New insight into the spatiotemporal variability and source apportionments of C₁–C₄ alkyl nitrates in Hong Kong

C₁–C₄ alkyl nitrates (RONO₂) were measured concurrently at a mountain site, Tai Mo Shan (TMS), and an urban site, Tsuen Wan (TW), at the base of the same mountain in Hong Kong from September to November 2010. Although the levels of parent hydrocarbons were much lower at TMS (<i>p</i> &lt; 0.05), similar alkyl nitrate levels were found at both sites regardless of the elevation difference, suggesting various source contributions of alkyl nitrates at the two sites. Prior to using a positive matrix factorization (PMF) model, the data at TW were divided into "meso" and "non-meso" scenarios for the investigation of source apportionments with the influence of mesoscale circulation and regional transport, respectively. Secondary formation was the prominent contributor of alkyl nitrates in the meso scenario (60 ± 2 %, 60.2 ± 1.2 pptv), followed by biomass burning and oceanic emissions, while biomass burning and secondary formation made comparable contributions to alkyl nitrates in the non-meso scenario, highlighting the strong emissions of biomass burning in the inland Pearl River delta (PRD) region. In contrast to TW, the alkyl nitrate levels measured at TMS mainly resulted from the photooxidation of the parent hydrocarbons at TW during mesoscale circulation, i.e., valley breezes, corresponding to 52–86 % of the alkyl nitrate levels at TMS. Furthermore, regional transport from the inland PRD region made significant contributions to the levels of alkyl nitrates (∼ 58–82 %) at TMS in the non-meso scenario, resulting in similar levels of alkyl nitrates observed at the two sites. The simulation of secondary formation pathways using a photochemical box model found that the reaction of alkyl peroxy radicals (RO₂) with nitric oxide (NO) dominated the formation of RONO₂ at both sites, and the formation of alkyl nitrates contributed negatively to O₃ production, with average reduction rates of 4.1 and 4.7 pptv pptv⁻¹ at TMS and TW, respectively