Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields

Sofiev, M., Buters, J., Tummon, F., Fatahi, Y., Sozinova, O., Adams-Groom, Beverley ORCID: https://orcid.org/0000-0002-1097-8876, Bergmann, K. C., Dahl, Å., Gehrig, R., Gilge, S., Seliger, A. K., Kouznetsov, R., Lieberherr, G., O'Connor, D., Oteros, J., Palamarchuk, J., Ribeiro, H., Werchan, B., Werchan, M. and Clot, B. (2023) Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields. Science of the Total Environment, 900 (165800). pp. 1-21. ISSN Print: 0048-9697 Online: 1879-1026

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Abstract

We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities.

Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper.

We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data.

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