High-resolution assessment of air quality in urban areas—a business model perspective

Abstract

The increasing availability of low-cost air quality sensors has led to novel sensing ap-proaches. Distributed networks of low-cost sensors, together with data fusion and analytics, have en-abled unprecedented, spatiotemporal resolution when observing the urban atmosphere. Several pro-jects have demonstrated the potential of different approaches for high-resolution measurement networks ranging from static, low-cost sensor networks over vehicular and airborne sensing to crowdsourced measurements as well as ranging from a research-based operation to citizen science. Yet, sustaining the operation of such low-cost air quality sensor networks remains challenging be-cause of the lack of regulatory support and the lack of an organizational framework linking these measurements to the official air quality network. This paper discusses the logical inclusion of lower-cost air quality sensors into the existing air quality network via a dynamic field calibration process, the resulting sustainable business models, and how this expansion can be self-funded.