Using the Google Earth Engine to estimate a 10 m resolution monthly inventory of soil fugitive dust emissions in Beijing, China.
Emission inventory
GEE
Particulate matter
Soil fugitive dust
Wind erosion
Journal
The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500
Informations de publication
Date de publication:
15 Sep 2020
15 Sep 2020
Historique:
received:
13
03
2020
revised:
30
04
2020
accepted:
30
04
2020
pubmed:
31
5
2020
medline:
31
5
2020
entrez:
31
5
2020
Statut:
ppublish
Résumé
Soil fugitive dust (SFD) is an important contributor to ambient particulate matter (PM), but most current SFD emission inventories are updated slowly or have low resolution. In areas where vegetation coverage and climatic conditions undergo significant seasonal changes, the classic wind erosion equation (WEQ) tends to underestimate SFD emissions, increasing the need for higher spatiotemporal data resolution. Continuous acquisition of precise bare soil maps is the key barrier to compiling monthly high-resolution SFD emission inventories. In this study, we proposed taking advantage of the massive Landsat and Sentinel-2 imagery data sets stored in the Google Earth Engine (GEE) cloud platform to enable the rapid production of bare soil maps with spatial resolutions of up to 10 m. The resulting improved spatiotemporal resolution of wind erosion parameters allowed us to estimate SFD emissions in Beijing as being ~5-7 times the level calculated by the WEQ. Spring and winter accounted for >85% of SFD emissions, while April was the dustiest month with SFD emissions of PM
Identifiants
pubmed: 32473441
pii: S0048-9697(20)32691-7
doi: 10.1016/j.scitotenv.2020.139174
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
139174Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.