Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Particles of matter smaller than 10 μm (PM10) are significant pollutants due to their impact on health and the environment. This study analyzed daily PM10 data from the Obispado station (Monterrey, Nuevo León, Mexico) provided by the INECC, covering the period from 1997 to 2014. Climatological variables such as precipitation, wind speed (at 2 and 10 m), and atmospheric pressure, obtained from NASA’s POWER project, were included. Data were partitioned into training and testing sets using an 80-20% split, employing 3798 daily observations for training (2002 to 2012) and 950 observations for testing (2012 to 2014). Descriptive analysis and time series decomposition were performed to identify trends and seasonality. ARIMA models, univariate and with transfer functions incorporating meteorological variables, were applied. Augmented Dickey-Fuller and Ljung-Box tests validated the stationarity and residual independence assumptions. The ARIMA (1,1,1)(0,0,0)[365] model with transfer functions outperformed the univariate model. A significant relationship between meteorological variables and PM10 predictions was identified, supporting their use for short-term forecasting (≤ 10 days). Future studies should consider applying multivariate models with additional predictors and geostatistical approaches to improve spatiotemporal characterization.

This article presents a detailed analysis of air pollutant dynamics in Puebla City, Mexico, using data collected between 2016 and 2024. The research examines the daily variation of five main pollutants: ozone (O3), particulate matter smaller than 10 microns (PM10), particulate matter smaller than 2.5 microns (PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2). To identify significant trends and seasonal patterns, the Mann-Kendall test, innovative trend analysis (ITA), and wavelet transform were applied. The results indicate statistically significant upward trends in O3, SO2, and NO2 concentrations, while PM10 and PM2.5 levels have exhibited a sustained decrease throughout the study period. The scalogram analysis highlights seasonal energy concentrations of SO2, potentially linked to industrial activity and meteorological conditions. Additionally, the Prophet forecasting model was used to estimate PM2.5 and PM10 levels from 2022 to 2024, achieving better performance over longer time horizons. This study is particularly relevant given the urban growth and industrial activity in Puebla, factors that can contribute to the deterioration of air quality and affect the health of the population. The identification of trends and patterns in air pollution is essential for the implementation of mitigation strategies and public policies aimed at improving air quality in the region.

A specific model for low-visibility forecasting in the Brazilian Northeast (BNE) has not been developed; therefore, the German Parameterized Fog (PAFOG) model was adapted for the region. Additionally, Fog Visibility (FogVIS), a simple equation-based tool, was developed and requires further testing. From 2008 to 2020, Meteorological Aerodrome Report and Terminal Aerodrome Forecast surface data were collected via the Meteorology Network of the Brazilian Air Force Application Programming Interface, identifying 218 fog events across three airports: Maceió (32 events), Recife (1 event), and Campina Grande (185 events). GOES satellite images were accessed from the Center for Weather Forecasting and Climate Studies database, and synoptic and thermodynamic analyses were performed using ERA5 reanalysis data. Humidity from nearby water sources (lagoon for Maceió, dam for Campina Grande) was a primary factor in fog formation. PAFOG demonstrated strong predictive performance for Maceió and Recife’s single brief events, especially in 12-h forecasts, particularly when fog events were preceded or followed by mist or light rain. In contrast, FogVIS often aligned closely with the observed visibility range and provided complementary results 18 hours in advance for Campina Grande’s events, which were more intense but less associated with rain or mist, and also showed higher Fog Stability Index results. Both models demonstrated efficiency, with PAFOG excelling in Maceió and FogVIS in Campina Grande, highlighting the applicability and accuracy of both models in predicting fog for the BNE.

This study aims to systematically evaluate the evolution of scientific research on the impacts of climate change on winter meteorological events and atmospheric pollution through a bibliometric analysis. Utilizing data from the Scopus database and the Bibliometrix package in R, the analysis investigates publication trends, international collaboration, and thematic developments from 1980 to 2024. The objectives are to identify key research areas, influential contributors, and emerging patterns within this interdisciplinary field. Results indicate a strong and sustained growth in scholarly output, with an annual increase of 12.48% and an average of 43.28 citations per publication, reflecting the rising global interest and relevance of this topic. Collaboration networks reveal robust partnerships among researchers from the United States, China, and Europe, though regional disparities persist—particularly in Eastern Europe. Thematic clustering and multiple correspondence analysis (MCA) identify three dominant research areas: statistically driven climate studies, investigations of seasonal weather dynamics, and analyses of extreme winter events. The findings highlight the field’s intellectual structure and underscore the need for expanded international cooperation and increased research efforts in underrepresented regions. This analysis provides valuable insights for future research and policymaking in the field of climate and atmospheric sciences.

The present study examined the monthly summer and autumn temperature (ºC) variability in Iraq and its relation to the global sea surface temperatures (SST). The dataset, collated from eight meteorological stations and spanning the period from 1971 to 2010, was provided by the Iraq Meteorological Organization and the Seismology Department. The SST modes were obtained from the Hadley Centre (HadiSST2). The statistical analysis used Empirical Orthogonal Functions (EOFs) and Principal Components (PCs) to identify the characteristics of Iraq’s spatial and temporal variability. EOFs’ results for summer and autumn identify that EOF1 is monopolar, with variances of 77.26 and 69.23%, respectively, which refer to the links between the climatological parameters and the large-scale. Meanwhile, the second EOF is bipolar, with variances of 8.04 and 10.10%, respectively, due to the local connection. The derived results from the correlation maps demonstrate a relationship between Iraq’s summer and autumn temperatures and large-scale SST patterns. The occurrence of La Niña in the Pacific Ocean, accompanied by a positive Atlantic Multidecadal Oscillation (AMO), is expected to lead to a rise in temperatures in the region. The Pearson correlation coefficients between ENSO and summer and autumn PC1 and PC2 are 0.11, 0.59, and 0.14, –0.27, respectively. The correlation coefficients of the AMO index with summer and autumn (PC1, PC2) are 0.31, –0.2, and 0.03, 0.19, respectively. The results confirm the slight impact of the two modes on Iraq’s climate variability.

The meteorological optical range (MOR) is an objective parameter for assessing atmospheric visibility. Data collected using optical disdrometers (PWS100) were used to analyze MOR estimates when extreme rainfalls occurred at two locations in Mexico: Chamela, on the Pacific coast, and Juriquilla, a continental sampling site. The performance of the disdrometer for rainfall estimation was found to be consistent and satisfactory when compared to rain gauges. Analyses based on rainfall rate (R) outcomes from tipping bucket rain gauge data showed that MOR measurements registered the most significant decreases during periods of highest R. The assessed coefficients for the extinction coefficient (σ) and R power-adjusted relationships are comparable to those obtained in previous studies, and the statistical performance of the fitted equations in modeling σ values is excellent. The equation coefficients for these mathematical expressions indicate that precipitation at the sampling sites is initiated from mixed (Bergeron-type) clouds, and it can be inferred that mixed-phase thunderstorms were predominant at the sampling sites during the chosen periods. Our findings indicate that MOR and σ are closely related to the large raindrop proliferation and the broadening of the raindrop size distribution (inferred from the increase of the median volume diameter). Despite the underestimation of small raindrops by the optical disdrometer, this study demonstrates the reliability of MOR estimates obtained with the PWS100 during rainfall events.

Racism is a structural problem that affects people’s daily lives, limit their access to fundamental rights, perpetuates historical inequalities, while discriminating against indigenous and Afro-descendants. To counteract these dynamics, anti-racist design is proposed as a political stance that recognizes the non-neutrality of design disciplines, encourages a more inclusive and conscious practice, capable of dealing with the complexity of social inequalities and promoting meaningful change in society.

This article establishes a dialogue based on diverse socio-spatial expressions and experiences of women, emphasizing the inequalities they face. The methodology focuses on exploring the dynamics related to mobility, employment, and caregiving from a critical perspective and through a gender perspective.

This essay delves into the urban renewal initiatives undertaken by the Mexico City government from 1930 to 1940. It uncovers how narratives of hygiene and mobility were employed to mask social cleansing efforts. The analysis highlights post-revolutionary Mexico City as a case study, illustrating how urban planning can be wielded as a political tool to reshape daily life and legitimize structural violence.

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