About this Research Topic
Sensors for air quality monitoring are increasingly attracting attention due to a growing awareness of the importance of air quality in connection to the three pillars of sustainability: environment, society, and economy. Nowadays challenges include improved selectivity, monitoring of complex processes, autonomous data processing and visualization, detection of sensor faults, rigorous data evaluation to ensure that performance specifications meet designated monitoring objectives, data integration from multiple sensors and sources of different quality, self-calibration, self-learning, and potential self-diagnosis.
Compared to conventional methods, sensors offer air pollution monitoring at a reduced cost, power consumption, and size, potentially allowing for ubiquitous and real-time monitoring. Unfortunately, at the current stage of development, measurements with low-cost sensors are often of lower data quality and uncertain reliability than results from conventional monitoring stations, analyzers, and other advanced equipment. The quality of results depends, among other factors, on technology, sensing materials, operating conditions, ambient parameters, experimental setup, data processing and data analysis, evaluation and validation methods, calibration issues, implementation, site, and intended application. All of these aspects need to be carefully considered and evaluated. A lot of multidisciplinary research and technological progress is moving forward in the field with the belief that sensors could soon become a game-changer in monitoring air pollution, traffic management, personal exposure and health assessment, citizen science, and air pollution assessment in both industrialized and developing countries. Today, sensors can complement measurement data from established highly expensive monitoring stations or satellite data, support air pollution research studies, and pave the way to groundbreaking research, disruptive technologies, and emerging applications that in a few years could make the sensor market skyrocket.
Advantages of developing and using sensors include ease of operation and data access, the possibility of expanded and faster data collection due to a much higher Spatio-temporal resolution of air quality measurement, promotion of community engagement, and personal monitoring, and potentially reduced socio-economic burden of disease. On the other hand, limitations include selectivity and cross-sensitivity issues, quality of data which is not on par with data generated by reference methods, metadata often not collected, reliability, and lifetime that need improvement.
In this Research Topic for Frontiers in Sensors, we invite submissions of original papers, mini-reviews, short communications, and commentaries from academia, research institutes, and industry, that introduce new knowledge as well as promote a better understanding of sensor devices, sensing mechanisms, operation, novel materials for sensing, sensor systems, methodologies, modeling and advanced computing, measurement and control systems, data processing, networking, and data communication used in air quality monitoring and control applications. As the collection is under the specialty section Sensor Devices, submitted papers should highlight the significance, advantages, limitations, impact, potentialities, and future perspectives of sensor devices in the field of air quality monitoring from proof-of-concept studies to real-world applications and introduction to the market.
Keywords: Gas Sensors, Particle Sensors, Chemical, Physical, Biological, Radiation Detection, Sensor Systems, Sensing Mechanisms, Novel Materials for Sensing, Measurement, Data-Driven Modeling, Air Quality Monitoring, Indoor and Outdoor Applications
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.