Air Quality Networks: Data Analysis, Calibration and Data Fusion

In: Environmental Informatics and Modeling Series

Abstract

Intro -- Preface -- Contents -- New Challenges in Air Quality Measurements -- 1 Introduction -- 2 Current Standard and Equivalence Measuring Methods -- 2.1 Problems Related to Current Air Quality Monitoring -- 3 Role of Low-Cost Sensors (LCS) in the Future Air Quality Networks -- 3.1 Low-Cost Sensor Technology -- 4 Data Elaboration of Low-Cost Sensors -- 4.1 Advantages of LCSs -- 4.2 Caveats of LCSs -- 5 Satellite Remote Sensors -- 5.1 Data Treatment -- 5.2 Advantages of Satellite Data -- 5.3 Caveats -- 5.4 Temporal and Spatial Resolution -- 5.5 Conclusion About Satellite Data -- 6 New Networks for Air Quality Monitoring -- 7 Conclusions -- References -- A Data Processing Architecture for Intelligent Hierarchical Air Quality Monitoring Networks in Urban Innovation and Citizen Science Applications -- 1 Introduction -- 2 General Architecture -- 2.1 AirHeritage IoT Inception and Storage Architecture -- 3 Data Processing Pipeline -- 3.1 Sensor Data Capture Stage: The MONICA Device -- 3.2 Calibration Stage -- 3.3 Sensor Fusion Stage -- 3.4 Personalized Feedback Stage -- 4 Conclusions -- References -- Using Continuous Integration Processes to Build Environments for Processing Air Quality Data from IoT Devices -- 1 Introduction -- 2 Software Engineering Processes in the Development of Complex Systems -- 3 Building an Environment for the Development of IoT Systems Using Good Software Engineering Practices -- 4 Verification of the IoT System Manufacturing Environment for the Construction of a Hybrid Information System on Air Quality for Gdańsk -- 5 Summary -- References -- AQ Mapping Through Low-Cost Sensor Networks -- 1 Introduction -- 2 Pollution Variables and Low-Cost Sensors -- 2.1 Common Pollutants in Urban Areas -- 2.2 Sensors -- 2.3 Low-Cost Commercial Sensors and Stations -- 3 AQ Data Collection Initiatives -- 3.1 Governmental and Private Efforts.