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Latin-American cities need efficient municipal solid waste (MSW) collection systems, specifically in municipalities with fast urbanization. Poor logistics in collection routes is one of the causes of inefficient MSW management. A strategy for designing the MSW collection routes, considering an environmental and economic analysis, was developed and tested in the Metropolitan Area of Monterrey (MMA), one of the cities with the highest urban and economic development in Mexico. Life cycle assessment and costs analysis were performed to evaluate archetypal routes’ environmental and economic impact in the current MSW collection system. The assessment of the environmental impact was realized through midpoint indicators of the ReCiPe 2008 method. The mathematical model describing the collection routes was developed using actual data from the MSW collection system in MMA, optimized by the Traveling Salesman Problem (TSP), and solved in RStudio. This study shows a reduction of between 9 and 20% of greenhouse gas emissions and distance covered in current collection stages, respectively. The results also demonstrate the influence of road direction, collection-truck efficiency, and traffic load in different stage on the environmental and economic impacts of the collection routes. A life cycle inventory, with realistic inputs and outputs of the MSW collection system, was developed. These inventories are scarce in Mexico and Latin America; their development helps designing cleaner MSW collection systems. Implications: The optimization of urban solid waste collection systems is a strategy to reduce costs and environmental impacts, considering factors such as distance or fuel consumption. However, mathematical models within the optimization require detailed information of the road network to achieve reliable results. In this context, Latin America shows difficulties in increasing its collection systems’ efficiency due to economic constraints and limited access to information from locals governments. The use of geographic information systems has been shown to collect real data on a city’s roads. This work aims to propose a strategy for designing urban solid waste collection routes with the least environmental and economic impacts through an optimization strategy that considers the road network’s real-time data, added to an environmental analysis developed with a life cycle assessment approach. We believe that our results could help the design of urban solid waste collection systems for cities with Latin American characteristics. Additionally, an inventory of specific inputs and emissions for waste collection in this type of city will be generated, supporting future sustainable management strategies.

In this study, coffee ground (CG) was used to remove lead ions from aqueous solution. The physicochemical properties of CG determined were: point of zero charge (pH pcz 4.5), acid and basic group quantity (1.52 and 0.17 meg/g, respectively), and specific surface area ( 2 /g). The pH effect (3–5) on lead adsorption was evaluated. An increase of solution pH causes an increment of adsorption capacity and the best adsorption capacity ( q = 22.9 mg/g) was obtained at pH 5. The calculation of the Langmuir and Freundlich isotherm parameters was performed via stochastic optimization methods, such as Genetic Algorithm, Pattern Search and Simulated Annealing, and a gradient-based method. Pattern Search showed the fastest convergence and it generated feasible parameters for both isotherm models. On the other hand, Genetic Algorithm and Simulated Annealing, sometimes generated unfeasible parameters. The Langmuir and Freundlich isotherm models were compared against an Artificial Neural Network, which has the ability to learn unmodeled phenomena not considered by the previous models. Thus, an Artificial Neural Network has the best prediction capabilities, although it lacks the physical interpretation the isotherm models have.

In this paper, the quantification of Pb2+ and Cd2+ at trace levels was carried out by differential pulse anodic stripping voltammetry technique, using a paste carbon electrode modified with spent coffee grounds (SCG) as working electrode. Different percentages of SCG (40, 50, 60, 70% of SCG) were tested in the experiments; the best electrochemical response was obtained with the electrode modified with 50% of SCG. An experimental design was performed in order to maximize the intensity of the oxidation current, using the accumulation time and the reduction potential as factors. The best experimental conditions for the electrodeposition of the cadmium ions were obtained at an accumulation time of 76 s, and the reduction potential of −1115 mV; while for the electrodeposition of lead ions, the best performance was obtained at an accumulation time of 120 s and a reduction potential of −1200 mV. The detection limit of the carbon paste electrode modified with 50% of SCG were 89 and 90 μM for Cd(II) and Pb(II), respectively, showing the potential of these electrodes as a viable and sustainable alternative for the determination of heavy metals in aqueous solutions.

When producing activated carbons from agricultural by-products, certain properties, such as yield and specific surface area, are very important for obtaining an economical and promising adsorbent material. Nevertheless, many researchers have not simultaneously optimized these properties and have obtained different optimal conditions for the production of activated carbon that either increases specific surface area but decreases yield or vice versa. In this research, the production of activated carbon from barley husks (BH) by chemical activation with zinc chloride was optimized by using a 2(3) factorial design with replicates at the central point, followed by a central composite design with two responses (the yield and iodine number) and three factors (the activation temperature, activation time, and impregnation ratio). Both responses were simultaneously optimized by using the desirability functions approach to determine the optimal conditions of this process. The findings reveal that after the simultaneous dual optimization, the maximal response values were obtained at an activation temperature of 436 °C, an activation time of 20 min, and an impregnation ratio of 1.1 g ZnCl₂/g BH, although the results after the single optimization of each response were quite different. At these conditions, the predicted values for the iodine number and yield were 829.58 ± 78.30 mg/g and 46.82 ± 2.64%, respectively, whereas experimental tests produced values of 901.86 mg/g and 48.48%, respectively. Moreover, activated carbons from BH obtained at the optimal conditions primarily developed a porous structure (mesopores > 71% and micropores > 28%), achieving a high surface area (811.44 m(2)/g) that is similar to commercial activated carbons and lignocellulosic-based activated carbons. These results imply that the pore width and surface area are large enough to allow the diffusion and adsorption of pollutants inside the adsorbent particles. In summary, two responses were optimized to determine the optimal conditions for the production of activated carbons because it is possible to increase both the specific surface area and yield.

This work discusses the decolorization and degradation of textile azo dye solutions containing Acid Yellow 36 (AY-36) by the electro-Fenton process (EF) using an undivided electrochemical cell containing a boron doped diamond (BDD) electrode as cathode for H2O2 production. The independent parameters of current density, dye concentration, Fe2 + concentration and electrolysis time in the range of 8–23 mA/cm2, 60–80 mg/L, 0.1–0.3 mM and 10–50 min, respectively, were evaluated. Experimental data were optimized by means of a 24 factorial design and Response Surface Methodology (RSM). These results revealed that the optimal operating conditions to achieve 95.9% efficiency for dye decolorization with complete degradation were current density = 15 mA/cm2, AY-36 concentration = 80 mg/L, Fe2 + content = 0.3 mM and electrolysis time = 50 min. This was confirmed with UV–vis and HPLC assessments during the EF/BDD treatment.

The aim of this work was to apply an experimental response surface methodology (RSM) to optimization of the Acid Yellow 36 (Ay 36) decolorization procedure the electro-Fenton process (EFP) using boron-doped diamond (BDD) electrodes. RSM was used for the evaluation of different operation parameters, process modelling, optimization study, and model prediction analysis. Optimization of the electro-Fenton process for decolorization of 60 mg L −1 of synthetic azo dye solution was analyzed using a central composite design (CCD) in RSM. The response variable for the experimental design was a percentage of the color removal. The three considered factors, at two different levels, were current density ( j = 8 and 23 mA/cm 2 ), catalytic Fe 2+ concentrations (0.1 and 0.3 mmol L −1 ), and electrolysis time (10 and 50 min). According to RSM, the optimum operation conditions were Fe 2+ = 0.24 mmol L −1 , j = 23 mA/cm 2 , and t = 48 min. The maximal decolorization efficiency of 98% was achieved under these conditions.

An experimental design methodology was applied to study the effects of temperature, pH, biomass dose, and stirring speed on copper removal from aqueous solutions by Aspergillus terreus in a biosorption batch system. To identify the effects of the main factors and their interactions on copper removal efficiency and to optimize the process, a full 2(4) factorial design with central points was performed. Four factors were studied at two levels, including stirring speed (50-150 min(-1)), temperature (30-50°C), pH (4-6) and biosorbent dose (0.01-0.175 g). The main factors observed were pH and biomass dose, along with the interactions between pH and biomass, and stirring speed. The optimal operational conditions were obtained using a response surface methodology. The adequacy of the proposed model at 99% confidence level was confirmed by its high adjusted linear coefficient of determination (R(Adj)(2)=0.9452). The best conditions for copper biosorption in the present study were: pH 6, biosorbent dose of 0.175 g, stirring speed of 50 min(-1) and temperature of 50°C. Under these conditions, the maximum predicted copper removal efficiency was 68.52% (adsorption capacity of 15.24 mg/g). The difference between the experimental and predicted copper removal efficiency at the optimal conditions was 4.8%, which implies that the model represented very well the experimental data.

La investigación tiene como objetivo analizar la alternativa de habilitar cursos semipresenciales para el programa de Ingeniero Industrial Administrador, basada en la experiencia obtenida de manera obligatoria por consecuencia de la pandemia de COVID-19. Este enfoque se hace para afrontar la gran demanda de la carrera además de evolucionar en metodologías de trabajo. Después de una investigación exploratoria cuantitativa deductiva, a través de un instrumento de investigación previo, se encuesta a una muestra representativa de estudiantes y profesores de dicha carrera. Además, se recopila información de diferentes artículos que tratan con el tema del sector educativo y cómo funcionan las diferentes carreras y cursos digitales alrededor del mundo. Los resultados presentan que es viable la opción de la modalidad mixta, sin embargo, se decide descartar de esta implementación diversas unidades de aprendizaje relacionadas al uso de las matemáticas, además de aquellas que contienen un apartado de laboratorio durante su curso, los cuales son más eficaces de manera presencial.