黑碳(BC)作为可吸入颗粒物PM_(2.5)的重要组成部分,由于其特殊的理化性质,对大气环境和人类健康构成严重威胁。目前,我国尚未建立完善的大气黑碳浓度地面观测网络和数据共享体系,区域尺度黑碳浓度产品的精度验证和适用性评价比较有限。...黑碳(BC)作为可吸入颗粒物PM_(2.5)的重要组成部分,由于其特殊的理化性质,对大气环境和人类健康构成严重威胁。目前,我国尚未建立完善的大气黑碳浓度地面观测网络和数据共享体系,区域尺度黑碳浓度产品的精度验证和适用性评价比较有限。本文从已发表文献中提取我国126个站点的1616个BC月监测数据,时间跨度为2000−2020年,对MERRA-2(Modern-Era Retrospective Analysis for Research and Applications,Version 2)和TAP(Tracking Air Pollution in China)的BC数据进行全面的精度验证和适用性评价。结果表明:①MERRA-2与TAP均低估了我国大气BC浓度,其中MERRA-2低估程度为8.13%,TAP低估程度为19.51%。TAP的大气BC浓度与地面站点监测数据的相关性〔R=0.62,模拟实测两倍因子(FAC2)=0.69〕高于MERRA-2(R=0.46,FAC2=0.58),MERRA-2的20年平均大气BC浓度(3.61μg/m^(3))更接近地面站点平均大气BC浓度(3.97μg/m^(3))。②MERRA-2和TAP的大气BC浓度在我国不同地区的精度存在较大差别,MERRA-2在我国华北和西南地区的精度优于TAP。两个数据集在西南地区都有较高的精度(R为0.68~0.84,FAC2为0.71~0.79),在华北地区精度均较低(R为0.41~0.48,FAC2为0.64~0.77)。③MERRA-2与TAP大气BC浓度在全国大部分地区呈显著正相关,其中,二者在四川省大气BC浓度差异(0.0045μg/m^(3))最小,在北京市差异(2.11μg/m^(3))最大。研究显示,MERRA-2有更长的时间跨度,而TAP更能准确表现大气BC浓度的空间分布,且二者在不同地区表现出较大差异。展开更多
The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 a...The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 and SO4, in addition to the aerosol optical properties (AOD) were analyzed over the region of the Middle East and North Africa (MENA) from satellite and Modern Era-Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis data. The SO2 and SO4 data used in these analyses are obtained from (MERRA-2) with a resolution of 0.5° × 0.625° throughout a period of 10 years (2005-2015). On the other hand, the temporal trend and spatial distribution of AOD were identified from four different satellite data. 1) moderate-resolution imaging spectroradiometer (MODIS) Level 3 AOD data at 550 nm wavelengths from Collection 6 algorithm (combined dark target and deep blue algorithms) are used for 10 years temporal analysis (2006-2015). 2) Multi-angle imaging spectroradiometer (MISR) with 0.5 deg spatial resolution for the same 10 years (2006-2015). 3) Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) with 0.5 deg for the period (2005-2010). 4) Ozone Monitoring Instrument (OMI) AOD at 500 nm wavelength with resolution 1 degree. This study presents more resent 10 years of Spatiotemporal of SO2, SO4 and AOD over MENA domain.展开更多
遥感反演土壤水分(SM)产品越来越多地应用于农业、气象、水文等研究,而微波土壤水分数据产品的区域适用性分析是其合理使用的必要前提。使用MERRA-2(Modern Era Retrospective-analysis for Research and Applications,Version 2)模拟...遥感反演土壤水分(SM)产品越来越多地应用于农业、气象、水文等研究,而微波土壤水分数据产品的区域适用性分析是其合理使用的必要前提。使用MERRA-2(Modern Era Retrospective-analysis for Research and Applications,Version 2)模拟土壤水分为参考数据,运用传统统计方法(原始数据相关性、距平相关性、偏差以及无偏均方根差)和TC(Triple-Collocation)不确定性误差模型分析的方法,对亚洲区域2012年7月～2016年7月两种被动微波土壤水分SMOS-L3-SM(Soil Moisture and Ocean Salinity,L3)和AMSR2-LPRM-SM(The Advanced Microwave Scanning Radiometer 2,Land Parameter Retrieval Model Product)进行对比评估。结果表明:①空间上SMOS-L3较AMSR2-LPRM数据与参考数据MERRA-2土壤水分的相关性较好,表现为SMOS-L3-SM具有较好的空间连续性,且在亚洲大多数地区有较小的无偏均方根差;②湿季条件下遥感土壤水分与参考值的相关性比干季条件下的相关性更好,且干季出现高纬地区(约>55°)缺失值较多的情况;③两遥感土壤水分的TC误差呈现相似的分布,区域TC平均误差两者均为0.076 m^3/m^3。总之,SMOS-L3-SM和AMSR2-LPRM-SM在空间相关性及TC误差评价方面都具有合理性,为遥感土壤水分在农业、气象、水文等方面的应用提供参考。展开更多
文摘黑碳(BC)作为可吸入颗粒物PM_(2.5)的重要组成部分,由于其特殊的理化性质,对大气环境和人类健康构成严重威胁。目前,我国尚未建立完善的大气黑碳浓度地面观测网络和数据共享体系,区域尺度黑碳浓度产品的精度验证和适用性评价比较有限。本文从已发表文献中提取我国126个站点的1616个BC月监测数据,时间跨度为2000−2020年,对MERRA-2(Modern-Era Retrospective Analysis for Research and Applications,Version 2)和TAP(Tracking Air Pollution in China)的BC数据进行全面的精度验证和适用性评价。结果表明:①MERRA-2与TAP均低估了我国大气BC浓度,其中MERRA-2低估程度为8.13%,TAP低估程度为19.51%。TAP的大气BC浓度与地面站点监测数据的相关性〔R=0.62,模拟实测两倍因子(FAC2)=0.69〕高于MERRA-2(R=0.46,FAC2=0.58),MERRA-2的20年平均大气BC浓度(3.61μg/m^(3))更接近地面站点平均大气BC浓度(3.97μg/m^(3))。②MERRA-2和TAP的大气BC浓度在我国不同地区的精度存在较大差别,MERRA-2在我国华北和西南地区的精度优于TAP。两个数据集在西南地区都有较高的精度(R为0.68~0.84,FAC2为0.71~0.79),在华北地区精度均较低(R为0.41~0.48,FAC2为0.64~0.77)。③MERRA-2与TAP大气BC浓度在全国大部分地区呈显著正相关,其中,二者在四川省大气BC浓度差异(0.0045μg/m^(3))最小,在北京市差异(2.11μg/m^(3))最大。研究显示,MERRA-2有更长的时间跨度,而TAP更能准确表现大气BC浓度的空间分布,且二者在不同地区表现出较大差异。
文摘The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 and SO4, in addition to the aerosol optical properties (AOD) were analyzed over the region of the Middle East and North Africa (MENA) from satellite and Modern Era-Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis data. The SO2 and SO4 data used in these analyses are obtained from (MERRA-2) with a resolution of 0.5° × 0.625° throughout a period of 10 years (2005-2015). On the other hand, the temporal trend and spatial distribution of AOD were identified from four different satellite data. 1) moderate-resolution imaging spectroradiometer (MODIS) Level 3 AOD data at 550 nm wavelengths from Collection 6 algorithm (combined dark target and deep blue algorithms) are used for 10 years temporal analysis (2006-2015). 2) Multi-angle imaging spectroradiometer (MISR) with 0.5 deg spatial resolution for the same 10 years (2006-2015). 3) Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) with 0.5 deg for the period (2005-2010). 4) Ozone Monitoring Instrument (OMI) AOD at 500 nm wavelength with resolution 1 degree. This study presents more resent 10 years of Spatiotemporal of SO2, SO4 and AOD over MENA domain.
文摘遥感反演土壤水分(SM)产品越来越多地应用于农业、气象、水文等研究,而微波土壤水分数据产品的区域适用性分析是其合理使用的必要前提。使用MERRA-2(Modern Era Retrospective-analysis for Research and Applications,Version 2)模拟土壤水分为参考数据,运用传统统计方法(原始数据相关性、距平相关性、偏差以及无偏均方根差)和TC(Triple-Collocation)不确定性误差模型分析的方法,对亚洲区域2012年7月～2016年7月两种被动微波土壤水分SMOS-L3-SM(Soil Moisture and Ocean Salinity,L3)和AMSR2-LPRM-SM(The Advanced Microwave Scanning Radiometer 2,Land Parameter Retrieval Model Product)进行对比评估。结果表明:①空间上SMOS-L3较AMSR2-LPRM数据与参考数据MERRA-2土壤水分的相关性较好,表现为SMOS-L3-SM具有较好的空间连续性,且在亚洲大多数地区有较小的无偏均方根差;②湿季条件下遥感土壤水分与参考值的相关性比干季条件下的相关性更好,且干季出现高纬地区(约>55°)缺失值较多的情况;③两遥感土壤水分的TC误差呈现相似的分布,区域TC平均误差两者均为0.076 m^3/m^3。总之,SMOS-L3-SM和AMSR2-LPRM-SM在空间相关性及TC误差评价方面都具有合理性,为遥感土壤水分在农业、气象、水文等方面的应用提供参考。
