Impact of parameterization choices on the restitution of ozone deposition over vegetation. Le Morvan-Quéméner, A., Coll, I., Kammer, J., Lamaud, E., Loubet, B., Personne, E., & Stella, P. Atmospheric Environment, 178(December 2017):49-65, Elsevier, 2018.
Impact of parameterization choices on the restitution of ozone deposition over vegetation [link]Website  doi  abstract   bibtex   
Ozone is a potentially phyto-toxic air pollutant, which can cause leaf damage and drastically alter crop yields, causing serious economic losses around the world. The VULNOZ (VULNerability to OZone in Anthropised Ecosystems) project is a biology and modeling project that aims to understand how plants respond to the stress of high ozone concentrations, then use a set of models to (i) predict the impact of ozone on plant growth, (ii) represent ozone deposition fluxes to vegetation, and finally (iii) estimate the economic consequences of an increasing ozone background the future. In this work, as part of the VULNOZ project, an innovative representation of ozone deposition to vegetation was developed and implemented in the CHIMERE regional chemistry-transport model. This type of model calculates the average amount of ozone deposited on a parcel each hour, as well as the integrated amount of ozone deposited to the surface at the regional or country level. Our new approach was based on a refinement of the representation of crop types in the model and the use of empirical parameters specific to each crop category. The results obtained were compared with a conventional ozone deposition modeling approach, and evaluated against observations from several agricultural areas in France. They showed that a better representation of the distribution between stomatal and non-stomatal ozone fluxes was obtained in the empirical approach, and they allowed us to produce a new estimate of the total amount of ozone deposited on the subtypes of vegetation at the national level.
@article{
 title = {Impact of parameterization choices on the restitution of ozone deposition over vegetation},
 type = {article},
 year = {2018},
 keywords = {FR_GRI,FR_HES,FR_LBR,FR_LUS},
 pages = {49-65},
 volume = {178},
 websites = {https://doi.org/10.1016/j.atmosenv.2018.01.003},
 publisher = {Elsevier},
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 last_modified = {2020-09-08T15:25:48.199Z},
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 abstract = {Ozone is a potentially phyto-toxic air pollutant, which can cause leaf damage and drastically alter crop yields, causing serious economic losses around the world. The VULNOZ (VULNerability to OZone in Anthropised Ecosystems) project is a biology and modeling project that aims to understand how plants respond to the stress of high ozone concentrations, then use a set of models to (i) predict the impact of ozone on plant growth, (ii) represent ozone deposition fluxes to vegetation, and finally (iii) estimate the economic consequences of an increasing ozone background the future. In this work, as part of the VULNOZ project, an innovative representation of ozone deposition to vegetation was developed and implemented in the CHIMERE regional chemistry-transport model. This type of model calculates the average amount of ozone deposited on a parcel each hour, as well as the integrated amount of ozone deposited to the surface at the regional or country level. Our new approach was based on a refinement of the representation of crop types in the model and the use of empirical parameters specific to each crop category. The results obtained were compared with a conventional ozone deposition modeling approach, and evaluated against observations from several agricultural areas in France. They showed that a better representation of the distribution between stomatal and non-stomatal ozone fluxes was obtained in the empirical approach, and they allowed us to produce a new estimate of the total amount of ozone deposited on the subtypes of vegetation at the national level.},
 bibtype = {article},
 author = {Le Morvan-Quéméner, Aurélie and Coll, Isabelle and Kammer, Julien and Lamaud, Eric and Loubet, Benjamin and Personne, Erwan and Stella, Patrick},
 doi = {10.1016/j.atmosenv.2018.01.003},
 journal = {Atmospheric Environment},
 number = {December 2017}
}

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