Effects of Environmental Factors on Ozone Flux over a Wheat Field Modeled with an Artificial Neural Network

doi:10.1155/2019/1257910

IGSNRR OpenIR

	Effects of Environmental Factors on Ozone Flux over a Wheat Field Modeled with an Artificial Neural Network
	Zhu, Zhilin1,2
	2019
Source Publication	ADVANCES IN METEOROLOGY
ISSN	1687-9309
Pages	11
Corresponding Author	Zhu, Zhilin(zhuzl@igsnrr.ac.cn)
Abstract	Ozone (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.
DOI	10.1155/2019/1257910
WOS Keyword	DRY
Indexed By	SCI
Language	英语
Funding Project	National Natural Science Foundation of China[41675147] ; National Key R&D program of China[2017YFC0503801]
Funding Organization	National Natural Science Foundation of China ; National Key R&D program of China
WOS Research Area	Meteorology & Atmospheric Sciences
WOS Subject	Meteorology & Atmospheric Sciences
WOS ID	WOS:000471969600001
Publisher	HINDAWI LTD
Citation statistics	Cited Times:1[WOS] [WOS Record] [Related Records in WOS]
Document Type	期刊论文
Identifier	http://ir.igsnrr.ac.cn/handle/311030/58902
Collection	中国科学院地理科学与资源研究所
Corresponding Author	Zhu, Zhilin
Affiliation	1.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.

Files in This Item:
There are no files associated with this item.

If you have any objections to this item, please fill out the form below and the administrator will contact you as soon as possible.
Content:
Email：	*
Institution:
Verification Code:	Refresh

Any comments and suggestions are welcomed.
Title:	*
Content:
Email：	*
Verification Code:	Refresh

中国科学院地理科学与资源研究所机构知识库