Development of Low-Cost Air Quality Stations for Next Generation Monitoring Networks: Calibration and Validation of PM2.5 and PM10 Sensors

被引:72
|
作者
Cavaliere, Alice [1 ]
Carotenuto, Federico [2 ]
Di Gennaro, Filippo [2 ]
Gioli, Beniamino [2 ]
Gualtieri, Giovanni [2 ]
Martelli, Francesca [2 ]
Matese, Alessandro [2 ]
Toscano, Piero [2 ]
Vagnoli, Carolina [2 ]
Zaldei, Alessandro [2 ]
机构
[1] Univ Firenze, Dept Informat Engn DINFO, Via Santa Marta 3, I-50139 Florence, Italy
[2] CNR, Inst Biometeorol CNR IBIMET, Via Caproni 8, I-50145 Florence, Italy
关键词
air quality monitoring; low-cost sensors; next generation networks; laboratory calibration; field validation; PM2.5; PM10; ELECTROCHEMICAL SENSORS; FIELD CALIBRATION; AVAILABLE SENSORS; ROBUST REGRESSION; POLLUTION; CLUSTER; PART;
D O I
10.3390/s18092843
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A low-cost air quality station has been developed for real-time monitoring of main atmospheric pollutants. Sensors for CO, CO2, NO2, O-3, VOC, PM2.5 and PM10 were integrated on an Arduino Shield compatible board. As concerns PM2.5 and PM10 sensors, the station underwent a laboratory calibration and later a field validation. Laboratory calibration has been carried out at the headquarters of CNR-IBIMET in Florence (Italy) against a TSI DustTrak reference instrument. A MATLAB procedure, implementing advanced mathematical techniques to detect possible complex non-linear relationships between sensor signals and reference data, has been developed and implemented to accomplish the laboratory calibration. Field validation has been performed across a full "heating season" (1 November 2016 to 15 April 2017) by co-locating the station at a road site in Florence where an official fixed air quality station was in operation. Both calibration and validation processes returned fine scores, in most cases better than those achieved for similar systems in the literature. During field validation, in particular, for PM2.5 and PM10 mean biases of 0.036 and 0.598 mu g/m(3), RMSE of 4.056 and 6.084 mu g/m(3), and R-2 of 0.909 and 0.957 were achieved, respectively. Robustness of the developed station, seamless deployed through a five and a half month outdoor campaign without registering sensor failures or drifts, is a further key point.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Spatial calibration and PM2.5 mapping of low-cost air quality sensors
    Chu, Hone-Jay
    Ali, Muhammad Zeeshan
    He, Yu-Chen
    [J]. SCIENTIFIC REPORTS, 2020, 10 (01)
  • [2] Spatial calibration and PM2.5 mapping of low-cost air quality sensors
    Hone-Jay Chu
    Muhammad Zeeshan Ali
    Yu-Chen He
    [J]. Scientific Reports, 10
  • [3] Long-term evaluation and calibration of three types of low-cost PM2.5 sensors at different air quality monitoring stations
    Hong, Gung-Hwa
    Le, Thi-Cuc
    Tu, Jing-Wei
    Wang, Chieh
    Chang, Shuenn-Chin
    Yu, Jhih-Yuan
    Lin, Guan-Yu
    Aggarwal, Shankar G.
    Tsai, Chuen-Jinn
    [J]. JOURNAL OF AEROSOL SCIENCE, 2021, 157
  • [4] Traceable PM2.5 and PM10 Calibration of Low-Cost Sensors with Ambient-like Aerosols Generated in the Laboratory
    Horender, Stefan
    Tancev, Georgi
    Auderset, Kevin
    Vasilatou, Konstantina
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (19):
  • [5] Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy)
    Gualtieri, Giovanni
    Brilli, Lorenzo
    Carotenuto, Federico
    Cavaliere, Alice
    Giordano, Tommaso
    Putzolu, Simone
    Vagnoli, Carolina
    Zaldei, Alessandro
    Gioli, Beniamino
    [J]. SENSORS, 2024, 24 (12)
  • [6] Performance of low-cost indoor air quality monitors for PM2.5 and PM10 from residential sources
    Wang, Zhiqiang
    Delp, William W.
    Singer, Brett C.
    [J]. BUILDING AND ENVIRONMENT, 2020, 171
  • [7] A big data analysis of PM2.5 and PM10 from low cost air quality sensors near traffic areas
    Chen, Shida
    Cui, Kangping
    Yu, Tai-Yi
    Chao, How-Ran
    Hsu, Yi-Chyun
    Lu, I-Cheng
    Arcega, Rachelle D.
    Tsai, Ming-Hsien
    Lin, Sheng-Lun
    Chao, Wan-Chun
    Chen, Chunneng
    Yu, Kwong-Leung J.
    [J]. Aerosol and Air Quality Research, 2019, 19 (08): : 1721 - 1733
  • [8] A Big Data Analysis of PM2.5 and PM10 from Low Cost Air Quality Sensors near Traffic Areas
    Chen, Shida
    Cui, Kangping
    Yu, Tai-Yi
    Chao, How-Ran
    Hsu, Yi-Chyun
    Lu, I-Cheng
    Arcega, Rachelle D.
    Tsai, Ming-Hsien
    Lin, Sheng-Lun
    Chao, Wan-Chun
    Chen, Chunneng
    Yu, Kwong-Leung J.
    [J]. AEROSOL AND AIR QUALITY RESEARCH, 2019, 19 (08) : 1721 - 1733
  • [9] Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring
    Badura, Marek
    Batog, Piotr
    Drzeniecka-Osiadacz, Anetta
    Modzel, Piotr
    [J]. JOURNAL OF SENSORS, 2018, 2018
  • [10] Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors
    Cavaliere, Alice
    Brilli, Lorenzo
    Andreini, Bianca Patrizia
    Carotenuto, Federico
    Gioli, Beniamino
    Giordano, Tommaso
    Stefanelli, Marco
    Vagnoli, Carolina
    Zaldei, Alessandro
    Gualtieri, Giovanni
    [J]. ATMOSPHERIC MEASUREMENT TECHNIQUES, 2023, 16 (20) : 4723 - 4740