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多平台遥感数据在东亚海域的应用:气溶胶特性和气溶胶类型。

Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types.

机构信息

College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai, 201306, China.

Estuarine and Oceanographic Mapping Engineering Research Center of Shanghai, Shanghai, 200123, China.

出版信息

Environ Sci Pollut Res Int. 2024 May;31(25):37175-37195. doi: 10.1007/s11356-024-33458-9. Epub 2024 May 20.

Abstract

It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)-Angstrom exponent (AE) method (AA1M), and AOD-AE method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.

摘要

为了监测和评估大气环境质量,探索东亚海域大气气溶胶的特征和规律非常重要。本研究基于气溶胶机器人网络(AERONET)、可见光红外成像辐射计(VIIRS)和云气溶胶激光雷达与红外探路卫星观测(CALIPSO)数据,采用图形分类法(FIGCM)、气溶胶光学厚度(AOD)-Angstrom 指数(AE)法(AA1M)和 AOD-AE 法(AA2M)研究了东亚海域气溶胶参数和类型的时空变化特征和差异。结果表明,东亚海域气溶胶特征和类型的季节变化趋势明显。秋、冬两季渤海-黄海和日本海的 AOD、体积浓度(Cv)和气溶胶有效半径(reff)较低,海洋型气溶胶出现频率较高。与渤海-黄海和日本海不同,人类活动在冬、夏、秋三季严重影响了东海和南海的空气质量。特别是在台北 CWB 站,从气溶胶参数和高生物质燃烧/城市工业(BB/UI)气溶胶来看,人类活动是台北 CWB 站高污染的一个重要因素。在 2020 年 3 月对渤海-黄海的安山和延世大学两个站点,采用 AA1M、FIGCM、AA2M 和 CALIPSO 的阈值分类方法对气溶胶类型进行了比较。结果表明,基于阈值分类方法的气溶胶类型通常具有更高的混合气溶胶结果,AA1M、FIGCM 和 AA2M 的海洋(MA)结果与 CALIPSO 的清洁海洋气溶胶结果较为接近。在空间尺度上比较 AA2M 和 CALIPSO 的结果,发现 CALIPSO 识别的清洁海洋气溶胶比例(0.38、0.48、0.82)与 AA2M 识别的东海、南海和西太平洋的 MA 比例(0.43、0.46、0.97)较为一致。

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