Lanzhou is a typical mountainous city with severe air pollution in northwestern China. This study uses hourly observational data of air pollutants at five air quality monitoring sites in Lanzhou from July to December 2015 to discuss data quality control and the representativeness of the monitoring sites (four urban sites and one suburban site). A fuzzy matrix is applied to study primary air pollutants. The results show that of the six routinely monitored pollutants, the primary pollutant is PM10 during the study period. Based on lag correlation analysis and one-way analysis of variance, it is concluded that there are redundant observations at the four urban sites for the timely diffusion and transport of air pollutants from the same general area. The coefficient of divergence (COD) method is then used to evaluate the spatial distribution differences, and the primary air pollutant PM10 shows differences at each site. COD can be used as a positive indicator to describe site representativeness. To evaluate the overall air pollution in the valley, correlation analysis is performed between the PM10 concentration retrieved from aerosol optical depth satellite data and the concentration from the four urban monitoring sites. Among these, the correlation between the workers’ hospital site data and the retrieval data is the highest, passing the 90% confidence level. A new representative evaluation model for air quality monitoring sites, Rs = 0.77COD + 0.23Rretrieval, is established by using COD and correlation coefficients between routine observations and satellite retrieval products. From this model, it can be concluded that the biological products institute site in Lanzhou is the most representative site for the evaluation of air pollution out of the four urban air quality monitoring sites from July to December 2015.