Water samples from municipal sources and specific sites in the distribution systems in five Mexican cities were analyzed for 40 volatile organic compounds using a gas chromatograph–mass spectrometer system coupled with a purge‐and‐trap sampler. Benzene and four halogenated compounds, methylene chloride, chloroform, dibromomethane, and dibromochloromethane, were consistently detected in all five cities. Another 20 analytes were identified in some of the 48 sites involved. In many cases, detected concentrations were higher than some internationally accepted drinking water standards. At the time of the study, Mexican regulations did not include values for maximum allowable concentrations levels for volatile organic compounds. From 1996, total trihalomethanes and 10 organochlorine pesticides have been included in Mexican drinking water regulations. © 2000 John Wiley & Sons, Inc. Environ Toxicol 15: 131–139, 2000

Water samples from municipal sources and specific sites in the distribution systems in five Mexican cities were analyzed for 40 volatile organic compounds using a gas chromatograph-mass spectrometer system coupled with a purge-and-trap sampler. Benzene and four halogenated compounds, methylene chloride, chloroform, dibromomethane, and dibromochloromethane, were consistently detected in all five cities. Another 20 analytes were identified in some of the 48 sites involved. In many cases, detected concentrations were higher than some internationally accepted drinking water standards. At the time of the study, Mexican regulations did not include values for maximum allowable concentrations levels for volatile organic compounds. From 1996, total trihalomethanes and 10 organochlorine pesticides have been included in Mexican drinking water regulations.

The basin of Rio de la Sabana is the largest tributary of the Tres Palos coastal lagoon in Southwest Mexico, east of Acapulco. This lagoon and its upstream basin areas have become a high priority area for the preservation of coastal and marine environments. To obtain information about water quality as affected by urban expansion since 2002, fourteen physicochemical parameters (temperature, pH, electrical conductivity, dissolved oxygen, ammonium, nitrate, nitrite, sulphate, phosphate), biochemical (biological and chemical oxygen demand, methylene blue active substances) and bacteriological parameters (total and fecal coliforms) were determined. This sampling was done for dry and rainy season conditions at seven locations (S1, S2, S3, …, S7) along the river, spaced 3 to 6 km apart to a total of 30.4 km. The results were grouped into four zones: (Z1) reference, (Z2) transition, (Z3) polluted, (Z4) recovery. The Alborada (S5) and Tunzingo (S6) sites, adjacent to dense high-class residential areas (Z3), had the greatest pollution charges in both seasons, while the La Poza (S7) site near the Tres Palos lagoon (Z4) showed a decrease in pollution. All parameters correlated with increasing head-to down-river sampling distance by following linear (pH, DO) or curvilinear patterns (all other parameters). Using sampling location and dry versus rainy sampling season as multivariate regression (predictor) variables led to least-squares capturing: 1) 66% to 95% of the T(˚C), pH, DO, and 3 4 PO − variations, and 2) 57% to 96% of the log-linear variations of the other parameters. Among the parameters,

BACKGROUND Dynamic modeling of the anaerobic treatment of agro‐industrial waste can help determine optimal operating conditions to maximize the process performance. For this, it is necessary to select an appropriate model and adapt it to the specific conditions of the substrate. In this work, a simple unstructured kinetic model for the anaerobic treatment of different agro‐industrial waste is proposed. The proposed model considers the three most relevant stages of anaerobic digestion (AD) and can be adapted for the treatment of different substrates, modes of operation (batch or continuous), and/or generated products (VFA or methane production), thus requiring a minimum of process macroscopic measurements. RESULTS To evaluate the scope of the model, two case studies were analyzed: (i) methane production from tequila vinasse and agave hydrolysates, and (ii) volatile fatty acids (VFA) and biogas production from raw cheese whey. For each case, parameter estimations were performed using the Levenberg – Marquardt algorithm, which yielded a simplified model with high determination coefficients (R2 > 0.95). Moreover, the kinetic parameters estimated were consistent physically and statistically. CONCLUSION Numerical results show that the proposed model can satisfactorily describe the dynamic behavior of the key variables of the three types of agro‐industrial waste evaluated. Therefore, the proposed model might be advantageous to determine the conditions that maximize performance without risking process stability. © 2022 Society of Chemical Industry (SCI).