基于红外光谱技术的秸秆还田环境下土壤氨挥发特征分析

研究氨近红外光谱特性并建立浓度反演算法模型, 重点优化相关性分析和温度修正功能.利用开放式激光吸收光谱技术建立氨区域监测系统, 于2015年在安徽涡阳秸秆还田示范区开展监测实验, 研究玉米和小麦种植情况下的土壤氨挥发特征.研究结果表明, 氨浓度具有日变化趋势: 白天浓度上升在正午达到最高值, 逐步降低到夜间至最小值.夏、秋季典型小时浓度变化范围为0.6×10-3 ~1.34×10-3 mmol/mol和1.14×10-3~1.82×10-3 mmol/mol, 秋季玉米和夏季小麦秸秆还田的最大氨日均浓度为4.6×10-4 mmol/mol和1.7×10-3 mmol/mol, 还田一个多月后氨浓度明显上升, 并存在一定季节性差异.近红外光谱技术为明晰土壤氨排放规律提供了技术支持.

Abstract

The infrared absorption spectral characteristics of ammonia were studied. Moreover, the quantitative inversion algorithm model was established, especially the correlation analysis and temperature correction function were optimized. The ammonia volatilization experiment was carried out in the demonstration area in Guoyang, Anhui in 2015 by the ammonia regional monitoring system based on Open-path Tunable Diode Laser Absorption Spectroscopy (OP-TDLAS). Then, ammonia dynamic volatilization character of corn and wheat straw returning to the field was studied. The monitoring results show that the ammonia concentration has a certain diurnal variation trend: it increased during the daytime and got to the maximum value at midday, then reduced gradually at night to the minimum. The typical hourly concentration varied from 0.6×10-3 to 1.34×10-3 mmol/mol in summer, and it varied from 1.14×10-3 to 1.82×10-3 mmol/mol in autumn. In autumn, the maximum daily average of ammonia volatilization from corn straw returning was 4.6×10-4 mmol/mol, and it was 1.7×10-3 mmol/mol from wheat straw returning in summer. The results indicate that the emission concentration rises significantly after more than one month of straw returning which has some certain seasonal difference in farmland scale. This infrared spectroscopy technology provides technical support for clarifying the ammonia emission rules in soil environment.

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何莹, 张玉钧, 尤坤, 高彦伟, 赵南京, 刘文清. 基于红外光谱技术的秸秆还田环境下土壤氨挥发特征分析[J]. 红外与毫米波学报, 2017, 36(4): 397. HE Ying, ZHANG Yu-Jun, YOU Kun, GAO Yan-Wei, ZHAO Nan-Jing, LIU Wen-Qing. Volatilization characteristics analysis of ammonia from soil by straw returning to the field based on the infrared spectroscopy technology[J]. Journal of Infrared and Millimeter Waves, 2017, 36(4): 397.

基于红外光谱技术的秸秆还田环境下土壤氨挥发特征分析

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