Avelino F Arellano

Interests

Teaching

data assimilation, atmospheric composition, air pollution, computational methods, physical meteorology, remote sensing

Research

atmospheric chemistry modeling and data assimilation, satellite remote sensing of atmospheric composition, biomass burning, anthropogenic pollution, urbanization

Courses

Scholarly Contributions

Journals/Publications

• Betito, G., Arellano, A., & Sorooshian, A. (2024). Influence of Transboundary Pollution on the Variability of Surface Ozone Concentrations in the Desert Southwest of the US: Case Study for Arizona. Atmosphere, 15(4), 401.
• Furlong, M. A., Paul, K. C., Parra, K. L., Fournier, A. J., Cockburn, M. G., Arellano, A. F., Bedrock, E., Beamer, P. I., & Ritz, B. (2024). Pre-Conception And First Trimester Exposure To Pesticides And Associations With Stillbirth. American Journal of Epidemiology. doi:https://doi.org/10.1093/aje/kwae198
• Gaubert, B., Anderson, J. L., Trudeau, M., Smith, N., McKain, K., Pétron, G., Raeder, K., Arellano, A. F., Granier, C., Emmons, L. K., Ortega, I., Hannigan, J., Tang, W., Worden, H. M., Ziskin, D., & Edwards, D. P. (2024). Nonlinear and non-Gaussian Ensemble Assimilation of MOPITT CO. Journal of Geophysical Research - Atmospheres. doi:https://doi.org/10.1029/2023JD040647
• Greenslade, M., Guo, Y., Betito, G., Mirrezaei, M. A., Roychoudhury, C., Arellano, A. F., & Sorooshian, A. (2024). On ozone's weekly cycle for different seasons in Arizona. Atmospheric Environment, 334, 120703.
• Guo, Y., Mirrezaei, M. A., Sorooshian, A., & Arellano, A. F. (2024). Source contribution to ozone pollution during June 2021 in Arizona: Insights from WRF-Chem tagged O 3 and CO. EGUsphere, 2024, 1--41.
• Guo, Y., Roychoudhury, C., Mirrezaei, M. A., Kumar, R., Sorooshian, A., & Arellano, A. F. (2024). Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling. Geoscientific Model Development. doi:https://doi.org/10.5194/gmd-17-4331-2024
• Lorenzo, G. R., Ziemba, L. D., Arellano, A. F., Barth, M. C., Crosbie, E. C., DiGangi, J. P., Diskin, G. S., Ferrare, R., Hilario, M., Shook, M. A., & others, . (2024). Measurement report: Characterization of Aerosol Hygroscopicity over Southeast Asia during the NASA CAMP 2 Ex Campaign. EGUsphere, 2024, 1--42.
• McKinnon, J., Roychoudhury, C., Gaubert, B., & Arellano, A. F. (2023). Spatiotemporal Pattern Analysis of Carbon Monoxide Using Varimax Rotation and Singular Spectrum Analysis. EGUsphere. doi:https://doi.org/10.5194/egusphere-2024-3440
• Miech, J. A., Herckes, P., Fraser, M. P., Arellano, A. F., Mirrezaei, M. A., & Guo, Y. (2024). Evaluating Phoenix Metropolitan Area Ozone Behavior Using Ground-Based Sampling, Modeling, and Satellite Retrievals. Atmosphere, 15(5), 555.
• Mirrezaei, M. A., Arellano, A. F., Guo, Y., Roychoudhury, C., & Sorooshian, A. (2024). Ozone Production over Arid Regions: Insights into Meteorological and Chemical Drivers. Environmental Research Communications.
• Mottungan, K., Brocchi, V., McKinnon, J., Roychoudhury, C., Mirrezaei, M. A., Guo, Y., Gaubert, B., Tang, W., & Arellano, A. F. (2024). Local and Regional Enhancements of CO, CO₂ and CH₄ Inferred from TCCON Column Measurements. Atmospheric Measurement Techniques. doi:https://doi.org/10.5194/amt-17-5861-2024
• Pan, K., Arellano, A. F., Guo, Y., & Demoz, B. (2024). Investigating the Impact of Multiphysics on Modeled Planetary Boundary Layer Height Estimates during the PECAN Field Campaign. Journal of Applied Meteorology and Climatology, 63(11), 1385--1407.
• Pan, K., Arellano, A., Guo, Y., & Demoz, B. (2024). Investigating the Impact of Multiphysics on Modeled Planetary Boundary Layer Height Estimates during the PECAN Field Campaign. Journal of Applied Meteorology and Climatology, 63(11). doi:10.1175/JAMC-D-24-0046.1
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  Accurate representation of the planetary boundary layer (PBL) in numerical weather prediction is crucial to air quality, weather forecasting, and climate change research and operations. Here, we evaluate the estimates of PBL height (PBLH) from a set of convective-permitting simulations conducted using the Weather Research and Forecasting (WRF) Model during the Plains Elevated Convection at Night (PECAN) campaign (from June to mid-July 2015). Our analysis aims to quantify the variability in PBLH, along with its associated surface variables and atmospheric profiles, to gauge the influence of model physics on the accuracy of simulated PBL properties. Specifically, we conducted twenty-four 45-day retrospective simulations encompassing different combinations of three PBL and two microphysics schemes, two initial and boundary condition (ICBC) datasets, and two model vertical grid spacings. We compare these simulations with measurements from surface sites and radiosonde launches across four sites in the southern Great Plains during PECAN. Our findings indicate that deriving PBLH from modeled atmospheric profiles yields a narrower spread (200–300 m) com-pared to PBLH calculated from the model’s PBL scheme (400–500 m) relative to radiosonde-derived PBLH under fair weather conditions. The choice of PBL scheme and ICBCs exerts the most significant impact (by up to 400 m) on the spread of modeled PBLH and associated atmospheric profiles, primarily influencing the representation of surface heating, transport, and mixing processes in the model. The model has difficulty reproducing the correct thermodynamic profile under cloud-intense conditions. These results underscore the benefit of using the physically consistent approach in retrieving, evaluating, and assimilating PBLH estimates, as well as the utility of multiphysics to better address model uncertainties.
• Roychoudhury, C., He, C., Kumar, R., & Arellano Jr, ,. A. (2024). Diagnosing Aerosol-Meteorological Interactions on Snow within the Earth System: A Proof-of-Concept Study over High Mountain Asia. EGUsphere, 2024, 1--42.
• Sorooshian, A., Arellano, A. F., Fraser, M. P., Herckes, P., Betito, G., Betterton, E. A., Braun, R. A., Guo, Y., Mirrezaei, M. A., & Roychoudhury, C. (2024). Ozone in the Desert Southwest of the United States: A Synthesis of Past Work and Steps Ahead. ACS ES&T Air. doi:https://doi.org/10.1021/acsestair.3c00033
• Tang, W., Gaubert, B., Emmons, L., Ziskin, D., Mao, D., Edwards, D., Arellano, A., Raeder, K., Anderson, J., & Worden, H. (2024). Advantages of assimilating multi-spectral satellite retrievals of atmospheric composition: A demonstration using MOPITT CO products. Atmospheric Measurement Techniques, 1--30. doi:https://doi.org/10.5194/amt-17-1941-2024
• Gaubert, B., Edwards, D. P., Anderson, J. L., Arellano, A. F., Barr'e, J., Buchholz, R. R., Darras, S., Emmons, L. K., Fillmore, D., Granier, C., & others, . (2023). Global Scale Inversions from MOPITT CO and MODIS AOD. Remote Sensing, 15(19), 4813.
• Gaubert, B., Edwards, D. P., Anderson, J. L., Arellano, A. F., Barré, J., Buchholz, R. R., Darras, S., Emmons, L. K., Fillmore, D., Granier, C., Hannigan, J. W., Ortega, I., Raeder, K., Soulié, A., Tang, W., Worden, H. M., & Ziskin, D. (2023).

  Global Scale Inversions from MOPITT CO and MODIS AOD

  . Remote Sensing, 15(19), 4813. doi:10.3390/rs15194813
• Hilario, M., Arellano, A. F., Behrangi, A., Crosbie, E. C., DiGangi, J. P., Diskin, G. S., Shook, M. A., Ziemba, L. D., & Sorooshian, A. (2024). Assessing potential indicators of aerosol wet scavenging during long-range transport. Atmospheric Measurement Techniques, 17(1), 37--55. doi:https://doi.org/10.5194/amt-17-37-2024
• Lorenzo, G. R., Arellano, A. F., Cambaliza, M. O., Castro, C., Templonuevo Cruz, M., Di Girolamo, L., Gacal, G. F., Hilario, M. A., Lagrosas, N., Ong, H. J., Simpas, J. B., Uy, S. N., & Sorooshian, A. (2023). An Aerosol Climatology via Remote Sensing over Metro Manila, Philippines. Atmospheric Chemistry and Physics, 23. doi:10.5194/acp-23-10579-202
• Risanto, C. B., Moker, J. M., Arellano, A. F., Castro, C. L., Serra, Y. L., Luong, T. M., & Adams, D. K. (2023).

  On the Collective Importance of Model Physics and Data Assimilation on Mesoscale Convective System and Precipitation Forecasts over Complex Terrain

  . Monthly Weather Review, 151(8), 1993-2008. doi:10.1175/mwr-d-22-0221.1
• Risotto, C. B., Arellano, A. F., Moker, J. M., Castro, C. L., Serra, Y. L., Luong, T. M., & Adams, D. K. (2023). On the Importance of Multi-scale Constraints on Mesoscale Convective System and Precipitation Forecasts over Complex Terrain. Monthly Weather Review, 151. doi:10.1175/MWR-D-22-0221.1
• Yuan, S., Arellano, A. F., Knickrehm, L., Chang, H., Castro, C. L., & Furlong, M. (2023). Towards quantifying atmospheric dispersion of pesticide spray drift in Yuma County Arizona. Atmospheric Environment, 319(120262). doi:10.1016/j.atmosenv.2023.120262
• Arellano, A. F., McKinnon, J. M., Roychoudhury, C., He, C., & Kumar, R. (2022). On the Relevance of Aerosols to Snow Cover Variability Over High Mountain Asia. Geophysical Research Letters, 49(18). doi:10.1029/2022gl099317
• Roychoudhury, C., He, C., Kumar, R., McKinnon, J. M., & Arellano Jr., ,. (2022). On the Relevance of Aerosols to Snow Cover Variability Over High Mountain Asia. Geophysical Research Letters, 49(18), e2022GL099317.
• Adams, D. K., Moker, J. M., Arellano, A. F., Castro, C. L., & Risanto, C. B. (2021). The impact of assimilating GPS precipitable water vapor in convective-permitting WRF-ARW on North American monsoon precipitation forecasts over northwest Mexico. Monthly Weather Review.
• Liang, J., Chen, Y., Arellano, A. F., & Mamun, A. A. (2021). Model Sensitivity Study of the Direct Radiative Impact of Saharan Dust on the Early Stage of Hurricane Earl. Atmosphere, 12(9).
• Lorenzo, G. R., Ba\~naga, P. A., Cambaliza, M. O., Cruz, M. T., AzadiAghdam, M., Arellano, A., Betito, G., Braun, R., Corral, A. F., Dadashazar, H., Edwards, E., Eloranta, E., Holz, R., Leung, G., Ma, L., MacDonald, A. B., Reid, J. S., Simpas, J. B., Stahl, C., , Visaga, S. M., et al. (2021). Measurement report: Firework impacts on air quality in Metro Manila, Philippines, during the 2019 New Year revelry. Atmospheric Chemistry and Physics, 21(8), 6155--6173.
• Pfister, G., Eastham, S., Arellano, A., Aumont, B., Barsanti, K., Barth, M., Conley, A., Davis, N., Emmons, L., Fast, J., Fiore, A., Gaubert, B., Goldhaber, S., Granier, C., Grell, G., Guevara, M., Henze, D., Hodzic, A., Liu, X., , Marsh, D., et al. (2021). Making MUSICA: The Multi-Scale Infrastructure for Chemistry and Aerosols. Bulletin of the American Meteorological Society, 102(9). doi:10.1175/BAMS-D-19-0331.A
• Risanto, C. B., Castro, C. L., Arellano, A. F., Moker, J. M., & Adams, D. K. (2021). The Impact of Assimilating GPS Precipitable Water Vapor in Convective-Permitting WRF-ARW on North American Monsoon Precipitation Forecast over Northwest Mexico. Monthly Weather Review. doi:https://doi.org/10.1175/MWR-D-20-0394.1
• Arellano, A. F., Pfister, G. G., Eastham, S. D., Aumont, B., Barsanti, K. C., Barth, M. C., Conley, A., Davis, N. A., Emmons, L. K., Fast, J. D., Fiore, A. M., Gaubert, B., Goldhaber, S., Granier, C., Grell, G. A., Guevara, M., Henze, D. K., Hodzic, A., Liu, X., , Marsh, D. R., et al. (2020). The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA). Bulletin of the American Meteorological Society, 101(10), E1743-E1760. doi:10.1175/bams-d-19-0331.1
• Gaubert, B., Emmons, L. K., Raeder, K., Tilmes, S., Miyazaki, K., Arellano Jr., ,. A., Elguindi, N., Granier, C., Tang, W., Barr\'e, J., Worden, H. M., Buchholz, R. R., Edwards, D. P., Franke, P., Anderson, J. L., Saunois, M., Schroeder, J., Woo, J., Simpson, I. J., , Blake, D. R., et al. (2020). Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ. Atmospheric Chemistry and Physics, 20(23), 14617--14647.
• Lorenzo, G. R., Ba\~naga, P. A., Cambaliza, M. O., Cruz, M. T., Azadi Agdham, M., Arellano, A., Betito, G., Braun, R., Corral, A. F., Dadashazar, H., Edwards, E., Eloranta, E., Holz, R., Leung, G., Ma, L., MacDonald, A. B., Simpas, J. B., Stahl, C., Visaga, S. M., & Sorooshian, A. (2020). Measurement report: Fireworks impacts on air quality in Metro Manila, Philippines during the 2019 New Year revelry. Atmospheric Chemistry and Physics Discussions, 2020, 1--34.
• Pfister, G. G., Eastham, S. D., Arellano, A. F., Aumont, B., Barsanti, K. C., Barth, M. C., Conley, A., Davis, N. A., Emmons, L. K., Fast, J. D., Fiore, A. M., Gaubert, B., Goldhaber, S., Granier, C., Grell, G. A., Guevara, M., Henze, D. K., Hodzic, A., Liu, X., , Marsh, D. R., et al. (2020). The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA). Bulletin of the American Meteorological Society, 101(10), E1743-E1760.
• Tang, W., Gaubert, B., Emmons, L., Choi, Y., DiGangi, J. P., Diskin, G. S., Xu, X., He, C., Worden, H., Tilmes, S., Buchholz, R., Halliday, H. S., & Arellano, A. F. (2020). On the relationship between tropospheric CO and CO$_2$ during KORUS-AQ and its role in constraining anthropogenic CO$_2$. Atmospheric Chemistry and Physics Discussions, 2020, 1--53.
• Arellano, A. F., Henze, D. K., & Saide, P. E. (2019). Data Assimilation and Inverse Modeling of the Atmospheric Composition II Posters. American Geophysical Union.
• Minjarez-Sosa, C. M., Fierro, L. M., Adams, D. K., Arellano, A. F., Moker, Jr., J. M., Castro, C. L., & Risanto, C. B. (2019). Evaluating Forecast Skills of Moisture from Convective-Permitting WRF-ARW Model during 2017 North American Monsoon Season. Atmosphere. doi:10.3390/atmos10110694
• Saide, P. E., Henze, D. K., & Arellano, A. F. (2019). Data Assimilation and Inverse Modeling of the Atmospheric Composition I. American Geophysical Union.
• Tang, W., Arellano, A. F., Gaubert, B., Miyazaki, K., & Worden, H. M. (2019). Satellite data reveal a common combustion emission pathway for major cities in China. Atmospheric Chemistry and Physics, 19(7), 4269--4288.
• Tang, W., Emmons, L. K., Arellano Jr, ,., Gaubert, B., Knote, C., Tilmes, S., Buchholz, R. R., Pfister, G. G., Diskin, G. S., Blake, D. R., Blake, N. J., Meinardi, S., DiGangi, J. P., Choi, Y., Woo, J., He, C., Schroeder, J. R., Suh, I., Lee, H., , Jo, H., et al. (2019). Source Contributions to Carbon Monoxide Concentrations During KORUS-AQ Based on CAM-chem Model Applications. Journal of Geophysical Research: Atmospheres, 124(5), 2796-2822.
• Arellano, A. F. (2018). Exploring Multiple Constraints of Anthropogenic Pollution in Combustion Regions from Current Satellite Retrievals of Atmospheric Composition. American Geophysical Union.
• Edwards, D. P., Worden, H. M., Neil, D., Francis, G., Valle, T., & Arellano Jr., ,. A. (2018). The CHRONOS mission: capability for sub-hourly synoptic observations of carbon monoxide and methane to quantify emissions and transport of air pollution. Atmospheric Measurement Techniques, 11(2), 1061--1085.
• Fox, A., Hoar, T., Anderson, J., Arellano, A. F., Smith, W., Litvak, M., MacBean, N., Schimel, D., & Moore, D. (2018). Evaluation of a Data Assimilation System for Land Surface Models using CLM4.5. Journal of Advances in Modeling Earth Systems.
• Granier, C., Arellano, A. F., & Stavrakou, J. (2018). The new Analysis of eMIssions usinG Observations (AMIGO) project of IGAC. IGACnews.
• Jiang, Z., Worden, H., Worden, J., Miyazaki, K., McDonald, B., Qu, Z., Henze, D., Jones, D., Arellano, A. F., Fischer, E., Zhu, L., & Boersma, K. F. (2018). Unexpected slowdown of US pollutant emission reduction in the past decade. Proceedings of the National Academy of Sciences.
• Moker, J., Castro, C., Serra, Y., Arellano, A. F., & Adams, D. (2018). Convective-permitting hindcast simulations during The North American Monsoon GPS Transect Experiment 2013: Establishing Baseline Model Performance Without Data Assimilation. Journal of Applied Meteorology and Climatology.
• Raman, A., Arellano, A. F., Monache, L. D., Alessandrini, S., Cheng, W., & Kumar, R. (2021). Exploring analog-based schemes for Aerosol Optical Depth forecasting with WRF-Chem. Atmospheric Environment, 246(118134). doi:10.1016/j.atmosenv.2020.118134
• Serra, Y. L., Haase, J. S., Adams, D. K., Fu, Q., Ackerman, T. P., Alexander, M. J., Arellano, A., Back, L., Chen, S., Emanuel, K., Fuchs, Z., Kuang, Z., Mapes, B., Neelin, D., Raymond, D., Sobel, A. H., Staten, P. W., Subramanian, A., Thompson, D., , Vecchi, G., et al. (2018). The Risks of Contracting the Acquisition and Processing of the Nation’s Weather and Climate Data to the Private Sector. Bulletin of the American Meteorological Society, 99(5), 869-870.
• Tang, W., Arellano, A. F., DiGangi, J. P., Choi, Y., Diskin, G. S., Agust'i-Panareda, A., Parrington, M., Massart, S., Gaubert, B., Lee, Y., Kim, D., Jung, J., Hong, J., Hong, J., Kanaya, Y., Lee, M., Stauffer, R. M., Thompson, A. M., Flynn, J. H., & Woo, J. (2018). Evaluating High-Resolution Forecasts of Atmospheric CO and CO2 from a Global Prediction System during KORUS-AQ Field Campaign. Atmospheric Chemistry and Physics, 18(15), 11007-11030. doi:10.5194/acp-18-11007-2018
• Tang, W., Arellano, A. F., Gaubert, B., Miyazaki, K., & Worden, H. M. (2018). Satellite Data Reveals a Common Combustion Emission Pathway for Major Cities in China. Atmospheric Chemistry and Physics Discussions, 2018, 1--27.
• Wespes, C., Hadji-lazaro, J., George, M., Clerbaux, C., Boynard, A., & Arellano, A. F. (2018). Emerging Patterns of O 3 Sensitivity to CO over Megacities Derived from Satellite Retrievals. The EGU General Assembly, 20.
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  The availability of long term multispecies retrievals offers an opportunity to study spatiotemporal patterns of atmo- spheric composition, especially over large anthropogenic pollution regions. Here, we jointly analyze IASI retrievals of O3 and CO (along with OMI NO2) to explore additional observational constraints on anthropogenic pollution. In particular, we estimate the trends of the enhancement ratios derived from IASI O3 and CO and OMI NO2 over major combustion regions in China and United States. Our results show intriguing differences of dO3/dCO across Chinese megacities. In particular, Beijing and Shenzhen shows a positive linear trend (0.58±2.15 and 0.38±0.42 %/yr respectively) while Shanghai shows a negative trend (-062±0.67%/yr). This may be attributed to differences in VOC-NOx-O3 regime between these cities, which predictive models of atmospheric composition should be able to capture. On the other hand, enhancements of O3 derived from these ratios show a pattern of decreasing to increasing trend across Beijing, Shanghai, and Shenzhen which may indicate differences in combustion-related activity between these cities consistent with the developing economic status of these cities. We suggest further evaluation against other datasets (ground- based, airborne, or other retrievals) to enhance the rigor of these find- ings. Nevertheless, this study offers an impetus towards characterizing other species relationships (e.g., IASI NH3, CH4, CO2) not only as basis for monitoring consistency in atmospheric composition but also as a way to fully utilize the information content of these retrieval products in the context of data assimilation and reanalysis.
• tang, W., Emmons, L., Arellano, A. F., Gaubert, B., Knote, C., Tilmes, S., Buchholz, R., Pfister, G., Diskin, G., Blake, D., Blake, N., DiGangi, J., & Choi, Y. (2018). Source Contribution to Carbon Monoxide during KORUS-AQ Using CAM-Chem Tagged Tracers. Journal of Geophysical Research.
• Arellano, A. F., & Raman, A. (2017). Spatial and Temporal Variations in Characteristic Ratios of Elemental Carbon to Carbon Monoxide and Nitrogen Oxides across the United States. Environmental Science & Technology, 51(12), 6829-6838. doi:10.1021/acs.est.7b00161
• Arellano, A. F., Gaubert, B., Worden, H. M., Emmons, L. K., Tilmes, S., Barré, J., Martinez Alonso, S., Vitt, F., Anderson, J. L., Alkemade, F., Houweling, S., & Edwards, D. P. (2017). Chemical Feedback From Decreasing Carbon Monoxide Emissions. Geophysical Research Letters, 44(19), 9985-9995. doi:10.1002/2017gl074987
• Edwards, D., Worden, H., Neil, D., Francis, G., Valle, T., & Arellano, A. F. (2017). The CHRONOS mission: Capability for sub-hourly synoptic observations of carbon monoxide and methane to quantify emissions and transport of air pollution. Atmospheric Measurement Techniques Discussions. doi:https://doi.org/10.5194/amt-2017-194
• Gaubert, B., Worden, H. M., Arellano, A. F., Emmons, L. K., Tilmes, S., Barre, J., Martinez-Alonso, S., Vitt, F., Anderson, J. L., & Edwards, D. P. (2017). Chemical feedback from decreasing carbon monoxide emissions. Geophysical Research Letters.
• Jiang, Z., Worden, H., Worden, J. R., Henze, D. K., Jones, D., Arellano, A. F., Fischer, E. V., Zhu, L., Miyazaki, K., Boersma, K. F., & Payne, V. H. (2017). Inconsistent decadal variations between surface and free tropospheric nitrogen oxides over United States. Atmospheric Chemistry and Physics Discussions, 2017, 1--27.
• Jiang, Z., Worden, J., Worden, H., Deeter, M., Jones, D., & Arellano, A. F. (2017). Fifteen year CO emission estimates constrained with MOPITT CO measurements. Atmospheric Chemistry and Physics.
• Montan'e, F., Fox, A. M., Arellano, A. F., MacBean, N., Alexander, M. R., Dye, A., Bishop, D. A., Trouet, V., Babst, F., Hessl, A. E., Pederson, N., Blanken, P. D., Bohrer, G., Gough, C. M., Litvak, M. E., Novick, K. A., Phillips, R. P., Wood, J. D., & Moore, D. (2017). Evaluating the effect of alternative carbon allocation schemes in a land surface model~(CLM4.5) on carbon fluxes, pools, and turnover in temperate forests. Geoscientific Model Development, 10(9), 3499--3517.
• Raman, A., & Arellano, A. F. (2017). Characteristic ratios of black carbon with carbon monoxide and nitrogen oxides across the United States. Environmental Science and Technology.
• Silva, S. J., & Arellano, A. F. (2017). Characterizing regional-scale combustion using satellite retrievals of CO, NO2, and CO2. Remote Sensing, 9(7). doi:doi:10.3390/rs9070744
• Arellano, A. F. (2016). Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system. Geoscientific Model Development, 9(3), 965-978. doi:10.5194/gmd-9-965-2016
• Barre, J., Edwards, D., Worden, H., Arellano, A. F., Gaubert, B., daSilva, A., Lahoz, W., & Anderson, J. (2016). On the feasibility of monitoring carbon monoxide in the lower troposphere from a constellation of Northern Hemisphere geostationary satellites: Part II. Atmospheric Environment.
• Gaubert, B., Arellano, A. F., Barre, J., Worden, H., Emmons, L., Tilmes, S., Buchholz, R., Wiedinmyer, C., Martinez-Alonso, S., Raeder, K., Collins, N., Anderson, J., Vitt, F., Edwards, D., Andreae, M., Hannigan, J., Petri, C., Strong, K., & Jones, N. (2016). Towards a chemical reanalysis in a coupled chemistry-climate model: An evaluation of MOPITT CO assimilation and its impact on tropospheric composition. Journal of Geophysical Research.
• Raman, A., Arellano, A. F., & Sorooshian, A. (2016). Decreasing Aerosol Loading in the North American Monsoon Region. Atmosphere, 7(2). doi:10.3390/atmos7020024
• Serra, Y., Adams, D., Minjares-Sosa, C., Castro, C., Moker, J., Arellano, A. F., Quintanar, A., Alatorre, L., Granados, A., Vasqueze, E., Holub, K., & DeMets, C. (2016). The North American Monsoon GPS Transect Experiment 2013. Bulletin of the American Meteorological Society.
• Tang, W., & Arellano, A. F. (2017). Investigating the dominant characteristics of fires across the Amazon during 2005–2014 through satellite data synthesis of combustion signatures. Journal of Geophysical Research.
• Worden, J. R., Worden, H. M., Jones, D. B., Jiang, Z., Henze, D. K., Deeter, M. N., & Arellano, A. F. (2016). A 15-year record of CO emissions constrained by MOPITT CO observations. Atmospheric Chemistry and Physics, 17(7), 4565-4583. doi:10.5194/acp-17-4565-2017
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  Abstract. Long-term measurements from satellites and surface stations have demonstrated a decreasing trend of tropospheric carbon monoxide (CO) in the Northern Hemisphere over the past decade. Likely explanations for this decrease include changes in anthropogenic, fires, and/or biogenic emissions or changes in the primary chemical sink hydroxyl radical (OH). Using remotely sensed CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument, in situ methyl chloroform (MCF) measurements from the World Data Centre for Greenhouse Gases (WDCGG) and the adjoint of the GEOS-Chem model, we estimate the change in global CO emissions from 2001 to 2015. We show that the loss rate of MCF varied by 0.2 % in the past 15 years, indicating that changes in global OH distributions do not explain the recent decrease in CO. Our two-step inversion approach for estimating CO emissions is intended to mitigate the effect of bias errors in the MOPITT data as well as model errors in transport and chemistry, which are the primary factors contributing to the uncertainties when quantifying CO emissions using these remotely sensed data. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, and unchanged anthropogenic CO emissions from Europe since 2008. We find decreasing trends of biomass burning CO emissions from boreal North America, boreal Asia and South America, but little change over Africa. In contrast to prior results, we find that a positive trend in CO emissions is likely for India and southeast Asia.
• Adams, D. K., Fernandes, R. M., Holub, K. L., Gutman, S. I., Barbosa, H. M., Machado, L. A., Calhlheiros, A. J., Bennett, R. A., Kursinski, E. R., Sapucci, L. F., DeMets, C., Chagas, G. F., Arellano, A., Filizola, N., Rocha, A. A., Silva, R. A., Assuncao, L. M., Cirino, G. G., Pauliquevis, T., , Portela, B. T., et al. (2015). THE AMAZON DENSE GNSS METEOROLOGICAL NETWORK A New Approach for Examining Water Vapor and Deep Convection Interactions in the Tropics. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 96(12), 2151-2165.
• Arellano, A. F. (2015). Data Assimilation and Inverse Modeling for Atmospheric Composition Applications I. American Geophysical Union.
• Arellano, A. F. (2015). Inverse Modeling of BC and CO Sources in WRF-Chem. NCAR.
• Arellano, A. F. (2015). The characteristics of tropospheric CO2 retrieved by AIRS, GOSAT and IASI in East Asia. Disaster Advances, 8(9), 1-13.
• Barre, J., Edwards, D. P., Gaubert, B., Worden, H. M., Arellano, A. F., & Anderson, J. L. (2015). Carbon Monoxide Data Assimilation for Atmospheric Composition and Climate Science: Evaluating Performance with Current and Future Observations. American Geophysical Union.
• Barre, J., Gaubert, B., Arellano, A. F., Worden, H. M., Edwards, D. P., Deeter, M. N., Anderson, J. L., Raeder, K., Collins, N., Tilmes, S., Francois, G., Clerbaux, C., Emmons, L. K., Pfister, G. G., Coheur, P., & Hurtmans, D. (2015). Assessing the impacts of assimilating IASI and MOPITT CO retrievals using CESM-CAM-chem and DART. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 120(19).
• Barré, J., Gaubert, B., Arellano, A. F., Worden, H. M., Edwards, D. P., Deeter, M. N., Anderson, J. L., Raeder, K., Collins, N., Tilmes, S., Francis, G., Clerbaux, C., Emmons, L. K., Pfister, G. G., Coheur, P., & Hurtmans, D. (2015). Assessing the impacts of assimilating IASI and MOPITT CO retrievals using CESM‐CAM‐chem and DART. Journal of Geophysical Research: Atmospheres, 120(19). doi:10.1002/2015jd023467
• Gaubert, B., Arellano, A. F., Barre, J., Worden, H. M., Emmons, L., Tilmes, S., Buchholz, R. R., Wiedinmyer, C., Vitt, F., Anderson, J. L., Deeter, M. N., & Edwards, D. P. (2015). Chemical Response of CESM/CAM-Chem to MOPITT CO Ensemble-based Chemical Data Assimilation. American Geophysical Union.
• Knote, C., Barre, J., Eckl, M., Hornbrook, R. S., Wiedinmyer, C., Emmons, L., Orlando, J. J., Tyndall, G. S., & Arellano, A. F. (2015). Inferring the unobserved chemical state of the atmosphere: idealized data assimilation experiments. American Geophysical Union.
• Mizzi, A., Arellano, A. F., Edwards, D. P., Anderson, J. L., & Pfister, G. G. (2015). Assimilating Compact Phase Space Retrievals of Atmospheric Composition with WRF-Chem/DART: A Regional Chemical Transport/Ensemble Kalman Filter Data Assimilation System. Geoscientific Model Development Discussion. doi:10.5194/gmdd-8-1-2015
• Montane, F., Arellano, A. F., Scaven, V. L., Moore, D. J., Fox, A. M., Arellano, A. F., & Alexander, M. R. (2015). Comparing Different Model Structures for Carbon Allocation in the Community Land Model (CLM). American Geophysical Union.
• Moon, Y. S., & Arellano, A. F. (2015). The characteristics of tropospheric CO2 retrieved by AIRS, GOSAT and IASI in East Asia. Disaster Advances, 8(9), 1-13.
• Raman, A., & Arellano, A. F. (2015). Using Combustion Tracers to Estimate Surface Black Carbon Distributions in WRF-Chem. American Geophysical Union.
• Arellano, A. F. (2014). Constraints on Local-­to-­Regional Anthropogenic CO2 from Satellite Retrievals of Combustion-­related Trace Gases: Initial Assessment Using Observing System Simulation Experiments (OSSEs). American Geophysical Union.
• Barre, J., Worden, H. M., Mizzi, A. P., Gaubert, B., Edwards, D. P., Arellano, A. F., & Anderson, J. L. (2014). Assessment of IASI CO and MOPITT CO Data Assimilation in CAM-Chem.. Journal of Geophysical Research.
• Edwards, D. P., Worden, H. M., Mizzi, A. P., Lahoz, W., Gaubert, B., Barre, J., Arellano, A. F., & Anderson, J. L. (2014). The atmospheric composition geostationary satellite constellation for air quality and climate science: Evaluating performance with Observation System Simulation Experiments. CEOS.
• Liu, Y., Liu, Y., Matthes, J. H., Moore, D. J., Dietze, M. C., Arellano, A. F., Arellano, A. F., Dawson, A., Fox, A. M., Goring, S., Mclachlan, J. S., Montane, F., Moreno, G., Poulter, B., Quaife, T., Ricciuto, D. M., Schaefer, K., Steinkamp, J., Williams, J. W., , Williams, J. W., et al. (2014). Assessing the long-term performance of terrestrial ecosystem models in northeastern United States: linking model structure and output. American Geophysical Union.
• Raman, A., Arellano Jr., A. F., & Brost, J. J. (2014). Revisiting haboobs in the southwestern United States: An observational case study of the 5 July 2011 Phoenix dust storm. Atmospheric Environment, 89, 179-188.
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  Abstract:Convectively-driven dust storms (or haboobs) are common phenomena in the southwestern United States. However, studies about haboobs in this region are limited. Here, we investigate the state and fate of a massive haboob that hit Phoenix, Arizona on 5 July 2011 using satellite, radar, and ground-based observations. This haboob was a result of strong outflow boundaries (with peak wind gusts of 29ms-1) from storms that were initiated in the southeast of Tucson. In particular, we find three major outflow systems (based on radar data) that were generated by forward propagating storms, ultimately merging near Phoenix. This resulted in peak hourly PM10 and PM2.5 concentrations of 1974μgm-3 and 907μgm-3 at US EPA stations near Phoenix. The high PM concentration is consistent in space and time with the dust wall movement based on our analysis of radar data on hydrometeor classification. Enhanced aerosol loadings over metropolitan Phoenix were also observed on 6 July from NASA Terra/Aqua MODIS aerosol optical depth (AOD) retrievals (AOD>0.8). We infer from CALIOP vertical feature masks and HYSPLIT back trajectories that remnants of the haboob were transported to northwest of Phoenix on 6 July at 2-4km above ground level. Ratios of PM2.5 to PM10 from IMPROVE stations also imply low-level transport to the east of Phoenix on 8 July. Finally, we find that this haboob, which had local and regional impacts, is atypical of other dust events in this region. We note from this analysis that extreme events such as this haboob require an integrated air quality observing system to provide a more comprehensive assessment of these events. © 2014 Elsevier Ltd.
• Rosolem, R., Hoar, T., Arellano, A., Anderson, J. L., Shuttleworth, W. J., Zeng, X., & Franz, T. E. (2014). Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale. HYDROLOGY AND EARTH SYSTEM SCIENCES, 18(11), 4363-4379.
• Zeng, X., Shuttleworth, W. J., Rosolem, R., Hoar, T. J., Franz, T. E., Arellano, A. F., & Anderson, J. L. (2014). Assimilation of near-surface cosmic-ray neutrons improves summertime soil moisture profile estimates at three distinct biomes in the USA. Hydrology and Earth System Sciences Discussions, 11(5), 5515-5558. doi:10.5194/hessd-11-5515-2014
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  Abstract. Aboveground cosmic-ray neutron measurements provide an opportunity to infer soil moisture at the sub-kilometer scale. Initial efforts to assimilate those measurements have shown promise. This study expands such analysis by investigating (1) how the information from aboveground cosmic-ray neutrons can constrain the soil moisture at distinct depths simulated by a land surface model, and (2) how changes in data availability (in terms of retrieval frequency) impact the dynamics of simulated soil moisture profiles. We employ ensemble data assimilation techniques in a "nearly-identical twin" experiment applied at semi-arid shrubland, rainfed agricultural field, and mixed forest biomes in the USA The performance of the Noah land surface model is compared without and with assimilation of observations at hourly intervals and every 2 days Synthetic observations of aboveground cosmic-ray neutrons better constrain the soil moisture simulated by Noah in root zone soil layers (0–100 cm) despite the limited measurement depth of the sensor (estimated to be 12–20 cm). The ability of Noah to reproduce a "true" soil moisture profile is remarkably good regardless of the frequency of observations at the semi-arid site. However, soil moisture profiles are better constrained when assimilating synthetic cosmic-ray neutrons observations hourly rather than every 2 days at the cropland and mixed forest sites. This indicates potential benefits for hydrometeorological modeling when soil moisture measurements are available at relatively high frequency. Moreover, differences in summertime meteorological forcing between the semi-arid site and the other two sites may indicate a possible controlling factor to soil moisture dynamics in addition to differences in soil and vegetation properties.
• Lopez, D. H., Rabbani, M. R., Crosbie, E., Raman, A., Arellano, A. F., & Sorooshian, A. (2016). Frequency and Character of Extreme Aerosol Events in the Southwestern United States: A Case Study Analysis in Arizona. Atmosphere, 7(1).
• Silva, S. J., Arellano, A. F., & Worden, H. M. (2013). Toward anthropogenic combustion emission constraints from space-based analysis of urban CO₂/CO sensitivity. Geophysical Research Letters, 40(18), 4971-4976.
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  Abstract: We explore the value of multispectral CO retrievals from NASA/Terra Measurement of Pollution In The Troposphere (MOPITT v5), along with Atmospheric CO2 Observations from Space (ACOSv2.9) CO2 retrievals from the Japan Aerospace Exploration Agency Greenhouse Gases Observing Satellite (GOSAT), for characterizing emissions from anthropogenic combustion. We use these satellite retrievals to analyze observed CO2/CO enhancement ratios (ΔCO2/ΔCO) over megacities. Since CO is coemitted with CO2 in anthropogenic combustion, the observed ΔCO 2/ΔCO characterizes the general trend in combustion activity. Our analyses show patterns in ΔCO2/ΔCO that correspond well with the developed/developing status of megacities, and ΔCO 2/ΔCO that agree well with available literature and emission inventories to approximately 20%. Comparisons with ΔCO2/ ΔCO derived from Total Carbon Column Observing Network measurements show similar agreement, where some of the differences in observed ΔCO 2/ΔCO are due to representativeness and limited GOSAT data. Our results imply potential constraints in anthropogenic combustion from GOSAT/MOPITT, particularly in augmenting our carbon monitoring systems. © 2013. American Geophysical Union. All Rights Reserved.
• Worden, H. M., Edwards, D. P., Deeter, M. N., Fu, D., Kulawik, S. S., Worden, J. R., & Arellano, A. (2013). Averaging kernel prediction from atmospheric and surface state parameters based on multiple regression for nadir-viewing satellite measurements of carbon monoxide and ozone. Atmospheric Measurement Techniques, 6(7), 1633-1646.
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  Abstract: A current obstacle to the observation system simulation experiments (OSSEs) used to quantify the potential performance of future atmospheric composition remote sensing systems is a computationally efficient method to define the scene-dependent vertical sensitivity of measurements as expressed by the retrieval averaging kernels (AKs). We present a method for the efficient prediction of AKs for multispectral retrievals of carbon monoxide (CO) and ozone (O3) based on actual retrievals from MOPITT (Measurements Of Pollution In The Troposphere) on the Earth Observing System (EOS)-Terra satellite and TES (Tropospheric Emission Spectrometer) and OMI (Ozone Monitoring Instrument) on EOS-Aura, respectively. This employs a multiple regression approach for deriving scene-dependent AKs using predictors based on state parameters such as the thermal contrast between the surface and lower atmospheric layers, trace gas volume mixing ratios (VMRs), solar zenith angle, water vapor amount, etc. We first compute the singular value decomposition (SVD) for individual cloud-free AKs and retain the first three ranked singular vectors in order to fit the most significant orthogonal components of the AK in the subsequent multiple regression on a training set of retrieval cases. The resulting fit coefficients are applied to the predictors from a different test set of test retrievals cased to reconstruct predicted AKs, which can then be evaluated against the true retrieval AKs from the test set. By comparing the VMR profile adjustment resulting from the use of the predicted vs. true AKs, we quantify the CO and O3 VMR profile errors associated with the use of the predicted AKs compared to the true AKs that might be obtained from a computationally expensive full retrieval calculation as part of an OSSE. Similarly, we estimate the errors in CO and O3 VMRs from using a single regional average AK to represent all retrievals, which has been a common approximation in chemical OSSEs performed to date. For both CO and O3 in the lower troposphere, we find a significant reduction in error when using the predicted AKs as compared to a single average AK. This study examined data from the continental United States (CONUS) for 2006, but the approach could be applied to other regions and times. © 2013 Author(s).
• Youn, J., Wang, Z., Wonaschuetz, A., Arellano, A., Betterton, E. A., & Sorooshian, A. (2013). Evidence of aqueous secondary organic aerosol formation from biogenic emissions in the North American Sonoran Desert. GEOPHYSICAL RESEARCH LETTERS, 40(13), 3468-3472.
• Hyer, E. J., Wang, J., & Arellano, A. F. (2012). Biomass Burning - Observations, Modeling, and Data Assimilation. Bulletin of the American Meteorological Society. doi:10.1175/BAMS-D-11-00064.1
• Friedli, H. R., Arellano Jr., A. F., Geng, F., Cai, C., & Pan, L. (2011). Measurements of atmospheric mercury in Shanghai during September 2009. Atmospheric Chemistry and Physics, 11(8), 3781-3788.
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  Abstract: We report on total gaseous mercury (TGM) measurements made in Pudong, Shanghai in August/September 2009. The average TGM was 2.7 ± 1.7 ng mg-3. This represents about 90% of the total atmospheric mercury. This is an underestimate for an annual-mean concentration because the meteorology in September favored predominantly easterly oceanic air, replaced in other seasons by airflow from industrial areas. The observed TGM follows a pattern seen in other cities around the world: a background elevated over mean hemispheric background (1.5 ng m-3), and pollution plumes of different magnitude and duration, interspersed with very sharp spikes of high concentration (60 ng mg-3). The September 2009 Shanghai measurements are lower than those reported for most other Chinese cities and Mexico City, and similar to concentrations found in some Asian and in North American cities. Such comparisons are tenuous because of differences in season and year of the respective measurements. Our results should not be used for regulatory purposes. We find that the observed TGM are most likely coming from coal fired power plants, smelters and industrial sources, based on its high correlation with NOx, SO2, CO and wind directions. © 2011 Author(s).
• Arellano Jr., A. F., Hess, P. G., Edwards, D. P., & Baumgardner, D. (2010). Constraints on black carbon aerosol distribution from Measurement of Pollution in the Troposphere (MOPITT) CO. Geophysical Research Letters, 37(17).
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  Abstract: We present an approach to constrain simulated atmospheric black carbon (BC) using carbon monoxide (CO) observations. The approach uses: (1) the Community Atmosphere Model with Chemistry to simulate the evolution of BC and CO within an ensemble of model simulations; (2) satellite CO retrievals from the MOPITT/Terra instrument to assimilate observed CO into these simulations; (3) the derived sensitivity of BC to CO within these simulations to correct the simulated BC distributions. We demonstrate the performance of this approach through model experiments with and without the BC corrections during the period coinciding with the Intercontinental Chemical Transport Experiment (INTEX-B). Our results show significant improvements (∼50%) in median BC profiles using constraints from MOPITT, based on comparisons with INTEX-B measurements. We find that assimilating MOPITT CO provides considerable impact on simulated BC concentrations, especially over source regions. This approach offers an opportunity to augment our current ability to predict BC distributions. © 2010 by the American Geophysical Union.
• Pfister, G., Emmons, L. K., Edwards, D. P., Arellano, A., Sachse, G., & Campos, T. (2010). Variability of springtime transpacific pollution transport during 2000-2006: The INTEX-B mission in the context of previous years. Atmospheric Chemistry and Physics, 10(3), 1345-1359.
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  Abstract: We analyze the transport of pollution across the Pacific during the NASA INTEX-B (Intercontinental Chemical Transport Experiment Part B) campaign in spring 2006 and examine how this year compares to the time period for 2000 through 2006. In addition to aircraft measurements of carbon monoxide (CO) collected during INTEX-B, we include in this study multi-year satellite retrievals of CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument and simulations from the chemistry transport model MOZART-4. Model tracers are used to examine the contributions of different source regions and source types to pollution levels over the Pacific. Additional modeling studies are performed to separate the impacts of inter-annual variability in meteorology and dynamics from changes in source strength. Interannual variability in the tropospheric CO burden over the Pacific and the US as estimated from the MOPITT data range up to 7% and a somewhat smaller estimate (5%) is derived from the model. When keeping the emissions in the model constant between years, the year-to-year changes are reduced (2%), but show that in addition to changes in emissions, variable meteorological conditions also impact transpacific pollution transport. We estimate that about 1/3 of the variability in the tropospheric CO loading over the contiguous US is explained by changes in emissions and about 2/3 by changes in meteorology and transport. Biomass burning sources are found to be a larger driver for inter-annual variability in the CO loading compared to fossil and biofuel sources or photochemical CO production even though their absolute contributions are smaller. Source contribution analysis shows that the aircraft sampling during INTEX-B was fairly representative of the larger scale region, but with a slight bias towards higher influence from Asian contributions.
• Prabhakar, G., Sorooshian, A., Toffol, E., Arellano, A. F., & Betterton, E. A. (2014). Spatiotemporal distribution of airborne particulate metals and metalloids in a populated arid region. ATMOSPHERIC ENVIRONMENT, 92, 339-347.
• Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., & Avellano, A. (2009). THE DATA ASSIMILATION RESEARCH TESTBED A Community Facility. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 90(9), 1283-1296.
• Edwards, D. P., Arellano Jr., A. F., & N., M. (2009). A satellite observation system simulation experiment for carbon monoxide in the lowermost troposphere. Journal of Geophysical Research D: Atmospheres, 114(14).
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  Abstract: We demonstrate the feasibility of using observing system simulation experiment (OSSE) studies to help define quantitative trace gas measurement requirements for satellite missions and to evaluate the expected performance of proposed observing strategies. The 2007 U.S. National Research Council Decadal Survey calls for a geostationary (GEO) satellite mission for atmospheric composition and air quality applications (Geostationary Coastal and Air Pollution Events Mission (GEO-CAPE)). The requirement includes a multispectral (near-infrared and thermal infrared) measurement of carbon monoxide (CO) at high spatiotemporal resolution with information on lowermost troposphere concentration. We present an OSSE to assess the improvement in surface CO characterization that would result from the addition of a GEO-CAPE CO measurement to current low Earth orbit (LEO) thermal infrared-only measurements. We construct instrument simulators for these two measurement scenarios and study the case of July 2004 when wildfires in Alaska and Canada led to significant CO pollution over the contiguous United States. Compared to a control experiment, an ensemble-based data assimilation of simulated satellite observations in a global model leads to improvements in both the surface CO distributions and the time evolution of CO profiles at locations affected by wildfire plumes and by urban emissions. In all cases, an experiment with the GEO-CAPE CO measurement scenario (overall model skill of 0.84) performed considerably better than the experiment with the current LEO/thermal infrared measurement (skill of 0.58) and the control (skill of 0.07). This demonstrates the advantages of increased sampling from GEO and enhanced measurement sensitivity to the lowermost troposphere with a multispectral retrieval. Copyright 2009 by the American Geophysical Union.
• Friedli, H. R., Arellano Jr., A. F., Cinnirella, S., & Pirrone, N. (2009). Mercury emissions from global biomass burning: Spatialand temporal distribution. Mercury Fate and Transport in the Global Atmosphere: Emissions, Measurements and Models, 193-220.
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  Abstract: This chapter represents a new addition to the UNEP global mercury budget: the mercury emissions from biomass burning, here defined as emissions from wildfires and prescribed burns, and excluding contributions from bio-fuel consumption and charcoal production and use. The results cover the 1997-2006 timeframe. The average annual global mercury emission estimate from biomass burning for 1997-2006 is 675 ± 240 Mg yr-1. This accounts for 8% of all current anthropogenic and natural emissions. The largest Hg emissions are from tropical and boreal Asia, followed by Africa and South America. They do not coincide with the largest carbon biomass burning emissions, which originate from Africa. Our methodology for budget estimation is based on a satellite-constrained bottom-up global carbon fire emission database (GFED version 2), which divides the globe into regions with similar ecosystems and burn behaviour. To estimate mercury emissions, the carbon model output is paired with regional emission factors for Hg, EF(Hg). There are large uncertainties in the budget estimation associated with burned area, fuel mass, and combustion completeness. The discrepancy between the model and traditional ground based assessments (e.g. FRA, 2000) is unacceptably large at this time. Of great urgency is the development and validation of a model for mercury cycling in forests, accounting for the biogeochemistry for each region. This would provide an understanding of the source/sink relationship and thus mercury accumulation or loss in ecosystems. Limiting the burning of tropical and boreal forests would have two beneficial effects: reducing the source of mercury releases to the atmosphere from burning, and maintaining a sink for atmospheric mercury. Restricting the global release mercury would reduce the vegetation/soil pools, and the potential Hg release in case of fire. © 2009 Springer-Verlag New York.
• Friedli, H. R., Arellano, A. F., Cinnirella, S., & Pirrone, N. (2009). Initial estimates of mercury emissions to the atmosphere from global biomass burning. Environmental Science and Technology, 43(10), 3507-3513.
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  PMID: 19544847;Abstract: The average global annual mercury emission estimate from biomass burning (BMB) for 1997-2006 is 675 ± 240 Mg/year. This is equivalent to 8% of all currently known anthropogenic and natural mercury emissions. By season, the largest global emissions occur in August and September, the lowest during northern winters. The interannual variability is large and region-specific, and responds to drought conditions. During this particular time period, the largest mercury emissions are from tropical and boreal Asia, followed by Africa and South America. They do not coincide with the largest carbon biomass burning emissions, which originate from Africa. Frequently burning grasslands in Africa and Australia, and agricultural waste burning globally, contribute relatively little to the mercury budget. The released mercury from BMB is eventually deposited locally and globally and contributes to the formation of toxic bioaccumulating methyl mercury. Furthermore, increasing temperature in boreal regions, where the largest soil mercury pools reside, is expected to exacerbate mercury emission because of more frequent, larger, and more intense fires. © 2009 American Chemical Society.
• Sachse, G. W., Pfister, G., Emmons, L. K., Edwards, D., Campos, T., & Arellano, A. F. (2009). Transpacific pollution transport during INTEX-B: spring 2006 in context to previous years. Atmospheric Chemistry and Physics, 9(4), 17817-17849.
• Malmberg, A., Arellano, A., Edwards, D. P., Flyer, N., Nychka, D., & Wikle, C. (2008). Interpolating fields of carbon monoxide data using a hybrid statistical-physical model. Annals of Applied Statistics, 2(4), 1231-1248.
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  Abstract: Atmospheric Carbon Monoxide (CO) provides a window on the chemistry of the atmosphere since it is one of few chemical constituents that can be remotely sensed, and it can be used to determine budgets of other greenhouse gases such as ozone and OH radicals. Remote sensing platforms in geostationary Earth orbit will soon provide regional observations of CO at several vertical layers with high spatial and temporal resolution. However, cloudy locations cannot be observed and estimates of the complete CO concentration fields have to be estimated based on the cloud-free observations. The current state-of-the-art solution of this interpolation problem is to combine cloud-free observations with prior information, computed by a deterministic physical model, which might introduce uncertainties that do not derive from data. While sharing features with the physical model, this paper suggests a Bayesian hierarchical model to estimate the complete CO concentration fields. The paper also provides a direct comparison to state-of-the-art methods. To our knowledge, such a model and comparison have not been considered before. © Institute of Mathematical Statistics.
• Arellano Jr., A. F., Raeder, K., Anderson, J. L., Hess, P. G., Emmons, L. K., Edwards, D. P., Pflster, G. G., Campos, T. L., & Sachse, G. W. (2007). Evaluating model performance of an ensemble-based chemical data assimilation system during INTEX-B field mission. Atmospheric Chemistry and Physics, 7(21), 5695-5710.
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  Abstract: We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3) with simplified chemistry and the Data Assimilation Research Testbed (DART) assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO) by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument. We verify the system performance using independent CO observations taken on board the NSF/NCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B). Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence). The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (∼ 140 ppbv). Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China) and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements.
• Bian, H., Chin, M., Kawa, S. R., Duncan, B., Arellano, A., & Kasibhatla, P. (2007). Sensitivity of global CO simulations to uncertainties in biomass burning sources. Journal of Geophysical Research D: Atmospheres, 112(23).
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  Abstract: One of the largest uncertainties for the modeling of tropospheric carbon monoxide (CO) concentration is the timing, location, and magnitude of biomass burning emissions. We investigate the sensitivity of simulated CO in the Unified Chemistry Transport Model (UCTM) to several biomass burning emissions, including four bottom-up and two top-down inventories. We compare the sensitivity experiments with observations from MOPITT, surface and airborne NOAA Global Monitoring Division network data, and the TRACE-P field campaign. The variation of the global annual emissions of these six biomass burning inventories is within 30%; however, their regional variations are often much higher (factor of 2-5). These uncertainties translate to about 6% variation in the global simulated CO but more than a 100% variation in some regions. The annual mean CO variation is greater in the Southern Hemisphere (>12%) than in the Northern Hemisphere (
• Arellano Jr., A. F., & Hess, P. G. (2006). Sensitivity of top-down estimates of CO sources to GCTM transport. Geophysical Research Letters, 33(21).
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  Abstract: Estimates of CO sources derived from inversions using satellite observations still exhibit discrepancies. Here, we conduct controlled inverse analyses to elucidate the influence of model transport on the robustness of regional CO source estimates. We utilized Model of Ozone and Related chemical Tracers global chemical transport models (GCTM) driven by National Centers for Environmental Prediction and European Centre for Medium-Range Weather Forecast reanalyses, and GEOS-Chem GCTM driven by Global Modeling and Assimilation Office assimilated meteorology to generate response functions for prescribed regional CO sources. We find that inter-model differences in CO due to differences in transport are within 10-30% of inter-model mean CO concentration. However, these differences can translate to regionally significant spread in source estimates. While we find that CO source estimates for East Asia and North Africa are reasonably robust, we find inconsistencies and inter-model spread of greater than 40% in our source estimates for Indonesia, South America, Europe and Russia. This indicates the need for rigorous assessment on uncertainties in top-down source estimates through model inter-comparisons and ensemble approaches. Copyright 2006 by the American Geophysical Union.
• Arellano Jr., A. F., Kasibhatla, P. S., Giglio, L., R., G., Randerson, J. T., & Collatz, G. J. (2006). Time-dependent inversion estimates of global biomass-burning CO emissions using Measurement of Pollution in the Troposphere (MOPITT) measurements. Journal of Geophysical Research D: Atmospheres, 111(9).
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  Abstract: We present an inverse-modeling analysis of CO emissions using column CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) instrument and a global chemical transport model (GEOS-CHEM). We first focus on the information content of MOPITT CO column retrievals in terms of constraining CO emissions associated with biomass burning and fossil fuel/biofuel use. Our analysis shows that seasonal variation of biomass-burning CO emissions in Africa, South America, and Southeast Asia can be characterized using monthly mean MOPITT CO columns. For the fossil fuel/biofuel source category the derived monthly mean emission estimates are noisy even when the error statistics are accurately known, precluding a characterization of seasonal variations of regional CO emissions for this source category. The derived estimate of CO emissions from biomass burning in southern Africa during the June-July 2000 period is significantly higher than the prior estimate (prior, 34 Tg; posterior, 13 Tg). We also estimate that emissions are higher relative to the prior estimate in northern Africa during December 2000 to January 2001 and lower relative to the prior estimate in Central America and Oceania/Indonesia during April-May and September-October 2000, respectively. While these adjustments provide better agreement of the model with MOPITT CO column fields and with independent measurements of surface CO from National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory at background sites in the Northern Hemisphere, some systematic differences between modeled and measured CO fields persist, including model overestimation of background surface CO in the Southern Hemisphere. Characterizing and accounting for underlying biases in the measurement model system are needed to improve the robustness of the top-down estimate. Copyright 2006 by the American Geophysical Union.
• Friedli, H. R., Arellano, A. F., Cinnirella, S., Pirrone, N., Pirrone, N., & Mason, R. (2006). Mercury Emissions from Global Biomass Burning: Spatial and Temporal Distribution. MERCURY FATE AND TRANSPORT IN THE GLOBAL ATMOSPHERE, 193-220.
• Van, G., Randerson, J. T., Giglio, L., Collatz, G. J., Kasibhatla, P. S., & Arellano Jr., A. F. (2006). Interannual variability in global biomass burning emissions from 1997 to 2004. Atmospheric Chemistry and Physics, 6(11), 3423-3441.
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  Abstract: Biomass burning represents an important source of atmospheric aerosols and greenhouse gases, yet little is known about its interannual variability or the underlying mechanisms regulating this variability at continental to global scales. Here we investigated fire emissions during the 8 year period from 1997 to 2004 using satellite data and the CASA biogeochemical model. Burned area from 2001-2004 was derived using newly available active fire and 500 m. burned area datasets from MODIS following the approach described by Giglio et al. (2006). ATSR and VIRS satellite data were used to extend the burned area time series back in time through 1997. In our analysis we estimated fuel loads, including organic soil layer and peatland fuels, and the net flux from terrestrial ecosystems as the balance between net primary production (NPP), heterotrophic respiration (Rh), and biomass burning, using time varying inputs of precipitation (PPT), temperature, solar radiation, and satellite-derived fractional absorbed photosynthetically active radiation (fAPAR). For the 1997-2004 period, we found that on average approximately 58 Pg C year -1 was fixed by plants as NPP, and approximately 95% of this was returned back to the atmosphere via Rh. Another 4%, or 2.5 Pg C year-1 was emitted by biomass burning; the remainder consisted of losses from fuel wood collection and subsequent burning. At a global scale, burned area and total fire emissions were largely decoupled from year to year. Total carbon emissions tracked burning in forested areas (including deforestation fires in the tropics), whereas burned area was largely controlled by savanna fires that responded to different environmental and human factors. Biomass burning emissions showed large interannual variability with a range of more than 1 Pg C year-1, with a maximum in 1998 (3.2 Pg C year -1) and a minimum in 2000 (2.0 Pg C year-1).
• Arellano Jr., A. F., Kasibhatla, P. S., Giglio, L., R., G., & Randerson, J. T. (2004). Top-down estimates of global CO sources using MOPITT measurements. Geophysical Research Letters, 31(1), L01104 1-5.
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  Abstract: We present a synthesis inversion of CO emissions from various geographical regions and for various source categories for the year 2000 using CO retrievals from the MOPITT (Measurements of Pollution in the Troposphere) instrument. We find a large discrepancy between our top-down estimates and recent bottom-up estimates of CO emissions from fossil fuel/biofuel (FFBF) use in Asia. A key conclusion of this study is that CO emissions in East Asia (EAS) are about a factor of 1.8-2 higher than recent bottom-up estimates. Copyright 2004 by the American Geophysical Union.
• R., G., Randerson, J. T., Collatz, G. J., Giglio, L., Kasibhatla, P. S., Arellano Jr., A. F., Olsen, S. C., & Kasischke, E. S. (2004). Continental-Scale Partitioning of Fire Emissions during the 1997 to 2001 El Niño/La Niña Period. Science, 303(5654), 73-76.
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  PMID: 14704424;Abstract: During the 1997 to 1998 El Niño, drought conditions triggered widespread increases in fire activity, releasing CH4 and CO 2 to the atmosphere. We evaluated the contribution of fires from different continents to variability in these greenhouse gases from 1997 to 2001, using satellite-based estimates of fire activity, biogeochemical modeling, and an inverse analysis of atmospheric CO anomalies. During the 1997 to 1998 El Niño, the fire emissions anomaly was 2.1 ± 0.8 petagrams of carbon, or 66 ± 24% of the CO2 growth rate anomaly. The main contributors were Southeast Asia (60%), Central and South America (30%), and boreal regions of Eurasia and North America (10%).
• Koe, L. C., F., A., & McGregor, J. L. (2003). Application of DARLAM to regional haze modeling. Pure and Applied Geophysics, 160(1-2), 189-204.
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  Abstract: The CSIRO Division of Atmospheric Research limited area model (DARLAM) is applied to atmospheric transport modeling of haze in southeast Asia. The 1998 haze episode is simulated using an emission inventory derived from hotspot information and adopting removal processes based on SO2. Results show that the model is able to simulate the transport of haze in the region. The model images closely resemble the plumes of NASA Total Ozone Mapping Spectrometer and Meteorological Service Singapore haze maps. Despite the limitation of input data, particularly for haze emissions, the three-month average pattern correlation obtained for the whole episode is 0.61. The model has also been able to reproduce the general features of transboundary air pollution over a long period of time. Predicted total particulate matter concentration also agrees reasonably well with observation. The difference in the model results from the satellite images may be attributed to the large uncertainties of emission, simplification of haze deposition and transformation mechanisms and the relatively coarse horizontal and vertical resolution adopted for this particular simulation.
• Kasibhatla, P., Arellano, A., Logan, J. A., Palmer, P. I., & Novelli, P. (2002). Top-down estimate of a large source of atmospheric carbon monoxide associated with fuel combustion in Asia. Geophysical Research Letters, 29(19), 6-1.
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  Abstract: Deriving robust regional estimates of the sources of chemically and radiatively important gases and aerosols to the atmosphere is challenging. Here, we focus on carbon monoxide. Using an inverse modeling methodology, we find that the source of carbon monoxide from fossil-fuel and biofuel combustion in Asia during 1994 was 350-380 Tg yr-1, which is 110-140 Tg yr-1 higher than bottom-up estimates derived using traditional inventory-based approaches. This discrepancy points to an important gap in our understanding of the human impact on atmospheric chemical composition.
• Koe, L. C., Arellano Jr., A. F., & McGregor, J. L. (2001). Investigating the haze transport from 1997 biomass burning in Southeast Asia: Its impact upon Singapore. Atmospheric Environment, 35(15), 2723-2734.
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  Abstract: The 1997 Indonesia forest fires was an environmental disaster of exceptional proportions. Such a disaster caused massive transboundary air pollution and indiscriminate destruction of biodiversity in the world. The immediate consequence of the fires was the production of large amounts of haze in the region, causing visibility and health problems within Southeast Asia. Furthermore, fires of these magnitudes are potential contributors to global warming and climate change due to the emission of large amounts of greenhouse gases and other pyrogenic products.The long-range transport of fire-related haze in the region is investigated using trajectories from the CSIRO Division of Atmospheric Research Limited Area Model (DARLAM). Emission scenarios were constructed for hotspot areas in Sumatra and Kalimantan for the months of September and October 1997 to determine the period and fire locations most critical to Singapore. This study also examines some transport issues raised from field observations. Results show that fires in the coastal areas of southeast Sumatra and southwest Kalimantan can be potential contributors to transboundary air pollution in Singapore. Singapore was directly affected by haze from these areas whereas Kuala Lumpur was heavily affected by the haze coming from Sumatra. In most cases, Singapore was more affected by fires from Kalimantan than was Kuala Lumpur. This was mainly a result of the shifting of monsoons. The transition of monsoons resulted in weaker low-level winds and shifted convergence zones near to the southeast of Peninsular Malaysia. In addition to severe drought and massive fire activity in 1997, the timing of the monsoon transition has a strong influence on haze transport in the region. Copyright © 2001 Elsevier Science Ltd.

Proceedings Publications

• Gaubert, B., Mirrezaei, M. A., Arellano, A. F., Fernandez, R. P., Ortega, I., Feng, C., Xu, Y., & Saiz-Lopez, A. (2025). Role of Atmospheric Chemistry in Monitoring Changes in the CH 4 Budget, Investigating the Role of Chemical Feedback. In 105th AMS Annual Meeting.
• Mirrezaei, M. A., Tang, W., Gaubert, B., Emmons, L. K., Guo, Y., Roychoudhury, C., & Arellano, A. F. (2025). Can Global Chemistry-Climate Models Capture Salient Features of an Urban Atmosphere?. In 105th AMS Annual Meeting.
• Pan, K., Arellano, A. F., Tangborn, A., Carroll, B., Demoz, B., & Santanello, J. A. (2025). Assimilation of Doppler Lidar-Derived Planetary Boundary Layer Heights Using the Ensemble Kalman Filter During the PECAN Field Campaign. In 105th AMS Annual Meeting.
• Risanto, C. B., Arellano, A. F., Castro, C. L., Koch, S. E., Shohan, S. S., Weckwerth, T. M., Pinto, J. O., & Kay, J. (2024). Assessing the Impact of Data Assimilation and Microphysics Schemes on Monsoon Precipitation Forecasts over Arizona Complex Terrain. In 21st Conference on Mountain Meteorology.
• Shohan, S. S. (2024). Evaluation of Optimal Mesonetwork Design for Monitoring and Predicting North American Monsoon (NAM) Convection Using Observing System Simulation Experiments (OSSE). In 21st Conference on Mountain Meteorology.

Presentations

• Arellano, A. F. (2023, January). Elucidating Non-linear Chemical and Aerosol Interactions in Earth System Models. Frontiers in Atmospheric Chemistry Seminar Series. Boston, MA: MIT.
• Arellano, A. F. (2023, March). Challenges and Opportunities in Inverse Modeling: A case with Carbon Monoxide Sources. BIRS Mathematic Approaches of Atmospheric Constituents Data Assimilation and Inverse Modeling. BANFF, Alberta, Canada (presented remotely): BANFF.
• Arellano, A. F., & Gaubert, B. (2023, January). Space-Based Observational and Coupled Model Constraints on Hydroxyl Radical Abundance and Methane Loss,. AMS Annual Meeting. Denver, CO: AMS.
• Furlong, M., & Arellano, A. F. (2023, January). Drift from Agricultural Pesticide Applications During Pre-conception and Pregnancy and Associations with Extremely Preterm Birth in Arizona. AMS Annual Meeting. Denver, CO: AMS.
• Gaubert, B., Tang, W., Emmons, L., Worden, H., Ortega, I., Edwards, D., & Arellano, A. F. (2023). Global ensemble chemical data assimilation to efficiently estimate initial conditions and emissions by source. 9th International Symposium on Non-CO2 Greenhouse Gases (NCGG8). Amsterdam, Netherlands.
• Lorenzi, G., Barth, M., Arellano, A. F., Crosbie, E., Diskin, G., Hilario, M., Tilmes, S., Wang, J., Zhang, J., Ziemba, L., & Sorooshian, A. (2023, January). Aerosol Convective Transport in Southeast Asia: Analysis and Evaluation of Aircraft and Modeled Data. AMS Annual Meeting. Denver, CO: AMS.
• Risanto, C. B., Moker, J., Arellano, A. F., Castro, C., Serra, Y., & Adams, D. (2023, January). On the Importance of Multi-Scale Constraints on Mesoscale Convective System and Precipitation Forecasts over Complex Terrain. AMS Annual Meeting. Denver, CO: AMS.
• Arellano, A. F. (2022, October). Towards the Identification of Emergent Properties in Local-to- Global Air Quality and Greenhouse Gases. CHEE Seminar Series. Tucson, AZ: UA CHEE.
• Arellano, A. F. (2021, March). On the Emergence of a Rise in Anthropogenic Combustion in Sub-Saharan Africa. Advancing Air Quality and Carbon Science in Africa (NCAR). Virtual: NCAR.
• Arellano, A. F. (2021, November). Towards Seamless Prediction of Chemical Weather and Air Quality. Program in Applied Mathematics Seminar Series (City Air and University of Arizona Air Quality Seminar). Virtual: UArizona Applied Mathematics and City Air.
• Arellano, A. F. (2022, January). The Impact of Precipitable Water Vapor Data Assimilation on North American Monsoon Precipitation Forecast in Northern Mexico. RIken Data Assimilation Seminar Series. Kobe, Japan (virtual): RIKEN Center for Computational Science.
• Arellano, A. F., & Gaubert, B. (2022, January). Investigating the Interactions between CH4, CO, and OH from Modeling and Observational Perspectives. American Meteorological Society (AMS) 102nd Annual Meeting: 24th Conference on Atmospheric Chemistry. Virtual: AMS.
• Arellano, A. F., McKinnon, J., Roychoudhury, C., Buccholtz, R., & Gaubert, B. (2021, December). Spatio-temporal Pattern Analysis of Trace Gases and Aerosol Abundance Using PCA, SOMs, and Convolution Auto-encoders. 2021 AGU Fall Meeting. New Orleans, LA: AGU.
• McKinnon, J., Roychoudhury, C., Gaubert, B., Buchholz, R., & Arellano, A. F. (2022, January). Spatiotemporal Pattern Analysis of Trace Gases and Aerosol Abundance over Sub-Saharan Africa Using PCA/CCA and SOMs. American Meteorological Society (AMS) 102nd Annual Meeting: 24th Conference on Atmospheric Chemistry. Virtual: AMS.
• Roychoudhury, C., He, C., Kumar, R., & Arellano, A. F. (2021, September). Exploring the association of meteorology and atmospheric composition to snow cover changes: A case study over High-Mountain Asia and Central Andes. Meteorology and Climate - Modeling for Air Quality Conference (MAC-MAQ). Virtual: UC Davis.
• Roychoudhury, C., He, C., Kumar, R., Shrivastava, M., McKinnon, J., & Arellano, A. F. (2021, December). Model simulations and satellite data analysis of aerosol impacts to snow cover over High Mountain Asia. 2021 AGU Fall Meeting. New Orleans, LA: AGU.
• Arellano, A. F. (2020, December). Observational Constraints of Anthropogenic Combustion from Space: Opportunities for Monitoring Efficiency. 1st International Conference on Innovative Technologies for a Sustainable Environment (ICITSE2020). Virtual Conference: Society of Environmental Engineers of the Philippines, Inc..
• Arellano, A. F. (2020, July). Towards the Identification of Emergent Properties in Atmospheric Composition Using Satellite Data: A Case of Megacity Emissions Monitoring from Space. 40th Anniversary and 2020 Annual Scientific Meeting (APAMS). Virtual Conference: Philippine-American Academy of Science and Engineering.
• Arellano, A. F. (2020, November). Investigating the Human Fingerprints in the Atmosphere: The Role of Remote Sensing and Data Science. UP DMMME Distinguished Alumni Seminar. Virtual Conference: University of the Philippines, Dept. of Mining, Metallurgical, and Materials Engineering.
• Brocchi, V., Mottungan, K., Gaubert, B., Tang, W., & Arellano, A. F. (2021, January). On the Emergence of a Rise in Anthropogenic Combustion in Sub-Saharan Africa. American Meteorological Society (AMS) 101st Annual Meeting. Virtual Conference: AMS.
• Mottungan, K., Arellano, A. F., Brocchi, V., & Gaubert, B. (2020, June). Utilizing the synergies between air quality and greenhouse gas measurements in constraining anthropogenic CO2 and CH4 over Sub-Saharan Africa. International Workshop oOn Greenhouse Gas Measurements from Space (IWGGMS-16). Virtual Conference: ECMWF/EUMETSAT/ESA/EC.
• Risanto, C. B., Castro, C. L., Arellano, A. F., Moker, J. M., & Adams, D. K. (2021, January). The Impact of PWV Data Assimilation in Convective-Permitting WRF-ARW on North American Monsoon Precipitation Forecasts over Northwest Mexico. American Meteorological Society (AMS) 101st Annual Meeting. Virtual Conference: AMS.
• Arellano, A. F. (2019, August). Exploring Multiple Observational and Modeling Constraints on Anthropogenic Pollution over Megacities and Biomass Burning Regions: Opportunities and Challenges in Improving Emissions Inventories. 2019 Panorama Actual De las Ciencias Atmosféricas. National Autonomous University of Mexico (UNAM), Mexico City, Mexico: UNAM.
• Arellano, A. F. (2019, August). Substantiating Key Synergies Between Air Quality (AQ) and Greenhouse Gas (GHG) Monitoring from Space: A case for anthropogenic CO2 and CH4 constraints from CO and NO2. Special Seminar, Dept. of Physics, Univ. of Toronto. Toronto, CA.
• Arellano, A. F. (2019, June). Investigating the Utility of CO2 and CO Analysis in Tracking Fossil Fuel CO2. CEOS AC-VC-15: The 15th Meeting of the Atmospheric Composition Virtual Constellation. Tokyo, Japan: JAXA.
• Arellano, A. F. (2019, September). Towards the Identification of Emergent Properties in Atmospheric Composition using Satellite Data. NCAR Frontiers of Atmospheric Science and Chemistry: Integration of Novel Applications and Technological Endeavors (FASCINATE). Boulder, CO: NCAR.
• Arellano, A. F., Gaubert, B., Miyazaki, K., Inness, A., Jiang, Z., Zheng, B., Flemming, J., & Yin, Y. (2019, June). Trends in Carbon Monoxide Abundance as Inferred from an Ensemble of Chemical Reanalyses and their Implications to Air Quality/Greenhouse Gas Emissions Monitoring. 8th International Symposium on Non-CO2 Greenhouse Gases (NCGG8). Amsterdam, The Netherlands: VVM.
• Brocchi, V., Arellano, A. F., Tang, W., & Gaubert, B. (2019, December). Understanding Anthropogenic Combustion in Major Cities of Africa from Multiple Data Streams. 2019 AGU Fall Meeting. San Francisco: AGU.
• Castro, C. L., Adams, D. K., Arellano, A. F., Quintanar, A. I., Ochoa-Moya, C., Minjarez-Sosa, C. M., Rodriguez, J., Lizarraga, C., Vivoni, E., Perez-Ruiz, E., Robles, A., Risanto, C. B., Chang, H. I., Mendoza-Fierro, L., & Moker, Jr., J. M. (2019, January). A New Hydrometeorological Testbed in Northern Mexico for Improved Weather Forecasts and Climate Monitoring. 99th Annual American Meteorological Society Meeting.
• Castro, C. L., Risanto, C. B., Moker, Jr., J. M., Arellano, A. F., Adams, D. K., & Mendoza-Fierro, L. (2019, January). CAZMEX 2017: Improving Monsoon Precipitation Forecasts in Northwest Mexico and Southwest United States. 99th Annual American Meteorological Society Meeting.
• Arellano, A. F. (2018, July/Summer). Emerging Patterns of O3 Sensitivity to CO over Megacities Derived from Satellite Retrievals. JAMSTEC RCGC/IACE/Big-Data seminar. Yokohama, Japan: JAMSTEC.
• Arellano, A. F. (2018, July/Summer). Observational Constraints of Anthropogenic Combustion from Space: Opportunities for Monitoring Efficiency,. Japan Agency for Marine-Earth Science and Technology Air Quality-Greenhouse Gases (AQ-GHG) Joint Meeting. Tokyo, Japan: JAMSTEC.
• Arellano, A. F. (2018, March/Spring). Impact of Total Column Water Vapor Measurements on Short-to-Medium-Range Forecasts of North American Monsoon Precipitation. InSAR​ ​Meteorology​ ​Workshop. Univ. of Miami, FL: NASA.
• Arellano, A. F. (2018, May/Spring). Observational Constraints of Anthropogenic Combustion from Space: Opportunities for Monitoring Efficiency. Committee on Earth Observation Satellites (CEOS) Atmospheric Composition (AC) Virtual Constellation GEOCAPE Joint Meeting. College Park, MD: CEOS.
• Arellano, A. F., Clerbaux, C., Boynard, A., George, M., Wespes, C., & Hadji-Lazaro, J. (2018, April/Spring). Emerging Patterns of O3 Sensitivity to CO over Megacities Derived from Satellite Retrievals. European Geophysical Union General Assembly. Vienna, Austria: EGU.
• Arellano, A. F., Gaubert, B., Miyazaki, K., Inness, A., Jiang, Z., Zheng, B., Flemming, J., & Yin, Y. (2019, January). Long-term Changes in Carbon Monoxide Abundance as Inferred from an Ensemble of Chemical Reanalysis. AMS 99th Annual Meeting. Phoenix, AZ: AMS.
• Arellano, A. F., Tang, W., & Gaubert, B. (2020, January). Anthropogenic Carbon Emission Constraints from CO and NO2 Data Streams. 22nd Conference on Atmospheric Chemistry/100th AMS Annual Meeting. Boston, MA: AMS.
• Risanto, C. B., Castro, C. L., Arellano, A. F., Fierro, L. M., & Moker, J. M. (2020, January). Forecasting North American Monsoon Precipitation with Data Assimilation. 24th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS)/100th AMS Annual Meeting,. Boston, MA: AMS.
• Tang, W., Emmons, L., Arellano, A. F., & Gaubert, B. (2018, June/Summer). CO Source Contributions and Combustion Characteristics during KORUS-AQ. Asia Oceania Geosciences Society (AOGS) Annual Meeting. Honolulu, Hawaii: AOGS.
• Tang, W., Gaubert, B., Arellano, A. F., Emmons, L. K., DiGangi, J., Choi, Y., & Diskin, G. (2018, December/Fall). Tracking Fossil Fuel Emissions in East Asia by Combining Model Simulations, Satellite Observations, and Field Measurements of the CO-to-CO2 Ratio. 2018 American Geophysical Union Fall Meeting. Washington D.C.: AGU.
• Arellano, A. F. (2017, November). On the Nexus Between Carbon Cycle and Air Quality: Exploring Multiple Constraints on Anthropogenic Combustion and Fires. ECMWF Seminar Series. Reading, UK: ECMWF.
• Arellano, A. F. (2017, November). On the Nexus Between Carbon Cycle and Air Quality: Exploring Multiple Constraints on Anthropogenic Combustion and Fires. LATMOS Seminar Series. UPMC, Paris France: LATMOS.
• Arellano, A. F. (2017, September). Confronting Recent Chemical Reanalyses with Satellite Data on Combustion Characteristics Over Megacities,. 18th GEIA Conference. Hamburg, Germany: IGAC/GEIA.
• Arellano, A. F., & Tang, W. (2017, December). Sensitivity of CAM-Chem/DART MOPITT CO Assimilation Performance to the Choice of Ensemble System Configuration: A Case Study for Fires in the Amazon. 2017 AGU Fall Meeting. New Orleans, LA: AGU.
• Arellano, A. F., Tang, W., Silva, S., & Raman, A. (2017, December). Exploring Multiple Constraints of Anthropogenic Pollution. 2017 AGU Fall Meeting. New Orleans, LA: AGU.
• Arellano, A. F., Tang, W., Silva, S., & Raman, A. (2018, January). Exploring Multiple Constraints of Anthropogenic Pollution in Combustion Regions from Current Satellite Retrievals of Atmospheric Composition. 20th Conference on Atmospheric Chemistry, AMS 98th Annual Meeting. Austin, Texas: AMS.
• Choi, Y., DiGangi, J., Diskin, G., Novak, J., Halliday, H., Pushed, S., Arellano, A. F., Tang, W., Knote, C., Woo, J., Lee, Y., Bu, C., Blake, D., Simpson, I., Blake, N., & Xu, X. (2017, December). Atmospheric Observations of Carbon Dioxide and Quantification of Fossil Fuel Carbon Dioxide and Emission Inventories using Radiocarbon in the Korean Peninsula during the KORUS-AQ Field Campaign. 2017 AGU Fall Meeting. New Orleans, LA: AGU.
• Gaubert, B., Emmons, L., Miyazaki, K., Buchholz, R., Tang, W., Arellano, A. F., Tilmes, S., Barre, J., Worden, H., Raeder, K., Anderson, J., & Edwards, D. (2017, December). Diagnostics of sources of tropospheric ozone using data assimilation during the KORUS-AQ campaign. 2017 AGU Fall Meeting. New Orleans, LA: AGU.
• Smith, W. K., Arellano, A. F., Barnes, M. L., Hudson, A. R., Montane, F., Fox, A. M., & Moore, D. J. (2017, Aug). Combining models and data to understand vegetation function across timescales. 102nd Annual Meeting of the Ecological Society of America. Portland, OR: ESA.
• Arellano, A. F. (2016, April). Data Assimilation for Monsoon Hydrometeorological Studies. UC-MEXUS Meeting.
• Arellano, A. F. (2016, August). Air Quality Data Assimilation: Methods Part 1. NCAR Advance Study Program Summer Colloquium on Advances in Air Quality Analysis and Prediction: The Interaction of Science and Policy.
• Arellano, A. F. (2016, August). Emission Estimation- State Augmentation. NCAR Advance Study Program Summer Colloquium on Advances in Air Quality Analysis and Prediction: The Interaction of Science and Policy.
• Arellano, A. F., Raman, A., Brost, J., & Sorooshian, A. (2016, December). Modeling and observations of dust aerosols during the North American Monsoon. AGU 2016 Fall Meeting.
• Edwards, D., Barre, J., Worden, H., & Arellano, A. F. (2016, September). Quantifying wildfire emissions and associated aerosols species using assimilation of satellite carbon monoxide retrievals. 2016 International Global Atmospheric Chemistry (IGAC) Project Science Conference.
• Raman, A., Arellano, A. F., & Kuma, R. (2016, December). Estimating black carbon concentrations from combustion tracers: synergistic perspective using in-situ measurements, multi-satellite retrievals, and chemical transport model. AGU 2016 Fall Meeting.
• Arellano, A. F. (2015, December). Inverse Modeling of BC and CO Sources in WRF-Chem. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Arellano, A. F. (2015, June). Data Assimilation in the NAM Region: Challenges and Opportunities. 3rd Meeting of Regional Meteorology Climatology and Northwest Mexico. Universidad Nacional Autónoma de México, Mexico City: UNAM.
• Arellano, A. F. (2015, November). Top-down Estimates of Combustion Characteristics Over Megacities and Major Fire Regions. 17th GEIA: Global Emissions Initiative Conference (Influence of Urbanization on Emissions Worldwide). Tsinghua University, Beijing China: GEIA.
• Arellano, A. F. (2015, October). Towards Seamless Prediction of Chemical Weather. UA GIDP Statistics Collquium. Tucson, AZ: GIDP Statistics.
• Knote, C., Barre, J., Eckl, M., Hornbrook, R., Wiedinmyer, C., Emmons, L., Orlando, J., Tyndall, G., & Arellano, A. F. (2015, December). Inferring the unobserved chemical state of the atmosphere: idealized data assimilation experiments. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Tang, W., Arellano, A. F., Raman, A., & Deeter, M. (2015, April). A Comparative Analysis on the Temporal and Spatial Distribution of Fire Characteristics in the Amazon and Equatorial Southern Africa Using Observations from Space. 2015 EGU Meeting. Vienna, Austria: EGU.
• Arellano, A. F., & Silva, S. (2014, April). Combustion signatures as seen from space: Implications for tracking anthropogenic CO2. OCO-2 Applications Workshop. Maryland, MD: NASA.
• Barre, J., Edwards, D., Arellano, A. F., Gaubert, B., Worden, H., Anderson, J., & Mizzi, A. (2014, December). Assessment of IASI CO and MOPITT CO Data Assimilation in CAM-Chem. 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Barre, J., Gaubert, B., Arellano, A. F., Worden, H., Edwards, D., Tilmes, S., Collins, N., Raeder, K., & Mizzi, A. (2014, August). Multivariate chemical data assimilation and chemistrydynamics interaction. World Weather Open Science 2014. Montreal, Canada: WMO.
• Edwards, D., Barre, J., Worden, H., Arellano, A. F., Gaubert, B., Anderson, J., & Mizzi, A. (2014, December). The atmospheric composition geostationary satellite constellation for air quality and climate science: Evaluating performance with Observation System Simulation Experiments. 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Gaubert, B., Arellano, A. F., Barre, J., Worden, H., Emmons, L., Wiedinmyer, C., Anderson, J., Mizzi, A., & Edwards, D. (2014, December). Optimizing global CO concentrations and emissions based on DART/CAM-CHEM. 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Gaubert, B., Barre, J., Worden, H., Edwards, D., Emmons, L., Tilmes, S., Mizzi, A., Arellano, A. F., Anderson, J., & Collins, N. (2014, August). Global CO data assimilation for emissions and trends analysis. World Weather Open Science 2014. Montreal, Canada: WMO.
• Mizzi, A., Arellano, A. F., Edwards, D., Anderson, J., & Barre, J. (2014, August). Ensemble Kalman Filter Assimilation of MOPITT CO Retrieval Profiles with WRF/Chem-DART. World Weather Open Science 2014. Montreal, Canada: WMO.
• Raman, A., Arellano, A. F., & Kumar, R. (2014, June). Quantifying regional emissions using WRF-Chem tagged tracers: Implications for cross-state pollution transport and extreme air quality events. 15th Annual WRF Users' Workshop. Boulder, CO: NCAR.
• Raman, A., Arellano, A. F., & Kumar, R. (2014, September). Using chemical ratios to disentangle sources of particulate matter pollution: Implications for population exposure and mortality. International Global Atmospheric Chemistry (IGAC) Science Conference on Atmospheric Chemistry. Natal, Brazil: IGAC.
• Silva, S., Arellano, A. F., & Worden, H. (2014, May). Exploring the utility of satellite-based CO2/CO and CO2/NO2 sensitivities over urban regions and point sources as constraints on anthorpogenic combustion. International Workshop on Greenhouse Gas Measurements from Space (IWGGMS-9). Noordwijk, The Netherlands: European Space Agency.
• Arellano, A. F. (2013, March). Towards Seamless Prediction of Chemical Weather. Alaska Weather Symposium. Fairbanks, AK: University of Alaska.
• Arellano, A. F. (2013, March). Towards Seamless Prediction of Chemical Weather. UA Applied Mathematics SIAM Student Chapter Seminar. Tucson, AZ: University of Arizona.
• Arellano, A. F. (2013, September). Towards Seamless Prediction of Atmospheric Composition Using Ensemble-based Data Assimilation. Biennial Air Quality Research Center Conference on Traversing New Terrain in Meteorological Modeling, Air Quality, and Dispersion. Davis, CA: AMS.
• Arellano, A. F., Raman, A., & Chatterjee, A. (2015, January). Comparison of algorithms for assimilating satellite partial column retrievals from MOPITT and IASI with WRF-Chem/DART. AMS 95th Annual Meeting. Phoenix, Arizona: AMS.
• Mizzi, A., Arellano, A. F., Edwards, D., Anderson, J., & Barre, J. (2014, February). An efficient algorithm for assimilation of satellite retrieval profiles of chemical trace gases in the troposphere with the DART ensemble Kalman filter in WRFCHEM. AMS 94th Annual Meeting. Atlanta, GA: AMS.
• Moker, J., Serra, Y., Castro, C., & Arellano, A. F. (2015, January). Impact of Precipitable Water on Forecasting the 2013 North American Monsoon. AMS 95th Annual Meeting. Phoenix, Arizona: AMS.
• Raman, A., & Arellano, A. F. (2013, June). A WRF/CHEM sensitivity study towards high resolution air qualityforecasting for southwestern United States. 14th Annual WRF Users' Workshop. Boulder, CO: NCAR.
• Rosolem, R., Hoar, T., Arellano, A. F., Anderson, J., Shuttleworth, W., Zeng, X., & Franz, T. (2014, December). Translating above-ground cosmic-ray neutron intensity to high-frequency soil moisture profile at sub-kilometer scale. 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Silva, S., & Arellano, A. F. (2013, May). Patterns of CO2 Sensitivity to CO from Space and their Implications for Carbon Monitoring. International Workshop on Greenhouse Gas Measurements from Space (IWGGMS-9). Yokohama, Japan: JAXA.

Poster Presentations

• Ajayi, T., Mirrezaei, S., Arellano, A. F., & Sorooshian, A. (2024, December).

  An Examination of the Weekly Periodicity of Surface Ozone Concentrations in Tucson, Arizona, Including Relationships with Monsoon Characteristics

  . AGU Fall Meeting. Washington DC.
• Gaubert, B., Mirrezaei, S., Arellano, A. F., Ortega, I., McKain, K., Bruhwiler, L., Oh, Y., Saez-Lopez, A., Fernandez, R., Saunois, M., Fang, C., Xu, Y., Emmons, L., & Worden, H. (2024, December).

  Investigating the impact of chemical feedback in global transient simulations driven by methane emissions

  . AGU Fall Meeting. Washington DC.
• Guo, Y., Arellano, A. F., Mirrezaei, S., & Sorooshian, A. (2024, December). Source contribution to ozone pollution during June 2021 wildfire season in Arizona: Insights from WRF-Chem tagged O₃ and CO. AGU Fall Meeting. Washington DC.
• McKinnon, J., Arellano, A. F., Roychoudhury, C., & Gaubert, B. (2024, September).

  Analysis of the seasonal variability of atmospheric composition using SSA, EOF, and Fourier Analysis

  . IGAC. Kuala Lumpur.
• McKinnon, J., Roychoudhury, C., Arellano, A. F., & Gaubert, B. (2024, December). Use of power spectral analysis to show correlations between the dominant time scale and chemical lifetime of greenhouse gases and trace gases. AGU Fall Meeting. Washington DC.
• Mirrezaei, M. A., Gaubert, B., & Arellano, A. F. (2024, January). Simulating CH₄ Lifetime and Abundance using the Global Carbon Project CH₄ flux estimates. 104th AMS Annual Meeting. Baltimore, MD: AMS.
• Mirrezaei, S., Gaubert, B., Ortega, I., McKain, K., Bruhwiler, L., Oh, Y., Saez-Lopez, A., Fernandez, R., Saunois, M., Emmons, L., Worden, H., Fang, C., Xu, Y., & Arellano, A. F. (2024, December). Constraining Tropospheric Hydroxyl Radical (OH) Using Emission-Driven CAM-Chem Simulations with Short-Lived Halogen Representation. AGU Fall Meeting. Washington DC.
• Mohammad, A., Mirrezaeri, S., Roychoudhury, C., & Arellano, A. F. (2024, December). Analysis of Air Quality Trends in Kuwait from 2015 to 2022. AGU Fall Meeting. Washington, DC: AGU.
• Pan, K., Arellano, A. F., Demoz, B., Santanello, J., & Blumberg, W. (2024, December). Assimilation of Planetary Boundary Layer Height Measurements with Multi-Physics using Ensemble Kalman Filter During the PECAN Field Campaign. AGU Fall Meeting. Washington DC.
• Pandey, S., Boots, M., Pan, K., Demoz, B., Arellano, A. F., & Caroll, B. (2024, December).

  Understanding PBL Dynamics and Thermodynamics in LLJ events over PECAN: Modeled and Observation

  . AGU Fall Meeting.
• Parakkat, L., Betito, G., Hilario, M., Arellano, A. F., & Sorooshian, A. (2024, December).

  Factors Coinciding with Extreme Events of Ozone Over Rural and Urban Sites in Arizona

  . AGU Fall Meeting. Washington DC.
• Robertson, M., Roychoudhury, C., Mirrezaei, M. A., McKinnon, J. M., Sorooshian, A., & Arellano, A. F. (2024). Assessing Uncertainties in Satellite Data on Arizona's Atmospheric Composition: Insights from Ground-Based Observations from AERONET and PANDORA. AGU24.
• Roychoudhury, C., & Arellano, A. F. (2024, December). Diagnosing Interactions at the Earth System Interface: Case Studies from Snowmelt and Chemical Feedbacks. AGU Fall Meeting. Washington DC.
• Roychoudhury, C., Arellano, A. F., Cheng, W., Mizukami, N., He, C., & Kumar, R. (2024, September).

  Is traditional Bayesian inversion sufficient to constrain black carbon abundance in High Mountain Asia?

  . IGAC.
• Roychoudhury, C., McKinnon, J., Mirrezaei, S., Guo, Y., & Arellano, A. F. (2024, December). Source attribution of wildfires in Arizona: An exploration of the June 2021 wildfire season. AGU Fall Meeting. Washington DC.
• Guo, Y., Arellano, A. F., Roychoudhury, C., Sorooshian, A., Kumar, R., & Pfister, G. (2023, January). Harnessing our Air Quality Modeling & Observational Capabilities to Establish Key Factors Influencing Ozone Levels in Arizona. AMS Annual Meeting. Denver, CO: AMS.
• Guo, Y., Arellano, A. F., Roychoudhury, C., Sorooshian, A., Kumar, R., & Pfister, G. (2023, September). Harnessing our Air Quality Modeling & Observational Capabilities to Establish Key Factors Influencing Ozone Levels in Arizona. Meteorology and Climate – Modeling for Air Quality Conference (MAC-MAQ). UC Davis.
• McKinnon, J., Roychoudhury, C., & Arellano, A. F. (2023, June). se of Covariance Discrimination Analysis to Determine Structural Bias in Modeled Carbon Monoxide. Global Emissions Initiative (GEIA) 20th Conference. Brussels, Belgium: International Global Atmospheric Chemistry.
• Mirrezaei, M. A., Gaubert, B., Fernandez, R. P., Kinnison, D. E., Ortega, I., & Arellano, A. F. (2023, December). Exploring the Variability of CH4 Abundance due to Uncertainties in CH4 Emissions and Chemistry. AGU Fall Meeting. San Francisco: AGU.
• Mirrezaei, M. A., Guo, Y., Roychoudhury, C., Sorooshian, A., Arellano, A. F., Tang, W., & Emmons, L. (2023, September). Investigating surface ozone sensitivity to HCHO/NO2 ratios over Arizona using the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) model. Meteorology and Climate – Modeling for Air Quality Conference (MAC-MAQ). UC Davis.
• Mirrezaei, M. A., Tang, W., Emmons, L., Guo, Y., Gaubert, B., & Arellano, A. F. (2023, December). The impact of horizontal resolution, chemistry, and emissions on surface ozone concentration using Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0). AGU Fall Meeting. San Francisco: AGU.
• Pan, K., & Arellano, A. F. (2023, January). Uncertainties of Modeled and Observed PBL Heights During the PECAN Field Campaign. AMS Annual Meeting. Denver, CO: AMS.
• Roychoudhury, C., Cheng, W., He, C., Kumar, R., & Arellano, A. F. (2023, December). MATCHA, Model for Atmospheric Transport and Chemistry in Asia: A novel regional climate-chemical reanalysis. AGU Fall Meeting. San Francisco: AGU.
• Roychoudhury, C., Cheng, W., He, C., Kumar, R., McKinnon, J., & Arellano, A. F. (2023, December). How uncertain are BC emissions in High Mountain Asia? An inverse modeling approach. AGU Fall Meeting. San Francisco: AGU.
• McKinnon, J., Roychoudhury, C., Arellano, A. F., & Gaubert, B. (2022, December). Spatiotemporal Pattern Analysis of Trace Gases and Aerosol Abundance Using Varimax Rotation. AGU Fall Meeting. Chicago, IL: AGU.
• Pan, K., & Arellano, A. F. (2022, December). Exploring the Range of Uncertainties of Modeled and Observed PBL Heights During the PECAN Field Campaign. AGU Fall Meeting. Chicago, IL: AGU.
• Roychoudhury, C., He, C., Kumar, R., McKinnon, J., & Arellano, A. F. (2022, December). Tracing the sources of black carbon deposition over the glaciers in High Mountain Asia: A tagged- tracer approach using WRF-Chem . AGU Fall Meeting. Chicago, IL: AGU.
• Roychoudhury, C., He, C., Kumar, R., McKinnon, J., & Arellano, A. F. (2022, September). Source attribution of aerosol impacts to snow cover over High Mountain Asia. International Global Atmospheric Chemistry (IGAC) Project Science Conference. Manchester, UK: IGAC.
• Knickrehm, L., Yuan, S., Roychoudhury, C., Arellano, A. F., & Furlong, M. (2022, January). An Ensemble Approach in Modeling the Atmospheric Dispersion of Pesticide Spray Drift in Yuma County. American Meteorological Society (AMS) 102nd Annual Meeting: 22nd Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA. Virtual: AMS.
• Roychoudhury, C., He, C., Kuman, R., & Arellano, A. F. (2021, September). Investigating the relationship of meteorology and atmospheric composition to snow cover: A comparative study over High-Mountain Asia and Ande. 2021 International Global Atmospheric Chemistry (IGAC) Project Science Conference. Virtual: IGAC.
• Mottungan, K., Arellano, A. F., Gaubert, B., DiGangi, J., Choi, Y., & Diskin, G. (2021, January). Characterizing the urban emission signatures of CO, CO2 and CH4 over Southeast Asia during CAMP2EX. American Meteorological Society (AMS) 101st Annual Meeting. Virtual Conference: AMS.
• Arellano, A. F., Tang, W., Gaubert, B., Choi, Y., DiGangi, J., & Diskin, G. (2019, December). Assessing the Utility of CO2:CO Correlations in Improving Top-down Estimates of Fossil-fuel CO2 Emissions. 2019 AGU Fall Meeting. San Francisco, CA: AGU.
• Arellano, A. F., Gaubert, B., Miyazaki, K., Inness, A., Jiang, Z., Yin, Y., & Flemming, J. (2018, December/Fall). Towards a Chemical Inverse Modeling System Experiment: First Results on CO Inter-comparison,. 2018 American Geophysical Union Fall Meeting. Washington, D.C.: AGU.
• Brocchi, V., Arellano, A. F., Tang, W., & Gaubert, B. (2020, January). Impact of African Urban Agglomerations to Global Air Quality,. 22nd Conference on Atmospheric Chemistry/100th AMS Annual Meeting. Boston, MA: AMS.
• Castro, C. L., Moker, Jr., J. M., Serra, Y., Arellano, A. F., & Adams, D. K. (2018, January). Convective-permitting hindcast simulations during the North American monsoon GPS Transect Experiment 2013: Establishing baseline model performance.. 98th Annual American Meteorological Society Meeting.
• Arellano, A. F., Tang, W., Silva, S., Gaubert, B., & Miyazaki, K. (2017, October). Multi-Species Analysis of Anthropogenic Pollution Using IASI Data: Emerging Patterns over Chinese Cities. EUMETSAT Meteorological Conference. Rome, Italy: EUMETSAT.
• Tang, W., & Arellano, A. F. (2017, January). Investigating Combustion and Emission Trends in Megacities through Synthesis of Combustion Signatures Using Multiple Datasets. AMS 2017 Annual Meeting.
• Tang, W., Arellano, A. F., Choi, Y., DiGangi, J., Woo, J., Diskin, G., Agusti-Panareda, A., Parrington, M., Massart, S., Lee, M., Kanaya, Y., Jang, J., Lee, Y., Hong, J., Flynn, J., Thompson, A., & Kim, D. (2017, December). Joint Evaluation of Copernicus Atmosphere Monitoring Service (CAMS) High-resolution Global Near-Real Time CO and CO2 Forecasts during KORUS-AQ Field Campaign. 2017 AGU Fall Meeting. New Orleans, LA: AGU.
• Tang, W., Arellano, A. F., Emmons, L., & Gaubert, B. (2018, January). Ensemble Simulation of Anthropogenic and Biomass Burning CO2 and CO in CAM-chem. 20th Conference on Atmospheric Chemistry, AMS 98th Annual Meeting. Austin, Texas: AMS.
• Deeter, M., Emmons, L., Arellano, A. F., Martinez-Alonso, S., Wiedinmyer, C., Val Martin, M., Gatti, L., Miller, J., Gloor, M., Domingues, L., & Carvalho-Correia, C. (2016, December). Towards Improved MOPITT-based Biomass Burning Emission Inventories for the Amazon Basin. AGU 2016 Fall Meeting.
• Gaubert, B., Barre, J., Arellano, A. F., Worden, H., Emmons, L., Tilmes, S., Martinez-Alonso, S., Anderson, J., & Edwards, D. (2016, December). Overview of the NCAR-MOPITT reanalysis, investigation of chemical error correlations. AGU 2016 Fall Meeting.
• Gaubert, B., Worden, H., Arellano, A. F., Barre, J., Emmons, L., Tilmes, S., Bucholz, R., Anderson, J., Martinez-Alonso, S., & Vitt, F. (2016, September). A Reanalysis of MOPITT-CO observations. 2016 International Global Atmospheric Chemistry (IGAC) Project Science Conference.
• Kumar, R., Raman, A., Delle-Monache, L., Alessandrini, S., Chang, W., Gaubert, B., & Arellano, A. F. (2016, December). A novel method to improve MODIS AOD retrievals in cloudy pixels using an analog ensemble approach. AGU 2016 Fall Meeting.
• Montane, F., Fox, A. M., Arellano, A. F., Alexander, M. R., & Moore, D. J. (2016, Fall). A Model-Data Intercomparison of Carbon Fluxes, Pools, and LAI in the Community Land Model (CLM) and Alternative Carbon Allocation Schemes. American Geophysical Union.
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  Francesc Montane, Andrew M Fox, Avelino F Arellano, M Ross Alexander, David J Moore B21B-0444: A Model-Data Intercomparison of Carbon Fluxes, Pools, and LAI in the Community Land Model (CLM) and Alternative Carbon Allocation Schemes
• Tang, W., & Arellano, A. F. (2016, September). Investigating Combustion and Emission Trends in Megacities trhough Synthesis of Combustion Signatures Using Mulitple Datasets,. 2016 International Global Atmospheric Chemistry (IGAC) Project Science Conference.
• Arellano, A. F., Tang, W., & Deeter, M. (2015, December). Joint Analysis of Bulk Wildfire Characteristics from Multiple Satellite Retrievals. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Barre, J., Edwards, D., Gaubert, B., Woren, H., Arellano, A. F., & Anderson, J. (2015, December). Carbon Monoxide Data Assimilation for Atmospheric Composition and Climate Science: Evaluating Performance with Current and Future Observations. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Gaubert, B., Arellano, A. F., Barre, J., Worden, H., Emmons, L., Tilmes, S., Buchholz, R., Wiedinmyer, C., Vitt, F., & Anderson, J. (2015, December). Chemical Response of CESM/CAM-Chem to MOPITT CO Ensemble-based Chemical Data Assimilation. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Mizzi, A., Arellano, A. F., Edwards, D., & Anderson, J. (2015, December). Comparison of the Assimilation of Compact Phase Space Retrievals (CPSRs) with Conventional Retrieval Assimilation Methods for MOPITT CO in WRF-Chem/DART. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Montane, F., Fox, A., Arellano, A. F., Scaven, V., Alexander, M., & Moore, D. (2015, December). Comparing Different Model Structures for Carbon Allocation in the Community Land Model (CLM). 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Raman, A., Arellano, A. F., & Kumar, R. (2015, December). Using Combustion Tracers to Estimate Surface Black Carbon Distributions in WRF-Chem. 2015 AGU Fall Meeting. San Francisco, CA: AGU.
• Liu, Y., Matthes, J., Moore, D., Dietze, M., Arellano, A. F., Dawson, A., Fox, A., Goring, S., McLachlan, J., Montane, F., Moreno, G., Poulter, B., Quaife, T., Ricciuto, D., Schaefer, K., Steinkamp, S., Williams, J., & Team, P. (2014, December). Assessing the long-term performance of terrestrial ecosystem models in northeastern United States: linking model structure and output. 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Montane, F., Fox, A., Hoar, T., Arellano, A. F., Liu, Y., Moreno, G., Quife, T., Richardson, A., Trouet, V., Chen, M., Hollinger, D., & Moore, D. (2014, December). Assimilating Multiple Data Types in the Community Land Model (CLM) for Deciduous Forests in North America. 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Arellano, A. F. (2014, December). Constraints on Local-­to-­Regional Anthropogenic CO2 from Satellite Retrievals of Combustion-­related Trace Gases: Initial Assessment Using Observing System Simulation Experiments (OSSEs). 2014 AGU Fall Meeting. San Francisco, CA: AGU.
• Barre, J., Worden, H., Edwards, D., Arellano, A. F., & Lahoz, W. (2013, December). Monitoring lowermost tropospheric carbon monoxide from a geostationary constellation: observation simulations. 2013 AGU Fall Meeting. San Francisco, CA: AGU.
• Mizzi, A., Arellano, A. F., Edwards, D., & Anderson, J. (2015, January). Comparison of efficient algorithms for assimilating satellite partial column retrievals with WRF-Chem/DART. AMS 95th Annual Meeting. Phoenix, Arizona: AMS.
• Silva, S., Arellano, A. F., Yang, M., & Crosbie, E. (2013, December). Exploring the utility of satellite-based CO2-CO-NO2 sensitivities over urban regions and point sources as constraints on anthropogenic combustion. 2013 AGU Fall Meeting. San Francisco, CA: AGU.