HONO chemistry at a suburban site during the EXPLORE-YRD campaign in 2018: formation mechanisms and impacts on O 3 production

• Published in: Atmospheric chemistry and physics Vol. 23; no. 24; pp. 15455 - 15472
• Main Authors: Ye, Can, Lu, Keding, Ma, Xuefei, Qiu, Wanyi, Li, Shule, Yang, Xinping, Xue, Chaoyang, Zhai, Tianyu, Liu, Yuhan, Li, Xuan, Li, Yang, Wang, Haichao, Tan, Zhaofeng, Chen, Xiaorui, Dong, Huabin, Zeng, Limin, Hu, Min, Zhang, Yuanhang
• Format: Journal Article
• Language: English
• Published: 18.12.2023
• ISSN: 1680-7324; 1680-7324
• DOI: 10.5194/acp-23-15455-2023

HONO is an important precursor for OH radicals that impact secondary-pollutant production. However, there are still large uncertainties about different HONO sources which hinder accurate predictions of HONO concentration and hence atmospheric oxidation capacity. Here HONO was measured during the EXPLORE-YRD campaign (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta), along with other important parameters, enabling us to comprehensively investigate HONO variation characteristics and evaluate the relative importance of different HONO sources by using a box model. HONO showed significant variations, ranging from several tens of parts per thousand to 4.4 ppb. The average diurnal pattern of HONO / NOx showed a maximum of 0.17 around noon and resembled that of j(O1D), indicating the existence of photo-induced sources. Modeling simulations with only the default HONO source (OH + NO) largely underestimated HONO concentrations, with the modeled-averaged noontime HONO concentration an order of magnitude lower than the observed concentration. The calculated strength of the unknown HONO source (Punknown) showed a nearly symmetrical diurnal profile with a maximum of 2.5 ppb h−1 around noon. The correlation analysis and sensitivity tests showed that the photo-induced NO2 conversion on the ground was able to explain Punknown. Additional HONO sources incorporated into the box model improved the model's performance in simulating HONO concentrations. The revised box model reproduced the nighttime HONO concentration well but still underestimated the daytime HONO concentration. Further sensitivity tests indicated the underestimation of daytime HONO was not due to uncertainties of photo-induced NO2 uptake coefficients on the ground or aerosol surfaces or the enhancement factor of nitrate photolysis but was more likely due to other sources that were not considered in the model. Among the incorporated HONO sources and the default gas-phase source, photo-induced NO2 conversion on the ground dominated the modeled HONO production during the daytime, accounting for 71 % of the total, followed by NO + OH, NO2 hydrolysis on the ground surface, vehicle emissions, photo-induced NO2 conversion on the aerosol surface, nitrate photolysis and NO2 hydrolysis on the aerosol surface. NO2 hydrolysis on the ground surface was the major source of nighttime HONO, contributing 55 % of total HONO production. HONO photolysis contributed 43 % of ROx production during the daytime, followed by O3 photolysis (17 %), HCHO photolysis (14 %), ozonolysis of alkenes (12 %) and carbonyl photolysis (10 %). With observed HONO as a model constraint, the average peak of net ozone production rate increased by 88 % to 12.6 ppb h−1 compared to that without observed HONO as a model constraint, indicating HONO evidently enhanced O3 production and hence aggravated O3 pollution in summer seasons. Our study emphasized the importance of heterogeneous NO2 conversion on the ground surface in HONO production and accurate parameterization of HONO sources in predicting secondary-pollutant production.