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基于氨挥发因子方法的中国农田氨排放量估算
引用本文:谢梓豪,樊品镐,武华,程琨,潘根兴.基于氨挥发因子方法的中国农田氨排放量估算[J].环境科学学报,2020,40(11):4180-4188.
作者姓名:谢梓豪  樊品镐  武华  程琨  潘根兴
作者单位:南京农业大学资源与环境科学学院,南京210095,南京农业大学资源与环境科学学院,南京210095,南京农业大学资源与环境科学学院,南京210095,南京农业大学资源与环境科学学院,南京210095,南京农业大学资源与环境科学学院,南京210095
基金项目:江苏高校品牌专业建设工程资助项目(No.PPZY2015A061);南京农业大学大学生创新创业训练计划项目(No.1913A22);国家自然科学基金面上项目(No.41877546)
摘    要:农田是氨的主要排放源,估算农田的氨挥发量可以明确其潜在的生态环境风险,为制定农田氨减排策略提供科学依据.通过文献收集,建立了包含867对观测值的中国农田氨挥发数据库,然后以氮肥施用量为自变量,氮肥施用引起的氨排放量为因变量,计算得到体现农业区、作物类型、肥料类型、土壤pH差异的氨挥发因子,采用独立样本进行验证,发现计算得到的氨挥发因子可以无偏地、较为准确地估算中国农田的氨挥发.不同区域、作物和管理措施下的氨挥发因子有显著差异,整体上,由于南方地区年均温和年降雨量均高于北方,导致南方的氨挥发因子高于北方,而碱性土壤的氨挥发因子高于中性和酸性土壤;与单施化肥相比,多数情况下施用有机肥可降低氨挥发因子,使用缓释控释肥或抑制剂可显著降低氨挥发因子;以单施化肥为例,水稻种植的氨挥发因子为9.9%~37.0%,高于蔬菜(2.2%~13.0%)和其他作物(3.3%~8.0%).2015年中国农田由无机氮肥使用引起的氨排放总量为3.21 Tg,95%置信区间为2.92~3.46 Tg,其中,粮食作物和蔬菜占比最高,分别为66%和20%,豆科作物占比最低(0.8%).由于气候、土壤、作物类型的差异,氨挥发呈现明显的空间异质性,长江中下游区排放量最高,而青藏区排放量最低.

关 键 词:氨挥发  农田  挥发因子  氮肥  空间异质性
收稿时间:2020/3/16 0:00:00
修稿时间:2020/5/15 0:00:00

Deriving volatile factors and estimating direct ammonia emissions for crop cultivation in China
XIE Zihao,FAN Pinhao,WU Hu,CHENG Kun,PAN Genxing.Deriving volatile factors and estimating direct ammonia emissions for crop cultivation in China[J].Acta Scientiae Circumstantiae,2020,40(11):4180-4188.
Authors:XIE Zihao  FAN Pinhao  WU Hu  CHENG Kun  PAN Genxing
Institution:College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095
Abstract:The increase in ammonia concentration in the atmosphere will affect human health and ecosystem quality, while farmland is the main source of ammonia emissions. Estimating the amount of ammonia emissions in farmland can clarify its potential risks to ecosystem, and provide a scientific basis for formulating farmland ammonia emissions reduction strategies. Through literature collection, a database consisting of 867 pairs of observations was established, of which 70% of observations were used to develop volatile factors, and 30% of observations were used to evaluate the accuracy of volatile factors. A linear regression method was performed to calculate the volatile factors, with nitrogen application rate as independent variable and ammonia emissions caused by nitrogen application as dependent variable. Ammonia volatile factors reflecting the differences in agricultural areas, crop types, fertilizer types and soil pH were developed. It was found that the determination coefficient (R2) was 0.41 and the simulating efficiency was 25%. There was no significant difference between the simulated and measured values, indicating that the developed ammonia volatile factor can accurately simulate the ammonia volatilization from farmland in China without bias. There were significant differences in ammonia volatile factors between different regions, crops and management measures. In general, the ammonia volatile factor in the south was higher than that in the north due to higher temperature and rainfall in the south than in the north. The volatile factor was higher in alkaline soils than in neutral and acid soils. Compared with mineral fertilizer application, in most cases, the application of organic fertilizer can reduce ammonia volatile factor, and the use of slow-release/controlled release fertilizer or inhibitor can significantly reduce ammonia volatile factor. Taking mineral fertilizer application as an example, the ammonia volatile factor of rice cultivation was 9.9%~37.0%, which was higher than that of vegetables (2.2%~13.0%) and other crops (3.3%~8.0%). In 2015, the total ammonia emissions caused by mineral nitrogen fertilizer application in Chinese farmland was estimated to be 3.21 Tg, with a 95% confidence interval of 2.92~3.46 Tg, of which grain crops and vegetables accounted for the highest proportion being 66% and 20%, respectively, and the lowest proportion was found in legume crops (0.8%). Due to differences in climate, soil, and crop types, ammonia volatilization exhibited significant spatial heterogeneity, with the highest emissions in Yangtze River agro-region and the lowest emissions in Qinghai-Tibet agro-region.
Keywords:ammonia volatilization  farmland  volatile factor  nitrogen fertilizer  spatial heterogeneity
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