A total of 45 children's toys and jewelry were tested for total and bioaccessible metal concentrations. Total As, Cd, Sb, Cr, Ni, and Pb concentrations were 0.22–19, 0.01–139, 0.1–189, 0.06–846, 0.14–2894 and 0.08–860,000 mg kg−1. Metallic products had the highest concentrations, with 3–7 out of 13 samples exceeding the European Union safety limit for Cd, Pb, Cr, or Ni. However, assessment based on hazard index >1 and bioaccessible metal showed different trends. Under saliva mobilization or gastric ingestion, 11 out of 45 samples showed HI >1 for As, Cd, Sb, Cr, or Ni. Pb with the highest total concentration showed HI <1 for all samples while Ni showed the most hazard with HI up to 113. Our data suggest the importance of using bioaccessibility to evaluate health hazard of metals in children's toys and jewelry, and besides Pb and Cd, As, Ni, Cr, and Sb in children's products also deserve attention.

Rapid monitoring and discriminating different anthropogenic pollution is a key scientific issue. To detect the applicability and sensitivity of magnetic measurements for evaluating different industrial pollution in urban environment, characteristics of topsoil from three typical fast developing industrial cities (Jinchang, Baiyin and Jiayuguan in Gansu province, northwestern China) were studied by magnetic and geochemical analyses. The results showed that magnetic susceptibility was enhanced near industrial areas, and PSD-MD magnetite dominated the magnetic properties. Magnetic concentration parameters (χlf, SIRM, and χARM) showed different correlations with heavy metals and PLI in the three cities, indicating significantly different magnetic response to different pollution sources. Principal component analysis showed that ferrimagnetic minerals coexist with heavy metals of Fe, As, Cu, Pb, and Zn in Baiyin and Fe, V, Cu, Mn, Pb, and Cr in Jiayuguan. Fuzzy cluster analysis and regression analysis further indicated that the sensitivity of magnetic monitoring to fuel dust is higher than that to mineral dust near non-ferrous metal smelters, and fossil fuel consumption is an important factor for increasing magnetite content. In all the three cities, the sensitivity of magnetic monitoring to pollutants from steel plants is much higher than that from non-ferrous metal plants. Therefore, magnetic proxies provide a rapid means for detecting heavy metal contamination caused by multi-anthropogenic pollution sources in a large scale area, however, the sensitivity was controlled by pollution sources.

We showed that 2.1% of 233 pieces of lumber debris after the Great East Japan Earthquake was chromated copper arsenate (CCA)-treated wood. Since hexavalent chromium (Cr), copper (Cu) and pentavalent arsenic (As) in the debris may be diffused in the air via incineration, we exposed human lung normal (BEAS-2B) and carcinoma (A549) cells to Cr, Cu and As at the molar ratio in a representative CCA-treated wood. Co-exposure to 0.10 μM Cr and 0.06 μM As, which solely had no effect on colony formation, synergistically promoted colony formation in BEAS-2B cells, but not A549 cells, with activation of the PI3K/AKT pathway. Sole exposure and co-exposure to Cu showed limited effects. Since previous reports showed Cr and As concentrations to which human lungs might be exposed, our results suggest the importance to avoid diffusion of Cr and As in the air via incineration of debris including CCA-treated wood after the disaster.

Actual measure-based studies have estimated ingestion rate of moderate and high daily use to female college students and career women in northeast of China. Sequential extraction analyses showed that total bioaccessible metals concentration in lipstick ranged from 2.103 to 31.103 μg/g and in lip balm ranged from 0.100 to 3.716 μg/g. The relationship between total bioaccessible metal concentrations and the cost of lip cosmetics showed a negative correlation. Lead was detected in all 30 products (100%), with an average concentration of 0.346 for lip balm and 0.407 μg/g for lipstick. With the exception of chromium content in three lipsticks, the estimated exposure in female college students and career women to target metals via lipstick and lip balm ingestion (calculated for moderate and high use) were much lower than the acceptable reference limits. The findings strongly emphasize the need to focus on the health risk of lip balm.

Field crops represent one of the highest contributions to dietary metal exposure. The aim of this study was to develop specific regression models for the uptake of metals into various field crops and to compare the usability of other available models. We analysed samples of potato, hop, maize, barley, wheat, rape seed, and grass from 66 agricultural sites. The influence of measured soil concentrations and soil factors (pH, organic carbon, content of silt and clay) on the plant concentrations of Cd, Cr, Cu, Mo, Ni, Pb and Zn was evaluated. Bioconcentration factors (BCF) and plant-specific metal models (PSMM) developed from multivariate regressions were calculated. The explained variability of the models was from 19 to 64% and correlations between measured and predicted concentrations were between 0.43 and 0.90. The developed hop and rapeseed models are new in this field. Available models from literature showed inaccurate results, except for Cd; the modelling efficiency was mostly around zero. The use of interaction terms between parameters can significantly improve plant-specific models.

We assessed the level of atmospheric contamination by S, N and metals before, during and after the installation of a new thermoelectric plant that provides power to an oil refinery in Cubatão, SE Brazil. We measured the foliar accumulation in Lolium multiflorum “Lema” with the aim of evaluating risks to the Atlantic Rainforest that grows in the region. Al, Co, Cr, Cu, K, N, Ni, S, V and Zn were appropriate markers of the new air contamination profile associated with the modern technology. With the exception of V, the leaf contents of these elements significantly increased between the pre-operation to post-operation phases (Al, Co, N, K, S), or only during the transition phase (Zn, Cu, Cr, Ni), and returned to the previous levels after the total shutdown of the old system. Therefore, the expected environmental gain was not achieved with the installation of the new technology.

Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation study in river sediments revealed that exchangeable, reducible and oxidizable fractions were dominant in all the studied metals (Cr, Ni, Cu, Zn, Cd, Pb) except Mn and Fe. High pollution load index (1.64–3.89) recommends urgent need of mitigation measures. Self-organizing Map-Artificial Neural Network (SOM-ANN) was applied to the data set for the prediction of major point sources of pollution in the river Ganga.

This study was conducted to identify and quantify the sources of selected volatile organic compounds (VOCs) and fine particulate matter (PM2.5) by using a partially constrained source apportionment model suitable for multiple time resolution data. Hourly VOC, 12-h and 24-h PM2.5 speciation data were collected during three seasons in 2013. Eight factors were retrieved from the Positive Matrix Factorization solutions and adding source profile constraints enhanced the interpretability of source profiles. Results showed that the evaporative emission factor was the largest contributor (25%) to VOC mass concentration, while the largest contributor to PM2.5 mass concentration was soil dust/regional transport related factor (26%). In terms of risk prioritization, traffic/industry related factor was the major cause for benzene, ethylbenzene, Cr, and polycyclic aromatic hydrocarbons (29–69%) while petrochemical related factor contributed most to the Ni risk (36%). This indicated that a larger contributor to mass concentration may not correspond to a higher risk.

Based on multiple geo-accumulation indices and correlation and partial redundancy analyses, we examined the spatial patterns of agricultural soil contaminations for As, Pb, Cd, Cr, and Ni in the Pearl River Delta, South China and their relations with landscape heterogeneity at small, medium and large spatial scales. We found that the concentrations of trace elements were slightly elevated, and most trace metals had a geogenic origin. Landscape variables explained 21–53% of the variation of elevated trace metal concentrations with an increasing explanatory power from the small to the large scale. The three variable groups representing parent materials, distance density characteristics and land use had different contributions to the elevated trace metals among scales. Both the distance density variables and land use pattern had a stronger influences on trace metal concentrations at a small scale than at a larger scale, while the parent materials was important at all the scales.