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全文摘要次数: 84 全文下载次数: 210
引用本文:

DOI:

10.11834/jrs.20211392

收稿日期:

2021-06-08

修改日期:

2021-09-18

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大气环境卫星遥感:污染气体和大气颗粒物协同观测综述
李正强1, 张莹1, 赵少华2, 张兴赢3,3, 林金泰4, 秦凯5, 刘诚6, 张元勋7
1.中国科学院空天信息创新研究院;2.生态环境部卫星环境应用中心;3.国家卫星气象中心环境卫星辐射定标与验证重点实验室;4.北京大学物理学院大气与海洋科学系;5.中国矿业大学环境与测绘学院;6.中国科学技术大学工程科学学院;7.中国科学院大学资源与环境学院
摘要:

空气污染作为一种重要的环境问题,直接影响人们的日常生活和身体健康。随着污染气体和颗粒物观测技术的逐步成熟,基于卫星平台的近地层大气污染物监测得到了快速的发展。本文概括性描述了大气环境关注的污染气体和大气颗粒物的主流遥感方法,对各方法的适用场景及优缺点进行了评述。我们发现,尽管差分吸收光谱方法对污染气体的监测十分有效,但最优估计算法可进一步从多光谱信息中提取部分污染气体(例如:臭氧、一氧化碳等)的分层信息,有助于更细致的刻画污染气体在整层大气中的垂直分布。对于大气颗粒物遥感方法,采用不同的技术手段进行地气解耦是算法的核心问题,增加光谱、角度、偏振以及时间序列信息都可有效增加算法的地气解耦能力。基于对污染气体和大气颗粒物反演算法的总结,本文从污染气体和颗粒物协同观测的角度对卫星平台及传感器的发展历程进行了梳理,论述了紫外、红外以及可见光波段的传感器协同观测的优势,展望了未来静止卫星星座的高时空分辨率大气污染监测能力以及中国卫星的贡献。本文还探讨了以近地面大气污染物监测卫星探测技术及遥感算法亟待解决的问题以及未来的可能发展方向。

Satellite remote sensing of atmospheric environment: Review of atmospheric gaseous and particulate pollution collaborative observation
Abstract:

As an important environmental problem, air pollution directly affects daily life and physical health of public. With the gradual maturity of polluted gas and particulate matter observation technology, the monitoring of air pollutants near the surface based on satellite platforms has developed rapidly. The aim of this study is to clarify the collaborative observation’s history for aerosols and gases, and then provide reference for future satellite platform design. In this study, the popular remote sensing methods for trace gases and atmospheric particulates that are concerned about atmospheric environment are firstly described and discuss the applicable scenarios, advantages and disadvantages of each method. Next, satellite platforms for collaborative observations of trace gases and aerosols are reviewed. According to the characteristics of remote sensing principle for the trace gases, the satellite platform is divided into ultraviolet and infrared bands, and the development course of sensors and satellite platforms are discussed and analyzed. Finally, we discuss the issues to be solved urgently by satellite platforms and remote sensing algorithms aiming to monitor air pollutants near the ground, as well as possible future development directions. For various trace gases, the good universal remote sensing methods are differential absorption spectrometry method and optimal estimation algorithm, which can make full use of the absorption spectrum lines to achieve inversion of gases. Although the differential absorption spectroscopy method is very effective for the monitoring of trace gases, the optimized estimation algorithm can further extract the layered information of trace gases from the hyperspectral information, which is helpful for obtaining a more detailed vertical distribution of trace gases in the atmospheric column. Because the band residual method and linear fitting method have strong pertinence to specific pollutant gases (such as sulfur dioxide), these simplified algorithms also have great advantages and application value. The core issue of the aerosol inversion algorithm is the signal decoupling of ground and atmosphere. Adding the information from spectrum, angle, polarization and time series can effectively increase the decoupling capabilities. The algorithms derived from these principles include Dark Target algorithm, Deep Blue algorithm, Empirical Orthogonal Function algorithm, Polarization algorithm and Time series algorithm. Since the launch of NOAA-9 carrying SBUV/2 and AVHRR/2 in 1984, the collaborative detection of polluted gases and particulate matter has begun. Subsequently, Europe, the United States, South Korea and China have launched satellites carrying advanced sensors, from the polar orbit to geostationary orbit, and in the future, FY-4A of China, Geo-kompsat-2b of South Korea, Sentinel-4 of Europe and TEMPO of the United States can be forming a global geostationary satellite constellation with high spatial resolution and hourly monitoring capability to achieve collaborative monitoring of polluted gases and particulate matter. Based on the summary of trace gas and atmospheric aerosol inversion algorithms, the development history of satellite platforms and sensors is combed from the perspective of cooperative observation of gas and particulate matter, discussing the advantages of cooperative observation of sensors in the ultraviolet, visible and infrared bands, looking forward to the high temporal and spatial resolution air pollution monitoring capabilities of the geostationary satellite constellation in the future and the contribution of Chinese satellites.

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