Search Results (12)

In many conurbations, the pressure on the quality of living increases and affects the most vulnerable human and non-human populations the most. This article describes a proposal for the mapping and design investigation of how a green metropolis can be developed. The approach distinguishes between the landscape producing pain, the ways of healing, and the opportunities to create environments that people can love. This approach reveals concrete and widespread pain in the metropolis, such as impacts on natural landscapes (rivers and mountains), air pollution, ecological degradation, and hydrological disconnections. The strategy to remediate this pain is to uncover hidden and altered creeks and rivers, creating an abundant zone of ecological space around them before human activities and urbanization change the land uses. In addition to this, specific design principles have been developed for hydro-ecological corridors, water retention, green islands, and greenways. Designs for these places can be replicated to support a healing strategy in the Monterrey Metropolitan Area (MMA). Each place creates an environment that the urban residents will appreciate and preserve. The approach to analyzing landscape pain, designing healing strategies, and promoting local places of love can be applied to enhance the quality of life for many urban residents and non-human ecologies in metropolitan areas around the globe. Full article

Contamination from wastewater infiltration, typically from leaky sewers, poses a threat to urban groundwater resources. Artificial sweeteners (Asws), used as sucrose substitutes in many products of daily consumption, are released into groundwater systems and may be used as tracers of wastewater in urban groundwater environments, because most of these compounds are discharged directly into sewer systems. Here, for the first time, we investigated the occurrence of Asws in an urban groundwater system in Mexico. Artificial sweetener concentrations of acesulfame (ACE), aspartame (ASP), cyclamate (CYC), saccharin (SAC), and sucralose (SUC) were tested in 42 production wells in the Monterrey Metropolitan Area (MMA). The detection frequencies of quantified Asws observations were in the order ACE (57%) > SUC (54%) > SAC (7%), with SUC being the most abundant Asws, with concentrations below the quantification limit (BQL) of 2.9 µg/L, followed by ACE (BQL 0.73 µg/L) and SAC (BQL 1.4 µg/L). ASP and CYC were not detected at any sampling site. Considerable Asws ingestion amongst the MMA population is the main input source of Asws into the city’s wastewater network, percolating into the urban groundwater system due to leaky sewers. Our work shows that the application of Asws as wastewater tracers (SUC and ACE) effectively determines wastewater sources affecting urban groundwater. Full article

Air-quality monitoring and analysis are initial parts of a comprehensive strategy to prevent air pollution in cities. In such a context, statistical tools play an important role in determining the time-series trends, locating areas with high pollutant concentrations, and building predictive models. In this work, we analyzed the spatio-temporal behavior of the pollutant PM₁₀ in the Monterrey Metropolitan Area (MMA), Mexico during the period 2010–2018 by applying statistical analysis to the time series of seven environmental stations. First, we used experimental variograms and scientific visualization to determine the general trends and variability in time. Then, fractal exponents (the Hurst rescaled range and Higuchi algorithm) were used to analyze the long-term dependence of the time series and characterize the study area by correlating that dependence with the geographical parameters of each environmental station. The results suggest a linear decrease in PM₁₀ concentration, which showed an annual cyclicity. The autumn-winter period was the most polluted and the spring-summer period was the least. Furthermore, it was found that the highest average concentrations are located in the western and high-altitude zones of the MMA, and that average concentration is related in a quadratic way to the Hurst and Higuchi exponents, which in turn are related to some geographic parameters. Therefore, in addition to the results for the MMA, the present paper shows three practical statistical methods for analyzing the spatio-temporal behavior of air quality. Full article

When conducting an analysis of nature’s time series, such as meteorological ones, an important matter is a long-range dependence to quantify the global behavior of the series and connect it with other physical characteristics of the region of study. In this paper, we applied the Higuchi fractal dimension and the Hurst exponent (rescaled range) to quantify the relative trend underlying the time series of historical data from 17 of the 34 weather stations located in the Río Bravo-San Juan Basin, Mexico; these data were provided by the National Water Commission CONAGUA) in Mexico. In this way, this work aims to perform a comparative study about the level of persistency obtained by using the Higuchi fractal dimension and Hurst exponent for each station of the basin. The comparison is supported by a climate clustering of the stations, according to the Köppen classification. Results showed a better fitting between the climate of each station and its Higuchi fractal dimension obtained than when using the Hurst exponent. In fact, we found that the more the aridity of the zone the more the persistency of rainfall, according to Higuchi’s values. In turn, we found more relation between the Hurst exponent and the accumulated amount of rainfall. These are relations between the climate and the long-term persistency of rainfall in the basin that could help to better understand and complete the climatological models of the study region. Trends between the fractal exponents used and the accumulated annual rainfall were also analyzed. Full article

Variogram models are a valuable tool used to analyze the variability of a time series; such variability usually entails a spherical or exponential behavior, and so, models based on such functions are commonly used to fit and explain a time series. Variograms have a quasi-periodic structure for rainfall cases, and some extra steps are required to analyze their entire behavior. In this work, we detailed a procedure for a complete analysis of rainfall time series, from the construction of the experimental variogram to curve fitting with well-known spherical and exponential models, and finally proposed a novel model: quadratic–exponential. Our model was developed based on the analysis of 6 out of 30 rainfall stations from our case study: the Río Bravo–San Juan basin, and was constructed from the exponential model while introducing a quadratic behavior near to the origin and taking into account the fact that the maximal variability of the process is known. Considering a sample with diverse Hurst exponents, the stations were selected. The results obtained show robustness in our proposed model, reaching a good fit with and without the nugget effect for different Hurst exponents. This contrasts to previous models, which show good outcomes only without the nugget effect. Full article

The use of statistical models and machine-learning techniques along satellite-derived aerosol optical depth (AOD) is a promising method to estimate ground-level particulate matter with an aerodynamic diameter of ≤2.5 μm (PM_2.5), mainly in urban areas with low air quality monitor density. Nevertheless, the relationship between AOD and ground-level PM_2.5 varies spatiotemporally and differences related to spatial domains, temporal schemes, and seasonal variations must be assessed. Here, an ensemble multiple linear regression (EMLR) model and an ensemble neural network (ENN) model were developed to estimate PM_2.5 levels in the Monterrey Metropolitan Area (MMA), the second largest urban center in Mexico. Four AOD-SDSs (Scientific Datasets) from MODIS Collection 6 were tested using three spatial domains and two temporal schemes. The best model performance was obtained using AOD at 0.55 µm from MODIS-Aqua at a spatial resolution of 3 km, along meteorological parameters and daily scheme. EMLR yielded a correlation coefficient (R) of ~0.57 and a root mean square error (RMSE) of ~7.00 μg m⁻³. ENN performed better than EMLR, with an R of ~0.78 and RMSE of ~5.43 μg m⁻³. Satellite-derived AOD in combination with meteorology data allowed for the estimation of PM_2.5 distributions in an urban area with low air quality monitor density. Full article

Aerosol and meteorological remote sensing data could be used to assess the distribution of urban and regional fine particulate matter (PM_2.5), especially in locations where there are few or no ground-based observations, such as Latin America. The objective of this study is to evaluate the ability of Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRA-2) aerosol components to represent PM_2.5 ground concentrations and to develop and validate an ensemble neural network (ENN) model that uses MERRA-2 aerosol and meteorology products to estimate the monthly average of PM_2.5 ground concentrations in the Monterrey Metropolitan Area (MMA), which is the main urban area in Northeastern Mexico (NEM). The project involves the application of the ENN model to a regional domain that includes not only the MMA but also other municipalities in NEM in the period from January 2010 to December 2014. Aerosol optical depth (AOD), temperature, relative humidity, dust PM_2.5, sea salt PM_2.5, black carbon (BC), organic carbon (OC), and sulfate (SO₄²⁻) reanalysis data were identified as factors that significantly influenced PM_2.5 concentrations. The ENN estimated a PM_2.5 monthly mean of 25.62 μg m⁻³ during the entire period. The results of the comparison between the ENN and ground measurements were as follows: correlation coefficient R ~ 0.90; root mean square error = 1.81 μg m⁻³; mean absolute error = 1.31 μg m⁻³. Overall, the PM_2.5 levels were higher in winter and spring. The highest PM_2.5 levels were located in the MMA, which is the major source of air pollution throughout this area. The estimated data indicated that PM_2.5 was not distributed uniformly throughout the region but varied both spatially and temporally. These results led to the conclusion that the magnitude of air pollution varies among seasons and regions, and it is correlated with meteorological factors. The methodology developed in this study could be used to identify new monitoring sites and address information gaps. Full article

To improve air quality in urban centers, vehicle Inspection and Maintenance (I/M) programs were created to identify highly polluting vehicles and force them to undergo mechanical maintenance. In this context, a methodology, based on a single measurement campaign using a Remote Sensing Device (RSD), is presented in this work to assess the reduction in vehicles emissions obtained from implementing I/M programs. As a case study, an RSD campaign was carried out in Mexico, specifically in Monterrey’s Metropolitan Area (MMA). Approximately 0.4% of the vehicles registered in this region were sampled under similar conditions to those found in I/M programs. The results obtained suggested that 39% of the vehicles would not comply with the current national regulations for circulating vehicles. Following a conservative scenario, the implementation of a vehicle I/M program in this urban center has the potential of reducing the current mass emissions of HC, CO and NO in approximately 69%, 42% and 28%, respectively. Full article

This study examines the spatial structure of children with cleft lip and palate (CLP) and its association with polluted areas in the Monterrey Metropolitan Area (MMA). The Nearest Neighbor Index (NNI) and the Spatial Statistical Scan (SaTScan) determined that the CLP cases are agglomerated in spatial clusters distributed in different areas of the city, some of them grouping up to 12 cases of CLP in a radius of 1.2 km. The application of the interpolation by empirical Bayesian kriging (EBK) and the inverse distance weighted (IDW) method showed that 95% of the cases have a spatial interaction with values of particulate matter (PM₁₀) of more than 50 points. The study also shows that 83% of the cases interacted with around 2000 annual tons of greenhouse gases. This study may contribute to other investigations applying techniques for the identification of environmental and genetic factors possibly associated with congenital malformations and for determining the influence of contaminating substances in the incidence of these diseases, particularly CLP. Full article

Here, we present an assessment of long-term trends in the O₃ weekend effect (WE) occurrences and spread within the Mexico City (MCMA), Guadalajara (GMA), and Monterrey (MMA) metropolitan areas, which are the three largest metropolitan areas (MAs) of Mexico and concentrate around 33% of the total population in the country. Daytime averages and peak differences in O₃ concentrations from weekdays to weekends were used as a proxy of WE occurrence. All MAs exhibited the occurrence of WE in all years at least in one monitoring site. Substantial differences in O₃ daytime averages and peaks from weekdays to weekends have decreased over time in all MAs, and since 1998 and 2013 for the MCMA and GMA, respectively, higher O₃ levels during weekends are typical during most of the year. The largest variations in the O₃ WE were observed at downwind and urban core sites of the MCMA and GMA. Significant increasing trends (p < 0.05) in the O₃ WE magnitude were observed for Sundays at all sites within the MCMA, with trends in annual averages ranging between 0.33 and 1.29 ppb O₃ yr⁻¹. Within the GMA, for Sundays, fewer sites exhibited increasing trends in the WE occurrence and at lower growth rates (0.32 and 0.48 ppb yr⁻¹, p < 0.1) than within the MCMA, while within the MMA no apparent trends were observed in marked contrast with the MCMA and GMA. Our findings suggest that policies implemented have been successful in controlling weekday ground-level O₃ within the MCMA and GMA, but further actions must be introduced to control the increases in the O₃ WE magnitude and spread. Full article

Tropospheric levels of O₃ have historically exceeded the official annual Mexican standards within the Monterrey Metropolitan Area (MMA) in NE Mexico. High-frequency and high-precision measurements of tropospheric O₃, NO_y, NO₂, NO, CO, SO₂, PM₁₀ and PM_2.5 were made at the Obispado monitoring site near the downtown MMA from September 2012 to August 2013. The seasonal cycles of O₃ and NO_y are driven by changes in meteorology and to a lesser extent by variations in primary emissions. The NO_y levels were positively correlated with O₃ precursors and inversely correlated with O₃ and wind speed. Recorded data were used to assess the O₃-Volatile Organic Compounds (VOC)-NO_x system’s sensitivity through an observational-based approach. The photochemical indicator O₃/NO_y was derived from measured data during the enhanced O₃ production period (12:00–18:00 Central Daylight Time (CDT), GMT-0500). The O₃/NO_y ratios calculated for this time period showed that the O₃ production within the MMA is VOC sensitive. A box model simulation of production rates of HNO₃ (P_HNO3) and total peroxides (P_perox) carried out for O₃ episodes in fall and spring confirmed the VOC sensitivity within the MMA environment. No significant differences were observed in O₃/NO_y from weekdays to weekends or for P_HNO3/P_perox ratios, confirming the limiting role of VOCs in O₃ production within the MMA. The ratified photochemical regime observed may allow the environmental authorities to revise and verify the current policies for air quality control within the MMA. Full article

Data from the annual, seasonal, and hourly behavior of the criteria air pollutants CO, NO₂, SO₂, O₃, and PM₁₀ in three Mexican metropolitan areas (the Mexico City Metropolitan Area (MCMA), Guadalajara Metropolitan Area (GMA), and Monterrey Metropolitan Area (MMA)) over the period 2000–2011 were analyzed; and compliance with Mexican air quality standards was evaluated, highlighting causes of specific episodes of high and low concentrations. Data analyzed were collected from automatic air-monitoring networks located in the MCMA (32 stations), GMA (8 stations), and MMA (5 stations). In the MCMA and MMA, correlations between wind direction and concentrations of SO₂ suggest that there was a considerable contribution of trans-boundary transport from outside of these areas. Analysis of annual trends revealed large reductions of CO in the MCMA, and SO₂ in the three metropolitan areas. However, the annual mean concentration of O₃ increased by 47% and 42% in the GMA and MMA, respectively, from 2000 to 2011, but decreased by 13% in the MCMA from 2005 to 2010. The annual mean concentration of PM₁₀ in the MMA was about 58% and 76% higher than that in the MCMA and GMA, respectively, from 2001 to 2010. Full article