Deriving Emission Factors and Estimating Direct Nitrous Oxide Emissions for Crop Cultivation in China

Qian Yue, Hua Wu, Jianfei Sun, Kun Cheng (Corresponding Author), Pete Smith, Jon Hillier, Xiangrui Xu, Genxing Pan

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66–0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China’s crop cultivation were estimated to be 194 Gg N2O–N with a 95% confidence interval of 180–208 Gg N2O–N in the year 2016.
Original languageEnglish
Pages (from-to)10246-10257
Number of pages12
JournalEnvironmental Science & Technology
Volume53
Issue number17
Early online date31 Jul 2019
DOIs
Publication statusPublished - 3 Sep 2019

Fingerprint

Nitrous Oxide
nitrous oxide
Linear regression
Crops
crop
Fertilizers
Maximum likelihood
Refining
Rivers
Water
confidence interval
rice
wheat
maize
emission factor
fertilizer
river
method
Uncertainty
water

Keywords

  • agricultural soil
  • nitrous oxide
  • emission factor
  • agro-region
  • cropping system
  • N fertilizer

Cite this

Deriving Emission Factors and Estimating Direct Nitrous Oxide Emissions for Crop Cultivation in China. / Yue, Qian; Wu, Hua; Sun, Jianfei; Cheng, Kun (Corresponding Author); Smith, Pete; Hillier, Jon; Xu, Xiangrui; Pan, Genxing.

In: Environmental Science & Technology, Vol. 53, No. 17, 03.09.2019, p. 10246-10257.

Research output: Contribution to journalArticle

Yue, Qian ; Wu, Hua ; Sun, Jianfei ; Cheng, Kun ; Smith, Pete ; Hillier, Jon ; Xu, Xiangrui ; Pan, Genxing. / Deriving Emission Factors and Estimating Direct Nitrous Oxide Emissions for Crop Cultivation in China. In: Environmental Science & Technology. 2019 ; Vol. 53, No. 17. pp. 10246-10257.
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abstract = "Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70{\%} of the observations. The remaining 30{\%} of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66–0.92{\%} in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China’s crop cultivation were estimated to be 194 Gg N2O–N with a 95{\%} confidence interval of 180–208 Gg N2O–N in the year 2016.",
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note = "ACKNOWLEDGMENTS This work was financially supported by Natural Science Foundation of China under a grant numbers 41877546 and U1612441. This work also contributes to the activities of NCircle, a BBSRC-Newton Funded project (BB/N013484/1), and National Key Research and Development Program of China (2016YFD0300908-02). Q.Y. thanks the China Scholarship Council (CSC) for funding to support study at the University of Aberdeen, U.K.",
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AU - Yue, Qian

AU - Wu, Hua

AU - Sun, Jianfei

AU - Cheng, Kun

AU - Smith, Pete

AU - Hillier, Jon

AU - Xu, Xiangrui

AU - Pan, Genxing

N1 - ACKNOWLEDGMENTS This work was financially supported by Natural Science Foundation of China under a grant numbers 41877546 and U1612441. This work also contributes to the activities of NCircle, a BBSRC-Newton Funded project (BB/N013484/1), and National Key Research and Development Program of China (2016YFD0300908-02). Q.Y. thanks the China Scholarship Council (CSC) for funding to support study at the University of Aberdeen, U.K.

PY - 2019/9/3

Y1 - 2019/9/3

N2 - Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66–0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China’s crop cultivation were estimated to be 194 Gg N2O–N with a 95% confidence interval of 180–208 Gg N2O–N in the year 2016.

AB - Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66–0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China’s crop cultivation were estimated to be 194 Gg N2O–N with a 95% confidence interval of 180–208 Gg N2O–N in the year 2016.

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KW - cropping system

KW - N fertilizer

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