PM2.5 were collected in March 2006 during the MILAGRO campaign (Megacities Initiative: Local and Global Research Observations) carried out in the northern region of the Mexico City Metropolitan Area (MCMA), in order to realize an individual characterization of particulate matter through scanning electron microscopy coupled with an energy–dispersive X–Ray analyzer (SEM–EDX), acquiring information from around 6 000 particles about their morphology, size and superficial chemical composition. Measurements of the aerosol were obtained at a site located in the northern part of Mexico City (T0) and also at a site located 30km northeast (T1) in four time intervals 6:00 – 9:00; 11:00 – 14:00; 16:00 – 19:00 and 21:00 – 0:00hrs. Employing backscattered electron detector (BSD) anthropogenic phases were analyzed with the EDX and elemental composition of individual particles showed mainly elemental composition of Fe–O (24% relative abundance) with spherical morphology congruent to emissions from metal–mechanic industrial process and soil re–suspension. Twenty percent of the aerosol was “Pb–rich” particles identified as agglomerations of nanometric spheres of individual size distributions among 1.0 – 600nm and they are related to high temperature industrial emissions. The “Ba– rich” particles (16%) presented chemical associations of Ba–S–O and irregular morphologies and they were related to emissions from the mineral phase of barite that constitutes the asbestos of the automobile pieces. “C–rich” group was the fourth most abundant (12%) one with predominant morphology corresponds to nanometric spheres (between 600 and 800nm) of compact and continuous surface, this kind of particles are mainly related to vehicle exhaust emissions and their temporal distribution presented a clear decrease during weekends when vehicle traffic is reduced on the MCMA. Elements like Ca, Zn, Cu, Sr, Sn, Al, Sb, Na and W were also detected in less relative abundance (28% of the total), and their individual morphology and possible source emissions are described

The residents of Mexico City face serious problems of air pollution. Identifying the most representative scenarios for the transport and dispersion of air pollutants requires the knowledge of the main wind circulation patterns. In this paper, a simple method to recognize and characterize the wind circulation patterns in a given region is proposed and applied to the Mexico City winds (2001–2006). This method uses a lattice wind approach to model the local wind events at the meso-β scale, and hierarchical cluster analysis to recognize their agglomerations in their phase space. Data of the meteorological network of Mexico City was used as input for the lattice wind model. The Ward’s clustering algorithm with Euclidean distance was applied to organize the model wind events in seasonal clusters for each year of the period. Comparison of the hourly population trends of these clusters permitted the recognition and detailed description of seven circulation patterns. These patterns resemble the qualitative descriptions of the Mexico City wind circulation modes reported by other authors. Our method, however, permitted also their quantitative characterization in terms of the wind attributes of velocity, divergence and vorticity, and an estimation of their seasonal and annual occurrence probabilities, which never before were quantified.

Seasonal changes in the PM1 chemical composition north of Mexico City