Direct Nitrous Oxide Emissions Related to Fertilizer-Nitrogen, Precipitation, and Soil Clay Fraction: Empirical Models

Direct nitrous oxide(N2O) emissions(DNEs) from croplands are required in national inventories of greenhouse gases. The Intergovernmental Panel on Climate Change(IPCC) guidelines provide an approach using direct emission factors(EFds) to estimate DNEs, which are constants for large regions. The goal...

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Bibliographic Details
Published in:Atmospheric and oceanic science letters = Daqi-he-haiyang-kexue-kuaibao 2015, Vol.8 (5), p.277-282
Main Author: ZHANG Wei GU Jiang-Xin ZHENG Xun-Hua
Format: Article
Language:English
Subjects:
Agricultural land
Clay
clay fraction
Climate change
Constants
direct emissions
Emissions
emissions
empirical
empirical model
Environmental factors
Fertilizers
Gases
Greenhouse effect
Greenhouse gases
Intergovernmental Panel on Climate Change
Inventories
model
nit
Nitrogen
nitrogen addition
nitrous
Nitrous oxide
oxide
direct
Precipitation
Soil
Soil fertility
Spatial variations
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Summary:Direct nitrous oxide(N2O) emissions(DNEs) from croplands are required in national inventories of greenhouse gases. The Intergovernmental Panel on Climate Change(IPCC) guidelines provide an approach using direct emission factors(EFds) to estimate DNEs, which are constants for large regions. The goal of this paper is to establish empirical models to account for the temporal and spatial variations of EFds, which, apart from the nitrogen addition rate, also vary with a range of environmental factors, so as to enhance the accuracy of regional/national DNE estimates. Therefore, the seasonal/annual DNEs(n = 71) from upland croplands, which are the differences in N2 O emissions between fields with and without fertilizer-nitrogen addition, were used to statistically relate DNEs to regulating factors including the fertilizer-nitrogen addition rate(FN), and environmental(climate and soil) factors. The multivariate stepwise linear regression results showed positive combined effects of FN and clay fraction on DNEs(R2 = 0.61, p < 0.001). Furthermore, the nonlinear regression of FN, precipitation, and clay fraction was also adopted for prediction(R2 = 0.50, p < 0.001). Validation with an independent dataset(n = 31) suggested that both models were better predictors of DNEs than the IPCC model, which only depends on FN. These empirical models may provide simple but reliable approaches for compiling regional/national, and even global inventories of DNEs from croplands. However, both models were restricted to a limited sample size. Understandably, more field observations are still required to further validate the global applicability of these simple approaches.
ISSN:1674-2834
2376-6123
DOI:10.3878/AOSL20150025