Mexico City Metropolitan Area Research Articles

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. (SO 2 ) 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. SO 2 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 SO 2 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: SO 4 2− /NO 3 − and NH 4 + /NO 3 − ratios, fractional acidity as well as neutralization factors. SO 2 ambient air concentrations have decreased from 2003 to 2018 by more than 70%, while NO x has decreased by 20%. The SO 2 /NOx ratio has declined about 60%, indicating more effective strategies in reducing SO 2 than for NOx emissions. The NOx emission sources are more diverse than for SO 2 , 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 SO 4 2− /NO 3 − 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 NH 4 + /NO 3 − 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. • Control strategies applied at Mexico City have achieved an important improvement in SO 2 air quality. • SO 4 2− continues to be the largest component anion of wet atmospheric deposition, being now a days the ratio SO 4 2− /NO 3 − around 1.4 at all sampling sites. • Apply strategies to reduce SO 2 emissions in sources located upwind and outside of Mexico City is needed. • NH 4 + stands out as the major ion in the chemical composition of precipitation and in the case of the inorganic nitrogen compounds. • A Network for Urban Atmospheric Nitrogen Chemistry at Mexico City, as well as a critical loads research agenda, are needed.

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 10μg/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 ≥80 years-old (1.91%, 95%CI: 1.51%-2.92%); respiratory system in females ≥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 (±86.5 SD), while mean PM2.5 and NO2 exposure was 22.5 µg/m3 (±3.5 SD) and 22.5 ppb (±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.

Land-cover change and urban growth in the Mexico-Lerma-Cutzamala Hydrological Region, 1993–2018

The Mexico-Lerma-Cutzamala Hydrological Region (MLCHR) encompasses all areas serving water needs of Mexico City Metropolitan Area and is home to 26.8 million people. Historically, this region has experienced extensive environmental and land cover changes due to urbanization, agricultural expansion, deforestation, growing population, floods and droughts. The main objectives of the study are to quantify the land cover changes and to identify spatial/temporal patterns of urban growth during 1993–2018. The results revealed that within the MLCHR over 25 years, urban land cover grew by 82% from its original extent in 1993. Shrubland and cropland contributed the most to the new urban land. The rate of change to urban has been increasing, from 38 km 2 /year in 1993–2004 to 53 km 2 /year in 2004–2018. Additionally, the spatial pattern of urbanization has become more dispersed over time, as new transitions to urban are happening farther away from existing urban land. This study is the first to quantify and locate urbanization within the entire hydrological region that serves the water and sanitation needs of the megalopolis. Its results will support future modeling efforts to understand the impacts of climate change on surface water bodies and aquifers within the MLCHR under different climate-change scenarios and to identify populations most vulnerable to projected water stress. • In the Mexico-Lerma-Cutzamala Hydrological Region urban land grew 82% over 25 years. • Shrubland and cropland are major contributors to urban growth. • Transitions to urban are happening further away from existing urban land. • Results will be used in a dynamic water balance model under climate-change scenarios.

Mutual information analysis between NO2 and O3 pollutants measured in Mexico City before and during 2020 Covid-19 pandemic year

The estimation of statistical dependence between two variables monitored simultaneously, which can come from a complex system, is an important task because allows identify temporal correlations between the components that are involved in the dynamical evolution of the studied system. In many areas of study, like environmental sciences, there are many problems associated with atmospheric pollution, weather, greenhouse effect or climatic change, among others, that remain open today. In general, the variables of complex systems are often linked through nonlinear relations which involve stochastic processes. In order to assessment correlations between random variables, the suitable measure employed to quantify the dependency is the mutual information (MI). In this work we perform a preliminary analysis of temporal dependence between nitrogen dioxide (NO2) and ozone (O3) monitored in the Mexico City Metropolitan Area (MCMA) during the years 2015, 2018 and 2020 being the last the Covid-19 pandemic year. The interest of this study is because NO2 is emitted in large volumes by cars, trucks and industries and O3 is a product from NO2. The aim is to estimate the global correlation between both gases by means the mutual information in three different conditions.

High mortality at the beginning of the COVID-19 pandemic in a referral center in the metropolitan area of Mexico City.

There is limited information about the coronavirus disease 2019 (COVID-19) disease in Latin-American countries. Our objective was to describe the clinical characteristics and outcomes of COVID-19 patients in Mexico. We conducted a retrospective cohort study with 333 consecutive patients who were admitted to Hospital de Especialidades "Dr. Antonio Fraga Mouret" in Mexico City with COVID-19 between April 1, 2020, and June 30, 2020. Demographic, clinical, laboratory data, treatment details and 30-day outcomes were analyzed. The patients studied included 52% men (172/233) and the median age was 45 years. Up to 75% (250/333) of patients were classified as overweight or obese. There were 185 (56%) inpatients; 85% (158/185) were hospitalized in the general ward, and 15% (27/185) in the Intensive Care Unit (ICU). Laboratory measurements showed significant differences between inpatients and outpatients such as lymphocyte-count (median 0.8 vs 1.2×109/L, p < 0.001), LDH (median 650 vs 294 U/L, p < 0.001), CRP (median 147 vs 5 mg/L, p = 0.007), CK-MB (median, 15 vs 10 U/L, p = 0.008), ferritin (median, 860 vs 392 ng/mL, p = 0.02), and D-dimer (median, 780 vs 600 ng/mL, p = 0.15). These differences were seen between survivor and non-survivor patients as well. The rate of death in mechanically ventilated patients was 94% (67/71). Mortality at 30-day follow-up was 57% (105/185). We observed that majority of the non-survivors were obese and young. Complications leading to death was observed in majority of the cases.

The evaluation of liver dysfunction and oxidative stress due to urban environmental pollution in Mexican population related to Madin Dam, State of Mexico: a pilot study.

One of the most important causes of disease and premature death in the world is environmental pollution. The presence of pollutants in both water and air contributes to the deterioration of the health of human populations. The Mexico City Metropolitan Area is one of the most populous and affected by air pollution worldwide; in addition, in recent years there has been a growing demand for water, so urban reservoirs such as the Madin dam are vital to meet the demand. However, this reservoir is highly polluted due to the urban settlements around it. Therefore, the aim of the present study was to evaluate oxidative stress in clinically healthy subjects by means of the degree of lipoperoxidation, as well as the modification of serum enzyme levels, such as alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase and lactate dehydrogenase associated with air and drinking water pollutants from three zones of the Mexico City Metropolitan Area, two of them related to Madin Dam. This descriptive cross-sectional study was conducted between March 2019 and September 2021 in 142 healthy participants (age range 18–65 years). Healthy subjects were confirmed by their medical history. The results showed that chronic exposure to air (SO2) and water pollutants (Al and Fe) was significantly associated with elevated levels of lipoperoxidation. There was evidence that contamination from the Madín dam can generate oxidative stress and affect the health status of people who receive water from this reservoir or who consume fish that inhabit it.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11356-022-22724-3.

Land Subsidence and Aquifer‐System Storage Loss in Central Mexico: A Quasi‐Continental Investigation With Sentinel‐1 InSAR

AbstractAquifers play an important role in addressing water needs worldwide. When overexploited, they may lose storage and compact, causing land subsidence and impacts on urban landscapes. Using Sentinel‐1 satellite imagery, we perform the largest ever‐made Interferometric Synthetic Aperture Radar (InSAR) survey over Mexico, across a 700,000 km2 area hosting &gt;85.2 million inhabitants. We estimate present‐day subsidence rates for yet unmapped and well‐known hotspots (e.g., −45 cm/year in Mexico City), and compute compaction volumes at &gt;300 aquifer‐systems (up to −60 hm3/year at Mexico City Metropolitan Area). InSAR‐derived aquifer‐system compaction generally correlates well with groundwater deficits, extractions and storage changes from management reports. Semi‐theoretical relationships for the whole Central Mexico and hydrological‐administrative regions VII, VIII, and XIII, enable the assessment of compaction rates and volumes resulting from groundwater exploitation. These could be used to inform groundwater management strategies towards adaptation to climate change and future needs of a growing population.

Human exposure to microplastics from urban decentralized pay-to-fetch drinking-water refill kiosks

Microplastics in the human diet have become a worldwide concern. To date, microplastics in urban drinking water supplies, such as decentralized drinking-water refill kiosks, have not been studied and are a pressing concern since they are so closely tied to human life and have a significant influence on health. This study evaluated the occurrence and characteristics of microplastics in 63 drinking water samples collected from decentralized refill kiosks in the Mexico City metropolitan area. All of the sampled drinking water contained microplastics in concentrations ranging from 11 to 860 microplastics L-1. The detected microplastics were mostly fiber (65 %), followed by fragment (28 %), and film (7 %). They were mainly composed of polyethylene terephthalate, polyamides, vinyl polymers, polyacetal, and cellophane in sizes ranging from 20 μm to 5 mm, with 75 % of them accounting for sizes <300 μm. SEM-EDX analysis revealed weathered microplastics, biota adherence, and the presence of inorganic elements on the surface of microplastics. We estimate that Mexico City residents inadvertently ingest 42 microplastics L-1, with an annual exposure of around 1.47 × 104 microplastics per adult and 6.73 × 103 microplastics per child. Therefore, future research is needed to strengthen drinking water refill kiosk guidelines and standards for better microplastic management. This study serves as a wake-up call to many developing countries that use similar urban water systems, drawing their attention to global microplastic contamination of drinking water.

Occurrence and characteristics of atmospheric microplastics in Mexico City

While atmospheric microplastics have attracted scientific attention as a significant source of microplastic contamination in the environment, studies in large population centers remain sparse. Here we present the first report on the occurrence and distribution of atmospheric microplastics in Mexico City (Latin America's second most densely populated city), collected using PM10 and PM2.5 active samplers at seven monitoring stations (urban, residential, and industrial) during the dry and wet seasons of 2020. The results showed that microplastics were detected in all of the samples examined, with mean microplastic concentrations (items m-3) of 0.205 ± 0.061 and 0.110 ± 0.055 in PM10 and PM2.5, respectively. The spatial distribution of microplastics showed seasonal variation, with greater abundances in locations closer to industrial and urban centers. There was also a significant difference in microplastic concentrations in PM10 and PM2.5 between the dry and wet seasons. The mean PM2.5/PM10 ratio was 0.576, implying that microplastics were partitioned more towards PM2.5 than PM10 in Mexico City. Fibers were the most prominent shape (>75 %), and blue was the most common color (>60 %). The size characteristics indicated microplastics of varying lengths, ranging from 39 to 5000 μm, with 66 % being <500 μm. Metal contaminants such as aluminum, iron, and titanium were detected using SEM-EDX on randomly selected microplastics. The microplastics were identified as cellophane, polyethylene, polyethylene terephthalate, polyamide, and cellulose (rayon) using ATR-FTIR spectral analysis. Our findings unravel the extent and characteristics of atmospheric microplastics in the Mexico City metropolitan area, which will aid future research to better understand their fate, transport, and potential health risks, demanding more investigations and close monitoring.

Daily Precipitation Data for the Mexico City Metropolitan Area from 1930 to 2015

The Metropolitan Zone of Mexico City, as well as the associated basin, includes the territories of Mexico City, some municipalities of the State of Mexico and the state of Hidalgo. In addition, this area is the most densely populated in Mexico. The region is influenced by mid-latitude and tropical weather systems and is vulnerable to extreme hydrometeorological events. In this context, we developed a dataset from the records of 136 geolocated sites that includes daily precipitation data from the CLImate COMputing (CLICOM) project and the Mexico City Water System. The data spans the period from 1930 to 2015 for the rainy months (June–October) from stations with records of 20 or more years. In each recording site, automatic and manual data quality control were performed to verify the consistency of the daily precipitation data. We believe that our highly dense precipitation dataset will be useful for climate, trend and extreme events analysis. Additionally, the data will allow validating simulations of numerical atmospheric models. The dataset is public, and it was previously used in other research to determine areas susceptible to flooding due to heavy rain events and to develop a web mapping application of daily precipitation data.

Phylodynamics of HIV in the Mexico City Metropolitan Region.

Evolutionary analyses of viral sequences can provide insights into transmission dynamics, which in turn can optimize prevention interventions. Here, we characterized the dynamics of HIV transmission within the Mexico City metropolitan area. HIV pol sequences from persons recently diagnosed at the largest HIV clinic in Mexico City (between 2016 and 2021) were annotated with demographic/geographic metadata. A multistep phylogenetic approach was applied to identify putative transmission clades. A data set of publicly available sequences was used to assess international introductions. Clades were analyzed with a discrete phylogeographic model to evaluate the timing and intensity of HIV introductions and transmission dynamics among municipalities in the region. A total of 6,802 sequences across 96 municipalities (5,192 from Mexico City and 1,610 from the neighboring State of Mexico) were included (93.6% cisgender men, 5.0% cisgender women, and 1.3% transgender women); 3,971 of these sequences formed 1,206 clusters, involving 78 municipalities, including 89 clusters of ≥10 sequences. Discrete phylogeographic analysis revealed (i) 1,032 viral introductions into the region, over one-half of which were from the United States, and (ii) 354 migration events between municipalities with high support (adjusted Bayes factor of ≥3). The most frequent viral migrations occurred between northern municipalities within Mexico City, i.e., Cuauhtémoc to Iztapalapa (5.2% of events), Iztapalapa to Gustavo A. Madero (5.4%), and Gustavo A. Madero to Cuauhtémoc (6.5%). Our analysis illustrates the complexity of HIV transmission within the Mexico City metropolitan area but also identifies a spatially active transmission area involving a few municipalities in the north of the city, where targeted interventions could have a more pronounced effect on the entire regional epidemic. IMPORTANCE Phylogeographic investigation of the Mexico City HIV epidemic illustrates the complexity of HIV transmission in the region. An active transmission area involving a few municipalities in the north of the city, with transmission links throughout the region, is identified and could be a location where targeted interventions could have a more pronounced effect on the entire regional epidemic, compared with those dispersed in other manners.

A Novel Tree Ensemble Model to Approximate the Generalized Extreme Value Distribution Parameters of the PM2.5 Maxima in the Mexico City Metropolitan Area

We introduce a novel spatial model based on the distribution of generalized extreme values (GEVs) and tree ensemble models to analyze the maximum concentrations levels of particulate matter with a diameter of less than 2.5 microns (PM2.5) in the Mexico City metropolitan area during the period 2003–2021. Spatial trends were modeled through a decision tree in the context of a non-stationary GEV model. We used a tree ensemble model as a predictor of GEV parameters to approximate nonlinear trends. The decision tree was built by using a greedy stagewise approach, the objective function of which was the log-likelihood. We verified the validity of our model by means of the likelihood and Akaike’s information criterion (AIC). The maps of the generalized extreme value parameters on the spatial plane show the existence of differentiated local trends in the extreme values of PM2.5 in the study area. The results indicated strong evidence of an increase in the west–east direction of the study area. A spatial map of risk with maximum concentration levels of PM2.5 in a period of 25 years was built.

A Unified Hydrogeological Conceptual Model of the Mexico Basin Aquifer after a Century of Groundwater Exploitation

The Mexico City Metropolitan Area, located within the Mexico Basin, is the most important economic center in Mexico. An ever-growing population, currently at 22 million with increasing water demands, has resulted in the overexploitation of groundwater with associated impacts to hydrological conditions for a century. Land subsidence due to chronic groundwater level declines has damaged infrastructure and increased water delivery and flood control challenges, causing loss of aquifer storage. An additional associated problem is groundwater quality deterioration, which reduces potable supplies due to increasing anthropogenic pollution and salinization. A new integrated conceptual model of the Mexico Basin Aquifer has been constructed based on a comprehensive compilation of existing and new hydrogeological knowledge. As a result, this conceptual model updates and improves the understanding of the characteristics of the aquifer and current hydrodynamic behavior of groundwater. Four hydrogeological units were identified, their heads and related flow system interdependencies were evaluated and their hydraulic properties associated; this allowed identifying local, intermediate and regional flow systems, aquifer transition from confined to unconfined conditions, changes to land subsidence and groundwater quality deterioration. This conceptual model could be the basis in building a numerical model, and as a powerful tool to test different management scenarios for decision-making.

Mapping of the cost of atmospheric corrosion of zinc and galvanised steel due to the effect of atmospheric pollution in the Mexico City Metropolitan area

ABSTRACT The deterioration of materials due to the effect of atmospheric pollution generates a cost to society because the maintenance and replacement of degraded materials. Galvanised steel is used in electrical industry to build electrical transmission towers (ETT). The objective of the study was to estimate the annual maintenance cost of galvanised steel used in the construction of ETT. The maintenance cost for galvanised steel was estimated considering the cost of the material surface area and the difference between the maintenance interval of clean and contaminated areas. Maps of intervals and maintenance costs were obtained for galvanised steel (85 and 100 µm), which are the thicknesses regulated in Mexico for ETT. In addition, an ArcGis geographic information system was used for a spatial representation of data from the anthropogenic environment. The mapping of areas at risk of corrosion shows that in the northwest zone, ETT presents the highest maintenance costs for the year 2019. For galvanised steel thicknesses of 85 and 100 µm, there are annual costs of, respectively, 8.68 and 10.16 USD/m2.

Effects of Urbanization on Extreme Climate Indices in the Valley of Mexico Basin

This study analyzes 50 annual climate change indices related to temperature and precipitation in the Valley of Mexico basin for the period 1951–2010. First, a quality and homogenization analysis of 90 weather stations (categorized as urban, suburban, and rural) in the basin was performed using the Climatol algorithm. The non-parametric Mann–Kendall test and the Sen’s slope method were applied to determine the existence of a trend and to estimate the magnitude of the change in extreme climate indices, respectively. To eliminate the serial correlation problem, the lag-1 method and the Patakamuri tests were used. Statistically significant positive trends were found for SU, TMm, TNm, TNn, TX90p, and WSDI, as well as negative ones for FD, TX10p, TN10p, CSDI, and HDDheat18. The results seem to support an influence of anthropogenic global warming on the study region, rather than local effects of urbanization. However, it is likely that some significant differences in the urban change rate of some indices could be due to local effects, such as the difference in land cover that occurs between urban and rural stations. Not enough statistically significant results were found for the climate change indices related to precipitation in most of the stations. Compared to other studies in the Mexico City area, the main contribution of this study is the analysis of 50 climate indices in a 60-year period working with a quality-controlled and homogenized database.

Water Stress, Peri-Urbanization, and Community-Based Water Systems: A Reflective Commentary on the Metropolitan Area of Mexico City

With a population of over 22 million, Mexico City's metropolitan area is facing enormous water security challenges. Its supply heavily relies on overdraft of groundwater and import from neighboring basins, leading to problems such as subsidence and raising concern over its sustainability. The impacts of the water stress in Mexico City are highly unequal across the metropolitan area and particularly severe in low-income peri-urban neighborhoods. This paper will first review the current water stress in Mexico City, its impacts on vulnerable communities, as well as some existing technical and institutional approaches aiming to tackle these challenges. We will then focus on the community-based water management systems in Mexico City's peri-urban areas, based on the case of Tecámac, one of the 59 municipalities that form the conurbation area. We will discuss the local water politics in the municipality, the historical evolution of the community-based water system, SAPTEMAC, as well as its current agenda. This essay highlights the importance of incorporating the community-based water systems in the development toward a solution to the water crisis in megacities like Mexico City: not only do they serve as provider of potable water to a considerable number of households, but they also represent a collective resistance against the speculation-driven (peri) urbanization and can make substantial contribution to the promotion of a comprehensive water reform in the country.