Intensive air quality measurements made from June 22–25, 2011 in the outflow of the Dallas–Fort Worth (DFW) metropolitan area are used to evaluate nitrous acid (HONO) sources and sinks. A two-layer box model was developed to assess the ability of established and recently identified HONO sources and sinks to reproduce observations of HONO mixing ratios. A baseline model scenario includes sources and sinks established in the literature and is compared to scenarios including three recently identified sources: volatile organic compound-mediated conversion of nitric acid to HONO (S1), biotic emission from the ground (S2), and re-emission from a surface nitrite reservoir (S3). For all mechanisms, ranges of parametric values span lower- and upper-limit values. Model outcomes for ‘likely’ estimates of sources and sinks generally show under-prediction of HONO observations, implying the need to evaluate additional sources and variability in estimates of parameterizations, particularly during daylight hours. Monte Carlo simulation is applied to model scenarios constructed with sources S1–S3 added independently and in combination, generally showing improved model outcomes. Adding sources S2 and S3 (scenario S2/S3) appears to best replicate observed HONO, as determined by the model coefficient of determination and residual sum of squared errors (r2 = 0.55 ± 0.03, SSE = 4.6 × 106 ± 7.6 × 105 ppt2). In scenario S2/S3, source S2 is shown to account for 25% and 6.7% of the nighttime and daytime budget, respectively, while source S3 accounts for 19% and 11% of the nighttime and daytime budget, respectively. However, despite improved model fit, there remains significant underestimation of daytime HONO; on average, a 0.15 ppt/s unknown daytime HONO source, or 67% of the total daytime source, is needed to bring scenario S2/S3 into agreement with observation. Estimates of ‘best fit’ parameterizations across lower to upper-limit values results in a moderate reduction of the unknown daytime source, from 0.15 to 0.10 ppt/s.


Earth Systems Research Center

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Atmospheric Environment



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Copyright © 2015 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.


This is an Accepted Manuscript of an article published by Elsevier in Atmospheric Environment in 2016, available online: This manuscript version is made available under the CC-BY-NC-ND 4.0 license