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Ammonia emissions and fine particulate matter: some evidence in Lombardy

  • Alessandro Fusta Moro
  • Matteo Salis
  • Andrea Zucchi
  • Michela Cameletti
  • Natalia Golini
  • Rosaria Ignaccolo

Lombardy is one of the most polluted regions at the European level, also due to its particular geographical structure and weather conditions which prevent the pollutants’ dispersion, and the high levels of emissions coming from human activities. Recently, some evidence has been found regarding the relationship between agriculture and air quality, particularly between ammonia - produced mainly by the livestock sector - and particulate matter concentrations. In this respect, Lombardy is the first Italian region for agriculture production, having 69% of its area classified as agricultural land and about 245 swine and 92 bovines per rural km2. In the Agriculture Impact On Italian Air project (AgrImOnIA, https://agrimonia.net, funded by Fondazione Cariplo within the framework of Data Science for science and society), we aim to predict continuously in space (i.e. mapping) air pollutants concentrations in Lombardy region, taking into account meteorology, land use and emissions coming from agriculture. In this regard, data integration and harmonization process have been carried out starting from data from different sources and characterized by different spatial and temporal resolutions. The first results are based on spatio-temporal Kriging models, with external drift, and an extension of the traditional random forest algorithm to consider the spatial and temporal correlation. These models will be used to generate scenario analysis which simulates the impact of policy interventions in the agricultural sector to mitigate its environmental impact on air quality.

  • Keywords:
  • Spatio-temporal Kriging,
  • Random Forest,
  • Predictive modeling,
  • Air quality,
  • Agriculture emissions,
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Alessandro Fusta Moro

University of Turin, Italy - ORCID: 0000-0003-1129-5038

Matteo Salis

University of Turin, Italy

Andrea Zucchi

University of Turin, Italy

Michela Cameletti

University of Bergamo, Italy - ORCID: 0000-0002-6502-7779

Natalia Golini

University of Turin, Italy - ORCID: 0000-0003-4457-5781

Rosaria Ignaccolo

University of Turin, Italy - ORCID: 0000-0003-2998-1714

  1. Cameletti, M., Ignaccolo, R., and Bande, S. (2011). Comparing spatio-temporal models for particulate matter in Piemonte. Environmetrics, 22(8):985–996.
  2. Gr¨aler, B., Pebesma, E., and Heuvelink, G. (2016). Spatio-Temporal Interpolation using gstat. The R Journal, 8(1):204–218.
  3. Gu, B., Zhang, L., Dingenen, R. V., Vieno, M., Grinsven, H. J. V., Zhang, X., Zhang, S., Chen, Y., Wang, S., Ren, C., Rao, S., Holland, M., Winiwarter, W., Chen, D., Xu, J., and Sutton, M. A. (2021). Abating ammonia is more cost-effective than nitrogen ox
  4. Hengl, T., Nussbaum, M., Wright, M. N., Heuvelink, G. B., and Gr¨aler, B. (2018). Random forestbas a generic framework for predictive modeling of spatial and spatio-temporal variables.bPeerJ, 6:e5518.
  5. INEMAR - ARPA Lombardia (2022). INEMAR, Inventario Emissioni in Atmosfera: emissioni in Regione Lombardia nell’anno 2019 - versione in revisione pubblica. ARPA Lombardia Settore Monitoraggi Ambientali. https://www.inemar.eu/xwiki/bin/view/InemarDatiWeb/In
  6. Thunis, P., Clappier, A., Beekmann, M., Putaud, J. P., Cuvelier, C., Madrazo, J., and de Meij, A. (2021). Non-linear response of PM2.5 to changes in NOX and NH3 emissions in the Po basin (Italy): consequences for air quality plans. Atmospheric Chemistry a
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  • Publication Year: 2023
  • Pages: 227-232
  • Content License: CC BY 4.0
  • © 2023 Author(s)

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  • Publication Year: 2023
  • Content License: CC BY 4.0
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Chapter Information

Chapter Title

Ammonia emissions and fine particulate matter: some evidence in Lombardy

Authors

Alessandro Fusta Moro, Matteo Salis, Andrea Zucchi, Michela Cameletti, Natalia Golini, Rosaria Ignaccolo

Language

English

DOI

10.36253/979-12-215-0106-3.40

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

ASA 2022 Data-Driven Decision Making

Book Subtitle

Book of short papers

Editors

Enrico di Bella, Luigi Fabbris, Corrado Lagazio

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press, Genova University Press

DOI

10.36253/979-12-215-0106-3

eISBN (pdf)

979-12-215-0106-3

eISBN (xml)

979-12-215-0107-0

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

46

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