The textile industry is known for its excessive water consumption and environmental impact. One of the major challenges it faces is managing pollution generated by dyes, particularly bifunctional dyes, such as sumireact supra yellow s-hbu, with a red appearance and sumifix supra lemon-yellow e-xf, with a yellow appearance. This study aimed to investigate the decolorization kinetics of synthetic solutions of said bifunctional dyes, which comprise triazine and vinylsulfon. We conducted various tests, including modifications of pH, the addition of TiO₂ P-50 nanoparticles, exposure to solar radiation, limited contact with oxygen, and eolic agitation. The initial solutions had a concentration of 1000 ppm of textile dye. The study showed that the reaction order for the “red” solutions in the R6 and R9 reactors and all the yellow solutions was ½. The concentration of nanoparticles and pH had a significant impact on the reaction rate. The yellow solutions with a concentration of 800 ppm and pH levels of 3.15, 4.13, and 2.25 demonstrated 100% color discoloration, followed by solutions with a concentration of 400 ppm and pH levels of 3.15, 2.25, and 4.13. The analysis of variance confirmed the reaction rate constants for the yellow solutions and emphasized the significance of pH in this process.

Acid mine drainage (AMD) is a major environmental issue due to its high heavy metal concentrations and low pH, posing risks to ecosystems and human health. In Hualgayoc, Cajamarca, Peru, AMD contamination from mining activities necessitates effective remediation strategies. This study evaluated the removal efficiency of organic amendments, municipal waste compost (MWC), cattle manure compost (CMC), vermicompost (HMS), corn stalk biochar (CSB), sludge biochar (SLB), pine biochar (PBC), and native macrophytes Carex pichinchensis (CAX), Juncus ecuadoriensis (JSP), and Myriophyllum aquaticum (MYA) in removing As, Cd, Cu, Fe, and Zn. A physicochemical characterization of AMD, amendments, and plants was conducted, and sorption capacity was determined through triplicate analyses. The results showed that SLB achieved a 100% Zn removal, while CSB removed over 90% of Cu and Fe. Among the organic amendments, CMC demonstrated the highest As and Cd removal (~100%). Regarding macrophytes, CAX achieved a ~97% Fe removal, and MYA exhibited Cd affinity. CSB had the highest sorption capacity for Cu (0.139 mg/g), Fe (1.942 mg/g), and Zn (0.149 mg/g), highlighting its potential for metal remediation. Organic amendments enhanced metal adsorption and stabilization, outperforming macrophytes in heavy metal removal. Combining organic amendments with native plants is recommended to assess their synergistic potential for AMD remediation.

Atmospheric pollution results from toxic gases in low concentrations, originating from natural processes and human activities. These gases interact with each other in the presence of solar radiation, forming much more complex compounds that contribute to the formation of photochemical smog. This study presents a mathematical model to estimate the daily concentrations of primary and secondary pollutants, assuming that spatial variation is not considered within a control volume. The model includes nitrogen oxides, ozone, hydrocarbons, aldehydes, alcohols, and other gases, which are related through 52 chemical and photochemical reactions with rate constants that depend on factors such as the time of day and temperature. The model formulation results in 31 ordinary differential equations that are solved using a variable-step algorithm in MATLAB R2019a. Two scenarios are simulated: the “closed-box” model (CBM), where there are no inflows or outflows of gaseous flux, and the “open-box” model (OBM), which includes inflows and outflows within the control volume. The OBM is particularly useful for predicting concentrations during thermal inversion episodes. The results show that several pollutants reach their maximum concentrations at midday, suggesting an increase in the formation of secondary pollutants under high solar radiation, especially in the closed-box model. In the open-box model, concentration peaks shift toward the afternoon. To compare both models, the closed-box system conditions are considered, incorporating airflow into the open-box model without accounting for pollutants transported by this flow. The complex nonlinear dynamics observed in the pollutants highlight the combined influence of solar radiation, temperature, and emission rates on air quality. This study underscores the usefulness of mathematical models in developing effective mitigation strategies and assessing environmental and public health impacts.

Introducción. El material particulado se constituye en uno de los criterios más transcendentales al momento de evaluar la contaminación del aire, debido a la gran diversidad de fuentes que lo pueden producir y a los efectos que tiene sobre la salud. Objetivo. El presente estudio tuvo por objetivo evaluar el material particulado PM2.5 y PM10, en la temporalidad horario, mensual, estacional y anual y la correlación con las variables meteorológicas en la zona del Distrito Metropolitano de Quito-Ecuador, en el periodo 2013-2020. Metodología. La base de datos y variables meteorológicas se obtuvieron de dos estaciones de monitoreo, Belisario y Carapungo, que están distribuidas en la zona de estudio. Se realizó un análisis exploratorio y correlación simple para 65718 datos de PM2.5 en Belisario, 66191 datos para PM2.5 en Carapungo y 61152 datos de PM10 en Carapungo. Resultados. Los resultados evidencian que la estación de Carapungo presenta mayor concentración de material particulado respecto a la estación Belisario. La relación PM2.5/PM10 de la estación Carapungo es de 0.41 de material fino anisotrópico, que comparados con algunas ciudades como Perú, Colombia, México y Chile es similar. Respecto a las correlaciones el PM2.5 y PM10 presentan una correlación significativa con la temperatura, humedad relativa, dirección del viento y precipitación, pero difieren en las dos estaciones. Conclusiones. Se concluye que el material particulado PM2.5 y PM10 en el área analizada no depende de factores climáticos, sino más bien, puede deberse a la topografía especifica de la zona la cual se encuentra caracterizada por estar rodeada de bosques, volcanes y montañas.

The objective of this study was to evaluate the solar photocatalytic degradation of the disperse textile dye 2-(4-amino-2-nitrophenyl)-1,3-benzothiazole using titanium dioxide nanoparticles (TiO₂ P25) under a mean solar irradiance of 492 ± 58 W/m², evaluating the effects of pH, photocatalyst concentration, and continuous aeration on process efficiency. The degradation of the dye was determined by monitoring its concentration by UV–Visible spectrophotometry, while the mineralization was evaluated by chemical oxygen demand (COD). Likewise, kinetic behavior was analyzed using pseudo-first-order and pseudo-second-order models. The results showed that the degradation efficiency increased with the concentration of TiO₂, reaching the highest yield with 400 ppm of TiO₂ and continuous aeration, which confirms that both variables are determining operating factors for maximizing photocatalytic efficiency. pH exerted a significant influence on the activity of the system, obtaining the highest degradation efficiencies and the greatest reductions in COD under slightly alkaline conditions (pH 8–9), a behavior attributed to the greater colloidal stability of TiO₂ and the modification of its surface properties with respect to its point of zero charge (pHpzc ≈ 6.2). The pseudo-second-order model generally provided an adequate empirical description of the experimental data; however, the best-fitting model varied depending on the experimental condition. The simultaneous decrease in the concentration of the dye and the COD confirmed that the treatment produced not only the decolorization of the solution, but also the progressive oxidation of the organic matter. Integrating kinetic analysis with the simultaneous assessment of decolorization and COD enabled clear experimental differentiation between adsorption and photocatalysis, strengthening the interpretation of TiO₂-based solar photocatalytic systems. In conclusion, solar photocatalysis using TiO₂ and the optimization of operational variables constitute an effective treatment strategy that takes advantage of solar irradiation as the primary energy source, thereby reducing dependence on conventional artificial UV irradiation. Within the scope of this study, the combination of solar radiation, continuous aeration and appropriate operating conditions demonstrated promising potential for the treatment of textile wastewater containing persistent dyes.

Accurate prediction of contaminant transport and self-purification processes in rivers remains challenging because pollutant dispersion, biochemical reactions, and hydrodynamic conditions interact across multiple spatial scales. This study aims to develop and compare mathematical models for soluble contaminant transport and biodegradable organic matter removal in channels and rivers. Unsteady advection–diffusion–reaction equations were formulated for one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) transport scenarios and solved through numerical techniques based on the transformation of partial differential equations into systems of ordinary differential or algebraic equations. In parallel, the classical Streeter–Phelps model and an extended formulation incorporating turbulent diffusion were implemented to evaluate organic load degradation and oxygen deficit dynamics. Simulations were performed using a Matlab R2019a-based computational framework under representative hydraulic and reaction conditions obtained from literature data and empirical correlations. The results showed that, under specific conditions, the 3D model reproduced trends comparable to those predicted by the 2D model, while the latter approached the behavior of the 1D formulation. The Streeter–Phelps model predicted an organic load removal efficiency of 97.74%, a purification index of 1.9564, a critical time of 18.43 h, and a critical distance of 6.93 km. These findings provide a useful framework for river water-quality assessment and support future applications involving complex hydrodynamic and pollutant-loading scenarios.