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Brazil has experienced one of the highest COVID-19 fatality rates globally. While numerous studies have explored the potential connection between air pollution, specifically fine particulate matter (PM2.5), and the exacerbation of SARS-CoV-2 infection, the majority of this research has been conducted in foreign regions-Europe, the United States, and China-correlating generalized pollution levels with health-related scopes. In this study, our objective is to investigate the localized connection between exposure to air pollution exposure and its health implications within a specific Brazilian municipality, focusing on COVID-19 susceptibility. Our investigation involves assessing pollution levels through spatial interpolation of in situ PM2.5 measurements. A network of affordable sensors collected data across 9 regions in Curitiba, as well as its metropolitan counterpart, Araucaria. Our findings distinctly reveal a significant positive correlation (with r-values reaching up to 0.36, p-value < 0.01) between regions characterized by higher levels of pollution, particularly during the winter months (with r-values peaking at 0.40, p-value < 0.05), with both COVID-19 mortality and incidence rates. This correlation gains added significance due to the intricate interplay between urban atmospheric pollution and regional human development indices. Notably, heightened pollution aligns with industrial hubs and intensified vehicular activity. The spatial analysis performed in this study assumes a pivotal role by identifying priority regions that require targeted action post-COVID. By comprehending the localized dynamics between air pollution and its health repercussions, tailored strategies can be implemented to alleviate these effects and ensure the well-being of the public.
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Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Humanos , Estados Unidos , COVID-19/epidemiologia , Poluentes Atmosféricos/toxicidade , Poluentes Atmosféricos/análise , Pandemias , Brasil/epidemiologia , SARS-CoV-2 , Material Particulado/toxicidade , Material Particulado/análise , Poluição do Ar/análiseRESUMO
The global burden of disease estimated that approximately 7.1 million deaths worldwide were related to air pollution in 2016. However, only a limited number of small- and middle-sized cities have air quality monitoring networks. To date, air quality in terms of particulate matter is still mainly focused on mass concentration, with limited compositional monitoring even in mega cities, despite evidence indicating differential toxicity of particulate matter. As this evidence is far from conclusive, we conducted PM2.5 bioaccessibility studies of potentially harmful elements in a medium-sized city, Londrina, Brazil. The data was interpreted in terms of source apportionment, the health risk evaluation and the bioaccessibility of inorganic contents in an artificial lysosomal fluid. The daily average concentration of PM2.5 was below the WHO guideline, however, the chemical health assessment indicated a considerable health risk. The in vitro evaluation showed different potential mobility when compared to previous studies in large-sized cities, those with 1 million inhabitants or more (Curitiba and Manaus). The new WHO guideline for PM2.5 mass concentration puts additional pressure on cities where air pollution monitoring is limited and/or neglected, because decision making is mainly revenue-driven and not socioeconomic-driven. Given the further emerging evidence that PM chemical composition is as, or even more, important than mass concentration levels, the research reported in the paper could pave the way for the necessary inter- and intra-city collaborations that are needed to address this global health challenge.
Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Cidades , Poluição do Ar/análise , Material Particulado/análise , Organização Mundial da Saúde , Monitoramento AmbientalRESUMO
Port-related activities have a detrimental impact on the air quality both at the point of source and for considerable distances beyond. These activities include, but are not limited to, heavy cargo traffic, onboard, and at-berth emissions. Due to differences in construction, operation, location, and policies at ports, the site-specific air pollution cocktail could result in different human health risks. Thus, monitoring and evaluating such emissions are essential to predict the risk to the community. Environmental agencies often monitor key pollutants (PM2.5, PM10, NO2, SO2), but the volatile organic carbons (VOCs) most often are not, due to its analytical challenging. This study intends to fill that gap and evaluate the VOC emissions caused by activities related to the port of Paranaguá - one of the largest bulk ports in Latin America - by characterizing BTEX concentrations at the port and its surroundings. At seven different sites, passive samplers were used to measure the dispersion of BTEX concentrations throughout the port and around the city at weekly intervals from November 2018 to January 2019. The average and uncertainty of BTEX concentrations (µg m-3) were 0.60 ± 0.43, 5.58 ± 3.80, 3.30 ± 2.41, 4.66 ± 3.67, and 2.82 ± 1.95 for benzene, toluene, ethylbenzene, m- and p-xylene, and o-xylene, respectively. Relationships between toluene and benzene and health risk analysis were used to establish the potential effects of BTEX emissions on the population of the city of Paranaguá. Ratio analysis (T/B, B/T, m,p X/Et, and m,p X/B) indicate that the BTEX levels are mainly from fresh emission sources and that photochemical ageing was at minimum. The cancer risk varied across the sampling trajectory, whereas ethylbenzene represented a moderate cancer risk development for the exposed population in some of the locations. This study provided the necessary baseline data to support policymakers on how to change the circumstances of those currently at risk, putting in place a sustainable operation.
Assuntos
Poluentes Atmosféricos , Humanos , Poluentes Atmosféricos/análise , Benzeno/análise , Monitoramento Ambiental , América Latina , Derivados de Benzeno/análise , Xilenos/análise , Tolueno/análiseRESUMO
For regulatory purposes, air pollution has been reduced to management of air quality control regions (AQCR), by inventorying pollution sources and identifying the receptors significantly affected. However, beyond being source-dependent, particulate matter can be physically and chemically altered by factors and elements of climate during transport, as they act as local environmental constraints, indirectly modulating the adverse effects of particles on the environment and human health. This case study, at an industrial site in a Brazilian coastal city - Joinville, combines different methodologies to integrate atmospheric dynamics in a strategic risk assessment approach whereby the influence of different wind regimes on environmental and health risks of exposure to PM2.5-bound elements, are analysed. Although Joinville AQCR has been prone to stagnation/recirculation events, distinctly different horizontal wind circulation patterns indicate two airsheds within the region. The two sampling sites mirrored these two conditions and as a result we report different PM2.5 mass concentrations, chemical profiles, geo-accumulation, and ecological and human health risks. In addition, feedback mechanisms between the airsheds seem to aggravate the air quality and its effects even under good ventilation conditions. Recognizably, the risks associated with Co, Pb, Cu, Ni, Mn, and Zn loadings were extremely high for the environment as well as being the main contributors to elevated non-carcinogenic risks. Meanwhile, higher carcinogenic risks occurred during stagnation/recirculation conditions, with Cr as the major threat. These results highlight the importance of integrating local airshed characteristics into the risk assessment of PM2.5-bound elements since they can aggravate air pollution leading to different risks at a granular scale. This new approach to risk assessment can be employed in any city's longer-term development plan since it provides public authorities with a strategic perspective on incorporating environmental constraints into urban growth planning and development zoning regulations.
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The Amazon rainforest is the world's largest tropical forest, and this biome may be a significant contributor to primary biological aerosol (PBA) emissions on a global scale. These aerosols also play a pivotal role in modulating ecosystem dynamics, dispersing biological material over geographic barriers and influencing climate through radiation absorption, light scattering, or acting as cloud condensation nuclei. Despite their importance, there are limited studies investigating the effect of environmental variables on the bioaerosol composition in the Amazon rainforest. Here we present a 16S rRNA gene-based amplicon sequencing approach to investigate the bacterial microbiome in aerosols of the Amazon rainforest during distinct seasons and at different heights above the ground. Our data revealed that seasonal changes in temperature, relative humidity, and precipitation are the primary drivers of compositional changes in the Amazon rainforest aerosol microbiome. Interestingly, no significant differences were observed in the bacterial community composition of aerosols collected at ground and canopy levels. The core airborne bacterial families present in Amazon aerosol were Enterobacteriaceae, Beijerinckiaceae, Polyangiaceae, Bacillaceae and Ktedonobacteraceae. By correlating the bacterial taxa identified in the aerosol with literature data, we speculate that the phyllosphere may be one possible source of airborne bacteria in the Amazon rainforest. Results of this study indicate that the aerosol microbiota of the Amazon Rainforest are fairly diverse and principally impacted by seasonal changes in temperature and humidity.
Assuntos
Microbiota , Floresta Úmida , Aerossóis , Florestas , Humanos , RNA Ribossômico 16S/genéticaRESUMO
Limited studies have reported on in-vitro analysis of PM2.5 but as far as the authors are aware, bioaccessibility of PM2.5 in artificial lysosomal fluid (ALF) has not been linked to urban development models before. The Brazilian cities Manaus (Amazon) and Curitiba (South region) have different geographical locations, climates, and urban development strategies. Manaus drives its industrialization using the free trade zone policy and Curitiba adopted a services centered economy driven by sustainability. Therefore, these two cities were used to illustrate the influence that these different models have on PM2.5 in vitro profile. We compared PM2.5 mass concentrations and the average total elemental and bioaccessible profiles for Cu, Cr, Mn, and Pb. The total average elemental concentrations followed Mn > Pb > Cu > Cr in Manaus and Pb > Mn > Cu > Cr in Curitiba. Mn had the lowest solubility while Cu showed the highest bioaccessibility (100%) and was significantly higher in Curitiba than Manaus. Cr and Pb had higher bioaccessibility in Manaus than Curitiba. Despite similar mass concentrations, the public health risk in Manaus was higher than in Curitiba indicating that the free trade zone had a profound effect on the emission levels and sources of airborne PM. These findings illustrate the importance of adopting sustainable air quality strategies in urban planning.
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Poluentes Atmosféricos/análise , Poluição do Ar/análise , Monitoramento Ambiental , Metais Pesados/análise , Material Particulado/análise , Reforma Urbana , Brasil , Cidades , Desenvolvimento Industrial , Exposição por Inalação , Medição de RiscoRESUMO
Among the new technologies developed for the heavy-duty fleet, the use of Selective Catalytic Reduction (SCR) aftertreatment system in standard Diesel engines associated with biodiesel/diesel mixtures is an alternative in use to control the legislated pollutants emission. Nevertheless, there is an absence of knowledge about the synergic behaviour of these devices and biodiesel blends regarding the emissions of unregulated substances as the Polycyclic Aromatic Hydrocarbons (PAHs) and Nitro-PAHs, both recognized for their carcinogenic and mutagenic effects on humans. Therefore, the goal of this study is the quantification of PAHs and Nitro-PAHs present to total particulate matter (PM) emitted from the Euro V engine fuelled with ultra-low sulphur diesel and soybean biodiesel in different percentages, B5 and B20. PM sampling was performed using a Euro V - SCR engine operating in European Stationary Cycle (ESC). The PAHs and Nitro-PAHs were extracted from PM using an Accelerated Solvent Extractor and quantified by GC-MS. The results indicated that the use of SCR and the largest fraction of biodiesel studied may suppress the emission of total PAHs. The Toxic Equivalent (TEQ) was lower when using 20% biodiesel, in comparison with 5% biodiesel on the SCR system, reaffirming the low toxicity emission using higher percentage biodiesel. The data also reveal that use of SCR, on its own, suppress the Nitro-PAHs compounds. In general, the use of larger fractions of biodiesel (B20) coupled with the SCR aftertreatment showed the lowest PAHs and Nitro-PAHs emissions, meaning lower toxicity and, consequently, a potential lower risk to human health. From the emission point of view, the results of this work also demonstrated the viability of the Biodiesel programs, in combination with the SCR systems, which does not require any engine adaptation and is an economical alternative for the countries (Brazil, China, Russia, India) that have not adopted Euro VI emission standards.
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Understanding the impact on human health during peak episodes in air pollution is invaluable for policymakers. Particles less than PM2.5 can penetrate the respiratory system, causing cardiopulmonary and other systemic diseases. Statistical regression models are usually used to assess air pollution impacts on human health. However, when there are databases missing, linear statistical regression may not process well and alternative data processing should be considered. Nonlinear Artificial Neural Networks (ANN) are not employed to research environmental health pollution even though another advantage in using ANN is that the output data can be expressed as the number of hospital admissions. This research applied ANN to assess the impact of air pollution on human health. Three well-known ANN were tested: Multilayer Perceptron (MLP), Extreme Learning Machines (ELM) and Echo State Networks (ESN), to assess the influence of PM2.5, temperature, and relative humidity on hospital admissions due to respiratory diseases. Daily PM2.5 levels were monitored, and hospital admissions for respiratory illness were obtained, from the Brazilian hospital information system for all ages during two sampling campaigns (2008-2011 and 2014-2015) in Curitiba, Brazil. During these periods, the daily number of hospital admissions ranged from 2 to 55, PM2.5 concentrations varied from 0.98 to 54.2⯵gâ¯m-3, temperature ranged from 8 to 26⯰C, and relative humidity ranged from 45 to 100%. Of the ANN used in this study, MLP gave the best results showing a significant influence of PM2.5, temperature and humidity on hospital attendance after one day of exposure. The Anova Friedman's test showed statistical difference between the appliance of each ANN model (pâ¯<â¯.001) for 1 lag day between PM2.5 exposure and hospital admission. ANN could be a more sensitive method than statistical regression models for assessing the effects of air pollution on respiratory health, and especially useful when there is limited data available.
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Poluentes Atmosféricos/análise , Poluição do Ar/estatística & dados numéricos , Exposição Ambiental/estatística & dados numéricos , Redes Neurais de Computação , Material Particulado/análise , Doenças Respiratórias/epidemiologia , Poluição do Ar/análise , Brasil/epidemiologia , Hospitalização , Humanos , Umidade , Modelos Lineares , Modelos Estatísticos , Análise de Regressão , Transtornos Respiratórios/epidemiologia , TemperaturaRESUMO
Although the particulate matter (PM) emissions from biodiesel fuelled engines are acknowledged to be lower than those of fossil diesel, there is a concern on the impact of PM produced by biodiesel to human health. As the oxidative potential of PM has been suggested as trigger for adverse health effects, it was measured using the Electron Spin Resonance (OP(ESR)) technique. Additionally, Energy Dispersive X-ray Fluorescence Spectroscopy (EDXRF) was employed to determine elemental concentration, and Raman Spectroscopy was used to describe the amorphous carbon character of the soot collected on exhaust PM from biodiesel blends fuelled test-bed engine, with and without Selective Catalytic Reduction (SCR). OP(ESR) results showed higher oxidative potential per kWh of PM produced from a blend of 20% soybean biodiesel and 80% ULSD (B20) engine compared with a blend of 5% soybean biodiesel and 95% ULSD (B5), whereas the SCR was able to reduce oxidative potential for each fuel. EDXRF data indicates a correlation of 0.99 between concentration of copper and oxidative potential. Raman Spectroscopy centered on the expected carbon peaks between 1100cm(-1) and 1600cm(-1) indicate lower molecular disorder for the B20 particulate matter, an indicative of a more graphitic carbon structure. The analytical techniques used in this study highlight the link between biodiesel engine exhaust and increased oxidative potential relative to biodiesel addition on fossil diesel combustion. The EDXRF analysis confirmed the prominent role of metals on free radical production. As a whole, these results suggest that 20% of biodiesel blends run without SCR may pose an increased health risk due to an increase in OH radical generation.
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Poluentes Atmosféricos/análise , Biocombustíveis/análise , Material Particulado/análise , Emissões de Veículos/análise , CatáliseRESUMO
Entender os processos naturais que regulam a composição da atmosfera é crítico para que se possa desenvolver uma estratégia de desenvolvimento sustentável na região. As grandes emissões de gases e partículas durante a estação seca provenientes das queimadas alteram profundamente a composição da atmosfera amazônica na maior parte de sua área. As concentrações de partículas de aerossóis e gases traço aumentam por fatores de 2 a 8 em grandes áreas, afetando os mecanismos naturais de uma série de processos atmosféricos na região amazônica. Os mecanismos de formação de nuvens, por exemplo, são profundamente alterados quando a concentração de núcleos de condensação de nuvens (NCN) passa de 200 a 300 NCN/cm³ na estação chuvosa para 5.000-10.000 NCN/centímetro cúbico na estação seca. As gotas de nuvens sofrem uma redução de tamanho de 18 a 25 micrômetros para 5 a 10 micrômetros, diminuindo a eficiência do processo de precipitação e suprimindo a formação de nuvens. A concentração de ozônio, um gás importante para a saúde da floresta amazônica passa de cerca de 12 partes por bilhão em volume (ppb) (concentração típica ao meio do dia na estação chuvosa) para valores em regiões fortemente impactadas por queimadas de até 100 ppb, nível que pode ser fitotóxico para a vegetação. O balanço de radiação é fortemente afetado, com uma perda líquida de até 70 por cento da radiação fotossinteticamente ativa na superfície.