An approach for domino effect reduction based on optimal layouts

An approach to reduce the probability of producing a domino effect in process industry is developed in this work. It is assumed that optimal layouts should include appropriate analysis to reduce risk during the process design stage. The model developed for this approach combines the estimation of probability of damage due to overpressure, proposed by Mingguang and Juncheng (2008), and escalation threshold values defined by Cozzani, Gubinelli, and Salzano (2006). These equations are combined with other typical layout constraints as well as bounding the probability constraint, which has resulted in a highly non-linear MINLP problem. Solving a case study used by other authors provides evidence for reliability of the developed approach. In this way, layouts are designed to reduce the escalation probability yielding safe distributions.     

Methods for collecting time/activity pattern information related to exposure to combustion products

Focus groups, surveys and questionnaires, diaries and observations can be used to gather information about people's exposure to a wide range of combustion products. Information about locations and durations of exposure, and sources of exposure can be obtained with these instruments. The types of instruments used must be fine tuned to meet the design characteristics of the community in which the study will be conducted.     

Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.     

DDT, DDE, and 1-hydroxypyrene levels in children (in blood and urine samples) from Chiapas and Oaxaca, Mexico

The aim of this study was to evaluate the DDT, DDE, and 1-hydroxypyrene exposure levels of children living in communities located in southeastern Mexico. The study communities were Lacanja and Victoria in Chiapas state and Ventanilla in Oaxaca state. Children living in Lacanja had total blood DDT levels (mean?±?SD, 29,039.6?±?11,261.4 ng/g lipid) that were significantly higher than those of children in Victoria (10,220.5?±?7,893.1 ng/g lipid) and Ventanilla (11,659.7?±?6,683.7 ng/g lipid). With respect to the 1-hydroxypyrene levels in urine samples, the levels in Lacanja (4.8?±?4.1 μg/L or 4.5?±?3.9 μmol/mol creatinine) and Victoria (4.6?±?3.8 μg/L or 3.9?±?3.0 μmol/mol Cr) were significantly higher than levels found in Ventanilla (3.6?±?1.4 μg/L or 2.5?±?0.5 μmol/mol Cr). In conclusion, our data indicate high levels of exposure in children living in the communities studied in this work. The evidence found in this study could be further used as a trigger to revisit local policies on environmental exposures.