Risk assessment and early warning of the presence of heavy metal pollution in strawberries

Biomonitoring of firefighters' exposure to priority pollutant metal(loid)s during wildland fire combat missions: Impact on urinary levels and health risks

Wildland firefighters are exposed to metal(loid)s released during wildfires through vegetation combustion, which also promotes remobilization of accumulated anthropogenic metal(loid)s. Studies biomonitoring metal(loid)s exposure promoted exclusively by wildfire suppression activities are lacking. This work aimed to characterize, for the first time, the impact of real-life wildland firefighting operations on urinary levels of priority pollutant metal(loid)s [14 included in ATSDR, 11 in USEPA, and 4 in Human Biomonitoring for Europe Initiative priority lists] in firefighters. Spot urines were sampled pre-exposure (105 non-smokers, 76 smokers) and post-exposure to firefighting activities (20 non-smokers, 25 smokers); among those, paired samples were collected from 14 non-smoking and 24 smoking firefighters. Smokers displayed significantly higher baseline levels of zinc (28 %), lithium (29 %), cadmium (55 %), rubidium (13 %), and copper (20 %) than non-smokers. Following wildfire suppression, the concentration of the WHO potentially toxic metal(loid)s rose from 2 % to 3 % in smokers and 2 % to 5 % in non-smokers (up to 4 % for all firefighters and up to 5 % in paired samples). Levels of nickel (33-53 %), antimony (45-56 %), and cesium (40-47 %) increased significantly post-exposure in non-smokers (in all firefighters and in paired samples), whose urinary concentrations were generally more impacted by wildfire emissions than those of smokers. Arsenic (80 %) displayed the only significant increase post-exposure in smokers, being the best discriminant of exposure to wildfire emissions in these subjects. Significant positive correlations were found for age and/or career length with cadmium, lead, barium, strontium, and mercury, and for body mass index with arsenic. The reference/guidance values were exceeded for arsenic, zinc, cesium, nickel, antimony, cadmium, lead, thallium, mercury, copper, and cobalt in 1-90 % of firefighters suggesting augmented health risks due to wildfire combating and emphasizing the need of mitigation strategies. This study also provides biomonitoring data to help setting reference values for the occupationally exposed part of population.

Association of exposure to multiple metals with hemoglobin levels in Chinese children and adolescents

BACKGROUND

Previous studies have linked single metal to hemoglobin levels in children and adolescents; however, studies with regards to metal mixtures are still limited.

OBJECTIVE

We aimed to investigate the associations of single metal and metal mixtures with hemoglobin levels in children and adolescents.

METHODS

We conducted a cross-sectional study of 2064 children and adolescents aged 6 to 19 years in Liuzhou, China in 2018. The concentrations of 15 metals in urine were determined by inductively coupled plasma mass spectrometry. Generalized linear regression and weighted quantile sum (WQS) regression were used to estimate the associations of single metal and metal mixtures with hemoglobin levels, respectively.

RESULTS

The multivariable-adjusted β-values for the highest versus the first quartiles of urinary metal concentrations were - 1.57 (95 % confidence interval [CI]: -3.01, -0.13) for chromium, -2.47 (95 % CI: -3.90, -1.05) for nickel and 1.88 (95 % CI: 0.49, 3.28) for copper. In addition, we found a significant negative association between the WQS index and hemoglobin levels (adjusted β = -0.93, 95 % CI: -1.69, -0.19), with nickel contributing the most to the WQS index at 59.0 %. Subgroup analyses showed that exposure to urinary nickel or metal mixtures were associated with decreased hemoglobin levels in adolescents, but not in children (all Pinteration < 0.001).

CONCLUSION

Among children and adolescents, urinary chromium and nickel concentrations were associated with decreased hemoglobin levels, while copper showed a positive relationship. Moreover, a negative association was observed between exposure to metal mixtures and hemoglobin levels. These findings need to be further validated in prospective studies.

Hybrid machine learning approach integrating GMDH and SVR for heavy metal concentration prediction in dust samples

In agricultural regions prone to dust storms, heavy metal contamination of soil and crops from airborne particulates poses significant risks to food safety and public health. This study has assessed the potential of machine learning models for predicting concentrations of toxic heavy metals like arsenic, chromium, and lead in dust from the agricultural Sistan region of southeastern Iran. This region experiences frequent dust storms mobilizing particulates from local dried lakes onto agricultural lands. The metals including nickel, copper, magnesium, cobalt, zinc, chromium, arsenic, and lead were measured in summer dust samples during 2012-2018 across 15 stations. Two hybrid models were developed combining group method of data handling (GMDH) and support vector regression (SVR) machine learning with harmony search optimization (H) so as to predict toxic metals arsenic, chromium, and lead using nickel, copper, magnesium, cobalt, and zinc inputs. Standard error maps were uncertainty higher in southern and western areas, and they are most impacted by dust storms. Results demonstrated that the hybrid GMDH + H and SVR + H models improved the accuracy of individual GMDH and SVR models in predicting heavy metals. The GMDH + H model performed the best for the lead with an agreement index (d-index) of 0.98, root mean square error (RMSE) of 2.87 ppm, normalized RMSE (NRMSE) of 0.12, and coefficient of determination (RR) of 0.96. The SVR + H model showed the highest accuracy for arsenic and chromium, obtaining d-index 0.96, RMSE 0.47 ppm, NRMSE 0.09, and RR 0.92 for arsenic, and d-index 0.96, RMSE 11.24 ppm, NRMSE 0.16, and RR 0.93 for chromium. Taylor's diagram and heatmap analysis confirmed the superiority of the hybrid techniques. This work demonstrates the utility of state-of-the-art computing for addressing complex environmental health challenges.

Ecological and health risk assessments of heavy metals and their accumulation in a peanut-soil system

Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil and peanut kernel paired samples across China. Soil As and Cd posed the greatest pollution risk with 47.1% and 17.6% of soil samples exceeding the risk screen levels, respectively, with 26.5% and 20.6% of the soil sites at relatively strong potential ecological risk level, respectively, and with the geo-accumulation levels at several soil sites in the uncontaminated to moderately contaminated categories. About 35.29% and 2.94% of soil sites were moderately and severely polluted based on Nemerow comprehensive pollution index, respectively, and a total of 32.4% of samples were at moderate ecological hazard level based on comprehensive potential ecological risk index values. The Cd, Cr, Ni, and Cu contents exceeded the standard in 11.76, 8.82, 11.76 and 5.88% of the peanut kernel samples, respectively. Soil metals posed more health risks to children than adults in the order As > Ni > Cr > Cu > Pb > Zn > Cd for non-carcinogenic health risks and Ni > Cr ≫ Cd > As > Pb for carcinogenic health risks. The soil As non-cancer risk index for children was greater than the permitted limits at 14 sites, and soil Ni and Cr posed the greatest carcinogenic risk to adults and children at many soil sites. The metals in peanut did not pose a non-carcinogenic risk according to standard. Peanut kernels had strong enrichment ability for Cd with an average bio-concentration factor (BCF) of 1.62. Soil metals contents and significant soil properties accounted for 35-74% of the variation in the BCF values of metals based on empirical prediction models.

Fractionation of metals in soil for strawberry cultivation: Effect on metal migration in food chain and application in risk assessment

Although trace metals in strawberry production system have attracted growing attention, little is known about metal fractionation in soil for strawberry cultivation. We hypothesized that the metal fractions in soil influenced by strawberry production had significant effect on food chain transport of metals and their risk in soil. Here, samples of strawberries and soil were gathered in the Yangtze River Delta, China to verify the hypothesis. Results showed that the acid-soluble Cr, Cd, and Ni in soil for strawberry cultivation were 21.5%-88.3% higher than those in open field soil, which enhanced uptake and bioaccessible levels of these metals in strawberries. Overall, the ecological, mobility, and health risks of Pb, Zn, Ni, and Cu in soil were at a low level. However, the ecological risk of bioavailable Cd, mobility risk of Cd, and cancer risk of bioavailable Cr in over 70% of the soil samples were at moderate, high, and acceptable levels, respectively. Since the increased acid-soluble Cr and Ni in soil were related to soil acidification induced by strawberry production, nitrogen fertilizer application should be optimized to prevent soil acidification and reduce transfer of Cr and Ni. Additionally, as Cd and organic matter accumulated in soil, the acid-soluble Cd and the ecological and mobility risks of Cd in soil were enhanced. To decrease transfer and risk of Cd in soil, organic fertilizer application should be optimized to mitigate Cd accumulation, alter organic matter composition, and subsequently promote the transformation of bioavailable Cd into residual Cd in soil.

Pollution indices of selected metals in tea (Camellia sinensis L.) growing soils of the Upper Assam region divulge a non-trifling menace of National Highway

The study investigated the influence of a National Highway (NH) traversing tea estates (TEs) on heavy metal (HM) contamination in the top soils of Upper Assam, India. The dispersion and accumulation of six HMs, viz. cadmium (Cd), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn), within tea-growing soils were assessed using diverse indices: contamination factor (CF), degree of contamination (DC), enrichment factor (EF), geo-accumulation index (Igeo), modified degree of contamination (MDC), Nemerow pollution index (PINemerow), pollution load index (PLI), potential ecological risk factor (Eri), and potential ecological risk index (RI). The order of HM prevalence was Fe > Mn > Zn > Ni > Cu > Cd. Elevated Cd levels near the NH prompted immediate attention, while Cd and Zn showed moderate pollution in CF, EF, and RI. The remaining metals posed minimal individual risk (Eri< 40), resulting in an overall contamination range of "nil to shallow," signifying slight contamination from the studied metals. From MDC values for investigated metals, it was found to be "zero to very low degree of contamination" at all locations except the vicinity of NH. Soil pollution, as determined by PLI, indicated unpolluted soils in both districts, yet PINemerow values indicated slight pollution. The statistical analysis revealed that there is a significant decrease in most of the indices of HM as the distance from NH increases. The application of multivariate statistical techniques namely Principal Component Analysis and Cluster Analysis showed the presence of three distinct homogenous groups of distances based on different indices. This investigation underscores NH-associated anthropogenic effects on TE soil quality due to HM deposition, warranting proactive mitigation measures.

Accumulation, migration and health risk of trace metals in a soil-strawberry-human system of the Yangtze River Delta region, China

Growing concern has been paid to metals in soil-strawberry system. In contrast, few attempts have been made to investigate bioaccessible metals in strawberries and further assess health risk based on bioaccessible metals. Moreover, the connections between soil parameters (e.g. soil pH, organic matter (OM), total and bioavailable metals) and metal transfer in soil-strawberry-human system still need to be systematically investigated as well. Considering that strawberries are extensively grown under plastic-shed conditions in China, a total of 18 paired plastic-shed soil (PSS) and strawberry samples were taken from the strawberry bases located in the Yangtze River Delta of China as a case study to assess accumulation status, migration and health risk of Cd, Cr, Cu, Ni, Pb, and Zn in the PSS-strawberry-human system. Overall, heavy application of organic fertilizers induced accumulation and contamination of Cd and Zn in PSS. In particular, 55.6% and 44.4% of PSS samples had considerable and moderate ecological risk caused by Cd, respectively. Despite no metal pollution in strawberry, PSS acidification mainly caused by high nitrogen input promoted Cd and Zn uptake by strawberry and enhanced bioaccessible concentrations of Cd, Cu, and Ni. In contrast, the increased soil OM caused by organic fertilizer application decreased Zn migration in PSS-strawberry-human system. Additionally, bioaccessible metals in strawberries induced limited non-cancer and cancer risk. To mitigate accumulation of Cd and Zn in PSS and metal transfer in the food chain, feasible fertilization strategies should be developed and carried out.

Heavy metal contamination and risk assessment in winter jujube (Ziziphus jujuba Mill. cv. Dongzao)

Winter jujube (Ziziphus jujuba Mill. cv. Dongzao) is a major fresh-eating jujube fruit with various important nutrients for humans. It can absorb heavy metals from polluted air, water and soils and applied pesticides, which may pose potential threats to consumers. Here, to evaluate the content of heavy metals in winter jujube and systematically evaluate the potential risks, we collected 212 winter jujube samples from four main producing areas in China and determined the contents of eight heavy metals (Cd, Cr, Pb, Ni, Cu, Zn, As, and Mn) using inductively coupled plasma mass spectrometer (ICP-MS). Based on the integrated pollution index (IPI) evaluation standard, more than 99.06% of samples were at safe levels. Moreover, clustering analysis divided the eight heavy metals into four groups, namely Cr/Ni, Cd/Pb, Cu/Mn/Zn, and As. Importantly, none of the analyzed heavy metals posed risks to adults as indicted by the average carcinogenic and non-carcinogenic risks. Notably, Cr and Cd could pose low carcinogenic risks to children (≤12 age group) when their concentration reached the 90^th percentile. This study systematically assessed the health risks associated with heavy metal intake through winter jujube consumption and highlighted the necessity of constant heavy metal monitoring in winter jujube.