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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/amt-2019-410
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-410
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 17 Dec 2019

Submitted as: research article | 17 Dec 2019

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This preprint is currently under review for the journal AMT.

High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam

Bas Mijling Bas Mijling
  • Royal Netherlands Meteorological Institute (KNMI), Postbus 201, 3730 AE, De Bilt, The Netherlands

Abstract. In many cities around the world people are exposed to elevated levels of air pollution. Often local air quality is not well known due to the sparseness of official monitoring networks, or unrealistic assumptions being made in urban air quality models. Low-cost sensor technology, which has become available in recent years, has the potential to provide complementary information. Unfortunately, an integrated interpretation of urban air pollution based on different sources is not straightforward because of the localized nature of air pollution, and the large uncertainties associated with measurements of low-cost sensors. In this study, we present a practical approach to producing high spatio-temporal resolution maps of urban air pollution capable of assimilating air quality data from heterogeneous data streams. It offers a two-step solution: (1) building a versatile air quality model, driven by an open source atmospheric dispersion model and emission proxies from open data sources, and (2) a practical spatial interpolation scheme, capable of assimilating observations with different accuracies.

The methodology, called Retina, has been applied and evaluated for nitrogen dioxide (NO2) in Amsterdam, the Netherlands, during the summer of 2016. The assimilation of reference measurements results in hourly maps with a typical accuracy of 39 % within 2 km of an observation location, and 53 % at larger distances. When low-cost measurements of the Urban AirQ campaign are included, the maps reveal more detailed concentration patterns in areas which are undersampled by the official network. During the summer holiday period, NO2 concentrations drop about 10 % due to reduced urban activity. The reduction is less in the historic city center, while strongest reductions are found around the access ways to the tunnel connecting the northern and the southern part of the city, which was closed for maintenance. The changing concentration patterns indicate how traffic flow is redirected to other main roads.

Overall, we show that Retina can be applied for an enhanced understanding of reference measurements, and as a framework to integrate low-cost measurements next to reference measurements in order to get better localized information in urban areas.

Bas Mijling

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Latest update: 13 Jul 2020
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Short summary
Many cities are experimenting with networks of low-cost sensors, complementary to their reference stations. Often the observations are published as dots on a map, as spatial interpolation is far from trivial. We introduce a new methodology to assimilate observations of different accuracy in a generic urban air quality model. It can be used for mapping local air quality based on reference measurements only, or as a framework to integrate low-cost measurements next to official measurements.
Many cities are experimenting with networks of low-cost sensors, complementary to their...
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