气象条件对珠三角秋季地表臭氧年变化及趋势的影响

基于2015~2022年珠三角O₃监测数据以及再分析气象资料,利用多元线性回归（MLR）和LMG方法量化了气象条件对臭氧（O₃）日最大8 h浓度平均值（MDA8-O₃）年变化和趋势的影响. 结果表明,基于关键气象参数建立的MLR模型性能良好,同时基于秋季各月参数建立的MLR模型模拟的MDA8-O₃变化会比基于整个秋季气象参数建立的MLR模型更准确. 总云量、相对湿度、 2 m最高温度和850 hPa经向风的共同作用导致了2020年MDA8-O₃相对于2019年减少了34.1 μg·m^-3,贡献率分别为31.3%、 45.2%、 15.8%和6.7%. 珠三角2015~2022年的9月、 10月、 11月和秋季观测的MDA8-O₃变化率分别为7.3、 5.2、 4.8和5.8 μg·（m³·a）^-1,其中由气象驱动的趋势分别为3.6、 2.4、 2.4和3.1 μg·（m³·a）^-1,整体而言,气象条件对2015~2022年珠三角秋季MAD8-O₃变化的贡献率为53.4%.

Meteorological Influences on Annual Variation and Trend of Autumn Surface Ozone in the Pearl River Delta

Based on the ozone （O₃） monitoring data of the Pearl River Delta （PRD） from 2015 to 2022 and the reanalysis of meteorological data, the impact of meteorological conditions on the annual variation and trends of the maximum daily 8-hour average O₃ concentration （MDA8-O₃） were quantified using multiple linear regression （MLR） and LMG methods. The results indicated that the MLR model constructed using meteorological parameters from individual months in autumn better simulated the variation in MDA8-O₃ compared to that in the model built using meteorological parameters from the entire autumn season. The combined influence of total cloud cover, relative humidity, 2 m maximum temperature, and 850 hPa zonal wind led to a reduction of 34.1 μg·m^-3 in MAD8-O₃ in 2020 compared to that in 2019, with contributions of 31.3%, 45.2%, 15.8%, and 6.7%, respectively. The observed trends of MDA8-O₃ in the PRD for September, October, November, and the autumn season during 2015-2022 were 7.3, 5.2, 4.8, and 5.8 μg·（m³·a）^-1, respectively. Among these, the trends driven by meteorological factors were 3.6, 2.4, 2.4, and 3.1 μg·（m³·a）^-1. Overall, meteorological conditions contributed 53.4% to the variations in autumn MDA8-O₃ in the PRD from 2015 to 2022.