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3. Tubelight Adrenals in Diabetic Ketoacidosis

Author

Yadav, Prakrati, Kumar, Akhilesh, Mathur, Rohit, Garg, Pawan, Gopalakrishnan, Maya, and Kumar Garg, Mahendra

Subjects
Diabetic ketoacidosis, acute pancreatitis, hypertriglyceridemia, CT hypoperfusion, tubelight adrenal
Abstract

Case Presentation: We report a patient with the triad of diabetic ketoacidosis, hypertriglyceridemia, and acute pancreatitis associated with computed tomography hypoperfusion complex and adrenal hyperdensity on abdominal imaging – an association not previously reported in diabetic ketoacidosis.Discussion: Presence of Computed tomography hypoperfusion complex with hyperdense ‘Tubelight adrenals’ in a patient with diabetic ketoacidosis is associated with poor prognosis and thus serves to guide clinicians towards early and aggressive management.

Published
2020

6. Security-Focused Mathematical Model for Voice Over Wireless Sensor Network

Author

Mathur, Rohit, Dubey, Tarun Kumar, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tripathi, Anshuman, editor, Soni, Amit, editor, Shrivastava, Ashish, editor, Swarnkar, Anil, editor, and Sahariya, Jagrati, editor

Published
2022
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11. Southeast Atmosphere Studies: learning from model-observation syntheses.

Author

Mao, Jingqiu, Carlton, Annmarie, Cohen, Ronald C, Brune, William H, Brown, Steven S, Wolfe, Glenn M, Jimenez, Jose L, Pye, Havala OT, Ng, Nga Lee, Xu, Lu, McNeill, V Faye, Tsigaridis, Kostas, McDonald, Brian C, Warneke, Carsten, Guenther, Alex, Alvarado, Matthew J, de Gouw, Joost, Mickley, Loretta J, Leibensperger, Eric M, Mathur, Rohit, Nolte, Christopher G, Portmann, Robert W, Unger, Nadine, Tosca, Mika, and Horowitz, Larry W

Subjects
Climate Action, Astronomical and Space Sciences, Atmospheric Sciences, Meteorology & Atmospheric Sciences
Abstract

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Published
2018

23. Anthropogenic enhancements to production of highly oxygenated molecules from autoxidation

Author

Pye, Havala O. T., D’Ambro, Emma L., Lee, Ben H., Schobesberger, Siegfried, Takeuchi, Masayuki, Zhao, Yue, Lopez-Hilfiker, Felipe, Liu, Jiumeng, Shilling, John E., Xing, Jia, Mathur, Rohit, Middlebrook, Ann M., Liao, Jin, Welti, André, Graus, Martin, Warneke, Carsten, de Gouw, Joost A., Holloway, John S., Ryerson, Thomas B., Pollack, Ilana B., and Thornton, Joel A.

Published
2019

24. Localization Independent Aspects of Topology Control in Wireless Sensor Networks

Author

Dubey, Tarun Kumar, Mathur, Rohit, Chouhan, Dungar Nath, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Janyani, Vijay, editor, Tiwari, Manish, editor, Singh, Ghanshyam, editor, and Minzioni, Paolo, editor

Published
2018
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36. Source specific bias correction of US background ozone modeled in CMAQ.

Author

Skipper, T. Nash, Hogrefe, Christian, Henderson, Barron H., Mathur, Rohit, Foley, Kristen M., and Russell, Armistead G.

Subjects
OZONE, CORRECTION factors, MULTISENSOR data fusion, OZONE layer, TROPOSPHERIC ozone, COUNTERFACTUALS (Logic)
Abstract

United States (US) background ozone (O3) is the counterfactual O3 that would exist with zero US anthropogenic emissions. Estimates of US background O3 typically come from chemical transport models (CTMs), but different models vary in their estimates of both background and total O3. Here, a measurement-model data fusion approach is used to estimate CTM biases in US anthropogenic O3 and multiple US background O3 sources, including natural emissions, long-range international emissions, short-range international emissions from Canada and Mexico, and stratospheric O3. Spatially and temporally varying bias correction factors adjust each simulated O3 component so that the sum of the adjusted components evaluates better against observations compared to unadjusted estimates. The estimated correction factors suggest a seasonally consistent positive bias in US anthropogenic O3 in the eastern US, with the bias becoming higher with coarser model resolution and with higher simulated total O3 though the bias does not increase much with higher observed O3. Correlation among different US background O3 components can increase the uncertainty in the estimation of the source-specific adjustment factors. Despite this, results indicate that there may be a negative bias in modeled estimates of the impact of stratospheric O3 at the surface. This type of data fusion approach can be extended to include data from multiple models to leverage the strengths of different data sources while reducing uncertainty in the US background ozone estimates. [ABSTRACT FROM AUTHOR]

Published
2024
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44. An analysis of CMAQ gas-phase dry deposition over North America through grid-scale and land-use-specific diagnostics in the context of AQMEII4

Author

Hogrefe, Christian, Bash, Jesse O., Pleim, Jonathan E., Schwede, Donna B., Gilliam, Robert C., Foley, Kristen M., Appel, K. Wyat, and Mathur, Rohit

Abstract

The fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4) is conducting a diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality models over North America and Europe. In this study, we analyze annual AQMEII4 simulations performed with the Community Multiscale Air Quality Model (CMAQ) version 5.3.1 over North America. These simulations were configured with both the M3Dry and Surface Tiled Aerosol and Gas Exchange (STAGE) dry deposition schemes available in CMAQ. A comparison of observed and modeled concentrations and wet deposition fluxes shows that the AQMEII4 CMAQ simulations perform similarly to other contemporary regional-scale modeling studies. During summer, M3Dry has higher ozone (O3) deposition velocities (Vd) and lower mixing ratios than STAGE for much of the eastern US, while the reverse is the case over eastern Canada and along the US West Coast. In contrast, during winter STAGE has higher O3 Vd and lower mixing ratios than M3Dry over most of the southern half of the modeling domain, while the reverse is the case for much of the northern US and southern Canada. Analysis of the diagnostic variables defined for the AQMEII4 project, i.e., grid-scale and land-use-specific effective conductances and deposition fluxes for the major dry deposition pathways, reveals generally higher summertime stomatal and wintertime cuticular grid-scale effective conductances for M3Dry and generally higher soil grid-scale effective conductances (for both vegetated and bare soil) for STAGE in both summer and winter. On a domain-wide basis, the stomatal grid-scale effective conductances account for about half of the total O3 Vd during daytime hours in summer for both schemes. Employing land-use-specific diagnostics, results show that daytime Vd varies by a factor of 2 between land use (LU) categories. Furthermore, M3Dry vs. STAGE differences are most pronounced for the stomatal and vegetated soil pathway for the forest LU categories, with M3Dry estimating larger effective conductances for the stomatal pathway and STAGE estimating larger effective conductances for the vegetated soil pathway for these LU categories. Annual domain total O3 deposition fluxes differ only slightly between M3Dry (74.4 Tg yr−1) and STAGE (76.2 Tg yr−1), but pathway-specific fluxes to individual LU types can vary more substantially on both annual and seasonal scales, which would affect estimates of O3 damage to sensitive vegetation. A comparison of two simulations differing only in their LU classification scheme shows that the differences in LU cause seasonal mean O3 mixing ratio differences on the order of 1 ppb across large portions of the domain, with the differences generally being largest during summer and in areas characterized by the largest differences in the fractional coverages of the forest, planted and cultivated, and grassland LU categories. These differences are generally smaller than the M3Dry vs. STAGE differences outside the summer season but have a similar magnitude during summer. Results indicate that the deposition impacts of LU differences are caused by differences in the fractional coverages and spatial distributions of different LU categories and the characterization of these categories through variables like surface roughness and vegetation fraction in lookup tables used in the land surface model and deposition schemes. Overall, the analyses and results presented in this study illustrate how the diagnostic grid-scale and LU-specific dry deposition variables adopted for AQMEII4 can provide insights into similarities and differences between the CMAQ M3Dry and STAGE dry deposition schemes that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.

Published
2023

50. 2002–2017 anthropogenic emissions data for air quality modeling over the United States

Author

Foley, Kristen M., primary, Pouliot, George A., additional, Eyth, Alison, additional, Aldridge, Michael F., additional, Allen, Christine, additional, Appel, K. Wyat, additional, Bash, Jesse O., additional, Beardsley, Megan, additional, Beidler, James, additional, Choi, David, additional, Farkas, Caroline, additional, Gilliam, Robert C., additional, Godfrey, Janice, additional, Henderson, Barron H., additional, Hogrefe, Christian, additional, Koplitz, Shannon N., additional, Mason, Rich, additional, Mathur, Rohit, additional, Misenis, Chris, additional, Possiel, Norm, additional, Pye, Havala O.T., additional, Reynolds, Lara, additional, Roark, Matthew, additional, Roberts, Sarah, additional, Schwede, Donna B., additional, Seltzer, Karl M., additional, Sonntag, Darrell, additional, Talgo, Kevin, additional, Toro, Claudia, additional, Vukovich, Jeff, additional, Xing, Jia, additional, and Adams, Elizabeth, additional

Published
2023
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