Abstract: In recent years, composite pollution caused by particulate pollution and photochemical pollution has become an important pollution problem in large urban agglomerations. Based on the air quality monitoring data of 26 cities in the Yangtze River Delta Urban Agglomeration (YRDUA) in 2017, we analyzed the time series characteristics and pollution status of O ₃ and PM _2.5 in the region using mathematical statistics method. Then the grid data of O ₃，PM _2.5 was generated by inverse distance weight model to analyze the spatial distribution pattern of O ₃ and PM _2.5 in the region. Finally, combined with the meteorological factors of ECMWF in the same period, we discussed the effect of meteorological conditions on the concentration of O ₃ and the thresholds for the formation of high O ₃ concentration. The results show that: (1) The O ₃ concentration in YRDUA is highest in May and September, and the daily variation of O ₃_8 h is characterized by a tensile S curve, which reaches the peak concentration at 19:00 and 20:00. The maximum peak concentration is 111 μg/m ³ in Chuzhou; The spatial distribution of O ₃ gradually decreased from north to south, and spring(136.57 μg/m ³)> summer(117.35 μg/m ³)> autumn(83.23 μg/m ³)> winter(77.06 μg/m ³); O ₃ is significantly correlated with its precursors CO and NO₂. When 15<T≤20℃, 100<PRS≤100.5 kpa, O ₃ pollution is the most serious. (2) Monthly variation of PM _2.5 concentration is irregularly U-shaped distribution, the trough period is in July and August, the daily variation is double-peak trend, the first peak in Shanghai, Zhejiang region occurs at 9:00 or 10:00, in Anhui, Jiangsu region occurs at 11:00 or 12:00, the second peak is at 21:00; PM _2.5 concentrations higher in inland cities than in coastal cities, Winter(62.21 μg/m³)> Spring(44.70 μg/m³)≈ Autumn(44.14 μg/m³)> Summer (31.33 μg/m³); Compared with NO   and SO₂, PM_2.5 and CO are more relevant; O3 is positively correlated with temperature and relative humidity, negatively correlated with wind speed, wind direction, air pressure, boundary layer height, and precipitation, PM_2.5 is positively correlated with wind direction and air pressure, and negatively correlated with other factors; The temperature is less than 5℃, 100<PRS≤100.5 kpa, PM_2.5 exceeding standard rate is highest in YRDUA.