Unmanned aerial systems for modelling air pollution removal by urban greenery
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F22%3A00564478" target="_blank" >RIV/86652079:_____/22:00564478 - isvavai.cz</a>
Alternative codes found
RIV/62156489:43410/22:43922144 RIV/60460709:41330/22:91590 RIV/47813059:19630/22:A0000221 RIV/61989100:27710/22:10251660
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1618866722003004?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1618866722003004?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ufug.2022.127757" target="_blank" >10.1016/j.ufug.2022.127757</a>
Alternative languages
Result language
angličtina
Original language name
Unmanned aerial systems for modelling air pollution removal by urban greenery
Original language description
Urban greenery plays an important role in reducing air pollution, being one of the often-used, nature-based measures in sustainable and climate-resilient urban development. However, when modelling its effect on air pollution removal by dry deposition, coarse and time-limited data on vegetation properties are often included, disregarding the high spatial and temporal heterogeneity in urban forest canopies. Here, we present a detailed, physics-based approach for modelling particulate matter (PM10) and tropospheric ozone (O-3) removal by urban greenery on a small scale that eliminates these constraints. Our procedure combines a dense network of low-cost optical and electrochemical air pollution sensors, and a remote sensing method for greenery structure monitoring derived from Unmanned aerial systems (UAS) imagery processed by the Structure from Motion (SfM) algorithm. This approach enabled the quantification of species- and individual-specific air pollution removal rates by woody plants throughout the growing season, exploring the high spatial and temporal variability of modelled removal rates within an urban forest. The total PM10 and O-3 removal rates ranged from 7.6 g m(-2) (PM10) and 12.6 g m(-2) (O-3) for mature trees of Acer pseudoplatanus to 0.1 g m(-2) and 0.1 g m(-2) for newly planted tree saplings of Salix daphnoides. The present study demonstrates that UAS-SfM can detect differences in structures among and within canopies and by involving these characteristics, they can shift the modelling of air pollution removal towards a level of individual woody plants and beyond, enabling more realistic and accurate quantification of air pollution removal. Moreover, this approach can be similarly applied when modelling other ecosystem services provided by urban greenery.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10511 - Environmental sciences (social aspects to be 5.7)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Urban Forestry & Urban Greening
ISSN
1618-8667
e-ISSN
1610-8167
Volume of the periodical
78
Issue of the periodical within the volume
DEC
Country of publishing house
DE - GERMANY
Number of pages
12
Pages from-to
127757
UT code for WoS article
000880161100006
EID of the result in the Scopus database
2-s2.0-85140805916