Abstract
PM2.5 measurements using a network of lost-cost sensors were conducted during 2017–2019 in the greater area of Patras, Greece. The average PM2.5 concentration in all sites during the study period was 9.4 μg m−3, varying from 6.2 μg m−3 in the background areas to 12.8 μg m−3 at the city center. The site with the peak PM2.5 levels was not located in an area with high traffic density but rather in a square with pedestrian-only zones and a high restaurant density. The highest PM2.5 concentrations were observed during the colder period (November–March) due to high emissions from residential wood burning for heating purposes. The measurements of the sensors were used to estimate the importance of regional and local PM2.5 sources. During the warm period, regional transport dominated, contributing approximately 80–85% of the PM2.5 in the city center; however, during the colder period, the local sources were responsible for approximately half the PM2.5. The network operated reliably during this multiyear study. Such measurements provide, at a very low cost, valuable insights not only about the temporal and spatial variability of PM2.5 in a city but also about its sources, including the role of regional transport.
Highlights
Atmospheric pollution affects the natural environment, climate, and human health.Particulate matter (PM) is a significant air pollutant consisting of inorganic and organic components from various anthropogenic and biogenic sources
Several epidemiological studies have shown that exposure to high PM2.5 concentrations is associated with adverse health effects [3–9]
In order to ensure the high quality of the retrieved data, measurements were considered valid only when the two values reported by the two sensors in the same PurpleAir monitor differed by less than 20% of their average or less than 2 μg m−3
Summary
Atmospheric pollution affects the natural environment, climate, and human health. Particulate matter (PM) is a significant air pollutant consisting of inorganic and organic components from various anthropogenic and biogenic sources. We describe the deployment and operation for 3 years of a network of 16 low-cost PM2.5 monitors in a modest-size urban area and its surroundings Their measurements are analyzed using a series of approaches to estimate the contribution of the various sources to the PM2.5 in the area and to identify the hot spots as well as the periods of high concentration levels. These are helpful for the evaluation of our results using the low-cost sensor network data. The results of the measurements are analyzed focusing on the spatial and temporal variability of PM2.5 in the study area and the impact of local sources as well as long-range transport
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