, and intestines. There is a lack of an integrated understanding of the impact of EDCs on porcine reproduction and development. Thus, this article aims to provide a comprehensive review of literature regarding the effects of EDCs in pigs.

Urban environments are characterized by multiple exposures that may influence body mass index (BMI) growth in early life. Previous studies are few, with inconsistent results and no evaluation of simultaneous exposures. Thus, this study aimed to assess the associations between exposure to air pollution, green spaces and built environment characteristics, and BMI growth trajectories from 0 to 5 years. This longitudinal study used data from an electronic primary care health record database in Catalonia (Spain), including 79,992 children born between January 01, 2011 and December 31, 2012 in urban areas and followed until 5 years of age. Height and weight were measured frequently during childhood and BMI (kg/m²) was calculated. Urban exposures were estimated at census tract level and included: air pollution (nitrogen dioxide (NO₂), particulate matter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅₎), green spaces (Normalized Difference Vegetation Index (NDVI) and % green space) and built environment (population density, street connectivity, land use mix, walkability index). Individual BMI trajectories were estimated using linear spline multilevel models with several knot points. In single exposure models, NO₂, PM₁₀, PM₂.₅, and population density were associated with small increases in BMI growth (e.g. β per IQR PM₁₀ increase = 0.023 kg/m², 95%CI: 0.013, 0.033), and NDVI, % of green spaces and land use mix with small reductions in BMI growth (e.g. β per IQR % green spaces increase = −0.015 kg/m², 95%CI: −0.026, −0.005). These associations were strongest during the first two months of life. In multiple exposure models, most associations were attenuated, with only those for PM₁₀ and land use mix remaining statistically significant. This large longitudinal study suggests that early life exposure to air pollution, green space and built environment characteristics may be associated with small changes in BMI growth trajectories during the first years of life, and that it is important to account for multiple exposures in urban settings.

The present investigation represents a new approach useful to evaluate the general population risk correlated with environmental exposure to air dispersed inorganic fibers. The used method is based on the evaluation of the respirable inorganic fibers both air dispersed in a big city and contained in lungs of the general population following their respiration. Moreover, these data allow to identify the sources of dispersion (anthropogenic or natural) in air of the inorganic fibers and therefore to apply strategies to improve air quality. To describe this approach, we investigated air samples from a big city in NW Italy and lung inorganic burden of people here lived. This paper reports the data of the airborne inorganic fibers detected in two sampling campaign (2014 and 2016), in 24 districts of Torino (Piemonte - NW Italy), and in some autoptic lungs of general population lived here. The airborne fibers (collected on mixed-cellulose esters membrane) were characterized by SEMEDS. The identified inorganic fiber species were assigned to 5 classes, one of these including 2 types of asbestos. These last are grouped as tremolite/actinolite asbestos. They are dispersed from natural sources (i.e. certain kinds of rocks outcropping in the city surrounding areas). In no-one of the 24 districts of Torino their concentration highlighted a situation of asbestos pollution in place.A correlation with inorganic fibers (collected on mixed-cellulose esters membrane and characterized by SEM-EDS) detected in lung tissue samples of 10 subjects lived in Torino all their life and without professional exposure to asbestos were attempted. The only types of fibers identified as asbestos are tremolite/actinolite asbestos, and they match those detected in air sampling. The number of fibers per 1 g of tissue dry weight is lower than the quantities reported as indicative of significant asbestos exposure. We observed interesting gender differences.

The influence of palm oil biodiesel content on the cytotoxicity, mutagenicity and genotoxicity of particle- and gas-phase diesel vehicle emissions was investigated. The emissions were collected on-board of a EURO IV diesel truck, fuelled with mixtures of 10% (B10), 20% (B20) and 100% (B100) of palm oil biodiesel, under real driving conditions. Organic extracts of the particulate matter (PM) and gases were characterised for 17 PAH (including EPA priority) and used for the biological assay. Increasing biodiesel content in the fuel mixture results in a decrease in the PM and PAH emission factors, both in the particulate and gas-phase. The majority of the PAH are present in the gas-phase. The mutagenic potencies, in TA98 bacteria, are higher for B20 in both phases, whereas the mutagenicity emission factor, that takes into account the lower emission of PM and PAH, is not significantly different between the fuels. Higher direct mutagenicity (TA98 + S9) is observed in all the tested fuels, indicating the action of carcinogenic compounds other than non-substituted PAH. The gas-phase extracts present higher cytotoxicity and genotoxicity in lung epithelial cell A549, which may be related to the higher PAH content in the gas-phase. The increase in biodiesel content have a different impact on cytotoxicity, being larger in the gas-phase and lower in the particle-phase. This indicates that pulmonary toxicity may be higher for the gaseous emissions, due to the role of different toxic compounds compared to the PM. The adverse biological effects when biodiesel content increases are not consequent with the reduction of the PAH characterised, indicating that other toxic compounds are more relevant. Further investigations to identify these compounds are required in order to update and focus the efforts regarding emission targets and controls.