Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions
<p>The primary source of measurement error from widely used particulate matter (PM) PurpleAir sensors is ambient relative humidity (RH). Recently, the US EPA developed a national correction model for <span class="inline-formula">PM<sub>2.5</sub></span> concen...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2024-11-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/17/6735/2024/amt-17-6735-2024.pdf |
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| author | M. E. Mathieu-Campbell C. Guo A. P. Grieshop J. Richmond-Bryant J. Richmond-Bryant |
| author_facet | M. E. Mathieu-Campbell C. Guo A. P. Grieshop J. Richmond-Bryant J. Richmond-Bryant |
| author_sort | M. E. Mathieu-Campbell |
| collection | DOAJ |
| description | <p>The primary source of measurement error from widely used particulate matter (PM) PurpleAir sensors is ambient relative humidity (RH). Recently, the US EPA developed a national correction model for <span class="inline-formula">PM<sub>2.5</sub></span> concentrations measured by PurpleAir sensors (Barkjohn model). However, their study included few sites in the southeastern US, the most humid region of the country. To provide high-quality spatial and temporal data and inform community exposure risks in this area, our study developed and evaluated PurpleAir correction models for use in the warm–humid climate zones of the US. We used hourly PurpleAir data and hourly reference-grade <span class="inline-formula">PM<sub>2.5</sub></span> data from the EPA Air Quality System database from January 2021 to August 2023. Compared with the Barkjohn model, we found improved performance metrics, with error metrics decreasing by 16 %–23 % when applying a multilinear regression model with RH and temperature as predictive variables. We also tested a novel semi-supervised clustering method and found that a nonlinear effect between <span class="inline-formula">PM<sub>2.5</sub></span> and RH emerges around RH of 50 %, with slightly greater accuracy. Therefore, our results suggested that a clustering approach might be more accurate in high humidity conditions to capture the nonlinearity associated with PM particle hygroscopic growth.</p> |
| format | Article |
| id | doaj-art-c8b8d51a526845cfac06a00227df7245 |
| institution | Kabale University |
| issn | 1867-1381 1867-8548 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj-art-c8b8d51a526845cfac06a00227df72452024-11-26T10:18:23ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482024-11-01176735674910.5194/amt-17-6735-2024Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditionsM. E. Mathieu-Campbell0C. Guo1A. P. Grieshop2J. Richmond-Bryant3J. Richmond-Bryant4Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USADepartment of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USADepartment of Civil, Construction and Environmental Engineering, North Carolina State University, Raleigh, NC 27695, USACenter for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USADepartment of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA<p>The primary source of measurement error from widely used particulate matter (PM) PurpleAir sensors is ambient relative humidity (RH). Recently, the US EPA developed a national correction model for <span class="inline-formula">PM<sub>2.5</sub></span> concentrations measured by PurpleAir sensors (Barkjohn model). However, their study included few sites in the southeastern US, the most humid region of the country. To provide high-quality spatial and temporal data and inform community exposure risks in this area, our study developed and evaluated PurpleAir correction models for use in the warm–humid climate zones of the US. We used hourly PurpleAir data and hourly reference-grade <span class="inline-formula">PM<sub>2.5</sub></span> data from the EPA Air Quality System database from January 2021 to August 2023. Compared with the Barkjohn model, we found improved performance metrics, with error metrics decreasing by 16 %–23 % when applying a multilinear regression model with RH and temperature as predictive variables. We also tested a novel semi-supervised clustering method and found that a nonlinear effect between <span class="inline-formula">PM<sub>2.5</sub></span> and RH emerges around RH of 50 %, with slightly greater accuracy. Therefore, our results suggested that a clustering approach might be more accurate in high humidity conditions to capture the nonlinearity associated with PM particle hygroscopic growth.</p>https://amt.copernicus.org/articles/17/6735/2024/amt-17-6735-2024.pdf |
| spellingShingle | M. E. Mathieu-Campbell C. Guo A. P. Grieshop J. Richmond-Bryant J. Richmond-Bryant Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions Atmospheric Measurement Techniques |
| title | Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions |
| title_full | Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions |
| title_fullStr | Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions |
| title_full_unstemmed | Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions |
| title_short | Calibration of PurpleAir low-cost particulate matter sensors: model development for air quality under high relative humidity conditions |
| title_sort | calibration of purpleair low cost particulate matter sensors model development for air quality under high relative humidity conditions |
| url | https://amt.copernicus.org/articles/17/6735/2024/amt-17-6735-2024.pdf |
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