No abstract

No abstract

h i g h l i g h t s < Urban PM emissions contribute less than 15% to the urban background. < Factor 2e3 higher EC, heavy metals and re-suspension concentrations in street canyons. < 14 C analysis indicates increasing contribution of biomass and biofuel to EC. C Rotterdam The Netherlands a b s t r a c tThe contribution of regional, urban and traffic sources to PM 2.5 and PM 10 in an urban area was investigated in this study. The chemical composition of PM 2.5 and PM 10 was measured over a year at a street location and up-and down-wind of the city of Rotterdam, the Netherlands. The 14 C content in EC and OC concentrations was also determined, to distinguish the contribution from "modern" carbon (e.g., biogenic emissions, biomass burning and wildfires) and fossil fuel combustion. It was concluded that the urban background of PM 2.5 and PM 10 is dominated by the regional background, and that primary and secondary PM emission by urban sources contribute less than 15%. The 14 C analysis revealed that 70% of OC originates from modern carbon and 30% from fossil fuel combustion. The corresponding percentages for EC are, respectively 17% and 83%. It is concluded that in particular the urban population living in street canyons with intense road traffic has potential health risks. This is due to exposure to elevated concentrations of a factor two for EC from exhaust emissions in PM 2.5 and a factor 2e3 for heavy metals from brake and tyre wear, and re-suspended road dust in PM 10 . It follows that local air quality management may focus on local measures to street canyons with intense road traffic.

The use of low-cost sensors for air quality measurements is expanding rapidly, with an associated rise in the number of citizens measuring air quality themselves. This has major implications for traditional air quality monitoring as performed by Environmental Protection Agencies. Here we reflect on the experiences of the Dutch Institute for Public Health and the Environment (RIVM) with the use of low-cost sensors, particularly NO2 and PM10/PM2.5-sensors, and related citizen science, over the last few years. Specifically, we discuss the Dutch Innovation Program for Environmental Monitoring, which comprises the development of a knowledge portal and sensor data portal, new calibration approaches for sensors, and modelling and assimilation techniques for incorporating these uncertain sensor data into air pollution models. Finally, we highlight some of the challenges that come with the use of low-cost sensors for air quality monitoring, and give some specific use-case examples. Our results show that low-cost sensors can be a valuable addition to traditional air quality monitoring, but so far, their use in official monitoring has been limited. More research is needed to establish robust calibration methods while ongoing work is also aimed at a better understanding of the public’s needs for air quality information to optimize the use of low-cost sensors.

No abstract