Exposure of the general population to airborne metals remains poorly estimated despite the potential health risks. Passive moss biomonitoring can proxy air quality at fine resolution over large areas, mainly in rural areas. We adapted the technique to urban areas to develop fine concentration maps for several metals for Constances cohort's participants. We sampled Grimmia pulvinata in 77 and 51 cemeteries within ∼50 km of Paris and Lyon city centers, respectively. We developed land-use regression models for 14 metals including cadmium, lead, and antimony; potential predictors included the amount of urban, agricultural, forest, and water around cemeteries, population density, altitude, and distance to major roads. We used both kriging with external drift and land use regression followed by residual kriging when necessary to derive concentration maps (500 × 500 m) for each metal and region. Both approaches led to similar results. The most frequent predictors were the amount of urban, agricultural, or forest areas. Depending on the metal, the models explained part of the spatial variability, from 6% for vanadium in Lyon to 84% for antimony in Paris, but mostly between 20% and 60%, with better results for metals emitted by human activities. Moss biomonitoring in cemeteries proves efficient for obtaining airborne metal exposures in urban areas for the most common metals.

Exposure to metals has been linked with the risk of hypertensive disorders of pregnancy (HDP), but little is known about the potential effects of exposure to metal mixtures. Thus, our study aimed to investigated the impact of a complex mixture of metals on HDP, especially the interactions among metal mixtures. We did a population-based nested case-control study from October 2013 to October 2016 in Wuhan, China, including 146 HDP cases and 292 controls. Plasma concentrations of Aluminum (Al), Barium (Ba), Cobalt (Co), Copper (Cu), Lead (Pb), Mercury (Hg), Molybdenum (Mo), Nickel (Ni), Selenium (Se), Strontium (Sr), Thallium (Tl), and Vanadium (V) were measured and collected between 10 and 16 gestational weeks. We employed quantile g-computation, conditional logistic regression models, and Bayesian Kernel Machine Regression (BKMR) to assess the association of individual metals and metal mixtures with HDP risk. In the quantile g-computation, the OR for a joint tertile increase in plasma concentrations was 3.67 (95% CI: 1.70, 7.91). Hg contributed the largest positive weights and followed by Al, Ni, and V. In conditional logistic regression models, concentrations of Hg, Al, Ni, and V were significantly associated with the risk of HDP (p-FDR < 0.05). Compared to the lowest tertiles, the ORs (95% CI) for the highest tertiles of these four metals were 2.67 (1.44, 4.95), 3.09 (1.70, 5.64), 5.31 (2.68, 10.53), and 4.52 (2.26, 9.01), respectively. In the BKMR analysis, we observed a linear positive association between Hg, Al, V, and HDP, and a nonlinear relationship between Ni and HDP. A potential interaction between Al and V was also identified. We found that exposure to metal mixtures in early pregnancy, both individually and as a mixture, was associated with the risk of HDP. Potential interaction effects of Al and V on the risk of HDP may exist.

Aging is a leading cause of mortality for the elderly and DNA methylation age is reported to be predictive of biological aging. However, few studies have investigated the associations between multiple metals exposure and accelerated aging in the elderly. We performed a pilot study of 288 elderly participants aged 50–115 years and measured genome-wide DNA methylation and 22 blood metals concentrations. Measures of DNA methylation age were estimated using CpGs from Illumina HumanMethylation EPIC BeadChip. Linear mixed regression and Bayesian kernel machine regression (BKMR) models were used to estimate the individual and overall associations between multiple metals and accelerated methylation aging. Single metal models revealed that each 1-standard deviance (SD) increase in log-transformed vanadium, cobalt, nickel, zinc, arsenic, and barium was associated with a −2.256, −1.318, 1.004, −1.926, 1.910 and −1.356 changes in ΔAge, respectively; meanwhile, for aging rate, the change was −0.019, −0.013, 0.010, −0.018, 0.023, and −0.012, respectively (all P < 0.05). The BKMR models showed reverse U-shaped associations of the overall metals mixture with ΔAge and aging rate. Downward trends of ΔAge and aging rate were observed for increasing quantiles of essential metals mixture, but upward trends were observed for non-essential metals mixture. Further individual analysis of the BKMR revealed that the 95% confidence interval of ΔAge and aging rate associated with vanadium, zinc, and arsenic did not cross 0, when other metals concentrations set at 25th, 50th, and 75th percentile. Our findings suggest reverse U-shaped associations of the overall metals mixture with accelerated methylation aging for the first time, and vanadium, zinc, and arsenic may be major contributors driving the associations.

Water pollution is one of the main challenges and water crises, which has caused the existing water resources to be unusable due to contamination. To understand the determinants of the distribution and abundance of antibiotic resistance genes (ARGs), we examined the distribution of 22 ARGs in relation to habitat type, heavy metal pollution and antibiotics concentration across six lakes and wetlands of Iran. The concentration of 13 heavy metals was determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES) by Thermo Electron Corporation, and five antibiotics by online enrichment and triple-quadrupole LC-MS/MS were investigated. We further performed a global meta-analysis to evaluate the distribution of ARGs across global lakes compared with our studied lakes. While habitat type effect was negligible, we found a strong correlation between waste discharge into the lakes and the abundance of ARGs. The ARGs abundance showed stronger correlation with the concentration of heavy metals, such as Vanadium, than with that of antibiotics. Our meta-analysis also confirmed that overuse of antibiotics and discharge of heavy metals in the studied lakes. These data point to an increase in the distribution of ARGs among bacteria and their increasing resistance to various antibiotics, implying the susceptibility of aquatic environment to industrial pollution.

The Tharsis mine is presently abandoned, but the past intense exploitation has left large dumps and other sulphide-rich mining wastes in the area generating acid mine drainages (AMD). The main goal of this work is to study the effect of hydrogeochemical processes, hydrological regime and the waste typology on the physicochemical parameters and dissolved concentrations of pollutants in a deeply AMD-affected zone. Extreme leachates are produced in the area, reaching even negative pH and concentrations of up to 2.2 g/L of As and 194 g/L of Fe. The results of the comparison of ore grades of sulphide deposits with dissolved concentrations in waters shows that Pb is the least mobile element in dissolution probably due to the precipitation of Pb secondary minerals and/or its coprecipitation on Fe oxyhydroxysulphates. Arsenic, Cr, and V are also coprecipitated with Fe minerals. Seasonal patterns in metal contents were identified: elements coming from the host rocks, such as Al, Mn and Ni, show their maximum values in the dry period, when dilution with freshwater is lower and the interaction of water-rock processes and evaporation is higher. On the other hand, As, Cr, Fe, Pb and V show minimum concentrations in the dry period due to intense Fe oxyhydroxysulphate precipitation. In this sense, large sulphide rich waste heaps would be a temporal sink of these elements (i.e. Pb, As, Cr and V) in the dry period, and a significant source upon intense rainfalls.

Whereas the adverse effects of vanadium released from smelting activities on soil microbial ecology have been widely recognized, little is known about spatiotemporal vanadium distribution and microbial community dynamics in typical contaminated sites. This study describes vanadium contents associated with health risk and microbial responses in both topsoil and subsoil during four consecutive seasons around an ongoing-production smelter in Panzhihua, China. Higher levels of vanadium concentration exceeding soil background value in China (82 mg/kg) were found close to the smelter. Vanadium concentrations decreased generally with the increase in distance to the smelter and depth below surface, as soil vanadium pollution is induced mainly by atmospheric deposition of vanadium bearing dust during smelting. Residual fraction was the predominated vanadium form in soils, with pronounced increase in bioavailable vanadium during rainfall period due to frequent drought-rewetting process. Topsoil close to the smelter exhibited significant contamination, inducing high probability of adverse health effects. Spatiotemporal vanadium distribution creates filtering effects on soil microorganisms, promoting metal tolerant genera in topsoil (e.g. Microvirga) and subsoil (e.g. Bacillus, Geobacter), which is the key in maintaining the community structure by promoting cooperative relation with other taxa. Our results reveal spatiotemporal vanadium distribution in soils at site scale with potential health risk and microbial responses, which is helpful in identifying severe contamination and implementing bioremediation.

Exposure to environmental metals has been reported to be associated with airway inflammation. Fractional exhaled nitric oxide (FeNO) is an important inflammatory biomarker of the airway. However, the associations between metal exposures and FeNO change and the underlying mechanisms remain unclear. To investigate the associations between urinary metals and FeNO, and the potential role of Club cell secretory protein (CC16), a lung epithelial biomarker, in these associations. We conducted a cross-sectional study from the Wuhan-Zhuhai cohort and measured eight urinary metals, plasma CC16 and FeNO among 3067 subjects by using inductively coupled plasma-mass spectrometry, enzyme-linked immunosorbent assay kit and Nano Coulomb Nitric Oxide Analyzer, respectively. Mixed linear models were used to quantify dose-relationships between urinary metals and FeNO, as well as urinary metals and plasma CC16. The potential role of plasma CC16 in the associations between urinary metals and FeNO was estimated using mediationanalyses. After adjusting for covariates, one percent increase in urinary vanadium, nickel or antimony was associated with a respective 6.60% (95% CI: 3.52%, 9.68%), 2.18% (0.45%, 3.91%), 4.87% (1.47%, 8.27%) increase in FeNO level. The adverse associations were much stronger among participants with low concentration of plasma CC16 than those with high CC16 level. Moreover, plasma CC16 decreased monotonically with increasing quartiles of urinary vanadium, nickel or antimony. Mediation analyses found that CC16 mediated the associations between urinary metals and FeNO by 5.64%, 39.06% and 25.18% for vanadium, nickel and antimony respectively. CC16 plays an important role in airway inflammation. General population with lower plasma CC16 concentration is more likely to suffer from airway inflammation when exposed to high levels of vanadium, nickel or antimony.

Huelva is a highly industrialized city in SW Spain hosting, among others, a Cu smelter, a phosphate fertilizer plant, a power plant, and oil refineries. This study aims to evaluate metal concentrations in lichens as bioindicators of atmospheric pollution in the impacted urban areas. Xanthoria parietina species from Huelva and nearby villages, as well as reference samples from remote, non-contaminated urban areas, were analyzed for trace elements (V, Cr, Mn, Co, Ni, Cu, Zn, Sr, As, Cd, Sb, Cs, Ba, La, Ce, Pr, Nd, Sm, Er, Tm, Yb, Lu, Pb, Th, U) using Inductively Coupled Plasma-Mass Spectrometry; and for major elements (Ca, K, Mg, P, and S) by Inductively Coupled Plasma-Optical Emission Spectrometry after acid digestion.The metal composition of X. parietina exhibits spatial distribution patterns with extremely elevated concentrations (Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Pb, U, and S) in the surroundings of the industrial estates to <1 km distance. Mean concentrations were significantly lower in the urban areas >1 km from the pollution sources. However, air pollution persists in the urban areas up to 4 km away, as the mean concentrations of Cu, Zn, As, Cd, Sb and S remained considerably elevated in comparison to the reference samples. Though rigorous source apportionment analysis was not the aim of this study, a good positive correlation of our results with metal abundances in ambient particulate matter and in pollution sources points to the Cu smelter as the main source of pollution. Hence, the severe air pollution affecting Huelva and nearby urban areas may be considered a serious health risk to local residents.

Substantial evidence has linked short-term exposure to ambient fine particulate matter (PM2.5) with increased cardiovascular mortality, however, the specific chemical constituent and emission source responsible for this effect remained largely unclear. A time series Poisson model was employed to quantify the association of cardiovascular mortality with two sets of shipping pollution emission: nickel (Ni), vanadium (V) (the indices of shipping emission) and estimated shipping emission using a source apportionment approach in Guangzhou, China in 2014. We observed that Ni, V, and estimated shipping emission in PM2.5 were associated with increased cardiovascular mortality, an inter-quartile range (IQR) increase in lag2 Ni was associated with 4.60% (95% CI: 0.14%, 9.26%) increase in overall cardiovascular mortality, and 13.35% (95% CI: 5.54%, 21.75%) increase in cerebrovascular mortality; each IQR increase of lag1 V was correlated with 6.01% (95% CI: 1.83%, 10.37%) increase in overall cardiovascular mortality, and 11.02% (95% CI: 3.15%, 19.49%) increase in cerebrovascular mortality; and each IQR increase in lag1 shipping emission was associated with 5.55% (95% CI: 0.78%, 10.54%) increase in overall cardiovascular mortality, and 10.39% (95% CI: 1.43%, 20.14%) increase in cerebrovascular mortality. The results remained robust to adjustment for PM2.5 mass and gaseous air pollutants. This study suggests that shipping emission is an important detrimental factor of cardiovascular mortality, and should be emphasized in air pollution control and management in order to protect the public health in Guangzhou, China.

Potentially toxic elements are widespread soil contaminants, whose occurrence could entail a concern for human health upon ingestion of fruit and vegetables harvested in a polluted area. This work set out to evaluate the concentrations of lead and cadmium as well as the levels of thirteen heavy metals for which a limit value is yet to be established by the food safety authorities, in order to perform a risk characterization related to the dietary intake of these metals and to provide a scientific opinion with wider relevance in the light of current worldwide regulatory issues. The sampling consisted of fruit and vegetables grown in a potentially contaminated area of southern Italy due to the illegal dump of hazardous wastes. An evaluation of the dietary exposure through the calculation of the Hazard Index (HI), the Maximum Cumulative Ratio (MCR) and the Target Cancer Risk (TCR) was adopted to this end. The results revealed that about the 30% of samples showed quantifiable levels of chemicals and no significant difference emerged between the potentially polluted area and the nearby cities that were selected as a control landfill site. The overall risk characterization for non-carcinogenic endpoints showed that the HI did not reach unsafe values, except for a small number of samples mainly because of aberrant occurrences and, in any case, the cumulative toxicity was mainly driven by thallium and vanadium. As far as the carcinogenic effects of arsenic are concerned, the distribution of TCR values broadly lay below the safety threshold; a certain percentage of data, however, exceeded this limit and should be taken into account for the enforcement of future regulatory thresholds.