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1 and 1 mm which is approximately 75% of the total microplastics. Micro-Raman spectroscopy analysis indicated that microplastics contained in drinking water were mainly polyesters (poly (trimethylene terephthalate)) and epoxy resin suggesting the possible contribution of wastewater discharges for microplastics contamination. Thus, this study findings show that free public drinking water fountains are potential microplastics hotspot for human consumption and provide useful references for mitigation measures. Acid mine drainage (AMD) is harmful to the environment and human health. Microorganisms-mineral interactions are responsible for AMD generation but can also remediate AMD contamination. Understanding the microbial response to AMD irrigation will reveal microbial survival strategies and provide approaches for AMD remediation. A terrace with sharp geochemical gradients caused by AMD flooding were selected to study the microbial response to changes in environmental parameters related to AMD contamination. AMD intrusion reduced soil microbial community diversity and further changed phylogenetic clustering patterns along the terrace gradient. We observed several genera seldom reported in AMD-related environments (i.e., Corynebacterium, Ochrobactrum, Natronomonas), suggesting flexible survival strategies such as nitrogen fixation, despite the poor nutritional environment. A co-occurrence network of heavily-contaminated fields was densely connected. The phyla Proteobacteria, Acidobacteria, Chloroflexi, and Euryarchad that the geochemical gradients substantially altered the soil microbiota and enriched the relevant microorganisms adapted to the different conditions. These findings provide mechanistic insights into the effects of contamination on the soil microbiota and establish a basis for in situ AMD bioremediation strategies. A novel amino-functionalized hydrochar material (referred to NH2-HCs) was prepared and used as the soil amendment to immobilize multi-contaminated soils for the first time. The results showed that the application of NH2-HCs significantly improved (P  less then  0.05) soil properties (i.e., pH value, cation exchange capacity and organic content). By introduction of NH2-HCs, the contaminated soil showed the highest value of 96.2%, 52.2% and 15.5% reductions in Cu, Pb and Cd bioavailable concentrations and the leaching toxicity of Cu, Pb and Cd were remarkably reduced by 98.1%, 31.3% and 30.4%, respectively. Most of exchangeable Cu, Pb and Cd reduced were transformed into its less available forms of oxidizable and residual fractions. Potential ecological risk assessment indicated that the element Cd accounted for the most of total risks in NH2-HCs amended soils. The mechanism study indicated that surface complexation, chemical chelating and cation-pi interaction of NH2-HCs played a vital role in the immobilization of heavy metals. Pot experiments further verified that the application of NH2-HCs significantly improved plant growth and reduced metal accumulations. The present study offered a novel approach to prepare amino-functionalized hydrochars with great potential as the green and alternative amendments for efficiently immobilizing heavy metals in multi-contaminated soil. The relationship between cadmium (Cd) concentration in rice grains and the soil that they are cultivated in is highly uncertain due to the influence of soil properties, rice varieties, and other undetermined factors. In this study, we introduce the probability of exceeding the threshold to characterize this uncertainty and then, build a probabilistic forewarning model. Additionally, a number of associated factors have been used as parameters to improve model performance. Considering that the physicochemical properties and Cd concentration in the soil (Cdsoil) do not follow a normal distribution, and are not independent of each other, a discriminative algorithm, represented by a logistic regression (LR), performed better than generative algorithms, such as the naive Bayes and quadratic discriminant analysis models. The performance of the LR based model was found to be 0.5% better in the case of the univariate model (Cdsoil) and 4.1% better with a multivariate model (soil properties used as additional factors) (p  less then  0.01). The output of the LR based model predicted probabilities that were positively correlated to the true exceedance rate (R2 = 0.949,p  less then  0.01), within an exceedance threshold range of 0.1-0.4 mg kg-1 and a mean deviation of 5.75%. see more A sensitivity analysis showed that the effect of soil properties on the exceedance probability weakens with an increase in Cd concentration in rice grains. When the threshold is below 0.15 mg kg-1, soil pH strongly influences the exceedance probability. As the threshold increases, the influence of pH on the exceedance probability is gradually superseded. By quantifying the uncertainty regarding the relationship between Cd concentration in rice grains and soil, the discriminative algorithm-based probabilistic forecasting model offers a new way to assess Cd pollution in rice grown in contaminated paddy fields. Clinical or pathological evidence demonstrated that air pollution could undermine other organ systems of human body besides respiratory and circulation systems. Investigations that directly relate hospital outpatient visits for endocrine (ENDO), digestive (DIGE), urological (UROL), and dermatological (DERM) diseases categories with ambient particulate matter (PM) are still lacking, particularly in heavily polluted cities. Here, we conducted a time-series analysis using 812,624, 1,111,342, 539,803, and 741,662 hospital visits for ENDO, DIGE, UROL, and DERM, respectively, in Nanjing, China from 2013 to 2019. A generalized additive model was applied to estimate the exposure-response associations. Results showed that a 10 μg/m3 increase in PM2.5 concentration on lag 0 day was significantly associated with 0.59% (95% CI 0.30%, 0.88%), 0.43% (0.15%, 0.70%), 0.36% (0.06%, 0.66%), and 0.65% (0.42%, 0.87%) increase for ENDO, DIGE, UROL, and DERM hospital visits, respectively. The estimated effects of PM10 were slightly smaller but still statistically significant.

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