Articles | Volume 23, issue 14
https://doi.org/10.5194/acp-23-8001-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-8001-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Remotely sensed and surface measurement- derived mass-conserving inversion of daily NOx emissions and inferred combustion technologies in energy-rich northern China
Xiaolu Li
Institute of Environmental Science, Shanxi University, Taiyuan,
030006, China
School of Environment and Spatial Informatics, China University of
Mining and Technology, Xuzhou, 221116, China
School of Environment and Spatial Informatics, China University of
Mining and Technology, Xuzhou, 221116, China
School of Environment and Spatial Informatics, China University of
Mining and Technology, Xuzhou, 221116, China
Hong Geng
Institute of Environmental Science, Shanxi University, Taiyuan,
030006, China
Xiaohui Wu
Shanxi Dadi Ecology and Environment Technology Research Institute
Ltd., Taiyuan, 030000, China
Liling Wu
School of Environment, Tsinghua University, Beijing, 10084, China
Chengli Yang
Shanxi Dadi Ecology and Environment Technology Research Institute
Ltd., Taiyuan, 030000, China
Rui Zhang
Shanxi Institute of Ecology and Environment Planning and Technology, Taiyuan, 030002, China
Liqin Zhang
Shanxi Institute of Ecology and Environment Monitoring and Emergency Response Center, Taiyuan, 030027, China
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Cited
29 citations as recorded by crossref.
- New Perspective on Using Observational Uncertainty to Improve Reliability of NO x Emissions Over Northern China L. Lu et al.
- Individual coal mine methane emissions constrained by eddy covariance measurements: low bias and missing sources K. Qin et al.
- Satellite-Based Estimation of Near-Surface NO2 Concentration in Cloudy and Rainy Areas F. Deng et al.
- How can we trust TROPOMI based methane emissions estimation: calculating emissions over unidentified source regions B. Zheng et al.
- Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method L. Lu et al.
- Classifying and quantifying decadal changes in wet deposition over Southeast and East Asia using EANET, OMI, and GPCP S. Wang et al.
- Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning S. Shetty et al.
- Satellite-Based Emission Inversion for Air Pollutants and Greenhouse Gases: A Review Z. Jiang et al.
- Remotely sensed BC columns over rapidly changing Western China show significant decreases in mass and inconsistent changes in number, size, and mixing properties due to policy actions Z. Liu et al.
- OMI-Derived Mass- and Number-Conserved Estimation of Black Carbon Emissions J. Liu et al.
- Surface-observation-constrained high-frequency coal mine methane emissions in Shanxi, China, reveal more emissions than inventories, consistent with satellite inversion F. Lu et al.
- Quantifying Urban Nitrogen Dioxide Emission From Space Based on Cross-Sectional Flux Method and Satellite Data X. Ye et al.
- Improving estimation of surface PM2.5 by including satellite observations of gases, aerosols, and radiation in tandem J. Kang et al.
- Identification of NO emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China H. Sheng et al.
- Retrieval and Evaluation of NOX Emissions Based on a Machine Learning Model in Shandong T. Liu et al.
- Trends and drivers of anthropogenic NO emissions in China since 2020 H. Li et al.
- GEMS逐小时对流层NO2产品数据质量评价与提升:以华东地区为例 高. Gao Hongrui et al.
- Space-based inversion reveals underestimated carbon monoxide emissions over Shanxi X. Li et al.
- The global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2 K. Qin et al.
- Multi-platform observations and constraints reveal overlooked urban sources of black carbon in Xuzhou and Dhaka P. Tiwari et al.
- Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al.
- Spatial drivers of atmospheric NO2 and NH3 in China: Disentangling source- versus process-driven controls S. Wang et al.
- New top-down estimation of daily mass and number column density of black carbon driven by OMI and AERONET observations J. Liu et al.
- Remote sensing of air pollutants in China to study the effects of emission reduction policies on air quality G. de Leeuw et al.
- Establishment and application of electricity-based industrial supervision indicators for heavy pollution emergencies K. Fan et al.
- Observationally constrained global NOx and CO emissions variability reveals sources which contribute significantly to CO2 emissions S. Wang et al.
- Global gridded NOx emissions using TROPOMI observations A. Rey-Pommier et al.
- In-tandem multi-waveband particulate absorption and size observations yield substantial changes in radiative forcing over industrial Central China L. Guan et al.
- Diurnal NO emission underestimation constrained using overlapping TROPOMI swaths Q. He et al.
29 citations as recorded by crossref.
- New Perspective on Using Observational Uncertainty to Improve Reliability of NO x Emissions Over Northern China L. Lu et al.
- Individual coal mine methane emissions constrained by eddy covariance measurements: low bias and missing sources K. Qin et al.
- Satellite-Based Estimation of Near-Surface NO2 Concentration in Cloudy and Rainy Areas F. Deng et al.
- How can we trust TROPOMI based methane emissions estimation: calculating emissions over unidentified source regions B. Zheng et al.
- Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method L. Lu et al.
- Classifying and quantifying decadal changes in wet deposition over Southeast and East Asia using EANET, OMI, and GPCP S. Wang et al.
- Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning S. Shetty et al.
- Satellite-Based Emission Inversion for Air Pollutants and Greenhouse Gases: A Review Z. Jiang et al.
- Remotely sensed BC columns over rapidly changing Western China show significant decreases in mass and inconsistent changes in number, size, and mixing properties due to policy actions Z. Liu et al.
- OMI-Derived Mass- and Number-Conserved Estimation of Black Carbon Emissions J. Liu et al.
- Surface-observation-constrained high-frequency coal mine methane emissions in Shanxi, China, reveal more emissions than inventories, consistent with satellite inversion F. Lu et al.
- Quantifying Urban Nitrogen Dioxide Emission From Space Based on Cross-Sectional Flux Method and Satellite Data X. Ye et al.
- Improving estimation of surface PM2.5 by including satellite observations of gases, aerosols, and radiation in tandem J. Kang et al.
- Identification of NO emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China H. Sheng et al.
- Retrieval and Evaluation of NOX Emissions Based on a Machine Learning Model in Shandong T. Liu et al.
- Trends and drivers of anthropogenic NO emissions in China since 2020 H. Li et al.
- GEMS逐小时对流层NO2产品数据质量评价与提升:以华东地区为例 高. Gao Hongrui et al.
- Space-based inversion reveals underestimated carbon monoxide emissions over Shanxi X. Li et al.
- The global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2 K. Qin et al.
- Multi-platform observations and constraints reveal overlooked urban sources of black carbon in Xuzhou and Dhaka P. Tiwari et al.
- Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al.
- Spatial drivers of atmospheric NO2 and NH3 in China: Disentangling source- versus process-driven controls S. Wang et al.
- New top-down estimation of daily mass and number column density of black carbon driven by OMI and AERONET observations J. Liu et al.
- Remote sensing of air pollutants in China to study the effects of emission reduction policies on air quality G. de Leeuw et al.
- Establishment and application of electricity-based industrial supervision indicators for heavy pollution emergencies K. Fan et al.
- Observationally constrained global NOx and CO emissions variability reveals sources which contribute significantly to CO2 emissions S. Wang et al.
- Global gridded NOx emissions using TROPOMI observations A. Rey-Pommier et al.
- In-tandem multi-waveband particulate absorption and size observations yield substantial changes in radiative forcing over industrial Central China L. Guan et al.
- Diurnal NO emission underestimation constrained using overlapping TROPOMI swaths Q. He et al.
Saved (final revised paper)
Latest update: 30 Apr 2026
Short summary
Remotely sensed NO2 and surface NOx are combined with a mathematical method to estimate daily NOx emissions. The results identify new sources and improve existing estimates. The estimation is driven by three flexible factors: thermodynamics of combustion, chemical loss, and atmospheric transport. The thermodynamic term separates power, iron, and cement from coking, boilers, and aluminum. This work finds three causes for the extremes: emissions, UV radiation, and transport.
Remotely sensed NO2 and surface NOx are combined with a mathematical method to estimate daily...
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