Page 247 - 《高原气象》2025年第6期

6 期 李春燕等：基于观测与模拟的北京光解速率长期变化特征研究 1655
tive error of 8. 8% and a root mean square error of 0. 00036. These results validate the model’s high applicability
under complex atmospheric conditions， providing an effective predictive tool. The reconstructed long-term datas‐
et reveals a significant upward trend in J（NO） in Beijing from 2013 to 2023， with an annual increase rate of
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2. 73%. The 2023 annual mean （4. 20×10 s ） increased by 31. 3% compared to 2013 （3. 20×10 s ）， closely
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linked to the continuous decline in PM concentrations （annual reduction rate： 5. 51%） and aerosol optical
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depth （AOD， annual reduction rate： 5. 74%）. These changes suggest that reduced particulate matter due to air
quality improvement measures has diminished UV radiation attenuation， indirectly promoting photolysis rate en‐
hancement. The study found that J（NO） significantly decreases under polluted conditions. When PM concen‐
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trations exceed 75 μg·m ³， the J（NO） maximum decreases by 22. 8% compared to clean conditions， indicating
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that PM concentration is a critical factor influencing photolysis rates. Analysis of aerosol optical properties re‐
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vealed that J（NO） is negatively correlated with AOD and Ångström exponent （AE）， but positively correlated
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with single-scattering albedo （SSA）. Sensitivity tests demonstrated that increasing AOD from 0. 5 to 2. 5 reduces
the daily maximum J（NO） by 45. 6%， with a noon attenuation rate of 49. 8% at AOD = 2. 5. Conversely， in‐
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creasing SSA from 0. 2 to 1. 0 enhances aerosol scattering capacity， raising the daily maximum J（NO） by 43%.
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Increasing AE from 0. 5 to 2. 0 results in only a 3. 0% reduction in J（NO） maxima， indicating that AE has a
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weaker influence compared to AOD and SSA. The hierarchy of aerosol impacts on photochemical processes is
ranked as AOD > SSA > PM > AE， with AOD exerting the most significant influence on J（NO） variations，
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highlighting the dominant role of aerosol extinction in suppressing photochemical processes. Additionally， vali‐
dation of the TUV model confirmed its reliability in simulating J（NO） spatiotemporal variations， with a correla‐
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tion coefficient of 0. 93 between simulated and observed values. This validation provides crucial methodological
support for quantifying aerosol-radiation-photochemistry coupling mechanisms.
Key words： NO photolysis rate； long-term trend； TUV； aerosols
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