A Novel Hyperspectral Remote Sensing Technique with Hour-Hectometer Level Horizontal Distribution of Trace Gases: To Accurately Identify Emission Sources

Author:

Lu Chuan12,Li Qihua3,Xing Chengzhi1,Hu Qihou1,Tan Wei1,Lin Hua12,Lin Jinan12,Zhang Zhiguo2,Chang Bowen3,Liu Cheng245ORCID

Affiliation:

1. Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.

2. Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.

3. Institutes of Physical Science and Information Technology, Anhui University, Hefei 230039, China.

4. Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China.

5. Anhui Province Key Laboratory of Polar Environment and Global Change, University of Science and Technology of China, Hefei 230026, China.

Abstract

High spatial-temporal resolution distribution of atmospheric gaseous pollutant is an important basis for tracing its emission, transport, and transformation. Typical methods for acquiring regional atmospheric gaseous pollutant distributions are satellite remote sensing and in situ observations. However, these approaches have limitations, such as sparse overpass times for satellites and restricted coverage for in situ monitoring. In this study, we propose a method for the long-term detection of the horizontal distribution of trace gases. This method based on effective optical paths (EOPs) as the instrument's detection range. It acquires the average trace gas concentration along the EOPs by utilizing different detection distances within the ultraviolet (UV) and visible (VIS) spectral bands. Subsequently, we use the onion-peeling method to obtain trace gas concentrations at two distinct distances. The obtained trace gas horizontal distribution was consistent with the in situ and mobile measurements. Compared with satellite remote sensing, this method achieved horizontal distribution results with higher spatial and temporal resolutions, and located several small high-value areas in Hefei, China. The tropospheric NO 2 vertical column density (VCD) results of the satellite at transit time (13:30) were consistent with the hyperspectral NO 2 horizontal distribution results at 13:00 to 14:00 on the same day but were not consistent with the daily average NO 2 results. The hourly NO 2 concentration in each area was 10% to 40% lower than the daytime average obtained by the hyperspectral remote sensing result. We evaluated the errors associated with the calculation of NO 2 emissions based on the satellite results and found a bias of approximately 69.45% to 83.34%. The spatial distribution of NO 2 concentration obtained from MAX-DOAS measurements may help in future bottom-up emission calculations.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

General Engineering

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