AERQ—A Web-Based Decision Support Tool for Air Quality Assessment
Technological advancements in low-cost devices, the Internet of Things (IoT), numerical models, big data infrastructures, and high-performance computing are revolutionizing urban management, particularly air quality governance. This study examines the application of smart technologies to address urb...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/4/2045 |
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| author | Pierluigi Cau Davide Muroni Guido Satta Carlo Milesi Carlino Casari |
| author_facet | Pierluigi Cau Davide Muroni Guido Satta Carlo Milesi Carlino Casari |
| author_sort | Pierluigi Cau |
| collection | DOAJ |
| description | Technological advancements in low-cost devices, the Internet of Things (IoT), numerical models, big data infrastructures, and high-performance computing are revolutionizing urban management, particularly air quality governance. This study examines the application of smart technologies to address urban air quality challenges using integrated sensor networks and predictive models. The decision support system (DSS), AERQ, incorporates the AERMOD modeling tool, achieving a 10 m spatial and 1 h temporal resolution for air quality predictions. It processes hourly climate and traffic data via a high-performance computing (HPC) platform, significantly enhancing prediction accuracy and decision-making efficiency. AERMOD has been calibrated and validated for NO<sub>2</sub>, showing a good performance against observations. Tested in Cagliari, Sardinia, Italy, AERQ demonstrated a 99% reduction in computation time compared to modern desktop systems, delivering detailed 5-year scenarios in under 15 h. AERQ equips stakeholders with air quality indices, scenario analyses, and mitigation strategies, combining advanced visualization tools with actionable insights. By enabling data-driven decisions, the system empowers policymakers, urban planners, and citizens to improve air quality and public health. This study underscores the transformative potential of integrating advanced technologies into urban management, providing a scalable model for efficient, informed, and responsive air quality governance. |
| format | Article |
| id | doaj-art-5a36699d826c44ad81e66e7d18928515 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-5a36699d826c44ad81e66e7d189285152025-08-20T02:44:52ZengMDPI AGApplied Sciences2076-34172025-02-01154204510.3390/app15042045AERQ—A Web-Based Decision Support Tool for Air Quality AssessmentPierluigi Cau0Davide Muroni1Guido Satta2Carlo Milesi3Carlino Casari4CRS4—Center for Advanced Studies, Research and Development in Sardinia, 09050 Pula, ItalyCRS4—Center for Advanced Studies, Research and Development in Sardinia, 09050 Pula, ItalyCRS4—Center for Advanced Studies, Research and Development in Sardinia, 09050 Pula, ItalyCRS4—Center for Advanced Studies, Research and Development in Sardinia, 09050 Pula, ItalyCRS4—Center for Advanced Studies, Research and Development in Sardinia, 09050 Pula, ItalyTechnological advancements in low-cost devices, the Internet of Things (IoT), numerical models, big data infrastructures, and high-performance computing are revolutionizing urban management, particularly air quality governance. This study examines the application of smart technologies to address urban air quality challenges using integrated sensor networks and predictive models. The decision support system (DSS), AERQ, incorporates the AERMOD modeling tool, achieving a 10 m spatial and 1 h temporal resolution for air quality predictions. It processes hourly climate and traffic data via a high-performance computing (HPC) platform, significantly enhancing prediction accuracy and decision-making efficiency. AERMOD has been calibrated and validated for NO<sub>2</sub>, showing a good performance against observations. Tested in Cagliari, Sardinia, Italy, AERQ demonstrated a 99% reduction in computation time compared to modern desktop systems, delivering detailed 5-year scenarios in under 15 h. AERQ equips stakeholders with air quality indices, scenario analyses, and mitigation strategies, combining advanced visualization tools with actionable insights. By enabling data-driven decisions, the system empowers policymakers, urban planners, and citizens to improve air quality and public health. This study underscores the transformative potential of integrating advanced technologies into urban management, providing a scalable model for efficient, informed, and responsive air quality governance.https://www.mdpi.com/2076-3417/15/4/2045air qualitynitrogen oxidesatmospheric pollutionair quality modelAERMODGIS |
| spellingShingle | Pierluigi Cau Davide Muroni Guido Satta Carlo Milesi Carlino Casari AERQ—A Web-Based Decision Support Tool for Air Quality Assessment Applied Sciences air quality nitrogen oxides atmospheric pollution air quality model AERMOD GIS |
| title | AERQ—A Web-Based Decision Support Tool for Air Quality Assessment |
| title_full | AERQ—A Web-Based Decision Support Tool for Air Quality Assessment |
| title_fullStr | AERQ—A Web-Based Decision Support Tool for Air Quality Assessment |
| title_full_unstemmed | AERQ—A Web-Based Decision Support Tool for Air Quality Assessment |
| title_short | AERQ—A Web-Based Decision Support Tool for Air Quality Assessment |
| title_sort | aerq a web based decision support tool for air quality assessment |
| topic | air quality nitrogen oxides atmospheric pollution air quality model AERMOD GIS |
| url | https://www.mdpi.com/2076-3417/15/4/2045 |
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