Next Article in Journal
On-Board Georeferencing Using FPGA-Based Optimized Second-Order Polynomial Equation
Previous Article in Journal
Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring
Previous Article in Special Issue
Assessing Effect of Targeting Reduction of PM2.5 Concentration on Human Exposure and Health Burden in Hong Kong Using Satellite Observation
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2019, 11(2), 123; https://doi.org/10.3390/rs11020123

Observation of CO2 Regional Distribution Using an Airborne Infrared Remote Sensing Spectrometer (Air-IRSS) in the North China Plain

1,2
,
1,3,4,* , 1,* , 1
and
1,*
1
Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
2
University of Science and Technology of China, Hefei 230026, China
3
CAS Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
4
University of Chinese Academy of Sciences, Beijing 100049, China
*
Authors to whom correspondence should be addressed.
Received: 12 November 2018 / Revised: 7 January 2019 / Accepted: 8 January 2019 / Published: 10 January 2019
Full-Text   |   PDF [5519 KB, uploaded 14 January 2019]   |  

Abstract

Carbon dioxide (CO2) is one of the most important anthropogenic greenhouse gases (GHG) and significantly affects the energy balance of atmospheric systems. Larger coverage and higher spatial resolution of CO2 measurements can complement the existing in situ network and satellite measurements and thus improve our understanding of the global carbon cycle. In this study, we present a self-made airborne infrared remote sensing spectrometer (Air-IRSS) designed to determine the regional distribution of CO2. The Air-IRSS measured CO2 in the spectral range between 1590 and 1620 nm at a spectral resolution of 0.45 nm and an exposure time of 1 s. It was operated onboard an aircraft at a height of 3 km with a velocity of 180 km/h, and a spatial resolution of 50.00 m × 62.80 m. Weighting function modified differential optical absorption spectroscopy (WFM-DOAS) was used to analyze the measured spectra. The results show that the total uncertainty estimated for the retrieval of the CO2 column was 1.26% for airborne measurements over a large region, and 0.30% for a fixed point, such as power points or factories. Under vibration-free static conditions, the on-ground Air-IRSS observations can adequately reproduce the variations observed by Greenhouse Gases Observing Satellite (GOSAT) with a correlation coefficient (r) of 0.72. Finally, we conducted an airborne field campaign to determine the regional distribution of CO2 over the North China Plain. The regional distribution of CO2 columns over four cities of Xing-tai, Hengshui, Shijiazhuang, and Baoding were obtained with the GPS information, which ranged from 2.00 × 1021 molec cm−2 to 3.00 × 1021 molec cm−2. The CO2 vertical distributions were almost uniform below a height of 3 km in the area without CO2 emission sources, and the highest values were found over Baoding City. View Full-Text
Keywords: greenhouse gases; remote sensing; infrared DOAS; regional distribution; airborne-instrument greenhouse gases; remote sensing; infrared DOAS; regional distribution; airborne-instrument
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wang, R.; Xie, P.; Xu, J.; Li, A.; Sun, Y. Observation of CO2 Regional Distribution Using an Airborne Infrared Remote Sensing Spectrometer (Air-IRSS) in the North China Plain. Remote Sens. 2019, 11, 123.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top