010) to 0.242 (0.176, 0.307) mmHg, and from -0.026 (-0.053, 0.001) to 0.051 (0.020, 0.082) mmHg, respectively. Statistically significant positive BP-PM2.5 associations were only found in South and North China for systolic levels and in Southwest China for diastolic levels. We further explored the regional study population characteristics and exposure-response curves, and found that the geographic variations in BP-PM2.5 associations were probably due to different population compositions or different PM2.5 exposure levels. Our study provided national-level evidence on the associations between ambient PM2.5 exposure and elevated BP levels. The magnitude of the estimated associations varied substantially by geographic location in China. CLINICAL TRIAL REGISTRATION The Clinical trial registration name was Survey on prevalence of hypertension in China; the registration number was ChiCTR-ECS-14004641. http//www.chictr.org.cn/showproj.aspx?proj=4932. The concentration of dissolved organic matter (DOM) in freshwaters is increasing in large areas of the world. In addition to carbon, DOM contains nitrogen and phosphorus and there is growing concern that these organic nutrients may be bioavailable and contribute to eutrophication. However, relatively few studies have assessed the potential for dissolved organic nitrogen (DON) or dissolved organic phosphorus (DOP) compounds to be bioavailable to natural river phytoplankton communities at different locations or times. Temporal and spatial variations in uptake, relative to environmental characteristics were examined at six riverine sites in two contrasting catchments in the UK. This study also examined how the uptake by riverine phytoplankton of four DON and four DOP compounds commonly found in rivers, varied with concentration. Total nitrogen (TN) and phosphorus (TP) concentrations, the proportion of inorganic nutrient species, and nutrient limitation varied temporally and spatially, as did the potential for DON and DOP uptake. All eight of the DOM compounds tested were bioavailable, but to different extents. Organic nutrient use depended on the concentration of the organic compound supplied, with simple compounds (urea and glucose-6-phosphate) supporting algal growth even at very low concentrations. DON use was negatively correlated with the TN and ammonia concentration and DOP use was negatively correlated with soluble reactive phosphorus (SRP) and dissolved organic carbon (DOC) concentration. The evidence indicates that DOM in rivers has been overlooked as a potential source of nutrients to phytoplankton and therefore as an agent of eutrophication. V.Organic UV filters are of emerging concern due to their occurrence and persistence in coastal ecosystems. Because marine bacteria are crucial in the major biogeochemical cycles, there is an urgent need to understand to what extent these microorganisms are affected by those chemicals. This study deciphers the impact of five common sunscreen UV filters on twenty-seven marine bacteria, combining both photobiology and toxicity analysis on environmentally relevant species. Seven bacteria were sensitive to different organic UV filters at 1000 μg L-1, including octinoxate and oxybenzone. This is the first report demonstrating inhibition of bacterial growth from 100 μg L-1. None of the UV filters showed any toxicity at 1000 μg L-1 on stationary phase cells, demonstrating that physiological state was found to be a key parameter in the bacterial response to UV-filters. Indeed, non-growing bacteria were resistant to UV filters whereas growing cells exhibited UV filter dependent sensitivity. Octinoxate was the most toxic chemical at 1000 μg L-1 on growing cells. Interestingly, photobiology experiments revealed that the toxicity of octinoxate and homosalate decreased after light exposure while the other compounds were not affected. In terms of environmental risk characterization, our results revealed that the increasing use of sun blockers could have detrimental impacts on bacterioplanktonic communities in coastal areas. Our findings contribute to a better understanding of the impact of the most common UV filters on bacterial species and corroborate the importance to consider environmental parameters such as solar radiation in ecotoxicology studies. Crown V. All rights reserved.Water deficit, exacerbated by global population increases and climate change, necessitates the investigation of alternative non-traditional water sources to augment existing supplies. Indirect potable reuse (IPR) represents a promising alternative water source in water-stressed regions.  https://www.selleckchem.com/products/ABT-263.html  Of high concern is the presence of pathogenic microorganisms in wastewater, such as enteric viruses, protozoa and bacteria. Therefore, a greater understanding of the potential impact to human health is required. The aim of this research was to use a quantitative microbial risk assessment (QMRA) approach to calculate the probability of potential pathogen infection risk to the public in surface waters used for a range of recreational activities under scenarios 1) existing de facto wastewater reuse conditions; 2) after augmentation with conventionally treated wastewater; and 3) after augmentation with reclaimed wastewater from proposed IPR schemes. Forty-four 31 l samples were collected from river sites and a coastal wastewater tnative water supply option selection. As such, this evidence may inform water managers and the public of the potential benefits of IPR and improve acceptance of such practices in the future. Urbanization processes have accelerated over recent decades, prompting efforts to model land use change (LUC) patterns for decision support and urban planning. Cellular automata (CA) are extensively employed given their simplicity, flexibility, and intuitiveness when simulating dynamic LUC. Previous research, however, has ignored the spatial heterogeneity among sub-regions, instead applying the same transition rules across entire regions; moreover, most existing methods extract neighborhood effects with only one data time slice, which is inconsistent with the nature of neighborhood interactions as a long-term process exhibiting obvious spatiotemporal dependency. Accordingly, we propose a hybrid cellular automata model coupling area partitioning and spatiotemporal neighborhood features learning, named PST-CA. We use a machine-learning-based partitioning strategy, self-organizing map (SOM), to divide entire regions into several homogeneous sub-regions, and further apply a spatiotemporal three-dimensional convolutional neural network (3D CNN) to extract the spatiotemporal neighborhood features.