Citizens' Surveillance Micro-network for the Mapping of PM2.5 in the City of Concón, Chile

Gramsch, E.; Morales, Luis; Baeza, Marcelo; Ayala, Cristian; Soto, Cristian; Neira-Román, José; Pérez, Patricio; Moreno, Francisco Grimaldo

doi:10.4209/aaqr.2019.04.0179

Cited by 10 publications

(9 citation statements)

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“…How the sensor is incorporated into the LCM and the overall design of the LCM does make a difference on the performance. Low cost sensors can range from $10 to $ 700 and are used as an alternative for air quality monitoring assessment (Snyder et al, 2013;Kumar, 2015;Morawska et al, 2018;Bulot et al, 2019;Feenstra et al, 2019;Mao et al, 2019), including a viewpoint of citizen science (Clements et al, 2019;Golumbic et al, 2019;Wesseling et al, 2019;Gramsch et al, 2020;Park et al, 2020). These low-cost networks can use a larger number of LCMs for the same area (Kumar and Jasuja, 2017;Barot et al, 2020), providing high spatial and temporal resolution.…”

Section: Introductionmentioning

confidence: 99%

“…It is also well known that LCMs have calibration, accuracy and long term variation problems which require various calibration techniques (Miskell et al, 2018;Badura et al, 2019;van Zoest et al, 2019;Chu et al, 2020;Gramsch et al, 2020;Han et al, 2021). Some LCMs have nonlinear response to particle size, with most of them having low performance for large particles (Feenstra et al, 2019;Kuula et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…When variations of these sources where traced across time, the effect of increased precipitations, produced a decrease of the natural dust source (composed of Si, Al, Fe, Mn, Ca, Mg, Ti), not observed in other sources. A study by Gramsch et al (2020), in Santiago, using data from 2011 to 2018 found that the Concentration Impact Factor (CIF) for the coarse fraction (PM 10-2.5 ), which is related to natural dust, decreased from 1 to 0.62 during days with rain and the CIF for PM 2.5 decreased from 1 to 0.82.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

Gramsch¹,

Oyola²,

Reyes³

et al. 2021

Front. Environ. Sci.

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In the last decade, many low-cost monitoring sensors and sensor-networks have been used as an alternative air quality assessment method. It is also well known that these low cost monitors have calibration, accuracy and long term variation problems which require various calibration techniques. In this work PM2.5 and PM10 low cost sensors (Plantower and Nova Fitness) have been tested in five cities under different environmental conditions and compared with collocated standard instruments. Simultaneously, particle composition (organic and black carbon, sulfate, nitrate, chloride, ammonium, and chemical elements) has been measured in the same places to study its influence on the accuracy. The results show a very large variability in the correlation between the low cost sensors and collocated standard instruments depending on the composition and size of particles present in the site. The PM10 correlation coefficient (R2) between the low cost sensor and a collocated regulatory instrument varied from to 0.95 in Temuco to 0.04 in Los Caleos. PM2.5 correlation varied from 0.97 to 0.68 in the same places. It was found that sites that had higher proportion of large particles had lower correlation between the low cost sensor and the regulatory instrument. Sites that had higher relative concentration of organic and black carbon had better correlation because these species are mostly below the 1 μm size range. Sites that had higher sulfate, nitrate or SiO2 concentrations in PM2.5 or PM10 had low correlation most likely because these particles have a scattering coefficients that depends on its size or composition, thus they can be classified incorrectly.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

Gramsch¹,

Oyola²,

Reyes³

et al. 2021

Front. Environ. Sci.

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“…The instrument allows the measurement of TSP and mass concentrations up to 6000 µg m −3 , PM 10 , PM 2.5 and PM 1 ; the relevant online data is summarized and presented in Table 2. Due to the fact that the TOPAS instrument went to maintenance and it was put offline on November 17 at 17:50 (UTC-5), the TOPAS was replaced with a new particle counter, Dylos DC1100 with PC interface (Gramsch et al 2020). The performance of the low-cost aerosol sensor (Dylos DC1100) compared to the TOPAS instrument was adequately validated prior to the data collection.…”

Section: Study Area and Instrumentationmentioning

confidence: 99%

Overview and Seasonality of PM10 and PM2.5 in Guayaquil, Ecuador

et al. 2021

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The focus of this study is the assessment of total suspended particles (TSP) and particulate matter (PM) with various aerodynamic diameters in ambient air in Guayaquil, a city in Ecuador that features a tropical climate. The urban annual mean concentrations of TSP (Total Suspended Particles), and particle matter (PM) with various aerodynamic diameters such as: PM10, PM2.5 and PM1 are 31 ± 14 µg m−3, 21 ± 9 µg m−3, 7 ± 2 µg m−3 and 1 ± 1 µg m−3, respectively. Air mass studies reveal that the city receives a clean Southern Ocean breeze. Backward trajectory analysis show differences between wet and dry seasons. During the dry season, most winds come from the south and southwest, while air masses from the peri urban may contribute as pollutant sources during the wet season. Although mean values of PM10 and PM2.5 were below dangerous levels, our year-round continuous monitoring study reveals that maximum values often surpassed those permissible limits allowed by the Ecuadorian norms. A cluster analysis shows four main paths in which west and southwest clusters account for more than 93% of the pollution. Total vertical column of NO2 shows the pollution footprint is strongest during the dry season, as opposed to the wet season. A microscopic morphological characterization of ambient particles within the city during the wet and the dry season reveals coarse mode particles with irregular and rounded shapes. Particle analysis reveals that samples are composed of urban dust, anthropogenic and organic debris during the dry season while mainly urban dust during the wet season.

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“…El material particulado se encuentra en el polvo, cenizas, hollín, partículas metálicas, cemento o polen. Otras fuentes de origen son la combustión industrial y doméstica del carbón, de los procesos industriales, incendios, erosión eólica y erupciones volcánicas, de las construcciones, demoliciones y otros (Salini, Medina, 2017;Gramsch et al, 2020;Đorđević et al, 2020). Los efectos principales en la salud humana van desde la irritación en las vías respiratorias, deposición en los pulmones que origina enfermedades como la silicosis y la asbestosis, así como empeoran el asma y las enfermedades cardiovasculares (Gramsch et al, 2016).…”

Section: Introduccionunclassified

Variables meteorológicas y niveles de concentración de material particulado de 10 μm en Andacollo, Chile: un estudio de dispersión y entropías

et al. 2020

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El objetivo de esta investigación es contrastar un modelo Gaussiano de dispersión de contaminantes, usando la rosa de los vientos de la ciudad de Andacollo (Chile), con un modelo cuya génesis está en la teoría del caos y que emplea datos crudos de carácter público de mediciones de la estación Andacollo del Sistema de Información Nacional de Calidad del Aire (SINCA) de Chile. Los datos conforman series de tiempo de material particulado, temperatura, humedad relativa, presión, radiación solar y magnitud de la velocidad del viento. El tratamiento caótico de cada serie entrega su exponente de Lyapunov, su coeficiente de Hurst y su entropía de correlación. La aproximación caótica muestra que las entropías de las variables meteorológicas actúan sobre la del contaminante provocando su decaimiento asintótico según perdida de persistencia, explicando sus interacciones térmicas localizadas. Se concluye que los modelos exhiben predicciones similares al comparar el decaimiento del contaminante PM10.

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Citizens' Surveillance Micro-network for the Mapping of PM2.5 in the City of Concón, Chile

Cited by 10 publications

References 0 publications

Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

Overview and Seasonality of PM10 and PM2.5 in Guayaquil, Ecuador

Variables meteorológicas y niveles de concentración de material particulado de 10 μm en Andacollo, Chile: un estudio de dispersión y entropías

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Citizens' Surveillance Micro-network for the Mapping of PM2.5 in the City of Concón, Chile

Cited by 10 publications

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Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

Influence of Particle Composition and Size on the Accuracy of Low Cost PM Sensors: Findings From Field Campaigns

Overview and Seasonality of PM10 and PM2.5 in Guayaquil, Ecuador

Variables meteorológicas y niveles de concentración de material particulado de 10 &#956;m en Andacollo, Chile: un estudio de dispersión y entropías

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Variables meteorológicas y niveles de concentración de material particulado de 10 μm en Andacollo, Chile: un estudio de dispersión y entropías