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The objective of this work is to study the immediate transport flows of PM2.5 diesel exhaust emissions on a city sidewalk. Under calm conditions largest direct exhaust PM2.5 diesel concentrations tend to accumulate at two preferred heights: higher ones at 200–225 cm due to truck and buses aerodynamics, and lower ones at 130–160 cm due to light vehicles. Obtained flows indicate that exhaust emissions are transported to these heights via vortices generated by vehicular traffic. The lower height vortices transporting PM2.5 direct diesel emissions place children aged between 7 and 15 at a higher acute exposure risk due to their stature. Also, the hourly averaged PM2.5 concentrations tend to accumulate nearer to the roadside. This information was obtained using a specially designed electromechanical near-surface atmospheric profiler equipped with a PM2.5 measurement instrument, a thermistor and a sonic anemometer installed on a sidewalk. Using signal analysis techniques, coherent flows of direct PM2.5 emissions and thermal information were obtained. The proposed methodology can be used to evaluate before and after urban interventions, obtain full-scale sidewalk data for exposure studies and provides criteria on where to place sidewalk measurement instruments.

Diesel-powered vehicles are intensively used in urban areas for transporting goods and people but can substantially contribute to high emissions of black carbon (BC), organic carbon (OC), and other gaseous pollutants. Strategies aimed at controlling mobile emissions sources thus have the potential to improve air quality and help mitigate the impacts of air pollutants on climate, ecosystems, and human health. However, in developing countries there are limited data on the BC and OC emission characteristics of diesel-powered vehicles, and thus there are large uncertainties in the estimation of the emission contributions from these sources. We measured BC, OC, and other inorganic components of fine particulate matter (PM), as well as carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), ethane, acetylene, benzene, toluene, and C2-benzenes under real-world driving conditions for 20 diesel-powered vehicles encompassing multiple emission level technologies in Mexico City with the chasing technique using the Aerodyne mobile laboratory. Average BC emission factors ranged from 0.41–2.48 g kg−1 of fuel depending on vehicle type. The vehicles were also simultaneously measured using the cross-road remote sensing technique to obtain the emission factors of nitrogen oxide (NO), CO, total hydrocarbons, and fine PM, thus allowing for the intercomparison of the results from the two techniques. There is overall good agreement between the two techniques and both can identify high and low emitters, but substantial differences were found in some of the vehicles, probably due to the ability of the chasing technique to capture a larger diversity of driving conditions in comparison to the remote sensing technique. A comparison of the results with the US EPA MOVES2014b model showed that the model underestimates CO, OC, and selected VOC species, whereas there is better agreement for NOx and BC. Larger OC / BC ratios were found in comparison to ratios measured in California using the same technique, further demonstrating the need for using locally obtained diesel-powered vehicle emission factor database in developing countries in order to reduce the uncertainty in the emissions estimates and to improve the evaluation of the effectiveness of emissions reduction measures.

A computational system consisting of an urban mobility simulator, validated fluid dynamics and an integral exposure model, is proposed to obtain cyclist and pedestrian exposure to PMx and NOx. Pedestrian activities in the urban anthroposphere include walking and running. The computational experiments take place in a computer-generated urban canyon, subject to emissions from diesel and gasoline Euro 5 and Euro 6 vehicular technologies, in continuous and stop-and-go traffic scenarios, and three wind directions at two speeds. The exposure time in the computational domain of slow and fast pedestrians were obtained. Slow pedestrians had exposure times around 17% more than fast pedestrians due to their higher sidewalk residence time. Runners and cyclists decreased their exposures by 57% and 73% respectively compared with walkers. Two traffic scenarios are implemented: one due the presence of a hump and another without a hump. The presence of the hump, increased exposure and fuel consumption by 60% per heavy duty vehicle, about 44–48% per light duty vehicle and about 54–71% per passenger car. Vehicular technology had a large influence on exposure: Heavy duty-Euro 6 vehicle decreased 86% the exposure to PM2.5 and 66% to NOX with respect to Euro 5. The proposed computational system provides information on how wind velocity influenced the inhomogeneous pollutant distribution in the street-canyon, causing exposure to be dependent on pedestrian route location. Microscale sidewalk areas in the order of meters containing higher concentrations were thus located. The cleanest routes in the urban canyon were identified. When the wind intensity doubled from 2 to 4 m s−1, exposure concentration decreased around 45%. The proposed system provides a computational platform to study urban atmospheric fluids, scenarios such as pedestrian routes, vehicular technologies, traffic velocities, meteorological conditions and urban morphology affecting pollution exposure.

Recurrent personal exposure to ambient PM2.5 is associated with adverse human health effects, in particular on the respiratory and cardiovascular systems. Here, we present an assessment of personal exposure and inhalation of PM2.5 for five modes of transport (walking, cycling, public bus (trolleybus and diesel bus), conventional car (CC) and hybrid-electric car (HEC)) and two routes of similar distance, along a major road in the Mexico City metropolitan area (MCMA). Arithmetic average exposure concentrations ranged from 16.5 ± 6.5 µg m−3 for walking to 81.7 ± 9.1 µg m−3 for cycling (henceforth shown as average ±1 SD), with no significant differences with geometric averages. The maximum exposure concentration of 110.9 µg m−3 was observed for the conventional car. The highest exposure concentrations depended on route and the mode of transport, being observed for cycling and walking. The PM2.5 measurements showed large spatial heterogeneity in the exposure levels for walking and cycling, while public buses and private transport showed less spatial heterogeneity. The greatest peaks in PM2.5 coincided with 4-way intersections for all modes of transport, being positively influenced by traffic density. The mass of PM2.5 inhaled depended mostly on the mode of transport, and ranged between 1.0 ± 0.3 and 30.1 ± 14.2 µg km−1 for the HEC and bicycle, respectively. Local area PM2.5 increments identified as ‘residuals’ after subtraction of data recorded at the closest fixed monitoring site from exposure concentrations along the studied road suggested that inhalation for bicycle and diesel buses is strongly influenced by vehicular emissions. Residuals estimated for the trolleybus, CC and HEC confirmed a lower inhalation than for the other modes of transport evaluated due to protection by the cabin.

A set of indicators are proposed to determine the effect of traffic-calming devices on the environment and economy. They are based on vehicular emissions and energy consumption and are used to evaluate the viability and positioning of traffic-calming devices. First, a time window is defined on which the influence of a traffic-calming device can be determined providing a convenient frame of reference. Second, a concept of local cruising conditions is defined in order to have a basis of comparison between cases “with” and “without” traffic calming devices. The emissions considered were: HC, NOx, CO, PM 10 , and CO 2 . From the latter fuel consumption was estimated. Valuation of speed bumps on a secondary road in Mexico City was obtained as an example application of the proposed methodology.

Two sets of experiments were performed for collected particulate mass emitted directly from the exhaust of diesel engines burning diesel and biodiesel fuels: First, a diesel truck was used in the field, and in the second test, a similar diesel engine was used in the laboratory. The mass of particles and polycyclic aromatic hydrocarbons (PAH) was determined. No reduction was observed in the mass of particles per min using biodiesel relative to that produced when burning diesel. Pyrene and phenanthrene showed the highest mass concentrations in diesel and biodiesel in both tests. Reductions in these PAHs greater than 80% (in the truck field test) and 35% ± 11% (in the engine laboratory test) were observed when using biodiesel in any mixture thereof, with respect to diesel. The mean ± standard deviation of the ratios of BaA/(BaA + Chry) and (BbF + BkF)BghiP for diesel emissions were consistent with the literature. Four ratios amongst PAHs were proposed, with relative standard deviation

An urbanized version of MM5 (uMM5) was used at a 500 m horizontal grid-resolution to study effects on morning urban mixing depths and near roof-top stability from use of extensive green roofs in Mexico City, which is characterized by large Bowen ratios and high building storages. The model uses urban-morphology data, while building hydrothermal uMM5 input parameters were obtained from measurements over green and nearby conventional roofs. Evaluation of uMM5 predicted values against rooftop and planetary boundary layer (PBL) observations from extensive field measurement campaigns showed that the model performed reasonably well. Additional simulations were carried assuming that the roofs in entire urban neighborhoods were greened. Predicted mixing depths from these simulations, along with observed air pollution concentrations, were then used in a simple box model to evaluate potential green roof impacts on concentration. Results showed that green roofs produced an early morning (7–10 LST) cooling of up to 1.2 °C at rooftop levels, which reduced mixing depths during that period. Effects were greater on a day with weak synoptic forcing that on one 48 h later with strong synoptic forcing. The mixing-depth decreases produced increased box-model pollutant concentrations. While the green roofs did not elevate the observed concentrations of CO, SO2, and NO2 above World Health Organization (WHO) health standards, they did increase PM10, values (which were already above its standard) by as much as 8% from 7 to 9 LST, when local populations are normally exposed to peak concentrations. This study has applications in the analyses of building energy efficiency.

A stochastic model based on empirical probability distribution functions has been applied to estimate human exposure to emissions from the resuspension of road dust due to isolated wakes from moving vehicles. The model incorporates the turbulent nature of resuspension due to vehicular wake erosion phenomena, and is tested by in situ measurements. It statistically estimates exposure as a function of ambient temperature, traffic activity, human height, and breathe intake rates as a function of age and activity. The model is applied to evaluate whether communities in the Molango region in Mexico are affected by vehicular resuspension of Manganese (Mn) contaminated soil from on-road activities related to mining. Results showed that six and 10 year old children are at higher risk to vehicular resuspended dust exposure than adults, due to their lower height and higher respiratory intake rates during periods of light and moderate activity.

The introduction of hybrid electric vehicle (HEV) technology in the private car fleet of Mexico City is evaluated in terms of private costs, energy, public health and CO2 emission benefits. In addition to constructing plausible scenarios for urban expansion, emission, car fleet, and fuel consumption for year 2026 and comparing them with a 2004 base case, a time series is built to obtain accumulated economic benefits. Experimental techniques were used to build a vehicle library for a car simulator that included a Prius 2002, chosen as the HEV technology representative for this work. The simulator is used to estimate the emissions and fuel consumption of the car fleet scenarios. In the context of an urban scenario for year 2026, a complex air quality model obtains the concentrations of criterion pollutants corresponding to these scenarios. Using a technology penetration model, the hybridized fleet starts unfolding in year 2009 reaching to 20% in 2026. In this year, the hybridized fleet resulted in reductions of about 10% of CO2 emissions, and yielded reductions in daytime mean concentrations of up to 7% in ozone and 3.4% in PM2.5 compared to the 2004 base case. These reductions are concentrated in the densely populated areas of Mexico City. By building a time series of costs and benefits it is shown that, depending on fuel prices and using a 5% return rate, positive accumulated benefits (CO2 benefits + energy benefits + public health benefits − private costs) will start generating in year 2015 reaching between 2.8 and 4.5 billion US Dlls in 2026. Another modernized private fleet consisting exclusively of Tier I and II cars did not yield appreciable results, signaling that a change in private car technology towards HEV's is needed to obtain significant accumulated benefits.

Using wind erosion and air quality models, a study on the effect of PM10 from aeolian erosion episodes in Mexico City is presented. The important contribution of aeolian erosion on urban air quality, its genesis, morphology, location and regional implications such as the role played by surface confluences, the dry Lake of Texcoco and agricultural lands to the east and south-east of Mexico City is established. All analyzed episodes showed that wind erosion is a major cause of high PM10 concentrations in Mexico City. The wind erosion and air quality models used here provide useful computational tools to study the aeolian erosion phenomenon, its sources and impact on urban regions.

A methodology for estimating vehicular emissions comprising a car simulator, a basic traffic model, and a geographical information system is capable of estimating vehicle emissions with high time and space resolution. Because of the extent of the work conducted, this article comprises two sections: In Part 1 of this work, we describe the system and its components and use examples for testing it. In Part 2 we will study in more detail the emissions of the sample fleet using the system and will make comparisons with another emission model. The experimental data for the car simulator is obtained using on-board measuring equipment and laboratory Fourier transform IR (FTIR) measurements with a dynamometer following typical driving cycles. The car simulator uses this data to generate emission factors every second. These emission factors, together with information on car activity and velocity profiles of highways and residential and arterial roads in Mexico City in conjunction with a basic traffic model, provide emissions per second of a sample fleet. A geographical information system is used to localize these road emissions.

Using a meteorological computational model it is shown how, in the Valley of Mexico, a high pressure system together with the complex orography of the region induce the formation of a local confluence line. With the aid of a prognostic air quality model it is shown that the maximum pollutant mixing ratios are placed on and follow the confluence line which crosses over the most populated areas of Mexico City. This phenomenon provides an explanation of why and when pollutants assume its geographical distribution in the valley during high mixing ratio episodes.

Using an air quality model, two future urban scenarios induced by the construction of the new international airport for Mexico City are compared at a regional level. The air quality model couples the meteorology model MM5 and state-of-the-art photochemistry. The air quality comparison is made using metrics for the criterion gases selected for the study. From the two urban scenarios compared, the option for Tizayuca is moderately better than the option for Texcoco, because relative reductions in O3 and other photochemical pollutants are achieved over highly populated areas. Regardless of the site, the air quality for the central region of Mexico in the future will deteriorate. In the region of central Mexico, SO2 and NO2 will become important pollutants.

Using a prognostic air quality model that includes actual emissions, air pollution regimes over the central region of Mexico are simulated. It is shown that due to the complex orography, vertical circular patterns develop over the metropolitan area of Mexico City. In this way reactive and non-reactive pollutants can travel near the surface, be transported vertically and land in an area opposite to its initial route due to convective downward currents. This changes the surface pollutant concentrations on the landing area. Also, it is shown that air pollution is transported near the surface from the metropolitan area of Mexico City through Chalco in the South-east corner of the Mexico Valley, to the Valley of Cuautla affecting this area.

Using a prognostic air quality model it is shown that by the partial recovery of Lake Texcoco near the Metropolitan Area of Mexico City, a local reduction of about 11% to 15% can be achieved in concentration levels of ozone (O3), carbon monoxide (CO), sulphur dioxide (SO2) and chemical compounds with the potential of forming aerosols. This phenomenon takes place because of the land–lake breeze effect and local temperature modulation induced by the location and size of the recovered lake areas.

"Using an air quality model, this study shows how emissions from the “ Miguel Hidalgo ” refinery of Petróleos Mexicanos (Pemex) and the thermoelectric plant “ Francisco Pérez Ríos ” of the Comisión Federal de Elec - tricidad (CFE, Federal Electricity Commission) in Tula, Hidalgo influence the atmosphere of the Mexico City Metropolitan Area (MCMA). The model couples meteorology and chemistry. The weather scenario encompasses the period from October 20-28, 2005. Two scenarios are compared: the first assumes a 40% reduction in emissions of NO x , SO 2, and volatile organic compounds (VOCs) from the Tula complex (reduction scenario), and the second considers the scenario without reduction (baseline scenario). The model is compared with measurements of the Red Automática de Monitoreo Atmosférico (Automatic Environmental Monitoring Network). We observe that under certain weather conditions, the energy sector of Tula, Hidalgo affects the air quality in the MCMA. The reduction scenario is effective in reducing SO 2 concentrations; however, despite a 40% decrease in the emissions of ozone precursors, their concentrations in the MCMA did not decrease."

Numerical simulations of thermal field variation due to land use changes, such as the reduction of the lacustrine system and the growth of the urban area, in the Basin of Mexico are presented. It is shown that the historically recorded warming in the basin could be attributed, not only to the growth of the urban area, but more importantly to the drastic reduction in the lacustrine system that existed in the basin.

A version of the random choice method (RCM), which we call the conservative random choice method (CRCM), is introduced to solve the variable coefficient linear advection equation. CRCM is an advection scheme that does not create numerical diffusion nor dispersion, enabling it to preserve initial conditions, discontinuities, and other nonsmooth features. It is capable of handling the variable coefficients case without creating or destroying mass, as is the case of the original RCM. These properties make CRCM a useful scheme for applications such as atmospheric and water transport.

The Random Choice Method (RCM), widely used in the area of Computational Fluid Dynamics, is introduced to solve the advective component of the Atmospheric Transport Equation. RCM offers computational economy without introducing numerical diffusion or dispersive waves. In conjunction with the Fractional Steps Method, RCM is capalable of handling pollution sources and dispersion in a multidimensional setting.

International audience; A methodology to acquire valuable information on the chemical composition and evolution of vehicular emissions is presented. The analysis of the gases is performed by passing a constant flow of a sample gas from the tail-pipe into a 10 L multi-pass cell. The absorption spectra within the cell are obtained using an FTIR spectrometer at 0.5 cm?1 resolution along a 13.1 m optical path. Additionally, the total flow from the exhaust is continuously measured from a differential pressure sensor on a \textit{Pitot} tube installed at the exit of the exhaust. This configuration aims to obtain a good speciation capability by coadding spectra during 30 s and reporting the emission (in g/km) of both criteria and non-regulated pollutants, such as CO2, CO, NO, SO2, NH3, HCHO and some NMHC, during predetermined driving cycles. The advantages and disadvantages of increasing the measurement frequency, as well as the effect of other parameters such as spectral resolution, cell volume and flow rate, are discussed. To test and evaluate the proposed technique, experiments were performed on a dynamometer running FTP-75 and typical driving cycles for the Mexico City Metropolitan Area (MCMA) on a Toyota Prius hybrid vehicle. This car is an example of recent marketed automotive technology dedicated to reduced emissions, increasing the need for sensitive detection techniques. This study shows the potential of the proposed technique to measure and report in real time the emissions of a large variety of pollutants, even from a super ultra-low emission vehicle (SULEV). The emissions of HC's, NOx, CO and CO2 obtained here were compared to experiments performed in other locations with the same model vehicle. The proposed technique provides a tool for future studies comparing in detail the emissions of vehicles using alternative fuels and emission control systems.

A methodology to acquire valuable information on the chemical composition and evolution of vehicular emissions is presented. The analysis of the gases is performed by passing a constant flow of a sample gas from the tail-pipe into a 10 L multi-pass cell. The absorption spectra within the cell are obtained using an FTIR spectrometer at 0.5 cm-1 resolution along a 13.1 m optical path. Additionally, the total flow from the exhaust is continuously measured from a differential pressure sensor on a Pitot tube installed at the exit of the exhaust. This configuration aims to obtain a good speciation capability by coadding spectra during 30 s and reporting the emission (in g/km) of key and non-regulated pollutants, such as CO2, CO, NO, SO2, NH3, HCHO, NMHC, during predetermined driving routines. The advantages and disadvantages of increasing the acquisition frequency, as well as the effect of other parameters such as spectral resolution, cell volume and flow rate, are discussed. With the aim of testing and evaluating the proposed technique, experiments were performed on a dynamometer running FTP-75 and typical driving cycles of the Mexico City Metropolitan Area (MCMA) on a Toyota Prius hybrid vehicle. This car is an example of recent automotive technology to reach the market dedicated to reduce emissions and therefore pressing the need of low detection techniques. This study shows the potential of the proposed technique to measure and report in real time the emissions of a large variety of pollutants, even from a super ultra-low emission vehicle (SULEV). The emissions of HC's, NOx, CO and CO2 obtained here are similar to experiments performed in other locations with the same vehicle model. Some differences suggest that an inefficient combustion process and type of gasoline used in the MCMA may be partly responsible for lower CO2 and higher CO and NO emission factors. Also, a fast reduction of NO emission to very low values is observed after cold ignition, giving rise to moderate N2O and eventually NH3 emissions. The proposed technique provides a tool for future studies comparing in detail the emissions of different technologies using alternative fuels and emission control systems.

In this note we present numerical experiments on a domain decomposition algorithm for nonlinear elliptic boundary value problems in planar domains. There has recently been much progress in the development of such algorithms for linear elliptic problems ([1],[2],[3],[4]). These have focused on variational characterizations of the problem and on the preconditioning of the Schur complement associated with the decomposition. Although these could be used as part of a global Newton-type iterative scheme to solve a nonlinear problem, we choose the alternate path of first decomposing the problem and then applying an iterative method. Our motivation for this is two-fold; first, we expect it will lead to algorithms which will require less communication between subproblems, an attractive property for implementations on parallel processors; second, this approach has even been found to be more efficient for serial computations in some cases [6]. The essential step in this method is the solution of what we call the basic equations, a nonlinear analogue of the Schur complement problem. We are particularly concerned with the choice of boundary conditions at boundaries where subdomains intersect and their effect on the basic equations. Note that the methods we propose may also be applied to linear problems and seem to be novel in that context. We restrict ourselves here to the study of a decomposition into two domains

We describe an application of a recently developed speech compression technique to automatic recognition of isolated words (from a given dictionary). The scheme maps sampled speech, from a given word, into a finite codebook (of the same size as the dictionary) using linear predictive coding (LPC) all-pole models and a minimum distortion or nearest neighbor rule between all samples from the given word and the codewords from the codebook. Standard LPC techniques are used to design the codebook, but the final system requires no on-line LPC analysis.

Air quality in a city with an important industrial and human development, is taking more and more relevance as a part of a background of sustainable development. The space and time distribution of radioactive particles (containing elements like 238U, 232Th, 40K, 7Be and 137Cs) has being studied in Chihuahua City, Mexico, by means of several sampling campaigns during the years of 2003, 2005 and 2007. In order to assess the behavior of the model in meteorological terms as much as in the isotope transport the data from March 6th to 8th and from April 11th to 13th 2007 have been analyzed. A Multiscale Model denominated MCCM has implemented along with Erosion Model named WEPS (Wind Erosion Prediction System). WEPS is a process-based, continuous, daily time-step model that simulates weather, field conditions, and erosion while MCCM is based on the Fifth Generation Mesoscale Model MM5.The soil samples collected during the period were analyzed by means of gamma spectrometry using a hyper pure germanium detector. The obtained results were processed using SURFER, which is an outline and threedimensional surface plotting software, in order to establish the space distribution of the radionuclide in the studied area. The results showed similarities between 137Cs and 7Be, and between 238U, 232Th and 40K remains a significant relationship in the distribution of natural radionuclide in the study area as well as between the cesium and beryllium. These results were reproduced by means of the MCCM, to which the isotopes of interest were incorporated as new variables. The obtained results match with those observed experimentally in 2007 when they were analyzed with visualization software. As later objectives to this work the analysis of the periods 2003 and 2005 will be added, in order to confirm the good performance of the model and carry out predictive calculations about the transport and distribution of the interest elements according to the weather conditions in the zone during the analysis periods.