Towards integration of LOTOS-EUROS high resolution simulations and heterogenous low-cost sensor observations
article
Official air quality monitoring networks are often scarce and unevenly spatially distributed. In recent years, the use of low-cost sensors next to official networks is increasing. These additional networks provide measurements of high spatial and temporal resolution and potentially reveal patterns and emissions sources that are hard to detect with conventional methods. In this work, the data assimilation method implemented around the LOTOS EUROS chemistry transport model is employed to assimilate measurements from heterogenous low-cost sensor networks around the city of Eindhoven in the Netherlands in November 2021. Three data assimilation experi ments are performed and evaluated against a free run of the model. In the first one, measurements from the low cost Innovatief Lucht Meetsysteem (ILM) network are exploited. In the second one, the citizen science network SamenMeten is used and in the third one, a combination of both datasets is applied. In the assimilation exper iments at a domain around the city of Eindhoven, it is shown to be essential to use boundary conditions from an assimilation on a larger domain to account for the variability in pollution that originates from sources outside the domain of interest. Such an improvement in boundary conditions counts for a decrease in the initial free run negative biases of 45% for PM10 and 23% for PM2.5 in the city of Eindhoven. The assimilation of low-cost.
TNO Identifier
997279
Source
Atmospheric Environment, 333, pp. 1-18.
Pages
1-18