The production and consumption of cassava (Manihot esculenta) occur in several places worldwide, producing large volumes of waste, mostly in the form of bark. This study sought to bring a new purpose to this biomass through producing activated carbon to use as an adsorbent to remove the herbicide Diuron from water. It was observed that the carbon contains the functional groups of methyl, carbonyl, and hydroxyl in a strongly amorphous structure. The activated carbon had a surface area of 613.7 m² g⁻¹, a pore volume of 0.337 cm³ g⁻¹, and a pore diameter of 1.18 nm. The Freundlich model was found to best describe the experimental data. It was observed that an increase in temperature favored adsorption, reaching a maximum experimental capacity of 222 mg g⁻¹ at 328 K. The thermodynamic parameters showed that the adsorption was spontaneous, favorable, and endothermic. The enthalpy of adsorption magnitude was consistent with physical adsorption. Equilibrium was attained within 120 min. The linear driving force (LDF) model provided a strong statistical match to the kinetic curves. Diffusivity (D_s) and the model coefficient (K_LDF) both increased with a rise in herbicide concentration. The adsorbent removed up to 68% of pollutants in a simulated effluent containing different herbicides. Activated carbon with zinc chloride (ZnCl2), produced from leftover cassava husks, was shown to be a viable alternative as an adsorbent for the treatment of effluents containing not only the herbicide Diuron but also a mixture of other herbicides.

O crescimento da população urbana tem gerado impactos negativos muito mais significativos sobre o meio ambiente, tais como as enchentes, que se mostram cada vez mais severas em decorrência da impermeabilização do solo com a falta de um plano de manejo das águas pluviais, e o emprego excessivo de canalizações. Diante da necessidade de uma mudança de paradigma na concepção das obras de drenagem pluvial, surgiu o conceito de Desenvolvimento de Baixo Impacto (DBI), cujo princípio é a gestão das águas pluviais próximo a sua origem, buscando a utilização de técnicas que permitam mimetizar funções naturais que são perdidas com a urbanização. Nesse contexto, os telhados verdes vêm sendo empregados, pois, além de outros benefícios, contribuem para o controle quali-quantitativo das águas pluviais. Neste trabalho são apresentados os resultados de um estudo de longo prazo sobre a eficiência de um telhado verde no controle quantitativo das águas pluviais. Foi possível reduzir, em média, 62% do escoamento superficial, promovendo um retardo no escoamento e reduzindo as vazões de pico, o que gerou o controle desejado. No entanto, sua eficiência é altamente influenciada pelas condições climáticas e de umidade do solo que antecedem cada evento chuvoso.

The Storm Water Management Model 5.1 (SWMM) is a widely adopted dynamic hydrologic and hydraulic model often used to estimate runoff quantity and quality in urban drainage systems. SWMM’s unsteady flow algorithm, EXTRAN, is based on a link-node solution that enables it to represent typical stormwater inflows well. Yet, for rapid inflow conditions associated with more extreme inflows, predictions yielded by SWMM underestimate surges and sometimes underrepresent sudden changes sewer flow conditions. Recent research showed the benefits of introducing artificial spatial discretization (ASD) models in SWMM to represent rapid inflows in sewers. However, with the recent addition of the Preissmann slot algorithm in the SWMM formulation, a systematic evaluation of the performance of this pressurization algorithm in complex and highly dynamic inflow scenarios is still missing. The present study applied the conditions presented in the Storm Water Management Model Quality Assurance Report and compared the use of either link-node or ASD along the original EXTRAN and the new Preissmann slot algorithm in modeling results. The performance of each of the selected modeling alternatives was evaluated in terms of continuity errors and numerical stability. The findings obtained in this study indicate modeling result improvements with an adequate selection of temporal and spatial discretization.