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e classroom ventilation plans.Microbial communities in agricultural soils underpin many ecosystem services including the maintenance of soil structure, food production, water purification and carbon storage. However, the impact of fertilization on the health of microbial communities is not well understood. This study investigates the spatial and temporal dynamics of nitrogen (N) transport away from a fertilizer granule with pore scale resolution. Specifically, we examined how soil structure and moisture content influence fertilizer derived N movement through the soil pore network and the subsequent impact of on soil microbial communities. We develop a mathematical model to describe N transport and reactions in soil at the pore-scale. Using X-ray Computed Tomography scans, we reconstructed a microscale description of a soil-pore geometry as a computational mesh. Solving two-phase water/air model produced pore-scale water distributions at 15, 30 and 70% water-filled pore volume. The N-speciation model considered ammonium (NH4+), nitrate (NOodel demonstrates the importance of pore-scale processes in regulating N movement and their interactions with the soil microbiome.The occurrence and dissemination of toxic metals, antibiotic resistant bacteria and their resistance genes (ARGs) in the aquatic ecosystems of sub-Saharan African countries are still understudied, despite their potential to threat human health and aquatic organisms. In this context, the co-contamination and seasonal distribution of toxic metals and ARG in river sediments receiving untreated urban sewages and hospital effluents from Kinshasa, the capital city of the Democratic Republic of the Congo were investigated. ARGs including β-lactam resistance (blaCTX-M and blaSHV), carbapenem resistance (blaVIM, blaIMP, blaKPC, blaOXA-48 and blaNDM) and total bacterial load were quantified by using quantitative polymerase chain reaction (qPCR) in total DNA extracted from sediment. The amount of toxic metals in sediments was quantified using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The results highlight high abundance of 16S rRNA and ARGs copy numbers in sediment samples. Strong pollution of rivers by toxic metals was found, with max values (mg kg-1) of 81.85(Cr), 5.09(Co), 33.84(Ni), 203.46 (Cu), 1055.92(Zn), 324.24(Pb) and 2.96(Hg). Results also highlight the high abundance of bacterial markers (8.06 × 109-2.42 × 1012 16S rRNA/g-1 DS) as well as antibiotic resistance genes (up to 4.58 × 108 ARG. g-1 DS) in the studied rivers. Significant correlations were observed between (i) metals (except Cd and Hg) and organic matter (R > 0.60, p 0.57, p less then 0.05) suggesting a tight link between (i) metal contamination and anthropogenic pressure and (ii) microbial contamination of river and dissemination of antibiotic resistance. Results demonstrated that multi-diffuse pollution originating from human activity contribute to the spread of toxic metals and ARGs into the aquatic ecosystems.An increasing use of Al and Fe as normalising elements in assessment of anthropogenic change (metal enrichment) in marine environments has prompted the current study. This investigation was facilitated by a unique, large data set comprising total- and size-normalised sedimentary metals data from 41 estuaries (n = 3494) in central New South Wales, Australia. Total sediment Al and Fe concentrations varied substantially in these estuaries, even for samples comprising 100% fine fraction (ff), due to changes in the clay mineral mix and variable clay mineral chemistry. Normalising sedimentary metals to 100% ff produced variable results, however this approach improved markedly when samples with less then 10% ff was removed. The technique of normalising sedimentary metals by adjusting total Al to 50,000 μg/g considered to represent 100% ff was critically assessed. Results showed that total Al for 100% ff varied between estuaries and the most appropriate Al concentration for normalisation was the intercept value of the trend line in total Al vs ff bivariate plots and the 100% ff axis. It is recommended that, in the absence of size-normalised metals data, this intercept value be used as the normalising Al concentration, which should be determined locally for 100% ff. Iron was also assessed as a normalising element using the same approach and provided similar results, but was less attractive due to diagenetic alteration. The post-extraction normalisation (PEN) method provided valid, normalised metals data capable of estimating enrichment (magnitude of anthropogenic change) in marine environments.Slaughterhouse process- and wastewater are considered as a hotspot for antibiotic-resistant bacteria and antimicrobial residues and may thus play an important role for their dissemination into the environment. In this study, we investigated occurrence and characteristics of ESKAPE bacteria (E. faecium, S. aureus, K. Derazantinib pneumoniae, A. baumannii, P. aeruginosa, Enterobacter spp.) and ESBL (extended spectrum β-lactamase) -producing E. coli in water samples of different processing stages of two German pig slaughterhouses (S1/S2) as well as their municipal wastewater treatment plants (mWWTPs). Furthermore, residues of various antimicrobials were determined. A total of 103 water samples were taken in delivery and dirty areas of the slaughterhouses S1/S2 (n = 37), their in-house WWTPs (n = 30) and mWWTPs including their receiving water bodies (n = 36). The recovered isolates (n = 886) were characterized for their antimicrobial resistance pattern and its genetic basis. Targeted species were ubiquitous along the slaughteto eliminate these bacteria leading to a discharge into the preflooder and a subsequent dissemination into the surface water.The water scarcity in China's coal bases is intensifying due to rapid development of modern coal chemical industry and inefficient water utilization. Previous studies on industrial water optimization were predominantly focused on direct water, overlooking the associated indirect water consumptions throughout supply chains. In this study, a water footprint (WF)-based allocation optimization framework is developed to obtain optimal solutions for water resources utilization constrained by quantity of water supply and coal chemical production related limiting factors. The framework comprises a novel WF accounting model especially used for the coal-to-chemical industry and a water allocation optimization model that integrates direct and indirect water consumptions. A typical major large-scale coal base in China was chosen as the study area. Results showed that the cradle-to-gate WF of the various coal-based products ranged from 2.01 m3/t to 70.85 m3/t, in which the internal operational and supply-chain blue WFs were the dominant contributors.