Observation-Based Diagnostics of Reactive Nitrogen Recycling through HONO Heterogenous Production: Divergent Implications for Ozone Production and Emission Control

Understanding of nitrous acid (HONO) production is crucial to photochemical studies, especially in polluted environments like eastern China. In-situ measurements of gaseous and particulate compositions were conducted at a rural coastal site during the 2018 spring Ozone Photochemistry and Export from China Experiment (OPECE). This data set was applied to investigate the recycling of reactive nitrogen through daytime heterogeneous HONO production. Although HONO levels increase during agricultural burning, analysis of the observation data does not indicate more efficient HONO production by agricultural burning aerosols than other anthropogenic aerosols. Box and 1-D modeling analyses reveal the intrinsic relationships between nitrogen dioxide (NO2), particulate nitrate (pNO3), and nitric acid (HNO3), resulting in comparable agreement between observed and simulated HONO concentrations with any one of the three heterogeneous HONO production mechanisms, photosensitized NO2 conversion on aerosols, photolysis of pNO3, and conversion from HNO3. This finding underscores the uncertainties in the mechanistic understanding and quantitative parametrizations of daytime heterogeneous HONO production pathways. Furthermore, the implications for reactive nitrogen recycling, ozone (O3) production, and O3 control strategies vary greatly depending on the HONO production mechanism. On a regional scale, the conversion of HONO from pNO3 can drastically enhance O3 production, while the conversion from NO2 can reduce O3 sensitivity to NOx changes in polluted eastern China.

(Eq S1) where r is the ambient aerosol radius, r dry is the dry aerosol radius, h is relative humidity (RH), and a = 0.78 and b=1.90 are two empirical parameters chosen accordingly with the assumption of aerosol composition to be ammonium sulfate.The squared radius ratio is then used as surface area ratio to convert dry surface area to ambient wet surface area (Eq.S2).
S A = S dry A × r r dry 2 (Eq S2) The calculated S A at the surface is scaled by the vertical profile measured by Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) to get S A above the surface.

Data preparation for particulate nitrate (pNO 3 ) measurement
Particulate inorganic ions are measured at a 1-minute time step by the aerosol mass spectrometer (AMS) and daily by PM 2.5 filter samples.A comparison between mass concentrations of particulate nitrate (pNO 3 ), sulfate (SO 2- 4 ), ammonium (NH + 4 ), and chloride (Cl -) provided by AMS and PM 2.5 filter analysis shows a lower bias of AMS data for pNO 3 , SO 2- 4 , and Cl -, except that filter-based NH + 4 is lower than that measured by AMS, probably due to sampling artifacts [2][3][4] .In our study, we combine data from these two types of measurements as observed pNO 3 .We first derive the hourly profile for each day from AMS data and then scale the hourly profile by the daily filter-based data.

Text S2. HONO source parameterizations Heterogeneous conversion of NO 2 on ground surfaces
We adopt the parameterization by Liu et al. 11 to simulate HONO formation from the ground conversion of NO 2 .The production of HONO is parameterized as a subsequent release following NO 2 dry deposition on the ground into the surface layer.The parameterization is where f is the yield of HONO from NO 2 reaching the surface; H is the height of the first model layer, and V d is the dry deposition velocity of NO 2 .Since the photoactive mechanisms have negligible impact at night, we estimate the yield coefficient (f) for HONO from deposited NO 2 so that simulated nocturnal HONO can match observed concentrations.

Photosensitized conversion from NO 2 on aerosols
We parameterize photosensitized NO 2 conversion on aerosol surfaces as a first order reaction: where S A is the aerosol surface area, R p ~ 0.1µm is the aerosol radius; D g is the NO 2 molecular diffusion coefficient; ω is the mean molecular speed for NO 2 and γ is the aerosol uptake coefficient.Recent studies show that sunlight can catalyze this process.To represent this photoenhanced characteristic, we consider a first-order enhancement from short wave radiation (SWR) where SWR is simulated by WRF and scaled by observed jNO 2 , and γ' is a constant.Conversion from pNO 3    Ye et al. 12 showed that the photolysis rate of pNO 3 has a median value of 8.3×10 -5 s -1 and it is usually computed by scaling the photolysis rate of gas-phase nitric acid (jHNO 3 ) to get the photolysis rate of pNO 3 (jpNO 3 ): where EF is the enhancement factor.As Andersen et al. 13 have pointed out, EF can be dependent on pNO 3 , through the Langmuir function.Therefore, in addition to selecting a constant EF to reproduce the observed HONO as in case S2-1, we also fitted this relationship of EF on pNO 3 as described in the following equation, where K L = 0.19 nmol -1 m 3 is the Langmuir equilibrium constant of nitrate ion, and a is the coefficient to be fitted: (Eq S8) Conversion from HNO 3    Song et al. 14 showed that nitric acid (HNO 3 ) from photooxidation of NO 2 can be converted into HONO with a yield coefficient (Y HONO ) of 53%.In our study, we followed the same parameterization as described in their study to incorporate the HONO source from HNO 3 .

Number of pages: 20 Number of supporting texts: 2
Number of supporting figures: 15 Number of supporting tables: 6 Text S1.Descriptions of observations and data preparations Text S2.HONO source parameterizations

Figure S1 .
Figure S1.Radius ratio of ambient to dry aerosols as a function of RH

Figure S4 .
Figure S4.Averaged noontime mixing ratios of VOCs during the study period

Figure S6 .
Figure S6.Averaged diurnal profile of the pNO 3 partitioning ratio during the study period.

Figure S7 .Figure S8 .Figure S11 .Figure S15 .
Figure S7.Time series for O 3 , NO x , HONO, pNO 3 , and S A from 23 March to 22 April 2018 Figure S1.Radius ratio of ambient to dry aerosols as a function of RH.

Figure S3 .
Figure S3.Averaged diurnal profile and standard deviation (denoted by the vertical bars) of the mixing layer height diagnosed from K zz during the study period.

Figure S5 .
Figure S5.Comparisons of simulated HONO with photo-enhanced ground source with the observed HONO.

Figure S7 .
Figure S7.Time series for O 3 , NO x , HONO, pNO 3 , and S A from 23 March to 22 April 2018.

Figure S9 .
Figure S9.Correlations of CH 3 CN with NO 2 , pNO 3 , S A and organic matters in aerosol.

Figure S12 .
Figure S12.Frequency histogram for observation data points of different levels of CH 3 CN.

Figure S13 .
Figure S13.Ozone production efficiency (OPE) as a function of initial NO x concentrations for cases F0 -F3.

Figure S15 .
Figure S15.Annual mean noontime NO 2 concentrations for eastern China from 2014 to 2022.

Table S1 .
Instruments used during the OPECE campaign

Table S2 .
Correlation test results for biomass burning analysis

Table S3 .
Correlation test results for aerosol acidity effect analysis

Table S4 .
Statistics of correlation tests of pHONO against the production terms

Table S5 .
Comparisons of HONO source parameterizations to previous studies

Table S6 .
Comparisons of HONO/NO 2 and HONO/pNO 3 of different studies

.
Instruments used during the OPECE campaign

Table S3 .
Correlation coefficients (r) and p values for the correlation analysis of pH with HONO, HONO/NO 2 , HONO/pNO 3 , SWR, and S A .

Table S4 .
Statistics of correlation tests of pHONO with the production terms.

Table S5 .
Comparisons of HONO source parameterizations to previous studies

Table S6 .
Comparisons of HONO/NO 2 and HONO/pNO 3 of different studies