Inferring Interstellar Medium Density, Temperature, and Metallicity from Turbulent H II Regions

TL;DR

This work demonstrates that supersonic turbulence in H II regions systematically alters nebular emission-line diagnostics used to infer $T_e$, $n_e$, and metallicity. By comparing homogeneous and turbulent 3D H II region models around a central O star with RAMSES-RTZ, the authors quantify shifts in key line ratios such as $[\mathrm{O}\,\textsc{iii}]/\mathrm{H}\beta$, $[\mathrm{N}\,\textsc{ii}]/\mathrm{H}\alpha$, and $[\mathrm{O}\,\textsc{iii}]/[\mathrm{O}\,\textsc{ii}]$, and assess biases in direct $T_e$ metallicities and density diagnostics. They find turbulence drives metallicity underestimates up to ~0.1 dex and causes density diagnostics to preferentially sample luminosity-weighted, rather than mass- or volume-weighted, densities due to density inhomogeneities with high-density tails dominating emission. The results imply that large grids of turbulent H II region models are needed to correctly interpret spectra across redshift, particularly for JWST-era observations, and highlight the importance of accounting for ISM turbulence in nebular diagnostics and galaxy-metallicity studies.

Abstract

Reliable nebular emission line diagnostics are essential for accurately inferring the physical properties (e.g. electron temperature, density, pressure, and metallicity) of H II regions from spectra. When interpreting spectra, it is typical to adopt a single zone model, e.g. at fixed density, pressure, or temperature, to infer H II region properties. However, such an assumption may not fully capture the complexities of a turbulent interstellar medium. To understand how a complex density field driven by supersonic turbulence impacts nebular emission lines, we simulate 3D H II regions surrounding a single O star, both with and without supersonic turbulence. We find that turbulence directly impacts the values of common strong line ratios. For example turbulent H II regions exhibit systematically higher [N II]/H$α$, lower [O III]/H$β$, and lower O32, compared to homogeneous H II regions with the same mean density and ionizing source. These biases can impact inferences of metallicity, ionization parameter, excitation, and ionization source. For our choice of turbulence, direct $T_e$ method metallicity inferences are biased low, by up to 0.1 dex, which is important for metallicity studies, but not enough to explain the abundance discrepancy problem. Finally, we show that large differences between measured electron densities emerge between infrared, optical, and UV density indicators. Our results motivate the need for large grids of turbulent H II regions models that span the range of conditions seen at both high and low redshift to better interpret observed spectra.

Figures (11)

• Figure 1: Normalized emission line ratio diagnostics as a function of electron density for each of the homogeneous boxes coloured by their metallicity. The smooth curves show the predicted ratio for a uniform electron temperature of 10$^4$ K.
• Figure 2: Normalized $R_{\lambda 4363}$ metallicity diagnostic as a function of line temperature (defined by Equation \ref{['eq:line_temp']}) for each of the homogeneous boxes colored by their metallicity. The curve shows the predicted ratio for a uniform electron number density of $300\per cm\cubed$.
• Figure 3: Top row, from left to right: hydrogen density slice, hydrogen column density map, temperature slice. Bottom row, from left to right: integrated O II map, O II slice, integrated O III map. The diameter of each panel is 10 pc.
• Figure 4: Comparison of diagnostic emission-line ratios from the homogeneous and turbulent simulations as a function of metallicity. [O III]/H$\rm\beta$, [N II]/H$\rm\alpha$, and [O III]/[O II] are showed in the left, center, and right, respectively. Orange points represent data from homogeneous simulations. Each blue point represents the average across 10 turbulent realizations, with error bars indicating the standard deviation.
• Figure 5: Comparison of diagnostic emission-line ratios from the homogeneous and turbulent simulations with observational data. The left panel shows $\rm log_{10}([N~II]/H\alpha)$ vs. $\rm log_{10}([O~III]/H\beta)$, the center panel shows $\rm log_{10}([S~II]/H\alpha)$ vs. $\rm log_{10}([O~III]/H\beta)$, and the right panel shows $\rm log_{10}([O~I]/H\alpha)$ vs. $\rm log_{10}([O~III]/H\beta)$. Small purple dots represent high redshift galaxies from the DAWN JWST Archive BrammerValentino2025. Homogeneous simulations are the larger dots and turbulent simulations are the brown-outlined stars. Both are colored by metallicity. The background gray histogram indicates the number density of galaxies from the Sloan Digital Sky Survey (SDSS, Aihara2011). The solid lines in each panel represent relations from Kewley:2002 to separate star-forming galaxies/H II regions from AGN. The dashed line in the first panel is the empirical discriminator Kauffmann_2003. AGN are filtered out according to the Kewley:2002 relation for $\rm log_{10}([N~II]/H\alpha)$ vs. $\rm log_{10}([O~III]/H\beta)$.