the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
High-resolution large-eddy simulation to understand ozone formation and atmospheric oxidation capacity in Houston, Texas
Abstract. Highly reactive volatile organic compounds (HRVOCs) from mobile and petrochemical sources are important players in atmospheric photochemistry that contribute to the formation of ozone (O3). In a typical elevated O3 episode, we applied a high-resolution large eddy simulation (LES), coupled with the Weather Research and Forecasting model with chemistry (WRF-LES-Chem) to understand the mechanism of high O3 production over the Houston area. Our modeling was constrained and evaluated using field measurements from the NASA Tracking Aerosol Convection Interactions ExpeRiment – Air Quality (TRACER-AQ) project, Texas Commission on Environmental Quality (TCEQ), and vertical column density observations from Pandora spectrometers. The modeling results show enhanced performance in the LES domain, compared to the mesoscale models in simulating key chemicals. O3 sensitivity in the Houston urban area demonstrates a nearly homogenous early morning VOC-limited regime and transits to a noontime NOX-limited regime. As the day progresses into the afternoon, the atmospheric oxidative capacity (AOC) increases with major contribution from hydroxyl (OH) radical (90 %). High concentrations of alkenes also increased O3 (8–10 %) contribution to AOC in the late afternoon. The OH reactivity (KOH) is dominated by isoprene (35.76 %), carbon monoxide (CO; 12.98 %), formaldehyde (HCHO; 12.21 %), and alkanes with C > 3 (6.29 %), thus accelerating the production of hydroperoxyl (HO2) and peroxy (RO2) radicals. The concentrations of short-lived VOCs such as HCHO and acetaldehyde from the oxidation of HRVOCs, increased in the afternoon, which elevated O3 production rates under a NOX-limited regime. The oxidation of isoprene also accelerated the production of HCHO and contributed to the production of HO2 radicals, thus leading to a high O3 production rate. This study suggests the possible impacts of NOX-O3-VOC sensitivity on O3 production rates in polluted urban areas with high emission of HRVOCs, and also provides insights on radical chemistry that drives the photochemical processes of O3 formation. Ultimately, the study underlines the need to control anthropogenic emissions such as alkenes and HCHO and also highlights the role of naturally emitted isoprene species in elevated urban O3 levels.
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Status: open (until 29 Aug 2024)
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RC1: 'Comment on egusphere-2024-1190', Maarten Krol, 27 Jul 2024
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This paper presents a detailed analysis of the photochemistry in Houston, Texas. The (too long?) paper presents detailed analyses of some relevant quantities linked to ozone formation, such as the ratios Ln/Q and FNR, OH reactivity, Atmospheric Oxidizing Capacity (AOC), which is interesting to read. I note, however, that all these metrics are derived from model data, and not linked to similar observational quantities. The authors do some effort to compare the model to observational data from meteorology and atmospheric composition and conclude that the “D04-LES-300m” domain performs better than the DO2-mesoscale domain. They also write " LES simulation 300 m spatial resolution adequately captures the surface concentration of O3, NOX , and HCHO”. They base this conclusion mainly on Figures 4, 5, and 6, and some figures in the Appendix. Based on this conclusion, they proceed with the detailed analysis of the model output from D04.
The comparison shows still large discrepancies with observations. For instance, the ozone profiles presented in figure 6 show large discrepancies. Moreover, figure 5 shows only averages (bit unclear). Apparently, there is a wealth of information on e.g. diurnal variations of isoprene, but we do not get to see these. I would therefore strongly advise to make a more convincing comparison to observational data.
From a modelling point of view, the authors take a big step to run on high resolution (300 m). Apart from concluding that on this resolution the model performs better, there is unfortunately little analysis of the reasons why this is the case. Is this because the chemical contrasts get larger, causing more extreme chemical regimes (e.g. larger disruptions of chemistry because high NOx emissions)? There are some hints that the boundary layer mixing is better resolved on 300 m resolution, but this aspect is not well worked out either.
In the end, the authors draw some conclusions that both isoprene is important (e.g. largest OH-reactivity) next to anthropogenic VOC emissions. VOC concentrations basically are not evaluated with observations. Moreover, I was shocked that existing NOx inventories had to be scaled by ~0.2 to get meaningful results. This hardly receives attention in the abstract and conclusions. How does the model behave if the emissions of anthropogenic VOCs are off by a similar amount?
In conclusion, the paper presents an interesting analysis of model data in terms of ozone production and chemical reactivity, but the analysis is based on poorly evaluated models results, and fails to address the reasons why a high-resolution simulation would be required to analyse valuable data from measurement campaigns.
Minor Issues
Referencing: it seems referencing is restricted to inner circle papers. There is a long history of research lines that address the effects of resolution on atmospheric chemistry that is totally missing.
Other comments are in the annotated manuscript.
Appendix:
Figure S1: Unclear how to interpret the bottom plots.
Figure S5: Panels d-f not in the caption.
Figure S6: Idem: lower panels are not explicitly mentioned in caption.
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