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基于地基高分辨率太阳吸收光谱观测大气中硝酸的时空分布

章惠芳1,2 王薇2 刘诚3 单昌功2 胡启后2 孙友文2 Nicholas Jones4

(1.安徽大学物质科学与信息技术研究院, 安徽合肥 230601)
(2.中国科学院合肥物质科学研究院安徽光学精密机械研究所环境光学与技术重点实验室, 安徽合肥 230031)
(3.中国科学技术大学地球和空间科学学院, 安徽合肥 230026)
(4.School of Chemistry,University of Wollongong,Wollongong, New South Wales 2522,Australia)

【摘要】利用高分辨率傅里叶变换红外光谱(FTIR)技术探测合肥地区大气硝酸(HNO3)的浓度,基于最优估算法由中红外太阳吸收光谱反演出HNO3的垂直廓线和柱总量。获得了2017年大气HNO3的垂直廓线和柱总量的时间序列,分析了HNO3的季节变化、浓度探测敏感性高度、反演平均核和自由度等特征。不同季节大气HNO3的垂直廓线表明,HNO3在20~30km的大气平流层浓度较高,在对流层浓度较低。HNO3的柱浓度显示出明显的季节变化,春季出现最大值,冬季出现最小值,季节变化幅值为9.82×1015 molecule/cm2。为了对地基FTIR的观测进行比对,选取Aura MLS卫星数据产品与地基测量数据进行比对。比对结果表明,地基遥感观测与卫星数据显示出的季节变化一致;尽管卫星偏柱量整体小于地基遥感的柱总量,但两者的相关系数为0.83,表明两者具有较好的一致性。地基观测结果验证了地基FTIR技术观测大气中HNO3时空分布的可靠性和准确性。

【关键词】 大气光学;傅里叶变换红外光谱技术;硝酸;垂直廓线;柱浓度;

【DOI】

【基金资助】 国家自然科学基金(41775025,41405134,41575021,91544212,41605018,41877309); 国家重点研发计划(2018YFC0213201,2016YFC0200404,2016YFC0203302,2017YFC0210002,2016YFC0200800); 广东省自然科学基金(2016A030310117); 国家高分辨率对地观测重大科技专项(05-Y30B01-9001-19/20-3);

Detection of Temporal and Spatial Distributions of Atmospheric Nitric Acid Based on Ground-Based High-Resolution Solar Absorption Spectra

ZHANG Huifang1,2 WANG Wei2 LIU Cheng3 SHAN Changgong2 HU Qihou2 SUN Youwen2 Nicholas Jones4

(1.Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui, China 230601)
(2.Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, China 230031)
(3.School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui, China 230026)
(4.School of Chemistry, University of Wollongong, Wollongong, New South Wales 2522, Australia)

【Abstract】In this study, the high-resolution Fourier transform infrared spectroscopy (FTIR) is used to detect the concentrations of nitric acid (HNO3) in the atmosphere above the Hefei site. The vertical profiles and total columns of HNO3 are retrieved from the mid-infrared solar absorption spectra using the optimal estimation method. The vertical profiles and time series of the total columns of atmospheric HNO3 are obtained over the entire year of 2017. Further, the characteristics of the seasonal variation of HNO3, sensitivity altitude of concentration detection, averaging kernels of retrieved profiles, and degrees of freedom are analyzed. The vertical profiles of atmospheric HNO3 in different seasons denote that the HNO3 concentrations are higher at an altitude of 20–30 km in the stratosphere and that they are lower in the troposphere. Furthermore, the total columns of HNO3 exhibit obvious seasonal variations, with a maximum in spring and minimum in winter. The amplitude of the seasonal variations is 9.82 × 1015 molecule/cm2. The data products obtained from the Aura MLS satellite are selected for performing a comparison with the ground-based data to validate the measurements of the ground-based FTIR using independent data. The comparison results denote that the ground-based remote sensing and satellite observations display a consistent seasonal HNO3 variability. The ground-based data exhibit a good agreement with the satellite data with a high correlation coefficient of 0.83 even though the partial columns of the satellite data are lower than the corresponding ground-based total columns. The observation results indicate the reliability and accuracy of the ground-based FTIR for observing the temporal and spatial distributions of the atmospheric HNO3.

【Keywords】 atmospheric optics; Fourier transform infrared spectroscopy; nitric acid; vertical profile; total column;

【DOI】

【Funds】 National Natural Science Foundation of China (41775025, 41405134, 41575021, 91544212, 41605018, 41877309); National Key Research and Development program (2018YFC0213201, 2016YFC0200404, 2016YFC0203302, 2017YFC0210002, 2016YFC0200800); Natural Science Foundation of Guangdong Province (2016A030310117); National Major Science and Technology Project of High-resolution Earth Observation (05-Y30B01-9001-19/20-3);

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This Article

ISSN:0253-2239

CN: 31-1252/O4

Vol 40, No. 02, Pages 23-33

January 2020

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Article Outline

Abstract

  • 1 Introduction
  • 2 Observation methods
  • 3 Results and discussion
  • 4 Conclusion
  • References