See enclosed

The study by Li et al. provides an extensive record of HONO measured during a field campaign Beijing, China in 2021. The novelty of this work comes from the fact that it HONO concentration measurements during the summer and autumn months, which have been lacking from previous studies conducted in Beijing, which have mostly occurred during the winter months (Figure 3). Detection of HONO was conducted using a LOPAP system. Analysis of the data was somewhat routine was focused on evaluating potential nighttime and daytime sources of HONO during the campaign, in addition to determining the impact of HONO relative to other OH sources on the oxidative capacity in the region. This approach is typical of many papers that attempt to determine the relative influence of the various HONO sources on observed ambient concentrations. The conclusions or analysis approaches are not novel. After calculating a rate of HONO formation from the unknown daytime source, there is some speculation that it is from photo-enhanced NO₂ conversion or nitrate photochemistry, which may be supported by some of the data, depending on the month.  The work is valuable as a record of HONO concentrations from an important urban area during a time of year that is less well studied and alone for that should be probably be published eventually-- after the manuscript is revised for clarity, based on the suggestions below.

Significant figures:  There are numerous cases within the text and in tables where too many significant figures are used when reporting numbers (e.g., Table 1 or section 3.1.1, reporting temperature to the hundredth of a degree, or relative humidity to a hundredth of a percent; section 3.1.2, trace gas measurements, etc. many of these measurements are likely not accurate out to that many decimal points and the values should be rounded off appropriately. 

Figure 2:  This figure was of very poor quality such that it was very difficult to read.  The resolution was very low and colors chosen (e.g., yellow or pink) were of low contrast, making it almost impossible to read. 

Section 3.2.1 and Figure 3: I feel it is difficult to make comparisons between HONO concentrations made during different seasons over a 20 year period in Beijing based simply on monthly averages. Error bars or any other indicator of variation in the data is not indicated for these values and it is not clear whether median concentrations may be a better way to report the data. Without consideration of the variation of these concentrations, it is not possible to make conclusions about whether values in summer are higher (in a statistically significant way) than in autumn or winter, etc.   

Line 242:  I found the term “corrected HONO concentration (HONOcorr) confusing. It would help to explain that this is the concentration of HONO in air that is not due to direct vehicular emissions.

Line 251: Symbols for the rate constants should be written with lower case “k” instead of capital letter, which would be understood as an equilibrium constant.

Line 275: HONOcorr is here referred to as the HONO concentration due to heterogeneous NO2-to-HONO conversion during the nighttime. However, in equation (3) it is all HONO that is not due to direct vehicular emissions.  Perhaps a different symbol or term should be used for referring to the nighttime HONO concentrations due solely to NO2 heterogeneous reaction to avoid confusion.  

Equations 5-7: The rational/derivation of these equations is not clear and symbolism is very unclear and there are several typos in the equations.  Besides the [HONOcorr] term described above, it was confusing to use the symbol “C” for a conversion frequency since C is used often to represent concentration, and the units of the “conversion frequency” suggest they are first-order rate constants. Also, it is not clear why the conversion frequencies are scaled to CO concentrations. A clarification would be useful here.

Table 3:  This table compares HONO conversion frequencies and production rates and forms the basis of a comparison. I recommend including errors and when comparing values from this study to others, one should conduct and report results of the appropriate statistical tests of significance.

Lines 334-343: This paragraph compares the production rate of HONO due to “unknown sources” derived from this work to values previously reported in the literature. It is one continuous string of values with references and as such is extremely difficult to read. I recommend including all this information in a table or figure to facilitate comparison.

A number of correlations are explored between P-unknown and various other data metrics (e.g., trace gas concentrations, light intensity, PM2.5 concentrations, and products thereof).  A number of correlations are reported using R values as an indicator of the quality of the fit. However, it is unclear whether these correlations are statistically significant.  Please provide information on statistical significance.  Also, with respect to the correlations, I am uncomfortable with choosing only the months that support a given hypothesis.  For example, it was noted that there is a strong correlation (R = 0.62) between P-unknown and (JNO2 x NO2 x PM2.5) in June, although this is the only month where this correlation seems to be significant. Yet, this is taken to be evidence for a light-induced heterogeneous reaction for NO2-to-HONO conversion. Why would this relationship only exist in June and not during other months.  Same for the correlations with various salt concentrations in October (lines 400-405).

Section 3.5:  This section explores the relationships between HONO concentrations, PM2.5 and ozone concentrations in the dataset. A positive correlation between particle pollution and HONO concentration in summer was taken to be evidence that particles are the source of HONO. However, correlation does not imply causation and it is possible that both PM2.5 and HONO are stem from the same sources (i.e., their concentrations would both increase during pollution events) and it is also possible that high HONO concentrations can lead to higher oxidative capacity and therefore higher rates of aerosol formation. 

Supporting Information figures and tables:  Place each figure or table on its own page and ensure that the figure captions are on the same page as the graphs or tables.

Figure S1:  What does the symbol WD and WS stand for.  Please define.

Lastly, although I felt the language used in the manuscript was relatively clear to understand, it would benefit from proofreading/editing by a native English speaker.