The air quality in a street canyon seriously affects the exposure level of pollutants for pedestrians and is directly related to the indoor air quality (IAQ) of surrounding buildings. In order to improve the street canyon environment, it is necessary to clarify the distribution and dispersion characteristics of pollutants. Through field tests, wind tunnel experiments, and numerical simulation, the current research studied the nature of pollutants in street canyons and provided some improvement measures. This paper comprehensively introduces the characteristics of pollutants in street canyons and reviews past studies on the following parts: (a) the dispersion principle and main impact factors of pollutants in street canyons, (b) the spatial and temporal distribution of pollutants in street canyons, (c) the relationship between pollutants in street canyons and indoor air quality, and (d) improvement measures of the street canyon environment. The dispersion of pollutants is dominated by the air exchange between the street canyon and the upper atmosphere, which is strengthened when the wind speed is high or when the temperature in the street canyon is obviously higher than the surrounding area. The heat island effect is beneficial for pollutant dispersion, while the inversion layer has a negative influence. Dense buildings mean lower pollutant diffusion capacity, which causes pollutants to easily gather. Pollutants tend to accumulate on the leeward side of buildings. The concentration of pollutants decreases with the increase of height and drops to the background level at a height of several hundred meters. The temporal distribution of pollutants in street canyons varies in diurnal, weekly, and annual periods, and the concentration peaks in the winter morning and summer evening. Besides, pollutants in street canyons have a significant influence on IAQ. To improve the street canyon environment, green belts and other facilities should be reasonably set up in the streets. Future research should pay attention to comprehensive test data, solving disagreement conclusions, and quantitative evaluation of the various impact factors on pollutants, etc.