Development and validation of a GC Orbitrap-MS method for the analysis of phthalate esters (PAE) and bis(2-ethylhexyl)adipate (DEHA) in atmospheric particles and its application for screening PM2.5 from Curitiba, Brazil.

Phthalates or phthalic acid esters (PAE) and bis(2-ethylhexyl)adipate (DEHA) are ubiquitous chemicals often used as plasticisers and additives in many industrial products and are classified as both persistent organic pollutants (POPs) and new emerging pollutants (NEPs). Exposure to these chemicals, especially through inhalation, is linked to a wide range of negative health effects, including endocrine disruption. Air particulate matter (PM) with an aerodynamic diameter ≤ 2.5 µm can be enriched with PAEs and DEHA and if inhaled can cause multi-system human toxicity. Therefore, proper monitoring of PAEs and DEHA in PM is required to assess human exposure to these pollutants. In this work, we developed and validated a new and sensitive gas-chromatography high-resolution mass spectrometry (GC-HRMS) method for targeted analysis of PAEs including dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), benzyl butyl phthalate (BBP), bis(2-ethylhexyl)adipate (DEHA), bis(2-ethylhexyl)phthalate (DEHP), di-n-octyl phthalate (DOP), in PM. Analytical aspects including sample preparation steps and GC-HRMS parameters, e.g., quadrupole isolation window, to enhance method sensitivity have been assessed. The estimated limit of detection (LODs) of target PAEs and DEHA ranged from 5.5 to 17 pg µL-1, allowing their trace-level detection in PM. Extraction efficiencies of 78-101% were obtained for the target compounds. Low DMP and DEP extraction efficiencies from the spiked filter substrates indicated that significant losses of higher volatility PAEs can occur during the sample collection when filter-based techniques are used. This work is the first targeted method based on GC-Orbitrap MS for PAEs and DEHA in environmental samples. The validated method was successfully applied for the targeted analysis of PAEs and DEHA in PM2.5 samples from the eighth most populous city in Brazil, Curitiba. This work is the first to report DBP, DEHA, DEHP, and DOP in urban PM from Brazil. The observed concentrations of PAEs (up to 29 ng m-3) in PM2.5 from Curitiba may not represent the extent of pollution by these toxic compounds since the analysed samples were collected during a COVID-19 restriction when anthropogenic activities were reduced.

BTEX profile and health risk at the largest bulk port in Latin America, Paranaguá Port.

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.

The new WHO air quality guidelines for PM2.5: predicament for small/medium cities.

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.

Mudanças na sazonalidade de polens de Poaceae em Curitiba / Seasonal changes in Poaceae pollen counts in Curitiba, south of Brazil

Introdução: Doenças alérgicas afetam de 10 a 30% da população mundial, e polens são frequentes desencadeantes. A polinose é doença decorrente da sensibilização ao pólen e é a forma sazonal da rinite alérgica e/ou asma mediada pela imunoglobulina E (IgE). A família Poaceae tem o maior número de gêneros de plantas que contribuem para a polinose, pois liberam alta quantidade de pólen na atmosfera e são largamente distribuídas. Objetivo: O presente trabalho quantificou a concentração de polens da família Poaceae na atmosfera de Curitiba e comparou a curva de distribuição de polens com os dados das décadas de 1980 e 90. Também classificou a concentração diária de pólen de gramíneas segundo a National Allergy Bureau (NAB). Método: O equipamento de amostragem foi o captador volumétrico Hirst, instalado a uma altura de aproximadamente 25 metros. Resultados: O pico de concentração diária de pólen total ocorreu no começo do mês de agosto, correspondendo a 302 grãos/m3. O mês de agosto também concentrou oito dos maiores picos diários de pólen total, sendo sete deles superiores a 200 grãos/m3. Foi encontrado pólen Poaceae ao longo de todo o ano e o maior pico de concentração foi de 27 grãos/m3 em agosto e setembro. Nas décadas de 80 e 90, os picos de polens foram no mês de novembro e período de polinização entre outubro e abril. Isso não foi observado no ano de 2018, uma vez que a época de polinização das gramíneas se adiantou, com início em agosto, e o pico de concentração foi em de agosto e setembro. Conclusão: Este estudo mostra que houve mudança na estação polínica. Os dois picos de dispersão de polens de Poaceae se repetem ao longo dos anos, mas têm sido encontrados em outros meses. Pacientes com alergia a polens podem ter sintomas por exposição fora das estações determinadas anteriormente.

Background: Allergic diseases affect 10% to 30% of the world population, with pollen as a major trigger. Pollinosis results from sensitization to pollen and is the seasonal form of allergic rhinitis and/or immunoglobulin E (IgE)-mediated allergic asthma. The Poaceae family is distributed worldwide and has the largest number of plant genera contributing to pollinosis, as they release large amounts of pollen into the atmosphere. Objective: To quantify pollen grains from the Poaceae family in the atmosphere of Curitiba, compare the pollen distribution curve with data from the 1980s and 1990s, and classify the daily concentration of grass pollen according to the National Allergy Bureau (NAB). Method: A Hirst-type volumetric sampler was placed at approximately 25 meters from the ground. Results: The peak of daily total pollen concentration occurred in early August, corresponding to 302 grains/m3. August also had 8 of the highest daily total pollen concentrations, 7 of which were greater than 200 grains/m3. Poaceae pollen was found throughout the year, with the highest concentration peak of 27 grains/m3 in August and September. In the 1980s and 1990s, the pollen peaks occurred in November and the pollen season occurred between October and April. In 2018, however, the pollen season started earlier, in August, and the pollen peaks occurred in August and September. Conclusion: This study shows a change in the grass pollen season. Although the 2 peaks of Poaceae pollen dispersion have repeated over the years, grass pollen is currently observed in other months of the year. Patients with pollen allergy may experience symptoms from allergen exposure outside the previously established grass pollen seasons.

Relative contributions of fossil fuel and biomass burning sources to black carbon aerosol on the Southern Atlantic Ocean Coast and King George Island (Antarctic Peninsula).

Carbonaceous aerosols can affect climate, especially particles containing black carbon (BC). BC originated from the incomplete combustion of fossil fuel and biomass, which can heat the atmosphere and increase ice melting, but little is known about BC sources to Antarctica. We quantified the contribution of distant origin (biomass burning) and local emissions (fossil fuel) to atmospheric BC concentration in the King George Island (Antarctic Peninsula) and the Southern Ocean. We examine the BC concentrations using a multi-wavelength Aethalometer AE-33 and AE-42 aboard the Brazilian Oceanographic Research Ship Almirante Maximiano. The results indicate that the region is influenced by local sources and air masses coming from surrounding continents. Fossil fuel combustion was the major source of carbonaceous aerosols in the region, whereas the total average concentration was 41.8 ± 22.8 ng m-3. The findings indicate a contribution of biomass burning coming from low and mid-latitudes of South America over the Antarctic Peninsula and the Southern Ocean around 62ºS latitude. We demonstrated that fossil fuel is the main contributor to atmospheric BC concentration for the Austral summer and autumn. Scientific stations, local tourism, and traffic are possible local BC sources. Our work invokes the urgency of questionable sustainability issues about Antarctica exploration.

Elemental Composition of PM2.5 and PM10 and Health Risks Assessment in the Industrial Districts of Chelyabinsk, South Ural Region, Russia.

Air pollution impacts all populations globally, indiscriminately and has site-specific variation and characteristics. Airborne particulate matter (PM) levels were monitored in a typical industrial Russian city, Chelyabinsk in three destinations, one characterized by high traffic volumes and two by industrial zone emissions. The mass concentration and trace metal content of PM2.5 and PM10 were obtained from samples collected during four distinct seasons of 2020. The mean 24-h PM10 ranged between 6 and 64 µg/m3. 24-h PM2.5 levels were reported from 5 to 56 µg/m3. About half of the 24-h PM10 and most of the PM2.5 values in Chelyabinsk were higher than the WHO recommendations. The mean PM2.5/PM10 ratio was measured at 0.85, indicative of anthropogenic input. To evaluate the Al, Fe, As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn concentration in PM2.5 and PM10, inductively coupled plasma mass spectrometry (ICP-MS) was used. Fe (337-732 ng/m3) was the most abundant component in PM2.5 and PM10 samples while Zn (77-206 ng/m3), Mn (10-96 ng/m3), and Pb (11-41 ng/m3) had the highest concentrations among trace elements. Total non-carcinogenic risks for children were found higher than 1, indicating possible health hazards. This study also presents that the carcinogenic risk for As, Cr, Co, Cd, Ni, and Pb were observed higher than the acceptable limit (1 × 10-6).

Influence of seasonality on the aerosol microbiome of the Amazon rainforest.

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.

Dynamic model to predict the association between air quality, COVID-19 cases, and level of lockdown.

Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O3, NO2, NO, PM2.5, and PM10, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error âˆ¼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution.

Photochemical reactions on aerosols at West Antarctica: A molecular case-study of nitrate formation among sea salt aerosols.

Environmental implications of climate change are complex and exhibit regional variations both within and between the polar regions. The increase of solar UV radiation flux over Antarctica due to stratospheric ozone depletion creates the optimal conditions for photochemical reactions on the snow. Modeling, laboratory, and indirect field studies suggest that snowpack process release gases to the atmosphere that can react on sea salt particles in remote regions such as Antarctica, modifying aerosol composition and physical properties of aerosols. Here, we present evidence of photochemical processing in West Antarctica aerosols using microscopic and chemical speciation of individual atmospheric particles. Individual aerosol particles collected at the Brazilian module Criosfera 1 were analyzed by scanning transmission X-ray microscopy with near edge X-ray absorption fine structure spectroscopy (STXM/NEXAFS) combined with computer-controlled scanning electron microscopy (CCSEM) with energy-dispersive X-ray (EDX) microanalysis. The displacement of chlorine relative to sodium was observed over most of the sea salt particles. Particles with a chemical composition consistent with NaCl-NO3 contributed up to 30% of atmospheric particles investigated. Overall, this study provides evidence that the snowpack and particulate nitrate photolysis should be considered in dynamic partition equilibrium in the troposphere. These findings may assist in reducing modeling uncertainties and present new insights into the aerosol chemical composition in the polar environment.

Atomic Absorption Spectrometry Methods to Access the Metal Solubility of Aerosols in Artificial Lung Fluid.

Recent studies to quantify the health risks that fine particulate matter with an aerodynamic less than 2.5 µm (PM2.5) pose use in vitro approaches. One of these approaches is to incubate PM2.5 in artificial lysosomal fluid for a given period at body temperature. These body fluids used have a high ionic strength and as such can be challenging samples to analyze with atomic spectroscopy techniques. As PM2.5 is a primary health hazard because it is tiny enough to penetrate deep into the lungs and could, in addition, dissolve in the lung fluid it is important to quantify elements of toxic and/or carcinogenic concerns, reliably and accurately. Sophisticated instrumentation and expensive pre-treatment of challenging samples are not always available, especially in developing countries. To evaluate the applicability of graphite furnace atomic absorption spectrometry (GFAAS) without Zeeman correction capability to detect trace quantities of heavy metals leached from PM2.5 on to artificial lung fluid, univariate and multivariate approaches have been used for optimization purposes. The limits of quantification, LOQ, obtained by the optimized method were: 2 µg L-1 (Cu), 3 µg L-1 (Cr), 1 µg L-1 (Mn), and 10 µg L-1 (Pb). The addition/recovery experiments had a mean accuracy of: (Cu) 99 ± 7%; 110 ± 8% (Cr); 95 ± 9% (Mn), and 96 ± 11% (Pb). The average soluble fractions of PM2.5 incubated in artificial lysosomal fluid (ALF) for 1 h were: 1.2 ± 0.01 ng m-3 Cu, 0.4 ± 0.01 ng m-3 Cr, 0.6 ± 0.01 ng m-3 Mn, and 4.8 ± 0.03 ng m-3 Pb. Using historical elemental averages of PM2.5 in Curitiba (Cu 3.3 ng m-3, Cr 2.1 ng m-3, Mn 6.1 ng m-3, Pb 21 ng m-3), the percentage bioaccessibility were determined to be Cu 38%, Cr 20%, Mn 10%, and Pb 23%. The elemental values of the atmospheric soluble fraction of Cu, Cr, and Mn were below the inhalation risk concentrations. However, for Pb, the atmospheric soluble fraction exceeded the inhalation unit risk of 0.012 ng m-3. This robust and straightforward GF AAS method is pivotal for low and middle-income countries were most air pollution adverse effects occur and established lower-cost technologies are likely unavailable.

A scoping study of component-specific toxicity of mercury in urban road dusts from three international locations.

This scoping study presents an investigation of the total and bioaccessible mercury concentrations in road dust (RD) from three international urban sites, where a one-off sampling campaign was conducted at each. This was done to address the hypothesis that the matrix in which mercury is found influences its ability to become accessible to the body once inhaled. For that purpose, the samples were analysed for total and pulmonary bioaccessible mercury and the data compared to the chemical structure of individual particles by SEM. The results obtained from this study suggest that a high mercury content does not necessarily equate to high bioaccessibility, a phenomenon which could be ascribed to the chemical character of the individual particles. It was found that the Manchester samples contained more pulmonary soluble mercury species (as determined by elemental associations of Hg and Cl) in comparison to the other two samples, Curitiba, Brazil, and Johannesburg, South Africa. This finding ultimately underlines the necessity to conduct a site-specific in-depth analysis of RD, to determine the concentration, chemical structure and molecular speciation of the materials within the complex matrix of RD. Therefore, rather than simply assuming that higher bulk concentrations equate to more significant potential human health concerns, the leaching potential of the metal/element in its specific form (for example as a mineral) should be ascertained. The importance of individual particle behaviour in the determination of human health risk is therefore highlighted.

The influence that different urban development models has on PM2.5 elemental and bioaccessible profiles.

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.

Radical Formation by Fine Particulate Matter Associated with Highly Oxygenated Molecules.

Highly oxygenated molecules (HOMs) play an important role in the formation and evolution of secondary organic aerosols (SOA). However, the abundance of HOMs in different environments and their relation to the oxidative potential of fine particulate matter (PM) are largely unknown. Here, we investigated the relative HOM abundance and radical yield of laboratory-generated SOA and fine PM in ambient air ranging from remote forest areas to highly polluted megacities. By electron paramagnetic resonance and mass spectrometric investigations, we found that the relative abundance of HOMs, especially the dimeric and low-volatility types, in ambient fine PM was positively correlated with the formation of radicals in aqueous PM extracts. SOA from photooxidation of isoprene, ozonolysis of α- and ß-pinene, and fine PM from tropical (central Amazon) and boreal (Hyytiälä, Finland) forests exhibited a higher HOM abundance and radical yield than SOA from photooxidation of naphthalene and fine PM from urban sites (Beijing, Guangzhou, Mainz, Shanghai, and Xi'an), confirming that HOMs are important constituents of biogenic SOA to generate radicals. Our study provides new insights into the chemical relationship of HOM abundance, composition, and sources with the yield of radicals by laboratory and ambient aerosols, enabling better quantification of the component-specific contribution of source- or site-specific fine PM to its climate and health effects.

Uncovering prokaryotic biodiversity within aerosols of the pristine Amazon forest.

Biological aerosols (bioaerosol) are atmospheric particles that act as a dispersion unit of living organisms across the globe thereby affecting the biogeographic distribution of organisms. Despite their importance, there is virtually no knowledge about bioaerosols emitted by pristine forests. Here we provide the very first survey of the prokaryotic community of a bioaerosol collected inside pristine Amazon forest at 2 m above ground. Total atmospheric particles were collected at the Amazon Tall Tower Observatory, subjected to metagenomic DNA extraction and the prokaryotic diversity was determined by 16S rRNA gene amplicon sequencing. A total of 271,577 reads of 250 bp of the 16S rRNA gene amplicon were obtained. Only 27% of the reads could be classified using the 16S SILVA database. Most belonged to Proteobacteria, Actinobacteria and Firmicutes which is in good agreement with other bioaerosol studies. Further inspection of the reads using Blast searches and the 18S SILVA database revealed that most of the dataset was composed of Fungi sequences. The identified microbes suggest that the atmosphere may act as an important gateway to interchange bacteria between plants, soil and water ecosystems.

Observations of particulate matter, NO2, SO2, O3, H2S and selected VOCs at a semi-urban environment in the Amazon region.

This research aims to assess air quality in a transitional location between city and forest in the Amazon region. Located downwind of the Manaus metropolitan region, this study is part of the large-scale experiment GoAmazon2014/5. Based on their pollutant potential, inhalable particulate matter (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), hydrogen sulfide (H2S), benzene, toluene, ethylbenzene and meta-, orto-, para-xylene (BTEX) were selected for analysis. Sampling took place during the wet season (March-April 2014) and dry season (August-October 2014). The number of forest fires in the surroundings was higher during the dry wet season. Results show significant increase during the dry season in mass concentration (wet: <0.01-10 µg m-3; dry: 9.8-69 µg m-3), NH4+ soluble content (wet: 13-125 µg m-3; dry: 86-323 µg m-3) and K+ soluble content (wet: 11-168 µg m-3; dry 60-356 µg m-3) of the PM2.5, and O3 levels (wet: 1.4-14 µg m-3; dry: 1.0-40 µg m-3), indicating influence of biomass burning emissions. BTEX concentrations were low in both periods, but also increased during the dry season. A weak correlation in the time series of the organic and inorganic gaseous pollutants indicates a combination of different sources in both seasons and NO2 results suggest a spatial heterogeneity in gaseous pollutants levels beyond initial expectations.

Polycyclic Aromatic Hydrocarbons (PAHs) and nitrated analogs associated to particulate matter emission from a Euro V-SCR engine fuelled with diesel/biodiesel blends.

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.

Assessing the impact of PM2.5 on respiratory disease using artificial neural networks.

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 µg 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 (p < .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.

Impact of the biomass burning on methane variability during dry years in the Amazon measured from an aircraft and the AIRS sensor.

The present study examines the spatiotemporal variability and interrelations of the atmospheric methane (CH4), carbon monoxide (CO) and biomass burning (BB) outbreaks retrieved from satellite data over the Amazon region during the 2003-2012 period. In the climatological context, we found consistent seasonal cycles of BB outbreaks and CO in the Amazon, both variables showing a peak during the dry season. The dominant CO variability mode features the largest positive loadings in the southern Amazon, and describes the interannual CO variations related to BB outbreaks along the deforestation arc during the dry season. In line with CO variability and BB outbreaks, the results show strong correspondence with the spatiotemporal variability of CH4 in the southern Amazon during years of intense drought. Indeed, the areas with the largest positive CH4 anomalies in southern Amazon overlap the areas with high BB outbreaks and positive CO anomalies. The analyses also showed that high (low) BB outbreaks in the southern Amazon occur during dry (wet) years. In consequence, the interannual climate variability modulates the BB outbreaks in the southern Amazon, which in turn have considerable impacts on CO and CH4 interannual variability in the region. Therefore, the BB outbreaks might play a major role in modulating the CH4 and CO variations, at least in the southern Amazon. This study also provides a comparison between the estimate of satellite and aircraft measurements for the CH4 over the southern Amazon, which indicates relatively small differences from the aircraft measurements in the lower troposphere, with errors ranging from 0.18% to 1.76%.

Health implications of atmospheric aerosols from asbestos-bearing road pavements traditionally used in Southern Brazil.

Serpentine and amphibole asbestos occur naturally in certain geologic settings worldwide, most commonly in association with ultramafic rocks, along associated faults. Ultramafic rocks have been used in Piên County, Southern Brazil for decades for the purpose of road paving in rural and urban areas, but without the awareness of their adverse environmental and health impact. The aim of this study was the chemical characterization of aerosols re-suspended in two rural roads of Piên, paved with ultramafic rocks and to estimate the pulmonary deposition of asbestos aerosols. Bulk aerosol samples were analyzed by means of X-ray fluorescence spectrometry and X-ray diffraction analysis, in order to characterize elemental composition and crystallinity. Single-particle compositions of aerosols were analyzed by computer-controlled electron-probe microanalysis, indicating the presence of a few percentages of serpentine and amphibole. Given the chemical composition and size distribution of aerosol particles, the deposition efficiency of chrysotile, a sub-group of serpentine, in two principal segments of the human respiratory system was estimated using a lung deposition model. As an important finding, almost half of the inhaled particles were calculated to be deposited in the respiratory system. Asbestos depositions were significant (∼25 %) in the lower airways, even though the selected breathing conditions (rest situation, nose breathing) implied the lowest rate of respiratory deposition. Considering the fraction of inhalable suspended chrysotile near local roads, and the long-term exposure of humans to these aerosols, chrysotile may represent a hazard, regarding more frequent development of lung cancer in the population of the exposed region.

Influence on the oxidative potential of a heavy-duty engine particle emission due to selective catalytic reduction system and biodiesel blend.

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.