HONO chemistry and its impact on the atmospheric oxidizing capacity over the Indo-Gangetic Plain.

Chemical processes involving nitrous acid (HONO) play a pivotal role as it is a notable source of hydroxyl (∙OH) radicals, influencing the oxidation capacity of the atmosphere. We conduct a comprehensive investigation into the temporal dynamics of HONO, other gases (nitrogen oxides (NOx), ozone (O3), ammonia (NH3), sulphur dioxide (SO2), and nitric acid (HNO3)), particulate matter (PM2.5), and meteorological parameters using measurements that took place during the Winter Fog Experiment (WiFEx) campaign in Delhi, India, during the winter of 2017-2018. Remarkable day-to-day variations in HONO concentrations are observed, with the peak value reaching 54.5 µg m-3 during a fog event. This coincides with elevated levels of sulfate and nitrate in aerosols, underscoring the significant role of heterogeneous fog chemistry in HONO production. We investigated HONO sources and sinks during fog periods by using a photochemical box model. The model shows that the gas-phased chemistry of HONO predicts concentrations lower by an order of magnitude compared to observations (peaking at 0.60 µg m-3 compared to the average observed value of 7.00 µg m-3). The calculated production rates of HONO from observations for daytime to nighttime peaks are 3.10 µg m-3 h-1 (1.1 × 107 molecules cm3 s-1) and 2.00 µg m-3 h-1 (7.1 × 106 molecules cm3 s-1), respectively. This shows the existence of an undefined heterogeneous reaction pathway for HONO production. At the peak of HONO concentration, we estimated an ∙OH formation rate of 9.4 × 107 molecules cm3 s-1 due to the photolysis of HONO, which is much higher than the production of HONO from the reaction of O1D with H2O. This underscores the predominant role of HONO photolysis as the primary source of ∙OH radicals compared to other pathways and highlights the significant role of HONO chemistry in influencing atmospheric oxidation capacity.

Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain.

The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM2.5 by a chemical transport model.