Spatiotemporal assessment of particulate matter (PM10 and PM2.5) and ozone in a Caribbean urban coastal city

Air pollution has become a critical issue in urban areas, so a broad understanding of its spatiotemporal characteristics is important to develop public policies. This study analyzes the spatiotemporal variation of atmospheric particulate matter (PM10 and PM2.5) and ozone (O3) in Barranquilla, Colombia from March 2018 to June 2019 in three monitoring stations. The average concentrations observed for the Móvil, Policía, and Tres Avemarías stations, respectively, for PM10: 46.4, 51.4, and 39.7 µg/m3; for PM2.5: 16.1, 18.1, and 15.1 µg/m3 and for O3: 35.0, 26.6, and 33.6 µg/m3. The results indicated spatial and temporal variations between the stations and the pollutants evaluated. The highest PM concentrations were observed in the southern part of the city, while for ozone, higher concentrations were observed in the north. These variations are mainly associated with the influence of local sources in the environment of each site evaluated as well as the meteorological conditions and transport patterns of the study area. This study also verified the existence of differences in the concentrations of the studied pollutants between the dry and rainy seasons and the contribution of local sources as biomass burnings from the Isla Salamanca Natural Park and long-range transport of dust particles from the Sahara Desert. This study provides a scientific baseline for understanding air quality in the city, which enables policy makers to adopt efficient measures that jointly prevent and control pollution

Estimation of the impact of biomass burning based on regional transport of PM2.5 in the Colombian Caribbean

Deterioration of air quality due to the increase in atmospheric emissions from biomass burning (BB) is one of the major environmental problems worldwide. In this study, we estimated the contributions of BB to PM2.5 concentrations in the municipalities of Soledad and Malambo located in the Colombian Caribbean. The evaluation period ranged from February 24 to March 30, 2018, a period with a high number of BB events recorded in the surroundings of the evaluated sites. The contribution of BB to the two sampling sites was estimated using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) dispersion model with forwarding trajectories from each of the burning points identified by satellite images (n = 1089). The PM2.5 emissions were determined using the fire radiative power (FRP), obtained by remote-sensing data, and corresponded to the radiant energy released per time unit by burning vegetation. The average PM2.5 concentrations during the evaluation period were 19.91 µg/m3 for Soledad and 22.44 µg/m3 for Malambo. The average contribution of BB to these municipalities was 22.8% and 28.8%, respectively. The methodology used in this study allowed to estimate the contribution of this important source without knowledge of a previous tracer of BB, thereby increasing the use of the proposed procedure worldwide. This information would enable the implementation of effective mitigation, thereby diminishing the adverse impact of PM2.5 on the health of the population

Geochemical study of submicron particulate matter (PM1) in a metropolitan area

Air pollution has become a major problem in urban areas due to increasing industrialization and urbanization. In this study ambient concentrations of PM1 and metal concentrations as well as source contributions were identified and quantified by using Positive Matrix Factorization (PMF) in receptor modeling in the Metropolitan Area of Porto Alegre, Brazil. The PM1 samples were collected on PTFE filters from December 2012 to December 2014 in two sampling sites. Major ion and trace element concentrations were assessed. The average concentrations were 12.8 and 15.2 µg/m3 for Canoas and Sapucaia do Sul sites, respectively. Major ion contributions of PM1 were secondary pollutants such as sulfate and nitrate. Trace elements, especially Cu, Pb, Zn, Cd, and Ni also made important contributions which are directly associated with anthropogenic contributions. Our results show significantly higher levels in winter than in summer. Most of the PM1 and the analyzed PM species and elements originated from anthropogenic sources, especially road traffic, combustion processes and industrial activities, which are grouped in 7 major contributing sources. A back-trajectory analysis showed that the long-range transport of pollutants was not relevant in relation to the contribution to PM1 and metal concentrations. This work highlights the importance of urban planning to reduce human health exposure to traffic and industrial emissions, combined with awareness-raising actions for citizens concerning the impact of indoor sources

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Avaliação analítica integrada de PM1 e nanopartículas atmosféricas

As nanopartículas atmosféricas podem causar diversos efeitos à saúde já que durante a inalação podem penetrar mais profundamente no sistema respiratório humano, atingindo inclusive os alvéolos e a corrente sanguínea, e, desta forma, aumentar os efeitos toxicológicos prejudiciais. Estas partículas podem ser emitidas diretamente para a atmosfera (partículas primárias) ou ser formadas por conversão gás-partícula (partículas secundárias). Durante a última década, estudos têm sido realizados para uma melhor compreensão sobre as concentrações de nanopartículas, avaliando sua emissão, formação, dispersão, exposição e os efeitos à saúde. No entanto, poucos estudos foram realizados no Brasil e desta forma ainda há pouca informação em relação a esta temática. A Região Metropolitana de Porto Alegre - RMPA (Brasil) possui forte tráfego veicular, cerca de 1,8 milhões de veículos e, apesar das fontes móveis impactarem fortemente a qualidade do ar nesta região e ser a principal fonte de nanopartículas, não há estudos que avaliem em profundidade os níveis deste importante poluente ambiental. Desta forma, no presente estudo foram avaliadas as concentrações de nanopartículas em diferentes pontos da RMPA. Além disso, foram avaliadas as concentrações ambientais de partículas <1 μm (MP1) e metais associados, bem como foram identificadas e quantificadas as contribuições de fontes utilizando o modelo receptor Positive Matrix Factorization (PMF). Em adição, foi realizada uma análise das assinaturas espectrais no infravermelho de nitro-hidrocarbonetos policíclicos aromáticos (nitro-HPAs) associados ao MP1. Este grupo de compostos orgânicos possui uma ampla distribuição no ambiente e, por possuírem propriedades mutagênicas e carcinogênicas, seus riscos ambientais foram calculados. Desta forma, considerando os resultados obtidos, verificou-se uma forte contribuição antropogênica dos poluentes avaliados na RMPA. Esta degradação da qualidade do ar está em geral associada ao tráfego veicular, especialmente no que se refere aos níveis de nanopartículas e nitro-HPAs associados ao MP1. Além disso, as emissões industriais, a queima de carvão, biomassa e óleo combustível, bem como a queima de combustíveis veiculares apresentaram forte influência nos níveis de metais observados em MP1.Atmospheric nanoparticles can cause health effects, as during inhalation penetrate more deeply into the human respiratory system, including the alveoli and reaching the bloodstream, and thereby increase the damaging toxicological effects. These particles can be emitted directly to the atmosphere (primary particles) or be formed by gas-to-particle conversion (secondary particle). Over the last decade, studies have been conducted for a better understanding of the nanoparticles, assessing the emission, formation, dispersion, exposure and health effects. However, few studies have been conducted in Brazil and thus there is little information regarding this subject. The Metropolitan Area of Porto Alegre - MAPA (Brazil) has a strong vehicular traffic, about 1.8 million vehicles and, despite mobile sources strongly impact the air quality in this region and be the main source of nanoparticles, there are no studies that evaluate in depth the levels of this important environmental pollutant. Thus, considering this knowledge gap, the present study evaluated the nanoparticle concentrations in different sites of the MAPA. In addition, environmental concentrations of particles <1 μm (MP1) and associated metals were evaluated and the sources were identified and quantified using the receptor model Positive Matrix Factorization (PMF). In addition, an analysis of the infrared spectral signatures of nitro polycyclic aromatic hydrocarbons (nitro-PAHs) associated with PM1 was performed. This group of organic compounds has a wide distribution in the environment, and because they have mutagenic and carcinogenic properties, their environmental risks were calculated. Thus, considering the obtained results, a strong anthropogenic contribution of the evaluated pollutants in the MAPA was observed. This degradation of the air quality in general is associated with vehicular traffic, especially regarding the levels of nanoparticles and nitro-PAHs associated with PM1. In addition, industrial emissions, coal, biomass and fuel oil combustion, as well as vehicle fuels combustion had a strong influence on the metal levels observed in PM1

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Caracterização espectroscópica dos sedimentos da bacia hidrográfica do Rio dos Sinos (RS)

O presente estudo teve como objetivo avaliar o teor de Cu, Cr, Ni, Zn, Pb, Mn, Al e Fe e sua partição geoquímica em sedimentos da bacia hidrográfica do rio dos Sinos, Sul do Brasil. Esta bacia apresenta elevada densidade populacional e industrial, especialmente dos setores de metalurgia, galvanoplastia, siderurgia, petroquímica e curtumes. As concentrações totais de metais, determinadas por espectroscopia de fluorescência de raios X, e as concentrações nas fases dos sedimentos, determinadas através da aplicação do esquema de extração sequencial BCR-701 proposto pelo Community Bureau of Reference, da Comunidade Europeia, utilizando ICP/OES, foram avaliadas nos sedimentos com granulometria <63 μm. Também foram considerados os teores extraídos através de uma solução de HCl 0,5 mol/L nesta fração dos sedimentos. Os resultados na região industrializada e com alta densidade populacional mostraram um aumento nas concentrações totais, para Cu, Cr, Zn e Pb, e nas frações potencialmente móveis para os metais Cu, Cr, Zn e Ni extraídos sequencialmente. O Cr destacou-se especialmente no arroio Portão, apresentando uma concentração total de 1286 mg/kg, devido à influência de curtumes localizados nesta região. Os sedimentos também foram caracterizados através de espectroscopia de reflectância, método rápido e não destrutivo de caracterização dos diferentes materiais, na região entre 400 e 2500 nm. Nos espectros de reflectância das amostras avaliadas observou-se que as principais feições espectrais são resultantes das absorções decorrentes da água, das ligações Al-OH e dos teores de ferro presentes. Ainda ficou evidenciada a influência da granulometria, dos teores de ferro e matéria orgânica sobre os espectros de reflectância resultantes. Não foi possível observar as feições espectrais decorrentes dos metais pesados, provavelmente devido às altas concentrações de ferro observadas nas amostras e devido ao fato destes metais apresentarem as suas feições espectrais nas mesmas regiões de comprimento de onda onde ocorrem as feições do ferro.The present study aimed to evaluate the content of Cu, Cr, Ni, Zn, Pb, Mn, Al, and Fe as well as their geochemical partitioning in sediments of the Sinos river basin in southern Brazil. This basin has a high population density and a great number of industries, especially metallurgy, electroplating works, steel mills, petrochemicals, and tanneries. The total metal concentrations, determined by X-ray fluorescence, and the concentrations in the sediment phases, determined by applying the BCR-701 sequential extraction method proposed by the Community Bureau of Reference of the European Community, using ICP/OES, were evaluated in the sediment fraction <63 μm. The contents extracted by a solution of 0.5 mol/L HCl were also considered in this fraction. Results in the industrialized and densely populated region showed an increase in the total concentrations for Cu, Cr, Zn, and Pb, and in the potentially mobile fractions for the sequentially extracted metals Cu, Cr, Zn and Ni. Cr stood out particularly in the Portão stream, showing a total concentration of 1,286 mg/kg, due to the influence of tanneries in this region. The sediments were also characterized by reflectance spectroscopy, a rapid and nondestructive method for characterization of different materials, in the region between 400 and 2500 nm. The reflectance spectra of the samples showed that the main spectral features are the result of the absorptions due to water, Al-OH bonds and contents of iron. The influences of particle size, organic matter and mineral composition on the absorption features and on the reflection coefficient of the spectra were also evidenced. It was not possible to observe the spectral features resulting from metals, probably due to high iron concentrations observed in the samples, and because these metals make their spectral features on the same wavelength regions where there are the iron spectral features

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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.MethodsThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.FindingsThe leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.InterpretationLong-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere