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Variação sazonal das concentrações e distribuições por tamanho de partículas em suspensão na atmosfera na cidade de Mirandela - Portugal
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Abstract(s)
A poluição atmosférica por material particulado (PM) representa um dos principais desafios ambientais e de saúde pública, associando-se a diversas doenças respiratórias e cardiovasculares. Este estudo analisou a variação sazonal das concentrações de PM na cidade de Mirandela, Portugal, considerando a influência de fatores meteorológicos e de eventos atmosféricos, como incêndios e inversão térmica. Para isso, foram realizadas campanhas de monitorização contínua durante um período do verão de 2024 e do inverno de 2025, utilizando o espectrómetro EDM 280 da Grimm Aerosol Technik para medições em tempo real. A análise dos dados envolveu a conversão dos dados originais em médias horárias e posteriormente, através de um script desenvolvido em Python, a avaliação de padrões temporais e o estabelecimento de correlacções de Spearman entre as concentrações de PM com variáveis meteorológicas, como temperatura, humidade relativa, precipitação e velocidade do vento. A matriz de correlação de Spearman foi utilizada para avaliar a significância estatística das relações, adotando um nível de significância de 5%. Além disso, para avaliar a influência da direção do vento na dispersão do material particulado, foram gerados gráficos polares (rosas de poluição). Para investigar o transporte de massas de ar a longas distâncias, como o possível transporte de areia do deserto do Saara ou de partículas provenientes de incêndios florestais, foi utilizado o modelo de retrotrajetórias HYSPLIT. Adicionalmente, a ocorrência de inversões térmicas, um fator que pode contribuir para a acumulação de PM em determinados dias, foi analisada com base em dados meteorológicos extraídos da plataforma Meteoblue. Os resultados indicaram que, ao comparar as campanhas, o inverno teve concentrações médias globais de partículas mais elevadas, com picos frequentes ao longo do período, enquanto no verão as concentrações são mais estáveis, com picos esporádicos. Quanto a influencia das condições meteorológicas na concentração de PM, tem-se na campanha de inverno, temperaturas mais baixas e maior humidade favorecem a concentração de PM, enquanto no verão o efeito sobre as partículas não foi estatisticamente significativo. Em relação a precipitação, destaca-se que o volume total de chuvas foi relativamente baixo durante o período de estudo, e as análises tiveram correlações fracas. Quanto a velocidade do vento, observou-se que o efeito foi mais evidente no inverno, com uma relação mais robusta dos ventos como um importante fator dispersor de particulas. A modelação de trajetórias atmosféricas pelo modelo HYSPLIT permitiu identificar potenciais fontes remotas de poluição em dias de excedência, revelando que, em algumas ocasiões, as massas de ar transportavam partículas de regiões externas a Mirandela. Além disso, a análise da inversão térmica indicou que essa condição esteve presente em grande parte dos dias com altas concentrações de PM, dificultando a dispersão dos poluentes e contribuindo para a sua acumulação nas camadas mais baixas da atmosfera. Esses resultados reforçam a importância de considerar fatores meteorológicos e atmosféricos na avaliação da qualidade do ar, destacando a necessidade de estratégias de mitigação que levem em conta a variabilidade sazonal e os padrões climáticos regionais.
Air pollution caused by particulate matter (PM) represents one of the main environmental and public health challenges, being associated with various respiratory and cardiovascular diseases. This study analyzed the seasonal variation of PM concentrations in the city of Mirandela, Portugal, considering the influence of meteorological factors and atmospheric events such as wildfires and thermal inversion. To achieve this, continuous monitoring campaigns were conducted during the summer of 2024 and the winter of 2025, using the EDM 280 spectrometer from Grimm Aerosol Technik for real-time measurements. Data analysis involved converting the original data into hourly averages and, subsequently, using a Python-developed script to evaluate temporal patterns and establish Spearman correlations between PM concentrations and meteorological variables such as temperature, relative humidity, precipitation, and wind speed. The Spearman correlation matrix was used to assess the statistical significance of these relationships, adopting a significance level of 5%. Additionally, to evaluate the influence of wind direction on particulate matter dispersion, polar plots (pollution roses) were generated. To investigate the long-range transport of air masses, such as the potential transport of Saharan desert dust or particles from wildfires, the HYSPLIT back-trajectory model was applied. Furthermore, the occurrence of thermal inversions—a factor that can contribute to PM accumulation on certain days—was analyzed based on meteorological data obtained from the Meteoblue platform. The results indicated that, when comparing the two monitoring campaigns, winter exhibited higher global average PM concentrations, with frequent peaks throughout the period, whereas summer showed more stable concentrations with sporadic peaks. Regarding the influence of meteorological conditions on PM concentration, the winter campaign revealed that lower temperatures and higher humidity levels favored PM accumulation, whereas in summer, these factors had no statistically significant effect. Regarding precipitation, the total rainfall volume was relatively low during the study period, and the analyses showed weak correlations. Concerning wind speed, a more evident effect was observed in winter, with a stronger relationship between winds and their role as an important dispersing factor for particles. The atmospheric trajectory modeling using the HYSPLIT model allowed the identification of potential remote pollution sources on exceedance days, revealing that, on certain occasions, air masses carried particles from regions outside Mirandela. Additionally, the thermal inversion analysis indicated that this condition was present on most days with high PM concentrations, hindering pollutant dispersion and contributing to their accumulation in the lower atmospheric layers. These findings reinforce the importance of considering meteorological and atmospheric factors when assessing air quality, highlighting the need for mitigation strategies that account for seasonal variability and regional climate patterns.
Air pollution caused by particulate matter (PM) represents one of the main environmental and public health challenges, being associated with various respiratory and cardiovascular diseases. This study analyzed the seasonal variation of PM concentrations in the city of Mirandela, Portugal, considering the influence of meteorological factors and atmospheric events such as wildfires and thermal inversion. To achieve this, continuous monitoring campaigns were conducted during the summer of 2024 and the winter of 2025, using the EDM 280 spectrometer from Grimm Aerosol Technik for real-time measurements. Data analysis involved converting the original data into hourly averages and, subsequently, using a Python-developed script to evaluate temporal patterns and establish Spearman correlations between PM concentrations and meteorological variables such as temperature, relative humidity, precipitation, and wind speed. The Spearman correlation matrix was used to assess the statistical significance of these relationships, adopting a significance level of 5%. Additionally, to evaluate the influence of wind direction on particulate matter dispersion, polar plots (pollution roses) were generated. To investigate the long-range transport of air masses, such as the potential transport of Saharan desert dust or particles from wildfires, the HYSPLIT back-trajectory model was applied. Furthermore, the occurrence of thermal inversions—a factor that can contribute to PM accumulation on certain days—was analyzed based on meteorological data obtained from the Meteoblue platform. The results indicated that, when comparing the two monitoring campaigns, winter exhibited higher global average PM concentrations, with frequent peaks throughout the period, whereas summer showed more stable concentrations with sporadic peaks. Regarding the influence of meteorological conditions on PM concentration, the winter campaign revealed that lower temperatures and higher humidity levels favored PM accumulation, whereas in summer, these factors had no statistically significant effect. Regarding precipitation, the total rainfall volume was relatively low during the study period, and the analyses showed weak correlations. Concerning wind speed, a more evident effect was observed in winter, with a stronger relationship between winds and their role as an important dispersing factor for particles. The atmospheric trajectory modeling using the HYSPLIT model allowed the identification of potential remote pollution sources on exceedance days, revealing that, on certain occasions, air masses carried particles from regions outside Mirandela. Additionally, the thermal inversion analysis indicated that this condition was present on most days with high PM concentrations, hindering pollutant dispersion and contributing to their accumulation in the lower atmospheric layers. These findings reinforce the importance of considering meteorological and atmospheric factors when assessing air quality, highlighting the need for mitigation strategies that account for seasonal variability and regional climate patterns.
Description
Mestrado de dupla diplomação com o Centro Federal de Educação Tecnológica de Minas Gerais, CEFET-MG
Keywords
Monitorização ambiental Material particulado Variação temporal Qualidade do ar