The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM
Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Zhengqiang [verfasserIn] Hou, Weizhen [verfasserIn] Hong, Jin [verfasserIn] Fan, Cheng [verfasserIn] Wei, Yuanyuan [verfasserIn] Liu, Zhenhai [verfasserIn] Lei, Xuefeng [verfasserIn] Qiao, Yanli [verfasserIn] Hasekamp, Otto P. [verfasserIn] Fu, Guangliang [verfasserIn] Wang, Jun [verfasserIn] Dubovik, Oleg [verfasserIn] Qie, LiLi [verfasserIn] Zhang, Ying [verfasserIn] Xu, Hua [verfasserIn] Xie, Yisong [verfasserIn] Song, Maoxin [verfasserIn] Zou, Peng [verfasserIn] Luo, Donggen [verfasserIn] Wang, Yi [verfasserIn] Tu, Bihai [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of quantitative spectroscopy & radiative transfer - New York, NY [u.a.] : Elsevier, 1961, 286 |
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| Übergeordnetes Werk: |
volume:286 |
| DOI / URN: |
10.1016/j.jqsrt.2022.108217 |
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| Katalog-ID: |
ELV007865759 |
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| 245 | 1 | 0 | |a The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM |
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| 520 | |a Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. | ||
| 650 | 4 | |a Polarization crossfire suite | |
| 650 | 4 | |a Fine particulate matter pm2.5 remote sensing | |
| 650 | 4 | |a Optimal estimation inversion | |
| 650 | 4 | |a Aerosol layer height | |
| 650 | 4 | |a Pcf | |
| 700 | 1 | |a Hou, Weizhen |e verfasserin |0 (orcid)0000-0003-0610-7944 |4 aut | |
| 700 | 1 | |a Hong, Jin |e verfasserin |4 aut | |
| 700 | 1 | |a Fan, Cheng |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Yuanyuan |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Zhenhai |e verfasserin |0 (orcid)0000-0001-5570-8450 |4 aut | |
| 700 | 1 | |a Lei, Xuefeng |e verfasserin |4 aut | |
| 700 | 1 | |a Qiao, Yanli |e verfasserin |4 aut | |
| 700 | 1 | |a Hasekamp, Otto P. |e verfasserin |0 (orcid)0000-0002-1494-2539 |4 aut | |
| 700 | 1 | |a Fu, Guangliang |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Jun |e verfasserin |0 (orcid)0000-0002-7334-0490 |4 aut | |
| 700 | 1 | |a Dubovik, Oleg |e verfasserin |0 (orcid)0000-0003-3482-6460 |4 aut | |
| 700 | 1 | |a Qie, LiLi |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Ying |e verfasserin |0 (orcid)0000-0001-5856-1052 |4 aut | |
| 700 | 1 | |a Xu, Hua |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Yisong |e verfasserin |4 aut | |
| 700 | 1 | |a Song, Maoxin |e verfasserin |4 aut | |
| 700 | 1 | |a Zou, Peng |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Donggen |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yi |e verfasserin |4 aut | |
| 700 | 1 | |a Tu, Bihai |e verfasserin |4 aut | |
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10.1016/j.jqsrt.2022.108217 doi (DE-627)ELV007865759 (ELSEVIER)S0022-4073(22)00152-2 DE-627 ger DE-627 rda eng 530 DE-600 33.00 bkl Li, Zhengqiang verfasserin aut The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. Polarization crossfire suite Fine particulate matter pm2.5 remote sensing Optimal estimation inversion Aerosol layer height Pcf Hou, Weizhen verfasserin (orcid)0000-0003-0610-7944 aut Hong, Jin verfasserin aut Fan, Cheng verfasserin aut Wei, Yuanyuan verfasserin aut Liu, Zhenhai verfasserin (orcid)0000-0001-5570-8450 aut Lei, Xuefeng verfasserin aut Qiao, Yanli verfasserin aut Hasekamp, Otto P. verfasserin (orcid)0000-0002-1494-2539 aut Fu, Guangliang verfasserin aut Wang, Jun verfasserin (orcid)0000-0002-7334-0490 aut Dubovik, Oleg verfasserin (orcid)0000-0003-3482-6460 aut Qie, LiLi verfasserin aut Zhang, Ying verfasserin (orcid)0000-0001-5856-1052 aut Xu, Hua verfasserin aut Xie, Yisong verfasserin aut Song, Maoxin verfasserin aut Zou, Peng verfasserin aut Luo, Donggen verfasserin aut Wang, Yi verfasserin aut Tu, Bihai verfasserin aut Enthalten in Journal of quantitative spectroscopy & radiative transfer New York, NY [u.a.] : Elsevier, 1961 286 Online-Ressource (DE-627)302718931 (DE-600)1491916-3 (DE-576)255266650 1879-1352 nnns volume:286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 33.00 Physik: Allgemeines AR 286 |
| spelling |
10.1016/j.jqsrt.2022.108217 doi (DE-627)ELV007865759 (ELSEVIER)S0022-4073(22)00152-2 DE-627 ger DE-627 rda eng 530 DE-600 33.00 bkl Li, Zhengqiang verfasserin aut The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. Polarization crossfire suite Fine particulate matter pm2.5 remote sensing Optimal estimation inversion Aerosol layer height Pcf Hou, Weizhen verfasserin (orcid)0000-0003-0610-7944 aut Hong, Jin verfasserin aut Fan, Cheng verfasserin aut Wei, Yuanyuan verfasserin aut Liu, Zhenhai verfasserin (orcid)0000-0001-5570-8450 aut Lei, Xuefeng verfasserin aut Qiao, Yanli verfasserin aut Hasekamp, Otto P. verfasserin (orcid)0000-0002-1494-2539 aut Fu, Guangliang verfasserin aut Wang, Jun verfasserin (orcid)0000-0002-7334-0490 aut Dubovik, Oleg verfasserin (orcid)0000-0003-3482-6460 aut Qie, LiLi verfasserin aut Zhang, Ying verfasserin (orcid)0000-0001-5856-1052 aut Xu, Hua verfasserin aut Xie, Yisong verfasserin aut Song, Maoxin verfasserin aut Zou, Peng verfasserin aut Luo, Donggen verfasserin aut Wang, Yi verfasserin aut Tu, Bihai verfasserin aut Enthalten in Journal of quantitative spectroscopy & radiative transfer New York, NY [u.a.] : Elsevier, 1961 286 Online-Ressource (DE-627)302718931 (DE-600)1491916-3 (DE-576)255266650 1879-1352 nnns volume:286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 33.00 Physik: Allgemeines AR 286 |
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10.1016/j.jqsrt.2022.108217 doi (DE-627)ELV007865759 (ELSEVIER)S0022-4073(22)00152-2 DE-627 ger DE-627 rda eng 530 DE-600 33.00 bkl Li, Zhengqiang verfasserin aut The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. Polarization crossfire suite Fine particulate matter pm2.5 remote sensing Optimal estimation inversion Aerosol layer height Pcf Hou, Weizhen verfasserin (orcid)0000-0003-0610-7944 aut Hong, Jin verfasserin aut Fan, Cheng verfasserin aut Wei, Yuanyuan verfasserin aut Liu, Zhenhai verfasserin (orcid)0000-0001-5570-8450 aut Lei, Xuefeng verfasserin aut Qiao, Yanli verfasserin aut Hasekamp, Otto P. verfasserin (orcid)0000-0002-1494-2539 aut Fu, Guangliang verfasserin aut Wang, Jun verfasserin (orcid)0000-0002-7334-0490 aut Dubovik, Oleg verfasserin (orcid)0000-0003-3482-6460 aut Qie, LiLi verfasserin aut Zhang, Ying verfasserin (orcid)0000-0001-5856-1052 aut Xu, Hua verfasserin aut Xie, Yisong verfasserin aut Song, Maoxin verfasserin aut Zou, Peng verfasserin aut Luo, Donggen verfasserin aut Wang, Yi verfasserin aut Tu, Bihai verfasserin aut Enthalten in Journal of quantitative spectroscopy & radiative transfer New York, NY [u.a.] : Elsevier, 1961 286 Online-Ressource (DE-627)302718931 (DE-600)1491916-3 (DE-576)255266650 1879-1352 nnns volume:286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 33.00 Physik: Allgemeines AR 286 |
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10.1016/j.jqsrt.2022.108217 doi (DE-627)ELV007865759 (ELSEVIER)S0022-4073(22)00152-2 DE-627 ger DE-627 rda eng 530 DE-600 33.00 bkl Li, Zhengqiang verfasserin aut The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. Polarization crossfire suite Fine particulate matter pm2.5 remote sensing Optimal estimation inversion Aerosol layer height Pcf Hou, Weizhen verfasserin (orcid)0000-0003-0610-7944 aut Hong, Jin verfasserin aut Fan, Cheng verfasserin aut Wei, Yuanyuan verfasserin aut Liu, Zhenhai verfasserin (orcid)0000-0001-5570-8450 aut Lei, Xuefeng verfasserin aut Qiao, Yanli verfasserin aut Hasekamp, Otto P. verfasserin (orcid)0000-0002-1494-2539 aut Fu, Guangliang verfasserin aut Wang, Jun verfasserin (orcid)0000-0002-7334-0490 aut Dubovik, Oleg verfasserin (orcid)0000-0003-3482-6460 aut Qie, LiLi verfasserin aut Zhang, Ying verfasserin (orcid)0000-0001-5856-1052 aut Xu, Hua verfasserin aut Xie, Yisong verfasserin aut Song, Maoxin verfasserin aut Zou, Peng verfasserin aut Luo, Donggen verfasserin aut Wang, Yi verfasserin aut Tu, Bihai verfasserin aut Enthalten in Journal of quantitative spectroscopy & radiative transfer New York, NY [u.a.] : Elsevier, 1961 286 Online-Ressource (DE-627)302718931 (DE-600)1491916-3 (DE-576)255266650 1879-1352 nnns volume:286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 33.00 Physik: Allgemeines AR 286 |
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10.1016/j.jqsrt.2022.108217 doi (DE-627)ELV007865759 (ELSEVIER)S0022-4073(22)00152-2 DE-627 ger DE-627 rda eng 530 DE-600 33.00 bkl Li, Zhengqiang verfasserin aut The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. Polarization crossfire suite Fine particulate matter pm2.5 remote sensing Optimal estimation inversion Aerosol layer height Pcf Hou, Weizhen verfasserin (orcid)0000-0003-0610-7944 aut Hong, Jin verfasserin aut Fan, Cheng verfasserin aut Wei, Yuanyuan verfasserin aut Liu, Zhenhai verfasserin (orcid)0000-0001-5570-8450 aut Lei, Xuefeng verfasserin aut Qiao, Yanli verfasserin aut Hasekamp, Otto P. verfasserin (orcid)0000-0002-1494-2539 aut Fu, Guangliang verfasserin aut Wang, Jun verfasserin (orcid)0000-0002-7334-0490 aut Dubovik, Oleg verfasserin (orcid)0000-0003-3482-6460 aut Qie, LiLi verfasserin aut Zhang, Ying verfasserin (orcid)0000-0001-5856-1052 aut Xu, Hua verfasserin aut Xie, Yisong verfasserin aut Song, Maoxin verfasserin aut Zou, Peng verfasserin aut Luo, Donggen verfasserin aut Wang, Yi verfasserin aut Tu, Bihai verfasserin aut Enthalten in Journal of quantitative spectroscopy & radiative transfer New York, NY [u.a.] : Elsevier, 1961 286 Online-Ressource (DE-627)302718931 (DE-600)1491916-3 (DE-576)255266650 1879-1352 nnns volume:286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 33.00 Physik: Allgemeines AR 286 |
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Li, Zhengqiang @@aut@@ Hou, Weizhen @@aut@@ Hong, Jin @@aut@@ Fan, Cheng @@aut@@ Wei, Yuanyuan @@aut@@ Liu, Zhenhai @@aut@@ Lei, Xuefeng @@aut@@ Qiao, Yanli @@aut@@ Hasekamp, Otto P. @@aut@@ Fu, Guangliang @@aut@@ Wang, Jun @@aut@@ Dubovik, Oleg @@aut@@ Qie, LiLi @@aut@@ Zhang, Ying @@aut@@ Xu, Hua @@aut@@ Xie, Yisong @@aut@@ Song, Maoxin @@aut@@ Zou, Peng @@aut@@ Luo, Donggen @@aut@@ Wang, Yi @@aut@@ Tu, Bihai @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV007865759</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524155828.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230507s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.jqsrt.2022.108217</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV007865759</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0022-4073(22)00152-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">530</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">33.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Li, Zhengqiang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. 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Li, Zhengqiang |
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Li, Zhengqiang ddc 530 bkl 33.00 misc Polarization crossfire suite misc Fine particulate matter pm2.5 remote sensing misc Optimal estimation inversion misc Aerosol layer height misc Pcf The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM |
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530 DE-600 33.00 bkl The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM Polarization crossfire suite Fine particulate matter pm2.5 remote sensing Optimal estimation inversion Aerosol layer height Pcf |
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The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM |
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The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM |
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Li, Zhengqiang Hou, Weizhen Hong, Jin Fan, Cheng Wei, Yuanyuan Liu, Zhenhai Lei, Xuefeng Qiao, Yanli Hasekamp, Otto P. Fu, Guangliang Wang, Jun Dubovik, Oleg Qie, LiLi Zhang, Ying Xu, Hua Xie, Yisong Song, Maoxin Zou, Peng Luo, Donggen Wang, Yi Tu, Bihai |
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the polarization crossfire (pcf) sensor suite focusing on satellite remote sensing of fine particulate matter pm |
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The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM |
| abstract |
Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. |
| abstractGer |
Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. |
| abstract_unstemmed |
Focusing on satellite remote sensing of fine particulate matter PM2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index ( m r f ) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VEf ), the aerosol effective density (ρ f ) and the hygroscopic growth factor of fine-mode particles (f(RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM2.5 retrievals are discussed, as well as the retrieval feasibility of PM10 by PCF strategy. |
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| title_short |
The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM |
| remote_bool |
true |
| author2 |
Hou, Weizhen Hong, Jin Fan, Cheng Wei, Yuanyuan Liu, Zhenhai Lei, Xuefeng Qiao, Yanli Hasekamp, Otto P. Fu, Guangliang Wang, Jun Dubovik, Oleg Qie, LiLi Zhang, Ying Xu, Hua Xie, Yisong Song, Maoxin Zou, Peng Luo, Donggen Wang, Yi Tu, Bihai |
| author2Str |
Hou, Weizhen Hong, Jin Fan, Cheng Wei, Yuanyuan Liu, Zhenhai Lei, Xuefeng Qiao, Yanli Hasekamp, Otto P. Fu, Guangliang Wang, Jun Dubovik, Oleg Qie, LiLi Zhang, Ying Xu, Hua Xie, Yisong Song, Maoxin Zou, Peng Luo, Donggen Wang, Yi Tu, Bihai |
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c |
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| doi_str |
10.1016/j.jqsrt.2022.108217 |
| up_date |
2024-07-06T17:44:07.829Z |
| _version_ |
1803852550328287232 |
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