Assessment of PM2.5 Exposure during Cycle Trips in The Netherlands Using Low-Cost Sensors

Air pollution, especially fine particulate matter (PM2.5), is a major environmental risk factor for human health in Europe. Monitoring of air quality takes place using expensive reference stations. Low-cost sensors are a promising addition to this official monitoring network as they add spatial and temporal resolution at low cost. Moreover, low-cost sensors might allow for better characterization of personal exposure to PM2.5. In this study, we use 500 dust (PM2.5) sensors mounted on bicycles to estimate typical PM2.5 levels to which cyclists are exposed in the province of Utrecht, the Netherlands, in the year 2020. We use co-located sensors at reference stations to calibrate and validate the mobile sensor data. We estimate that the average exposure to traffic related PM2.5, on top of background concentrations, is approximately 2 μg/m3. Our results suggest that cyclists close to major roads have a small, but consistently higher exposure to PM2.5 compared to routes with less traffic. The results allow for a detailed spatial representation of PM2.5 concentrations and show that choosing a different cycle route might lead to a lower exposure to PM2.5. Finally, we conclude that the use of mobile, low-cost sensors is a promising method to estimate exposure to air pollution.

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Personal exposure to fine particulate matter and benzo[a]pyrene from indoor air pollution and leukocyte mitochondrial DNA copy number in rural China

Carcinogenesis ◽

10.1093/carcin/bgx068 ◽

2017 ◽

Vol 38 (9) ◽

pp. 893-899 ◽

Cited By ~ 18

Author(s):

Jason YY Wong ◽

Wei Hu ◽

George S Downward ◽

Wei Jie Seow ◽

Bryan A Bassig ◽

...

Keyword(s):

Air Pollution ◽

Mitochondrial Dna ◽

Indoor Air ◽

Copy Number ◽

Indoor Air Pollution ◽

Rural China ◽

Fine Particulate Matter ◽

Personal Exposure ◽

Fine Particulate ◽

Mitochondrial Dna Copy Number

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Changes in outdoor air pollution due to COVID-19 lockdowns differ by pollutant: evidence from Scotland

Occupational and Environmental Medicine ◽

10.1136/oemed-2020-106659 ◽

2020 ◽

Vol 77 (11) ◽

pp. 798-800 ◽

Cited By ~ 2

Author(s):

Ruaraidh Dobson ◽

Sean Semple

Keyword(s):

Air Pollution ◽

Motor Vehicle ◽

Fine Particulate Matter ◽

Personal Exposure ◽

Indoor Environments ◽

Similar Data ◽

Outdoor Air ◽

Fine Particulate ◽

Hourly Data ◽

The Impact

ObjectivesTo examine the impact of COVID-19 lockdown restrictions in March/April 2020 on concentrations of nitrogen dioxide (NO2) and ambient fine particulate matter (PM2.5) air pollution measured at roadside monitors across Scotland by comparing data with previous years.MethodsPublicly available data of PM2.5 concentrations from reference monitoring systems at sites across Scotland were extracted for the 31-day period immediately following the imposition of lockdown rules on 23 March 2020. Similar data for 2017, 2018 and 2019 were gathered for comparison. Mean period values were calculated from the hourly data and logged values compared using pairwise t-tests. Weather effects were corrected using meteorological normalisation.ResultsNO2 concentrations were significantly lower in the 2020 lockdown period than in the previous 3 years (p<0.001). Mean outdoor PM2.5 concentrations in 2020 were much lower than during the same period in 2019 (p<0.001). However, despite UK motor vehicle journeys reducing by 65%, concentrations in 2020 were within 1 µg/m3 of those measured in 2017 (p=0.66) and 2018 (p<0.001), suggesting that traffic-related emissions may not explain variability of PM2.5 in outdoor air in Scotland.ConclusionsThe impact of reductions in motor vehicle journeys during COVID-19 lockdown restrictions may not have reduced ambient PM2.5 concentrations in some countries. There is also a need for work to better understand how movement restrictions may have impacted personal exposure to air pollutants generated within indoor environments.

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City Wide Participatory Sensing of Air Quality

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.773778 ◽

2021 ◽

Vol 9 ◽

Author(s):

Andrew Rebeiro-Hargrave ◽

Pak Lun Fung ◽

Samu Varjonen ◽

Andres Huertas ◽

Salla Sillanpää ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Low Cost ◽

Age Groups ◽

Personal Exposure ◽

Urban Environments ◽

Sensor Data ◽

Automated System ◽

Participatory Sensing ◽

Good Correspondence

Air pollution is a contributor to approximately one in every nine deaths annually. Air quality monitoring is being carried out extensively in urban environments. Currently, however, city air quality stations are expensive to maintain resulting in sparse coverage and data is not readily available to citizens. This can be resolved by city-wide participatory sensing of air quality fluctuations using low-cost sensors. We introduce new concepts for participatory sensing: a voluntary community-based monitoring data forum for stakeholders to manage air pollution interventions; an automated system (cyber-physical system) for monitoring outdoor air quality and indoor air quality; programmable platform for calibration and generating virtual sensors using data from low-cost sensors and city monitoring stations. To test our concepts, we developed a low-cost sensor to measure particulate matter (PM2.5), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) with GPS. We validated our approach in Helsinki, Finland, with participants carrying the sensor for 3 months during six data campaigns between 2019 and 2021. We demonstrate good correspondence between the calibrated low-cost sensor data and city’s monitoring station measurements. Data analysis of their personal exposure was made available to the participants and stored as historical data for later use. Combining the location of low cost sensor data with participants public profile, we generate proxy concentrations for black carbon and lung deposition of particles between districts, by age groups and by the weekday.

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