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In this comprehensive analysis of Chile's air quality dynamics spanning 2016 to 2021, the utilization of data from the National Air Quality Information System (SINCA) and its network of monitoring stations was undertaken. Quintero, Puchuncaví, and Coyhaique were the focal points of this study, with the primary objective being the construction of predictive models for sulfur dioxide (SO2), fine particulate matter (PM2.5), and coarse particulate matter (PM10). A hybrid forecasting strategy was employed, integrating Autoregressive Integrated Moving Average (ARIMA) models with Artificial Neural Networks (ANN), incorporating external covariates such as wind speed and direction to enhance prediction accuracy. Vital monitoring stations, including Quintero, Ventanas, Coyhaique I, and Coyhaique II, played a pivotal role in data collection and model development. Emphasis on industrial and residential zones highlighted the significance of discerning pollutant origins and the influence of wind direction on concentration measurements. Geographical and climatic factors, notably in Coyhaique, revealed a seasonal stagnation effect due to topography and low winter temperatures, contributing to heightened pollution levels. Model performance underwent meticulous evaluation, utilizing metrics such as the Akaike Information Criterion (AIC), Ljung-Box statistical tests, and diverse statistical indicators. The hybrid ARIMA-ANN models demonstrated strong predictive capabilities, boasting an R2 exceeding 0.90. The outcomes underscored the imperative for tailored strategies in air quality management, recognizing the intricate interplay of environmental factors. Additionally, the adaptability and precision of neural network models were highlighted, showcasing the potential of advanced technologies in refining air quality forecasts. The findings reveal that geographical and climatic factors, especially in Coyhaique, contribute to elevated pollution levels due to seasonal stagnation and low winter temperatures. These results underscore the need for tailored air quality management strategies and highlight the potential of advanced modeling techniques to improve future air quality forecasts and deepen the understanding of environmental challenges in Chile.

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The PM2.5/PM10 ratio is a metric used to distinguish the primary sources of particulate matter (PM) within a given environment. Higher ratios often indicate significant contributions from anthropogenic sources, while smaller ratios suggest a substantial influence from natural origins. However, various contextual factors can influence this ratio. Our study aimed to investigate the PM2.5/PM10 ratio in four distinct Brazilian cities, each characterized by varying levels of urbanization and primary economic activities. Additionally, we explored meteorological variables that may influence PM behavior across the years and different seasons. Our main finding reveals an association between the spatial distribution of PM and the primary economic activities in the investigated cities, with the highest PM2.5/PM10 ratio observed in the city engaged in coal activities, even though it did not exhibit the highest levels of PM. Conversely, coastal cities showed the lowest ratios. Furthermore, we observed that meteorological conditions also play a significant role in influencing PM behavior, with wind speed and the UV index emerging as the most influential meteorological parameters affecting this ratio. A subtle increase in PM2.5/PM10 ratios was noted in the fourth and fifth years of investigation across all cities, suggesting a potential impact from the restriction measures and the subsequent resumption of activities related to the COVID-19 pandemic in the region. However, these ratios stabilized in the post-pandemic years, returning to patterns similar to those observed pre-pandemic. Moreover, winter consistently exhibited the highest PM2.5/PM10 ratio across all cities, also being the season with the highest levels of both PM10 and PM2.5. Beyond providing important information about PM behavior in the evaluated scenarios, our findings emphasize the necessity of considering meteorological and economic factors in studies of this nature.

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OBJECTIVE: To evaluate the performance of satellite-derived PM2.5 concentrations against ground-based measurements in the municipality of Salvador (state of Bahia, Brazil) and the implications of these estimations for the associations of PM2.5 with daily non-accidental mortality. METHODS: This is a daily time series study covering the period from 2011 to 2016. A correction factor to improve the alignment between the two data sources was proposed. Effects of PM2.5 were estimated in Poisson generalized additive models, combined with a distributed lag approach. RESULTS: According to the results, satellite data underestimated the PM2.5 levels compared to ground measurements. However, the application of a correction factor improved the alignment between satellite and ground-based data. We found no significant differences between the estimated relative risks based on the corrected satellite data and those based on ground measurements. CONCLUSION: In this study we highlight the importance of validating satellite-modeled PM2.5 data to assess and understand health impacts. The development of models using remote sensing to estimate PM2.5 allows the quantification of health risks arising from the exposure.

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Significant environmental challenges, such as urban and industrial expansion, alongside vegetation preservation, directly influence the concentrations of critical air pollutants and greenhouse gases in cities and their surroundings. The urban development and expansion process is aptly captured by classifying land use and land cover (LULC). We aimed to analyze LULC changes in an Andean area, Ecuador, and to reveal the relations of LULC classes with three air pollutants ozone ( O 3 ), nitrogen dioxide ( N O 2 ), and sulfur dioxide ( S O 2 ), using remote sensing datasets (Sentinel-5P - Sentinel 1 - Sentinel-2) across different periods. Results showed that S O 2 is not a reliable indicator for assessing its behavior based on LULC classes, as it was difficult to distinguish between different land cover types using this pollutant. For N O 2 , the analysis showed a moderate distinction among LULC classes, suggesting some variability in its distribution across different land cover classes. On the other hand, O 3 analysis shows that all land cover classes are statistically distinguishable, demonstrating that urban, shrubland, green areas, and forest classes influenced ozone distribution. These findings emphasize the importance of accurate land cover classification in understanding air pollutants' spatial distribution and dynamics. This analysis is crucial for understanding the impacts of land use and land cover changes on urban health and well-being and the effects of rapid urban expansion.

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INTRODUCTION: Prenatal and early-life exposure to air pollution and extreme temperatures are associated with childhood asthma and wheeze. However, potential windows of susceptibility and their sex-specific and interactive effects have not been fully elucidated. We aimed to identify critical windows of susceptibility and evaluate sex-specific effects in these associations, and evaluate exposure interactions. METHODS: We analyzed data from 468 mother-child pairs enrolled in the PROGRESS birth cohort in Mexico City. Daily residential levels of PM2.5, NO2, and temperature were generated from our validated spatiotemporally resolved models from conception to age 4 years. Childhood asthma and wheeze outcomes were collected at 4-6 and 7-8 years. Distributed lag nonlinear models (DLNMs) were used to identify susceptible windows for prenatal weekly-specific and postnatal monthly-specific associations of air pollution and temperature with respiratory outcomes adjusting for covariates. To evaluate sex-specific effects, DLNMs were stratified. Joint effects were assessed using relative excess risk due to interaction and attributable proportion. RESULTS: Mid-gestation was a critical window for both PM2.5 (weeks 20-28, cumulative OR: 1.18 [95% CI: 1.01, 1.37]; weeks 19-26, cumulative OR: 1.18 [95% CI: 1.02, 1.36]) and NO2 (weeks 18-25, cumulative OR: 1.16 [95% CI: 1.02, 1.31]) exposure, associated with higher odds of wheeze. Postnatal exposure to PM2.5 and NO2 during the first year of life was also linked to higher odds of wheeze. The warmer and colder temperatures showed mixed effects on respiratory outcomes. We observed a synergistic interaction between high PM2.5 and high temperature exposure during the first year of life, associated with higher odds of current wheeze. The associations of prenatal air pollution and temperature exposure with respiratory outcomes were more pronounced in males. CONCLUSIONS: Early-life air pollution exposure contributes to the development of childhood asthma and wheeze, while exposure to temperature showed mixed associations with respiratory outcomes.

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Many cities have promoted decarbonized transportation modes to mitigate climate change, reduce air pollution and promote healthy behaviors. However, cyclists may be particularly exposed to higher concentrations of on-road air pollutants than other commuters due to their proximity to traffic, higher breathing rates, and prolonged commutes. In addition, there is scarce information analyzing the geographic exposure levels of cyclists in medium-sized urban agglomerations of Latin American cities. We aimed to assess cyclists' exposure to PM2.5 at the spatio-temporal level using low-cost sensors in the Mendoza Metropolitan Area, Argentina. We calculated PM2.5 inhalation doses (IDs) for different routes with distinctive characteristics, considering different age ranges and gender of cyclists. The dose was represented as temporally and spatially disaggregated exposure maps, one of the first to represent it in Latin America using this method. All link types analyzed exhibited significant differences in PM2.5 concentrations, although the most frequent concentrations were less than 5 µg m-3, with secondary peaks of 6.5 and 9 µg m-3. As expected, ID increases with age and is greater in males than in females. Our findings further reinforce the fact that route choice (busy vs. quiet) and time of day (peak vs. off-peak) appreciably affect the pollutant exposure of cyclists. All these results could be helpful in the selection of alternative cycling routes with lower PM2.5 at different hours of day but also enable us to investigate further implications of exposure to PM2.5 for the health of urban bicycle commuters.

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Scientific literature on the health effects of air pollution is diverse, and broadly acknowledges the importance of human experience and social and economic precarity as modifying factors. Still, the inclusion of the embodied experience of air pollution has been limited. Also, the health effects of pollution are often studied at the group or population level, without adequately considering individual difference. This paper uses a Bio3Science framework, which integrates biology, biography, and biosphere, to explore how air pollution affects residents in Medellín, Colombia. By using qualitative research on individual experiences of air pollution (biography) to probe the intersection of individual health (biology) and environment (biosphere), we illustrate how pollution shapes lived rhythms at multiple scales. Our findings emphasize that air pollution's health impacts extend beyond measurable pollutants to include the complex synergies of smoke, noise, stress, and disruptions to daily life. This comprehensive approach provides a nuanced understanding of how air pollution materially shapes the lives of individuals and communities, advocating for research models that capture the subtle, everyday experiences often overlooked by traditional group or population-level analyses.

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Ambient air pollution is a significant environmental risk factor for adverse pregnancy outcomes, including preterm birth. However, the impact of different pollutants across various regions and trimesters of pregnancy has not been fully investigated in Brazil. This study aimed to examine the associations between exposure to PM2.5, NO2, and O3 during different trimesters of pregnancy and the risk of preterm birth across five regions of Brazil. We used logistic regression models to estimate the odds ratios (OR) of preterm birth associated with PM2.5, NO2, and O3 adjusting for potential confounders such as maternal age, education, and socioeconomic status. Our study included over 9.9 million live births from 2001 to 2018, with data obtained from the Ministry of Health in Brazil. On average, for each 1-µg/m3 increase in PM2.5, we estimated a 0.26 % (95 % CI: 0.08-0.44 %) increase in the risk of preterm birth nationally in the first trimester. For NO2, each 1ppb increase was associated with a percentage increase in preterm birth risk of 7.26 % (95 % CI: 4.77-9.74 %) in the first trimester, 8.05 % (95 % CI: 5.73-10.38 %) in the second trimester, and 7.48 % (95 % CI: 5.25-9.72 %) in the third trimester. For O3, each 1ppb increase was associated with a percentage increase in preterm birth risk of 1.24 % (95 % CI: 0.29-2.18 %) in the first trimester, 1.51 % (95 % CI: 0.60-2.41 %) in the second trimester, and 0.72 % (95 % CI: -0.18-1.62 %) in the third trimester. This study highlights the significant impact of ambient air pollution on preterm birth risk in Brazil, with significant regional variations. Our findings underscore the need for targeted public health interventions to mitigate the effects of air pollution on pregnancy outcomes, particularly in the most affected regions.

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The high concentrations of air pollutants in Peru remain a persistent problem, significantly impacting public health. Understanding the extent to which the COVID-19 lockdown affected these contaminants is crucial. To determine variations in NO2, O3, CO, and SO2 concentrations in 10 Peruvian cities before, during, and after lockdown. A comparative ecological study was conducted in urban areas of 10 major Peruvian cities using the Google Earth Engine (GEE) platform. Data on atmospheric pollutant concentrations were extracted from the Sentinel-5P/TROPOMI satellite images for the period between March 16 and June 30, across the years 2019, 2020, 2021, and 2022, for comparative analysis. The Wilcoxon test was used to evaluate changes between the study periods. We included 10 urban cities located across three geographic regions of Peru. Most urban cities experienced a decrease in NO2 concentrations and an increase in O3 and CO levels during the lockdown, while SO2 concentrations remained relatively constant. The lockdown has caused variations in NO2, O3 and CO concentrations. Future studies with accurate data on air pollutant concentrations are needed to ensure targeted and effective interventions.

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Cement factories significantly contribute to atmospheric pollution by generating fine particulate matter (PM2.5), which can potentially increase the mortality risk. The lack of information on the health impacts of PM2.5 pollution from cement operations in Brazil prompted this investigation. We used corrected PM2.5 measurements from low-cost sensors from March 2021 to October 2022 in Rio Branco do Sul, city in the southern region of the country and home to Latin America's largest cement plant, to assess exposure data. Disability-adjusted life years (DALY) method was applied to estimate the years of life lost (YLL) and cost estimate due to deaths from non-accidental causes, cardiovascular and respiratory diseases. The total YLL attributable to PM2.5 concentration was estimated by calculating the attributable fraction (AF) through relative risk. We also collected PM2.5 using a Harvard impactor to evaluate health risks from toxic metals components. During the study period, the analysis of chemical characterization of PM2.5 showed enrichment factors for most elements and the possible influence of the calcination process facilities on the PM2.5 levels. The mean concentration of PM2.5 exceeded the annual WHO air quality guideline (AQG) level, accounted for 3.5%, 4.7%, and 4.3% of total YLL from all causes, cardiovascular, and respiratory diseases, which corresponded to 0.23 (95% CI: 0.17-0.26), 0.06 (95% CI: 0.05-0.07) and 0.03 (95% CI: 0.01-0.06) years loss in life expectancy, respectively. An indirect health cost attributable to PM2.5 resulted in US$ 1.4 million, equivalent to about 3.5% of the total local annual health costs in Rio Branco do Sul, underscoring the significant financial burden of PM2.5 exposures. The greatest economic loss was found in the male age group of 40-69 years and among those with cardiovascular disease, rather than those with respiratory disease. Despite this, the carcinogenic and non-carcinogenic risks from inhalation of hazardous elements were within safe ranges. This work demonstrated PurpleAir's potential for air quality and public health applications. Our findings indicate health and economic benefits from reducing PM2.5 levels by adopting WHO air pollution standards. The results can guide policies toward delivering more effective health care.

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The relationship between COVID-19 infections and environmental contaminants provides insight into how environmental factors can influence the spread of infectious diseases. By integrating epidemiological and environmental variables into a mathematical framework, the interaction between virus spread and the environment can be determined. The aim of this study was to evaluate the impact of atmospheric contaminants on the increase in COVID-19 infections in the city of Quito through the application of statistical tests. The data on infections and deaths allowed to identify the periods of greatest contagion and their relationship with the contaminants O3, SO2, CO, PM2.5, and PM10. A validated database was used, and statistical analysis was applied through five models based on simple linear regression. The models showed a significant relationship between SO2 and the increase in infections. In addition, a moderate correlation was shown with PM2.5, O3, and CO, and a low relationship was shown for PM10. These findings highlight the importance of having policies that guarantee air quality as a key factor in maintaining people's health and preventing the proliferation of viral and infectious diseases.

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Despite a growing literature for complex air quality models, scientific evidence lacks of the influences of varying exposure assessments and air quality data sources on the estimated mortality risks. This case-crossover study estimated cardiovascular mortality risks from fine particulate matter (PM2.5) and ozone (O3) exposures, using varying exposure methods, to aid understanding of the impact of exposure methods in the health risk estimation. We used individual-level cardiovascular mortality data in the city of Rio de Janeiro, 2012-2016. PM2.5 and O3 exposure levels (from the date of death to seven prior days [lag0-7]) were estimated at the individual level or district level using either the WRF-Chem modeling data or monitoring data, resulting in a total of 10 exposure methods. The exposure-response relationships were estimated using multiple logistic regressions. The changes in cardiovascular mortality were represented as an odds ratio (OR) and 95% confidence intervals (CIs) for an interquartile range (IQR) increase in the exposures. Results showed that socioeconomically more advantaged populations had lower access to the stationary monitoring networks. Higher variance in the estimated exposure levels across the 10 exposure methods was found for PM2.5 than O3. PM2.5 exposure was not associated with mortality risk in any exposure methods. WRF-Chem-based O3 exposure estimated for each individual of the entire population found a significant mortality risk (OR = 1.06, 95% CI: 1.01, 1.11), but not the other exposure methods. Higher risks for females and older populations were suggested for O3 estimates estimated for each individual using the WRF-Chem data. Findings indicate that decisions on exposure methods and data sources can lead to substantially varying implications for air pollution risks and highlight the need for comprehensive exposure and health impact assessments to aid local decision-making for air pollution and public health.

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Low birth weight (LBW) is a global health concern. While it is commonly associated with maternal health and behavior, exposure to ambient air pollution, can also play a role in contributing to LBW. In Brazil, where diverse environmental conditions and regional disparities exist, assessing the impact of ambient air pollution on LBW becomes particularly pertinent. To our knowledge, there is a gap in the existing literature, as no previous study has specifically investigated the relationship between ambient air pollution and LBW nationwide in Brazil. This study aims to fill this gap by examining the association between ambient air pollution and LBW in each trimester of pregnancy across the Brazilian states. In this work, birth data from January 1, 2001, to December 31, 2018 has been used. We utilized logistic regression models to estimate the odds ratio (OR) for low birth weight (LBW) associated with ambient air pollution (PM2.5, NO2, and O3) during each trimester of pregnancy (1st to 3rd trimester) across all 27 Brazilian states in our nationwide case-control study. We adjusted our model for several variables, including ambient temperature, relative humidity, and socioeconomic status (SES) variables at the individual level. We also conducted effect modification analyses by infant sex, mother's age, and the number of prenatal visits. Our study comprises over 10,213,144 birth records nationwide. Of these, 479,204 (4.92%) infants were included as cases of LBW. Our results indicate positive associations between PM2.5 and LBW, mainly in the Southern region. For example, in the state of Santa Catarina (South region), ORs were 1.003 (95% CI: 1.002, 1.004), 1.003 (95% CI: 1.002, 1.004), and 1.005 (95% CI: 1.003, 1.007) for the 1st, 2nd, and 3rd trimesters of exposure, respectively. NO2 had a robust association with LBW in the Northern and Northeastern states, including the state of Amapá (North region, where the Amazon Forest is located) with ORs of 1.377 (95% CI: 1.010, 1.878), 1.390 (95% CI: 1.020, 1.894), and 1.747 (95% CI: 1.297, 2.352) for the 1st, 2nd, and 3rd trimesters of exposure, respectively. Similarly, O3 had a robust association in the North and Midwest states, as observed in the state of Amapá with ORs of 1.033 (95% CI: 1.012, 1.054), and 1.033 (95% CI: 1.013, 1.053) for the 2nd, and 3rd trimesters, respectively. In the stratified analysis, boys were more vulnerable than girls, and the lower number of prenatal visits was associated with higher OR. Our findings are essential to the development of guidelines to prevent maternal exposure and protection of newborns in Brazil. This study provides valuable insights for region-specific strategies to improve maternal and neonatal health.

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Objectives: For the development of the 2021 global air quality guidelines, the World Health Organization (WHO) commissioned a series of systematic reviews and meta-analyses to assess the association between exposure to air pollution and all-cause and cause-specific mortality. One of these reviews, which we aim to update, focused on the effects of long-term exposure to PM2.5 and PM10 on all-cause and cause-specific mortality. Methods: The protocol for this study was registered in PROSPERO (CRD42023425327). We searched the PubMed and Embase databases for studies published between September 2018 and May 2023. Study-specific effects were pooled using random-effects models. Results: We included 106 studies in the meta-analysis, 46 studies from the previous review and 60 from this update. All exposure-outcome pairs analysed showed positive and significant associations, except for PM10 and cerebrovascular mortality. The certainty of the evidence was rated as high for the majority of exposure-outcome pairs. Conclusion: We included a large number of new cohorts, and provided new concentration-response functions that will inform WHO advice on the use of this information for air pollution health risk assessments.

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Introduction: Air quality is a matter of interest for public health due to its rapid deterioration in low- and middle-income countries and the effects of polluted air on the health of populations. Objective: To explore the air quality conditions in which digital platform delivery workers carry out their work, evaluating the localities of Kennedy and Usaquén in Bogotá, 2021. Materials and methods: We developed a mixed parallel convergent study based on four sources of information: 1) Ethnographic observation in five commercial locations of the two localities; 2) Monitoring of PM10 and PM2.5 in 56 delivery routes using a low-cost sensor; 3) Daily logs of the routes to support the device data interpretation, and 4) A semi-structured interview applied to the drivers to explore their danger perception during the routes. Results: We identified elements causing environmental injustice among digital platform delivery workers between the two study locations. The routes made by the delivery drivers in the locality of Kennedy registered higher concentrations of PM10 and PM2.5, compared to the values observed in Usaquén. The sources of air pollution identified by the delivery drivers through ethnographic observation and the router logbook showed the worst parameters in Kennedy. Conclusions: We evidenced that air quality, urban equipment, road infrastructure, mobile sources, and geospatial location are elements that mark the presence of environmental injustice for the digital platform delivery drivers in the studied localities. To reduce this inequity, it is necessary for digital delivery platforms and the district government to implement strategies that reduce the exposure and emission of air pollutants to protect the health of digital platform delivery workers.

Introducción: La calidad del aire es un asunto de interés para la salud pública por su rápido deterioro en los países de bajos y medianos ingresos, y los efectos del aire contaminado en la salud de las poblaciones. Objetivo: Explorar las condiciones de la calidad del aire en las que los repartidores de plataformas digitales desarrollaron su trabajo en las localidades de Kennedy y Usaquén de Bogotá durante el 2021. Materiales y métodos: Se llevó a cabo un estudio mixto, paralelo y convergente, basado en cuatro fuentes de información: 1) observación etnográfica en cinco ubicaciones comerciales de las dos localidades; 2) monitoreo de PM10 y PM2.5 en 56 rutas de reparto, empleando un equipo de bajo costo; 3) bitácoras diarias de los recorridos que apoyaron la interpretación de los datos del equipo, y 4) entrevista semiestructurada con el rutero para explorar sus percepciones frente a los peligros durante los recorridos. Resultados: Se identificaron diferencias en las condiciones de trabajo, las percepciones y las exposiciones a material particulado de los repartidores entre las dos localidades de estudio que constituyeron fuentes de injusticia ambiental. Los recorridos que realizaron los repartidores en la localidad de Kennedy registraron mayores concentraciones de PM10 y PM2.5. Las fuentes de contaminación atmosférica identificadas por los repartidores mostraron los peores parámetros en Kennedy. Conclusiones: Se evidenció que la calidad del aire, el equipamiento urbano, la infraestructura vial, las fuentes móviles y la ubicación geoespacial son elementos que marcan la presencia de injusticia ambiental para los repartidores. Para disminuir esta inequidad, es necesario que las plataformas de reparto digital y el gobierno distrital implementen estrategias que reduzcan la exposición y la emisión de contaminantes del aire con el fin de proteger la salud de los repartidores de plataformas.

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OBJECTIVE: This study aimed to explore the correlation between ambient particulate matter 2.5 (PM2.5) concentration and sperm quality among northern Thai men exposed to the seasonal air pollution from the agricultural burning process. METHODS: The demographic data and semen analysis of Thai men living in Chiang Mai, Thailand, who visited the infertile clinic were collected. The correlation test between the monthly amount of PM2.5 and sperm quality was carried out. RESULTS: From 2017 to 2021, 1,109 Thai men visited the Infertile Clinic. The correlation test between PM2.5 and sperm quality in years with a better climate revealed a weak positive correlation between the mean PM2.5 and percentage of progressive motile sperm and normal morphology (r=0.08, p=0.05 and r=0.1, p=0.02). However, there was a negative correlation between the mean PM2.5 and sperm concentration, progressive motility and normal sperm morphology during the years with a higher amount of ambient PM2.5, and especially PM2.5 exposure 3 months before semen collection (r=-0.12, p=0.01, r=-0.11, p=0.003, r=-0.15, p=0.004). CONCLUSIONS: Exposure to a high amount of PM2.5 air pollution negatively affects sperm quality.

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Introducción. La calidad del aire es un asunto de interés para la salud pública por su rápido deterioro en los países de bajos y medianos ingresos, y los efectos del aire contaminado en la salud de las poblaciones. Objetivo. Explorar las condiciones de la calidad del aire en las que los repartidores de plataformas digitales desarrollaron su trabajo en las localidades de Kennedy y Usaquén de Bogotá durante el 2021. Materiales y métodos. Se llevó a cabo un estudio mixto, paralelo y convergente, basado en cuatro fuentes de información: 1) observación etnográfica en cinco ubicaciones comerciales de las dos localidades; 2) monitoreo de PM10 y PM2.5 en 56 rutas de reparto, empleando un equipo de bajo costo; 3) bitácoras diarias de los recorridos que apoyaron la interpretación de los datos del equipo, y 4) entrevista semiestructurada con el rutero para explorar sus percepciones frente a los peligros durante los recorridos. Resultados. Se identificaron diferencias en las condiciones de trabajo, las percepciones y las exposiciones a material particulado de los repartidores entre las dos localidades de estudio que constituyeron fuentes de injusticia ambiental. Los recorridos que realizaron los repartidores en la localidad de Kennedy registraron mayores concentraciones de PM10 y PM2.5. Las fuentes de contaminación atmosférica identificadas por los repartidores mostraron los peores parámetros en Kennedy. Conclusiones. Se evidenció que la calidad del aire, el equipamiento urbano, la infraestructura vial, las fuentes móviles y la ubicación geoespacial son elementos que marcan la presencia de injusticia ambiental para los repartidores. Para disminuir esta inequidad, es necesario que las plataformas de reparto digital y el gobierno distrital implementen estrategias que reduzcan la exposición y la emisión de contaminantes del aire con el fin de proteger la salud de los repartidores de plataformas.

Introduction. Air quality is a matter of interest for public health due to its rapid deterioration in low- and middle-income countries and the effects of polluted air on the health of populations. Objective. To explore the air quality conditions in which digital platform delivery workers carry out their work, evaluating the localities of Kennedy and Usaquén in Bogotá, 2021. Materials and methods. We developed a mixed parallel convergent study based on four sources of information: 1) Ethnographic observation in five commercial locations of the two localities; 2) Monitoring of PM10 and PM2.5 in 56 delivery routes using a low-cost sensor; 3) Daily logs of the routes to support the device data interpretation, and 4) A semi-structured interview applied to the drivers to explore their danger perception during the routes. Results. We identified elements causing environmental injustice among digital platform delivery workers between the two study locations. The routes made by the delivery drivers in the locality of Kennedy registered higher concentrations of PM10 and PM2.5, compared to the values observed in Usaquén. The sources of air pollution identified by the delivery drivers through ethnographic observation and the router logbook showed the worst parameters in Kennedy. Conclusions. We evidenced that air quality, urban equipment, road infrastructure, mobile sources, and geospatial location are elements that mark the presence of environmental injustice for the digital platform delivery drivers in the studied localities. To reduce this inequity, it is necessary for digital delivery platforms and the district government to implement strategies that reduce the exposure and emission of air pollutants to protect the health of digital platform delivery workers.

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The increase in the frequency and severity of global wildfires has been largely influenced by climate change and land use changes. From February 2 to 6, 2024, central Chile experienced its most devastating wildland-urban interface wildfire in history, severely impacting the Valparaíso region. This catastrophic event, which led to extensive forest destruction, the loss of thousands of homes, and over a hundred human fatalities, directly impacted the area surrounding the campus of Federico Santa María Technical University. In that period, an air quality monitoring campaign was set up on the campus to measure black carbon (BC) and particulate matter (PM) during the wildfire season. The monitoring station was located directly within the smoke plume, allowing for the collection of unprecedented air quality data. Extremely high concentrations of BC at 880 nm were reported during the wildfires, with a daily mean (±σ) of 14.83 ± 19.52 µg m-3. Peak concentrations measured at 880 nm and 375 nm reached 812.89 µg m-3 and 1561.24 µg m-3, respectively. The maximum daily mean BC concentrations at these wavelengths were 55 and 99 times higher, respectively, compared to the pre-event period. The mean Ångström absorbing coefficient during the event was 1.66, indicating biomass burning as the primary BC source, while the maximum BC/PM2.5 ratio (at 375 nm) reached 57 %. From February 2 to 5, 2024, PM concentrations exceeded the Chilean air quality standard by 82 % and 198 % for coarse and fine particles, respectively. These levels are 4.7 and 6.0 times higher than the World Health Organization's recommendations. These elevated concentrations persisted for up to three days after the fire was extinguished. This study provides unique evidence of the rapid deterioration of regional air quality during a wildfire event using in situ measurements, serving as a stark reminder of the far-reaching consequences of a warming climate.

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BACKGROUND: Recent evidence has linked air pollution with frailty, yet little is known about the role of NO2 in this association. Our aim was to assess the association between frailty and NO2 air concentrations in Mexican older adults. METHODS: We used georeferenced data from the population-based Nutrition and Health Survey in Mexico (NHNS) 2021, representative of national and subnational regions, to measure a frailty index based on 31 health deficits in adults aged 50 and older. Air pollution due to NO2 concentrations was estimated from satellite images validated with data from surface-level stations. Maps were produced using Jensen's Natural break method. The association of frailty and NO2 concentrations was measured using the frailty index (multivariate fractional response logit regression) and a frailty binary variable (frailty index [FI] ≥0.36, multivariate logit regression). RESULTS: There was a positive and significant association of the frailty index with the NO2 concentrations, adjusting for age, sex, urban and rural area, years of education, socioeconomic status, living arrangement, particulate matter smaller than 2.5 microns, and indoor pollution. For each standard deviation increase in NO2 concentrations measured 10 years before the survey, the odds of being frail were 15% higher, and the frailty index was 14.5% higher. The fraction of frailty attributable to NO2 exposure ranged from 1.8% to 23.5% according to different scenarios. CONCLUSIONS: Frailty was positively associated with exposure to NO2 concentrations. Mapping frailty and its associated factors like NO2 air concentrations can contribute to the design of targeted pro-healthy aging policies.