Towards improving top-down national CO2 estimation in Europe : potential from expanding the ICOS atmospheric network in Italy
(2025) In Environmental Research Letters 20(5).- Abstract
This study investigates the requirements for estimating CO2 emissions at the country scale using observational data from the Integrated Carbon Observation System (ICOS) atmosphere network, taking Italy as a case study. In particular, we explore the potential expansion of Italy’s current atmospheric ICOS network by identifying additional existing and future stations that would most effectively improve the constraint of carbon flux estimations, with a focus on the southern region. Through a series of Observing System Simulation Experiments using the LUMIA regional inverse system, we evaluated 23 potential stations and identified Chieti (CHI, located in the Abruzzo region in mid-Italy) and Lecce (ECO, located in the southeastern... (More)
This study investigates the requirements for estimating CO2 emissions at the country scale using observational data from the Integrated Carbon Observation System (ICOS) atmosphere network, taking Italy as a case study. In particular, we explore the potential expansion of Italy’s current atmospheric ICOS network by identifying additional existing and future stations that would most effectively improve the constraint of carbon flux estimations, with a focus on the southern region. Through a series of Observing System Simulation Experiments using the LUMIA regional inverse system, we evaluated 23 potential stations and identified Chieti (CHI, located in the Abruzzo region in mid-Italy) and Lecce (ECO, located in the southeastern Puglia region) as the most promising additions. These stations demonstrated significant value in recovering the annual and seasonal cycles of the assumed true CO2 fluxes (simulated by LPJ-GUESS) in southern Italy. Incorporating both CHI and ECO into the current network reduces the prior biases by approximately 82%, compared to the 48% reduction achieved when adding the CHI station alone. Our findings also suggest that adding more stations beyond CHI and ECO results in only marginal gains in flux precision. We therefore emphasize the need for targeted research funding to support the integration of these current and future stations into the ICOS atmospheric network in southern Italy, where the current network is sparse, with only Potenza as an ICOS atmospheric station. This research highlights the importance of strategic station selection to optimize network performance and improve regional carbon flux assessments, ultimately contributing to better reconciliation and understanding of discrepancies between bottom-up and top-down greenhouse gas estimation methods.
(Less)
- author
- Villalobos, Yohanna
LU
; Gómez-Ortiz, Carlos LU
; Scholze, Marko LU
; Monteil, Guillaume ; Karstens, Ute LU
; Fiore, Angela ; Brunner, Dominik ; Thanwerdas, Joël and Cristofanelli, Paolo
- organization
- publishing date
- 2025-05-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- atmospheric network design, carbon cycle, carbon dioxide, data assimilation, inverse modelling
- in
- Environmental Research Letters
- volume
- 20
- issue
- 5
- article number
- 054002
- pages
- 12 pages
- publisher
- IOP Publishing
- external identifiers
-
- scopus:105002227866
- ISSN
- 1748-9326
- DOI
- 10.1088/1748-9326/adc41e
- language
- English
- LU publication?
- yes
- id
- ceb92b84-51b4-4283-ae55-cb6ff0a86c66
- date added to LUP
- 2025-04-09 12:52:40
- date last changed
- 2025-06-02 09:53:49
@article{ceb92b84-51b4-4283-ae55-cb6ff0a86c66, abstract = {{<p>This study investigates the requirements for estimating CO<sub>2</sub> emissions at the country scale using observational data from the Integrated Carbon Observation System (ICOS) atmosphere network, taking Italy as a case study. In particular, we explore the potential expansion of Italy’s current atmospheric ICOS network by identifying additional existing and future stations that would most effectively improve the constraint of carbon flux estimations, with a focus on the southern region. Through a series of Observing System Simulation Experiments using the LUMIA regional inverse system, we evaluated 23 potential stations and identified Chieti (CHI, located in the Abruzzo region in mid-Italy) and Lecce (ECO, located in the southeastern Puglia region) as the most promising additions. These stations demonstrated significant value in recovering the annual and seasonal cycles of the assumed true CO<sub>2</sub> fluxes (simulated by LPJ-GUESS) in southern Italy. Incorporating both CHI and ECO into the current network reduces the prior biases by approximately 82%, compared to the 48% reduction achieved when adding the CHI station alone. Our findings also suggest that adding more stations beyond CHI and ECO results in only marginal gains in flux precision. We therefore emphasize the need for targeted research funding to support the integration of these current and future stations into the ICOS atmospheric network in southern Italy, where the current network is sparse, with only Potenza as an ICOS atmospheric station. This research highlights the importance of strategic station selection to optimize network performance and improve regional carbon flux assessments, ultimately contributing to better reconciliation and understanding of discrepancies between bottom-up and top-down greenhouse gas estimation methods.</p>}}, author = {{Villalobos, Yohanna and Gómez-Ortiz, Carlos and Scholze, Marko and Monteil, Guillaume and Karstens, Ute and Fiore, Angela and Brunner, Dominik and Thanwerdas, Joël and Cristofanelli, Paolo}}, issn = {{1748-9326}}, keywords = {{atmospheric network design; carbon cycle; carbon dioxide; data assimilation; inverse modelling}}, language = {{eng}}, month = {{05}}, number = {{5}}, publisher = {{IOP Publishing}}, series = {{Environmental Research Letters}}, title = {{Towards improving top-down national CO<sub>2</sub> estimation in Europe : potential from expanding the ICOS atmospheric network in Italy}}, url = {{http://dx.doi.org/10.1088/1748-9326/adc41e}}, doi = {{10.1088/1748-9326/adc41e}}, volume = {{20}}, year = {{2025}}, }