Air pollution has become a significant health, environmental and economic problem worldwide. The conventional approach of deploying fixed high-end air quality monitoring stations provides accurate measurements but can be expensive to deploy and maintain. As a result, the stations are typically deployed in a few strategic locations with various spatial interpolation or prediction models to estimate the air quality values from unsampled points. Recently, drive-by air quality sensing has emerged as a popular approach due to its dynamic nature, high spatial coverage, and low operational costs while providing highresolution data. At the same time, drive-by sensing has introduced a range of novel research challenges in terms of spatial and temporal coverage, mobile sensor calibration, and deployment strategies. This paper provides a systematic review and analysis of the recent work in this area, focusing on vehicular platforms, deployment strategies, primary challenges, and promising research directions.