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 approaches. Distributed networks of low-cost sensors, together with data fusion and analytics, have enabled unprecedented, spatiotemporal resolution when observing the urban atmosphere. Several projects 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 because 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.

Integration of Indoor Air Quality Prediction into Healthy Building Design

“…The refinement means that in addition to data from ambient stations, the toolbox needs to collect ambient pollution data on a smaller scale (city or community), which can better represent outdoor pollution surrounding a target building. It requires input from high-geological-resolution mapping of air quality in urban environments, which is a trend in the field of smart and healthy cities [84][85][86]. Future work should also perform more case studies with the i-IAQ toolbox to further validate and enhance the accuracy of the toolbox.…”

Dense Air Quality Sensor Networks: Validation, Analysis, and Benefits

“…It is expected that in the near future, air quality sensor network deployment would generate profits and revenues to the investors of air quality infrastructures and service providers. The information obtained from such sensor network are expected to move towards sophisticated business models, as described in [6]. The total size of the global air quality monitoring market which includes both reference stations, LCS hardware and services is estimated to reach $6.4 billion in the next 3 years [45].…”

“…Thanks to advances in communication and networking technologies, and the Internet of Things (IoT), low-cost sensors (LCSs) has emerged as an alternative that can be deployed on a massive scale in cities. This deployment facilitates obtaining hyperlocal air pollution information that can vary by more than eight times within 200 m [6]; and offers high resolution of spatio-temporal air quality information [7]. In massive deployment approach, LCSs can be installed in strategic locations in urban areas or the air quality data can be gathered through crowd-sourced-based sensing [8].…”

Sensitivity Operator Framework for Analyzing Heterogeneous Air Quality Monitoring Systems

“…For example, K can be a priori known source locations or the whole domain. We can evaluate characteristics ( 13), (14), and ( 16) on K. Corresponding cumulative characteristics are:…”

“…Choosing or optimizing the configuration of a monitoring system or observational experiment [3][4][5][6][7][8][9][10][11] is a multi-criteria decision-making task. It is necessary to compare the cost and accuracy of measuring equipment, maintenance costs, the goals of building such a system, its use cases, and other factors [12][13][14]. An essential criterion for choosing the configuration of the monitoring system is the value of the information content of prospective measurements.…”