Air pollution persistent exceedance events in the Brazilian metropolis of Sao Paulo and associated surface weather patterns

Oliveira, M. C.; Drumond, Anita; Rizzo, L. V.

doi:10.1007/s13762-021-03778-1

Cited by 8 publications

(5 citation statements)

References 34 publications

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“…Under the SASA in winter, SEB experiences weather with clear skies, weak winds, and subsidence movements, the blocking of the synoptic system's passage and inhibition of cloud formation, and developing thermal inversions in the atmosphere. All these conditions are unfavorable to the dispersion of pollutants in the most urbanized Brazilian region [192,193].…”

Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

A New Look into the South America Precipitation Regimes: Observation and Forecast

Ferreira

Reboita

2022

Atmosphere

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South America is a vast continent characterized by diverse atmospheric phenomena and climate regimes. In this context, seasonal climate predictions are helpful for decision-making in several relevant socioeconomic segments in this territory, such as agriculture and energy generation. Thus, the present work evaluates the performance of ECMWF-SEAS5 in simulating the South American precipitation regimes by applying a non-hierarchical clustering technique. In addition, the study describes the main atmospheric systems that cause precipitation in each cluster and updates a previous work performed in South America in 2010. As a result, ECMWF-SEAS5 simulates (with good correspondence) the eight climate regimes identified in the analysis of precipitation from the Climate Prediction Center (CPC). Moreover, ECMWF-SEAS5 has a satisfactory ability in representing the rainfall regime in low and medium climate predictability regions, such as central and southern South America. ECMWF-SEAS5 has good performance in the climate characterization of South America and it gives us confidence in using its seasonal climate predictions throughout the continent.

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Section: Cluster 5-region 5 (R5)mentioning

confidence: 99%

A New Look into the South America Precipitation Regimes: Observation and Forecast

Ferreira

Reboita

2022

Atmosphere

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“…PM 2.5 concentrations also responded to the dry conditions, with peak concentrations in April and in the austral winter (June-August) of 2016 (Figure 6A). In addition to the lower precipitation rates, the winter at MASP typically shows unfavorable conditions for air pollution dispersion, resulting in relatively high concentrations of primary pollutants (Carvalho et al, 2015;Silva et al, 2021;Oliveira et al, 2022). The seasonal behavior and concentration range of PM 2.5 were very similar in all three study areas (Figure 6A), showing that they are subjected to the same regional-scale climate forcing and have comparable air pollution burdens.…”

Section: Seasonality Of Pm 25 Removalmentioning

confidence: 89%

PM2.5 removal by urban trees in areas with different forestry conditions in São Paulo using a big-leaf modeling approach

Brito

Rizzo

2022

Rev. Bras. Ciênc. Ambient.

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Air pollution is one of the main environmental problems in megacities, such as the metropolitan area of São Paulo (MASP), in Brazil. Urban forests can alleviate air pollution by providing a surface for the dry deposition of particles and trace gases. To benefit from this environmental service and design future green structures, it is crucial to estimate the removal rate of air pollutants by trees. The removal rates of fine particulate matter (PM2.5) by urban trees were quantitatively assessed for the first time in Brazil. A big-leaf modeling approach was adopted, using the i-Tree Eco software. In situ dendrometric data, hourly PM2.5 concentrations, and meteorological variables were used as inputs to the model. PM2.5 removal fluxes ranged between 0.06 and 0.21 g/m2/year in three study areas with contrasting urban forestry conditions. The neighborhood with the greatest canopy cover and tree diversity had the highest removal rates. The evergreen character of the urban forest in the MASP possibly contributed to the relatively high PM2.5 removal fluxes, as compared to other cities around the world. Removal rates were higher in the austral summer, when high precipitation rates restricted the resuspension of deposited particles back to the atmosphere. When extrapolated to the whole metropolitan area, assuming homogeneous forestry conditions, the estimated PM2.5 removal rates were comparable to the magnitude of vehicular emissions, showing that air pollution removal by trees can be substantial in the MASP. The results demonstrate the contribution of urban trees to the improvement of air quality and can boost the development of public policies on urban afforestation in the MASP.

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“…Daily data on surface meteorological variables were provided by the IAG/USP meteorological station. Persistent exceedance events (PEE) were identified using the criteria [2]: exceedance events that occurred simultaneously in at least 50% monitoring stations, persisting for at least 5 consecutive days. PEE occurrence was represented as a timeseries of a binary variable.…”

Section: Methodsmentioning

confidence: 99%

“…An exceedance event occurs when air pollutant concentrations exceed the air quality standards. Persistent exceedance events (PEE) are defined as exceedance events that last for many consecutive days and occur simultaneously at many air quality monitoring stations across the MASP [2]. This study aims to develop a predictive model for the occurrence of PEE in the MASP based on surface meteorological variables.…”

Section: Introductionmentioning

confidence: 99%

Prediction of air pollution events in São Paulo based on surface meteorological variables

Miranda

Rizzo

2022

Preprint

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Large urban centers like the Metropolitan Region of São Paulo (MASP) are impacted by air pollution, especially by Inhalable particle matter (PM10). Persistent exceedance events (PEE) are defined as exceedance events that last for many consecutive days and occur simultaneously at many air quality monitoring stations across the MASP. This study aims to develop a predictive model for the occurrence of PEE in the MASP based on surface meteorological variables. Hourly PM10 concentrations from 12 air quality monitoring stations in the MASP between 2005 and 2021 were provided by the São Paulo State Environmental Agency (CETESB). Daily data on surface meteorological variables were provided by the IAG/USP meteorological station. Persistent exceedance events (PEE) were identified using the criteria: exceedance events that occurred simultaneously in at least 50% monitoring stations, persisting for at least 5 consecutive days. PEE occurrence was represented as a timeseries of a binary variable. The resulting daily dataset had 6204 lines and 13 attributes, without missing values. The dataset was divided into a training set (80%) and a test set (20%). A logistic regression model was applied, having the PEE occurrence (positive = 1) as the target value. The Variance Inflation Factor and the Stepwise Feature Selection method was applied to obtain an optimized subset of predictors. Model accuracy was accessed by the ROC curve and by a confusion matrix. Results indicate that PEE can be satisfactorily predicted by surface meteorological variables using a logistic regression. As for the next steps, we intend to extract easy-tocommunicate classification rules, aiming to support the development of warnings systems for air quality poor conditions in the MASP.

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Air pollution persistent exceedance events in the Brazilian metropolis of Sao Paulo and associated surface weather patterns

Cited by 8 publications

References 34 publications

A New Look into the South America Precipitation Regimes: Observation and Forecast

A New Look into the South America Precipitation Regimes: Observation and Forecast

PM2.5 removal by urban trees in areas with different forestry conditions in São Paulo using a big-leaf modeling approach

Prediction of air pollution events in São Paulo based on surface meteorological variables

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