113 results on '"Jin, Jianbing"'
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2. A decadal atmospheric ammonia reanalysis product in China
3. An improved hourly-resolved atmospheric NOx emission inventory of industrial sources based on Continuous Emission Monitoring System data: Case of Jiangsu Province, China
4. Dust storm forecasting through coupling LOTOS-EUROS with localized ensemble Kalman filter
5. Clustering-based spatial transfer learning for short-term ozone forecasting
6. A Novel Method for Quantifying the Contribution of Regional Transport to PM2.5 in Beijing (2013–2020): Combining Machine Learning with Concentration-Weighted Trajectory Analysis.
7. Unlocking nitrogen management potential via large-scale farming for air quality and substantial co-benefits.
8. Reply on RC2
9. Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001–2018)
10. Machine learning based bias correction for numerical chemical transport models
11. Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities.
12. A decadal atmospheric ammonia reanalysis product in China
13. Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001–2018).
14. Improving estimation of a record breaking East Asian dust storm emission with lagged aerosol Ångström Exponent observations.
15. Spatially varying parameter estimation for dust emissions using reduced-tangent-linearization 4DVar
16. A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter
17. Satellite NO2Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001–2018)
18. Reply on RC2
19. A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter
20. 4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals
21. Supplementary material to "EnKF-based fusion of site-available machine learning air quality predictions from RFSML v1.0 and gridded chemical transport model forecasts from GEOS-Chem v13.1.0"
22. EnKF-based fusion of site-available machine learning air quality predictions from RFSML v1.0 and gridded chemical transport model forecasts from GEOS-Chem v13.1.0
23. How aerosol size matters in aerosol optical depth (AOD) assimilation and the optimization using the Ångström exponent
24. Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data
25. Composited analyses of the chemical and physical characteristics of co-polluted days by ozone and PM2.5 over 2013–2020 in the Beijing–Tianjin–Hebei region
26. Supplementary material to "How aerosol size matters in AOD assimilation and the optimization using Ångström exponent"
27. How aerosol size matters in AOD assimilation and the optimization using Ångström exponent
28. Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China
29. Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multisource data
30. Supplementary material to "Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multisource data"
31. Composited analyses of the chemical and physical characteristics of co-polluted days by ozone and PM2.5 over 2013–2020 in the Beijing–Tianjin–Hebei region
32. Supplementary material to "Composited analyses of the chemical and physical characteristics of co-polluted days by ozone and PM2.5 over 2013–2020 in the Beijing–Tianjin–Hebei region"
33. Reply on RC2
34. Supplementary material to "Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China"
35. Future Co‐Occurrences of Hot Days and Ozone‐Polluted Days Over China Under Scenarios of Shared Socioeconomic Pathways Predicted Through a Machine‐Learning Approach
36. Development of a regional feature selection-based machine learning system (RFSML v1.0) for air pollution forecasting over China
37. Inverse modeling of the 2021 spring super dust storms in East Asia
38. Supplementary material to "Inverse modeling of the 2021 spring super dust storms in East Asia"
39. Model‐Reduced Adjoint‐Based Inversion Using Deep‐Learning: Example of Geological Carbon Sequestration Modeling
40. Improved gridded ammonia emission inventory in China
41. Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0
42. Reply on RC2
43. Supplementary material to "Improved gridded ammonia emission inventory in China"
44. Evaluating the influence of COVID-19 pandemic on NO2 concentration variation in selected regions in China using TROPOMI data, surface measurements and modeling approaches
45. Dust storm emission inversion using data assimilation
46. Mono-mercapto-functionalized pillar[5]arene: a host–guest complexation accelerated reversible redox dimerization
47. Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China
48. Response to the comments of Referee #3
49. Response to the comments of Referee #4
50. Source backtracking for dust storm emission inversion using adjoint method: case study of northeast China
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