| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 6.99 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
A qualidade do ar é uma área de bastante importância no mundo atual, devido ao facto de esta
ter vindo ao longo de alguns anos a ser afetada pela emissão de poluentes atmosféricos
maioritariamente a partir de fontes antropogénicas, mas também a partir de fontes naturais.
Assim sendo, urge a consciencialização de que é fundamental existir uma monitorização,
avaliação, gestão e controlo mais eficiente e rigoroso principalmente em centros urbanos
poluídos. O referido anteriormente é deveras importante, não só pela manutenção do equilíbrio
dos ecossistemas do planeta, mas também a nível da microescala, pelo facto da exposição do
ser humano, tanto de curta como de longa duração, a determinados níveis de concentrações de
determinados poluentes atmosféricos pode acarretar problemas à saúde com vários graus de
gravidade, podendo ainda diminuir o tempo de duração de vida.
Neste sentido, a monitorização da qualidade do ar é realizada através de uma rede de Estações
de Monitorização da Qualidade do Ar (EMQA), que utilizam para as suas medições os métodos
de referência ou métodos equivalentes, sendo estas denominadas de medições fixas. No entanto,
estes métodos cobrem uma limitada área, onde as EMQA situam-se em maior quantidade nas
grandes cidades, deixando outras grandes áreas sem este tipo de monitorização. Aumentar a
quantidade das EMQA de modo a aumentar a área de influência seria demasiado dispendioso e
impraticável. Por isso, uma alternativa é a possibilidade de utilizar redes de monitorização
complementar utilizando equipamentos constituídos por sensores de baixo custo, que
constituem métodos de medições indicativas.
Neste trabalho é avaliado o desempenho em campo de uma estação portátil de monitorização
da qualidade do ar constituída por sensores de baixo custo, a “SmartAirSense –
MONITARSENSE”, com o objetivo futuro de validar a estação como um método de medição
indicativa.
Para avaliação do desempenho da estação em estudo foram realizados ensaios de
intercomparação com EMQA que utilizam métodos de referência, em vários locais distintos (no
IPV e em Lisboa). Procederam-se a comparação dos resultados e o cálculo de estimativas de
incertezas para posterior comparação com os Objetivos de Qualidade dos Dados definidos na
legislação em vigor, para medições indicativas.
Relativamente aos resultados obtidos nos ensaios realizados para o O3, de forma geral
obtiveram-se valores de coeficientes de correlação elevados, entre as estações SmartAirSense
e as estações de referência. Em relação ao NO2, na a estação do IPV, obtiveram-se valores de
correlações quase nulos ou residuais, já nas estações presentes em Lisboa os valores das
correlações do NO2 foram elevados. Em relação às PM10 para a estação do IPV apenas se obteve
um valor elevado de correlação na alternativa onde se excluiu os dados referentes a episódios com influência de poeiras e partículas provenientes do Norte de África e nas estações presentes
em Lisboa obtiveram-se valores de correlação relativamente elevados.
Relativamente as estimativas de incerteza de medição verificou-se que para a estação do IPV
apenas se obteve valores de incerteza abaixo dos objetivos de qualidade dos dados (O3 = 30%;
NO2 = 25%; PM10 = 50%) nas PM10 considerando a alternativa do conjunto de dados excluindo
os dados referentes a episódios com influência de poeiras e partículas provenientes do Norte de
África (13,9%) e no O3 (12,7%; 15,2%; 20,7%). Por outro lado, nas estações presentes em
Lisboa, excetuando o resultado da estimativa de incerteza do NO2 da estação de Benfica
(34,2%) que ficou um pouco acima do objetivo de qualidade dos dados, todos os outros
resultados de estimativa de incerteza, tanto do O3 (26,9%; 21,9%), do NO2 (13,1%; 10,3%;
19,2%) e das PM10 (21,0%; 27,7%; 21,5%; 22,7%), cumpriram os objetivos de qualidade dos
dados.
ABSTRACT: Air quality is an area of great importance in today's world, due to the fact that it has been affected by the emission of atmospheric pollutants over a few years, mainly from anthropogenic sources, but also from natural sources. Therefore, it is urgent to be aware that it is essential to have more efficient and rigorous monitoring, evaluation, management and control, especially in polluted urban centres, but not only that. The aforementioned is very important, not only for the maintenance of the balance of the planet's ecosystems, but also at the micro-scale level, due to the fact that human beings are exposed, both for short and long term, to certain levels of concentrations of certain atmospheric pollutants. it can lead to health problems with varying degrees of severity, and it can also shorten the life span. In this sense, air quality monitoring is carried out through a network of Air Quality Monitoring Stations (EMQA), which use reference methods or equivalent methods for their measurements, these being called fixed measurements. However, these methods cover a limited area, where EMQAs are found in greater numbers in large cities, leaving other large areas without this type of monitoring. Increasing the number of EMQAs in order to increase the area of influence would be too costly and impractical. Therefore, an alternative is the possibility of using complementary monitoring networks using equipment consisting of low-cost sensors, which are indicative measurement methods. In this work, the field performance of a portable air quality monitoring station made up of lowcost sensors, “SmartAirSense – MONITARSENSE”, is evaluated in the field, with the future objective of validating the station as an indicative measurement method. To evaluate the performance of the station under study, intercomparison tests were performed with EMQA using reference methods, in several different locations. The results were compared, and uncertainty estimates were calculated for later comparison with the Data Quality Objectives defined in the legislation in force, for indicative measurements. Regarding the results obtained in the tests carried out for the O3, in general, high values of correlation coefficients were obtained between the SmartAirSense stations and the reference stations. Regarding NO2, for the IPV station, almost zero or residual correlation values were obtained, whereas in the stations present in Lisbon the values of NO2 correlations were high. In relation to PM10 for the IPV station, a high correlation value was only obtained in the alternative where data referring to episodes with the influence of dust and particles from North Africa and were excluded and at stations present in Lisbon relatively high correlation values were obtained. Regarding the estimates of measurement uncertainty, it was found that for the IPV station only uncertainty values were obtained below the data quality objectives (O3 = 30%; NO2 = 25%; PM10 = 50%) in PM10 considering the alternative from the dataset excluding data referring to episodes with the influence of dust and particles from North Africa (13,9%) and O3 (12,7%; 15,2%; 20,7%). On the other hand, at the stations present in Lisbon, except for the result of the estimation of uncertainty of the NO2 of the station in Benfica (34,2%) which was slightly above the objective of data quality, all other results of uncertainty estimation, both from O3 (26,9%; 21,9%), from NO2 (13,1%; 10,3%; 19,2%) and from PM10 (21,0%; 27,7%; 21,5 %; 22,7%) fulfilled the data quality objectives.
ABSTRACT: Air quality is an area of great importance in today's world, due to the fact that it has been affected by the emission of atmospheric pollutants over a few years, mainly from anthropogenic sources, but also from natural sources. Therefore, it is urgent to be aware that it is essential to have more efficient and rigorous monitoring, evaluation, management and control, especially in polluted urban centres, but not only that. The aforementioned is very important, not only for the maintenance of the balance of the planet's ecosystems, but also at the micro-scale level, due to the fact that human beings are exposed, both for short and long term, to certain levels of concentrations of certain atmospheric pollutants. it can lead to health problems with varying degrees of severity, and it can also shorten the life span. In this sense, air quality monitoring is carried out through a network of Air Quality Monitoring Stations (EMQA), which use reference methods or equivalent methods for their measurements, these being called fixed measurements. However, these methods cover a limited area, where EMQAs are found in greater numbers in large cities, leaving other large areas without this type of monitoring. Increasing the number of EMQAs in order to increase the area of influence would be too costly and impractical. Therefore, an alternative is the possibility of using complementary monitoring networks using equipment consisting of low-cost sensors, which are indicative measurement methods. In this work, the field performance of a portable air quality monitoring station made up of lowcost sensors, “SmartAirSense – MONITARSENSE”, is evaluated in the field, with the future objective of validating the station as an indicative measurement method. To evaluate the performance of the station under study, intercomparison tests were performed with EMQA using reference methods, in several different locations. The results were compared, and uncertainty estimates were calculated for later comparison with the Data Quality Objectives defined in the legislation in force, for indicative measurements. Regarding the results obtained in the tests carried out for the O3, in general, high values of correlation coefficients were obtained between the SmartAirSense stations and the reference stations. Regarding NO2, for the IPV station, almost zero or residual correlation values were obtained, whereas in the stations present in Lisbon the values of NO2 correlations were high. In relation to PM10 for the IPV station, a high correlation value was only obtained in the alternative where data referring to episodes with the influence of dust and particles from North Africa and were excluded and at stations present in Lisbon relatively high correlation values were obtained. Regarding the estimates of measurement uncertainty, it was found that for the IPV station only uncertainty values were obtained below the data quality objectives (O3 = 30%; NO2 = 25%; PM10 = 50%) in PM10 considering the alternative from the dataset excluding data referring to episodes with the influence of dust and particles from North Africa (13,9%) and O3 (12,7%; 15,2%; 20,7%). On the other hand, at the stations present in Lisbon, except for the result of the estimation of uncertainty of the NO2 of the station in Benfica (34,2%) which was slightly above the objective of data quality, all other results of uncertainty estimation, both from O3 (26,9%; 21,9%), from NO2 (13,1%; 10,3%; 19,2%) and from PM10 (21,0%; 27,7%; 21,5 %; 22,7%) fulfilled the data quality objectives.
Description
Keywords
Qualidade do Ar Poluentes Atmosféricos Monitorização Ambiental Métodos Indicativos Sensores de Baixo Custo