As the most important urban agglomeration in Northwestern China, the ozone pollution in Guanzhong region has gradually become a prominent problem affecting local air quality in recent years. It is of great significance to explore its spatio-temporal variation characteristics and influencing factors for the atmospheric environment management in this region. Based on hourly mass concentration data of ozone from state-controlled environmental monitoring stations and hourly meteorological data from national meteorological stations in five cities of Guanzhong region from 2014 to 2020, the characteristics of near-ground ozone pollution and its meteorological influencing factors were analyzed comparatively. The results are as follows: (1) The ozone had gradually replaced PM₁₀ as the primary air pollutant after PM_2.5 in Guanzhong region in recent 7 years, and the proportion of days with ozone as the primary pollutant had a fluctuant increasing trend in the whole. (2) The monthly distributions of ozone mass concentration in five cities of Guanzhong region appeared a typical single-peak pattern, the ozone mass concentration was higher in summer (from June to August), and the value of concentration in Xi’an, Xianyang, Weinan, Tongchuan and Baoji decreased in order. The diurnal variations of ozone mass concentration also showed a single-peak pattern, with the trough from 07:00 to 08:00 and the peak from 15:00 to 16:00 in five cities of Guanzhong region. (3) When the maximum temperature is higher than 36 ℃, relative humidity is between 45% and 70% and the average wind speed is between 2 and 3 m·s^-1, the ozone is easy to exceed the standard in Guanzhong region, and the higher maximum temperature is, the greater exceeding standard rate of ozone is. The favorable wind direction to ozone pollution in Xi’an, Tongchuan, Xianyang and Weinan is NE, while that in Baoji is SE or NW. (4) The easterly route from the central and western parts of Henan Province is the most important transport route affecting ozone concentration in summer in Xi’an City. Except for neighbour cities of Shaanxi Province, the central and western Henan Province, Yuncheng of Shanxi Province and the northern Hubei Province are also major potential sources of O₃ pollution in Xi’an City.

Based on daily PM2.5 concentration data during 2014-2017, the annual and monthly variations of PM2.5 concentration were analyzed in Xi’an, and in heating and non-heating seasons its difference was obvious. Combined with daily meteorological elements observations from  meteorological stations, the correlation between meteorological elements and PM2.5 concentration in different seasons was analyzed. The hourly PM2.5 concentration data of 13 air-quality automatic monitoring stations in 2017 were used to analyze the spatial distribution and diurnal variation of PM2.5 concentration in Xi’an. The main conclusions are as follows: The PM2.5 concentration showed a U-shaped characteristic within a year, which was higher in winter but lower in summer. The difference of PM2.5 concentration in recent years was mainly in January, February, November and December，during this period, the wind speed, precipitation and cold air activity frequency had some influence on PM2.5 concentration. The days of PM2.5 exceeding standard in heating season and its ratio to PM2.5 exceeding standard days in the whole year increased but both of them declined in non-heating season. The difference of PM2.5 pollution in various regions was larger in winter but it was smaller in summer. The PM2.5 concentration presented obvious diurnal variation, and its fluctuation curve was M-shaped. The correlation between meteorological factors such as temperature, relative humidity, wind speed and precipitation and PM2.5  concentration was different in different seasons. High level PM2.5 pollution was more likely to occur on those days with low temperature, high humidity, low wind speed and less precipitation. The range of basic meteorological elements under different levels of PM2.5 pollution condition obtained by statistics had some indicative significance for the air quality forecast of PM2.5 pollution.