Highly local sources and large spatial variations in PM<sub>2.5</sub> across a city: evidence from a city-wide sensor network in Cork, Ireland

Byrne, Rósín; Ryan, Kevin; Venables, Dean S.; Wenger, John C.; Hellebust, Stig

doi:10.1039/d2ea00177b

Cited by 4 publications

(1 citation statement)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Once all monitoring data were combined and corrected, the R package Openair [24] was used to generate graphs showing average daily and hourly concentrations. This package has many functionalities and has been used in conjunction with PurpleAir data to describe temporal and spatial variations in particulate matter concentrations for similar applications [25,26]. For the Hysplit analyses (below), the data from both sensors were averaged to obtain a single series for the city.…”

Section: Air Quality Data Analysismentioning

confidence: 99%

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

Connerton,

Nogueira,

Kumar

et al. 2023

Atmosphere

View full text Add to dashboard Cite

Ambient air quality is the most important environmental factor affecting human health, estimated by the WHO to be responsible for 4.2 million deaths annually. Having timely estimates for air quality is critical for implementing public policies that can limit anthropogenic emissions, reduce human exposure and allow for preparation and interventions in the health sector. In Brazil, wildfires constitute an important source of particulate matter emission, particularly in the country’s northern and midwestern regions, areas that are under-served in terms of air quality monitoring infrastructure. In the absence of regulatory-grade monitoring networks, low-cost sensors offer a viable alternative for generating real-time, publicly available estimates of pollutant concentrations. Here, we examine data from two low-cost sensors deployed in Brasília, in the Federal District of Brazil, during the 2022 wildfire season and use NOAA’s HYSPLIT model to investigate the origin of a particulate matter peak detected by the sensors. There was high agreeability of the data from the two sensors, with the raw values showing that daily average PM2.5 concentrations reached peak values of 46 µg/m3 and 43 µg/m3 at the school and park sites, respectively. This study demonstrates the value of low-cost sensors and their possible application in real-time scenarios for environmental health surveillance purposes.

show abstract

Section: Air Quality Data Analysismentioning

confidence: 99%

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

Connerton,

Nogueira,

Kumar

et al. 2023

Atmosphere

View full text Add to dashboard Cite

show abstract

Interpretable machine learning tools to analyze PM2.5 sensor network data so as to quantify local source impacts and long-range transport

de Foy,

Edwards,

Joy

et al. 2024

Atmospheric Research

View full text Add to dashboard Cite

Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experiment

Caseiro,

Schmitz,

von Schneidemesser

2024

Environ. Sci.: Atmos.

View full text Add to dashboard Cite

show abstract

Highly local sources and large spatial variations in PM_2.5 across a city: evidence from a city-wide sensor network in Cork, Ireland

Abstract: When dominated by local emissions, levels of ambient particulate matter (PM) can vary appreciably within a city. In Ireland, residential solid fuel burning is the main PM2.5 emission source.

Cited by 4 publications

References 34 publications

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

Interpretable machine learning tools to analyze PM2.5 sensor network data so as to quantify local source impacts and long-range transport

Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experiment

Contact Info

Product

Resources

About

Highly local sources and large spatial variations in PM2.5 across a city: evidence from a city-wide sensor network in Cork, Ireland

Abstract: When dominated by local emissions, levels of ambient particulate matter (PM) can vary appreciably within a city. In Ireland, residential solid fuel burning is the main PM2.5 emission source.

Cited by 4 publications

References 34 publications

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

Interpretable machine learning tools to analyze PM2.5 sensor network data so as to quantify local source impacts and long-range transport

Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – a field experiment

Contact Info

Product

Resources

About

Highly local sources and large spatial variations in PM_2.5 across a city: evidence from a city-wide sensor network in Cork, Ireland