The current state of the art in air-quality monitoring is by using static (or slowly moving) in situ measurements. The main strength of the conventional strategy is the high accuracy of the measurement. Weaknesses are the results of the static nature of the monitoring system which does not allow any kind of flexibility. Our aim here is to produce a U-turn by a synergistic approach capitalizing the huge technological progress achieved in the last a few years in the field of autonomous drone swarms, autonomous mobile robots, and cheap and accurate air-quality sensors. Exploiting in concert these technologies, a paradigm shift will be possible by transforming the classical 2d-notion of environmental measure (1d in space and 1d in time) into a frontier 4d-based acquisition strategy (3d in space and 1d in time). State-of-the-art meteorological models and air quality models will work in concert to provide accurate weather/air-quality forecasts as proxies of potentially risky situations to be handled by the joint action of drones and robots. These latter will communicate with a node via suitable protocols the acquired environmental information to be handled remotely for successive actions, including the sending of warning messages A proof-of-concept will be delivered having the aim of monitoring an industrial area characterized by potentially serious environmental impacts. With minor modifications, e.g., to the type of used sensors, the proof-of-concept can be easily adapted to operate in different contexts non necessarily related to industrial plants.