62 citations as recorded by crossref.

1. Constraining CO<sub>2</sub> emissions from open biomass burning by satellite observations of co-emitted species: a method and its application to wildfires in Siberia I. Konovalov et al. 10.5194/acp-14-10383-2014
2. Global climate change driven by soot at the K-Pg boundary as the cause of the mass extinction K. Kaiho et al. 10.1038/srep28427
3. NDACC harmonized formaldehyde time series from 21 FTIR stations covering a wide range of column abundances C. Vigouroux et al. 10.5194/amt-11-5049-2018
4. Biomass Burning Plumes in the Vicinity of the California Coast: Airborne Characterization of Physicochemical Properties, Heating Rates, and Spatiotemporal Features A. Mardi et al. 10.1029/2018JD029134
5. Differences in satellite-derived NO x emission factors between Eurasian and North American boreal forest fires S. Schreier et al. 10.1016/j.atmosenv.2014.08.071
6. Fire emission heights in the climate system – Part 1: Global plume height patterns simulated by ECHAM6-HAM2 A. Veira et al. 10.5194/acp-15-7155-2015
7. Fire evolution in the radioactive forests of Ukraine and Belarus: future risks for the population and the environment N. Evangeliou et al. 10.1890/14-1227.1
8. Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates J. Müller et al. 10.5194/acp-24-2207-2024
9. Characterising Brazilian biomass burning emissions using WRF-Chem with MOSAIC sectional aerosol S. Archer-Nicholls et al. 10.5194/gmd-8-549-2015
10. CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design J. Tackett et al. 10.5194/amt-11-4129-2018
11. An evaluation of empirical and statistically based smoke plume injection height parametrisations used within air quality models J. Wilkins et al. 10.1071/WF20140
12. Gas‐aerosol partitioning of ammonia in biomass burning plumes: Implications for the interpretation of spaceborne observations of ammonia and the radiative forcing of ammonium nitrate F. Paulot et al. 10.1002/2017GL074215
13. Two global data sets of daily fire emission injection heights since 2003 S. Rémy et al. 10.5194/acp-17-2921-2017
14. Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions Z. Loh et al. 10.5194/acp-15-305-2015
15. Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product P. Freeborn et al. 10.3390/rs6031890
16. Improved estimates of smoke exposure during Australia fire seasons: importance of quantifying plume injection heights X. Feng et al. 10.5194/acp-24-2985-2024
17. Insights into the aging of biomass burning aerosol from satellite observations and 3D atmospheric modeling: evolution of the aerosol optical properties in Siberian wildfire plumes I. Konovalov et al. 10.5194/acp-21-357-2021
18. A Coupled Wildfire-Emission and Dispersion Framework for Probabilistic PM2.5 Estimation D. Melecio-Vázquez et al. 10.3390/fire6060220
19. Levoglucosan on Tibetan glaciers under different atmospheric circulations C. You et al. 10.1016/j.atmosenv.2016.12.021
20. Downwind Ozone Changes of the 2019 Williams Flats Wildfire: Insights From WRF‐Chem/DART Assimilation of OMI NO2, HCHO, and MODIS AOD Retrievals A. Pouyaei et al. 10.1029/2022JD038019
21. Modulation of snow reflectance and snowmelt from Central Asian glaciers by anthropogenic black carbon J. Schmale et al. 10.1038/srep40501
22. How consistent are top-down hydrocarbon emissions based on formaldehyde observations from GOME-2 and OMI? T. Stavrakou et al. 10.5194/acp-15-11861-2015
23. Global Wildfire Plume‐Rise Data Set and Parameterizations for Climate Model Applications Z. Ke et al. 10.1029/2020JD033085
24. Nine years of global hydrocarbon emissions based on source inversion of OMI formaldehyde observations M. Bauwens et al. 10.5194/acp-16-10133-2016
25. The vertical distribution of biomass burning pollution over tropical South America from aircraft in situ measurements during SAMBBA E. Darbyshire et al. 10.5194/acp-19-5771-2019
26. Wildfires in northern Eurasia affect the budget of black carbon in the Arctic – a 12-year retrospective synopsis (2002–2013) N. Evangeliou et al. 10.5194/acp-16-7587-2016
27. Status and future of numerical atmospheric aerosol prediction with a focus on data requirements A. Benedetti et al. 10.5194/acp-18-10615-2018
28. Impact of Anthropogenic Emission Injection Height Uncertainty on Global Sulfur Dioxide and Aerosol Distribution Y. Yang et al. 10.1029/2018JD030001
29. HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 1: global and regional module M. Guevara et al. 10.5194/gmd-12-1885-2019
30. Technical note: Intermittent reduction of the stratospheric ozone over northern Europe caused by a storm in the Atlantic Ocean M. Sofiev et al. 10.5194/acp-20-1839-2020
31. Uncertainties of wild-land fires emission in AQMEII phase 2 case study J. Soares et al. 10.1016/j.atmosenv.2015.01.068
32. Sensitivity of tropospheric loads and lifetimes of short lived pollutants to fire emissions N. Daskalakis et al. 10.5194/acp-15-3543-2015
33. Fire Influences on Atmospheric Composition, Air Quality and Climate A. Voulgarakis & R. Field 10.1007/s40726-015-0007-z
34. Wildfire influences on the variability and trend of summer surface ozone in the mountainous western United States X. Lu et al. 10.5194/acp-16-14687-2016
35. Lidar observations of pyrocumulonimbus smoke plumes in the UTLS over Tomsk (Western Siberia, Russia) from 2000 to 2017 V. Zuev et al. 10.5194/acp-19-3341-2019
36. Contribution of ship emissions to the concentration and deposition of air pollutants in Europe S. Aksoyoglu et al. 10.5194/acp-16-1895-2016
37. Reviewing the links and feedbacks between climate change and air pollution in Europe U. Im et al. 10.3389/fenvs.2022.954045
38. Assessing Vertical Allocation of Wildfire Smoke Emissions Using Observational Constraints From Airborne Lidar in the Western U.S. X. Ye et al. 10.1029/2022JD036808
39. Estimates of the Height of Rise and Buoyancy of Smoke Plumes from High Chimneys of Thermal Power Plants from Satellite Information V. Raputa et al. 10.1134/S1024856023060167
40. Responses of wildfire-induced global black carbon pollution and radiative forcing to climate change X. Liu et al. 10.1088/1748-9326/acff7a
41. The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics H. Ahsan et al. 10.5194/acp-23-14779-2023
42. Smoke emissions from the extreme wildfire events in central Portugal in October 2017 A. Fernandes et al. 10.1071/WF21097
43. Spaceborne lidar retrieved composite and speciated aerosol extinction profiles and optical depths over India: A decade of observations P. Kulkarni & V. Sreekanth 10.1016/j.apr.2020.02.007
44. Assessing the spatial fidelity of sedimentary charcoal size fractions as fire history proxies with a high-resolution sediment record and historical data R. Vachula et al. 10.1016/j.palaeo.2018.07.032
45. Wildfires in Chernobyl-contaminated forests and risks to the population and the environment: A new nuclear disaster about to happen? N. Evangeliou et al. 10.1016/j.envint.2014.08.012
46. Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer P. Monks et al. 10.5194/acp-15-8889-2015
47. Description and evaluation of the tropospheric aerosol scheme in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS-AER, cycle 45R1) S. Rémy et al. 10.5194/gmd-12-4627-2019
48. Optimizing 4 years of CO2 biospheric fluxes from OCO-2 and in situ data in TM5: fire emissions from GFED and inferred from MOPITT CO data H. Peiro et al. 10.5194/acp-22-15817-2022
49. Forecasting the regional fire radiative power for regularly ignited vegetation fires T. Partanen & M. Sofiev 10.5194/nhess-22-1335-2022
50. Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends P. Young et al. 10.1525/elementa.265
51. California Case Study of Wildfires and Prescribed Burns: PM2.5 Emissions, Concentrations, and Implications for Human Health L. Kiely et al. 10.1021/acs.est.3c06421
52. Biomass-burning smoke heights over the Amazon observed from space L. Gonzalez-Alonso et al. 10.5194/acp-19-1685-2019
53. A review of approaches to estimate wildfire plume injection height within large-scale atmospheric chemical transport models R. Paugam et al. 10.5194/acp-16-907-2016
54. Informing sedimentary charcoal-based fire reconstructions with a kinematic transport model R. Vachula & N. Richter 10.1177/0959683617715624
55. Traces of Canadian Pyrocumulonimbus Clouds in the Stratosphere over Tomsk in June-July, 1991 V. Gerasimov et al. 10.1134/S1024856019030096
56. Satellite-derived emissions of carbon monoxide, ammonia, and nitrogen dioxide from the 2016 Horse River wildfire in the Fort McMurray area C. Adams et al. 10.5194/acp-19-2577-2019
57. New fire diurnal cycle characterizations to improve fire radiative energy assessments made from MODIS observations N. Andela et al. 10.5194/acp-15-8831-2015
58. Pan-Eurasian Experiment (PEEX): towards a holistic understanding of the feedbacks and interactions in the land–atmosphere–ocean–society continuum in the northern Eurasian region H. Lappalainen et al. 10.5194/acp-16-14421-2016
59. Chemistry and deposition in the Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace gas Emissions (MAGRITTE v1.1) – Part 1: Chemical mechanism J. Müller et al. 10.5194/gmd-12-2307-2019
60. Estimation of Cs-137 emissions during wildfires and dust storm in Chernobyl Exclusion Zone in April 2020 using ensemble iterative source inversion method I. Kovalets et al. 10.1016/j.atmosenv.2022.119305
61. Simulation study of radionuclide atmospheric transport after wildland fires in the Chernobyl Exclusion Zone in April 2020 M. Таlerko et al. 10.1016/j.apr.2021.01.010
62. Improving air quality modelling systems by using on-line wild land fire forecasting tools coupled into WRF/Chem simulations over Europe R. Jose et al. 10.1016/j.uclim.2016.09.001