Vibrational dependence, temperature dependence, and prediction of line shape parameters for the H2O-N2 collision system

Bastien Vispoel, João H. Cavalcanti, Evan T. Paige, Robert R. Gamache

Research output: Contribution to journalArticlepeer-review

Abstract

In a recent work [JQSRT 228,79(2019)], Vispoel et al. optimized the intermolecular potential used in the Modified Complex Robert-Bonamy (MCRB) formalism for the H2O-N2 collision system. Calculations were made for a number of transitions in the rotation and ν2 bands. The needs of the spectroscopic and astrophysics communities include data for water vapor transitions that have multiple vibrational quanta exchanged. In this work, MCRB calculations were made for 0–4 vibrational quanta exchanged in the ν1, ν2, and ν3 bands for 13 temperatures from 200–3000 K; 7272 transitions for each band. From these data, the vibrational and temperature dependence of the half-width and line shift were determined. The temperature dependence was determined using the Gamache-Vispoel model [JQSRT 217, 440(2018)]. The data allowed the development of a routine that can predict the half-width, line shift, and their temperature dependence for transitions not yet studied. The prediction algorithm is based on theory [JQSRT, 83, 119(2004)] and yields line shape parameters with much smaller uncertainty than obtained by fitting with ad hoc polynomials or J” averaged values. A line file based on the 2020 update to the HITRAN2016 water vapor line file was created with N2 as the broadening species. These data are useful for combustion studies and as a first step to determining air-broadening for the HITRAN and GEISA databases.

Original languageEnglish
Article number107030
JournalJournal of Quantitative Spectroscopy and Radiative Transfer
Volume253
DOIs
Publication statusPublished - Sep 2020

Fingerprint Dive into the research topics of 'Vibrational dependence, temperature dependence, and prediction of line shape parameters for the H<sub>2</sub>O-N<sub>2</sub> collision system'. Together they form a unique fingerprint.

Cite this