Although microplastic pollution in the soil environment is currently an important research topic, few studies have focused on farmland soil in arid regions. This study investigated the abundances, sizes, polymer compositions, and forms of microplastics across nine agricultural plots cultivated with maize, sunflower, and potato (three of each crop) plants to determine the influences of different cropping characteristics and agricultural practices. The study area was within the arid region of the Ulungur River basin in Qinghe County, Altay, Xinjiang, China. The main forms of microplastics were fragments and fibers, and polyethylene was the dominant polymer (91.6%). The microplastic abundance ranged from 11 347 items/kgdw to 78 061 items/kgdw (mean of 52 081.7 items/kgdw). The abundance and proportion of microplastics with a diameter of <0.2 mm were significantly higher in the sunflower and maize plots (i.e., tall crops) than in the potato plots (i.e., short crops) (p < 0.05). This is due to straw residues affecting the migration and recovery of the mulch. The abundance and fragmentation of microplastics were significantly higher in the sunflower and maize plots where plastic mulch was extensively used because these tall crops anchored the mulch near their stem–root systems. The mulch was then slowly aged (e.g., via wind erosion) before being fragmented due to agricultural practices (e.g., mechanical plowing and residue retention). Although microplastics sourced from mulch are probably immobilized by straw residues in the short term, fragile and easily broken pieces of mulch are eventually released into the soil due to agricultural practices. The findings suggest that different cropping characteristics can affect the abundance and fragmentation of microplastics in agricultural soils, even within the same region, and thus the level and type of microplastic pollution. Traditional plastic mulch should be replaced with biodegradable mulch to reduce microplastic pollution in agricultural fields.

Volatile organic compounds (VOCs) promote cyanobacteria dominating eutrophicated waters, with aquatic plant decrease and even disappearance. To uncover the toxic mechanism of cyanobacterial VOCs on aquatic plants, we investigated the growth, photosynthetic pigment levels, photosynthetic abilities and related gene expression in duckweed treated with β-cyclocitral and β-ionone, 2 main components in the VOCs. The levels of chlorophylls and carotenoids gradually declined with raising the concentration of the 2 compounds and prolonging the treatment time. Their decline should result from the down-regulation of 8 genes associated with photosynthetic pigment biosynthesis and up-regulation of 2 genes involved in carotenoid degradation. The reduction was also found in the photosystem II (PSII) efficiency and O₂ evolution rate, which should result from the lowered photosynthetic pigment levels and down-regulation of 38 genes related with photosynthetic process. The frond numbers, total frond area and fresh weight gradually decreased with raising the 2 compound concentration, which may result from the lowered photosynthetic abilities as well as down-regulated expression of 7 genes associated with growth-promoting hormone biosynthesis and signal transduction. It can be speculated that cyanobacterial VOCs may poison aquatic plants by lowering the photosynthesis and growth through altering related gene expression.

The biomagnification of toxic methylmercury (MeHg) and selenium (Se) through aquatic food webs using nitrogen stable isotopes (δ¹⁵N) varies among ecosystems but underlying mechanisms are yet unexplained. Given the strong links between MeHg and thiol-containing amino acids and proteins containing selenocysteine, our hypothesis was that cysteine content is a better predictor of MeHg and Se transfer through lake food webs than δ¹⁵N. Food web samples were collected from six lakes in Kejimkujik National Park, Nova Scotia, Canada, and the regression slopes of log MeHg or Se versus protein-bound cysteine or bulk δ¹⁵N were compared. Across all six lakes, MeHg varied by a factor of 10 among taxa and was significantly and positively related to both cysteine (R² = 0.65–0.80, p < 0.001) and δ¹⁵N (R² = 0.88–0.94, p < 0.001), with no among-system differences in these slopes. In contrast, total Se concentrations varied by less than a factor of 2 among taxa in four lakes and were significantly related to cysteine in only two food webs (R² = 0.20 & 0.37, p = 0.014 & < 0.001); however, δ¹⁵N was not a predictor of Se in any lake (p = 0.052–0.777). Overall, these novel results indicate that cysteine content predicts MeHg, and sometimes Se, across trophic levels, providing a potential mechanism for among-system differences in their biomagnification.

The role of coarse particles has recently been proven to be underestimated in the atmosphere and can strongly influence clouds, ecosystems and climate. However, previous studies on atmospheric chemistry of volatile organic compounds (VOCs) have mostly focused on the products in fine particles, it remains less understood how coarse particles promote secondary organic aerosol (SOA) formation. In this study, we investigated water-soluble compounds of size-segregated aerosol samples (0.056 to >18 μm) collected at a coastal rural site in southern China during late summer and found that oxygenated organic matter was abundant in the coarse mode. Comprehensive source apportionment based on mass spectrum and ¹⁴C analysis indicated that different from fossil fuel SOA, biogenic SOA existed more in the coarse mode than in the fine mode. The SOA in the coarse mode showed a unique correlation with biogenic VOCs. ¹³C and elemental composition strongly suggested a pathway of heterogeneous reactions on coarse particles, which had an abundant low-acidic aqueous environment with soil dust to possibly initiate iron-catalytic oxidation reactions to form SOA. This potential pathway might complement understanding of both formation of biogenic SOA and sink of biogenic VOCs in global biogeochemical cycles, warrantying future relevant studies.

Rice paddy fields are major sources of atmospheric methane (CH₄) and nitrous oxide (N₂O). Rice variety is an important factor affecting CH₄ and N₂O emissions. However, the interactive effects of rice metabolites and microorganisms on CH₄ and N₂O emissions in paddy fields are not clearly understood. In this study, a high greenhouse gas-emitting cultivar (YL 6) and a low greenhouse gas-emitting cultivar (YY 1540) were used as experimental materials. Metabolomics was used to examine the roots, root exudates, and bulk soil metabolites. High-throughput sequencing was used to determine the microbial community composition. YY 1540 had more secondary metabolites (flavonoids and isoflavonoids) in root exudates than YL 6. It was enriched with the uncultured members of the families Gemmatimonadanceae and Rhizobiales_Incertae_Sedis in bulk soil, and genera Burkholderia-Caballeronia-Paraburkholderia, Magnetospirillum, Aeromonas, and Anaeromyxobacter in roots, contributing to increased expression of pmoA and nosZ genes and reducing CH₄ and N₂O emissions. YL 6 roots and root exudates contained higher contents of carbohydrates [e.g., 6-O- acetylarbutin and 2-(3- hydroxyphenyl) ethanol 1′-glucoside] than those of YY 1540. They were enriched with genera RBG-16-58-14 in bulk soil and Exiguobacterium, and uncultured member of the Kineosporiaceae family in roots, which contributed to increased expression of mcrA, ammonia-oxidizing archaea, ammonia-oxidizing bacteria, nirS, and nirK genes and greenhouse gas emissions. In general, these results established a link between metabolites, microorganisms, microbial functional genes, and greenhouse gas emissions. The metabolites of root exudates and roots regulated CH₄ and N₂O emissions by influencing the microbial community composition in bulk soil and roots.

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.

Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010–2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reflection of the burden associated with AT. The heat effect appeared at lag 0–1 days, with 19% (95% CI, 11–26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0–28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents’ per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.

The theory-guided air quality model solves the mathematical equations of chemical and physical processes in pollution transportation numerically. While the data-driven model, as another scientific research paradigm with powerful extraction of complex high-level abstractions, has shown unique advantages in the PM₂.₅ prediction applications. In this paper, to combine the two advantages of strong interpretability and feature extraction capability, we integrated the partial differential equation of PM₂.₅ dispersion with deep learning methods based on the newly proposed DPGN model. We extended its ability to perform long-term multi-step prediction and used advection and diffusion effects as additional constraints for graph neural network training. We used hourly PM₂.₅ monitoring data to verify the validity of the proposed model, and the experimental results showed that our model achieved higher prediction accuracy than the baseline models. Besides, our model significantly improved the correct prediction rate of pollution exceedance days. Finally, we used the GNNExplainer model to explore the subgraph structure that is most relevant to the prediction to interpret the results. We found that the hybrid model is more biased in selecting stations with Granger causality when predicting.

Distillery sludge is a major source of aquatic pollution, but little is known about their microbial community and their association with the organic and metal pollutants. Sugarcane molasses-based distillery is an important industry in India, although the waste is usually treated prior to disposal, the treatment is often inadequate. The adverse effects of the organic and metal pollutants in sugarcane molasses-based distillery sludge on the microbial biodiversity and abundance in the disposal site have not been elucidated. This study aims to address this gap of knowledge. Samples were collected from the discharge point, 1 and 2 km downstream (D1, D2, and D3, respectively) of a sugarcane distillery in Uttar Pradesh, India, and their physico-chemical properties characterised. Using QIIME, taxonomic assignment for the V3 and V4 hypervariable regions of 16 S rRNA was performed. The phyla Proteobacteria (28–39%), Firmicutes (20–28%), Bacteriodetes (9–10%), Actinobacteria (5–10%), Tenericutes (1–9%) and Patescibacteria (2%) were the predominant bacteria in all three sites. Euryechaeota, were detected in sites D1 and D2 (1–2%) but absent in D3. Spirochaetes (5%), Sinergistetes (2%) and Cloacimonetes (1%) were only detected in samples from site D1. Shannon, Simpson, Chao1, and Observed-species indices indicated that site D1 (10.18, 0.0013, 36706.55 and 45653.84, respectively) has higher bacterial diversity and richness than D2 (6.66, 0.0001, 25987.71 and 49655.89, respectively) and D3 (8.31, 0.002, 30345.53 and 30654.88, respectively), suggesting the organic and metal pollutants provided the stressors to favour the survival of microbial community that can biodegrade and detoxify them in the distillery sludge. This study confirmed that the treatment of the distillery waste was not sufficiently effective and provided new metagenomic information on its impact on the surrounding microbial community. It also offered new insights into potential bioremediation candidates.

Phenanthrene (Phe) is a polycyclic aromatic hydrocarbon widely present in foods and drinking water. To explore the detrimental effects of Phe on body metabolism, female Kunming mice were treated with Phe in drinking water at concentrations of 0.05, 0.5 and 5 ng/mL. After exposure for 270 d, the animals exhibited dose-dependent reduced body weight and increased water consumption. The dose-dependent accumulation of Phe in the brain decreased hypothalamic neuron numbers, upregulated hypothalamic expression of anaplastic lymphoma kinase, elevated norepinephrine levels in white adipose tissue (WAT) and further activated lipolysis in WAT, leading to a reduction in fat mass. Brown adipose tissue formation was reduced, accompanied by the inhibition of the bone morphogenetic protein signaling pathway. A simultaneous reduced serum levels of antidiuretic hormone (arginine vasopressin) might be one of the reasons for increased water consumption. The present results indicate an environmental etiology and prevention way for the development of emaciation-thirst disease.