Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam
Abstract Air pollution is a serious concern in urban areas, especially cities such as Ho Chi Minh City (HCMC). Because the air quality directly affects people’s health, air quality monitoring is urgently needed. In this study, the models of Weather Research and Forecasting (WRF), Sparse Matrix Opera...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2020-04-01
|
| Series: | Aerosol and Air Quality Research |
| Subjects: | |
| Online Access: | https://doi.org/10.4209/aaqr.2019.10.0490 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1825197489617108992 |
|---|---|
| author | Nguyen Ky Phung Nguyen Quang Long Nguyen Van Tin Dang Thi Thanh Le |
| author_facet | Nguyen Ky Phung Nguyen Quang Long Nguyen Van Tin Dang Thi Thanh Le |
| author_sort | Nguyen Ky Phung |
| collection | DOAJ |
| description | Abstract Air pollution is a serious concern in urban areas, especially cities such as Ho Chi Minh City (HCMC). Because the air quality directly affects people’s health, air quality monitoring is urgently needed. In this study, the models of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emission (SMOKE), and Community Multiscale Air Quality (CMAQ) were integrated to develop an air quality forecasting system. Drawing input data from transportation and industrial emission inventories, the forecasting system was calibrated and configured using local parameters to deliver hourly forecasts for HCMC. To increase the accuracy of WRF and the meteorological forecasting, the global DEM and land use data were replaced by Lidar data, and land use data were also retrieved from MODIS. Output from the MOZART model served as the boundary conditions for CMAQ, and AOD values reported by the MODIS Aerosol Product were assimilated to enhance the accuracy of the results. A low-cost PM2.5 sensor connected to a LinkIt ONE, a development board for Internet of things (IoT) devices, was employed for calibration and verification. The strong correlation (R2 = 0.8) between the measured and predicted concentrations indicates that the estimates delivered by the proposed forecasting system are consistent with the values obtained via monitoring. |
| format | Article |
| id | doaj-art-2a2252c6f0304127be3dc2c0069c170b |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2020-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-2a2252c6f0304127be3dc2c0069c170b2025-02-09T12:19:02ZengSpringerAerosol and Air Quality Research1680-85842071-14092020-04-012061454146810.4209/aaqr.2019.10.0490Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, VietnamNguyen Ky Phung0Nguyen Quang Long1Nguyen Van Tin2Dang Thi Thanh Le3Institute for Computational Science and TechnologyHo Chi Minh City University of Science, VietNam National UniverstySub-Isntitute of Hydrometeorology and Climate ChangeHo Chi Minh City University of Science, VietNam National UniverstyAbstract Air pollution is a serious concern in urban areas, especially cities such as Ho Chi Minh City (HCMC). Because the air quality directly affects people’s health, air quality monitoring is urgently needed. In this study, the models of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emission (SMOKE), and Community Multiscale Air Quality (CMAQ) were integrated to develop an air quality forecasting system. Drawing input data from transportation and industrial emission inventories, the forecasting system was calibrated and configured using local parameters to deliver hourly forecasts for HCMC. To increase the accuracy of WRF and the meteorological forecasting, the global DEM and land use data were replaced by Lidar data, and land use data were also retrieved from MODIS. Output from the MOZART model served as the boundary conditions for CMAQ, and AOD values reported by the MODIS Aerosol Product were assimilated to enhance the accuracy of the results. A low-cost PM2.5 sensor connected to a LinkIt ONE, a development board for Internet of things (IoT) devices, was employed for calibration and verification. The strong correlation (R2 = 0.8) between the measured and predicted concentrations indicates that the estimates delivered by the proposed forecasting system are consistent with the values obtained via monitoring.https://doi.org/10.4209/aaqr.2019.10.0490WRFCMAQLow-cost sensorsIoTPM2.5 |
| spellingShingle | Nguyen Ky Phung Nguyen Quang Long Nguyen Van Tin Dang Thi Thanh Le Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam Aerosol and Air Quality Research WRF CMAQ Low-cost sensors IoT PM2.5 |
| title | Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam |
| title_full | Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam |
| title_fullStr | Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam |
| title_full_unstemmed | Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam |
| title_short | Development of a PM2.5 Forecasting System Integrating Low-cost Sensors for Ho Chi Minh City, Vietnam |
| title_sort | development of a pm2 5 forecasting system integrating low cost sensors for ho chi minh city vietnam |
| topic | WRF CMAQ Low-cost sensors IoT PM2.5 |
| url | https://doi.org/10.4209/aaqr.2019.10.0490 |
| work_keys_str_mv | AT nguyenkyphung developmentofapm25forecastingsystemintegratinglowcostsensorsforhochiminhcityvietnam AT nguyenquanglong developmentofapm25forecastingsystemintegratinglowcostsensorsforhochiminhcityvietnam AT nguyenvantin developmentofapm25forecastingsystemintegratinglowcostsensorsforhochiminhcityvietnam AT dangthithanhle developmentofapm25forecastingsystemintegratinglowcostsensorsforhochiminhcityvietnam |