scholarly journals Airborne particles in the Brazilian city of São Paulo: One-year investigation for the chemical composition and source apportionment

2017 ◽  
Author(s):  
Guilherme Martins Pereira ◽  
Kimmo Teinilä ◽  
Danilo Custódio ◽  
Aldenor Gomes Santos ◽  
Huang Xian ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Source Apportionment ◽  
Health Risks ◽  
Biomass Burning ◽  
Sao Paulo ◽  
Airborne Particles ◽  
São Paulo ◽  
Carbonaceous Species ◽  
Local Sources

Abstract. São Paulo in Brazil has relatively relaxed regulations for ambient air pollution standards and often experiences high air pollution levels due to emissions of airborne particles from local sources and long-range transport of biomass burning-impacted air masses. In order to evaluate the sources of particulate air pollution (PM) and related health risks, a year-round sampling was performed for PM2.5 (≤ 2.5 μm) and PM10 (≤ 10 μm) in 2014 through intensive (every day sampling in wintertime) and extensive campaigns (once a week for the whole year) with 24 h of sampling. This year was characterized to have lower average precipitation comparing to meteorological data, and high pollution episodes were observed all year round, with a significant increase of pollution level in the intensive campaign, which was performed during wintertime. Different chemical constituents, such as carbonaceous species, polycyclic aromatic hydrocarbons (PAHs) and derivatives, water-soluble ions and biomass burning tracers were identified in order to evaluate health risks and to apportion sources. The species such as PAHs, inorganic and organic ions and monosaccharides were determined by chromatographic techniques and carbonaceous species by thermal-optical analysis. The associated risks to particulate matter exposure based on PAH concentrations were also assessed, along with indexes such as the benzo[a]pyrene equivalent (BaPE) and lung cancer risk (LCR). High BaPE and LCR were observed in most of the samples, rising to critical values in the wintertime. Also, biomass burning tracers and PAHs were higher in this season, while secondarily formed ions presented low variation throughout the year. Meanwhile, vehicular tracer species were also higher in the intensive campaign suggesting the influence of lower dispersion conditions in that period. Source apportionment was done by Positive Matrix Factorization (PMF), which indicated five different factors: road dust, industrial emissions, vehicular exhaust, biomass burning and secondary processes. The results highlighted the contribution of vehicular emissions and the significant input from biomass combustion in wintertime, suggesting that most of the particulate matter is due to local sources, besides the influence of pre-harvest sugarcane burning.

scholarly journals Particulate pollutants in the Brazilian city of São Paulo: 1-year investigation for the chemical composition and source apportionment

2017 ◽  
Vol 17 (19) ◽  
pp. 11943-11969 ◽  
Author(s):  
Guilherme Martins Pereira ◽  
Kimmo Teinilä ◽  
Danilo Custódio ◽  
Aldenor Gomes Santos ◽  
Huang Xian ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Source Apportionment ◽  
Health Risks ◽  
Biomass Burning ◽  
Sao Paulo ◽  
São Paulo ◽  
Carbonaceous Species ◽  
Particulate Pollutants ◽  
Local Sources

Abstract. São Paulo in Brazil has relatively relaxed regulations for ambient air pollution standards and often experiences high air pollution levels due to emissions of particulate pollutants from local sources and long-range transport of air masses impacted by biomass burning. In order to evaluate the sources of particulate air pollution and related health risks, a year-round sampling was done at the University of São Paulo campus (20 m a.g.l.), a green area near an important expressway. The sampling was performed for PM2. 5 ( ≤ 2. 5 µm) and PM10 ( ≤  10 µm) in 2014 through intensive (everyday sampling in wintertime) and extensive campaigns (once a week for the whole year) with 24 h of sampling. This year was characterized by having lower average precipitation compared to meteorological data, and high-pollution episodes were observed all year round, with a significant increase in pollution level in the intensive campaign, which was performed during wintertime. Different chemical constituents, such as carbonaceous species, polycyclic aromatic hydrocarbons (PAHs) and derivatives, water-soluble ions, and biomass burning tracers were identified in order to evaluate health risks and to apportion sources. The species such as PAHs, inorganic and organic ions, and monosaccharides were determined using chromatographic techniques and carbonaceous species using thermal-optical analysis. Trace elements were determined using inductively coupled plasma mass spectrometry. The risks associated with particulate matter exposure based on PAH concentrations were also assessed, along with indexes such as the benzo[a]pyrene equivalent (BaPE) and lung cancer risk (LCR). High BaPE and LCR were observed in most of the samples, rising to critical values in the wintertime. Also, biomass burning tracers and PAHs were higher in this season, while secondarily formed ions presented low variation throughout the year. Meanwhile, vehicular tracer species were also higher in the intensive campaign, suggesting the influence of lower dispersion conditions in that period. Source apportionment was performed using positive matrix factorization (PMF), which indicated five different factors: road dust, industrial emissions, vehicular exhaust, biomass burning and secondary processes. The results highlighted the contribution of vehicular emissions and the significant input from biomass combustion in wintertime, suggesting that most of the particulate matter is due to local sources, in addition to the influence of pre-harvest sugarcane burning.

scholarly journals Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia

2021 ◽  
Vol 18 (21) ◽  
pp. 11608
Author(s):  
Worku Tefera ◽  
Abera Kumie ◽  
Kiros Berhane ◽  
Frank Gilliland ◽  
Alexandra Lai ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Addis Ababa ◽  
Atmospheric Particulate Matter ◽  
Motor Vehicles ◽  
Soil Dust ◽  
Rain Season ◽  
The Impact

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June–September) and short rain season (February–April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public’s health.

scholarly journals Association between COVID-19, mobility and environment in São Paulo, Brazil

2021 ◽  
Author(s):  
Sergio Ibarra-Espinosa ◽  
Edmilson Dias de Freitas ◽  
Karl Ropkins ◽  
Francesca Dominici ◽  
Amanda Rehbein
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Relative Humidity ◽  
Residential Mobility ◽  
Additive Model ◽  
Sao Paulo ◽  
São Paulo ◽  
Ambient Particulate Matter ◽  
Mobility Index ◽  
Small Increments

AbstractBackgroundBrazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to control quarantines and prevent the transmissions of SARS-CoV2.In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in São Paulo, BrazilObjectivesTo estimate the associations between daily residential mobility index (RMI), air pollution, and meteorology, and daily cases and deaths for COVID-19 in São Paulo, Brazil.MethodsWe applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between residential mobility index and cases and deaths due to COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 3-21 days and 2) the association between exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility.ResultsWe found an RMI of 45.28% results in 1,212 cases (95% CI: 1,189 to 1,235) and 44 deaths (95% CI: 40 to 47). Reducing mobility 5% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 μg·m-3 of PM2.5 risk of 1.140 (95% CI: 1.021 to 1.274) for cases and of 1.086 (95% CI: 1.008 to 1.170) for deaths, while O3 produces a relative risk of 1.075 (95% CI: 1.006 to 1.150) for cases and 1.063 (95% CI: 1.006 to 1.124) for deaths, respectively.DiscussionWe compared our results with observations and literature review, finding well agreement. These results implicate that authorities and policymakers can use such mobility indices as tools to support social distance activities and assess their effectiveness in the coming weeks and months. Small increments of air pollution pose a risk of COVID-19 cases.ConclusionSpatial distancing is a determinant factor to control cases and deaths for COVID-19. Small increments of air pollution result in a high number of COVID-19 cases and deaths. PM2.5 has higher relative risks for COVID-19 than O3.

scholarly journals Association between particulate matter air pollution and monthly inhalation and nebulization procedures in Ribeirão Preto, São Paulo State, Brazil

2012 ◽  
Vol 28 (8) ◽  
pp. 1591-1598 ◽  
Author(s):  
Estela Cristina Carneseca ◽  
Jorge Alberto Achcar ◽  
Edson Zangiacomi Martinez
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Sao Paulo ◽  
Respiratory Morbidity ◽  
São Paulo ◽  
Random Factor ◽  
Paulo State ◽  
São Paulo State ◽  
The Impact ◽  
The Relationship

The study was designed to investigate the impact of air pollution on monthly inhalation/nebulization procedures in Ribeirão Preto, São Paulo State, Brazil, from 2004 to 2010. To assess the relationship between the procedures and particulate matter (PM10) a Bayesian Poisson regression model was used, including a random factor that captured extra-Poisson variability between counts. Particulate matter was associated with the monthly number of inhalation/nebulization procedures, but the inclusion of covariates (temperature, precipitation, and season of the year) suggests a possible confounding effect. Although other studies have linked particulate matter to an increasing number of visits due to respiratory morbidity, the results of this study suggest that such associations should be interpreted with caution.

Source apportionment of fine particulate matter by positive matrix factorization in the metropolitan area of São Paulo, Brazil

2018 ◽  
Vol 202 ◽  
pp. 253-263 ◽  
Author(s):  
Regina Maura de Miranda ◽  
Maria de Fatima Andrade ◽  
Flavia Noronha Dutra Ribeiro ◽  
Kelliton José Mendonça Francisco ◽  
Pedro José Pérez-Martínez
Keyword(s):  
Particulate Matter ◽  
Source Apportionment ◽  
Metropolitan Area ◽  
Matrix Factorization ◽  
Fine Particulate Matter ◽  
Positive Matrix Factorization ◽  
Sao Paulo ◽  
São Paulo ◽  
Positive Matrix ◽  
Fine Particulate

scholarly journals Health Risks and Economic Costs of Absenteeism Due to Air Pollution in São Paulo, Brazil

2012 ◽  
Vol 12 (5) ◽  
pp. 826-833 ◽  
Author(s):  
Fernando Rodrigues-Silva ◽  
Ubiratan de Paula Santos ◽  
Paulo Hilário Nascimento Saldiva ◽  
Luis Fernando Amato-Lourenço ◽  
Simone Georges El Khouri Miraglia
Keyword(s):  
Air Pollution ◽  
Health Risks ◽  
Sao Paulo ◽  
São Paulo ◽  
Economic Costs

scholarly journals Application of machine learning algorithms to PM2.5 concentration analysis in the state of São Paulo, Brazil

2020 ◽  
Vol 56 (1) ◽  
pp. 152-165
Author(s):  
Angela Rosa Locateli Godoy ◽  
Ana Estela Antunes da Silva ◽  
Mirelle Candida Bueno ◽  
Simone Andréa Pozza ◽  
Guilherme Palermo Coelho
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Carbon Monoxide ◽  
Particulate Matter ◽  
Meteorological Factors ◽  
Sao Paulo ◽  
The State ◽  
São Paulo ◽  
The Relationship ◽  
Pm2.5 Concentration

Air quality monitoring data are useful in different areas of research and have varied applications, especially with a focus on the relationship between air pollution, respiratory problems, and other health hazards. The main atmospheric pollutants are: ozone (O3), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and particulate matter (PM). PM is one of the main objects of study when one intends to protect people from exposure to pollutants. This study contributes to the analysis of PM2.5 in 21 stations in the state of São Paulo monitored by the Environmental Company of São Paulo State (CETESB). It employs cluster analysis, a prominent data mining method for detecting patterns and discovering similarities which is important for assessing air pollution, especially in a geographically vast area such as that of the state of São Paulo, which does not follow a single pattern. Another data mining technique (association rules) supports the analysis of the relationship between pollutants and meteorological variables, as it allows identifying changes between elements that occur together, in a wide variety of data. Our objectives include determining stations with similar behaviors and exploring the temporal variety of the pollutant as it relates to the dominant meteorological factors in the periods of high concentration. The clustering algorithm automatically separates stations according to their monthly averages of PM2.5 concentration between 2017 and 2019. The clusters of stations that showed the highest pollution rates essentially included urban centers with emissions by industries and vehicles, while those with the lowest rates were located further inland. A cyclical behavior in pollutant variation was also observed in the three years under study and for both clusters. For the months with the highest concentration of PM2.5, association rule learning was applied to connect air temperature, relative humidity, and wind speed with PM2.5 and carbon monoxide (CO) concentrations. The obtained results are useful to analyze the temporal and geolocation profiles of pollution by particulate matter, since they identify the behavior of the meteorological factors that predominate in periods of greater concentration.

THE IMPACT OF DIFFERENT URBAN LAND USE TYPES ON AIR POLLUTION IN THE MEGACITY OF SÃO PAULO

2020 ◽  
Vol 7 (1) ◽  
pp. 91
Author(s):  
Júlio Barboza Chiquetto ◽  
Maria Elisa Siqueira Silva ◽  
Rita Yuri Ynoue ◽  
Flávia Noronha Dutra Ribieiro ◽  
Débora Souza Alvim ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Urban Land ◽  
Sao Paulo ◽  
Urban Land Use ◽  
São Paulo ◽  
Land Use Types ◽  
The Impact

A poluição do ar é influenciada por fatores naturais e antropogênicos. Quatro pontos de monitoramento (veicular, comercial, residencial e background urbano (BGU))da poluição do ar em São Paulo foram avaliados durante 16 anos, revelando diferenças significativas devidoao uso do solo em todas as escalas temporais. Na escala diurna, as concentrações de poluentes primários são duas vezes mais altas nos pontos veicular e residencial do que no ponto BGU, onde a concentração de ozonio (O3) é 50% mais alta. Na escala sazonal, as concentrações de monóxido de carbono(CO) variaram em 80% devido ao uso do solo, e 55% pela sazonalidade.As variações sazonais ede uso do solo exercem impactos similares nas concentrações de O3 e monóxido de nitrogênio (NO). Para o material particulado grosso (MP10) e o dióxido de nitrogênio(NO2), as variações sazonais são mais intensas do que as por uso do solo. Na série temporal de 16 anos, o ponto BGU apresentou correlações mais fortes e significativas entre a média mensal de ondas longas (ROL) e o O3 (0,48) e o MP10 (0,37), comparadas ao ponto veicular (0,33 e 0,22, respectivamente). Estes resultados confirmam que o uso do solo urbano tem um papel significativo na concentração de poluentes em todas as escalas de análise, embora a sua influência se torne menos pronunciada em escalas maiores, conforme a qualidade do ar transita de um sistema antropogênico para um sistema natural. Isto poderá auxiliar decisões sobre políticas públicas em megacidades envolvendo a modificação do uso do solo.

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