To investigate the evolutionary patterns of atmospheric photochemical parameters and the influence mechanisms of aerosols in Beijing，this study analyzed the spatiotemporal characteristics of nitrogen dioxide photolysis rate J（NO2）and explored the impacts of aerosols on J（NO2）based on near-surface observations of J （NO2）and ultraviolet（UV）radiation in Beijing from September 2018 to August 2019，combined with radiative transfer model TUV simulations and aerosol optical parameter analysis. Additionally，this 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 J（NO2）exhibits a typical unimodal pat‐ tern，with the peak generally occurring during the noon period［12:00-13:00，（Local Time ，the same as after）］，directly influenced by changes in solar zenith angle. The daytime maxima of J（NO2）in summer are 1. 9 times those in winter，measuring 5. 65×10-3 s-1 and 2. 95×10-3 s-1，respectively，indicating significantly enhanced photolysis rates in summer due to higher solar radiation intensity. Seasonal variations follow the order：summer （3. 77×10-3 s-1）> spring（3. 51×10-3 s-1）> autumn（2. 97×10-3 s-1）> winter（2. 25×10-3 s-1），driven by seasonal changes in solar radiation intensity and the combined effects of increased summer precipitation. Furthermore，an estimation model for J（NO2）constructed using the UV clear-sky index（KUV）and the cosine of solar zenith angle demonstrated a linear correlation coefficient of 0. 99 between calculated and observed values，with 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 conditions，providing an effective predictive tool. The reconstructed long-term dataset reveals a significant upward trend in J（NO2）in Beijing from 2013 to 2023，with an annual increase rate of 2. 73%. The 2023 annual mean（4. 20×10-3 s-1）increased by 31. 3% compared to 2013（3. 20×10-3 s-1），closely linked to the continuous decline in PM 2. 5 concentrations（annual reduction rate：5. 51%）and aerosol optical 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 enhancement. The study found that J（NO2）significantly decreases under polluted conditions. When PM2. 5 concentrations exceed 75 μg·m-³，the J（NO2）maximum decreases by 22. 8% compared to clean conditions，indicating that PM 2. 5 concentration is a critical factor influencing photolysis rates. Analysis of aerosol optical properties revealed that J（NO2）is negatively correlated with AOD and Ångström exponent（AE），but positively correlated with single-scattering albedo（SSA）. Sensitivity tests demonstrated that increasing AOD from 0. 5 to 2. 5 reduces the daily maximum J（NO2）by 45. 6%，with a noon attenuation rate of 49. 8% at AOD = 2. 5. Conversely，in‐ creasing SSA from 0. 2 to 1. 0 enhances aerosol scattering capacity，raising the daily maximum J（NO2）by 43%. Increasing AE from 0. 5 to 2. 0 results in only a 3. 0% reduction in J（NO2）maxima，indicating 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 > AE，with AOD exerting the most significant influence on J（NO2）variations， highlighting the dominant role of aerosol extinction in suppressing photochemical processes. Additionally，vali‐ dation of the TUV model confirmed its reliability in simulating J（NO2）spatiotemporal variations，with a correlation coefficient of 0. 93 between simulated and observed values. This validation provides crucial methodological support for quantifying aerosol-radiation-photochemistry coupling mechanisms.