Nitrogen (N) deposition has been conventionally thought to decrease forest soil methane (CH₄) uptake, while the biome specific and dose dependent effect is poorly understood. Based on a meta-analysis of 63 N addition trials from 7 boreal forests, 8 temperate forests, 13 subtropical and 4 tropical forests, we evaluated the effects of N addition on soil CH₄ uptake fluxes across global forest biomes. When combining all N addition levels, soil CH₄ uptake was insignificantly decreased by 7% in boreal forests, while N addition significantly decreased soil CH₄ uptake by 39% in temperate forests and by 21% in subtropical and tropical forests, respectively. Meta-regression analyses, however, indicated a shift from a positive to a negative effect on soil CH₄ uptake with increasing N additions both in boreal forests (threshold = 48 kg N ha⁻¹ yr⁻¹) and temperate forests (threshold = 27 kg N ha⁻¹ yr⁻¹), while no such shift was found in subtropical and tropical forests. Considering that current N deposition to most boreal and temperate forests is below the abovementioned thresholds, N deposition likely exerts a positive to neutral effect on soil CH₄ uptake in both forest biomes. Our results provide new insights on the biome specific and dose dependent effect of N addition on soil CH₄ sink in global forests and suggest that the current understanding that N deposition decreases forest soil CH₄ uptake is flawed by high levels of experimental N addition.

Common varieties of genetically modified (GM) cotton increasingly display insect-resistant properties via expression of bacterial-derived toxins from Bacillus thuringiensis (Bt). This necessitates a deeper understanding of the possible effects of these crops on non-target insects. The mirid bug Apolygus lucorum is a major pest in cotton production in China, however, the effect of GM cotton on this non-target species is currently virtually unknown. This insect is exposed to these transgenic plants by consuming genetically modified (GM) leaves. In this study, laboratory experiments were conducted to assess the toxicity of CCRI41 and CCRI45, (genetically modified cotton varieties which express the toxins Cry1Ac and CpTI (Cowpea Trypsin Inhibitor)) on nymphs and adults of A. lucorum. There was no detectable increase in mortality after A. lucorum fed on GM cotton leaves for 20 days. While we detected trace amounts of Cry1Ac proteins in both A. lucorum nymphs and adults (<10 ng/g fresh weight), the expression of genes related to detoxification did not detectably differ from those feeding on non-GM cotton. Our binding assays did not show Cry1Ac binding to receptors on the midgut brush border membrane from either A. lucorum nymphs or adults. Our findings collectively indicate that feeding on leaves of the GM cotton varieties CCRI41 and CCRI45 have few toxic effects on A. lucorum.

Understanding the composition and assembly mechanism of waterborne pathogen is essential for preventing the pathogenic infection and protecting the human health. Here, based on 16S rRNA sequencing, we investigated the composition and spatial variation of potentially pathogenic bacteria from different sections of the Pearl River, the most important source of water for human in Southern China. The results showed that the potential pathogen communities consisted of 6 phyla and 64 genera, covering 11 categories of potential pathogens mainly involving animal parasites or symbionts (AniP), human pathogens all (HumPA), and intracellular parasites (IntCelP). Proteobacteria (75.87%) and Chlamydiae (20.56%) were dominant at the phylum level, and Acinetobacter (35.01%) and Roseomonas (8.24%) were dominant at the genus level. Multivariate analysis showed that the potential pathogenic bacterial community was significantly different among the four sections in the Pearl River. Both physicochemical factors (e.g., NO₃–N, and suspended solids) and land use (e.g., urban land and forest) significantly shaped the pathogen community structure. However, spatial effects contributed more to the variation of pathogen community based on variation partitioning and path analysis. Null model based normalized stochasticity ratio analysis further indicated that the stochastic process rather than deterministic process dominated the assembly mechanisms by controlling the spatial patterns of potential pathogens. In conclusion, high-throughput sequencing shows great potential for monitoring the potential pathogens, and provided more comprehensive information on the potentially pathogenic community. Our study highlighted the importance of considering the influences of dispersal-related processes in future risk assessments for the prevention and control of pathogenic bacteria.

The traditional incremental lifetime cancer risk (ILCR) model of urban soil polycyclic aromatic hydrocarbon (PAH) health risk assessment has a large spatial scale and commonly calculates relevant statistics by regarding the whole area as a geographic unit but fails to consider the high heterogeneity of the PAH distribution and differences in population susceptibility and density in an area. Therefore, the risk assessment spatial performance is insufficient and does not reflect the characteristics of cities, which are centered on human activities and serve the needs of humans, thus making it difficult to effectively support PAH prevention and treatment measures in cities. Here, the random forest model combined with the kriging residual model (RFerr-K) is used to estimate high-precision PAH distributions, separately considering the exposure characteristics of children and adults with different susceptibilities, and kindergarten point-of-interest (POI) and population density index (PDI) data were used to estimate the distributions of the kindergarten children and adults in the study area. Through the refined expression of these three dimensions, a new spatially explicit model of the incremental lifetime cancer-causing population distribution (MapPILCR) was constructed, and the risk threshold range delineation method was proposed to accurately identify regional risk levels. The results showed that the RFerr-K model significantly improves the accuracy of PAH prediction. The susceptibility index (SI) of children is 45% higher than that of adults, and POI and PDI data can be used effectively in population distribution estimation. The MapPILCR model provides a useful method for the spatially explicit assessment of the cancer risk of urban populations to inspire urban pollution grid management.

Both microplastics and persistent organic pollutants (POPs) are ubiquitously present in natural water environment, posing a potential threat to aquatic organisms. While it has been suggested that the immune responses of aquatic organisms could be hampered by exposure to microplastics and POPs, the synergistic immunotoxic impact of these two types of pollutants remain poorly understood. In addition, little is known about the mechanism behind the immunotoxic effect of microplastics. Therefore, in the present study, the immunotoxicity of microplastics and two POPs, benzo[a]pyrene (B[a]P) and 17β-estradiol (E2), were investigated alone or in combination in a bivalve species, Tegillarca granosa. Evident immunotoxicity, as indicated by alterations of haemocyte count, blood cell composition, phagocytic activity, intracellular content of ROS, concentration of Ca²⁺ and lysozyme, and lysozyme activity, was revealed for both microplastics and the two POPs examined. In addition, the expression of six immune-, Ca²⁺ signalling-, and apoptosis-related genes was significantly altered by exposure of clams to the contaminants studied. Furthermore, the toxicity of POPs was generally aggravated by smaller microplastics (500 nm) and mitigated by larger ones (30 μm). This size dependent effect on POP toxicity may result from size dependent interactions between microplastics and POPs. Data obtained in this study also indicate that similar to exposure to B[a]P and E2, exposure to microplastics may hamper the immune responses of clams through a series of interdependent physiological and molecular processes.

High concentration of fluoride (up to 20.9 mg/L) in groundwater with significant variation (p = 5.9E-128) among samples was reported from Birbhum district, an acknowledged fluoride endemic region in India. The groundwater samples (N = 368) were grouped based on their hydrochemical properties and aquifer geology for hydro-geochemical characterization. Friedman’s test showed p < 0.0001 confidence level which indicates that fluoride concentration among geological groups and water groups are independent. Bland-Altman plot was used to study the inter-relationships among the groups through bias value (∂) and limit of agreement (LoA). Among the geological groups, laterites and granite-gneiss groups exhibited statistically significantly difference in fluoride geochemistry; whereas the younger and older alluvium groups displayed similar characteristics. The fluoride concentration was found to be in the order Lateritic > Granite-gneiss > Older alluvium ≥ Younger alluvium. Dissolution of minerals (such as fluorite, biotite) in laterite sheeted basalt, and granite-gneiss is the main source of groundwater fluoride in the region. Fluoride concentration is also influenced by depth of water table. Hydrochemical study indicated that fluoride concentration was higher in Na–HCO₃ than in Ca–SO₄ and Ca–HCO₃ type of groundwater. The fluoride concentration were positively correlated with Na⁺ and pH and negatively correlated with the Ca²⁺ and Mg²⁺ signifying linkage with halite dissolution and calcite, dolomite precipitation. Geostatistical mapping of WQI through empirical bayesian kriging (EBK) with respect to regional optimal guideline value (0.73 mg/L) classified that groundwater in some parts of the district are unfit for drinking purpose. Health survey (N = 1767) based on Dean’s criteria for dental fluorosis indicated presence of slight to moderate dental hazard. Besides, providing baseline data for management of groundwater quality in the study area, the study demonstrated the applicability of Bland-Altman analysis and empirical bayesian kriging (EBK) in delineation and interpolation of fluoride contaminated region.

Cadmium (Cd), a major environmental contaminant, is closely associated with male reproductive health. Selenium (Se) has been recognized as an effective chemo-protectant against Cd toxicity, but the underlying mechanisms remain unclear. The objective of present study was to illustrate the toxic effect of Cd on testis, and then compare the antagonistic effect among different Se sources on growth performance, testicular damage, ion homeostasis, antioxidative potential, and the expression of selenotranscriptome and biosynthetic related factors in Cd-treated chicken. Male chickens were fed with (Ⅰ) Control group: basal diet; (Ⅱ) Cd group: basal diet with 140 mg/kg CdCl₂; (Ⅲ) YSe + Cd group: basal diet with 140 mg/kg CdCl₂ and 3 mg/kg Yeast-Se; (Ⅳ) NSe + Cd group: basal diet with 140 mg/kg CdCl₂ and 1 mg/kg Nano-Se; (Ⅴ) SSe + Cd group: basal diet with 140 mg/kg CdCl₂ and 3 mg/kg Na₂SeO₃. It was observed that different Se treatments dramatically alleviated Cd-induced testicular developmental disorder, ion homeostasis disorder, hormone secretion disorder and oxidative stress. Simultaneously, Se mitigated Cd-induced testicular toxicity by regulating selenoprotein biosynthetic related factors to promote selenoprotein transcription. Finally, this study indicated that dietary supplementation of Yeast-Se produced an acceptable Se form to protect testis from Cd exposure.

To characterise the mass concentration, size-distribution, and respiratory deposition of selected trace metals (Cr, Mn, Fe, Ni, Cu, Zn, Ba, and Pb) in size-segregated PM₂.₅, a long-term monitoring campaign was undertaken at an urban background site in Como (Northern Italy). 96-h aerosol samples were collected weekly, from May 2015 to March 2016, using a 13-stage low pressure impactor and analysed via laser ablation-inductively coupled plasma-mass spectrometry. Significantly higher levels of trace metals were generally found during the heating season (two to more than four times) compared to the non-heating period at all size ranges, especially for concentrations in PM₀.₁–₁. Distinct distribution profiles characterised the different elements, even though the corresponding heating and non-heating shapes always exhibited similar features, with negligible seasonal shifts in the average mass median aerodynamic diameters. Fe, Ba, and Cu had >70% of their mass in PM₁–₂.₅, whereas Pb, Zn, and Ni showed higher contributions in the accumulation mode (>60%). Finally, broad size-distributions were found for Cr and Mn. The multiple-path particle dosimetry model estimated the overall deposition fractions in human airways varying between 27% (Pb) and 48% (Ba). The greatest deposition variability was always registered in the head region of the respiratory system, with the highest contributions for those metals predominantly accumulated in the PM₂.₅ coarse modes. In contrast, the deposition in the deepest respiratory tract maintained nearly constant proportions over time, becoming notably important for Pb, Ni, and Zn (∼13%) with respect to their total deposition. The comparison with national limits established for Pb and Ni suggested the absence of significant risks for the local population, as expected, with average concentrations two orders of magnitude lower than the corresponding annual limit and objective value. Similar findings were reported for all the other metals, for which the estimated hazard quotients were always well <1.

Persistent organic pollutants (POPs) are believed to alter metabolic homeostasis during fetal development, leading to childhood obesity. However, limited studies have explored how fetal chemical exposures relate to birth and infant weight outcomes in low-income Hispanic families at the highest risk of obesity. Therefore, we sought to determine associations between neonatal POPs exposure measured in newborn dried blood spots (DBS) and prenatal diet quality, birth weight, and overweight status at 18 months old. We conducted a case-control study nested within the Starting Early Program randomized controlled trial comparing POPs concentrations in infants with healthy weight (n = 46) and overweight status (n = 52) at age 18 months. Three categories of POPs, organochlorine pesticides (OCPs), polybrominated diphenyl ethers (PBDEs) and perfluoroalkyl substances (PFASs) were measured in archived newborn DBS. We assessed correlations between prenatal diet quality and neonatal POPs concentrations. Multivariable regression analyses examined associations between POPs (dichotomized at the mean) and birth weight z-score and weight status at 18 months, controlling for confounders. Seven of eight chemicals had detectable levels in greater than 94% of the sample. Higher protein, sodium and refined grain intake during pregnancy were correlated with lower POPs in newborn DBS. We found that high concentrations of perfluorooctanesulfonate (unstandardized coefficient [B]: −0.62, 95% confidence interval [CI]: −0.96 to −0.29) and perfluorohexanesulfate (B: −0.65, 95% CI: −0.99 to −0.31) were related to lower birth weight z-scores compared to those with low concentrations. We did not find associations between PBDEs, OCPs, and the other PFASs with birth weight z-scores, or between any POPs and weight status at 18 months. In conclusion, two PFASs were associated with lower birth weight, an important indicator of child health and growth, although direct associations with infant overweight status were not found. Whether neonatal POPs exposures contribute to economic and ethnic disparities in early obesity remains unclear.

Uncertainty assessment of parameters associated with non-point source pollution mechanism modeling are crucial for improving the effectiveness of pollution controlling. In this study, an approach based on Bayesian inference and integrated Markov chain Monte Carlo and multilevel factorial analysis has been developed, and it can not only apply straightforward Bayesian inference to assess parameter uncertainties, but also quantitatively investigate the main and interactive effects of multiple parameters on the model response variables by measuring the specific variations of model outputs. Its applicability and advantages are presented through the application of the Soil and Water Assessment Tool to Shitoukoumen Reservoir Catchment in northeast China. This study investigated the uncertainties of a set of sensitive parameters and their multilevel effects on model response variables, including average annual runoff (AAR), average annual sediment (AAS) and average annual total nitrogen (AAN). Results revealed that (i) soil conservation service runoff curve number for moisture condition II (CN2) had a positive effect on all response variables; (ii) available water capacity of the soil layer (SOL_AWC) had a negative effect on all response variables; (iii) the universal soil loss equation support practice (USLE_P) had a positive effect on AAS and AAN, and little effect on AAR; while the nitrate percolation coefficient (NPERCO) had a positive effect on AAN, and little effect on AAS and AAR; and (iv) the interactions amongst parameters had obvious interdependent effects on the model response variables, for example, the interaction between CN2 and SOL_AWC had a major impact on AAR. The above findings can improve the simulating and predicting capabilities of non-point source pollution mechanism model. Overall, this study highlights that the proposed approach represents a promising solution for uncertainty assessment of model parameters in non-point source pollution mechanism modeling.