In recent years, due to various anthropogenic activities, such as agriculture and livestock, the presence of nitrogen-associated contaminants has been increasing in surface- and groundwater resources. Among these, the main compounds present in groundwater are ammonia, nitrite, and nitrate. However, it is sometimes difficult to assess such effects given the scarcity or lack of information and the complexity of the system. In the current study, a methodology is proposed to assess nitrate in groundwater from diffuse sources considering spatiotemporal patterns of hydrological systems using a coupled SWAT/MODFLOW/MT3DMS model. The application of the model is carried out using a simplified simulation scheme of hydrological and agricultural systems because of the limited spatial and temporal data. The study area includes the Cuitzeo Lake basin in superficial flow form and the Morelia–Querendaro aquifer in groundwater flow form. The results within the methodology are surface runoff, groundwater levels, and nitrate concentrations present in surface- and groundwater systems. The results indicate that the historical and simulated nitrate concentrations were obtained within acceptable values of the statistical parameters and, therefore, are considered adequate.

Groundwater models serve the function of predicting and analyzing aquifer behavior. They require input information, such as hydrogeological parameters like hydraulic conductivity and storage coefficient, which are used to calibrate the model, and elementary actions that include recharge and extracted volumes. There are cases in which it is insufficient to know the homogeneous recharge entering through the surface basin, referred to as traditional recharge, since, in many instances, the distribution is altered by changes in land use. For this reason, based on the geomorphological characteristics of the basin, weighting is proposed for sites with greater recharge capacity. The present work shows a solution to the recharge distribution using the potential groundwater recharge (PGR) map, which is formed by weighting spatially distributed information: (i) drainage, (ii) precipitation, (iii) land use, (iv) geological faults, (v) soil type, (vi) slope, and (vii) hydrogeology. A comparison is made between groundwater modeling using traditional recharge and PGR recharge. It is noted that the modeling perform similarly for both recharges, and the errors do not exceed 5% absolute error, which validates the model’s reliability. This manuscript demonstrates how to model and calibrate groundwater in aquifers with scarce information and variable recharge, making it reproducible.

A systematic review of the scientific literature focused on the analysis of the main strategies related to the management of Eichhornia crassipes [water hyacinth] in Mexico is presented. The review was classified according to the levels of the biomass valorization pyramid, using specific inclusion and exclusion criteria: (i) eradication; (ii) physical control of the plant; and (iii) exploitation of its biomass. It focused on research conducted in Mexico from 1971 to 2023, which allowed for the analysis of a total of 147 studies. The results indicated that 73.4% of the research in Mexico is oriented towards the exploitation and valorization of water hyacinth biomass through the transformation of the plant into mid-value products, such as chemicals and materials (70.7%), energy (12.2%), food (7.3%) and health and lifestyle products (9.8%); however the sectors considered high-added-value, such as pharmaceuticals, fine chemicals and food, continue to be areas of opportunity. The remaining 26.6% focuses on control and eradication strategies, through the insertion of biological enemies, and physical control, by means of cutting and crushing the plant in situ. This situation underscores the importance of promoting integrated management approaches that incorporate biomass recovery, contributing to environmental sustainability and the responsible use of this invasive resource.

Arsenic (As) is a globally distributed metalloid that is emitted from natural sources, including geothermal processes, as well as from anthropogenic activities. The village of Araró, in the state of Michoacán, is located in the Trans-Mexico volcanic belt, which is a highly active geothermal site in central Mexico. The aim of this study is to evaluate the health risk to residents of the town from As exposure from dust through oral, dermal and inhalation pathways, using Monte Carlo simulation. Forty dust samples were randomly collected in Araró village, and these were analyzed using portable X-ray fluoroscopy. The As levels obtained for dust samples ranged from 5.94 to 42.53 mg/kg. Point estimation of hazard quotient (HQ) and its probability distribution was assessed using U.S. Environmental Protection Agency (USEPA) formulas and Monte Carlo simulation, respectively, for oral, dermal and inhalation pathways. Anthropometrical data were obtained from the Health and Nutrition National Survey 2018. Mean average daily dose (ADD) for all age groups (preschooler, Elementary (6–12), adolescent and adult) were below safety limits. A total of 4 and 6% of preschooler and Elementary dermal ADDs were above safety limits. For oral and dermal exposure in children, HQ and hazard index (HI) mean values were higher than other age groups, despite safety limits not being reached. Also, it was found that dermal carcinogenic risk (CR) value for adults may represent a potential cancer risk. Despite a relatively low reported concentration of As it is important that more As exposure routes be explored to determine the severity of the problem because previous studies have shown high As concentrations in drinking water.

The objective of this study is to investigate the drying kinetics of fruit and vegetable peel biowaste using a sustainable technique as a key-pretreatment for its conversion into useful feedstock. Biowaste represents a missed potential source of bioenergy and bioproducts, but moisture removal is required, and conventional drying methods are expensive since they require great quantity of energy supplied, almost always, by a non-renewable energy. In this study six batches with the same quantity of biowaste, and heterogeneous physical composition were dried under open-sun conditions. We evaluated the influence of the interaction between drying area and the initial moisture content on drying rate. Eight semi-theoretical models were fitted using Levenberg–Marquardt algorithm to predict drying rate, and their accuracy was assessed through goodness-of-fit tests. Maximum moisture content to preserve biomass (10%) was reached on 5^th day and the equilibrium on 16^th day of drying. According to goodness-of-fit test (R² = 0.999, χ² = 4.666 × 10⁻⁵, RMSE = 0.00683) the best model to predict drying rate was Two-term model. The mathematical model obtained from Fick’s second law is reliable to predict drying kinetics, R² (0.9648 ± 0.0106); despite the variation between drying area and initial moisture content. Kruskal-Wallis test showed that drying rates between batches are not significantly different (p = 0.639; 0.05); nor effective diffusion coefficient (D_eff = 4.97 × 10⁻¹¹ ± 0.3491 × 10⁻¹¹), (p = 0.723; 0.05). The study of drying kinetics is crucial for selecting the optimal biowaste treatment based on its generation context. This could enable its use as feedstock for bioproduct or bioenergy production, thereby reducing waste accumulation in landfills and environmental impact.

Surface hydrologic modeling becomes a problem when insufficient spatial and temporal information is available. It is common to have useful modeling periods of less than 15 years. The purpose of this work is to develop a methodology that allows the selection of meteorological and hydrometric stations that are suitable for modeling when information is scarce in the area. Based on the scarcity of data, a series of statistical tests are proposed to eliminate stations according to a decision-making process. Although the number of stations decreases drastically, the information used is reliable and of adequate quality, ensuring less uncertainty in the surface simulation models. Individual basin modeling can be carried out considering the poor data. The transfer of parameters can be applied through the nesting of basins to have information distributed over an extensive area. Therefore, temporally and spatially extended modeling can be achieved with information that preserves statistical parameters over time. If data management and validation is performed, the modeled watersheds are well represented; if this is not done, only 26% to 50% of the runoff is represented.