TY  -  
T1  - Neural Network Analysis to Evaluate Ozone Damage to Vegetation Under Different Climatic Conditions 
SN  -  /  
UR  - http://hdl.handle.net/10138/318897 
T3  -  
A1  - Savi, Flavia; Nemitz, Eiko; Coyle, Mhairi; Aitkenhead, Matt; Frumau, Kfa; Gerosa, Giacomo; Finco, Angelo; Gruening, Carten; Goded, Ignacio; Loubet, Benjamin; Stella, Patrick; Ruuskanen, Taina; Weidinger, T.; Horvath, L.; Zenone, Terenzio; Fares, Silvano 
A2  -  
PB  -  
Y1  - 2020 
LA  - eng 
AB  - Tropospheric ozone (O-3) is probably the air pollutant most damaging to vegetation. Understanding how plants respond to O(3)pollution under different climate conditions is of central importance for predicting the interactions between climate change, ozone impact and vegetation. This work analyses the effect of O(3)fluxes on net ecosystem productivity (NEP), measured directly at the ecosystem level with the eddy covariance (EC) technique. The relationship was explored with artificial neural netwo... 
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KW  - 1172 Environmental sciences; 4112 Forestry; net ecosystem exchange; european forest; stomatal deposition; tropospheric ozone; artificial neural networks; climate change; STOMATAL CONDUCTANCE; PRIMARY PRODUCTIVITY; FLUX MEASUREMENTS; RISK-ASSESSMENT; CARBON-DIOXIDE; DEPOSITION; ECOSYSTEM; FOREST; GROWTH 
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