Polishing of painting process effluents through adsorption with biochar from winemaking residues

Environmental Science and Pollution Research - A real industrial effluent from the pre-treatment and painting processes was polished through adsorption using alternative biochar derived from grape...     

Water demand of central pivot-irrigated areas in Bahia,Brazil: management of water resources applied to sustainable production

When performed without technical criteria, the rapid expansion of irrigated agricultural frontiers can result in overexploitation of water, causing worrying impacts on the balance of agroecosystems. This study proposes a model applied to the state of Bahia, to estimate the water demand of areas irrigated by a central pivot, in order to contribute to information that will subsidize the inspection and planning of water resources in the promotion of sustainable agriculture. The irrigated areas were identified and measured by photointerpretation using orbital images from the Landsat-8 satellite. With a historical series of data, the reference evapotranspiration was calculated and monthly water balance was elaborated. The data obtained were spatialized by kriging, and with punctual values of water deficit (mm), the water demand of the irrigated perimeter of the equipment was estimated. The results were described considering strategic planning units, proposed from municipalities, hydrographic basins and biomes. A total of 4075 pivots were quantified, covering an irrigated area of 265,896.30 ha and with an average annual consumption of 1,333,473,208.02 m³ of water. Areas of high demand were identified, especially in the western region of Bahia, which includes the hydrographic basin of the São Francisco River and the Cerrado biome, concentrating 80.85% and 75.47% of the state water demand for pivots, respectively. Considering possible points of water vulnerability and continuity of this expansion, the results provide the primary information needed to encourage the adoption of public policies aimed at the management of water resources. The study method proposes guidelines that condition the application in any region of interest in the world.

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Recycling Expanded Polystyrene with a Biodegradable Solvent to Manufacture 3D Printed Prototypes and Finishing Materials for Construction

Journal of Polymers and the Environment - The amount of plastic waste generated is causing damage to the environment, such as sea and soil pollution, and one of the alternatives for disposing of...     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.     

Conceptual Stormwater Quality Models by Alternative Linear and Non-linear Formulations: an Event-Based Approach

Environmental Modeling & Assessment - Different linear transfer functions (TFs) models are compared to the traditional non-linear rating curve (RC) model in a novel event-based exploratory...