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Esse trabalho tem como objetivo analisar ilhas de Calor e Frio Urbano e sua relação com os padrões da paisagem urbana no Município de Curitiba e suas mudanças ao longo dos últimos 30 anos, durante a estação do inverno dos anos de 1989 e 2019, através do satélite Landsat. Utilizou-se os dados obtidos pelo satélite Landsat 5 e 8, processados no software Qgis, identificados pela órbita/ponto 220/078 em dois anos diferentes no período do inverno. Para a estimativa da Temperatura da Superfície Terrestre (TST) foi utilizada a banda 6, para o Landsat 5 e banda 10 para o Landsat 8, a qual foi convertida para temperatura de brilho. Para a avaliação da cobertura do solo foi utilizada a classificação feita pelo Projeto Mapbiomas. Após a transformação da emissividade em temperatura de superfície terrestre, esses valores foram convertidos em graus Celsius. O mapa de uso e ocupação do solo apresenta uma redução de áreas de lavouras e um aumento nas áreas urbanizadas. O município de Curitiba possui diversas áreas verdes dentro da área urbana que gerou pequenas ilhas de frio em relação a áreas onde não havia presença de áreas verdes.

O avanço da pandemia provocada pela COVID-19, além de causar danos à saúde humana, também apresentou efeitos indiretos na qualidade do ar, apresentando melhorias significativas. A relação entre a transmissibilidade do vírus SARS-Cov-2 e a poluição do ar suscita a preocupação em estudar o impacto das medidas de proteção contra o avanço da doença na qualidade do ar. As coletas de material particulado (MP) foram realizadas em abril de 2020, período em que foram observadas medidas de restrição à circulação de veículos e sua relaxação, utilizando amostradores tipo ciclone de baixo volume para as frações MP1,0 e MP2,5. A quantificação do Black Carbon foi realizada por meio do reflectômetro (EEL 43M). As medidas adotadas para combater a COVID-19, por reduzirem fontes de emissão, contribuíram diretamente para a melhoria da qualidade do ar, resultando em uma diminuição na concentração de todos os analitos estudados neste trabalho. Houve uma variação na concentração de MP1,0 e MP2,5 de 31,5% e 27,4% respectivamente em MHL e 40,1% e 34,2% em TOU. As medidas adotadas para conter o avanço da COVID-19 contribuíram diretamente para a melhora na qualidade do ar.

Low-cost sensors have the potential to significantly reduce costs compared to reference devices. The problem, however, is that measurements from low-cost sensors can be unreliable when it comes to certifying water quality. This work investigates the possibility of using low-cost sensors to monitor water quality parameters and automate the monitoring process through the concept of the Internet of Things (IoT). The sensors evaluated are turbidity, temperature, dissolved oxygen and hydrogen potential. The evaluation of the sensors was performed both in a controlled environment with standard solutions and in a real environment. The results show that the sensors provide readings that are close to reference values when tested in a controlled environment, but some challenges remain when tested in the real world.

Assessing the contribution of multiple air pollutant sources is essential to effective emission control policy design, towards which numerical air quality modelling can provide fundamental guidance. In Piracicaba, an industrial municipality in Sao Paulo, Brazil, a straightforward control strategy focusing on local direct and precursor emission reduction has been proposed, as part of a state-wide program following the update of state Air Quality Standards in 2013. The WRF-SMOKE-CMAQ modelling system was used to investigate the effectiveness of the control scenario proposed in achieving expected air quality levels. Meteorological fields were modelled using the WRF model, for two 7-day periods (January 11–17 in summer and July 26 to Aug 01 in winter) during 2015. Emission scenarios were prepared using the SMOKE pre-processor, by combining a local industrial emission inventory with global emissions from the EDGAR HTAP_V2 database, for input in CMAQ modelling system. EDGAR industrial PM emission rate was similar to local inventory rate: 14% and 22% overestimated in summer and winter, respectively, albeit poorly spatially distributed, hindering its applicability in local studies. A 20% reduction in PM emissions improves average PM ambient levels in up to 15.5%, but a 20% reduction in O3 precursors emissions hardly impacts average O3 concentration levels (

The concentration of ions, metals, and metalloids in hailstone samples was evaluated for the first time in South America. The samples were previously cleaned with ultrapure water to eliminate potential contaminants. The ions concentrations in the samples showed a general pattern according to the following sequence: Ca2+ > N O 3 - > K+ > CHOO− > Mg2+ > Cl− > S O 4 2 _ > Na+ > NH 4 + > F−. Regarding the metals and metalloids concentrations, the order was of Zn > Al > Fe > Mn > Sr > Ba > Cu > Ni > Cr > Pb > Co > V. Ca2+ was the most abundant and agricultural activity, one of the sources due to long-distance transport. Concentrations of K+ and Cl− may originate from fires that occur every year in the North and Center-West regions of Brazil. Local sources also contributed to the chemical composition, such as soil resuspension contributing mainly to the species and elements Al, Fe, Na+, K+, S O 4 2 _ , and F−. Besides that, the region is an agricultural area with unpaved roads and use of fertilizer; therefore, the species and elements NH 4 + , Mg2+, K+, Cl−, Cu, and Zn, were also associated with local sources, including emissions from vegetation. A possible vehicular contribution was also observed. Among the few existing studies, this is the first to evaluate the hailstones cleaning procedure's efficiency. The findings also support the previous studies' conclusion that the concentration of chemical species varies considerably according to the region of study's characteristics. This work contributes to improve the understanding of local and remote natural and anthropic emissions in this complex atmospheric phenomenon.

According to IPCC reports, global climate change is likely to be accompanied by a greater frequency, intensity, and duration of heat waves in urban areas. This is related to predicted and ongoing variation of atmospheric temperature and its association with the dynamical evolution of cities. Changes in the roughness pattern of the surface, wind intensity, soil available humidity and radiative properties compared to the natural surfaces characterize the formation of the Urban Heat Island (UHI). A dynamical downscaling of A2 and B1 SRES’s future scenarios from Intergovernmental Panel on Climate Change were performed for Londrina, a medium-size city of Southern Brazil, using the Weather Research and Forecasting model. The main objective of this study is to investigate the impact of these scenarios on the UHI formation and intensity based on different input data, and its role and influence in the rural area. For this, an evaluation of the model and a comparison with the scenarios were done to mitigate the current trends. The results show a tendency in the current situation in following the pessimistic A2 scenario. Also, a drier rural area for the sustainable projection (B1) is found which implicates in a higher temperature and wind patterns modification for both sites, urban and rural region. Both future projections have a direct influence on the UHI intensity and formation, yielding effects in the agriculture and affecting conditions on human comfort over the region.

Urban areas concentrate more than 50% of the world’s population and are highly impacted by human activities, mainly due to high population density, directly affecting the micro-climate. In this sense, green infrastructures (GIs) have been pointed out to be helpful in mitigating these effects in large urban areas, where most of the studies were conducted. Therefore, this study evaluates the impacts on meteorological variables in a medium-sized city through the Weather Research and Forecasting model by implementing urban classes of Local Climate Zones (LCZ). Five urban parks and an urban lake were identified and expanded in the inner model grid to analyze the effects of GIs on meteorological variables in the urban environment. Results show that the 10 m wind speed can present an improvement for all statistical indices due to the better vertical representation of urban structures in the central urban area by the LCZ urban classes. In addition, green areas contributed locally to reducing the urban heat island (UHI) effects, resulting in cooling rates around these infrastructures. Compared to the lake, the use of the urban LCZ classes has proven to be an effective way to improve the representation of meteorological variables by a mesoscale weather model. Regarding GIs, this practice performs environmental services capable of mitigating the effects of UHI, sustaining the importance of these systems in urban projects, even for medium-sized cities. Finally, these findings provide support for public decision-makers in creating Master Plans for medium-sized cities regarding the implementation of GIs.

Aerosols and primary biological aerosol particles (PBAPs) play an important role in regulating the global climate, but information summarizing the available knowledge is limited. Here, we present a systematic review of in situ studies performed in the last 35 years on aerosols–PBAPs in Brazil, with 212 studies encompassing 474 cases. The Amazon rainforest was the most studied biome, represented by 72% of cases, followed by the Atlantic Forest with 18%. Studies focusing the Amazon mostly investigated climate-related issues and aerosol physics, with less than 5% examining the biological identity of aerosols, whereas outside the Amazon, this number reached 16%. Whilst more than half of the cases within Amazon (55%) were held at seven sampling sites only, conclusions were mainly extrapolated to the entire biome. Contrarily, research beyond the Amazon has mostly addressed the temporal and biological characterisation of PBAPs, and not only is it scattered, but also scarce. Regarding sampling efforts, most cases (72%) had fewer than 100 days of sampling, and 60% of them spanned less than half a year of study. We argue that scientists should produce more detailed/complete assessments of aerosols–PBAPs in Brazil as a whole, particularly considering their biological identity, given their importance to global climate regulation.

The main objective of this study was to investigate the trends on average and extreme events in time series of daily precipitation from 1980 to 2010 in the Parana River basin, Brazil. The nonparametric Mann–Kendall test was applied to detect monotonic trend in the precipitation series. The occurrence of extreme values was analysed based on three generalized extreme values (GEV) models: Model 1 (stationary), Model 2 (non-stationary for location parameter), and Model 3 (non-stationary for location and scale parameters). The GEV parameters were estimated by the Generalized Maximum Likelihood method (GMLE) and for the non-stationary models, the parameters were estimated as linear functions of time. To choose the most suitable model, the maximum likelihood ratio test (D) was used. From the results observed at the monthly scale, it was possible to infer that the months with the highest probability of an extreme weather event occurrence are February (climates Aw and Cfa), July (Cfa and Cfb), and October (Aw, Cfa, and Cfb). Approximately 90% of the 1,112 stations presented no trend regarding the GEV parameters. The non-stationarity showed by other stations (Models 2 and 3) might be associated with several factors, such as the alteration of land use due to the north expansion of the agricultural border of the Parana River basin. (Less)

Most of the world’s population lives in rural areas or small to medium-sized cities (totalling 68% of the world population), all of which are impacted by distant air pollution sources. In Brazil, primary pollutant emissions have decreased in urban centres because of government actions, while secondary pollutants such as surface ozone (O3) increased. In addition, O3 and its precursors can be worsening air quality in areas already affected by biofuels production, especially ethanol. We provide almost 3 months of hourly data (June 7, 2019 to August 25, 2019) for concentrations of O3, CO2 and other priority pollutants from a mobile station positioned to distinguish among pollutant plumes (biomass burning, metropolitan area of São Paulo (MASP) and other cities). Although the concentrations of O3 and CO2 were highest in the plumes from biomass burning, the MASP accounted for up to 80% of the O3 concentration in communities over 200 km away.

In large cities, pollution can not only cause deaths and illnesses due to exposure of people to it, but it can also reduce visibility on days of high atmospheric stability and high emission of pollutants, which can even result in vehicular accidents. Ozone is an atmospheric oxidizing gas that forms in minimal amounts naturally. People's health can be affected by the ozone present in the air they breathe, even in low concentrations, which can worsen preexisting diseases and increase hospital admissions for respiratory diseases, especially in babies, after episodes of high levels of this pollutant. An increase in secondary peaks during the night of this atmospheric pollutant occurs in several parts of the world, but its formation depends on the local condition. In this sense, this work aims to study the regional atmospheric characteristics for the nocturnal ozone formation in the Metropolitan Area of Sao Paulo (MASP). For this, the Simple Photochemical Module (SPM) coupled to the BRAMS (Brazilian Developments of Regional Atmospheric Modeling System) will be used to simulate this condition for the urban region. The results showed that the secondary nocturnal maximum of ozone concentrations in MASP is related to vertical transport of this pollutant from higher levels of the atmosphere to the surface.

This study aims to assess the concentrations of size-fractioned particle mass (PM1.0, PM2.5, PM4.0, PM10) and number (PNC0.3, PNC0.5, PNC1.0, PNC2.5), bacteria, and fungi in a Materials Recycling Facility (MRF) in Brazil. The measurements were performed inside the waste processing shed (P1) and in the outdoor environment (P2) during working days in winter and spring of 2017, and summer of 2019. A total of 2,400 min of PM, 1,440 min of PNC, and 216 samples of bioaerosols were collected in the morning and afternoon. P1 has the strongest air contamination with mean values of 475.5 ± 563.7 µg m−3 for PM10, 58.6 ± 36.0 cm−3 for PNC0.3, 1,088.8 ± 825.2 colony-forming units per cubic meter (CFU m−3) for bacteria, and 2,738.3 ± 1,381.3 CFU m−3 for fungi. The indoor/outdoor ratios indicated the large influence of indoor sources due to the activities performed inside P1 that promote the generation and resuspension of pollutants. Gram-positive bacteria dominated with 58.6% of indoor samples. Overall, our results show a critical indoor air quality situation in a Brazilian MRF, which may cause several health risks for waste pickers. Finally, we call attention to the lack of occupational exposure limits for bioaerosols in industrial workplaces and mainly in MRFs.

Made available in DSpace on 2018-12-11T17:23:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-01-13 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS), in which different previous versions for weather, chemistry, and carbon cycle were unified in a single integrated modeling system software. This new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. The description of the main model features includes several examples illustrating the quality of the transport scheme for scalars, radiative fluxes on surface, and model simulation of rainfall systems over South America at different spatial resolutions using a scale aware convective parameterization. Additionally, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America, are shown. Atmospheric chemistry examples show the model performance in simulating near-surface carbon monoxide and ozone in the Amazon Basin and the megacity of Rio de Janeiro. For tracer transport and dispersion, the model capabilities to simulate the volcanic ash 3-D redistribution associated with the eruption of a Chilean volcano are demonstrated. The gain of computational efficiency is described in some detail. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near-surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding both its functionalities and skills are discussed. Finally, we highlight the relevant contribution of this work to building a South American community of model developers. Centro de Previsão de Tempo e Estudos Climáticos Instituto Nacional de Pesquisas Espaciais Divisão de Ciência da Computação Instituto Tecnológico de AeronáUtica Universidade Estadual Paulista (Unesp) Faculdade de Ciências Centro de Meteorologia de Bauru (IPMet) Departamento de Ciências Ambientais Universidade Federal de São Paulo Instituto de Astronomia Geofísica e Ciências Atmosféricas Universidade de São Paulo Departamento de Ciências Atmosféricas Universidade Federal de Campina Grande Embrapa Informática Agropecuária Instituto de Ciência e Tecnologia Universidade Federal de São Paulo Departamento de Ciências Atmosféricas e Climáticas Programa de Pós Graduação em Ciências Climáticas Universidade Federal Do Rio Grande Do Norte Centro de Ciências Do Sistema Terrestre Instituto Nacional de Pesquisas Espaciais Departamento de Geociências Universidade Federal de São João Del-Rei Laboratório Associado de Computação e Matemática Aplicada Instituto Nacional de Pesquisas Espaciais Instituto de Ciências Agrárias e Ambientais Mediterrânicas Universidade de Évora Centro Interdisciplinar de Desenvolvimento em Ambiente Gestão Aplicada e Espaço Universidade Lusófona de Humanidades e Tecnologia Campo Grande Faculdade de Meteorologia Universidade Federal de Pelotas Universidade Tecnológica Federal Do Paraná Universities Space Research Association Goddard Earth Sciences Technology and Research at the Global Modeling and Assimilation Office NASA Goddard Space Flight Center Universidade Estadual Paulista (Unesp) Faculdade de Ciências FAPESP: 2014/01563-1 FAPESP: 2014/01564-8 FAPESP: 2015/10206-0 CNPq: 306340/2011-9

Highlights • CA/CPB nanofibers have a filtration efficiency of 99.9% for aerosol (7-300 nm). • The Ergun’s porosity of the nanofibers is 98% and the permeability about 10-11 m². • CA/CPB nanofibers are biodegradable and sustainable novel air filters. • The nanofibers are able to retention environmental PM2.5, BC and also virus., The increase of the industrialization process brought the growth of pollutant emissions into the atmosphere. At the same time, the demand for advances in aerosol filtration is evolving towards more sustainable technologies. Electrospinning is gaining notoriety, once it enables to produce polymeric nanofibers with different additives and also the obtaining of small pore sizes and fiber diameters; desirable features for air filtration materials. Therefore, this work aims to evaluate the filtration performance of cellulose acetate (CA) nanofibers and cationic surfactant cetylpyridinium bromide (CPB) produced by electrospinning technique for retention of aerosol nanoparticles. The pressure drop and collection efficiency measurements of sodium chloride (NaCl) aerosol particles (diameters from 7 to 300 nm) were performed using Scanning Mobility Particle Sizer (SMPS). The average diameter of the electrospun nanofibers used was 239 nm, ranging from 113 to 398 nm. Experimental results indicated that the nanofibers showed good permeability (10-9 cm2) and high-efficiency filtration for aerosol nanoparticles (about 100%), which can include black carbon (BC) and the new coronavirus. The pressure drop was 1.8 kPa at 1.6 cm s-1, which is similar to reported for some high-efficiency nanofiber filters. In addition, it also retains BC particles present in air, which was about 90 % for 375 nm and about 60% for the 880 nm wavelength. Finally, this research provided information for future designs of indoor air filters and filter media for facial masks with renewable, non-toxic biodegradable, and potential antibacterial characteristics.

Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.

Hailstorms cause great damage to plantations, kill animals and cause great damage to the population. The southern region of Brazil suffers from the damages caused by hailstorms each year, with the triple border of Parana, Santa Catarina, and Argentina being the region with the highest incidence of this event. With averages above 2.60 days yr−1 recorded at Bernardo de Irigoyen, Argentina, Chapeco and Sao Miguel do Oeste stations in Santa Catarina. >70% of events are recorded in late winter and spring, with September and October being the months with the highest number of occurrences. The trend analysis of hail events for winter and spring was carried out, and it was observed that for most seasons, there were no statistically significant trends for the analyzed series, but the station Montes Caseros, in Argentina presented a positive and significant tendency. The Bernardo de Irigoyen and Curuzu Cuatia stations, also in Argentina, have shown a significant negative trend that may be the result of global warming. The synoptic analysis of three events suggests that there is a combined action of atmospheric systems, which in association with the topography of the region, promote the development of severe hailstorms. There is evidence that the combination of the atmospheric conditions, including South American Low-Level Jet (SALLJ), local thermodynamic instability, frontal systems, and strong upper-level winds, create a favorable environment for hail formation in deep convection. This combination involves the transport of heat and moisture from tropical regions, high level divergence and strong directional wind shear.

This work presents an analysis of the observed trends in extreme precipitation events in the Paraná River basin (PRB) from 1977 to 2016 (40 yr) based on daily records from 853 stations. The Mann–Kendall test and inverse-distance-weighted interpolation were applied to annual and seasonal precipitation and also for four extreme precipitation indices. The results show that the negative trends (significance at 95% confidence level) in annual and seasonal series are mainly located in the northern and northeastern parts of the basin. In contrast, except in the autumn season, positive trends were concentrated in the southern and southeastern regions of the basin, most notably for annual and summer precipitation. The spatial distributions of the indices of annual maximum 5-day precipitation and number of rainstorms indicate that significant positive trends are mostly located in the south-southeast part of the basin and that significant negative trends are mostly located in the north-northeast part. The index of the annual number of dry days shows that 88% of significant trends are positive and that most of these are located in the northern region of the PRB, which is a region with a high number of consecutive dry days (>90). The simple daily intensity index showed the highest number of stations (263) with mostly positive significant trends.

Within a single region, it is possible to identify opposite changes in flow production. This proved to be the case for several basins in southeastern South America. It remains challenging to the causes this behavior and whether changes in streamflow will continue at current levels or decline in the coming decades. In this study, we used the Soil Water Assessment Tool to simulate monthly river discharge in the Ivaí River Basin, an unregulated medium-sized catchment and tributary of the Upper Paraná River Basin. After calibration, the simulated flow regime for the five streamflow stations based on the Nash-Sutcliffe Efficiency index (NSE) rated four of the streamflow stations Very Good (NSE between 0.86 and 0.89) and only one in the Good index (0.70). The overall flow behavior was well represented, although an underestimation was identified in four monitoring stations. Through assessment of its functionality and limitations in terms of specific flow duration curves percentages, the calibrated model could provide (to managers) the reliability needed for a realistic intervention. The results of this study may assist managers and support public policies for the use of water resources at the Ivaí River basin.

A dengue é uma doença viral transmitida pela fêmea do mosquito Aedes aegypti. A ocorrência de sucessivas epidemias de dengue tem se tornado um problema à saúde pública, que é recorrente em locais de climas tropical e subtropical, em função de suas características ambientais, climáticas e sociais. Assim, compreender a relação entre os casos de dengue e variáveis meteorológicas, como temperatura, precipitação e umidade relativa do ar, é de grande importância. Desta forma, esse estudo consistiu em investigar essa relação para Londrina, uma cidade do sul do Brasil. O estudo foi realizado por meio de Modelos Lineares Generalizados, considerando-se a série temporal de 2010 a 2014. Dados semanais de casos confirmados de dengue e das variáveis meteorológicas foram utilizados para analisar as possíveis associações. O modelo que se mostrou mais adequado foi o Binomial negativo. Os resultados indicaram que no período houve uma elevação de aproximadamente 1°C na temperatura mínima, e que este foi suficiente para influenciar o comportamento do mosquito fazendo com que os casos se concentrassem entre a 11ª e a 21ª semanas do ano, período correspondente ao outono no sul do Brasil. Além disso, a umidade e principalmente a temperatura mínima apresentaram associações positivas, tanto quando analisado individualmente os anos, como o conjunto completo de dados. Desta forma, pode-se concluir que o aumento das temperaturas mínimas leva ao aumento de casos de dengue na região.Palavras-chave: Dengue; Temperatura; Análise de regressão; Clima. Study of the relationship between meteorological variables and the occurrence of dengue cases in Londrina - PRA B S T R A C T Dengue fever is a viral disease transmitted by the female mosquito Aedes aegypti. The occurrence of successive dengue epidemics has become a public health problem, which typically occurs in tropical and subtropical climates, due to its environmental, climatic and social characteristics. Thus, to understand the relationship between the reported cases of dengue and the meteorological variables, such as temperature, rainfall and relative humidity of air is of great importance. This study aims to investigate such relationship for Londrina, a southern Brazilian city, by using a Generalized Linear Models for the period 2010 to 2014. Weekly data of confirmed dengue cases and the meteorological variables were used to analyze the possible associations. The Binomial Negative model presented the best fit. The results indicated that in the period there was an increase of 1 ºC in the minimum temperature, which was enough to cause changes in the mosquito behavior, so that the cases would concentrate between the 11th and 21st weeks of the year, corresponding to Autumn in Brazil. Furthermore, the humidity and mainly the minimum temperature presented positive associations, when years were individually analyzed, but also for the complete dataset. Thus, it can be concluded that the increase in minimum temperatures leads to the increase of dengue cases in the region.Keywords: Dengue, Temperature, Regression analysis, Climate.

Air pollution is currently one of the major environmental risk to human health in the world. Several studies link health to air pollution through the Poisson regression model. However, this study showed that the best method is the regression model with Negative Binomial distribution. The analysis was made based on daily data for the period between 2010 and 2014 regarding hospitalizations due to circulatory and respiratory diseases, stratified by age due to the concentration of air pollutants: CO, PM10, NO2, SO2 and O3 and meteorological variables. The results with Negative Binomial distribution model indicate, for interquartile range (IQR), that CO is a risk factor (1.00259–1.19688, 95% CI) for circulatory diseases in the elderly (aged over 64) and for respiratory diseases in the population aged 10–19 years old, while NO2 is a risk factor for the population in the range of 20–64 years (1.00313–1.25827, 95% CI) in the city of Araucaria. In Curitiba, air pollutants presenting a risk factor for respiratory diseases were PM10 (RR = 1.05322) in the range of 0–9 years old, CO and O3 (RR = 1.05047) in the range of 20–64 years old, and CO for the elderly. It could be verified that exposure to air pollutants is harmful to health even when their concentrations are below the standards set out in legislation. Additionally, the city of Araucaria presented the highest number of hospital admissions, which may be associated with the large number of industries and lower human development index in the city.

Air pollution by lead, even in small concentrations, can cause serious health effects. In the atmosphere this element can generally be found in particulate matter (PM), and in general in small concentrations. This work proposes the development of an analytical method for lead determination in inhaled PM based on ultrasound-assisted extraction with subsequent supramolecular solvent based dispersive liquid–liquid microextraction (SM-DLLME), using reverse micelles of dodecanoic acid as an extractor dispersed in a continuous phase of tetrahydrofuran (THF)/water. The rich phase was then analyzed by thermospray flame furnace atomic absorption spectrometry (TS-FF-AAS) coupled on-line to a flow injection analysis (FIA). An analytical curve in the range of 15.0–200.0 μg L−1 (R2 = 0.999), an enrichment factor of 18.1 times and the limits of detection (LOD) and quantification (LOQ) equal to 3.7 and 11.3 μg L−1, respectively, were obtained. The accuracy of the method was successfully attested by comparing with EDX analysis through the paired t-test at a confidence level of 95%. The amount of lead determined in the samples of PM collected in different environments varied from 19.3 to 94.8 ng m−3.

The long-range transport of aerosols is a global issue since it may significantly affect the air quality of regions without high concentrations of fine particulate matter (PM2.5). Two significant occurrences of long-range transport of aerosols over the state of Parana in Brazil, which occurred during the periods Aug. 16–18 and Sep. 10–14 of 2016, were studied in order to characterize the atmospheric synoptic conditions of these events and to estimate their contribution to the air quality conditions in the northern region of the state. The South American Low Level Jet (SALLJ) was the key meteorological component used to define the origin of the air mass trajectories over the region. In the first event, the SALLJ lost its configuration, bringing air masses from the western part of Sao Paulo (state), while in the second event, the SALLJ formed over southern Brazil and brought air masses from the northern and central parts of the nation. The significant number of fires from biomass burning in central Brazil associated with synoptic conditions contributed to the increase in PM2.5 concentrations by approximately 70–87% in the region. The transport of aerosols was a determining factor in PM2.5 exceeding the air quality standard in the region. Therefore, to minimize this problem, it is imperative to control biomass burning in Brazil.

Sixteen years of hourly atmospheric pollutant data (1996â2011) in the Metropolitan Area of São Paulo (MASP), and seven years (2005â2011) of data measured in the Metropolitan Area of Rio de Janeiro (MARJ), were analyzed in order to study the extreme pollution events and their return period. In addition, the objective was to compare the air quality between the two largest Brazilian urban areas and provide information for decision makers, government agencies and civil society. Generalized Extreme Value (GEV) and Generalized Pareto Distribution (GPD) were applied to investigate the behavior of pollutants in these two regions. Although GEV and GPD are different approaches, they presented similar results. The probability of higher concentrations for CO, NO, NO2, PM10 and PM2.5 was more frequent during the winter, and O3 episodes occur most frequently during summer in the MASP. On the other hand, there is no seasonally defined behavior in MARJ for pollutants, with O3 presenting the shortest return period for high concentrations. In general, Ibirapuera and Campos Elísios stations present the highest probabilities of extreme events with high concentrations in MASP and MARJ, respectively. When the regions are compared, MASP presented higher probabilities of extreme events for all analyzed pollutants, except for NO; while O3 and PM2.5 are those with most frequent probabilities of presenting extreme episodes, in comparison other pollutants. Keywords: Air pollutants, Extreme events, Megacities, Ozone, Particulate matter

This paper evaluates the contributions of the emissions from mobile, stationary and biogenic sources on air pollution in the Amazon rainforest by using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. The analyzed air pollutants were CO, NOx, SO2, O3, PM2. 5, PM10 and volatile organic compounds (VOCs). Five scenarios were defined in order to evaluate the emissions by biogenic, mobile and stationary sources, as well as a future scenario to assess the potential air quality impact of doubled anthropogenic emissions. The stationary sources explain the highest concentrations for all air pollutants evaluated, except for CO, for which the mobile sources are predominant. The anthropogenic sources considered resulted an increasing in the spatial peak-temporal average concentrations of pollutants in 3 to 2780 times in relation to those with only biogenic sources. The future scenario showed an increase in the range of 3 to 62 % in average concentrations and 45 to 109 % in peak concentrations depending on the pollutant. In addition, the spatial distributions of the scenarios has shown that the air pollution plume from the city of Manaus is predominantly transported west and southwest, and it can reach hundreds of kilometers in length.

The aim of this study was to characterize the inorganic chemical composition of fine inhalable atmospheric particulate matter (PM_(2.5)) in medium-sized cities in Brazil. These cities account for a significant proportion of the population and are growing at rates above the national average, thereby demonstrating the importance of carefully analysing the possible impact of such growth on air quality over the coming decades. In 2013 and 2014, this study collected PM_(2.5) samples from sites in the cities of Londrina and Maringa in two seasons: winter and summer. The mean concentration of PM_(2.5) ranged from 4.4 μg m^(-3) and 3.7 μg m^(-3) during the summer to 10.3 μg m^(-3) and 8.0 μg m^(-3) in winter in Londrina and Maringa, respectively. The analysis of the major water-soluble ions, nitrate, sulphate and chloride, showed that they accounted for between 16.5% and 35.1% from the mass of PM_(2.5), with sulphate providing the greatest contribution in all the campaigns. The nitrate/sulphate ratios ranged from 0.2 and 0.6, which are similar to the figures cited in the literature for other regions of the world. Although the PM_(2.5) concentrations are much lower than those observed in Asia and in Sao Paulo the participation of ions (%) is very close to that observed in Asian cities and significantly higher than the values recorded in other areas of Brazil, possibly as a result of the increased influence of burning of biomass and waste. The metals Zn, Pb, Cu and Mn found in the samples from all campaigns indicate that, in general, mobile sources are the main contributor to PM_(2.5). The winter campaigns showed the highest concentrations of black carbon equivalent (BCe). Absolute principal component analysis and enrichment factor analysis indicate the contribution of vehicular emission sources and biomass and waste burning to the inorganic chemical composition of PM_(2.5).

In this work, atmospheric pollutant emissions of NOx, SOx, CO, particulate matter (PM), total organic compounds (TOC), and CO2 from larger stationary sources of pollutants in Brazil were inventoried and spatialized over the whole Brazilian territory for the base year 2011. The developed inventory comprises a total of 16 refining units, 1730 thermoelectric power plants (TPPs), 96 cement industries, and 64 paper and cellulose industries. To obtain the dataset, some strategies were used, including mail contact, official datasets, personal requesting, web maps usage, and official industry websites. The emission factors were based on lower and upper limits proposed by the AP-42 standards of the US Environmental Protection Agency – USEPA, as well as, emission factors provided by air pollution control agencies, industries, and those identified in the scientific literature. The results show values of 857 ± 415 Gg/year for NOx, 1.51 ± 1.23 Tg/year for SOx, 21.2 ± 13.7 Tg/year for CO, 10.4 ± 10.1 Tg/year for PM, 1.14 ± 0.95 Tg/year for TOC, and 476 ± 142 Tg/year for CO2. In comparison with the official vehicular emission inventory provided by the Ministry of Environment for the year 2011, the total NOx emissions estimated in this work were slightly lower than vehicular emissions, while SOx was 300 times greater than vehicular emissions. For CO, the stationary emissions inventoried were around 17 times greater than vehicular emissions, while PM was approximately 360 times greater than those from vehicles. In terms of comparison with existing global databases, the estimates of this work showed a good level of agreement with the pollutants estimated by the Global Emissions EDGAR v4.3.1, except for PM and CO, which were higher in our estimates. The major contribution of the proposed inventory lies in its improved spatialized distribution, higher resolution, and greater distinctness about the high level of uncertainty associated with the emission inventories for the region.

This study presents a new land cover map for the Upper Parana River Basin (UPRB-2015), with high spatial resolution (30 m), and a high number of calibration and validation sites. To the new map, 50 Landsat-8 scenes were classified with the Support Vector Machine (SVM) algorithm and their level of agreement was assessed using overall accuracy and Kappa coefficient. The generated map was compared by area and by pixel with six global products (MODIS, GlobCover, Globeland30, FROM-GLC, CCI-LC and, GLCNMO). The results of the new classification showed an overall accuracy ranging from 67% to 100%, depending on the sub-basin (80.0% for the entire UPRB). Kappa coefficient was observed ranging from 0.50 to 1.00 (average of 0.73 in the whole basin). Anthropic areas cover more than 70% of the entire UPRB in the new product, with Croplands covering 46.0%. The new mapped areas of croplands are consistent with local socio-economic statistics but don’t agree with global products, especially FROM-GLC (14,9%), MODIS (33.8%), GlobCover (71.2%), and CCI (67.8%). In addition, all global products show generalized spatial disagreement, with some sub-basins showing areas of cropland varying by an order of magnitude, compared to UPRB-2015. In the case of Grassland, covering 25.6% of the UPRB, it was observed a strong underestimation by all global products. Even for the Globeland30 and MODIS, which show some significant fraction of pasture areas, there is a high level of disagreement in the spatial distribution. In terms of general agreement, the seven compared mappings (including the new map) agree in only 6.6% of the study area, predominantly areas of forest and agriculture. Finally, the new classification proposed in this study provides better inputs for regional studies, especially for those involving hydrological modeling as well as offers a more refined LU/LC data set for atmospheric numerical models.

In this paper, we analyze the variability of the ozone concentration over São Paulo Macrometropolis, as well the factors, whichdetermined the tendency observed in the last two decades. Time series of hourly ozone concentrations measured at 16 automatedstations from an air quality network from 1996 to 2017 were analyzed. The temporal variability of ozone concentrations exhibitswell-defined daily and seasonal patterns. Ozone presents a significant positive correlation between the number of cases (thresh-olds of 100–160μgm−3) and the fuel sales of gasohol and diesel. The ozone concentrations do not exhibit significant long-termtrends, but some sites present positive trends that occurs in sites in the proximity of busy roads and negative trends that occurs insites located in residential areas or next to trees. The effect of atmospheric process of transport and ozone formation was analyzedusing a quantile regression model (QRM). This statistical model can deal with the nonlinearities that appear in the relationship ofozone and other variables and is applicable to time series with non-normal distribution. The resulting model explains 0.76% ofthe ozone concentration variability (with global coefficient of determinationR1= 0.76) providing a better representation than anordinary least square regression model (with coefficient of determinationR2= 0.52); the effect of radiation and temperature arethe most critical in determining the highest ozone quantiles

Great efforts have been made over the years to assess the effectiveness of air pollution controls in place in the metropolitan area of Sao Paulo (MASP), Brazil. In this work, the community multiscale air quality (CMAQ) model was used to evaluate the efficacy of emission control strategies in MASP, considering the spatial and temporal variability of fine particle concentration. Seven different emission scenarios were modeled to assess the relationship between the emission of precursors and ambient aerosol concentration, including a baseline emission inventory, and six sensitivity scenarios with emission reductions in relation to the baseline inventory: a 50% reduction in SO2 emissions; no SO2 emissions; a 50% reduction in SO2, NOx, and NH3 emissions; no sulfate (PSO4) particle emissions; no PSO4 and nitrate (PNO3) particle emissions; and no PNO3 emissions. Results show that ambient PM2.5 behavior is not linearly dependent on the emission of precursors. Variation levels in PM2.5 concentrations did not correspond to the reduction ratios applied to precursor emissions, mainly due to the contribution of organic and elemental carbon, and other secondary organic aerosol species. Reductions in SO2 emissions are less likely to be effective at reducing PM2.5 concentrations at the expected rate in many locations of the MASP. The largest reduction in ambient PM2.5 was obtained with the scenario that considered a reduction in 50% of SO2, NOx, and NH3 emissions (1 to 2 μg/m3 on average). It highlights the importance of considering the role of secondary organic aerosols and black carbon in the design of effective policies for ambient PM2.5 concentration control.

Mobility restrictions are among actions to prevent the spread of the COVID-19 pandemic and have been pointed as reasons for improving air quality, especially in large cities. However, it is crucial to assess the impact of atmospheric conditions on air quality and air pollutant dispersion in the face of the potential variability of all sources. In this study, the impact of mobility restrictions on the air quality was analyzed for the most populous Brazilian State, São Paulo, severely impacted by COVID-19. Ground-based air quality data (PM10, PM2.5, CO, SO2, NOx, NO2, NO, and O3) were used from 50 automatic air quality monitoring stations to evaluate the changes in concentrations before (January 01 - March 25) and during the partial quarantine (March 16 - June 30). Rainfall, fires, and daily cell phone mobility data were also used as supplementary information to the analyses. The Mann-Whitney U test was used to assess the heterogeneity of the air quality data during and before mobility restrictions. In general, the results demonstrated no substantial improvements in air quality for most of the pollutants when comparing before and during restrictions periods. Besides, when the analyzed period of 2020 is compared with the year 2019, there is no significant air quality improvement in the São Paulo State. However, special attention should be given to the Metropolitan Area of São Paulo (MASP), due to the vast population residing in this area and exposed to air pollution. The region reached an average decrease of 29% in CO, 28% in NOx, 40% in NO, 19% in SO2, 15% in PM2.5, and 8% in PM10 concentrations during the mobility restrictions period compared to the same period in 2019. The only pollutant that showed an increase in concentration was ozone, with a 20% increase compared to 2019 during the mobility restrictions period. Before the mobility restrictions period, the region reached an average decrease of 30% in CO, 39% in NOx, 63% in NO, 12% in SO2, 23% in PM2.5, 18% in PM10, and 16% in O3 concentrations when compared to the same period in 2019. On the other hand, Cubatão, a highly industrialized area, showed statistically significant increases above 20% for most monitored pollutants in both periods of 2020 compared to 2019. This study reinforces that the main driving force of pollutant concentration variability is the dynamics of the atmosphere at its various time scales. An abnormal rainy season, with above average rainfall before the restrictions and below average after it, generated a scenario in which the probable significant reductions in emissions did not substantially affect the concentration of pollutants., Graphical abstract Image 1