Abstract:
Exploring the fluctuations of air quality index in a short period by using historical observation data can be helpful to formulate air pollution prevention and control measures, which is of great significance for coordinating development of regional environment and economy. In order to study the air quality characteristics of the Shaanxi Province, Gansu Province and Ningxia Hui Autonomous Region (referred to as 'Shaan-Gan-Ning Area') from 2015 to 2017, the mass concentration characteristics of AQI (air quality index) and six pollutants, including ρ(PM2.5), ρ(PM10), ρ(O3), ρ(NO2), ρ(SO2), ρ(CO) were investigated. The data of 32, 910 samples from 29 cities were sorted by mathematical statistics, while the spatial and temporal variation characteristics of the AQI and six pollutant concentrations were analyzed by Kriging interpolation. The results showed:(1) From the space, the pollution in the Guanzhong Plain in Central Shaanxi Province, the northern part of Ningxia Hui Autonomous Region, and the northwestern part of Gansu Hexi Corridor was relatively serious, but in the southwestern part of the region was relatively light. The higher ρ(O3) mainly distributed in the northwest of the region, while the higher ρ(CO) and ρ(NO2) were located the eastern part of the region. ρ(PM2.5) and ρ(PM10) were similar to those of AQI, and ρ(SO2) was higher in the northern part of the region. (2) From the time, the average value of AQI has been stabilized within the national standard value range (88) for three years. The order of seasonal variation in AQI was winter (108) > spring (88) > autumn (78) > summer (74). (3) The monthly variation characteristics of each pollutant concentration were as following:ρ(O3) was the highest in summer, the peak concentration was 140.3 μg/m3, then followed by spring and autumn, and lowest value was found in winter. The concentration of other pollutants showed the highest in winter, the peak concentration were ρ(PM2.5)(83.7 μg/m3), ρ(PM10)(155.9 μg/m3), ρ(SO2)(72.6 μg/m3), ρ(NO2)(52.1 μg/m3) and ρ(CO)(2.04 mg/m3), respectively. (4) Correlation analysis showed that the correlation coefficients of AQI with the mean temperature, average precipitation and pressure were -0.859, -0.903 and 0.620, respectively. The average temperature, average precipitation and AQI showed a significant negative correlation (P < 0.01), but pressure was significantly and positively related to it (P < 0.05); The DEM terrain relief analysis found that the higher the terrain relief level, the smaller the AQI value. AQI was mainly influenced by the number of the industrial companies, the correlation coefficients was 0.634. The study showed that the natural factors have a stronger impact on AQI than the socio-economic factors, and meteorological conditions play an important role in the spread of air pollution.