systems in which to further investigate and understand geo-biodiversity relationships.In recent years, soil pollution is a major global concern drawing worldwide attention. Earthworms can resist high concentrations of soil pollutants and play a vital role in removing them effectively. Vermiremediation, using earthworms to remove contaminants from soil or help to degrade non-recyclable chemicals, is proved to be an alternative, low-cost technology for treating contaminated soil. However, knowledge about the mechanisms and framework of the vermiremediation various organic and inorganic contaminants is still limited. Therefore, we reviewed the research progress of effects of soil contaminants on earthworms and potential of earthworm used for remediation soil contaminated with heavy metals, polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), polycyclic aromatic hydrocarbons (PAHs), pesticides, as well as crude oil. Especially, the possible processes, mechanisms, advantages and limitations, and how to boost the efficiency of vermiremediation are well addressed in this review. Finally, future prospects of vermiremediation soil contamination are listed to promote further studies and application of vermiremediation in contaminated soils.We propose and exemplify a framework to assess Natural Background Levels (NBLs) of target chemical species in large-scale groundwater bodies based on the context of Object Oriented Spatial Statistics. The approach enables one to fully exploit the richness of the information content embedded in the probability density function (PDF) of the variables of interest, as estimated from historical records of chemical observations. As such, the population of the entire distribution functions of NBL concentrations monitored across a network of monitoring boreholes across a given aquifer is considered as the object of the spatial analysis. Our approach starkly differs from previous studies which are mainly focused on the estimation of NBLs on the basis of the median or selected quantiles of chemical concentrations, thus resulting in information loss and limitations related to the need to invoke parametric assumptions to obtain further summary statistics in addition to those considered for the spatial analysis. Our work enables one to (i) assess spatial dependencies among observed PDFs of natural background concentrations, (ii) provide spatially distributed kriging predictions of NBLs, as well as (iii) yield a robust quantification of the ensuing uncertainty and probability of exceeding given threshold concentration values via stochastic simulation. We illustrate the approach by considering the (probabilistic) characterization of spatially variable NBLs of ammonium and arsenic detected at a monitoring network across a large scale confined groundwater body in Northern Italy.Phytoremediation is a promising inexpensive method of detoxifying arsenic (As) contaminated soils using plants and associated soil microorganisms. The potential of Pteris vittata to hyperaccumulate As contamination has been investigated widely. Since As(V) is efficiently taken up by P. vittata than As(III), As speciation by associated rhizobacteria could offer enormous possibility to enhance As phytoremediation. Specifically, increased rhizobacteria mediated As(III) to As(V) conversion appeared to be a crucial step in As mobilization and translocation. In this study, Pseudomonasvancouverensis strain m318 with the potential to improve As phytoremediation was inoculated to P. vittata in a field trial for three years to evaluate its long-term efficacy and stability for enhancing As phytoextraction. The biomass, As concentration, and As accumulation of ferns showed to be increased by inoculation treatment. Although this trend occasionally declined which may be accounted to lower As concentration in soil and amount of precipitation during experiments, the potential of inoculation was observed in increased enrichment coefficients. Further, the arsenite oxidase (aioA-like) genes in the rhizosphere were detected to evaluate the influence of inoculation on As phytoremediation. The findings of this study suggested the potential application of rhizosphere regulation to improve phytoremediation technologies for As contaminated soils. However, the conditions which set the efficacy of this method could be further optimized.Children are exposed to many potentially toxic compounds in their daily lives and are vulnerable to the harmful effects. To date, very few non-invasive methods are available to quantify children’s exposure to environmental chemicals. Due to their ease of implementation, silicone wristbands have emerged as passive samplers to study personal environmental exposures and have the potential to greatly increase our knowledge of chemical exposures in vulnerable population groups. Nevertheless, there is a limited number of studies monitoring children’s exposures via silicone wristbands. In this study, we implemented this sampling technique in ongoing research activities in Montevideo, Uruguay which aim to monitor chemical exposures in a cohort of elementary school children. The silicone wristbands were worn by 24 children for 7 days; they were quantitatively analyzed using gas chromatography with tandem mass spectrometry for 45 chemical pollutants, including polychlorinated biphenyls (PCBs), pesticides, polybrominateands and clearly points to a need for further studies.The increasing human population requires ongoing efforts in food production. This is frequently associated with an increased use of agrochemicals, leading to environmental contamination and altering microbial communities, including human fungal pathogens that reside in the environment. Cryptococcus gattii is an environmental yeast and is one of the etiological agents of cryptococcosis. Benomyl (BEN) is a broad-spectrum fungicide used on several crops. To study the effects of agrochemicals on fungal pathogens, we first evaluated the susceptibility of C. gattii to BEN and the interactions with clinical antifungals. Antagonistic interaction between BEN and fluconazole was seen and was strain- and concentration-dependent. We then induced BEN-resistance by culturing strains in increasing drug concentrations. One strain demonstrated to be more resistant and showed increased multidrug efflux pump gene (MDR1) expression and increased rhodamine 6G efflux, leading to cross-resistance between BEN and fluconazole. Morphoo unintended consequences on non-target species and this could result in severe healthy problems worldwide.Microalgae usually co-exist with bacteria, which may influence the microalgal growth, in aquatic environment. In this study, thirteen strains that can promote microalgal growth were isolated from Scenedesmus sp. LX1 culture. Additional results showed that these strains could secrete gibberellin (GA), which is a phytohormones, promoting the growth and metabolism of the Scenedesmus sp. LX1. Low concentration (0.1 mg L-1) of GA can increase the microalgae biomass by 51% after 4 days. GA could enhance the photosynthetic activity by increasing the photosynthetic pigment content, such as culture after 2 h with low GA concentration (0.1 mg L-1), chlorophyll a and β-carotene increased from 0.59 μg per 106 cells to 0.72 μg per 106 cells and from 0.20 μg per 106 cells to 0.38 μg per 106 cells, respectively. In addition, GA could also stimulate the dehydrogenase activity, ATP accumulation, and carbonic anhydrase activity to increase the metabolic activity of the microalgae. Interestingly, the microalgae can selectively enhance the bacterial GA secretion in turn, indicating that there was a specific feedback regulation mechanism between the microalgae and the bacteria. The results of this study show a new mechanism of symbiotic-bacteria that enhances microalgal growth. It’s a great significance to understand the microalgal growth and water bloom in aquatic environment.Microplastics (MPs) serve as a niche for colonization of biofilm-forming microorganisms, termed as plastisphere. Distinct microbial assemblages between MPs and surrounding waters have been well reported, but little is known about driving factors affecting biofilm development on plastic surfaces. Here, to investigate the influence of plastic colors on microbial assemblages, we performed a biofilm incubation experiment, in an aquaculture pond, using MPs in colors (blue, yellow and transparent) that commonly found in the aquatic environments for 30 days. We examined the community structure and function of plastisphere by using 16S rRNA sequencing. The results showed that plastisphere communities exhibited a higher diversity and evenness compared with the water community. MPs especially the blue MPs had more unique species, which might indicate a plastic color/additive-driven selection of microorganisms on MPs. A significant distinctness in bacterial community composition between MPs and the water was found, mainly caused by large amounts of Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium but trace amounts of Microcystis_PCC-7914 on MPs. Due primarily to rich in Aquabacterium but lack of norank_f__norank_o__1-20 on blue MPs than on transparent and yellow MPs, a clear separation between plastisphere communities of three colors of MPs was also observed. Moreover, compared with the water column, the metabolic pathways, e.g., transport and metabolism of amino acid, carbohydrate and inorganic ion, on plastisphere especially those of blue MPs were generally enriched. Biofilms colonizing on blue MPs appeared to have a higher functional diversity than those on transparent or yellow MPs. These results might suggest that plastic colors have impacts on the community structure and functional diversity of plastisphere.Due to a lack of routine monitoring, bespoke measurements are required to develop ultrafine particle (UFP) land use regression (LUR) models, which is especially challenging in megacities due to their large area. As an alternative, for London, we developed separate models for three urban residential areas, models combining two areas, and models using all three areas. Models were developed against annual mean ultrafine particle count cm-3 estimated from repeated 30-min fixed-site measurements, in different seasons (2016-2018), at forty sites per area, that were subsequently temporally adjusted using continuous measurements from a single reference site within or close to each area. A single model and 10 models were developed for each individual area and combination of areas. Within each area, sites were split into 10 groups using stratified random sampling. Each of the 10 models were developed using 90% of sites. Hold-out validation was performed by pooling the 10% of sites held-out each time. The transferability of models was tested by applying individual and two-area models to external area(s). In model evaluation, within-area mean squared error (MSE) R2 ranged from 14% to 48%. Transferring individual- and combined-area models to external areas without calibration yielded MSE-R2 ranging from -18 to 0. MSE-R2 was in the range 21% to 41% when using particle number count (PNC) measurements in external areas to calibrate models. Our results suggest that the UFP models could be transferred to other areas without calibration in London to assess relative ranking in exposures but not for estimating absolute values of PNC.