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Effects of Environmental Factors on Ozone Flux over a Wheat Field Modeled with an Artificial Neural Network
Zhu, Zhilin1,2
2019
Source PublicationADVANCES IN METEOROLOGY
ISSN1687-9309
Pages11
Corresponding AuthorZhu, Zhilin(zhuzl@igsnrr.ac.cn)
AbstractOzone (O-3) flux-based indices are considered better than O-3 concentration-based indices in assessing the effects of ground O-3 on ecosystem and crop yields. However, O-3 flux (F-o) measurements are often lacking due to technical reasons and environmental conditions. This hampers the calculation of flux-based indices. In this paper, an artificial neural network (ANN) method was attempted to simulate the relationships between F-o and environmental factors measured over a wheat field in Yucheng, China. The results show that the ANN-modeled F-o values were in good agreement with the measured F-o values. The R-2 of an ANN model with 6 routine independent environmental variables exceeded 0.8 for training datasets, and the RMSE and MAE were 3.074nmolm(-2)s and 2.276nmolm(-2)s for test dataset, respectively. CO2 flux and water vapor flux have strong correlations with F-o and could improve the fitness of ANN models. Besides the combinations of included variables and selection of training data, the number of neurons is also a source of uncertainties in an ANN model. The fitness of the modeled F-o was sensitive to the neuron number when it ranged from 1 to 10. The ANN model consists of complex arithmetic expressions between F-o and independent variables, and the response analysis shows that the model can reflect their basic physical relationships and importance. O-3 concentration, global radiation, and wind speed are the important factors affecting O-3 deposition. ANN methods exhibit significant value for filling the gaps of F-o measured with micrometeorological methods.
DOI10.1155/2019/1257910
WOS KeywordDRY
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41675147] ; National Key R&D program of China[2017YFC0503801]
Funding OrganizationNational Natural Science Foundation of China ; National Key R&D program of China
WOS Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000471969600001
PublisherHINDAWI LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/58902
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhu, Zhilin
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Zhilin. Effects of Environmental Factors on Ozone Flux over a Wheat Field Modeled with an Artificial Neural Network[J]. ADVANCES IN METEOROLOGY,2019:11.
APA Zhu, Zhilin.(2019).Effects of Environmental Factors on Ozone Flux over a Wheat Field Modeled with an Artificial Neural Network.ADVANCES IN METEOROLOGY,11.
MLA Zhu, Zhilin."Effects of Environmental Factors on Ozone Flux over a Wheat Field Modeled with an Artificial Neural Network".ADVANCES IN METEOROLOGY (2019):11.
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