Natural environments have been linked to decreased risk of cardiovascular disease (CVD) and respiratory disease (RSD) mortality. However, few cohort studies have looked at associations of natural environments with CVD or RSD hospitalization. The aim of this study was to evaluate these associations in a cohort of U.S. Medicare beneficiaries (∼63 million individuals). Our open cohort included all fee-for-service Medicare beneficiaries (2000–2016), aged ≥65, living in the contiguous U.S. We assessed zip code-level park cover based on the United States Geological Survey Protected Areas Database, average greenness (Normalized Difference Vegetation Index, NDVI), and percent blue space cover based on Landsat satellite images. Cox-equivalent Poisson models were used to estimate associations of the exposures with first CVD and RSD hospitalization in the full cohort and among those living in urban zip codes (≥1000 persons/mile²). NDVI was weakly negatively correlated with percent park cover (Spearman ρ = −0.23) and not correlated with percent blue space (Spearman ρ = 0.00). After adjustment for potential confounders, percent park cover was not associated with CVD or RSD hospitalization in the full or urban population. An IQR (0.27) increase in NDVI was negatively associated with CVD (HR: 0.97, 95%CI: 0.96, 0.97), but not with RSD hospitalization (HR: 0.99, 95%CI: 0.98, 1.00). In urban zip codes, an IQR increase in NDVI was positively associated with RSD hospitalization (HR: 1.02, 95%CI: 1.00, 1.03). In stratified analyses, percent park cover was negatively associated with CVD and RSD hospitalization for Medicaid eligible individuals and individuals living in low socioeconomic status neighborhoods in the urban population. We observed no associations of percent blue space cover with CVD or RSD hospitalization. This study suggests that natural environments may benefit cardiorespiratory health; however, benefits may be limited to certain contexts and certain health outcomes.

Growing epidemiological evidence has shown that exposure to ambient air pollution contributes to poor sleep quality. However, whether variability in air pollution exposure affects sleep quality remains unclear. Based on a large sample in China, this study linked individual air pollutant exposure levels and temporal variability with subjective sleep quality. Town-level data on daily air pollution concentration for 30 days prior to the survey date were collected, and the monthly mean value, standard deviations, number of heavily polluted days, and trajectory for six common pollutants were calculated to measure air pollution exposure and its variations. Sleep quality was subjectively assessed using the Pittsburgh Sleep Quality Index (PSQI), and a PSQI score above 5 indicated overall poor sleep quality. Multilevel and negative control models were used. Both air pollution exposure and variability contributed to poor sleep quality. A one-point increase in the one-month mean concentration of particulate matter with aerodynamic diameters of ≤2.5 μm (PM₂.₅) and ≤10 μm (PM₁₀) led to 0.4% (95% confidence interval (CI): 1.002–1.006) and 0.3% (95% CI: 1.001–1.004) increases in the likelihoods of overall poor sleep quality (PSQI score >5), respectively; the odds ratios of a heavy pollution day with PM₂.₅ and PM₁₀ were 2.2% (95% CI: 1.012–1.032) and 2.2% (95% CI: 1.012–1.032), respectively. Although the mean concentrations of nitrogen dioxide, sulfur dioxide, and carbon monoxide met the national standard, they contributed to the likelihood of overall poor sleep quality (PSQI score >5). A trajectory of air pollution exposure with maximum variability was associated with a higher likelihood of overall poor sleep quality (PSQI score >5). Subjective measures of sleep latency, duration, and efficiency (derived from PSQI) were affected in most cases. Thus, sleep health improvements should account for air pollution exposure and its variations in China under relatively high air pollution levels.

Microplastics (MPs), which are emerging environmental pollutants, remain uncertainties in their toxic mechanism. MPs have been linked to severe liver metabolic disorders and neurotoxicity, but it is still unknown whether the abnormal metabolites induced by MPs can affect brain tissue through the liver-brain axis. Exposed to MPs of chickens results in liver metabolic disorders and increased glutamine and glutamate synthesis. The relative expression of glutamine in the C group was −0.862, the L-PS group was 0.271, and the H-PS group was 0.592. The expression of tight junction proteins in the blood-brain barrier (BBB) was reduced by PS-MPs. Occludin protein expression decreased by 35.8%–41.2%. Claudin 3 decreased by 19.6%–42.3%, and ZO-1 decreased by 28.3%–44.6%. Excessive glutamine and glutamate cooperated with PS-MPs to inhibit the Nrf2-Keap1-HO-1/NQO1 signaling pathway and triggered autophagy-dependent ferroptosis and apoptosis. GPX protein expression decreased by 30.9%–38%. LC3II/LC3I increased by 54%, and Caspase 3 increased by 45%. Eventually, the number of Purkinje cells was reduced, causing neurological dysfunction. In conclusion, this study provides new insights for revealing the mechanism of nervous system damaged caused by PS-MPs exposed in chickens.

Zinc oxide nanoparticles (ZnO NPs) and its sulfidized form (ZnS NPs) are increasingly entering into freshwater systems through multiple pathways. However, their impacts on the composition and function of sedimentary microbial communities are still largely unknown. Here, two kinds of lake-derived microcosms were constructed and incubated with ZnO NPs, or ZnS NPs to investigate the short-term (7 days) and long-term (50 days) impacts on sedimentary microbial communities and nitrogen cycling. After 7 days, both ZnO NPs and ZnS NPs dosed microbial communities experienced distinct alterations as compared to the undosed controls. By day 50, the structural shifts of microbial communities caused by ZnO NPs were significantly enlarged, while the microbial shifts induced by ZnS NPs were largely resolved. Additionally, ZnO NPs and ZnS NPs could significantly alter nitrogen species and nitrogen cycling genes in sediments, revealing their non-negligible impacts on nitrogen cycling processes. Furthermore, our data clearly indicated that the impacts of ZnO NPs and ZnS NPs on nitrogen cycling differed distinctly in different lake-derived microcosms, and the impacts were significantly correlated with microbial community structure. Overall, this research suggests that the entrance of pristine or sulfidized ZnO NPs into freshwater systems may significantly impact the sedimentary microbial community structure and nitrogen cycling.

Although many toxicological studies on pesticides and nanoparticles have been conducted, it is not clear whether nanoparticles will increase the toxicity of pesticides. In this study, we chose imidacloprid (IMI) as a representative pesticide, and explored the influence of ZnO NPs on the toxic effect of IMI. In addition, we studied the bioaccumulation of IMI in mice. Using biochemical index analysis, liver histopathological analysis, non-targeted metabolomics, and LC/MS analysis, we found that ZnO NPs increased the toxicity of IMI, which may be related to the increase in IMI bioaccumulation in mice. In addition, we used intestinal histopathological analysis, RT-qPCR, and 16sRNA sequencing to find that the disturbance of the gut microbiota and the impaired intestinal barrier caused by ZnO NPs may be the reason for the increase in IMI bioaccumulation. In summary, our results indicate that ZnO NPs disrupted the intestinal barrier and enhanced the bioaccumulation of IMI, and therefore increased the toxicity of IMI in mice. Our research has deepened the toxicological insights between nanomaterials and pesticides.

Eutrophication transforms clear water into turbid water in shallow lakes. Current restoration techniques focus on re-establishing the clear-water state rather than on its maintenance. We investigated the response of submerged macrophytes to temporary grass carp (Ctenopharyngodon idella) and scraping snail (Bellamya aeruginosa) introductions. We also explored the impacts of herbivores on underwater light conditions to identify their long- and short-term potential to halt regime shift from clear to turbid after clear-water state reestablishment. Herbivores reduced both the biomass of submerged macrophytes and accumulated nutrients in the tissue of submerged macrophytes. This potentially avoided the pulse of endogenous nutrient release which would have exceeded the threshold required for the regime shift from clear to turbid. However, herbivores had a non-significant impact on submerged macrophyte-reduced light attenuation coefficient, which has a positive linear relationship with water chlorophyll a. Further, grass carp and snails enhanced the inhibition ratio of submerged macrophytes to phytoplankton by 3.96 and 2.13 times, respectively. Our study provides novel findings on the potential of herbivore introduction as an indirect biomanipulation tool for halting the regime shift of shallow lakes from clear to turbid after the restoration of submerged macrophytes.

Tyre wear particles may be the largest source of microplastic to the natural environment, yet information on their biological impacts is inadequate. Two key estuarine invertebrates; the clam Scrobicularia plana and the ragworm Hediste diversicolor were exposed to 10% tyre particles in sediment for three days. Both species consumed the particles, although S. plana consumed 25x more than H. diversicolor (967 compared with 35 particles.g⁻¹ wet weight, respectively). We then investigated the impact of 21 days exposure to different concentrations of tyre particles in estuarine sediments (0.2, 1, and 5% dry weight sediment) on aspects of the health of S. plana and H. diversicolor. Reductions in feeding and burial rates were observed for S. plana but not H. diversicolor, whilst both species showed a decrease in protein content in response to the greatest tyre particle concentration (5%), linked to an 18% decrease in energy reserves for H. diversicolor. Five percent tyre particle exposure led to an increase in total glutathione in the tissues of H. diversicolor, whilst lipid peroxidation decreased in the digestive glands of S. plana, possibly due to an increase in cell turnover. This study found that S. plana's health was impacted at lower concentrations than H. diversicolor, likely due to its consumption of large quantities of sediment. At the high exposure concentration (5%), the health of both invertebrates was impacted. This study did not separate the effects caused by the microplastic particles versus the effects of the chemical additives leaching from these particles, but our results do indicate that future studies should investigate effects in isolation and in combination, to determine the main drivers of toxicity.

This study proposes a red tide risk assessment method based on intercriteria correlation (CRITIC), technique for order preference by similarity to an ideal solution (TOPSIS), assessment of estuarine trophic status (ASSETS) methods and Monte Carlo simulation (MCS) to calculate the probability of each risk level. The integrated TOPSIS-ASSETS method is used to calculate the risk levels of each year, where index weight is determined by CRITIC method. MCS method is employed to calculate the probability of each risk level. The results showed that level III to level V indicates high possibility of red tides in the case study area (Tolo Harbor). The highest risk rating was level V in 1988. The change of the risk level of red tide is consistent with the real situation of the occurrence of red tide. Another case of the east part of Skagerrak Strait shows that the results of this method are consistent with field situation. When there is an error between the evaluation results and the real situation, MCS can further suggest the probability of error in the evaluation results. Meanwhile, sensitivity analysis was used to test the performance of the evaluation model and two comparative methods. The results show that the proposed risk assessment method has better performance than other methods and can provide an effective risk evaluation for red tide management.

As(V) reduction mediated by microorganisms might be an essential process in resisting As toxicity since As(V) is the major species in the landfill. LSZ has been considered as a trigger of all types of microbial activity inside a landfill site. This research investigated the microbial As(V)-reducing behavior in LSZ. The results revealed that higher As(V)-reduction efficiency in higher As(V) content-stress LSZ scenario. The corresponding microbial diversity also varied with the As(V) content. The microbial community structure was related to arrA and arsC distribution, which encode respiratory As(V) reductase and cytoplasmic As(V) reductase, respectively. The landfill As bio-reduction pathways were modeled, as well as the As functional gene distribution among different As(V) contents at different landfill stages. The C, N, and S metabolic processes generally affected the As(V)-resistance genes distribution. Thiosulfate oxidation, denitrification, and dissimilatory nitrate reduction positively affected arsC, while dissimilatory sulfate reduction and methanogenesis trended to play a negative role. This research provides new insight into As(V) bio-reduction inside a landfill site in terms of functional genes distribution and correlation with nutrient elements metabolic processes.

The 2015 Paris agreement aims to cut greenhouse gas emissions and keep global temperature rise below 2 °C above pre-industrial levels. Reducing CH₄ emissions from leaking pipelines presents a relatively achievable objective. While walking and driving surveys are commonly used to detect leaks, the detection probability (DP) is poorly characterized. This study aims to investigate how leak rates, survey distance and speed, and atmospheric conditions affect the DP in controlled belowground conditions with release rates of 0.5–8.5 g min⁻¹. Results show that DP is highly influenced by survey speed, atmospheric stability, and wind speed. The average DP in Pasquill–Gifford stability (PG) class A is 85% at a low survey speed (2–11 mph) and decreases to 68%, 63%, 65%, and 60% in PGSC B/C, D, E/F, and G respectively. It is generally less than 25% at a high survey speed (22–34 mph), regardless of stability conditions and leak rates. Using the measurement data, a validated DP model was further constructed and showed good performance (R2: 0.76). The options of modeled favorable weather conditions (i.e., PG stability class and wind speed) to have a high DP (e.g., >50%) are rapidly decreased with the increase in survey speed. Walking survey is applicable over a wider range of weather conditions, including PG stability class A to E/F and calm to medium winds (0–5 m s⁻¹). A driving survey at a low speed (11 mph) can only be conducted under calm to low wind speed conditions (0–3 m s⁻¹) to have an equivalent DP to a walking survey. Only calm wind conditions in PG A (0–1 m s⁻¹) are appropriate for a high driving speed (34 mph). These findings showed that driving survey providers need to optimize the survey schemes to achieve a DP equivalence to the traditional walking survey.