Mexico City Metropolitan Area Research Articles

Predicting fine-scale daily NO2 over Mexico city using an ensemble modeling approach

In recent years, there has been growing interest in developing air pollution prediction models to reduce exposure measurement error in epidemiologic studies. However, efforts for localized, fine-scale prediction models have been predominantly focused in the United States and Europe. Furthermore, the availability of new satellite instruments such as the TROPOsopheric Monitoring Instrument (TROPOMI) provides novel opportunities for modeling efforts. We estimated daily ground-level nitrogen dioxide (NO2) concentrations in the Mexico City Metropolitan Area at 1-km2 grids from 2005 to 2019 using a four-stage approach. In stage 1 (imputation stage), we imputed missing satellite NO2 column measurements from the Ozone Monitoring Instrument (OMI) and TROPOMI using the random forest (RF) approach. In stage 2 (calibration stage), we calibrated the association of column NO2 to ground-level NO2 using ground monitors and meteorological features using RF and extreme gradient boosting (XGBoost) models. In stage 3 (prediction stage), we predicted the stage 2 model over each 1-km2 grid in our study area, then ensembled the results using a generalized additive model (GAM). In stage 4 (residual stage), we used XGBoost to model the local component at the 200-m2 scale. The cross-validated R2 of the RF and XGBoost models in stage 2 were 0.75 and 0.86 respectively, and 0.87 for the ensembled GAM. Cross-validated root-mean-squared error (RMSE) of the GAM was 3.95 μg/m3. Using novel approaches and newly available remote sensing data, our multi-stage model presented high cross-validated fits and reconstructs fine-scale NO2 estimates for further epidemiologic studies in Mexico City.

COVID-19, social identity, and socially responsible food consumption between generations.

The objective of the research was to analyze the effect of COVID-19 with the predictors of the health belief model (perceived severity, perceived benefits, and cue to action) on the social identity of the consumer and the social identity of the socially responsible food consumption among four generation groups of adults based on the stimulus-organism-response model. The study had a quantitative approach explanatory design and a cross-sectional temporal dimension. A total of 834 questionnaires were collected from adults in the metropolitan area of Mexico City, and the data were analyzed through partial least squares structural equation modeling. The results indicated that perceived severity, perceived benefits, and cue to action positively and significantly influenced social identity, and this positively and significantly influenced socially responsible consumption. In addition, identity was found to be a variable that had a total mediation effect between perceived severity and socially responsible consumption, perceived benefits and socially responsible consumption, and cue to action and socially responsible consumption. While the perceived barriers only had a direct effect on socially responsible consumption. Likewise, a difference was found between generation X and Y, generation Z and X, and generation Y and X in the relationship between cue to action, belonging to a social network group, and social identity. In this sense, these results allow us to consider that when environmental stimuli (predictors of the health belief model) affect the organism (social identity), it will respond with socially responsible food consumption. This type of consumption is explained through social identity and is modified according to the age of the consumers due to the effects of social networks.

Seasonal characterization of tropospheric ozone fluctuation in Mexico City

The air pollution due to tropospheric ozone (O3) is one of the most serious problems of large industrialized cities in the world. The excessive increase in O3 has a negative impact on the population health. Consequently, researchers have focused their efforts establishing measures to characterize the statistical analysis of spatio-temporal data. This work shows a study based on seasonal analysis of spatio-temporal data through second order structure function to and the scale behavior in power law by using the Hurst exponent (H) and analyzing the trend of fluctuations associated with O3 pollution concentration records at four monitoring stations in the Metropolitan Area of Mexico City (MAMC) considering the four season of the year. The records were consulted from the database of the Automatic Atmospheric Monitoring Network (AAMN) in Mexico City from 2010 to 2018. The results show the differences in behavior of ozone according to the seasons of the year in this megacity. The behavior of statistical persistence predominates in spring, with 63.89% of occurrence over the total of the samples analyzed. In winter, the observed regime is antipersistent, with 80.56%. The three regimes: persistence, randomness and antipersistence were observed in summer and autumn, with a similar proportion of occurrence of 33% ± 3%. Given the above, the climatological characteristics of each season could be associated with the regimes of persistent, random and antipersistent behavior of the fluctuation of the concentration of the pollutant O3

Measurement report: Spatiotemporal variability of peroxy acyl nitrates (PANs) over Mexico City from TES and CrIS satellite measurements

Abstract. Peroxy acyl nitrates (PANs) are photochemical pollutants with implications for health and atmospheric oxidation capacity. PANs are formed via the oxidation of non-methane volatile organic compounds (NMVOCs) in the presence of nitrogen oxide radicals (NOx = NO + NO2). While urban environments are large sources of PANs, in situ observations in urban areas are limited. Here we use satellite measurements of PANs from the Tropospheric Emission Spectrometer (TES) and the Suomi National Polar-orbiting Partnership (S-NPP) Cross-track Infrared Sounder (CrIS) to evaluate the spatiotemporal variability of PANs over and around Mexico City. Monthly mean maxima in PANs over the Mexico City Metropolitan Area (MCMA) occur during spring months (March–May). This time of year coincides with a peak in local photochemistry and more frequent air stagnation. Local fire activity also typically peaks between February and May, which leads to strong interannual variability of PANs over the MCMA. We use S-NPP CrIS data to probe the spatial outflow pattern of PANs produced within urban Mexico City during the month with the largest mixing ratios of PANs (April). Peak outflow in April occurs to the northeast of the city and over the mountains south of the city. Outflow to the northwest appears infrequently. Using observations during 2018 versus 2019, we also show that PANs were not significantly reduced during a year, with a significant decrease in NOx over Mexico City. Our analysis demonstrates that the space-based observations provided by CrIS and TES can increase understanding of the spatiotemporal variability of PANs over and surrounding Mexico City.

Physiological status of House Sparrows (Passer domesticus) along an ozone pollution gradient

Mexico City is one of the most polluted cities in the world, and one in which air contamination is considered a public health threat. Numerous studies have related high concentrations of particulate matter and ozone to several respiratory and cardiovascular diseases and a higher human mortality risk. However, almost all of those studies have focused on human health outcomes, and the effects of anthropogenic air pollution on wildlife species is still poorly understood. In this study, we investigated the impacts of air pollution in the Mexico City Metropolitan Area (MCMA) on house sparrows (Passer domesticus). We assessed two physiological responses commonly used as biomarkers: stress response (the corticosterone concentration in feathers), and constitutive innate immune response (the concentration of both natural antibodies and lytic complement proteins), which are non-invasive techniques. We found a negative relationship between the ozone concentration and the natural antibodies response (p = 0.003). However, no relationship was found between the ozone concentration and the stress response or the complement system activity (p > 0.05). These results suggest that ozone concentrations in air pollution within MCMA may constrain the natural antibody response in the immune system of house sparrows. Our study shows, for the first time, the potential impact of ozone pollution on a wild species in the MCMA presenting the Nabs activity and the house sparrow as suitable indicators to assess the effect of air contamination on the songbirds.

‘Seeing is experiencing’: impact of showcasing fashion merchandise on digital platforms

Purpose The principal purpose of this study is to analyze the consumer emotions on virtual merchandising in the context of social consumption ecosystem driven by value and lifestyle across the big middle consumer segment. Design/methodology/approach The qualitative information has been collected from 114 respondents selected through snowballing technique within the metropolitan area of Mexico City. A semi-structured research instrument was used to conduct the in-depth interviews online. Findings The results of the study indicate that technology-led virtual merchandising stimulates arousal and merriment among consumers, which converges the self-image congruence and appearance similarity. The subjects of the study have endorsed that visual stimulus leading to self-image and body image congruence develop consistent arousal and merriment, which lead to positive purchase intentions and buying decisions and inculcate the perception as seeing is experiencing. Research limitations/implications The samples drawn for this study may also limit the possibilities of generalization of the study results and map the consumer behavior in a predetermined pattern. Practical implications This study is founded on the theoretical maxims of theory of visual perceptions, cognitive theory of reasoning, theory of appearance and reality and Heider’s balance theory and contributes to these theories by explaining the relationship between the social self-concept and self-image congruence. Social implications Firms retailing online fashion apparel should also be engaged in developing user-generated contents through communications on social media encouraging experiential videos, slogans and reviews. Originality/value This paper significantly contributes to theoretical and practical implications on virtual shopping, emotions and beliefs and consumption culture.

Spatial patterns and risk of aggression of dogs and cats in a central township of Mexico City

Dog and cat aggressions are public health concerns associated with rabies transmission to the human population. The social and environmental conditions of marginalized and urban areas stand a risk due to people's contact with dogs. This study aimed to identify spatial patterns related to dog and cat aggression in a densely populated area in the center of Mexico City, analyzing the risk of aggression at the census unit level in the 2018–2020 triennium. This cross-sectional study was carried out in Coyoacán, in the south-central area of Mexico City's urbanized region. The total number of cases (n = 1,078) was obtained from monthly records of aggressions by dogs and cats, from the Control and Prevention of Zoonoses-Rabies Program of the Coyoacán Sanitary Jurisdiction. The information collected was related to the victims and the aggressors. Associations between the occurrence of bites and the characteristics of the victim were evaluated using a geographic information system (GIS), as well as the spatio-temporal distribution of the aggressions to the census unit level. Out of 1,078 cases reported, 977 (90.6%) were caused by dogs and 101 (9.4%) by cats, 55.1% (n = 587) occurred within the same household, and 13.7% (n = 148) were categorized as severe injuries. Adult men were the most affected group. Attacks on the street had a higher risk of resulting in a severe injury, compared to those that occurred at home (OR 1.63, 95CI 1.15 - 2.31, p <0.006). According to the standardized rate of the triennium, the values ​​ranged between 54.1 and 619 aggressions per 100,000 inhabitants, and summer was the season with a higher probability of occurrence. These results provide a basis for the analytical investigation of the spatial patterns of dog and cat aggression, highlighting the need to implement efficient surveillance systems and public health strategies.

Commercial agreements with retailers to strengthen an early response to earthquakes in an area of Mexico City

Commercial agreements with retailers to strengthen an early response to earthquakes in an area of Mexico City

Dependence of bioavailability of lead compounds in soils on the type and source of contamination (the example of Mexico City and mining area of Parral, Mexico)

Evaluation and monitoring of soil contamination with heavy metals relies in most cases on their bulk concentrations whereas the risks of negative effects on human health depend upon the content of their bioavailable forms. The paper presents the study of the dependence of lead bioavailability in the surface soil horizons upon the contamination type and source. Two territories in Mexico with sharp difference of the source of pollution: Mexico City megapolis where the lead in soils originates from the ethyl gasoline burning and mining district in the south of Chihuahua State where the mine tailings are the source of the toxic elements including lead. Bulk lead concentrations were measured by the X-ray fluorescence method, bioavailability was estimated by the method imitating the effect of the stomach and intestine solutions. The research has shown that both in Mexico City (especially in its central part) and in the mining district in the Chihuahua State bulk lead concentrations are several times higher than the background values. The soils of the mining district have average bulk lead concentrations 787,5 mg/kg and show the average bioavailability values 64% whereas in the Mexico City megapolis average bulk concentrations of lead are lower - 324,7 mg/kg but bioavailability reaches 83% and in some samples even 100%. These results support the conclusion that despite lower bulk lead concentrations in Mexico City the risk of its negative effect on humans is higher than in the mining district polluted with the wastes of mining industry. The explanation of the observed tendency is that the chemical form of lead has a major influence on its bioavailability. Dependence of bioavailability upon the bulk concentrations within each study territory has not been established.

Ethnoentomological knowledge of an edible insect (Coleoptera: Cerambycidae) in a peri urban area of Mexico City

Human interactions with insects are represented in a wide range of manifestations. This has been evinced in what is called ethnoentomological knowledge, in other words, the knowledge about insects that is passed on through time within a community. In Isidro Fabela, a semi-rural municipality located in the surroundings of the metropolitan area of Mexico City, the inhabitants know the larvae of a beetle aschizas. Children up to the elderly consume them through different cooking methods. However, to date, this had not been investigated yet. Therefore, due to the lack of studies, our first task was to find out its taxonomic identity and document the ethnoentomological knowledge through 33 personal interviews following a semi-structured form and participatory observation. Results indicate thatchizas are the larvae ofTrichoderes pini Chevrolat 1843, a cerambycid species related to decaying wood and found for the first time in the study area. The termchiza comes from the Otomi indigenous language that means ‘the one who eats wood’ and people recognise their importance as contributors to the wood degradation process in the forest. Although for most peoplechizas consumption is mainly regarded as a hobby or traditional practice, for some people selling them represents an opportunity to earn an extra income. Finally, a decrease inchizas occurrence was found, probably because of the rural-urban transition process, absence of regulations concerning the wild insects’ exploitation, and public policies for fire and forest management. We suggest that the knowledge that inhabitants have and is presented in this paper, should be shared and promoted for a future implementation of conservation strategies including their sustainable management, together with more academic research.

The Use of Mobile Phones and Other Unsafe Behavior While Cycling in the Metropolitan Area of Mexico City

Unsafe behavior while driving contributes to road accidents. The paper addresses cyclists’ risky behavior by employing a questionnaire-based survey to a sample of n = 1136 in the metropolitan area of Mexico City. The main results are as follows: (a) 31.4% and 24.2% of the participants use a mobile phone for talking and text messaging while cycling, respectively, with males engaging in these unsafe acts more often than females; (b) a high percentage of participants are most likely to communicate with their parents, through either talking (48.9%) or text messaging (39.6%); (c) regarding the use of mobile phones for talking/texting (along with social network and gender) as predictors of a crash/fall while cycling, it was found that a one SD change in the frequency of talking while cycling increased the odds of a crash/fall by a factor of 1.198, as did a one SD increase in the frequency of texting by 1.232, while gender contributed to the outcome but not the individuals to whom cyclists talk or text; (d) cycling “without holding the handlebars” contributed significantly to the outcome. An education campaign or legislation enforcement (or both) may be needed to prevent single-bicycle crashes related to this unsafe act.

Food Producers in The Peri-Urban Area of Mexico City. A Study on the Linkages between Social Capital and Food Sustainability

Small producers in peri-urban areas have been identified as key actors in building more sustainable urban food systems, but they often have limited capacities to develop and consolidate their initiatives. This article describes the conditions of peri-urban farmers in Mexico City who work with agroecological schemes, analyzing the role of social and cultural capital in their ability to consolidate their economic-productive projects and establish links with consumers in the city. The research was developed from an anthropological perspective based on field visits and interviews conducted in 60 production units located in the peri-urban area of Mexico City. The article discusses the literature on peri-urban agriculture and the contextual particularities of the case study and then describes a typology constructed based on the analysis of the documented cases, considering the objectives of the initiatives and the different types of social and cultural capital on which their activities and marketing strategies are based are considered. The discussion argues that the social and cultural capital of the production units are key elements in determining the viability of the agroecological transition, reaffirming the importance of social articulation and other sociocultural aspects for the promotion of sustainable food projects.

Use of evolutionary computation and guide curves to optimize the operating policies of a reservoir system established to supply drinking water

The objective of the present study was to develop a genetic algorithm capable of establishing optimal operating policies for monthly extractions from the three main reservoirs of the Cutzamala System, which supply drinking water to the Mexico City metropolitan area. In previous studies, annual water extraction defined with an annual Z curve in terms of the total water storage in the reservoirs on November 1 was optimized using genetic algorithms. In this study, a percentage of total annual extraction for each reservoir was also optimized, but monthly water extractions were adjusted too, when the water level fell outside the upper or lower limits of guide curves stablished for each reservoir. The capabilities of the genetic algorithms combined with a detailed simulation of reservoirs operation were used to optimize the levels of the guide curves and also to optimize the adjusted monthly programed extractions as linear functions of the difference between the actual storage level at the beginning of each month and the corresponding level of the guide curves. Therefore, 90 parameters were established: four to define the Z curve, two to establish the percentage assigned to each reservoir, 72 to establish the monthly levels of the guide curves and 12 to define the parameters of the linear functions used to adjust the monthly programed extractions when the actual water level exceeds the limits of the guide curves. For each alternative of the 90 parameters, a detailed simulation is done using the last 20 years of hydrological data on the inflow of water to the three main reservoirs, including the net contributions of five diversion dams, and the objective function sought to maximize water delivery to the treatment plant, while penalizing possible spills and deficits in the system is evaluated. The optimal policies found in this research resulted in smaller spills than those that occurred during the historical operation of the reservoir system. Therefore, the optimal monthly operating decisions required for each reservoir are provided by the genetic algorithm.

The role of tillage systems on the presence of heavy metals in corn grains

The contamination of heavy metal influences in different environmental as it is in soil, water and plant, as has been presented in the region of the Mezquital Valley, state of Hidalgo, where for more than 100 years it has been used the wastewater from the metropolitan area of Mexico City (ZMCM) for agricultural purposes; where the uptake of heavy metals by plants is usually the first step for entry into the food chain as a result of conventional agriculture. The present research work was aimed to evaluate the concentration of lead, cadmium and chromium in corn grain produced in the Mezquital Valley, by the different tillage systems and residue management with the aim of identifying the best system of agricultural production. Using an experimental design of randomized blocks with two replications and a test of means (Tukey, p&gt;0.05), it becomes an invitation to producers in the region to change the traditional system applied by implement a rotation of corn with oats, in zero tillage with stubble on the surface (MA, CL, D); still this treatment is the ideal to ensure minimal concentrations of heavy metals in the grain of corn.

Nitrogen and sulfur compounds in ambient air and in wet atmospheric deposition at Mexico city metropolitan area

Mexico City Metropolitan Area (MCMA), one of the most populous cities in the world, has historically represented a challenge in terms of air pollution. Particulates and sulfur dioxide.(SO2) were identified as the main atmospheric pollutants three decades ago. In order to reduce emissions of these pollutants, replacing of fuel oil by natural gas in power plants was carried out in the late 1980s. This strategy resulted in the reduction of ambient air concentrations of both pollutants. SO2 no longer exceeds its ambient air quality standard; however, acid rain remains a significant issue, with sulfate remaining as the principal component in the wet atmospheric deposition.In this study, spatial and temporal variations in the chemical composition of precipitation (sulfate and nitrate ions, and pH) were obtained weekly at 16 sampling stations, as well as atmospheric SO2 and nitrogen oxides (NOx) from an air quality monitoring network from 2003 to 2018 in the MCMA. Some indicators were applied to evaluate wet atmospheric deposition: SO42−/NO3− and NH4+/NO3− ratios, fractional acidity as well as neutralization factors.SO2 ambient air concentrations have decreased from 2003 to 2018 by more than 70%, while NOx has decreased by 20%. The SO2/NOx ratio has declined about 60%, indicating more effective strategies in reducing SO2 than for NOx emissions. The NOx emission sources are more diverse than for SO2, and NOx has more complex mechanisms of atmospheric deposition and photochemistry.The pH values of the samples at the stations located in the south were more acidic than the samples for the stations in the north. This result is in line with meteorological conditions, where prevailing winds blow from north to south, as well as emission sources located in the north sector, both inside and outside MCMA. For SO42−/NO3− ratio, all sampling sites present current values in the same magnitude order, around 1.4, which is higher compared with urban sites in USA. The 2018 NH4+/NO3− ratio was 1.98 for the southern sampling site, while all northern sampling sites were approximately 2.28. These results are on the same order that urban sites in USA. It was concluded that ammonium was a very important neutralizing agent of pH within the MCMA precipitation.It is recommended to apply strategies for the emissions reduction of acid rain precursors in external sources to the North the MCMA, and to establish a Network for Urban Atmospheric Nitrogen Chemistry.

Heterogeneity in acute PM₂.₅ mortality: big data strategies in the Mexico City Metropolitan Area

Background and aim. Identification of subgroups at greater risk of mortality from PM₂.₅ may inform targeted public health interventions. The case-crossover design is a powerful tool for studying acute PM₂.₅ mortality associations in large registries where statistical interaction indicates differentially susceptible subgroups. We explore shrinkage with resampling to identify these groups in a big data context. Methods. We used a time-stratified case-crossover design to investigate the association between PM₂.₅ with 1.5 million ICD-10 coded non-external 18+ years-old death records from the Mexico City Metropolitan Area, 2004–2019. Daily municipal-level exposures for PM₂.₅ and temperature came from population-weighting 1km satellite-based model predictions, and were scaled to z-scores. We assessed whether the subgroup-specific association of PM₂.₅ exposure (lag₀₁) with daily mortality varied from the overall association for PM₂.₅ by including weighted effect coded interaction terms of lag₀₁ PM₂.₅ by cause-of-death:age-group:sex groupings (56 interaction terms), adjusting for temperature. We fit conditional logistic regression with shrinkage for regularization (ridge regression), and cross-validation to select the value of λ with the minimum mean square error. Finally, bootstrap resampling was used for coefficient confidence intervals (95%CI). Results. Overall, a 10&amp;#x3bc;g/m³ higher lag₀₁ PM₂.₅ was associated with 1.46% higher mortality (95%CI: 1.30-1.77). Subgroups exhibited substantial variation (point estimates from 1.1% to 1.91%) with the strongest associations seen for: circulatory system in females &amp;#x2265;80 years-old (1.91%, 95%CI: 1.51%-2.92%); respiratory system in females &amp;#x2265;80 years-old (1.86%, 95%CI: 1.44%-3.30%); and respiratory system in females 65-79 years-old (1.83%, 95%CI: 1.56%-3.61%). Conclusion. Regularization techniques and inclusion of multi-way interactions in big data analyses aid in systematically identifying specific subpopulations with enhanced response to PM₂.₅ relative to the population-average association. Keywords PM₂.₅, penalized regression, case crossover, mortality, big data

Predicting fine-scale daily NO₂ over Mexico City using an ensemble modeling approach

Background and Aim: In recent years, there has been growing interest in developing air pollution prediction models to reduce exposure measurement error in epidemiologic studies. However, efforts for localized, fine-scale prediction models have been predominantly focused in the United States and Europe, with substantially less work conducted in low- and middle-income countries. Furthermore, the availability of new satellite instruments such as the TROPOspheric Monitoring Instrument (TROPOMI) provides novel opportunities for modeling efforts. Methods: We estimate daily ground-level nitrogen dioxide (NO₂) concentrations in the Mexico City Metropolitan Area at 1-km² grids from 2005 to 2019 using a multi-stage approach. In stage 1, we impute missing satellite NO₂ column measurements from the Ozone Monitoring Instrument (OMI) and TROPOMI using the random forest (RF) approach based on estimates from atmospheric ensemble models. In stage 2, we calibrate the association of column NO₂ to ground-level NO₂ using ground monitors and meteorological features using linear mixed-effects (LME) and RF models. In stage 3, we predict the stage 2 model over each 1-km² grid in our study area, then ensemble the results using a generalized additive model (GAM). In stage 4, we used RF to model the local component at the 200-m² scale by explaining the residual between predicted NO₂ from stage 3 and measured NO₂ at the monitoring stations. Results: The cross-validated R² of the LME and RF models in stage 2 were 0.69 and 0.75 respectively, and 0.83 for the ensembled GAM. Cross-validated root-mean-squared prediction error (RMSPE) of the GAM was 4.41 µg/m³. The RF model in stage 4 further explained on average 54% of the variation in the residual NO₂ concentrations. Conclusions: Using novel approaches and newly available remote sensing data, our multi-stage model presented high cross-validated fits and reconstructs fine-scale NO₂ estimates for further epidemiologic studies in Mexico City.

Ambient air pollution and Carotid Intima-Media Thickness: a cross-sectional analysis from the Mexican Teachers’ Cohort (MTC)

Background/Aim. Is well known that ambient air pollution increases the risk of cardiovascular health outcomes. Carotid Intima-Media Thickness (CIMT) is a marker of subclinical atherosclerosis and a strong predictor of both prevalent and incident cardiovascular morbidity and mortality, including coronary heart disease, myocardial infarction, and stroke. CIMT has been positively associated with air pollutants such as PM2.5 and NO2, nevertheless evidence from low- and middle-income countries is scarce. We evaluated the cross-sectional association between long-term exposure to air pollutants and mean (left and right) CIMT in a population of middle-aged women from the MTC. Methods. We analyzed a randomized selected clinical subsample of the MTC participants living in the Mexico City Metropolitan Area, who were measured the mean CIMT once in 2017, using a standardized protocol (n=265). Self-administered questionnaires collected information on health and sociodemographic characteristics. Ambient PM2.5 and NO2 annual averages were predicted at home and work addresses using high resolution Generalized Additive Models, which were validated using ground measurements. We fitted multiple linear regression models adjusting for potential confounders: age, diabetes, body mass index, cholesterol, triglycerides, smoking and socioeconomic status. Results. Mean CIMT among participants was 618.5 µm (&amp;#xb1;86.5 SD), while mean PM2.5 and NO2 exposure was 22.5 µg/m3 (&amp;#xb1;3.5 SD) and 22.5 ppb (&amp;#xb1;6.6 SD) respectively. After confounder adjustment, each 10-unit increment of PM2.5 and NO2 exposure was positively non-significant associated with a 12.97 µm (95% CI: -16.91, 42.86) and 12.26 µm (95% CI: -1.46, 29.97) higher CIMT, respectively. Sensitivity analyses evaluating CIMT sides shown larger effects on the left CIMT. Conclusions. Although with limited precision, these results suggest that long-term PM2.5 and NO2 exposure is associated with subclinical atherosclerosis in an upper-middle income country women population. Small sample size may have limited the statistical power to detect the effect. Keywords: Air pollution, atherosclerosis, Carotid Intima-Media Thickness

Prediction of daily mean and one-hour maximum PM2.5 concentrations and applications in Central Mexico using satellite-based machine-learning models.

Machine-learning algorithms are becoming popular techniques to predict ambient air PM2.5 concentrations at high spatial resolutions (1 × 1 km) using satellite-based aerosol optical depth (AOD). Most machine-learning models have aimed to predict 24 h-averaged PM2.5 concentrations (mean PM2.5) in high-income regions. Over Mexico, none have been developed to predict subdaily peak levels, such as the maximum daily 1-h concentration (max PM2.5). Our goal was to develop a machine-learning model to predict mean PM2.5 and max PM2.5 concentrations in the Mexico City Metropolitan Area from 2004 through 2019. We present a new modeling approach based on extreme gradient boosting (XGBoost) and inverse-distance weighting that uses AOD, meteorology, and land-use variables. We also investigated applications of our mean PM2.5 predictions that can aid local authorities in air-quality management and public-health surveillance, such as the co-occurrence of high PM2.5 and heat, compliance with local air-quality standards, and the relationship of PM2.5 exposure with social marginalization. Our models for mean and max PM2.5 exhibited good performance, with overall cross-validated mean absolute errors (MAE) of 3.68 and 9.20 μg/m3, respectively, compared to mean absolute deviations from the median (MAD) of 8.55 and 15.64 μg/m3. In 2010, everybody in the study region was exposed to unhealthy levels of PM2.5. Hotter days had greater PM2.5 concentrations. Finally, we found similar exposure to PM2.5 across levels of social marginalization. Machine learning algorithms can be used to predict highly spatiotemporally resolved PM2.5 concentrations even in regions with sparse monitoring. Our PM2.5 predictions can aid local authorities in air-quality management and public-health surveillance, and they can advance epidemiological research in Central Mexico with state-of-the-art exposure assessment methods.

Of cooks, crooks and slum-dwellers: Exploring the lived experience of energy and mobility poverty in Mexico's informal settlements

So-called “slum-dwellers” living in informal settlements in Mexico City Metropolitan Area (MCMA) often confront poor health outcomes, face chronic accommodation insecurity and are frequent victims of social intolerance, discrimination and racism. In addition, they usually reside in living environments with precariously hazardous conditions that often lead to their well-being endangerment. Based on extensive original research with slum-dwellers from the MCMA including focus groups (N = 18 participants), household interviews (N = 51 participants), and site visits (N = 5), this study investigates their energy and housing needs, transport and mobility patterns and challenges to their overall quality of life and health. The MCMA is one of the largest metropolitan regions globally, and most of its inhabitants experience a “double energy vulnerability,” circumstances whereby people are at an intensified risk of energy and transport poverty simultaneously. Our investigation circles around three key themes. In exploring the subject of extreme poverty and vulnerability, we show not only the problems they confront but also illegal practices such as electricity thefts and coping strategies. In investigating the subject of perpetual peripheralization, we show troubling patterns of discrimination, racism and social intolerance. In exploring the subject of spatial justice, we suggest a set of policies that ought to help achieve it.