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中国作物种植中排放系数的推导和直接一氧化二氮排放的估算。

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

机构信息

Institute of Resource, Ecosystem and Environment of Agriculture , Nanjing Agricultural University , 1 Weigang , Nanjing , Jiangsu 210095 , China.

Key Laboratory for Crop and Animal Integrated Farming of Ministry of Agriculture and Rural Affairs/Recycling Agriculture Research Center , Jiangsu Academy of Agricultural Sciences , Nanjing 210014 , China.

出版信息

Environ Sci Technol. 2019 Sep 3;53(17):10246-10257. doi: 10.1021/acs.est.9b01285. Epub 2019 Aug 23.

Abstract

Updating and refining the NO emission factors (NO-EFs) are vital to reduce the uncertainty in estimates of direct NO emissions. Based on a database with 1151 field measurements across China, the NO-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 NO-EFs. The third method had the highest 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 NO-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher NO-EFs in maize and wheat seasons than other regions, and the highest NO-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 NO-EFs. Based on the best estimation by the selected method, direct NO emissions from China's crop cultivation were estimated to be 194 Gg NO-N with a 95% confidence interval of 180-208 Gg NO-N in the year 2016.

摘要

更新和完善氮氧化物排放因子(NO-EFs)对于降低直接氮氧化物排放估算的不确定性至关重要。本研究基于包含中国 1151 个田间测量的数据库,采用三种方法建立了 NO-EFs,包括最大似然法、带有截距的线性回归和截距为 0 的线性回归,其中 70%的观测值用于建立模型,其余 30%的观测值用于评估预测的 NO-EFs。第三种方法的拟合优度最高(0.39),模型效率最高(0.38),且不存在显著偏差,表明其计算效率最佳。结果表明,NO-EFs 随农业区、作物和管理模式而异。黄淮海和长江农业区的玉米和小麦季 NO-EFs 高于其他地区,而南方和西南农业区的水稻季 NO-EFs 最高可达 0.66-0.92%。肥料类型和水分管理模式对 NO-EFs 有显著影响。基于所选方法的最佳估计,2016 年中国作物种植的直接氮氧化物排放量估计为 194 Gg NO-N,置信区间为 180-208 Gg NO-N。

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