Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept
With the continuous improvement of air quality in China, the characteristics of emission sources of pollutants have changed significantly, from their distribution to emitted atmospheric species and the corresponding emission concentrations and source localization has become increasingly challenging....
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Environment International |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412025001266 |
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| author | Chengzhi Xing Haochen Peng Cheng Liu Qihua Li Zhijian Tang Wei Tan Haoran Liu Qianqian Hong |
| author_facet | Chengzhi Xing Haochen Peng Cheng Liu Qihua Li Zhijian Tang Wei Tan Haoran Liu Qianqian Hong |
| author_sort | Chengzhi Xing |
| collection | DOAJ |
| description | With the continuous improvement of air quality in China, the characteristics of emission sources of pollutants have changed significantly, from their distribution to emitted atmospheric species and the corresponding emission concentrations and source localization has become increasingly challenging. The localization uncertainties of in situ observations are further amplified when combined with model simulations, which seriously restricts the realization of China’s strategic goal of “reducing pollution and carbon.” In this study, we established a localization and emission warning scheme for emission sources based on various hyperspectral remote sensing techniques with different observation spatial resolutions. These include satellite remote sensing, horizontal remote sensing, Unmanned Aerial Vehicle (UAV) remote sensing, and imaging. Based on this study, we aimed to locate high-concentration emission sources of NO2 (coal-fired power plants), HCHO (chemical and coking industries), and CH2CCH3CHO (metallurgical and material synthesis industries) and provide excess emission warnings for these species. Moreover, hyperspectral imaging remote sensing technology provides a possible method to obtain a dynamic emission inventory of pollutants, and the emission concentrations of NO2, SO2, HCHO, CHOCHO, and CH2CCH3CHO emitted from the coking industry at different timescales were obtained. The localization and emission warning scheme of pollutants established based on stereoscopic remote sensing, as well as the dynamic emission inventory established based on hyperspectral imaging remote sensing, provides technical and data support for air pollution control efforts. |
| format | Article |
| id | doaj-art-323bed4dfbfc4c1daa40fd73ba32c7dd |
| institution | DOAJ |
| issn | 0160-4120 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj-art-323bed4dfbfc4c1daa40fd73ba32c7dd2025-08-20T03:14:54ZengElsevierEnvironment International0160-41202025-04-0119810937510.1016/j.envint.2025.109375Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory conceptChengzhi Xing0Haochen Peng1Cheng Liu2Qihua Li3Zhijian Tang4Wei Tan5Haoran Liu6Qianqian Hong7Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaKey Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, ChinaKey Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China; Corresponding author.Institute of Physical Science and Information Technology, Anhui University, Hefei 230601, ChinaDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, ChinaKey Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, ChinaInstitute of Physical Science and Information Technology, Anhui University, Hefei 230601, ChinaKey Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Wuxi University, Wuxi 214105, ChinaWith the continuous improvement of air quality in China, the characteristics of emission sources of pollutants have changed significantly, from their distribution to emitted atmospheric species and the corresponding emission concentrations and source localization has become increasingly challenging. The localization uncertainties of in situ observations are further amplified when combined with model simulations, which seriously restricts the realization of China’s strategic goal of “reducing pollution and carbon.” In this study, we established a localization and emission warning scheme for emission sources based on various hyperspectral remote sensing techniques with different observation spatial resolutions. These include satellite remote sensing, horizontal remote sensing, Unmanned Aerial Vehicle (UAV) remote sensing, and imaging. Based on this study, we aimed to locate high-concentration emission sources of NO2 (coal-fired power plants), HCHO (chemical and coking industries), and CH2CCH3CHO (metallurgical and material synthesis industries) and provide excess emission warnings for these species. Moreover, hyperspectral imaging remote sensing technology provides a possible method to obtain a dynamic emission inventory of pollutants, and the emission concentrations of NO2, SO2, HCHO, CHOCHO, and CH2CCH3CHO emitted from the coking industry at different timescales were obtained. The localization and emission warning scheme of pollutants established based on stereoscopic remote sensing, as well as the dynamic emission inventory established based on hyperspectral imaging remote sensing, provides technical and data support for air pollution control efforts.http://www.sciencedirect.com/science/article/pii/S0160412025001266Hyperspectral remote sensingAir pollutantsStereoscopic monitoringSource localization & warningDynamic emission inventory |
| spellingShingle | Chengzhi Xing Haochen Peng Cheng Liu Qihua Li Zhijian Tang Wei Tan Haoran Liu Qianqian Hong Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept Environment International Hyperspectral remote sensing Air pollutants Stereoscopic monitoring Source localization & warning Dynamic emission inventory |
| title | Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept |
| title_full | Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept |
| title_fullStr | Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept |
| title_full_unstemmed | Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept |
| title_short | Hyperspectral remote sensing for air pollutants: Stereoscopic monitoring, source localization & warning, and a dynamic emission inventory concept |
| title_sort | hyperspectral remote sensing for air pollutants stereoscopic monitoring source localization amp warning and a dynamic emission inventory concept |
| topic | Hyperspectral remote sensing Air pollutants Stereoscopic monitoring Source localization & warning Dynamic emission inventory |
| url | http://www.sciencedirect.com/science/article/pii/S0160412025001266 |
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