Hourly average monitoring data for mass concentrations of PM₁, PM_2.5, PM₁₀, and black carbon (BC) were measured in Wuhan from December 2013 to December 2014, which has a flourishing steel industry, to analyze the characteristics of PM and their relation to BC, using statistical methods. The results indicate that variations in the monthly average mass concentrations of PM have similar concave parabolic shapes, with the highest values occurring in January and the lowest values appearing in August or September. The correlation coefficient of the linear regression model between PM₁ and PM_2.5 is quite high, reaching 0.99. Furthermore, the proportion of PM₁ contained within PM_2.5 is roughly 90%, directly proving that ultrafine particles whose diameter less than 1 μm may be a primary component of PM_2.5 in Wuhan. Additionally, better seasonal correlation between PM and BC occurs only in summer and autumn, due to multiple factors such as topography, temperature, and the atmosphere in winter and spring. Finally, analysis of the diurnal variation of PM and BC demonstrates that the traffic emissions during rush hour, exogenous pollutants, and the shallow PBLH with stagnant atmosphere, all contribute to the severe pollution of Wuhan in winter.