VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions
Abstract Volatile organic compound (VOC) related air pollution cause public concern and pose adverse effects on human health in the communities in most developed and developing countries. Our recent studies have applied a quadrotor drone (Mavic Pro, DJI) equipped with a micro needle trap sampler (NT...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2023-09-01
|
| Series: | Aerosol and Air Quality Research |
| Subjects: | |
| Online Access: | https://doi.org/10.4209/aaqr.230169 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823862798772338688 |
|---|---|
| author | Wen-Hsi Cheng Ching-Ho Lin Chung-Shin Yuan |
| author_facet | Wen-Hsi Cheng Ching-Ho Lin Chung-Shin Yuan |
| author_sort | Wen-Hsi Cheng |
| collection | DOAJ |
| description | Abstract Volatile organic compound (VOC) related air pollution cause public concern and pose adverse effects on human health in the communities in most developed and developing countries. Our recent studies have applied a quadrotor drone (Mavic Pro, DJI) equipped with a micro needle trap sampler (NTS), and it could fast arrive at the polluted locations for immediately sampling and further tracking the suspended VOC sources. Notably, a remote-controlled telescoping sampling device was also equipped on the drone in order to extend the NTS outside the disturbed downward wind zone, which was resulted from the rotating propellers. Two plants which manufacture petrochemical products at an industrial complex in Kaohsiung City, southern Taiwan, were applied as the targets for VOCs sampling and further qualitative and quantitative analysis in the laboratory. Aromatic hydrocarbons, including toluene of 433 ppb, ethylbenzene and xylenes of 100–200 ppb and phenol of 111 ppb were identified. Additionally, an air mass backward trajectory model, FYTRAJ, was used to track the paths of VOC emitted from the potential sources and transported in the ambient air. According to the analyzed constituents of VOCs and the raw material data of the suspected plant, which was combined with the backward trajectory tracking simulation of VOC plumes, the NTS carried by a drone has been proven as a cost-effective air pollution monitoring apparatus for locating the VOC emission sources. |
| format | Article |
| id | doaj-art-35ebecf2ff2c4e12ba4ce1bec42502ee |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-35ebecf2ff2c4e12ba4ce1bec42502ee2025-02-09T12:22:57ZengSpringerAerosol and Air Quality Research1680-85842071-14092023-09-01231011210.4209/aaqr.230169VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial EmissionsWen-Hsi Cheng0Ching-Ho Lin1Chung-Shin Yuan2Department of Occupational Safety and Hygiene, Fooyin UniversityDepartment of Environmental Engineering and Science, Fooyin UniversityInstitute of Environmental Engineering, National Sun Yat-sen UniversityAbstract Volatile organic compound (VOC) related air pollution cause public concern and pose adverse effects on human health in the communities in most developed and developing countries. Our recent studies have applied a quadrotor drone (Mavic Pro, DJI) equipped with a micro needle trap sampler (NTS), and it could fast arrive at the polluted locations for immediately sampling and further tracking the suspended VOC sources. Notably, a remote-controlled telescoping sampling device was also equipped on the drone in order to extend the NTS outside the disturbed downward wind zone, which was resulted from the rotating propellers. Two plants which manufacture petrochemical products at an industrial complex in Kaohsiung City, southern Taiwan, were applied as the targets for VOCs sampling and further qualitative and quantitative analysis in the laboratory. Aromatic hydrocarbons, including toluene of 433 ppb, ethylbenzene and xylenes of 100–200 ppb and phenol of 111 ppb were identified. Additionally, an air mass backward trajectory model, FYTRAJ, was used to track the paths of VOC emitted from the potential sources and transported in the ambient air. According to the analyzed constituents of VOCs and the raw material data of the suspected plant, which was combined with the backward trajectory tracking simulation of VOC plumes, the NTS carried by a drone has been proven as a cost-effective air pollution monitoring apparatus for locating the VOC emission sources.https://doi.org/10.4209/aaqr.230169DroneMicro samplerBackward trajectory simulationVolatile organic compoundsSource tracking |
| spellingShingle | Wen-Hsi Cheng Ching-Ho Lin Chung-Shin Yuan VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions Aerosol and Air Quality Research Drone Micro sampler Backward trajectory simulation Volatile organic compounds Source tracking |
| title | VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions |
| title_full | VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions |
| title_fullStr | VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions |
| title_full_unstemmed | VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions |
| title_short | VOC Sampler on a Drone Assisting in Tracing the Potential Sources by a Dispersion Model — Case Study of Industrial Emissions |
| title_sort | voc sampler on a drone assisting in tracing the potential sources by a dispersion model case study of industrial emissions |
| topic | Drone Micro sampler Backward trajectory simulation Volatile organic compounds Source tracking |
| url | https://doi.org/10.4209/aaqr.230169 |
| work_keys_str_mv | AT wenhsicheng vocsampleronadroneassistingintracingthepotentialsourcesbyadispersionmodelcasestudyofindustrialemissions AT chingholin vocsampleronadroneassistingintracingthepotentialsourcesbyadispersionmodelcasestudyofindustrialemissions AT chungshinyuan vocsampleronadroneassistingintracingthepotentialsourcesbyadispersionmodelcasestudyofindustrialemissions |