Urban Air Quality Monitoring with Networked Low-Cost Sensor-Systems †
<p>Map of: (<b>a</b>) air quality monitoring stations (10 units) managed by ARPA-Puglia, environmental protection local authority, in the Bari city; (<b>b</b>) wireless sensors network based on 10 low-cost stationary nodes deployed for urban air quality monitoring and operated by ENEA.</p> "> Figure 2
<p>(<b>a</b>) Virtual Private Network (VPN) by ENEA (Brindisi Research Center) to manage the deployed air quality sensor network; (<b>b</b>) Selected locations in Bari (Italy) of the installed stationary nodes AIRBOX for urban air quality monitoring operated by ENEA.</p> "> Figure 3
<p>(<b>a</b>) Trend of the PM<sub>10</sub> monthly mean (January–December 2016) measured in the Node 1 (ENEL), Node 2 (ENEA) and Node 6 (Airport) by AIRBOX sensors deployed at Bari (Italy) for air quality monitoring; (<b>b</b>) Trend of the PM<sub>10</sub> monthly mean (January–December 2016) measured in the Node 2 (ENEA) by AIRBOX sensor (PPD20V, Shinyei) compared to the official reference data of the air quality monitoring station (Via Caldarola) in Bari (Italy) managed by ARPA-Puglia.</p> "> Figure 4
<p>(<b>a</b>) PM<sub>10</sub> AQI measured by AIRBOX sensor (PPD20V, Shinyei) in the Node 6 (Airport) versus analyzer (ARPA-Puglia—EN2 Modugno) in Bari on May 2017; (<b>b</b>) Classification US EPA for AQI standard to assign risk categories to human health due to personal exposure to air pollution.</p> "> Figure 5
<p>Typical CO, NO<sub>2</sub>, PM<sub>10</sub> and CO<sub>2</sub> air quality index (AQI) trend (1 min average on 9 November 2015) of the mobile sensor-node installed on the roof of a public bus (AMTAB) circulating in Bari (Italy).</p> ">
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Stationary Wireless Sensors Network: PM10
3.2. PM10 Air Quality Index (AQI): Sensor versus Analyzer
3.3. Air Quality Mobile Sensing
4. Summary and Conclusions
Acknowledgments
Conflicts of Interest
References
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Node 1 | Node 2 | Node 6 | ||||
---|---|---|---|---|---|---|
MAE 1 (µg/m3) | Accuracy 2 (%) | MAE (µg/m3) | Accuracy (%) | MAE (µg/m3) | Accuracy (%) | |
PM10—2016 | 5.6 | 24.8 | 5.6 | 21.6 | 5.6 | 20.5 |
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Penza, M.; Suriano, D.; Pfister, V.; Prato, M.; Cassano, G. Urban Air Quality Monitoring with Networked Low-Cost Sensor-Systems. Proceedings 2017, 1, 573. https://doi.org/10.3390/proceedings1040573
Penza M, Suriano D, Pfister V, Prato M, Cassano G. Urban Air Quality Monitoring with Networked Low-Cost Sensor-Systems. Proceedings. 2017; 1(4):573. https://doi.org/10.3390/proceedings1040573
Chicago/Turabian StylePenza, Michele, Domenico Suriano, Valerio Pfister, Mario Prato, and Gennaro Cassano. 2017. "Urban Air Quality Monitoring with Networked Low-Cost Sensor-Systems" Proceedings 1, no. 4: 573. https://doi.org/10.3390/proceedings1040573