Rowlinson et al. present a new parameterization of particulate nitrate photolysis to explain high HONO concentrations observed in recent field campaigns conducted in less polluted regions. They include this parameterization in the GEOS-Chem model and compare simulations against HONO observations from additional campaigns, finding improved agreement compared to simulations without this source. However, including this new HONO source leads to large changes in the global NOx source and the O₃ and OH burdens in the model, which are inconsistent with observational constraints. The authors, therefore, conclude that these HONO measurements highlight a gap in our current understanding of atmospheric chemistry.

The study addresses an important issue: photolysis of HONO is a source of NOx and HOx, both key species in tropospheric chemistry. Observations in remote areas have reported unexpectedly high HONO concentrations, suggesting an unidentified source that could significantly influence NOx and HOx cycling. Some prior studies have suggested particulate nitrate photolysis as this source and have derived photolysis rates based on the inferred HONO source. This study expands on that approach using a broader observational dataset and evaluates its global implications.

Although the results are potentially impactful, there are some major issues to be addressed:

i) The study adopts a narrow framing of uncertainties surrounding HONO sources, assuming particulate nitrate photolysis as the sole explanation for observed HONO (cf. Eq. 1), without adequate justification. Notably, the role of heterogeneous NO₂ reactions on aerosols is not discussed, although this process is included in GEOS-Chem. What is the uncertainty associated with it? What other mechanisms have been proposed in the literature, and why are they insufficient to explain the observed HONO? Addressing these questions is necessary to substantiate the study’s conclusion that the HONO observations point to a fundamental gap in our understanding.

ii) The key result supporting this conclusion is the large effect of the proposed HONO source on the modeled burdens of O₃ and OH, which is pushed beyond observational bounds. This occurs even though the model underestimates particulate nitrate concentrations and potentially also the HONO source. The issue again is that the study assumes that the missing HONO source is only from particulate nitrate photolysis. If the missing reaction producing HONO consumes NOx (and HOx), then the impact on O₃ and OH would be smaller. Li et al. (2014; doi: 10.1126/science.1248999) hypothesized such a mechanism, and recent laboratory work by Song et al. (2023; doi: 10.1038/s41612-023-00357-8) provides empirical evidence for another such reaction. This alternative explanation seems more plausible and should be considered.

iii) The physical interpretation of the parameterization for HONO production from particulate nitrate photolysis is unclear.

From Eqs. 1–4, the HONO production rate is given by:

P(HONO) = (2/3) × J(HNO₃) × EF × [pNO₃]

where EF = C1 / (1 + C2 × [pNO₃]). At atmospherically relevant [pNO₃], C2 × [pNO₃] >> 1, which reduces the EF to:

EF ≈ (C1 / C2) / [pNO₃]

and thus,

P(HONO) ≈ (2/3) × J(HNO₃) × (C1 / C2)

This implies that the HONO production rate is effectively independent of [pNO₃], which is difficult to interpret physically if particulate nitrate photolysis is the missing HONO source. 

General Comments

This study presents a compelling investigation into the role of nitrate aerosol photolysis as a major source of nitrous acid (HONO) in the troposphere, and the role of HONO source in the distribution of NOx and OH. By integrating multi-platform observational data (aircraft, ship, and ground-based campaigns), the authors validate a novel parameterization for nitrate photolysis enhancement factors (EFs), which is first proposed based on laboratory studies. Taking advantage of this parameterization method, the work highlights a previously underestimated renoxification pathway that contributes significantly to reactive nitrogen recycling (~48 Tg N yr⁻¹), rivaling direct anthropogenic NOx emissions. While the author point out that these HONO measurements represent a key uncertainty in our current understanding of atmospheric chemistry, there are several major issues concerning the model, measurements and their comparsions.

Specific comments:

1. The two assumptions of the parameterization method are critical to the study’s conclusions but require rigorous uncertainty propagation analysis. Addressing these through sensitivity analyses, mechanistic refinements, and observational validation would strengthen the parameterization’s robustness and provide clearer boundaries for the proposed renoxification impacts. Attributing observed HONO enhancements exclusively to nitrate photolysis lacks comprehensive validation, as alternative NOₓ-related HONO sources  could not contribute to NOₓ regeneration source. A fixed HONO/NO₂ production ratio, based on a median value reported in Ye et al., neglects a large span of it. Such ratio uncertainties directly affect NOₓ and O₃ simulations, just like EF and particulate nitrate.
2. Althought the “new” parameterization adapts the pNO3 dependence and fit the field data with a R²=0.41, the substantial divergence between fitted and observed EFs (spanning >1 order of magnitude) introduces critical uncertainties in HONO predictions.
3. It is a bit confusing that particulate nitrate is underestimated in Figure 2, but overestimated in Figure 6?
4. The accurate representation of particulate nitrate (pNO₃⁻) concentrations is paramount for reliable HONO source quantification in the model. A key limitation arises because even with the proposed parameterization, the model cannot reconcile observed HONO levels if pNO₃⁻ is misrepresented (e.g., the current -95% low bias in total nitrate). This interdependency introduces a fundamental uncertainty: errors in pNO₃⁻ simulation propagate directly into HONO and NOₓ predictions, undermining confidence in the inferred atmospheric chemistry impacts (e.g., O₃ and OH increases). While the study acknowledges this issue, it does not address strategies to improve pNO₃⁻ modeling (e.g., aerosol-phase thermodynamics)—a gap that weakens the mechanistic credibility of the conclusions.
5. Current model uncertainties in simulating particulate nitrate, HONO, and NOₓ arise not only from incomplete mechanistic understanding but also from critical observational data gaps. Addressing both mechanism weaknesses and these data gaps is essential to advance model.