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In 2018, a truck-driver strike in Sao Paulo, Brazil, provided conditions for conducting a real-world experiment on the relationship between vehicle emissions, air quality, and public health. During the strike, no truck traffic, a 40–70% bus-traffic reduction, and a reduction in auto traffic was observed. The objective of this study is to evaluate the effects of vehicle-traffic reduction on the air quality and public health in Sao Paulo by taking advantage of the truck-driver strike. The corresponding analysis was based on the comparison of the air quality (NOx (nitrogen oxides), PM10 (particle matter of diameter less than 10 μm), and O3 (ozone) concentrations) during the strike and that registered on days having similar meteorological conditions. A relative-risk function was used to associate the decrease in the PM10 concentration during the strike with avoided mortality. The results demonstrated that, on workdays, the reduction in vehicle traffic during the strike was responsible for a 29.4%–40.9% improvement in NOx air quality and 19.2%–21.4% in PM10 concentration. The reduction in the PM10 concentration resulted in the prevention of between six and eight deaths during the strike, which implies between 321 and 442 avoided deaths in a year. In terms of the O3 concentration, no difference was identified between strike days and the comparative ones. An analysis of different sites of the city revealed that the greatest air-quality improvement was observed near an arterial road and near a bus terminal. Air-quality improvement was also detected in a park that was distant from the main roads. The results of the study provide evidence for supporting cleaner transportation investments and traffic restriction policies.

A large part of the population and the economic activities of South America are located in eastern regions of the continent, where extreme climate events are a recurrent phenomenon. This study identifies and characterizes the dry and wet climate periods at domain-scale occurring over the eastern South America (ESA) during 1980&ndash, 2018 through the multi-scalar Standardized Precipitation&ndash, Evapotranspiration Index (SPEI). For this study, the spatial extent of ESA was defined according to a Lagrangian approach for moisture analysis. It consists of the major continental sink of the moisture transported from the South Atlantic Ocean throughout the year, comprising the Amazonia, central Brazil, and the southeastern continental areas. The SPEI for 1, 3, 6, and 12 months of accumulation was calculated using monthly precipitation and potential evapotranspiration time series averaged on ESA. The analysis of the climate periods followed two different approaches: classification of the monthly SPEI values as mild, moderate, severe, and extreme, the computation of the events and their respective parameters (duration, severity, intensity, and peak). The results indicate that wet periods prevailed in the 1990s and 2000s, while dry conditions predominated in the 2010s, when the longest and more severe dry events have been identified at the four scales.

Extraterrestrial spectral response calibration of a multi-filter rotating shadow band radiometer (MFRSR) under pristine Amazonian Forest atmosphere conditions was performed using the Langley plot method. The MFRSR is installed in central Amazonia as part of a long-term monitoring site, which was used in the context of the GoAmazon2014/5 experiment. It has been operating continuously since 2011 without regular extraterrestrial calibration, preventing its application to accurate monitoring of aerosol particles. Once calibrated, the MFRSR measurements were applied to retrieve aerosol particle columnar optical properties, specifically aerosol optical depth (AODλ) and Ångström exponent (AE), which were evaluated against retrievals from a collocated Cimel Sun photometer belonging to the AErosol RObotic NETwork (AERONET). Results obtained revealed that pristine Amazonian conditions are able to provide MFRSR extraterrestrial spectral response with relative uncertainty lower than 1.0 % in visible channels. The worst estimate (air mass =1) for absolute uncertainty in AODλ retrieval varied from ≈0.02 to ≈0.03, depending on the assumption regarding uncertainty for MFRSR direct normal irradiance measured at the surface. The obtained root mean square error (RMSE ≈0.025) from the evaluation of MFRSR retrievals against AERONET AODλ was, in general, lower than estimated MFRSR AODλ uncertainty, and close to the uncertainty of AERONET field Sun photometers (≈0.02).

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

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 PM2.5in 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.

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.

The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial–temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km × 100 km) networks: 1) a 1-yr (April 2011–April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized.

The Observations and Modeling of the Green Ocean Amazon 2014–2015 (GoAmazon2014/5) experiment took place around the urban region of Manaus in central Amazonia across 2 years. The urban pollution plume was used to study the susceptibility of gases, aerosols, clouds, and rainfall to human activities in a tropical environment. Many aspects of air quality, weather, terrestrial ecosystems, and climate work differently in the tropics than in the more thoroughly studied temperate regions of Earth. GoAmazon2014/5, a cooperative project of Brazil, Germany, and the United States, employed an unparalleled suite of measurements at nine ground sites and on board two aircraft to investigate the flow of background air into Manaus, the emissions into the air over the city, and the advection of the pollution downwind of the city. Herein, to visualize this train of processes and its effects, observations aboard a low-flying aircraft are presented. Comparative measurements within and adjacent to the plume followed the emissions of biogenic volatile organic carbon compounds (BVOCs) from the tropical forest, their transformations by the atmospheric oxidant cycle, alterations of this cycle by the influence of the pollutants, transformations of the chemical products into aerosol particles, the relationship of these particles to cloud condensation nuclei (CCN) activity, and the differences in cloud properties and rainfall for background compared to polluted conditions. The observations of the GoAmazon2014/5 experiment illustrate how the hydrologic cycle, radiation balance, and carbon recycling may be affected by present-day as well as future economic development and pollution over the Amazonian tropical forest.

The intercontinental transport of aerosols from the Sahara desert plays a significant role in nutrient cycles in the Amazon rainforest, since it carries many types of minerals to these otherwise low-fertility lands. Iron is one of the micronutrients essential for plant growth, and its long-range transport might be an important source for the iron-limited Amazon rainforest. This study assesses the bioavailability of iron Fe(II) and Fe(III) in the particulate matter over the Amazon forest, which was transported from the Sahara desert (for the sake of our discussion, this term also includes the Sahel region). The sampling campaign was carried out above and below the forest canopy at the ATTO site (Amazon Tall Tower Observatory), a near-pristine area in the central Amazon Basin, from March to April 2015. Measurements reached peak concentrations for soluble Fe(III) (48 ng m−3), Fe(II) (16 ng m−3), Na (470 ng m−3), Ca (194 ng m−3), K (65 ng m−3), and Mg (89 ng m−3) during a time period of dust transport from the Sahara, as confirmed by ground-based and satellite remote sensing data and air mass backward trajectories. Dust sampled above the Amazon canopy included primary biological aerosols and other coarse particles up to 12 µm in diameter. Atmospheric transport of weathered Saharan dust, followed by surface deposition, resulted in substantial iron bioavailability across the rainforest canopy. The seasonal deposition of dust, rich in soluble iron, and other minerals is likely to assist both bacteria and fungi within the topsoil and on canopy surfaces, and especially benefit highly bioabsorbent species. In this scenario, Saharan dust can provide essential macronutrients and micronutrients to plant roots, and also directly to plant leaves. The influence of this input on the ecology of the forest canopy and topsoil is discussed, and we argue that this influence would likely be different from that of nutrients from the weathered Amazon bedrock, which otherwise provides the main source of soluble mineral nutrients.

CNPq fellowship program CAPES project on the program Science without Frontiers SAVERNET project FAPESP Research Program on Global Climate Change Cirrus clouds cover a large fraction of tropical latitudes and play an important role in Earth's radiation budget. Their optical properties, altitude, vertical and horizontal coverage control their radiative forcing, and hence detailed cirrus measurements at different geographical locations are of utmost importance. Studies reporting cirrus properties over tropical rain forests like the Amazon, however, are scarce. Studies with satellite profilers do not give information on the diurnal cycle, and the satellite imagers do not report on the cloud vertical structure. At the same time, ground-based lidar studies are restricted to a few case studies. In this paper, we derive the first comprehensive statistics of optical and geometrical properties of upper-tropospheric cirrus clouds in Amazonia. We used 1 year (July 2011 to June 2012) of ground-based lidar atmospheric observations north of Manaus, Brazil. This dataset was processed by an automatic cloud detection and optical properties retrieval algorithm. Uppertropospheric cirrus clouds were observed more frequently than reported previously for tropical regions. The frequency of occurrence was found to be as high as 88% during the wet season and not lower than 50% during the dry season. The diurnal cycle shows a minimum around local noon and maximum during late afternoon, associated with the diurnal cycle of precipitation. The mean values of cirrus cloud top and base heights, cloud thickness, and cloud optical depth were 14.3 +/- 1.9 (SD) km, 12.9 +/- 2.2 km, 1.4 +/- 1.1 km, and 0.25 +/- 0.46, respectively. Cirrus clouds were found at tem-peratures down to 90 degrees C. Frequently cirrus were observed within the tropical tropopause layer (TTL), which are likely associated to slow mesoscale uplifting or to the remnants of overshooting convection. The vertical distribution was not uniform, and thin and subvisible cirrus occurred more frequently closer to the tropopause. The mean lidar ratio was 23.3 +/- 8.0 sr. However, for subvisible cirrus clouds a bimodal distribution with a secondary peak at about 44 sr was found suggesting a mixed composition. A dependence of the lidar ratio with cloud temperature (altitude) was not found, indicating that the clouds are vertically well mixed. The frequency of occurrence of cirrus clouds classified as subvisible (tau < 0 : 03) were 41.6 %, whilst 37.8% were thin cirrus (0 : 03 < tau < 0 : 3) and 20.5% opaque cirrus (tau > 0 : 3). Hence, in central Amazonia not only a high frequency of cirrus clouds occurs, but also a large fraction of subvisible cirrus clouds. This high frequency of subvisible cirrus clouds may contaminate aerosol optical depth measured by sun photometers and satellite sensors to an unknown extent. Univ Sao Paulo, Inst Phys, Dept Appl Phys, Sao Paulo, SP, Brazil Meteorol Inst Cuba, Atmospher Opt Grp Camaguey, Camaguey, Cuba Univ Magallanes, Atmospher Res Lab, Punta Arenas, Chile Leibniz Inst Tropospher Res TROPOS, Leipzig, Germany Univ Fed Sao Paulo, Dept Environm Sci, Diadema, SP, Brazil Univ Fed Sao Paulo, Dept Environm Sci, Diadema, SP, Brazil CAPES: A016_2013 FAPESP Research Program on Global Climate Change: 2008/58100-1 FAPESP Research Program on Global Climate Change: 2009/15235-8 FAPESP Research Program on Global Climate Change: 2012/16100-1 FAPESP Research Program on Global Climate Change: 2013/50510-5 FAPESP Research Program on Global Climate Change: 2013/05014-0 Web of Science

The intercontinental transport of aerosols from the Sahara is likely to play a significant role in nutrient cycles in the Amazon rainforest, since it carries many types of minerals to these otherwise low-fertility lands. Iron is one of the micronutrients essential for plant growth, and the Amazon rainforest is iron-limited. The main aim of this study was to assess the input and potential impact of iron bioavailability from Saharan dust, namely, the soluble fraction Fe(II)/Fe(III). Seven other soluble elements that are also essential for plants were measured. Dust particles entrained in the air were collected and analyzed, but not dust deposited in rainfall as atmospheric washout. The sampling campaign was carried out at the ATTO site (Amazon Tall Tower Observatory), from March to April 2015, and samplers were placed both above and below the canopy. Mineral dust aerosol at ATTO showed peak concentrations for Fe(III) (47.6 ng m−3), Fe(II) (16.2 ng m−3), Na (470 ng m−3), Ca (194 ng m−3), K (64.7 ng m−3), and Mg (88.8 ng m−3) during the presence of dust transported from the Sahara, as determined by remote ground-based and satellite sensing data and backward trajectories. Atmospheric transport of weathered Saharan dust, followed by surface deposition, results in substantial iron bioavailability across the rainforest canopy. The seasonal deposition of dust rich in soluble iron and other minerals is likely to affect both bacteria and fungi within the topsoil and on canopy surfaces, and especially benefit highly bioabsorbent epiphytes, such as lichens. In this scenario, Saharan dust can provide essential macronutrients and micronutrients to plant roots, and also directly to plant leaves. The influence on the ecology of the forest canopy and topsoil would likely be different from that of nutrients from the weathered Amazon bedrock, which provides the main source of soluble mineral nutrients.

A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.

Made available in DSpace on 2018-12-11T17:02:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-08-01 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 (OPESR) 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). OPESR 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 1100 cm-1 and 1600 cm-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. Environmental Engineering Department Federal University of Parana Division of Chemistry and Environmental Science School of Science and the Environment Manchester Metropolitan University LAVIE - Institute of Chemistry São Paulo State University - UNESP Chemical Engineering Department Federal University of Parana Vehicle Emissions Laboratory Institute of Technology for Development (LACTEC) Analytical Chemistry Department Institute of Chemistry São Paulo State University - UNESP Laboratory of Experimental Air Pollution Department of Pathology School of Medicine University of São Paulo Department of Natural and Earth Sciences Federal University of São Paulo LAVIE - Institute of Chemistry São Paulo State University - UNESP Analytical Chemistry Department Institute of Chemistry São Paulo State University - UNESP