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

作     者：ZHANG Wei GU Jiang-Xin ZHENG Xun-Hua 

作者机构：State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC) Institute of Atmospheric Physics Chinese Academy of Sciences University of Chinese Academy of Sciences College of Natural Resources and Environment Northwest A & F University 

出 版 物：《Atmospheric and Oceanic Science Letters》 (大气和海洋科学快报（英文版）)

年 卷 期：2015年第8卷第5期

页      面：277-282页

核心收录：

学科分类：082803[工学-农业生物环境与能源工程] 07[理学] 08[工学] 0828[工学-农业工程] 070602[理学-大气物理学与大气环境] 09[农学] 0903[农学-农业资源与环境] 0706[理学-大气科学] 

基　　金：supported by the Ministry of Science and Technology(Grant No. 2012CB417106) the National Natural Science Foundation of China(Grant No. 41321064) 

主　　题：nitrous oxide direct emissions empirical model nit 

摘      要：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.