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Although microplastics (MPs; < 5 mm) have been recognized as one of the most challenging environmental pollutants in the ocean, our understanding of the environmental fate of freshwater MPs falls far behind, particularly on smaller MPs (

Several occupational exposure models are recommended under the EU's REACH legislation. Due to limited availability of high-quality exposure data, their validation is an ongoing process. It was shown, however, that different models may calculate significantly different estimates and thus lead to potentially dangerous conclusions about chemical risk. In this paper, the between-model translation rules defined in TREXMO were used to generate 319000 different in silico exposure situations in ART, Stoffenmanager, and ECETOC TRA v3. The three models' estimates were computed and the correlation and consistency between them were investigated. The best correlated pair was Stoffenmanager-ART (R, 0.52-0.90), whereas the ART-TRA and Stoffenmanager-TRA correlations were either lower (R, 0.36-0.69) or no correlation was found. Consistency varied significantly according to different exposure types (e.g. vapour versus dust) or settings (near-field versus far-field and indoors versus outdoors). The percentages of generated situations for which estimates differed by more than a factor of 100 ranged from 14 to 97%, 37 to 99%, and 1 to 68% for Stoffenmanager-ART, TRA-ART, and TRA-Stoffenmanager, respectively. Overall, the models were more consistent for vapours than for dusts and solids, near-fields than for far-fields, and indoor than for outdoor exposure. Multiple linear regression analyses evidenced the relationship between the models' parameters and the relative differences between the models' predictions. The relative difference can be used to estimate the consistency between the models. Furthermore, the study showed that the tiered approach is not generally applicable to all exposure situations. These findings emphasize the need for a multiple-model approach to assessing critical exposure scenarios under REACH. Moreover, in combination with occupational exposure measurements, they might also be used for future studies to improve prediction accuracy.

Objectives Methanogenic archaea have been found to make up part of the bioaerosols in pig, cattle, and poultry farms. So far no attempts have been made to determine how season, farm type, and farm characteristics may affect workers’ exposure to archaea. Methods Personal filter samples from 327 farmers working on 89 Danish farms were analysed for the number of 16S rRNA gene copies from archaea and bacteria and for their dust and endotoxin content. The farms were visited during summer and winter. Information on farm type and stable characteristics were collected using self-reported activity diaries and walk-through surveys. Differences in archaea and bacteria levels with farm type and stable characteristics and correlations with dust and endotoxin levels were examined. Results Personal archaea exposure was documented in all farm types including, for the first time, during mink farming. At 7.3*104 gene copies m−3 the archaea levels were around two orders of magnitude lower than bacteria levels at 5.7*106 gene copies m−3. At 1.7*105 gene copies m−3 among pig farmers and 1.9*104 gene copies m−3 among cattle farmers the archaea levels differed with farm type (P < 0.0005). The archaea and bacteria levels correlated weakly with a Pearson correlation coefficient of 0.17. Neither archaea nor bacteria levels differed by season. In pig farms the archaea levels differed by type of ventilation and by wetness of the floor. Conclusions Archaea levels were not neglible and appeared to vary greatly between farm types. In pig farms they varied with some farm characteristics. Archaea levels appeared to depend on factors that differed from those of bacteria.

The widespread industrial application of nanotechnology has increased the number of workers exposed to engineered nanomaterials (ENMs), but it is not clear to what extent prevention guidance is practiced. Our aim was to explore the extent that companies manufacturing and/or using ENMs apply risk assessment and management measures. Thirty-four companies were surveyed with an international 35-item questionnaire investigating company and workforce features, types of ENM handled, and risk evaluation and preventive measures adopted. Among participating companies, 62% had a maximum of 10 employees. Metal-based nanomaterials were most frequently identified (73%). Environmental monitoring was performed by 41% of the companies, while engineering exposure controls were approximately reported by 50%. Information and training programs were indicated by 85% of the sample, only 9% performed specific health surveillance for ENM workers. Personal protective equipment primarily included gloves (100%) and eye/face protection (94%). This small-scale assessment can contribute to the limited amount of published literature on the topic. Future investigations should include a greater number of companies to better represent ENM workplaces and a direct access to industrial settings to collect information on site. Finally, deeper attention should be paid to define standardized frameworks for ENM risk assessment that may guide nano-specific preventive actions.

Guanabara Bay is a tropical estuarine ecosystem that receives massive anthropogenic impacts from the metropolitan region of Rio de Janeiro. This ecosystem suffers from an ongoing eutrophication process that has been shown to promote the emergence of potentially pathogenic bacteria, giving rise to public health concerns. Although previous studies have investigated how environmental parameters influence the microbial community of Guanabara Bay, they often have been limited to small spatial and temporal gradients and have not been integrated into predictive mathematical models. Our objective was to fill this knowledge gap by building models that could predict how temperature, salinity, phosphorus, nitrogen and transparency work together to regulate the abundance of bacteria, chlorophyll and Vibrio (a potential human pathogen) in Guanabara Bay. To that end, we built artificial neural networks to model the associations between these variables. These networks were carefully validated to ensure that they could provide accurate predictions without biases or overfitting. The estimated models displayed high predictive capacity (Pearson correlation coefficients ≥0.67 and root mean square error ≤ 0.55). Our findings showed that temperature and salinity were often the most important factors regulating the abundance of bacteria, chlorophyll and Vibrio (absolute importance ≥5) and that each of these has a unique level of dependence on nitrogen and phosphorus for their growth. These models allowed us to estimate the Guanabara Bay microbiome's response to changes in environmental conditions, which allowed us to propose strategies for the management and remediation of Guanabara Bay.

Long-term exposure to air pollution is considered a major public health concern and has been related to overall mortality and various diseases such as respiratory and cardiovascular disease. Due to the spatial variability of air pollution concentrations, assessment of individual exposure to air pollution requires spatial datasets at high resolution. Combining detailed air pollution maps with personal mobility and activity patterns allows for an improved exposure assessment. We present high-resolution datasets for the Netherlands providing average ambient air pollution concentration values for the year 2009 for NO2, NOx, PM2.5, PM2.5absorbance and PM10. The raster datasets on 5×5 m grid cover the entire Netherlands and were calculated using the land use regression models originating from the European Study of Cohorts for Air Pollution Effects (ESCAPE) project. Additional datasets with nationwide and regional measurements were used to evaluate the generated concentration maps. The presented datasets allow for spatial aggregations on different scales, nationwide individual exposure assessment, and the integration of activity patterns in the exposure estimation of individuals.

Stoffenmanager®v4.5 and Advanced REACH Tool (ART) v1.5, two higher tier exposure assessment tools for use under REACH, were evaluated by determining accuracy and robustness. A total of 282 exposure measurements from 51 exposure situations (ESs) were collected and categorized by exposure category. In this study, only the results of liquids with vapor pressure (VP) > 10 Pa category having a sufficient number of exposure measurements (n = 251 with 42 ESs) were utilized. In addition, the results were presented by handling/activity description and input parameters for the same exposure category. It should be noted that the performance results of Stoffenmanager and ART in this study cannot be directly compared for some ESs because ART allows a combination of up to four subtasks (and nonexposed periods) to be included, whereas the database for Stoffenmanager, separately developed under the permission of the legal owner of Stoffenmanager, permits the use of only one task to predict exposure estimates. Thus, it would be most appropriate to compare full-shift measurements against ART predictions (full shift including nonexposed periods) and task-based measurements against task-based Stoffenmanager predictions. For liquids with VP > 10 Pa category, Stoffenmanager®v4.5 appeared to be reasonably accurate and robust when predicting exposures [percentage of measurements exceeding the tool’s 90th percentile estimate (%M > T) was 15%]. Areas that could potentially be improved include ESs involving the task of handling of liquids on large surfaces or large work pieces, allocation of high and medium VP inputs, and absence of local exhaust ventilation input. Although the ART’s median predictions appeared to be reasonably accurate for liquids with VP > 10 Pa, the %M > T for the 90th percentile estimates was 41%, indicating that variance in exposure levels is underestimated by ART. The %M > T using the estimates of the upper value of 90% confidence interval (CI) of the 90th percentile estimate (UCI90) was considerably reduced to 18% for liquids with VP > 10 Pa. On the basis of this observation, users might be to consider using the upper limit value of 90% CI of the 90th percentile estimate for predicting reasonable worst case situations. Nevertheless, for some activities and input parameters, ART still shows areas to be improved. Hence, it is suggested that ART developers review the assumptions in relation to exposure variability within the tool, toward improving the tool performance in estimating percentile exposure levels. In addition, for both tools, only some handling/activity descriptions and input parameters were considered. Thus, further validation studies are still necessary.

Young children differ from adults in their exposure and susceptibility to environmental chemicals (e.g. pesticides) because of various factors such as behavior, diet and physiology. Their heightened vulnerability to environmental stressors makes it important to obtain appropriate urine samples for exposure characterization. However, collecting urine from non-toilet-trained children has been shown to be methodologically and practically challenging. Four urine collection approaches were tested: a disposable diaper, a urine bag, a collection pad and the clean catch. The success rate and the user rating of each method was evaluated. The success rates were 67%, 21%, 17% and 4% for the disposable diaper, urine bag, collection pad and clean catch, respectively. The average user ratings on a 0-10 (0 = inconvenient, 10 = convenient) scale were 9.0, 4.7, 7.3 and 2.5, respectively. Subsequently, the best rated method, the disposable polyacrylate diaper was tested with hydroxy-tebuconazole as an exposure biomarker for the fungicide tebuconazole and creatinine for urine density adjustment. After LC-MS/MS analysis, the recoveries of hydroxy-tebuconazole in the range of 0.05-25 ng/mL were on average 106%, and for creatinine 87%. Precisions (relative standard deviation) were for both 3%. The overall procedure including collection and extraction was assessed, resulting in three out of seven positive samples. Based on this study, the disposable diaper is a suitable method for urine collection of non-toilet-trained children for biomonitoring of tebuconazole. This method can serve as a basis for extension to other substances of interest.

Poyang Lake is the largest freshwater lake in China and an important drinking water source. Since the year 2000, toxic cyanobacteria have been observed frequently in Poyang Lake. In the present study, spatial and seasonal variations of microcystins (MCs; MC-RR, MC-YR, and MC-LR) in water column were examined monthly from January to December (except the months of March, May, and November) in 2013, by using ultra-high-performance liquid chromatography-electrospray ionization tandem triple quadrupole/mass spectrometry (UPLC-MS/MS). MC-RR was the most dominant variant, followed by MC-LR, while MC-YR was detected in low concentration. Total MC concentrations (intracellular + extracellular MCs) ranged from 1.26 to 9916.05 ng/L, with an average of 469.99 ng/L, and only 3.14% (6 out of 192 samples) of the water samples contained MC concentrations that exceeded the drinking water guideline level of 1 μg/L for MC-LR proposed by the World Health Organization (WHO). MC concentrations in water column showed obvious seasonal variations in Poyang Lake. Intracellular and extracellular MCs were both at a low level from January to April but increased quickly from June to August and decreased dramatically thereafter. Intracellular MCs exhibited similar spatial distribution pattern with extracellular MCs. Both intracellular and extracellular MC concentrations in eastern bays and around Songmen Mountain of Poyang Lake were higher than other regions. Intracellular MC concentrations were positively correlated with Chl a (r = 046, P < 0.01), pH (r = 0.25, P < 0.01), cyanobacterial biomass (r = 0.40, P < 0.01), and temperature (r = 0.36, P < 0.01) but negatively correlated with TN (r = − 0.28, P < 0.01), suggesting that TN, cyanobacteria biomass, pH, and temperature might be regulating factors for MC production in Poyang Lake.

Many epidemiological studies have used proximity to sources as air pollution exposure assessment method. However, proximity measures are not generally good surrogates because of their complex non-linear relationship with exposures. Neuro-fuzzy inference systems (NFIS) can be used to map complex non-linear systems, but its usefulness in exposure assessment has not been extensively explored. We present a novel approach for exposure assessment using NFIS, where the inputs of the model were easily-obtainable proximity measures, and the output was residential exposure to an air pollutant. We applied it to a case-study on NH 3pollution, and compared health effects and exposures estimated from NFIS, with those obtained from emission-dispersion models, and linear and non-linear regression proximity models, using 10-fold cross validation. The agreement between emission-dispersion and NFIS exposures was high (Root-mean-square error (RMSE) =0.275, correlation coefficient (r)=0.91) and resulted in similar health effect estimates. Linear models showed poor performance (RMSE=0.527, r=0.59), while non-linear regression models resulted in heterocedasticity, non-normality and clustered data. NFIS could be a useful tool for estimating individual air pollution exposures in epidemiological studies on large populations, when emission-dispersion data are not available. The tradeoff between simplicity and accuracy needs to be considered.

Mercury is used globally to extract gold in artisanal and small-scale gold mining. The mercury-free gravity-borax method for gold extraction was introduced in two mining communities using mercury in the provinces Kalinga and Camarines Norte. This article describes project activities and quantitative changes in mercury consumption and analyzes the implementation with diffusion of innovations theory. Activities included miner-to-miner training; seminars for health-care workers, school teachers, and children; and involvement of community leaders. Baseline (2011) and follow-up (2013) data were gathered on mining practices and knowledge about mercury toxicology. Most miners in Kalinga converted to the gravity-borax method, whereas only a few did so in Camarines Norte. Differences in the nature of the social systems impacted the success of the implementation, and involvement of the tribal organization facilitated the shift in Kalinga. In conclusion, the gravity-borax method is a doable alternative to mercury use in artisanal and small-scale gold mining, but support from the civil society is needed.

'Reproduced with permission from Environmental Health Perspectives', Background: For Europe as a whole, data on internal exposure to environmental chemicals do not yet exist. Characterization of the internal individual chemical environment is expected to enhance understanding of the environmental threats to health. Objectives: We developed and applied a harmonized protocol to collect comparable human biomonitoring data all over Europe. Methods: In 17 European countries, we measured mercury in hair and cotinine, phthalate metabolites, and cadmium in urine of 1,844 children (5–11 years of age) and their mothers. Specimens were collected over a 5-month period in 2011–2012. We obtained information on personal characteristics, environment, and lifestyle. We used the resulting database to compare concentrations of exposure biomarkers within Europe, to identify determinants of exposure, and to compare exposure biomarkers with healthbased guidelines. Results: Biomarker concentrations showed a wide variability in the European population. However, levels in children and mothers were highly correlated. Most biomarker concentrations were below the health-based guidance values. Conclusions: We have taken the first steps to assess personal chemical exposures in Europe as a whole. Key success factors were the harmonized protocol development, intensive training and capacity building for field work, chemical analysis and communication, as well as stringent quality control programs for chemical and data analysis. Our project demonstrates the feasibility of a Europe-wide human biomonitoring framework to support the decision-making process of environmental measures to protect public health., The research leading to these results received funding for the COPHES project (COnsortium to Perform Human biomonitoring on a European Scale) from the European Community’s Seventh Framework Programme [FP7/2007–2013] under grant agreement 244237. DEMOCOPHES (DEMOnstration of a study to COordinate and Perform Human biomonitoring on a European Scale) was co-funded (50%:50%) by the European Commission LIFE+ Programme (LIFE09/ENV/BE/000410) and the partners. For information on both projects as well as on the national co-funding institutions, see http://www.eu-hbm.info/. The sponsors had no role in the study design, data collection, data analysis, data interpretation or writing of the report.

In this paper we describe the construction and use of a set of bioluminescent yeast strains for the detection of compounds that can affect androgen or estrogen receptor mediated hormonal signalling. The set includes Saccharomyces cerevisiae strains expressing human androgen receptor (AR), estrogen receptor alpha (ERalpha) or estrogen receptor beta (ERbeta), along with firefly luciferase controlled by a respective hormone responsive promoter. A constitutively luminescent strain was included in the set for determining the cytotoxicity of the sample. Yeast cells were incubated with pure chemicals or complex samples for 2.5 h, after which the signal could be detected from the cell-sample mixture after simply adding the D-luciferin substrate. The assays could be completed in one day and they required no cell lysis or centrifugation steps, which makes them suitable for high-throughput analysis of samples. Due to a short incubation time the assays are directly applicable to different sample matrices, requiring no pretreatment of the samples. The assays were used to assess the hormonal activity in moisturizing lotions as an example of a complex sample matrix known to contain endocrine disrupting chemicals. Six out of eight tested moisturisers showed high estrogenic activity, whereas no androgenic activity was observed in the samples.