Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations
Abstract Given the significant environmental and health risks associated with near-surface nitrogen dioxide (NO2), machine learning is frequently employed to estimate near-surface NO2 concentrations (SNO2) from satellite-derived tropospheric NO2 column densities (CNO2). However, data-driven methods...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-024-00891-z |
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| author | Bowen Chang Haoran Liu Chengxin Zhang Chengzhi Xing Wei Tan Cheng Liu |
| author_facet | Bowen Chang Haoran Liu Chengxin Zhang Chengzhi Xing Wei Tan Cheng Liu |
| author_sort | Bowen Chang |
| collection | DOAJ |
| description | Abstract Given the significant environmental and health risks associated with near-surface nitrogen dioxide (NO2), machine learning is frequently employed to estimate near-surface NO2 concentrations (SNO2) from satellite-derived tropospheric NO2 column densities (CNO2). However, data-driven methods often face challenges in explaining the complex relationships between these variables. In this study, the correlation between CNO2 and SNO2 is examined using vertical profile observations from China’s MAX-DOAS network. Cloud cover and air convection substantially weaken (R = −0.68) and strengthen (R = 0.71) the CNO2-SNO2 correlation, respectively. Meteorological factors dominate the correlation (R2 = 0.58), which is 31% stronger in northern regions than in the southwest. Additionally, anthropogenic emissions impact SNO2, while topographical features shape regional climate patterns. At the Chongqing site, the negative impacts of unfavorable meteorological conditions, high emissions, and basin topography lead to significant contrasts and delays in daily CNO2 and SNO2 variations. This study enhances understanding of the spatial and temporal dynamics and influencing mechanisms of CNO2 and SNO2, supporting improved air quality assessments and pollution exposure evaluations. |
| format | Article |
| id | doaj-art-e1202db6f74542fc9b5b8db89fc0c12f |
| institution | Kabale University |
| issn | 2397-3722 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | npj Climate and Atmospheric Science |
| spelling | doaj-art-e1202db6f74542fc9b5b8db89fc0c12f2025-01-05T12:12:47ZengNature Portfolionpj Climate and Atmospheric Science2397-37222025-01-018111210.1038/s41612-024-00891-zRelating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observationsBowen Chang0Haoran Liu1Chengxin Zhang2Chengzhi Xing3Wei Tan4Cheng Liu5Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui UniversityInformation Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui UniversityDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaKey Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of SciencesKey Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of SciencesDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of ChinaAbstract Given the significant environmental and health risks associated with near-surface nitrogen dioxide (NO2), machine learning is frequently employed to estimate near-surface NO2 concentrations (SNO2) from satellite-derived tropospheric NO2 column densities (CNO2). However, data-driven methods often face challenges in explaining the complex relationships between these variables. In this study, the correlation between CNO2 and SNO2 is examined using vertical profile observations from China’s MAX-DOAS network. Cloud cover and air convection substantially weaken (R = −0.68) and strengthen (R = 0.71) the CNO2-SNO2 correlation, respectively. Meteorological factors dominate the correlation (R2 = 0.58), which is 31% stronger in northern regions than in the southwest. Additionally, anthropogenic emissions impact SNO2, while topographical features shape regional climate patterns. At the Chongqing site, the negative impacts of unfavorable meteorological conditions, high emissions, and basin topography lead to significant contrasts and delays in daily CNO2 and SNO2 variations. This study enhances understanding of the spatial and temporal dynamics and influencing mechanisms of CNO2 and SNO2, supporting improved air quality assessments and pollution exposure evaluations.https://doi.org/10.1038/s41612-024-00891-z |
| spellingShingle | Bowen Chang Haoran Liu Chengxin Zhang Chengzhi Xing Wei Tan Cheng Liu Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations npj Climate and Atmospheric Science |
| title | Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations |
| title_full | Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations |
| title_fullStr | Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations |
| title_full_unstemmed | Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations |
| title_short | Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations |
| title_sort | relating satellite no2 tropospheric columns to near surface concentrations implications from ground based max doas no2 vertical profile observations |
| url | https://doi.org/10.1038/s41612-024-00891-z |
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