Characterisation of Long-term Changes in Photolysis Rate in Beijing based on Observation and Simulation

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  • 1. College of Electronic EngineeringChengdu University of Information TechnologyChengdu 610225SichuanChina
    2. State Key Laboratory of Atmospheric Environment and Extreme MeteorologyInstitute of Atmospheric Physics
    Chinese Academy of SciencesBeijing 100029China
    3. School of Chemistry and Chemical EngineeringDezhou UniversityDezhou 253000ShandongChina
    4. School of Resources and EnvironmentNortheast Agricultural UniversityHarbin 150030HeilongjiangChina

Online published: 2025-06-04

Abstract

To investigate the evolutionary patterns of atmospheric photochemical parameters and the influence mechanisms of aerosols in Beijingthis study analyzed the spatiotemporal characteristics of nitrogen dioxide photolysis rate JNO2and explored the impacts of aerosols on JNO2based on near-surface observations of J NO2and ultravioletUVradiation in Beijing from September 2018 to August 2019combined with radiative transfer model TUV simulations and aerosol optical parameter analysis. Additionallythis study reconstructed a long-term photolysis rate dataset from 2013 to 2023 to further reveal the correlation between long-term trends and aerosol characteristics. The results show that the diurnal variation of JNO2exhibits a typical unimodal pat‐ ternwith the peak generally occurring during the noon period12:00-13:00,(Local Time the same as after)],directly influenced by changes in solar zenith angle. The daytime maxima of JNO2in summer are 1. 9 times those in wintermeasuring 5. 65×10-3 s-1 and 2. 95×10-3 s-1respectivelyindicating significantly enhanced photolysis rates in summer due to higher solar radiation intensity. Seasonal variations follow the ordersummer 3. 77×10-3 s-1> spring3. 51×10-3 s-1> autumn2. 97×10-3 s-1> winter2. 25×10-3 s-1),driven by seasonal changes in solar radiation intensity and the combined effects of increased summer precipitation. Furthermorean estimation model for JNO2constructed using the UV clear-sky indexKUVand the cosine of solar zenith angle demonstrated a linear correlation coefficient of 0. 99 between calculated and observed valueswith a mean relative error of 8. 8% and a root mean square error of 0. 00036. These results validate the model’s high applicability under complex atmospheric conditionsproviding an effective predictive tool. The reconstructed long-term dataset reveals a significant upward trend in JNO2in Beijing from 2013 to 2023with an annual increase rate of 2. 73%. The 2023 annual mean4. 20×10-3 s-1increased by 31. 3% compared to 20133. 20×10-3 s-1),closely linked to the continuous decline in PM 2. 5 concentrationsannual reduction rate5. 51%and aerosol optical depthAODannual reduction rate5. 74%. These changes suggest that reduced particulate matter due to air quality improvement measures has diminished UV radiation attenuationindirectly promoting photolysis rate enhancement. The study found that JNO2significantly decreases under polluted conditions. When PM2. 5 concentrations exceed 75 μg·m-³the JNO2maximum decreases by 22. 8% compared to clean conditionsindicating that PM 2. 5 concentration is a critical factor influencing photolysis rates. Analysis of aerosol optical properties revealed that JNO2is negatively correlated with AOD and Ångström exponentAE),but positively correlated with single-scattering albedoSSA. Sensitivity tests demonstrated that increasing AOD from 0. 5 to 2. 5 reduces the daily maximum JNO2by 45. 6%with a noon attenuation rate of 49. 8% at AOD = 2. 5. Converselyin‐ creasing SSA from 0. 2 to 1. 0 enhances aerosol scattering capacityraising the daily maximum JNO2by 43%. Increasing AE from 0. 5 to 2. 0 results in only a 3. 0% reduction in JNO2maximaindicating that AE has a weaker influence compared to AOD and SSA. The hierarchy of aerosol impacts on photochemical processes is ranked as AOD > SSA > PM 2. 5 > AEwith AOD exerting the most significant influence on JNO2variationshighlighting the dominant role of aerosol extinction in suppressing photochemical processes. Additionallyvali‐ dation of the TUV model confirmed its reliability in simulating JNO2spatiotemporal variationswith a correlation coefficient of 0. 93 between simulated and observed values. This validation provides crucial methodological support for quantifying aerosol-radiation-photochemistry coupling mechanisms.

Cite this article

LI Chunyan, ZHAO Shuman, WU Shumin, LIU Kun1, HU Bo . Characterisation of Long-term Changes in Photolysis Rate in Beijing based on Observation and Simulation[J]. Plateau Meteorology, 0 : 1 . DOI: 10.7522/j.issn.1000-0534.2025.00037

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