We aimed to explore the effects of mixtures of lead and various metals on blood pressure (BP) and the odds of pre-hypertension (systolic blood pressure (SBP) 120–139 mmHg, and/or diastolic blood pressure (DBP) 80–89 mmHg) and hypertension (SBP/DBP ≥140/90 mmHg) among Chinese adults in a cross-sectional study. This study included 11,037 adults aged 18 years or older from the 2017–2018 China National Human Biomonitoring. Average BP and 13 metals (lead, antimony, arsenic, cadmium, mercury, thallium, chromium, cobalt, molybdenum, manganese, nickel, selenium, and tin) in blood and urine were measured and lifestyle and demographic data were collected. Weighted multiple linear regressions were used to estimate associations of metals with BP in both single and multiple metal models. Weighted quantile sum (WQS) regression was performed to assess the relationship between metal mixture levels and BP. In the single metal model, after adjusting for potential confounding factors, the blood lead levels in the highest quartile were associated with the greater odds of both pre-hypertension (odds ratio (OR): 1.56, 95% CI: 1.22–1.99) and hypertension (OR:1.75, 95% CI: 1.28–2.40) when compared with the lowest quartile. We also found that blood arsenic levels were associated with increased odds of pre-hypertension (OR:1.31, 95% CI:1.00–1.74), while urinary molybdenum levels were associated with lower odds of hypertension (OR:0.68, 95% CI:0.50–0.93). No significant associations were found for the other 10 metals. WQS regression analysis showed that metal mixture levels in blood were significantly associated with higher SBP (β = 1.56, P < 0.05) and DBP (β = 1.56, P < 0.05), with the largest contributor being lead (49.9% and 66.8%, respectively). The finding suggests that exposure to mixtures of metals as measured in blood were positively associated with BP, and that lead exposure may play a critical role in hypertension development.

Atmospheric bioaerosols contain live and dead biological components that can enter the human respiratory tract (HRT) and affect human health. Here, the total microorganisms in a coastal megacity, Qingdao, were characterized on the basis of long-term observations from October 2013 to January 2021. Particular attention was given to the size dependence of inhalable bioaerosols in concentration and respiratory deposition in different populations on foggy and hazy days. Bioaerosol samples stained with 4,6-diamidino-2-phenylindole (DAPI) were selected to measure the total airborne microbe (TAM) concentrations with an epifluorescence microscope, while a multiple-path particle dosimetry model was employed to calculate respiratory deposition. The mean TAM concentrations in the particle size range of 0.65–1.1 μm (TAM₀.₆₅–₁.₁) were 1.23, 2.02, 1.60 and 2.33 times those on sunny reference days relative to the corresponding values on days with slight, mild, moderate and severe levels of haze, respectively. The mean concentration of TAMs in the particle size range of 0.65–2.1 μm (TAM₀.₆₅–₂.₁) on severely hazy days was (2.02 ± 3.28) × 10⁵ cells/m³, with a reduction of 4.16% relative to that on the reference days. The mean TAM₀.₆₅–₂.₁ concentration changed from (1.50 ± 1.37) × 10⁵ cells/m³ to (1.76 ± 1.36) × 10⁵ cells/m³, with TAM₀.₆₅–₁.₁ increasing from (7.91 ± 7.97) × 10⁴ cells/m³ to (1.76 ± 1.33) × 10⁵ cells/m³ on days with light fog days and medium fog, respectively. The modeling results showed that the majority of TAM₀.₆₅–₂.₁ deposition occurred in the extrathoracic (ET) region, followed by the alveolar (AL) region. When different populations were examined separately, the deposition doses (DDs) in adult females and in children ranked at the minimum value (6.19 × 10³ cells/h) and maximum value (1.08 × 10⁴ cells/h), respectively. However, the inhalation risks on polluted days, such as hazy, foggy and mixed hazy–foggy (HF) days, were still below the threshold for adverse impacts on human health.

Facing the challenge of global microplastics (MPs) pollution, full characterization of MPs biohazards is urgent. Recent intensive studies revealed that the toxicity depends on the material, size, and exposure concentration of MP. To better elucidate MPs biohazards, we investigated the impact of polystyrene-MPs of size 0.1 μm at a low dose of 50 μg/L on the neuromuscular, retinal, and reproductive phenotypes of fruit fly model, by voltage-clamped electrophysiology, electroretinogram, and reproductive assay, respectively. We found that MPs decreased the frequency of spontaneous junction currents of synapse and altered the receptor potential amplitude of the retina. Furthermore, MPs lowered the rate of embryo-laying of fruit flies. The differential gene expression of ligand-receptor interaction, endocytosis, phototransduction, and Toll/Imd signaling pathways might underlie these MPs-induced phenotypes. These findings call for further investigation on the potential biohazards of low-dose MPs.

One of the fundamental sustainable development goals has been recognized as having access to clean water for drinking purposes. In the Anthropocene era, rapid urbanization put further stress on water resources, and associated groundwater contamination expanded into a significant global environmental issue. Natural arsenic and related water pollution have already caused a burden issue on groundwater vulnerability and corresponding health hazard in and around the Ganges delta. A field based hydrogeochemical analysis has been carried out in the elevated arsenic prone areas of moribund Ganges delta, West Bengal, a part of western Ganga- Brahmaputra delta (GBD). New data driven heuristic algorithms are rarely used in groundwater vulnerability studies, specifically not yet used in the elevated arsenic prone areas of Ganges delta, India. Therefore, in the current study, emphasis has been given on integration of heuristic algorithms and random forest (RF) i.e., “RF-particle swarm optimization (PSO)”, “RF-grey wolf optimizer (GWO)” and “RF-grasshopper optimization algorithm (GOA)”, to identify groundwater vulnerable zones on the basis of field based hydrogeochemical parameters. In addition, correspondence health hazard of this area was assessed through human health hazard index. The spatial distribution of groundwater vulnerability revealed that middle-eastern and north-western part of the study area covered by very high and high, whereas central, western and south-western part are covered by very low and low vulnerability zones in outcomes of all the applied models. The evaluation result indicates that RF-GOA (AUC = 0.911) model performed the best considering testing dataset, and thereafter RF-GWO, RF-PSO and RF with AUC value is 0.901, 0.892 and 0.812 respectively. Findings also revealed the groundwater in this study region is quite unfavorable for drinking and irrigation purposes. The suggested models demonstrate their usefulness in foretelling sustainable groundwater resource management in various deltaic regions of the world through taking appropriate measures by policy-makers.

Exposure to endocrine disruptors such as bisphenols, can lead to and be the explanation for idiopathic infertility. In our study, we assessed the effect of exposure to bisphenol S (BPS) via breast milk on the testicular tissue health of adult male mice. Milking dams were exposed to BPS through drinking water (0.216 ng g bw/day and 21.6 ng g bw/day) from post-natal day 0–15. Although there was no significant difference in testicular histopathology between the control and experimental groups, we observed an increase in the number of tight and gap junctions in the blood-testis barrier (BTB) of adult mice after nursing BPS exposure. Moreover, there was an increase in oxidative stress markers in adult testicular tissue of mice exposed during nursing. Our nursing model indicates that breast milk is a route of exposure to an endocrine disruptor that can be responsible for idiopathic male infertility through the damage of the BTB and weakening of oxidative stress resistance in adulthood.

Globally distributed karstic soils are characterized by the high accumulation of heavy metal(loid)s, such as Cd. Biogeochemistries and transferability of metal(loid)s in such soils are notably different from that in soils of anthropogenic pollution as evidenced by increasing studies about rice and maize. To solve the question about metal(loid) background and transferability in the system of karstic soils and crops with underground fruits, we designedly collected 246 paired soil–peanut seed samples in a world-famous karstic region in Southwestern China covering an area of 98,700 km². The concentrations of eight regulatory metal(loid)s (Cd, As, Cr, Cu, Hg, Ni, Pb, and Zn) in soil samples exceeded current standards to different degrees, demonstrating a typical high background. However, the transferability of metal(loid)s from soils to peanut seeds is quite low, resulting in a low exceedance rate of metal(loid)s (Cd, 12.2% and Pb, 1.2%) in seeds (“seed metal(loid)s”), in accordance with the results that metal(loid)s in soils mostly distributed in the inert/residual fractions. Based on the distinct response characteristics of peanut seed metal(loid)s to soil status from rice/maize grain metals, a model was further developed for effectively predicting the concentration of Cd in peanut seeds. Collectively, this study provides a basis for the assessment of soil environmental quality and safety zoning of upland field in karst areas.

Biochar particles are extensively used in soil remediation and interact with microplastics (MPs), especially metal oxide-modified biochar may have stronger interactions with MPs. The mechanism of interactions between humic acid (HA) and different valence cations is different and the co-effect on the transport of MPs is not clear. In this study, the co-effects of HA and cations (Na⁺, Ca²⁺) on the transport and retention of MPs in saturated porous media with peanut shell biochar (PSB) and MgO-modified PSB (MgO-PSB) were systematically investigated. Breakthrough curves (BTCs) of MPs were fitted by the two-site kinetic retention model for analysis. In the absence of HA, the addition of PSB and MgO-PSB significantly hindered the transport of MPs in saturated porous media, and the retention of MPs increased from 34.2% to 59.1% and 75.5%, respectively. In Na⁺ solutions, the HA concentration played a dominant role in controlling MPs transport, compared to the minor role of Na⁺. The transport capacity of MPs always increased gradually with the increase of HA concentration. Whereas, in Ca²⁺ solutions, Ca²⁺ concentrations had a stronger effect than HA. The transport ability of MPs was instead greater than that in Na⁺ solutions as the HA concentration increased at low ionic strength (1 mM). However, the transport capacity of MPs was significantly reduced with increasing HA concentrations at higher ionic strength (10, 100 mM). The two-site kinetic retention model indicated that chemical attachment and physical straining are the main mechanisms of MPs retention in the saturated porous media.

Although dust storms have been associated with adverse health outcomes, studies on the burden of dust storms on deaths are limited. As global warming has induced significant climate changes in recent decades, which have accelerated desertification worldwide, it is necessary to evaluate the burden of dust storm-induced premature mortality using a critical measure of disease burden, such as the years of life lost (YLL). The YLL attributable to dust storms have not been examined to date. This study investigated the association between Asian dust storms (ADS) and the YLL in Seoul, South Korea, during 2002–2013. We conducted a time-series study using a generalized additive model assuming a Gaussian distribution and applied a distributed lag model with a maximum lag of 5 days to investigate the delayed and cumulative effects of ADS on the YLL. We also conducted stratified analyses using the cause of death (respiratory and cardiovascular diseases) and sociodemographic status (sex, age, education level, occupation, and marital status). During the study period, 108 ADS events occurred, and the average daily YLL was 1511 years due to non-accidental causes. The cumulative ADS exposure over the 6-day lag period was associated with a significant increase of 104.7 (95% CI, 31.0–178.5 years) and 34.4 years (4.0–64.7 years) in the YLL due to non-accidental causes and cardiovascular mortality, respectively. Sociodemographic analyses revealed associations between ADS exposure and the YLL in males, both <65 and ≥ 65 years old, those with middle-level education, and the unemployed, unmarried, and widowed (26.5–83.8 years). This study provides new evidence suggesting that exposure to dust storms significantly increases the YLL. Our findings suggest that dust storms are a critical environmental risk affecting premature mortality. These results could contribute to the establishment of public health policies aimed at managing dust storm exposure and reducing premature deaths.

Reliable long-horizon PM₂.₅ forecasts are crucial and beneficial for health protection through early warning against air pollution. However, the dynamic nature of air quality makes PM₂.₅ forecasts at long horizons very challenging. This study proposed a novel machine learning-based model (MCNN-BP) that fused multiple convolutional neural networks (MCNN) with a back-propagation neural network (BPNN) for making spatiotemporal PM₂.₅ forecasts for the next 72 h at 74 stations covering the whole Taiwan simultaneously. Model configuration involved an ensemble of massive hourly air quality and meteorological monitoring datasets and the existing publicly-available PM₂.₅ simulated (forecasted) datasets from an atmospheric chemical transport (ACT) model. The proposed methodology collaboratively constructed two CNNs to mine the observed data (the past) and the forecasted data from ACT (the future) separately. The results showed that the MCNN-BP model could significantly improve the accuracy of spatiotemporal PM₂.₅ forecasts and substantially reduce the forecast biases of the ACT model. We demonstrated that the proposed MCNN-BP model with effective feature extraction and good denoising ability could overcome the curse of dimensionality and offer satisfactory regional long-horizon PM₂.₅ forecasts. Moreover, the MCNN-BP model has considerably shorter computational time (5 min) and lower computational load than the compute-intensive ACT model. The proposed approach hits a milestone in multi-site and multi-horizon forecasting, which significantly contributes to early warning against regional air pollution.

Ambient particles with aerodynamic diameter <0.1 μm (PM₀.₁) have been suggested to have significant health impact. However, studies on the association between long-term PM₀.₁ exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006–2009 average PM₀.₁ concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM₀.₁ concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM₀.₁ concentration was associated with a 5.75 (95% Confidence interval, 3.24–8.25) mg/dl and a 6.05 (2.85–9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10–1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM₀.₁ exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.