A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States
Considerable financial resources are allocated for measuring ambient air pollution in the United States, yet the locations for these monitoring sites may not be optimized to capture the full extent of current pollution variability. Prior research on best sensor placement for monitoring fine particul...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2022-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ac548f |
| _version_ | 1797747093333344256 |
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| author | Makoto M Kelp Samuel Lin J Nathan Kutz Loretta J Mickley |
| author_facet | Makoto M Kelp Samuel Lin J Nathan Kutz Loretta J Mickley |
| author_sort | Makoto M Kelp |
| collection | DOAJ |
| description | Considerable financial resources are allocated for measuring ambient air pollution in the United States, yet the locations for these monitoring sites may not be optimized to capture the full extent of current pollution variability. Prior research on best sensor placement for monitoring fine particulate matter (PM _2.5 ) pollution is scarce: most studies do not span areas larger than a medium-sized city or examine timescales longer than 1 week. Here we present a pilot study using multiresolution dynamic mode decomposition (mrDMD) to identify the optimal placement of PM _2.5 sensors from 2000 to 2016 over the contiguous United States. This novel approach incorporates the variation of PM _2.5 on timescales ranging from 1 d to over a decade to capture air pollution variability. We find that the mrDMD algorithm identifies more high-priority sensor locations in the western United States than those expected along the eastern coast, where a large number of Environmental Protection Agency (EPA) PM _2.5 monitors currently reside. Specifically, 53% of mrDMD optimized sensor locations are west of the 100th meridian, compared to only 32% in the current EPA network. The mrDMD sensor locations can capture PM _2.5 from wildfires and high pollution events, with particularly high skill in the west. These results suggest significant gaps in the current EPA monitoring network in the San Joaquin Valley in California, northern California, and in the Pacific Northwest (Idaho, and Eastern Washington and Oregon). Our framework diagnoses where to place air quality sensors so that they can best monitor smoke from wildfires. Our framework may also be applied to urban areas for equitable placement of PM _2.5 monitors. |
| first_indexed | 2024-03-12T15:47:14Z |
| format | Article |
| id | doaj.art-aafd132a2f0f4432ab7d2cfcaffc7d96 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:47:14Z |
| publishDate | 2022-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-aafd132a2f0f4432ab7d2cfcaffc7d962023-08-09T15:24:41ZengIOP PublishingEnvironmental Research Letters1748-93262022-01-0117303403410.1088/1748-9326/ac548fA new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United StatesMakoto M Kelp0https://orcid.org/0000-0003-0451-3439Samuel Lin1J Nathan Kutz2https://orcid.org/0000-0002-6004-2275Loretta J Mickley3https://orcid.org/0000-0002-7859-3470Department of Earth and Planetary Sciences, Harvard University , Cambridge, MA 02138, United States of AmericaDepartment of Computer Science, Harvard University , Cambridge, MA 02138, United States of AmericaDepartment of Applied Mathematics, University of Washington , Seattle, WA 98195, United States of AmericaJohn A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, MA 01238, United States of AmericaConsiderable financial resources are allocated for measuring ambient air pollution in the United States, yet the locations for these monitoring sites may not be optimized to capture the full extent of current pollution variability. Prior research on best sensor placement for monitoring fine particulate matter (PM _2.5 ) pollution is scarce: most studies do not span areas larger than a medium-sized city or examine timescales longer than 1 week. Here we present a pilot study using multiresolution dynamic mode decomposition (mrDMD) to identify the optimal placement of PM _2.5 sensors from 2000 to 2016 over the contiguous United States. This novel approach incorporates the variation of PM _2.5 on timescales ranging from 1 d to over a decade to capture air pollution variability. We find that the mrDMD algorithm identifies more high-priority sensor locations in the western United States than those expected along the eastern coast, where a large number of Environmental Protection Agency (EPA) PM _2.5 monitors currently reside. Specifically, 53% of mrDMD optimized sensor locations are west of the 100th meridian, compared to only 32% in the current EPA network. The mrDMD sensor locations can capture PM _2.5 from wildfires and high pollution events, with particularly high skill in the west. These results suggest significant gaps in the current EPA monitoring network in the San Joaquin Valley in California, northern California, and in the Pacific Northwest (Idaho, and Eastern Washington and Oregon). Our framework diagnoses where to place air quality sensors so that they can best monitor smoke from wildfires. Our framework may also be applied to urban areas for equitable placement of PM _2.5 monitors.https://doi.org/10.1088/1748-9326/ac548ffine particulate matter (PM2.5)sensor placementmultiscale dynamics |
| spellingShingle | Makoto M Kelp Samuel Lin J Nathan Kutz Loretta J Mickley A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States Environmental Research Letters fine particulate matter (PM2.5) sensor placement multiscale dynamics |
| title | A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States |
| title_full | A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States |
| title_fullStr | A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States |
| title_full_unstemmed | A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States |
| title_short | A new approach for determining optimal placement of PM2.5 air quality sensors: case study for the contiguous United States |
| title_sort | new approach for determining optimal placement of pm2 5 air quality sensors case study for the contiguous united states |
| topic | fine particulate matter (PM2.5) sensor placement multiscale dynamics |
| url | https://doi.org/10.1088/1748-9326/ac548f |
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