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.

Many naturally seleniferous soils are faced with Cd contamination problem, which severely limits crop cultivation in these areas. Straw returning has been widely applied in agricultural production due to its various benefits to soil physicochemical properties, soil fertility, and crops yield. However, effects of straw application on the fates of Se and Cd in Cd-contaminated seleniferous soils remain largely unclear. Therefore, the effects of straw application on the fates of Se and Cd in Cd-contaminated seleniferous soils were investigated in this study. The results showed that iron reduction driven by Clostridium and Anaeromyxbacter was responsible for the variations in Se and Cd fates in soil. Straw application respectively increased the gene copy numbers of Clostridium and Anaeromyxbacter by 19.5–56.3% and 33.6–39.8%, thus promoting iron reductive dissolution, eventually resulting in a high release amount of Se and Cd from Fe(III) (oxyhydr) oxides. Under reducing conditions, the released Cd was adsorbed by the newly formed metal sulfides or reacted with sulfides to generate CdS precipitates. Straw application decreased the soil exchangeable Se and soil exchangeable Cd concentration during flooding phase. However, straw application significantly increased Se/Cd in soil solution which had the highest bioavailability during flooding. In addition, straw application increased soil exchangeable Se concentration, but it had no significant effects on soil exchangeable Cd concentration after soil drainage. Taken together, straw application increased Se bioavailability and Cd mobility. Therefore, straw application is an effective method for improving Se bioavailability, but it is not suitable for the application to Cd-contaminated paddy soils. In the actual agricultural production, straw could be applied in seleniferous soils to improve Se bioavailability. At the same time, straw application should be cautious to avoid the release of Cd from Cd-contaminated soil.

We measured the concentrations of cesium isotopes (¹³³Cs, ¹³⁴Cs, and ¹³⁷Cs) in zooplankton samples collected in waters off the east coast of Japan from May 2015 to June 2020. By combining these data with those obtained previously from May 2012 to February 2015, we evaluated the long-term impacts of the Fukushima Dai-ichi Nuclear Power Plant accident on marine zooplankton. Relatively high ¹³⁷Cs concentrations in zooplankton, exceeding 10 Bq/kg-dry weight, were sporadically observed until June 2016, regardless of year or station. After May–June 2017, ¹³⁷Cs concentrations decreased to below 1 Bq/kg-dry at most stations, and by May 2020, concentrations were below 0.5 Bq/kg-dry except those off Fukushima Prefecture. Since the accident, the ¹³⁷Cs/¹³³Cs atom ratios of zooplankton samples were higher than those of ambient seawater until 2019, but in May–June 2020 the ratios matched those of seawater except off Fukushima Prefecture. Highly radioactive particles were not detected in zooplankton samples by autoradiography using imaging plates after May–June 2017, although they were before. Therefore, the persistence of elevated ¹³⁷Cs/¹³³Cs ratios in zooplankton relative to seawater for nine years after the accident was probably due to the incorporation of highly radioactive particles (cesium-bearing particles or clay-mineral aggregates with highly adsorbed radiocesium) onto/into zooplankton for several years after the accident. However, since at least May–June 2017, these elevated ratios have likely been caused by small highly radioactive particles (or larger particles disaggregated into small pieces) entering the ocean from land via rivers or directly discharged from the Fukushima Nuclear Power Plant. Microplastics enriched with radiocesium with higher ¹³⁷Cs/¹³³Cs ratios than seawater may have also contributed ¹³⁷Cs to the zooplankton.

Ocean acidification (OA) and microplastics (MPs) contamination are two results of human excises. In regions like estuarine areas, OA and MPs exposure are happening at the same time. The current research investigated the synthesized effects of OA and MPs exposure for a medium-term duration on the physiology and energy budget of the thick shell mussel Mytilus coruscus. Mussels were treated by six combinations of three MPs levels (0, 10 and 1000 items L⁻¹) × two pH levels (7.3, 8.1) for 21 d. As a result, under pH 7.3, clearance rate (CR), food absorption efficiency (AE), respiration rate (RR), and scope for growth (SFG) significantly decreased, while the fecal organic dry weight ratio (E) significantly increased. 1000 items L⁻¹ MPs led to decrease of CR, E, SFG and increase of AE under pH 8.1. Interactive effects from combination of pH and MPs were found in terms of CR, AE, E and RR, but not for SFG of M. coruscus.

In the current investigation, we presented the success of the modified hydrothermal method for synthesizing the iron-oxide nanoparticles (Fe₂O₃-NPs) efficiently. These NPs were further characterized by using different techniques such as X-ray diffraction (XRD), scanning electron microscope (SEM) micrographs, energy-dispersive X-ray spectroscopy (EDAX)/Mapping pattern, Raman Spectroscopy Pattern, ultra violet (UV) and Photoluminescence (PL). All these analyses revealed highly pure nature of Fe₂O₃-NPs with no internal defects, and suggested its application for plant growth improvement. Therefore, we further investigated the separate as well as combined effects of the Fe₂O₃-NPs and citric acid (CA) in the alleviation of arsenic (As) toxicity in the soybean (Glycine max L.), by evaluating the different plant growth and metabolic attributes. Results of our study revealed that As-induced growth inhibition, reduction of photosynthesis, water use efficiency (WUE), and reactive oxygen species (ROS) accumulation whereas application of the Fe₂O₃-NPs and CA significantly reversed all these adverse effects in soybean plants. Moreover, the As-stress induced malondialdehyde (MDA) and hydrogen peroxide (H₂O₂) production were partially reversed by the Fe₂O₃-NPs and CA in the As-stressed plants by 16% and 10% (MDA) and 29% and 12% (H₂O₂). This might have resulted due to the Fe₂O₃-NPs and CA induced activities of the antioxidant defense in plants. Overall, the Fe₂O₃-NPs and CA supplementation separately and in combination positively regulated the As tolerance in soybean; however, the effect of the combined application on the As tolerance was more profound relative to the individual application. These results suggested the synergetic effect of the Fe₂O₃-NPs and CA on the As-tolerance in soybean. However, in-depth mechanism underlying the defense crosstalk between the Fe₂O₃-NPs and CA needs to be further explored.

Benzene is a common environmental carcinogen that induces leukemia. Studies suggest that metabolic disorder has a relationship with the toxicity of benzene. Pyruvate kinase M2 (PKM2) is a key rate-limiting enzyme in glycolysis. However, the upstream and downstream regulatory mechanisms of PKM2 in benzene-induced hematotoxicity and the therapeutic effects of targeting PKM2 in vivo are unclear. This study aims to provide insights into the new mechanism of benzene-induced hematotoxicity and reveal the therapeutic significance of targeting PKM2. Herein, we demonstrated that PKM2-dependent glycolysis contributes to benzene-induced hematotoxicity by regulating inflammation reaction. Mechanistically, acetylated proteomics revealed that 1,4-benzoquinone (1,4-BQ) induced acetylation of PKM2 at position K66, and this modification contributed to the increase of PKM2 expression and can be inhibited by inhibition of acetyltransferase GCN5. Meanwhile, the elevated PKM2 was shown to prompt the activation of nuclear phosphorylated Stat3 (p-Stat3) and IL17A. Clinically, pharmacological inhibition of PKM2 alleviated the blood toxicity induced by benzene, which was mainly characterized by an increase in routine blood parameters and improvement of hematopoietic imbalance. Besides, elevated PKM2 is a promising biomarker in people occupationally exposed to benzene. Overall, we identified PKM2/p-Stat3/IL-17A axis participates in the hematotoxicity of benzene, and targeting PKM2 has certain therapeutic implications in hematologic diseases.

The significant reduction in PM₂.₅ mass concentration after the outbreak of COVID-19 provided a unique opportunity further to study the formation mechanism of secondary inorganic aerosols. Hourly data of chemical components in PM₂.₅, gaseous pollutants, and meteorological data were obtained from January 1 to 23, 2020 (pre-lockdown) and January 24 to February 17, 2020 (COVID-lockdown) in Zhengzhou, China. Sulfate, nitrate, and ammonium were the main components of PM₂.₅ during both the pre-lockdown and COVID-lockdown periods. Compared with the pre-lockdown period, even though the concentration and proportion of nitrate decreased, nitrate was the dominant component in PM₂.₅ during the COVID-lockdown period. Moreover, nitrate production was enhanced by the elevated O₃ concentration, which was favorable for the homogeneous and hydrolysis nitrate formation despite the drastic decrease of NO₂. The proportion of sulfate during the COVID-lockdown period was higher than that before. Aqueous-phase reactions of H₂O₂ and transition metal (TMI) catalyzed oxidations were the major pathways for sulfate formation. During the COVID-lockdown period, TMI-catalyzed oxidation became the dominant pathway for aqueous-phase sulfate formation because the elevated acidity favored the dissolution of TMI. Therefore, the enhanced TMI-catalyzed oxidation affected by the elevated particle acidity dominated the sulfate formation, resulting in the slight increase of sulfate concentration during the COVID-lockdown period in Zhengzhou.

Metals may affect adversely cardiovascular system, but epidemiological evidence on the associations of priority-controlled metals including antimony (Sb), arsenic (As), cadmium, lead, and thallium with children's blood pressure (BP) was scarce and inconsistent. We conducted two panel studies with 3 surveys across 3 seasons among 144 and 142 children aged 4–12 years in Guangzhou and Weinan, respectively. During each seasonal survey, urine samples were collected for 4 consecutive days and BP was measured on the 4th day. We obtained 786 BP values and urinary metals measurements at least once within 4 days, while 773, 596, 612, and 754 urinary metals measurements were effective on the health examination day (Lag 0), and the 1ˢᵗ, 2ⁿᵈ, and 3ʳᵈ day preceding BP measurement (Lag 1, lag 2 and lag 3), respectively. We used linear mixed-effect models, generalized estimating equations and multiple informant models to assess the associations of individual metal at each lag day and accumulated lag day (4 days averaged, lag 0–3) with BP and hypertension, and Bayesian Kernel Machine Regression to evaluate the relations of metals mixture at lag 0–3 and BP outcomes. We found Sb was positively and consistently related to systolic BP (SBP), mean arterial pressure (MAP), and odds of having hypertension within 4 days, which were the strongest at lag 0 and declined over time. And such relationships at lag 0–3 showed in a dose-response manner. Meanwhile, Sb was the only contributor to the relations of mixture with SBP, MAP, and odds of having hypertension. Also, synergistic interaction between Sb and As was significant. In addition, modification effect of passive smoking status on the association of Sb and SBP was more evident in passive smokers. Accordingly, urinary Sb was consistently and dose-responsively associated with increased BP and hypertension, of which Sb was the major contributor among children.

A drastic decrease in the suspended sediment of Dongting Lake (DTL) has been observed due to Three Gorges Dam (TGD) impoundment operation since 2003. However, the relationship between sediment loads and metal fluxes has not been studied. This study comprehensively analyzed the content characteristics of seven metal(loid)s (As, Cd, Cr, Cu, Hg, Pb, and Zn) in the surface sediment of DTL from 2000 to 2019. The period of 2005–2009 corresponded to a metal(loid) enrichment stage in the sediment of DTL. The metal(loid) cumulative input of DTL from 2000 to 2019 reached 153 × 10³ t, and the increasing rate was gradually diminished because of TGD operation, while the metal(loid) cumulative output reached 132 × 10³ t. Undergoing an input-output state transition, the metal(loid) cumulative deposition of DTL in 2019 was only 42% of its peak in 2007. Especially, the metal(loid) fluxes of DTL all became negative for the first time in 2006. It is worth noting that Cd in DTL has shifted to a net export during the study period. Finally, the assessment results of pollution, risk, and toxicity indicated that metal(loid) effects on sediment quality were weakening in recent years. This study confirmed that DTL has shifted from metal(loid) deposition to export, providing new information for future DTL management options.

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.